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					 MINISTRY OF AGRICULTURE AND COOPERATIVES


            DEPARTMENT OF AGRICULTURE

               TECHNICAL SERVICES BRANCH



                   COPPERBELT PROVINCE

CENTRE FOR DEVELOPMENT OF ADVANCED APPLIED COMPUTING
                            (CDAC), INDIA
       B-30, Institutional Area, Sector-62, Noida- 201307 (U.P.)


 TRAINING REPORT SUBMITED BY CHARLES BWALYA CHISANGA


 Specialized Programme on Application Development using GIS & Remote
                               Sensing




                 Date 17th January to 11th March 2011
Table of Contents

Introduction..................................................................................................................................... 1
   Education at CDAC, NOIDA ..................................................................................................... 1

Training Methodology .................................................................................................................... 1
  Training Programme Objectives: ................................................................................................ 1

Software used during the training programme................................................................................ 1
    Lectures................................................................................................................................... 2

Books and literature used for the training programme ................................................................... 2

Week 1: 17th -21st January 2011 .................................................................................................... 3
 Lecture: Nimesh Dagur............................................................................................................... 3
    AutoCAD Map........................................................................................................................ 3
    Exercise/Practical.................................................................................................................... 3
 Lecture: Dr. Shalini Singh........................................................................................................... 5
    Introduction to GIS ................................................................................................................. 5
 Lecture: Dr. Shalini Singh........................................................................................................... 6
    Geographic Information System (GIS)................................................................................... 6

Week 2: 24th – 28th January 2011 .................................................................................................11
 Lecture: Dr. Shalini Singh..........................................................................................................11
    ArcGIS ...................................................................................................................................11
    Exercise/Practical...................................................................................................................11
 Lecture: Dr Shalini Singh ......................................................................................................... 21
    Exploring GIS concepts ........................................................................................................ 21
    Exercise/Practical.................................................................................................................. 21
 Lecture: Vinay Shankar Prasad Sinha....................................................................................... 27
    Application of GIS in Watershed Analysis using ArcMap, ArcCatalog, ArcToolbar ........... 27
    Geo-statistical Analysis, Conceptual model, and Practical Exercise .................................... 28
    Exercise/Practical.................................................................................................................. 29
    GIS DATA MODELS............................................................................................................ 32

Week 3: 31st January – 4th February 2011 ................................................................................... 34
 Lecturer: Nimesh Dugar ........................................................................................................... 35
    MapInfo................................................................................................................................. 35
    Exercise/Practical.................................................................................................................. 35
 Lecturer: Dr. Shalini Singh ....................................................................................................... 36
    Remote Sensing and Data Collection ................................................................................... 36
    Digital image Processing ...................................................................................................... 36
    Digital Numbers.................................................................................................................... 36
    Exercise/Practical.................................................................................................................. 36
 Lecture: Shailendra Suman ....................................................................................................... 36
    Software Project Management.............................................................................................. 36

                                                                        ii
     Software Development Life Cycle (SDLC) - SDLC Model................................................. 36
   Lecture: Shailendra Suman ....................................................................................................... 38
     Global Positioning System (GPS)......................................................................................... 38
     Exercise/Practical.................................................................................................................. 38
   Lecture: Shailendra Suman ....................................................................................................... 41
     Principles of Remote Sensing (RS)....................................................................................... 41
   Lecture: Dr. Shalini Singh......................................................................................................... 47
     ERDAS IMAGINE ............................................................................................................... 47
     Exercise/Practical.................................................................................................................. 47

Week 4: 7th – 11th February 2011 ................................................................................................ 47
 Lecture: Shailendra Suman ....................................................................................................... 47
    Space Segment Consideration (continued from week 3)...................................................... 47
    Thermal Infrared Remote Sensing (continued from week 3) ............................................... 47
    Active microwave (RADAR) ............................................................................................... 47
 Lecture: Dr. Shalini Singh......................................................................................................... 49
    ArcGIS .................................................................................................................................. 49
    Introduction to Image Interpretation..................................................................................... 49
    Digital Image Processing ...................................................................................................... 49
    Digital Image Enhancement.................................................................................................. 49
    Digital Image Classification ................................................................................................. 49
    ERDAS Imagine ................................................................................................................... 49
    Practicals on Image to image registration, Re-sampling nearest neighbor, striping and
   banding, Atmospheric correction, Classification, Image manipulation, Spectral
    Enhancement, Radiometric Correction, Modeler using ERDAS.......................................... 49
    Remote Sensing and Data Collection ................................................................................... 50
 Lecture: Dr. Shalini Singh......................................................................................................... 50
    Digital image Processing and Classification......................................................................... 50
    Linear Stretching................................................................................................................... 50
    Change Detection.................................................................................................................. 50
    Exercise/Practical.................................................................................................................. 50
    Principal Component Analysis (PCA) .................................................................................. 50
    Exercise/Practical.................................................................................................................. 50

Week 5: 14th – 19th February 2011 .............................................................................................. 50
 Lecture: Dr. Shalini Singh......................................................................................................... 50
    Digital Image classification .................................................................................................. 50
    Exercise/Practical.................................................................................................................. 50
    GIS Modeling, ArcGIS3.3 and ArcGIS, Arctoolbox and ArcCatalog .................................. 53
    Exercise/Practical.................................................................................................................. 53
 Lecture: Nimesh Dagur............................................................................................................. 55
    MapInfo................................................................................................................................. 55
    Exercise and practical ........................................................................................................... 55
Week 6: 21st – 25th February 2011 .............................................................................................. 58
 Lecture: Nimesh Dagur............................................................................................................. 58
    Application GIS - RDBMS (SQL) – Oracle 9i..................................................................... 58

                                                                      iii
       Introduction to Programming using Visual Studio 2005 ...................................................... 59
       Exercise/Practical.................................................................................................................. 59

Week 7: 28th February – 5th March 2011 .................................................................................... 60
 Lecture: Nimesh Dagur............................................................................................................. 60
    Loop, Object Oriented Concepts........................................................................................... 60
    Exercise/Practical.................................................................................................................. 60
    Accessing Databases............................................................................................................. 60

Week 8: 7th – 11th March 2011 .................................................................................................... 61
 Lecturer: Amjad Khan............................................................................................................... 61
    Developing Application for Web Based GIS (continuation from week 7) ........................... 61
    MapGuide and WebGIS ........................................................................................................ 61
    Exercise/Practical.................................................................................................................. 61
 Lecture: Amjad Khan ................................................................................................................ 61
    MapGuide and WebGIS ........................................................................................................ 61
    Exercise/Practical.................................................................................................................. 61
    Use of MapObjects and Microsoft Visual Studio .NET to build a simple mapping
    application using the Visual Basic (VB) language................................................................ 62
    Exercise/Practical.................................................................................................................. 62

Industrial visit ............................................................................................................................... 63
    RAMTech Cooperation ......................................................................................................... 63
    MapMyIndia ......................................................................................................................... 63

Conclusion .................................................................................................................................... 64

APPENDICES ................................................................................................................................. i

Appendix 1: Course layout .............................................................................................................. i
Appendix 2: list of Participants...................................................................................................... iii




                                                                        iv
   Introduction

Education at CDAC, NOIDA
Centre for Development of Advanced Computing (C-DAC) is a national initiative of the
Government. of India, Ministry of Communication and IT to mobilize human and technical
resources in order to attain technological advancement in the ever-evolving arena of Information
Technology for the benefit of masses. C-DAC is a scientific society and one of the premier
research institute of DIT, MCIT and has successfully integrated its computer education and
training activities in Hi-tech areas with Research & Development in the area of Information
Technology like Embedded Systems, Broadband, Multilingual technologies, GIS based
Solutions, Digital library, Health care, eGovernance etc. CDAC has also established
collaboration alliance with global technology leaders like Microsoft, IBM, Compaq and Oracle.
It professes the policy of establishing the balance between research and teaching for higher
education

The training programmes conducted for international participants at C-DAC Noida are sponsored
by the Govt. of India under the ITEC and SCAAP programmes. The allowance admissible to the
participants includes the cost of air passage, free tuition, living allowance and lodging as per
availability of accommodation.


   Training Methodology

C-DAC adopts professional approach in imparting training to the participants wherein tentatively
50% time is devoted to lectures and same amount of time is devoted to labs to help participants
to have a better understanding of concepts learnt in theory sessions. State-of-the-art
infrastructure, well equipped library, experienced and qualified faculties are few of the things
that make learning at CDAC a memorable experience. Besides classroom training, programmes
such as expert sessions, visit to industries, cultural visits to historical monuments are conducted
as a part of the training. The Historical sites of interest visited included Tajma hall (Agra), Red
Fort, Baha’i Faith Temple, Botanical Garden.


Training Programme Objectives:
   • To understand the GIS & Remote Sensing concepts;
   • To understand information relating to integration of GIS, Remote Sensing and
       Application software development; and
   • To understand about Development of GIS Applications using Client/Server Architecture.



   Software used during the training programme

   •   AutCAD Map
   •   MapInfo 9.1

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   •   ArcView3.3
   •   ArcGIS9.1
   •   ERDAS9.1
   •   ORACLE 9i
   •   Visual Basic 2008
   •   Map Objects
   •   MapWindowGIS
   •   MapGuide Studio
   •   MapGuide Maestro 2.1.4 & MapGuideOpenSource-2.1.0.4283-Final

Lectures              Course Name
Amjad Khan            Application Development for Web Based GIS (MapWindowGIS),
                      MapGuide and WebGIS, MapGuide Studio
Dr. Shalini Singh     Remote Sensing, DIP using ERDAS
Nimesh Dagur          AutoCAD Map, MapInfo, Visual Basic dot Net, MapObjects, SQL,
                      Introduction to Programming
Nishant Sinha         Remote Sensing (Principal Component Analysis)
R. Kumar              Remote Sensing: Active microwave (RADAR)
Shailendera Suman     Remote Sensing, System Development Life Cycle (SDLC)
Vinay Prasad Sinha    GIS Modeling


   Books and literature used for the training programme


1. Bayross Ivan (2009), SQL, Pl/SQL The programming language of Oracle, 4th Revised
   Edition, BPB Publishing, New Delhi
2. Concepts on Geographic Information System
3. ERDAS Image Reference Manual
4. Heywood I, Cornelius S. and Carver S. (2009), An Introduction to Geographical Information
   Systems 3rd Edition, Published by Dorling Kindersley, India Pvt Ltd
5. Lillesand T. M., Kiefer R. W., and Chipman J. W. (2004), Remote Sensing and image
   Interpretation, Fifth Edition, Wiley Student Edition, John Wiley & Sons
6. Newsome B. and Willis T. (2008), Beginning Microsoft Visual Basic 2008, Wiley India Pvt
   Ltd
7. Wilpen L. Gorr and Kristen S. Kurland, 2004, Learning and using Geographical Information
   Systems; Cengage learning India Private Ltd, New Delhi
8. CD from CDAC

List of participants (see Appendix 2)




                                             2
   Week 1: 17th -21st January 2011

Lecture: Nimesh Dagur
AutoCAD Map
Exercise/Practical

AutoCAD Map
Key terms
   • Map: a flat representation of a globe
   • Cartography - the art and science of mapmaking
   • Projection: The system used to transfer locations from Earth’s surface to a flat map.
   • Scale: The relationship between the size of an object on a map and the actual size of the
       same feature on Earth’s surface.
   • Map scale determines the size and shape of features

Map Scale
  • Map scale is an important but often misunderstood concept in cartography. To represent a
      portion of the earth’s surface on a map, the area must be reduced. The extent of this
      reduction is expressed as a ratio called map scale. Map scale is the ratio of map distance
      to ground distance.
  • For example, if you draw a 4.8-km road as a 20-cm line on your map, the following
      statements would describe the map scale:
  • 20 cm : 4.8 km, 20 cm : 480,000 cm, 1 cm : 24,000 cm, 1 : 24,000
  • The latter is known as a representative fraction (RF) because the values on either side of
      the colon represent the proportion between distance on the map and distance on the
      ground; that is, “1:24,000” means “1 map inch represents 24,000 ground inches”, “1 map
      meter represents 24,000 ground meters”, or “1 map centimeter represents 24,000 ground
      centimeters”, and so on.
  • Map scale can be expressed in several different manners: as a fraction (1:24,000), as a
      verbal statement (one centimeter equals one kilometer), or as a bar.
  • Map scale indicates how much a given distance was reduced to be represented on a map.
      For maps with the same paper size, features on a small-scale map (1:1,000,000) look
      smaller than those of a large-scale map (1:1,200). In other words, a dime-sized lake on a
      large scale map (l: 1,200) would be less than the size of the period at the end of this
      sentence on a small-scale map (1:1,000,000).
  • In general, small-scale maps depict large ground areas, but they have low spatial
      resolution, showing little detail. On the other hand, large-scale maps depict small ground
      areas but have high spatial resolution, showing many details. The features on large-scale
      maps more closely represent real-world features because the extent of reduction is lower
      than that of a small-scale map. As map scale decreases, features must be smoothed and
      simplified or not shown at all. For example, at a scale of 1:63,360 (in which 1 inch = 1
      mile), it is difficult to represent area features smaller than 1/8th of a mile long or wide
      because they will be 1/8th of an inch long or wide on a map.




                                               3
AutCAD Map
   • AutoCAD Map is the leading engineering solution for creating and managing spatial
     data.
   • AutoCAD Map bridges the gap between Computer Aided Design
   • (CAD) and Geographic Information Systems (GIS).
   • AutoCAD Map provides direct access to the leading data formats used in design and GIS.
   • Use AutoCAD tools to maintain a broad variety of geospatial information.

Purpose of a map
A map is a representation of the features that occur on the Earth. Maps allow us to accomplish a
number of things, such as:
   • Visualize Information
   • Obtain the spatial orientation and relationships of our data
   • Present results of analysis

AutoCAD uses file extension *.dwg, *.dgn and *.dxf. It can also display shapefiles. Vector based
shapefiles are comprised of a combination of four layer types: point, line, polygon and
annotation. A shapefile is a digital vector storage format for storing geometric location and
associated attribute information. This format lacks the capacity to store topological information.
Shapefiles are simple because they store primitive geometrical data types of points, lines, and
polygons. These primitives are of limited use without any attributes to specify what they
represent. Therefore, a table of records will store properties/attributes for each primitive shape in
the shapefile. Shapes (points/lines/polygons) together with data attributes can create infinitely
many representations about geographical data. Representation provides the ability for powerful
and accurate computations.

While the term "shapefile" is quite common, a "shapefile" is actually a set of several files. Three
individual files are mandatory to store the core data that comprises a shapefile: ".shp", ".shx",
".dbf", and other extensions on a common prefix name (e.g., "lakes.*"). The actual shapefile
relates specifically to files with the ".shp" extension, but alone is incomplete for distribution, as
the other supporting files are required.

There are a further eight optional files which store primarily index data to improve performance.
Each individual file should conform to the MS DOS 8.3 filename convention (8 character
filename prefix, period, 3 character filename suffix such as shapefil.shp) in order to be
compatible with past applications that handle shapefiles, though many recent software
applications accept files with longer names. For this same reason, all files should be located in
the same folder.

Mandatory files:
• .shp — shape format; the feature geometry itself
• .shx — shape index format; a positional index of the feature geometry to allow seeking
  forwards and backwards quickly
• .dbf — attribute format; columnar attributes for each shape, in dBase IV format



                                                 4
Optional files:
• .prj — projection format; the coordinate system and projection information, a plain text file
   describing the projection using well-known text format
• .sbn and .sbx — a spatial index of the features
• .fbn and .fbx — a spatial index of the features for shapefiles that are read-only
• .ain and .aih — an attribute index of the active fields in a table or a theme's attribute table
• .ixs — a geocoding index for read-write shapefiles
• .mxs — a geocoding index for read-write shapefiles (ODB format)
• .atx — an attribute index for the .dbf file in the form of shapefile.columnname.atx
• .shp.xml — metadata in XML format
• .cpg — used to specify the code page (only for.dbf) for identifying the character encoding to
   be used

In each of the .shp, .shx, and .dbf files, the shapes in each file correspond to each other in
sequence. That is, the first record in the .shp file corresponds to the first record in the .shx and
.dbf files, and so on. The .shp and .shx files have various fields with different endianness, so as
an implementor of the file formats you must be very careful to respect the endianness of each
field and treat it properly.

Shapefiles deal with coordinates in terms of X and Y, although they are often storing longitude
and latitude, respectively. While working with the X and Y terms, be sure to respect the order of
the terms (longitude is stored in X, latitude in Y).

Shapefile shape format (.shp)
The main file (.shp) contains the primary geographic reference data in the shapefile. The file
consists of a single fixed length header followed by one or more variable length records. Each of
the variable length records includes a record header component and a record contents
component. A detailed description of the file format is given in the Esri Shapefile Technical
Description. This format should not be confused with the AutoCAD shape font source format,
which shares the .shp extension.


Lecture: Dr. Shalini Singh
Introduction to GIS
Geography and Technology

   •   Geography affects us in many ways:
          – Our natural environment
          – Our human environment

   •   Geography has become a high tech discipline
          – Earth Observation
          – Global Positioning Systems (GPS)
          – Geographic Information Systems (GIS)
Earth Observation
   • SPOT

                                                 5
   •   Landsat TM
   •   RadarSAT
   •   NOAA
   •   ERS

Global Positioning Systems
   • GPS is a revolutionary navigation system
          – 24 satellites orbiting the earth
          – Provide location within metres or less anywhere on the globe.
          – Now available in many cars as an option

Geographic Information System (GIS)

   •   A Method of Organizing Data
          – Geographic Data (Maps)
          – Descriptive Data (Databases)
          – Images
   •   A Method of Distributing Data
   •   A Method of Analyzing Data
   •   A Method of Visualizing Data

GIS – Describing Our World
We can describe any element of our world in two ways:
Location Information: Where is it? (51°N, 112°W)
Attribute Information:What is it? (Species: Oak; Height: 15m; Age: 75 Yrs; Condition: Good)

GIS - Links Datasets
GIS software links the location data and the attribute data

GIS - Analysis
GIS software can answer questions about our world:
Spatial Questions: What provinces border Saskatchewan?
Attribute Questions: What provinces have more than 1.5 million people?

How GIS works
  • In a GIS, different types of information are represented as separate map layers
  • Each layer is linked to descriptive information
  • Layers are combined to make a map


Lecture: Dr. Shalini Singh
Geographic Information System (GIS)
Definitions
• A system for capturing, storing, checking, manipulating, analyzing and displaying data which
are spatially referenced to the Earth.
• Any manual or computer based set of procedures used to store and manipulate geographically

                                                 6
referenced data (Runoff, 1989)
• A database system in which most of the data are spatially indexed, and upon which a set of
procedures operated in order to answer queries about spatial entities in the database. (Smith,
1987)

A geographic information system (GIS) is a collection of hardware, software, geographic data,
and personnel designed to create, store, edit, manipulate, analyze and display geographically
referenced information.

How does a GIS work?
• GIS stores information as a collection of thematic layers
• Thematic layers are linked together by geography

•   Explicit geographic reference (latitude and longitude) Implicit reference (address, postal
    code, FIPS code, census tract, road name)
•   GIS can create explicit geographic features (e.g., customer) from implicit references like
    customer address
•   Geographic features (points, lines, polygons) used for visualization and analysis
•   GIS is a computerized decision support system that integrates geographic data, attribute data
    and other spatially referenced data. GIS is used to capture, store, retrieve, analyze, and
    display spatial data

GIS is an integration of five basic components




Data for GIS
   • Base Maps
        Political boundaries, postal areas
Municipal boundaries
Highways, streets, rivers

                                                7
Lakes, parks, landmarks
   • Business Maps and Data
           – Business/Customer locations
           – Census/Demography
           – Consumer products, financial services
           – Health care, real estate
   • Environmental Maps and Data
           – Environmental risk
           – Satellite imagery, weather
           – Topography, natural resource
           – General Reference Maps
           – World boundaries
           – Country boundaries
           – City locations, time zones

GIS function is to capture, store, query, output, display and out put.

Application of GIS
• Land use Information
• Urban & Township Planning
• Site Location for Facility
• Field of Hydrology
• Geological & Geographic Maps
• Atlas Maps
• Plot Maps
• Network Path Analysis
• Field of Transportation
• Tourist Information
• Environmental Analysis
• Health Management
• Market Analysis

APPLICATION OF GIS IN LAND INFORMATION SYSTEMS (LIS)
Land information is essential – to making sound land use planning decisions and protecting
provincial and local interests

PRESENTATION OVERVIEW
• Introduction
• Data Sources
• Managing Data
• Using Data

Land information is significant to the success of the Planning System
Introduction: what are the key messages that we need to keep in mind about land information?
Data Sources: where does data come from?
Managing: where do we store data and how do we process it?

                                                  8
Why LIS
As community grows land usage and the ownership changes continuously over the period of
time. Planning based on these information's is a continuous process and sometimes seem to be
critical. Taking decisions online effectively can be easier and faster using the technology of GIS,
where the decision-maker can visualize the database before the decision pictorially too.

The elementary part of a country as an “Object” is the village. The information generated from
the village should flow faster to administration for proper management. The citizens should also
get the information about their property with zero error. This is possible using a proper tool with
GIS interface. GIS technology is a concept that makes things easier to take a decision and get
information through visualization.

Before taking a decision the management / administrator requires the authenticated and accurate
data and a proper computer aided tool, which will incorporate & analyze data with auxiliary
information and spatial information faster for the decision making. The data has to be generated
and compatible application software has to be developed keeping in view suitability of the user.

Objectives
The main objective of any Land information system is to retrieve information's (like: - plot no.,
plot area, owner name, location) etc. about a plot mentioned in a Town, cities or village. The
automation of land record can give higher accuracy in day-to-day work.
The integration between land record’s data and associated map data is achieved through the GIS
(Geographic information systems) technology with higher accuracy and speed i.e. if a Plot is
identified in a village map, the computer can give the data relating to that Plot by accessing the
database instantaneously. Similarly aggregation of land records data and associated map data,
will be able to produce higher-level integrated geo-dataset
To browse the information irrespective of any desired location by using the Web based Internet
Technology.

Use of land records System
• Locating Plot(s) belonging to person(s)
• Plot Records maintenance
• Faster Updating & Presentation of Data
• Planning of revenue generation
• Tax Collection
• Planning of irrigation pattern
• Land acquisition / Disbursement
• Finding land use like residential, commercial etc.
• Generating a report with adequate maps
• Generating a component for MIS
• Accessing the attributes at the fingertips

MIS ACTIVITIES MAY INCLUDE LAND RECORD AUTOMATION
• Locating plot(s) belonging to person(s).
• Faster update and presentation of data (Spatial & Non-spatial)

                                                9
•   Planning of revenue generation.
•   Planning of irrigation pattern.
•   Land acquisition.
•   Development of existing and planning of new structures.
•   Finding of land use like residential, commercial, industrial, water bodies etc.
•   Generating of reports for higher officials / management with adequate maps.
•   Generating a component for MIS at State/National level.
•   Accessing the data at the fingertips.

STAGES OF APPLICATION TOOL DEVELOPMENT
The data utilized here could be divided into two groups i.e. Non-Spatial auxiliary data and
Spatial map data. The non-spatial data should be in the form of external database, which
facilitate the user to use the same database for other application like MIS. The database could be
in Access, ORACLE. The database is stored in different tables using the concepts of RDBMS for
faster and easier accessing of the data with proper multi threaded security. Hence it can be
divided into MIS & GIS Activities:
• MIS Activities (Activities related with Non-Spatial Data Capturing)
• GIS Activities (Activities related with Spatial Data Capturing)

GIS Activities (Activities related with Spatial Data Capturing)
The data stored in GIS/or geo database consists of two sets of information;

GEOMETRIC LOCATION of geographic features (that is location of point, line, or polygon)
ATTRIBUTE DATA (a characteristic of a geographic feature described by nos., or characters
stored in a tabular format and linked to the geographic features)

The spatial data conversion process normally begins with the identification of the data source for
the land base. These sources of information may range from extremely accurate surveyed maps
containing no ground control references. Before starting the creation of database the source data
has to be updated and verified so as to generate the accurate existing data. Sometimes the data is
not clear enough to distinguish the features, which create problems for the operator and
inaccurate data may get generated. As the decisions of a planner are based on the data, the
inaccuracy in the base data may create problems to the planner too. So the map has to be made
distinguishable before considering it as source data.

STAGES OF SPATIAL DATA CAPTURING
Scanning Of Source Maps - (It is a process of converting paper/cloth map on to the digital
media.)
Map Preparation (The scanned Maps will be scaled on the basis of the dimensions given by the
clients through rubber sheet process after which on screen digitization will be done to convert
raster drawings (maps) to vector format through CAD systems (Auto Cad Map) .
Digitization/vectorisation is the process of converting graphical information into a digital format.
These vectorised village maps are made error free with GIS tools and are geo referenced in
respect of the Survey of India Maps. An integrated single map is being generated from several
cloth maps. This makes the user to access all the village maps at the same time.



                                                10
The Map is digitized into different layers, or themes. There is one layer for each set of
geographic features or phenomena for which attribute information’s if available will be recorded.
For example, outer boundary, road, plots, etc. and each will be stored as a separate spatial data
sources, rather than trying to store them all together in one. The features of the map drawings
(roads, plots, boundaries etc.) are spread across many sheets; hence one complete village may
have 6-7 sheets. As logical connectivity of features of the map is very important, all the
maps/sheets needs to be edge matched from all the sides with the adjacent sheets/maps. After
edge matching other processes like cleaning, topology building is done along with attribute data
insertion which is done in textual format. Finally a master map containing the entire village or
tehsil is generated.

Data Linkage (The next important activity after spatial and attribute data capturing is the
process of linking the two data sets. So far these databases are in different environments and
need to be integrated for mapping related queries. For integration of data there should be a
unique field in both spatial as well as attributes data sets. After inserting the unique field link is
made between both the databases, which provides relevant information for each geometric
features. This is done through ESRI platform (Arc view software).

Map Integration (The Application for integration purpose can be developed in Map Object
Software through visual basic where both maps, its attribute data and external data can be
visualized at a time and all the GIS related mapping
Operations i.e. query analysis; thematic mapping, zooming, panning, addition and deletion of
layer etc will be possible through this application.


   Week 2: 24th – 28th January 2011

Lecture: Dr. Shalini Singh
ArcGIS
Exercise/Practical

ArcView Applications
• ArcMap
• ArcCatalog
• ArcToolbox
• Getting Help

ArcMap
   • Primary display application
   • Perform map-based tasks
         – Displaying
         – Editing
         – Querying
         – Analyzing
         – Charting
         – Reporting

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ArcCatalog
   • A window into your database
   • Explore your data
   • Manage your data
   • Create and view data
   • Write or view documentation (metadata)

ArcToolbox
   • Available in ArcCatalog and ArcMap
   • Geographic processing functions
         – Analysis and conversion
         – Tools vary between ArcGIS products (ArcView and extensions)

Accessing the applications
   • ArcView 9 shares common applications
   • ArcMap, ArcCatalog
          – ArcToolbox and Command Line windows

Getting Help
   • Tabs
          – Contents
          – Index
          – Search
          – Favorites
   • Other help
          – Tool tips
          – Online Support

ArcMap
ArcMap provides tools for creating visual displays of the data, querying, and creating
presentation-quality maps. ArcMap makes it easy to lay out your maps for printing, embedding
in other documents, or electronic publishing. It also includes analysis, charting, reporting
functions, and a comprehensive suite of editing tools for creating and editing geographic data.
When you save a map, all of your layout work, symbols, text, and graphics are automatically
preserved. ArcMap is the primary ArcGIS application for displaying, querying, editing, creating,
and analyzing data.

ArcCatalog
The ArcCatalog application helps you organize and manage all your GIS data. It includes tools
for browsing and finding geographic information, recording and viewing metadata, quickly
viewing any dataset, and defining the schema structure for your geographic data layers.

ArcToolbox
The ArcToolbox window provides you with tools for data conversion, managing coordinate
systems, changing map projections, and more. ArcToolbox supports easy-to-use drag-and-drop

                                              12
operations from ArcCatalog; with ArcMap, you need to browse to or type in the variables. For
ArcInfo users, ArcToolbox provides additional and more sophisticated data conversion and
spatial analysis tools.

All ArcGIS products (ArcView, ArcEditor, and ArcInfo) are comprised of the ArcMap and
ArcCatalog applications, both of which contain the Toolbox and Geoprocessing windows.
ArcMap is the application for performing analysis and making maps. ArcCatalog is a tool for
accessing and managing your data. ArcToolbox contains tools for data conversion and
management. The Geoprocessing window allows you to write, import and run scripts, and access
individual commands.

The ArcGIS Desktop applications are standard Windows applications. This means that they store
application data in the registry. For example, when you start ArcMap, move it to a certain
location on the screen and resize it; the next time you start ArcMap it will come up at the same
location and in the same size you selected. ArcGIS applications support other functions that users
of Windows software often use. For example, you can use Object Linking and Embedding (OLE)
to insert a Microsoft Excel spreadsheet of well sampling attributes into ArcMap, while you view
the well sample locations on a map. When you need to view the spreadsheet, simply double-click
the spreadsheet to start Microsoft Excel. You also have the option of hyperlinking (analogous to
hotlinking in ArcView GIS 3.x) to the Excel spreadsheet if you choose to do so.

Layers can be dragged from ArcCatalog and dropped into ArcMap to display the layer. You can
turn on/off each toolbar and dock it anywhere you like within the application. Through a simple
and intuitive customization, you can move a buttons or a tool from one toolbar to another and
access their properties.

The ArcGIS Desktop Help provides several methods for finding the help you need to use the
software most productively. The Contents tab lets you search for information by topic. The Index
tab lets you search for topics containing words from the Help index, such as Layer or Table. The
Search tab lets you search the Help document for a word you specify. The Favorites tab lets you
store your favorite help topics so you can easily access them when needed. Your word does not
have to be in the index in order to search the document for it, but the search will take longer if it
is not in the index.

In ArcCatalog, ArcMap, and ArcToolbox, button and tool names are displayed when you move
the mouse over them (these are called ToolTips). You can also click the What’s This? tool in
ArcMap or ArcCatalog and then click on a button or tool to access additional help about it (this is
called context-sensitive help). For applications like ArcMap that have graphical user interfaces,
context-sensitive help is useful for finding out what all the various buttons and tools do.

Features of the ArcMap interface
• The Title bar displays the map name.
• The toolbars are dockable.
• The Table of Contents lists the Data Views and layer legends. The Table of Contents is
   dockable and can be resized by horizontally dragging the vertical divider between the Table
   of Contents and the display area.

                                                 13
•   The display area is where the map features draw.
•   The Status bar, besides reporting the coordinates, displays a description of the selected
    buttons and menu items.

Data View
You will work in Data View if you want to display, query, edit, explore, and analyze data.

Layout View
When you choose to create a hard copy map, you need to move to the Layout View. This view is
where you add all the other map elements, such as the north arrow, legend, scale, title, and other
textual information (e.g., author, data date, map date, projection type). Once the map is complete,
you can send it to a plotter or printer or export it as a graphic file.

Layers, data frames, and maps
Layers store the path to a data source as well as the display properties of that data source. A data
frame is a container for layers. When you create a new empty map, a default data frame named
Layers is automatically added to the top of the Table of Contents, but you can highlight and
change its name. In the example above, the data frame name was changed to Europe. Like the
layers they contain, data frames also have properties that you can manipulate.

A map is the document that stores the data frames, layers, and any map elements such as
graphics and text. A map may contain several data frames. For example, you might create a map
that contains one data frame with layers that show an entire country and another data frame that
displays layers of a particular region.

Data frames
Data frames let you organize your data into logical groupings, such as themes or geographic
areas. You may want to consider using multiple data frames when you want to compare layers
side by side or create insets and overviews that highlight a particular location.

You can add as many layers as you want to a data frame; however, a data frame containing too
many layers can be more difficult to work with. You may want to consider multiple data frames
organized by theme or geography when you have numerous layers.

When a map has more than one data frame, one of them is the active data frame. The active data
frame is the one you are currently working with in the ArcMap display. For example, when you
add a new layer to a map, it gets added to the active data frame. You can always tell which data
frame is active because its name is shown in bold text in the Table of Contents. Of course, if a
map has only one data frame, it is always the active one.

To make a data frame active, right-click on the data frame and click Activate. The active data
frame appears in bold font in the Table of Contents. A data frame can also be activated in the
Layout View when you use your mouse to select it from the page.

Maps
The ArcMap document helps you visualize geographic information by showing you the location

                                                14
of features, which are symbolized to help you understand what they are and why they are being
shown. A map can include additional information, such as graphics and map elements, that help
explain its context and purpose. When you open a map document, ArcMap checks the links to
the data sources. If it cannot find some data (i.e., if the source data for a layer has been deleted or
renamed or if a network drive is not accessible), it does not display. The layer is still part of the
map, and its name appears in the Table of Contents, but a small red exclamation mark appears
right of the layer symbol. When you work in ArcMap, you are always working within an ArcMap
document. The ArcMap document (MXD) lets you save the display of your data.

ArcView function is Data Manipulation, Data Analysis and Data Presentation

Identify Features tool
This tool allows you to display the attributes for any feature you click on with your pointer.

Navigating the Editor toolbar
In ArcMap, editing operations are controlled through the Editor toolbar. The toolbar contains
several important controls:
• Editor menu: This menu contains the commands for beginning, ending, and saving edit
   sessions. It also provides access to several editing operations, snapping controls, and editing
   options.
• Edit Tool: This tool is used to select features for editing.
• Sketch Tool: This is the primary tool for editing spatial features. It allows you to digitize in
   new features or modify the shape of existing features. The actual operation the tool performs
   is controlled by the Task list.
• Task list: You choose your desired editing operation from this dropdown list.
• Target layer: This control allows you to select the layer you want to edit.
• Split tool: Allows you to divide a select feature into two features.
• Rotate tool: Allows you to interactively rotate selected features using the mouse or an
   angular measurement.
• Attribute dialog: This window allows you to edit the attribute values of selected features.
• Sketch Properties: Allows you to edit the vertices of a sketch.

Select by location (spatial query)
You will often need to find features based on their geographic, or spatial, relationship to other
features. Instead of using the cursor or geometric shapes to select features, you use features from
one layer to select features in another layer. For this reason, Select By Location is called spatial
query.

When selecting features with spatial queries, you use the Select By Location dialog, available
from ArcMap’s Selection menu, to create a statement about what you want to select.
Your selection procedures include:

•   Select features from
•   Add to the currently selected features
•   Remove from the currently selected features
•   Select from the currently selected features

                                                  15
The selected features depend on the mode used. Regardless of the mode you use, you have the
option of narrowing your selection to a specific layer by checking off all the layers that you want
to exclude. You can also select features using a certain buffer distance. The Select by Location
dialog is where you can easily query your data using the topological relationships, which exist
between features and layers.

Layer symbology in ArcMap
Drawing properties can be set within the Symbology tab of the layer’s Layer Properties dialog.
In the Show panel of the Symbology tab, ArcMap has several options for creating both
qualitative and quantitative thematic maps. When you chose a certain method, the properties
options to the right of the Show panel change according to the type of thematic mapping method
used.

Display qualitative values
Often, seeing where something is—and where it is not—can tell you exactly what you need to
know. Mapping the location of features reveals patterns and trends that can help you make better
decisions. The easiest way to see where features are is to draw them using a single symbol. You
can draw any type of data this way. When you create a new layer, ArcMap draws it with a single
symbol by default.

A category describes a set of features with the same attribute value. For example, given parcel
data with an attribute describing land use (e.g., residential, commercial, and public areas), you
can use a different symbol to represent each unique landuse type. Drawing features this way
allows you to see where features are and what category they belong to. This can be useful if you
are targeting a specific type of feature for some action or policy. For instance, a city planner
might use the landuse map to target areas for redevelopment.
In general, look for these kinds of attributes when mapping by category or unique value:
• Attributes describing the name, type, or condition of a feature
• Attributes containing measurements or quantities that are already grouped (e.g., “0–99” or
    “100–199”)
• Attributes that uniquely identify features (e.g., a county name attribute could be used to draw
    each county with a unique color)
You can let ArcMap assign a symbol to each unique value based on a color scheme you choose,
or you can explicitly assign a specific symbol to a specific attribute value.

Display quantitative values
When you want your map to communicate how much of something there is, you need to draw
features using a quantitative measure. This measure might be a count, a ratio (such as a
percentage), or a rank (such as high, medium, or low).

You can represent quantities on a map by varying the color or symbol size you use to draw
features. For example, you might use increasingly darker shades of blue to represent increasingly
higher rainfall amounts or larger circles to represent cities with larger populations. Generally,
you need to classify your data when you display it. You can either manually define classes or
apply one of the standard classification schemes to do so automatically—just specify the number

                                                16
of classes you want to show. Once you have defined the classes, you can add more classes, delete
classes, or redefine class ranges.

Pie charts, bar charts, and stacked bar charts can present large amounts of quantitative data in an
eye-catching fashion. For example, if you are mapping population by county, you can use a pie
chart to show the percentage of the population by ethnic group for each county.
Generally, you will draw a layer with charts when your layer has a number of related numeric
attributes that you want to compare. Use pie charts if you want to show how much of the total
amount each category takes up. Use bar charts to show relative amounts rather than a proportion
of a total.

Calculating summary statistics
After making a spatial or attribute selection, you may want to calculate a simple statistics
summary. This can be done by clicking the Statistics option from the Selection dropdown list.
This operation invokes the Selection Statistics dialog. Here you need to select the layer, as well
as the field in the feature attribute table, that you want the statistics to be calculated for. Once
these are selected, a numeric statistics summary, as well as a frequency distribution chart,
appears in that window.

Graphs
By displaying data values graphically, graphs simplify the often difficult task of interpreting the
large amount of quantitative (numerical) attribute data associated with layers.

You can represent your data and analysis results using many styles of graphs including two-
dimensional and 3D graphs. ArcGIS uses graphics server software that provides a variety of
chart types so you can represent your data in the clearest and most efficient manner.

Values for ArcGIS graphs come directly from feature attribute tables. Some graphs are better
than others at presenting certain kinds of information. Carefully consider the information you
want to present before choosing a graph style.

You can control most visual aspects of the graph in order to create an effective display of your
data. For example, you can add titles, label axes, change the color of graph markers, or change
the color and font of the chart’s text.

Once you have created a graph, you can add it to a map in ArcMap’s Layout View. When placed
on the layout, a graph becomes a graphic element that you can size and position as desired.

Map and design objectives
A map conveys geographic information, highlights important geographic relationships, and
presents analysis results. Because most GIS users have to present their spatial data graphically to
a wide variety of readers, they have also become map designers or cartographers.
Any GIS analysis ends with some results that need to be communicated. You can help fulfill the
purpose of your map by using proper placement of map elements and choosing symbols and
cartographic elements that are tailored for the message you want to communicate. How you
design a map depends on your particular objective (i.e., why you want to create a map in the first

                                                17
place).
One obvious objective for creating a map is to show the results of your analysis. Other map
objectives may be to simply share information, guide people, or highlight relationships.
Your primary objective is usually not to create a beautiful map but to create a product that
communicates effectively, efficiently, and clearly.

What other map elements are missing?
        • Scale text (1:100,000)
        • Other text (author name, disclaimers, projection information, date of data, date of
            map, and so on)
        • Logos
Are all these map elements really necessary?
Some map elements can be ignored if other map elements or features can substitute for it. For
example, a north arrow is redundant if you have neatlines shown with coordinate labels such as
latitude and longitude; a north arrow and a scale bar are both redundant if you are depicting the
population of the United States in a book on United States demographic statistics; a scale bar can
be redundant if neatlines are shown with the proper coordinate system and units.
Avoid placing any information that does not comply with the map’s objectives. These are
considered ‘visual noise’ and distract from effective map communication.

Printing procedure
Follow the steps below to print your map.
• From the File dropdown list, click Print.
• In the Print dialog, point to the available printer and select the Printer Engine by clicking the
    Setup button. The PostScript and Windows Printer Engine drivers are available with your
    Windows operating system. The ArcPress Printer is a separate ESRI extension product
    specifically designed to facilitate high-quality map production. You choose between printer
    drivers in the Page Setup window.
• On the Document Properties dialog of your printer or plotter, select the paper size and
    source, the number of copies, the orientation, and the color appearance. Depending on which
    printer engine was selected, the Document Properties dialog may be different from the
    graphic shown in the slide.

Once you have created a map, you may want to export it from a map document to an image file.
The new image can then be inserted into another document (for example, Microsoft Word or
PowerPoint). Export a map by choosing Export Map from the File menu. You can export maps as
several types of files. Some of these formats are:
• EMF (Enhanced Metafiles) are Windows native vector graphics, raster graphics, or both.
   They are useful for embedding in Windows documents because they can be resized without
   distortion.
• BMP (bitmap) files are simple, native Windows raster images. They do not scale as well as
   EMF files.
• EPS (Encapsulated PostScript) files are primarily used for vector graphics and printing, and
   can be sent directly as a printer file.
• PDF (Portable Document Format) files are designed to be consistently viewable across
   different platforms. They are commonly used for distributing documents on the Web.

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•   JPEG (Joint Photographic Experts Group) files are compressed image files. They are
    commonly used for images on the Web because they are more compact than many other file
    types.

Copy map to clipboard
You may not need to create a new separate file for your map but only need to embed it into
another document. Under the Edit menu, there is the option to temporarily store the map layout
in the clipboard on your computer.

ArcGIS (ArcView) geoprocessing tools allow you to aggregate data based on various tabular
and spatial relationships. It’s easiest to think about them as a mathematical equation. There is an
input or multiple inputs of data, an operation is performed on the input data that alters it in a
certain way, and the data is returned as a new output.

Geoprocessing is based on a framework of data transformation. A typical geoprocessing tool
performs an operation on an ArcGIS dataset (such as a shapefile, feature class, raster, or table)
and produces a new dataset as the result of the tool.

Geocoding is the process of assigning a geographic location to point data based on a description.
The description usually comes in the form of street addresses, postal codes, or cities. The
geocoding service then converts this descriptive information into a point feature on a map with
precise location coordinates. In order to create the point feature, a reference layer such as a street
file with addresses is required.

An Address Locator defines the process for converting these descriptions to points on a map by
setting the parameters of the transformation. It is possible to rerun the geocoding service in order
to match unmatched points interactively and thereby increase the percentage of matched points.
It is important to note that geocoding is not an exact science. Each point that is inputted into the
geocoding service is compared with potential candidates in a Reference Table. The points are
then assigned a score based on their sameness to points in the reference table. Scores that exceed
a user defined percentage are automatically matched. Points that fall below the designated grade
are not matched but can be rematched interactively. Once the points have been geocoded a new
output table containing 4 new auto generated columns will appear in your map view.

Model Builder
A model is a representation of reality. A model represents only those factors that are important to
your work flow and creates a simplified, manageable view of the real world. ModelBuilder is an
interface used to conduct geographic processing or geoprocessing functions in ArcGIS. It is part
of ArcGIS’s core technology. Visually, it looks a lot like a flow chart. The power of
ModelBuilder is that it allows users to automate geoprocessing functions on their data easily
without writing any code. The visual nature of the interface makes it very easy to design and
follow workflows and makes it a great tool for teaching students.

Joins and relates tables
ArcMap provides two methods to associate data stored in tables with geographic features: joins
and relates. When you join two tables, you append the attributes from one onto the other, based

                                                 19
on a field common to both tables. When you relate tables, you define a relationship between the
two tables—also based on a common field—but do not append the attributes of one to the other.
Instead, you can access the related data when necessary.

You join two tables when the data in the tables has a one-to-one or a many-to-one relationship
(e.g., you have a layer showing store locations, and you want to join a table of the latest monthly
sales figures to it).

You relate two tables when the data in the tables has a one-to-many or many-to-many
relationship (e.g., your map displays a parcel database, and you have a table of owners; a parcel
may have more than one owner, and an owner may own more than one parcel).

Joins and relates are reconnected whenever you open the map. This way, if the underlying data in
your tables changes, it is reflected in the join or relate.

A join is used to append the fields of one table to those of another through an attribute or field
common to both tables. Within ArcMap, a table can be joined to a preexisting dataset to provide
a spatial extent. Unlike a join, a relate defines a relationship between two tables. The associated
data isn't appended to the layer's attribute table like it is with a join. Instead, you can access the
related data when you work with the layer's attributes.

Buffering: A buffer is a zone of a specified distance around a certain feature or features. Buffers
tend to be used in instances where one is trying to lessen or absorb an impact. For instance,
environmentalists wanting to lessen the impact of erosion into rivers as a result of logging might
suggest that a 500 metre buffer be placed around the rivers. This would prevent any logging
within 500 metres of the river. In addition, buffers can also be used to assess and closely analyze
impacts,

MapTips and hyperlinks: If you have MapTips set for a layer, when you move the mouse
pointer over a feature in the layer, a rectangular box containing textual information appears.
The MapTip text comes from a field in the attribute table of that layer. You have to set which
field you want attribute values to be reported from when using the MapTips.

You can display Web pages accessed over the Internet and documents (such as a text file or
image) or run a macro (script). You can dynamically create hyperlinks as you browse your map,
or you can store hyperlinks with your data in an attribute field.

When you click on a feature, ArcMap determines which program is needed to display the
hyperlink. If you specify a Web address, ArcMap launches your default Web browser and
displays the page. If you specify a different type of document (e.g., a text document), ArcMap
displays it using its native program (such as Notepad or another text editor). The Hyperlink
Manager allows you to set more than one hyperlink per feature; these are called Dynamic
Hyperlinks.

If you are creating maps that people will access interactively or if you want to explore your data
before you do analysis, MapTips and hyperlinks are useful ways to present more information

                                                 20
about the map’s features.

Layering
One of the main features of a layer is that it can exist outside your map as a file on disk. This
makes it easy for others to access the layers you've built. When you save a layer to disk, you save
everything about the layer, such as the symbolization and labeling. When you add a layer file to
another map, it will draw exactly as it was saved. Others can drop those layers onto their maps
without having to know how to access the database or classify the data; this can be helpful when
sharing data stored in a multiuser geodatabase with nontechnical staff members. You can share
layers over the network as well as e-mail layers, along with the data, to people or enclose the
layer within the data's metadata.

The layer file that is created will reference its data source using the Data Source Options setting
currently specified for the map on the Document Properties dialog box (accessed from the
ArcMap File menu). By default, this setting specifies that data sources will be referenced with
their full path.

GIS Information about spatial features is typically stored in tables using a database management
system. Typically the databases are stored as spreadsheets with each row or record corresponding
to one feature such as a point, line, or polygon. Each column in the table corresponds to a feature
attribute. The table columns are typically called fields or items. Each column in a table typically
has the following characteristics:

•   Item Name. The item name is simply the name of the table column.
•   Item Type. The item types most commonly used are binary integer (B), floating point (F),
    character (C), and date (D). Examples of binary integer items include categorical attributes
    such as soil texture class, vegetation class, or road surface type. Examples of floating point
    items include quantitative values such soil pH, tree diameter, or road length. Examples of
    character items include names such as soil order, plant genus/species, or street name.
•   Item Width. This refers to the number of bytes required to store each item. The most basic
    storage unit for computers is a Bit (or Binary Digit). A bit has two possible states, either a 0
    or 1. Eight bits together make up a Byte.


Lecture: Dr Shalini Singh
Exploring GIS concepts
Exercise/Practical

Database: A database is an integrated set of data on a particular subject.
DBMS: “A database management system is a software application designed to organize the
efficient and effective storage and access of data.”
RDBMS: “A relational DBMS comprises a set of tables, each a 2-D array of records containing
attributes about the objects under study”

Geodatabase and Feature Dataset
A geodatabase is a relational database that stores geographic data. At its most basic level, the

                                                21
geodatabase is a container for storing spatial and attribute data and the relationships that exist
among them. In a geodatabase, which is a vector data format, features and their associated
attributes can be structured to work together as an integrated system using rules, relationships,
and topological associations.

The basic building blocks of a geodatabase are feature (object) classes, feature datasets, and non
spatial tables. Using these, you can build more complex objects in your geodatabase.
Associations among geodatabase components created based on spatial relationships (topology) or
attributes (relationship classes).

    •  A geodatabase is a relational database that stores geographic information.
    •  A feature dataset is a collection of feature classes that share the same spatial reference
       frame.
• Why geodatabases?
To establish and store relationships based on tabular information.
• Why feature datasets?
To establish and store relationships based on geographic information.

•   A feature class is a collection of features that share the same geometry type (point, line, or
    polygon) and spatial reference.
•   A feature dataset is a collection of feature classes. All the feature classes in a feature dataset
    must have the same spatial reference.
•   A non spatial table contains attribute data that can be associated with feature classes.

A feature class is a collection of geographic features with the same geometry type, attributes, and
spatial reference. Feature classes can also store annotation (text or graphics that can be
individually selected, positioned, and modified). Feature classes may exist independently in a
geodatabase as standalone feature classes or they can be grouped into feature datasets.

A feature dataset contains a group of feature classes that share the same spatial reference. That is,
the feature classes must have the same coordinate system and their features must fall within a
common geographic extent.
• Feature datasets are primarily used to store feature classes that have topological relationships,
    such as connectivity, adjacency, or containment. For example, streams in a particular
    watershed are connected to rivers; therefore, streams and rivers are topologically related.
• In order for a geodatabase to maintain topological relationships among feature classes, the
    feature classes must reside in the same feature dataset.

There are only two types of tables that you interact with directly: feature class and non spatial
• Both types are created and managed in Arc Catalog and edited in Arc Map. Both display in
   the traditional row-and-column format. The difference is that feature class tables have one or
   more columns that store feature geometry.
• Non spatial tables contain only attribute data (no feature geometry) and display in Arc
   Catalog with the table icon. They exist in a geodatabase as standalone tables, and they can be
   associated with other tables or feature classes. When a non spatial table is associated with a
   feature class, you can query, select, and symbolize features based on the data stored in the

                                                 22
   non spatial table.

In a geodatabase, relationship classes provide a way to model relationships that exist between
real-world objects such as parcels and buildings or streams and water sample data. For example,
in the real world, buildings are always located on parcels. When the ownership of a parcel
changes, the ownership of the buildings on the parcel usually changes as well. If a building
footprint changes, it can affect the parcel (the value of the parcel improvements may increase or
decrease). By setting up a relationship class between these two feature classes, you can help
make sure that when a feature in one of the feature classes changes, related features in the other
feature class are updated

The GIS Data Model
The purpose of the model is to allows the geographic features in real world locations to be
digitally represented and stored in a database so that they can be abstractly presented in map
(analog) form, and can also be worked with and manipulated to address some problem

Geodatabase model
A geodatabase (short for geographic database) is a physical store of geographic information
(spatial, attribute, metadata, and relationships) inside a relational database management system
(RDBMS).

   •   Stores geographic coordinates as one attribute in a relational database table
   •   Uses MS Access for “Personal Geodatabase” (single user)
   •   Uses Oracle, MySQL, PostgreSQL, Sybase, Ingress or other commercial relational
       databases for “Enterprise Geodatabases” (many simultaneous users)

Relational Database Management System (RDBMS)
• A type of database in which the data can be spread across several tables that are related
   together. Data in related tables are associated by shared attributes. Any data element can be
   found in the database through the name of the table, the attribute (column) name, and the
   attribute values that uniquely identify each row. In contrast to other database structures, an
   RDBMS requires few assumptions about how data is related or how it will be extracted from
   the database. As a result, the data can be arranged in different combinations.
• All data (vector, raster, address, measures, CAD, etc.) is stored together in a commercial off-
   the-shelf RDBMS. This means that organizations can have an integrated data management
   policy covering all data, which can significantly simplify support and maintenance, and
   reduce costs.
• Geodatabases offer many advantages for GIS users. The range of functionality available is
   extensive and includes centralized data storage, support for advanced feature geometry, and
   more accurate data entry and editing through the use of subtypes, attribute domains, and
   validation rules
• Geodatabases can be created and managed easily using the standard tools in ArcCatalog, and
   ArcMap provides simple tools to work with geodatabases. The advanced features described
   above are also available for those users with demanding application requirements




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Geodatabase objects
Basic objects:
   - feature classes,
   - feature datasets,
   - nonspatial tables.
Complex objects building on the basic objects:
   - topology,
   - relationship classes,
   - geometric networks

Feature class
• A feature class is a collection of geographic objects in tabular format that have the same
   behavior and the same attributes.
• A feature class is a geographic feature which includes points, lines, polygons, and annotation
   feature class.
• Feature classes may exist independently in a geodatabase as stand-alone feature classes or
   you can group them into feature datasets

Feature datasets
• A feature dataset is composed of feature classes that have been grouped together so they can
   participate in topological relationships with each other. All the feature classes in a feature
   dataset must share the same spatial reference (or coordinate system)
• Edits you make to one feature class may result in edits being made automatically to some or
   all of the other feature classes in the feature dataset

Tables
• Feature class tables and nonspatial attribute tables.
• Both types of tables are created and managed in ArcCatalog and edited in ArcMap. Both
   display in the traditional row-and-column format. The difference is that feature class tables
   have one or more columns that store feature geometry.
• Nonspatial tables contain only attribute data (no feature geometry) and display in ArcCatalog
   with the table icon. They can exist in a geodatabase as stand-alone tables, or they can be
   related to other tables or feature classes.

Topology
• In a GIS, spatial relationships among feature classes in a feature dataset are defined by
   topology. You can choose whether to create topology for features.
• The primary spatial relationships that you can model using topology are adjacency,
   coincidence, and connectivity
• There are three types of topology available in the geodatabase: geodatabase topology (over
   20 topology rules), map topology, and geometric network topology. Each type of topology is
   created from feature classes that are stored within a feature dataset. A feature class can
   participate in only one topology at a time

Object class
An object class is a collection of objects in tabular format that have the same behavior and the

                                               24
same attributes.

Relationship
   • A relationship is an association or link between two objects in a database.
   • A relationship can exist between spatial objects (features in feature classes), non-spatial
       objects (objects in object classes), or between spatial and non-spatial objects.

Geometric Network
• In the real world, examples of networks abound: streams joining together to form larger
   streams, pipes carrying water to homes and businesses throughout a city, and power lines
   carrying electricity.
• In a geodatabase, you can model each of these real-world networks with a geometric
   network. Starting with simple point and line feature classes, you use ArcCatalog to create a
   geometric network that will enable you to answer questions such as: Which streams will be
   affected by a proposed dam? Which areas will be affected by a water main repair? What is
   the quickest route between two points in the network?
• Feature classes that participate in the network are automatically converted from simple
   feature classes to network feature classes, and one or more attribute fields containing network
   information are added to the feature class table.
• There are more restrictions involved with managing network feature classes than with
   managing simple feature classes. You cannot rename, delete, or copy a network feature class.
   To perform any of these actions, you must convert the network feature class back to a simple
   feature class by deleting the geometric network.
• When you build a geometric network, there are a number of options you can choose from to
   make your network model more realistic. For example, you can:
                   set the direction that resources will flow through the network
                   assign weights that control the speed of flow through different parts of the
                   network
                   specify rules that control how each element in the network connects to the
                   others
   • A network is a set of edges (lines) and junctions (points) that are topologically connected
       to each other.
   • Each edge knows which junctions are at its endpoints
   • Each junction knows which edges it connects to

Relationship class
In a geodatabase, relationship classes provide a way to model real-world relationships that exist
between objects such as parcels and buildings or streams and water sample data. By using
relationship classes, you can make your GIS database more accurately reflect the real world and
facilitate data maintenance.

The relationships stored in a relationship class can be between two feature classes (such as
buildings and parcels) or between a feature class and a nonspatial attribute table (such as streams
and water quality sampling data).

The relationship class is identical to a relate in ArcInfo -- the two items to be related must have a

                                                 25
common attribute (primary and foreign keys). The related information will show up in ArcMap if
you do an Identify on a feature, and the related data can be edited through ArcMap, ArcInfo, or
ArcEditor. To use the related information for symbology purposes in ArcMap, you must create a
join in ArcMap, but you will be able to choose the relationship class on which to base the join
instead of defining it again.

Three types of relationship
• In a 1-1 (on-to-one) relationship, each object of the origin table/feature class can be related to
   zero or one object of the destination table/feature class.
• In a 1-M (one-to-many) relationship, each object in the origin table/feature class can be
   related to multiple objects in the destination table/feature class.
• In a M-N (many-to-many) relationship, multiple objects of the origin table/feature class can
   be related to multiple objects of the destination table/feature class.

Two (2) types of geodatabase
• personal
• enterprise

Personal Geodatabase
The personal geodatabase is given a name of filename.mdb that is browsable and editable by the
ArcGIS, and it can also be opened with Microsoft Access. It can be read by multiple people at
the same time, but edited by only one person at a time. maximum size is 2 GB. no support of
raster

Multiuser Geodatabase
• Multiuser (ArcSDE or enterprise) geodatabase are stored in IBM DB2, Informix, Oracle,
  MySQL, PostgreSQL or Microsoft SQL Server.
• It can be edited through ArcSDE by many users at the same time, is suitable for large
  workgroups and enterprise GIS implementations. no limit of size. support raster data.

Geodatabase components - Raster data
• Raster data referenced only in personal geodatabase
• Raster data physically stored in multiusergeodatabse
• Raster datasets and raster catalogs
      A raster dataset is created from one or more individual rasters. When creating a raster
      dataset from multiple rasters, the data is mosaicked, or aggregated, into a single, seamless
      dataset in which areas of overlap have been removed. The input rasters must be
      contiguous (adjacent) and have the same properties, including the same coordinate
      system, cell size, and data format. For each raster dataset (.img, grid, JPEG, MrSID,
      TIFF), ArcGIS creates an ERDAS IMAGINE file (.img).
      –A raster catalog is defined as a table in the geodatabase which you can view like any
      other table in ArcCatalog. Each raster in the catalog is represented by a row in the table.
      It contains a collection of rasters that can be noncontiguous, stored in different formats,
      and have other different properties. In order to view all the rasters in the catalog, they
      must have the same coordinate system and a common geographic extent


                                                26
Grid datasets
• Cellular-based data structure composed of square cells of equal size arranged in rows and
   columns.
• The grid cell size and extension (number of rows and columns), as well as the value at each
   cell have to be stored as part of the grid definition.

Image datasets
   • Supported image formats:
         – ARC Digitized Raster Graphics (ADRG)
         – Windows bitmap images (BMP) [.bmp]
         – Multiband (BSQ, BIL and BIP) and single band images [.bsq, .bil and .bip]
         – ERDAS [.lan and .gis]
         – ESRI Grid datasets
         – IMAGINE [.img]
         – IMPELL Bitmaps [.rlc]
         – Image catalogs
         – JPEG [.jpg]
         – MrSID [.sid]
         – National Image Transfer Format (NITF)
         – Sun rasterfiles [.rs, .ras and .sun]
         – Tag Image File Format (TIFF) [.tiff, .tif and .tff]
         – TIFF/LZW

Representing Data with Raster and Vector Models
Raster Model
   • area is covered by grid with (usually) equal-sized, square cells
   • Attributes are recorded by assigning each cell a single value based on the majority feature
       (attribute) in the cell, such as land use type.
   • Image data is a special case of raster data in which the “attribute” is a reflectance value
       from the geomagnetic spectrum
            – cells in image data often called pixels (picture elements)

Vector Model
The fundamental concept of vector GIS is that all geographic features in the real work can be
represented either as:
    • points or dots (nodes): trees, poles, fire plugs, airports, cities
    • lines (arcs): streams, streets, sewers,
    • areas (polygons): land parcels, cities, counties, forest, rock type
Because representation depends on shape, ArcView refers to files containing vector data as
shapefiles


Lecture: Vinay Shankar Prasad Sinha
Application of GIS in Watershed Analysis using ArcMap, ArcCatalog, ArcToolbar

                                               27
Geo-statistical Analysis, Conceptual model, and Practical Exercise

ModelBuilder
The ModelBuilder Window in ArcGIS provides a graphical environment in which you can
build models.
A model is a representation of reality. It can describe static physical and non-physical
properties, work-flow processes, or both.

Why build models?
Building a model helps you manage and automate your geoprocessing work flow. Managing
processes and their supporting data can be difficult without the aid of a model.
Advantages of ModelBuilder
• • Visually representing workflow (excellent for students)
• • Automating workflows
• • Rerunning geoprocesses unlimited times with different data and parameters
• • Sharing models with other users
• • Exporting models as graphics for reports

It is easiest to think about ModelBuilder like a mathematical equation. There is an input or
multiple inputs of data, an operation is performed on the input data that alters it in a certain way,
and the data is returned as a new output.

ModelBuilder starts when you create or modify a model, done through ArcToolbox. Models can
be exported as graphics or scripts (models cannot loop, scripts can)
Similar to ArcView 3.x and ERDAS IMAGINE ModelBuilder programmes
    • Data Elements
    • Tool Elements
    • Derived Data Elements
    • Connectors
    • Text labels




   •   Graphics keep track of running process
          • Run = running process
          • Drop shadow = process/data completed
   •   As data is created, it can be added to ArcMap as layers
          • Right-click derived data, “Add to Display”
   •   Variables can be set on any process
   •   Models and scripts can be used as input to other models and scripts
   •   Models can be documented and shared
                                                 28
           •   It’s not just about sharing data any more!

Lecture: Vinay Shankar Prasad Sinha
M.A. (Geog.), P.G.Dip.(R.S.), M.Tech.(R.S.) “Research Associate”
The Energy and Resources Institute, New Delhi.
Exercise/Practical

Brief on GIS: Basics, Component, System, Sub-system, Capture, Database type/design, Storing
Methods, Manipulation, Analysis, query, Display and Data retrieval.

GIS is defined in a multi-disciplinary as:
“GIS: Geographical Intelligent System (The system which explain the geographical phenomena
with the help of software supported intelligent power)”

Geographical information system (GIS) is an organized collection of computer hardware,
software & geographic data designed to efficiently capture, store, manipulate, analyze and
display all forms of geographically referenced information. GIS is an interdisciplinary tool,
which has application in various fields such as Geography, Geology, Cartography, Comp. &
other Engineering, Surveying, Rural & Urban planning, Agriculture, Water resources, etc.

Spatial Information
Geographical features are depicted on map by Point, Line & Polygon.
POINT feature -A discrete location depicted by a special symbol or label. A single x, y
coordinates.
LINE feature -Represents a linear feature. A set of ordered x, y coordinates.
POLYGON feature - An area feature where boundary encloses a homogeneous area.

Non-spatial Information
Representation of non-spatial (Attribute) information -consists, of textural description on the
properties associated with geographical entities. Attributes are stored as a set of numbers and
characters in the form of a table. Many attribute data files can be linked together through the use
of common identifier code.

Component of GIS:
• Software component
• Hardware component
• Management factor

Hardware - Used to store, process and display data. Hardware capabilities affect processing
speed, ease of use and type of outputs available.
Software - Perform GIS operations. It contains procedures for performing various tasks.
Expertise - People, who provide the intelligence to use the system, develop procedures and
define the tasks of GIS.


Software component:

                                                29
Efficient Operating System: To processes large volume of data.
GIS software (Raster & Vector): To Create user oriented/ Define queries
Image processing software: To use old scan data or Remote Sensing data.
Other programming software (Window or Command): To create object-oriente programme for
different department requirements

Hardware Component:
– Basic computer component
– Scanner: To scan the maps & other geographical information.
– Plotter/ Printer: To print the Map/ Information or query about Geographical Phenomena.
– Digitizer: To convert hardcopy maps/ information in digital files.

Management Component:
To get efficient work.
To get maximum outputs.
To get proper maintenance of hardware & software component.

Capabilities of GIS
Uses of geographic information technology vary widely. There has been an explosion of GIS
applications in spatial data analysis over the past few years. There are very good example to
solve geo-scientific problems. Three major capabilities of GIS are:

Cartographic capability
Data management capability
Analytical capability

Cartographic capability allows accurate maps and engineering drawing to be produced
efficiently. This capability includes digitizing (converting analog products to digital form),
graphic display generation, interactive graphic manipulation (e.g. add, modify, delete, create
window) and plotting.
Data management capability enables the efficient storage and manipulation of geographic data,
both graphic and non-graphic. Storage and retrieval of non-geographic data is linked to graphic
images. It is sometimes called Attribute Processing. Attribute processing can select data and
produce graphic and reports on the basis of attribute value.
Analytical capability permits sophisticated processing and interpretation of spatial data.
Collectively, these capabilities give managers an enhanced ability to manipulate and use data
more effectively. Graphic representations are especially powerful for conveying information.

GIS As a Set of Interrelated Sub-Systems
GIS is a combination of various sub-systems. They are as follows:
Data processing system:
Data Analysis Subsystem:
Information Use subsystem:


Database management

                                              30
A data base here refer to a computerized collection of related information stored in such a way
that retrieval can be performed by linking various pieces of information together. It consists of
one or more data files, which are collection of related information treated as one unit on a
computer. Databases are managed and accessed via software termed Database Management
System (DBMS). Data base management system (DBMS) is a set of computer programs for
organizing the information in a database. Typically, a DBMS contains routines for data input,
verification, storage, retrieval and combination. The combination of hardware, software and the
database itself is referred to as a data base system.

The main characteristic of Geographical database is its spatial nature. A spatial database is a
collection of spatially referenced data that act as a model of reality. All the basic data types in
geography / geology are spatially distributed such as geomorphological feature, rock type, well
site, lineaments, roads etc. Hence Geographic Information System provides an excellent tool to
design, implement and manage geographical data in a most efficient manner.

Database Design:
As in normal activity, GIS database needs to be properly designed to cater to the needs of
specific application. The design should define a comprehensive framework of database,
identification of essential and correct data elements, updating procedure etc. Generally, the
database design include-

Conceptual design: It is independent of software and hardware and defines the application needs
and the objective of GIS database-
Specific to the ultimate use of GIS database, E.g., GIS database for natural resource
management, Ground water management etc.

Defining level of database indicates the scale or level of data contents of database
Spatial elements of database – defining the spatial database (primary & derived) that will
populate the database.
Non-spatial elements of the database – defining the non-spatial datasets (primary & derived) that
will populate the database.
Sources of spatial and non-spatial data- identifying the data collection and data generation
activity.

Logical design:
It pertains to the logical definition of the database and is specific to a GIS package. It includes-
Defining the coordinate system of the database – All spatial elements can be referenced to
uniform coordinate system.
Defining spatial framework – Latitude /Longitude graticules, spatial files design, identification
of registration points.

Defining attribute codes and their description
Spatial database normalization-
        • Identification of master templates
        • Ensuring that the features of various elements are coordnate coincident.
Tolerance definitions-

                                                31
       •   Coordinate movement tolerance – Defines the position and is a function of scale.
       •   Weed Tolerance- Minimum separation between coordinates while digitization.
       •   MSU- Maximum spatial units, indicating the smallest representative area. Feature
           having less area than MSU can be aggregated.
       •   Defining the linkage between spatial and non-spatial database through a code.

Physical design: It is based on experience and pertains to-
       • Disk space requirement.
       • Load of database.
       • Access and speed requirement.
       • Platform related aspects.

Database characteristics:
It should be contemporaneous – should contain information of the same vintages for the entire
measured variable.
    • It should be positionally accurate.
    • The category of information and sub categories within them should contain all the data
        needed to analyze or model the behavior of the resource using conventional methods and
        model.
    • Exactly compatible with other information that may be compared with it
    • Internally accurate, portraying the nature of phenomena without error requires clear
        definition of phenomena that are included.
    • Readily updated on a regular schedule.
    • Accessible to whoever needs it.

GIS DATA MODELS
Geographical variations are infinitely complex and must be represented in terms of discrete
objects. Conversion of real world geographical variation into discrete objects is done through
data models. It represents the linkage between the real world domain of geographic data and
computer representation of these features.

Raster data model:
   • Divides the entire area into rectangular grid cells, where x = y distance
   • Each cell contains a single value and every location corresponds to a cell.
   • One set of cells and associated values is a LAYER / CHANNEL.

Vector data model:
   • Uses discrete line segments or points represented by their explicit x, y coordinates to
       identify locations.
   • Discrete objects (boundaries, streams) are formed by connecting line segments.
   • Area is defined by set of line segments.

IMPORTANT GIS ANALYSIS (Line/Area)
    • SPATIAL ANLYSIS (Lineament Direction or filter)
    • ROUTE / NETWORK ANALYSIS

                                                32
       •   LINE BUFFER
       •   SURFACE ANALYSIS (TIN OR GRID)
       •   IDENTITY ANALYSIS (Line in polygon)
       •   INTERSECT ANALYSIS (Line in polygon)
       •   NEAREST ANALYSIS
                 • APPEND
                 • CLIP
                 • ERASE
                 • SPLIT
                 • LINE OF SIGHT
                 • VISIBILITY ANALYSIS
                 • CONTOUR GENERATION
                 • PROFILE

Working with Grid feature:
This feature represent by number of cells in X & Y direction with equal size. Z-direction
represents the attribute of spatial feature.

IMPORTANT GIS ANALYSIS
    • DIGITAL ELEVATION MODEL
    • TOPOGRAPHICAL ELEVATION MODEL
    • SLOPE DIRECTION
    • RUN OFF ANALYSIS (FLOW DIRECTION)
    • FLOW ACCUMILATION.
    • DARCY FLOW VECTOR.
    • WATERSHED DEFINATION.

Manipulation & Analysis
Geographical analysis allows studying the real world process by developing and applying
manipulation and analysis criteria.

Step for performing geographical analysis:
For doing any kind of analysis for arriving at desired results, the goals and objectives must be
define which will set the sequence of analysis functions to be performed on the data.

Generally, following steps are involved –
   • Establish objectives and analysis criteria.
   • Prepare data for spatial operations.
   • Perform spatial operations.
   • Perform tabular analysis.
   • Evaluate and interpret the results.
   • Refine the analysis if necessary.
   • Produce final maps and tabular reports.

Topological Overlays:

                                              33
   •   Spatial Join
   •   Identity
   •   Intersect
   •   Union
   •   Feature Extraction
   •   Clip
   •   Erase
   •   Reselect
   •   Feature Merging
   •   Dissolve
   •   Eliminate
   •   Proximal Operations
   •   Buffer
   •   Coordinate Transformation
   •   Transform
   •   Project
   •   Map Database Merging and Splitting
   •   Mapjoin
   •   Split

DATA MODELS:
Geographical variations are infinitely complex and must be represented in terms of discrete
objects. Conversion of real world geographical variation into discrete objects is done through
data models. It represents the linkage between the real world domain of geographic data and
computer representation of these features.

Raster data model:
Divides the entire area into rectangular grid cells, where x = y distance
Each cell contains a single value and every location corresponds to a cell.
One set of cells and associated values is a LAYER / CHANNEL

Vector data model:
Uses discrete line segments or points represented by their explicit x, y coordinates to identify
locations.
Discrete objects (boundaries, streams) are formed by connecting line segments.
Area is defined by set of line segments.

Raster data structure:
   • Chain Code
   • Block Code
   • Quadra tree
   • Run length



   Week 3: 31st January – 4th February 2011

                                                34
Lecturer: Nimesh Dugar
MapInfo
Exercise/Practical

As with most other GIS packages, several files are required to allow the user to open a data set
for viewing within Mapinfo Professional. The most basic view would be the browser view only.
This environment provides storage of attribute or object data and is represented like a
spreadsheet. Only data can be seen in a tabular format with this environment, no geographic
information is available at this point.
Minimum files required for the basic Mapinfo browser environment:
    • .DAT (The file which stores the attribute data. This usually a dBase III DBF file)
    • .TAB (The ASCII file which is the link between all other files and holds information
       about the type of data file )
To view geographic information (the graphic representation of data) in Mapinfo Professional,
two additional files are required and added to the basic requirements for simply viewing data.
Minimum files required to view a map with the data previously discussed:

.ID (Stores information linking graphic data to the database information. This contains a 4-byte
integer index into the MAP file for each feature)
.MAP (Stores the graphic and geographic information needed to display a map on the users
screen)
.IND (Optional index files for tabular data. This is present if any fields are indexed).

The basic file set for viewing data and its graphic representation within Mapinfo Professional
requires a minimum of four files, the *.DAT, *.TAB, *.ID and *.MAP
If you have only textual information and there are no graphic objects, then a minimum of two
files is needed, *.DAT and *.TAB. If one opens, *.TXT, *.XLS *.WK*, *.MDB, then MapInfo
creates a .TAB file that contains the definition of file, and data structure, so next time one can
open the TAB file only.

There   are also temporary files created by MapInfo while there are some edits on the file. Those
are
    •   .TDA Temporary database file
    •   .TIN Temporary index file
    •   .TMA Temporary Map File
    •   When using a remote table such as Oracle Locator or Spatial, if the data is downloaded to
        the local machine, the temporary file extensions are:
   •    .LDA Local Temporary database file
   •    .LIN Local Temporary index file
   •    .LMA Local Temporary Map File

If MapInfo halts or in case the edited changes are not saved and the power is gone, those files
remain in the computer.

The software is capable of overlaying raster and vector layers on the same map; the former can
be made semi-transparent, so that they can serve as more than mere backdrops.

                                                35
MapInfo is popular both in business and the public sector, where a typical user is analyzing pre-
built map data layers.


Lecturer: Dr. Shalini Singh
Remote Sensing and Data Collection
Digital image Processing
Digital Numbers
Exercise/Practical


Lecture: Shailendra Suman
Software Project Management
Software Development Life Cycle (SDLC) - SDLC Model
A framework that describes the activities performed at each stage of a software development
project. It is a top-down approach which converts data into an operational database. The phases
of SDLC are:

   •   Strategy and analysis
   •   Design
   •   Build and documentation
   •   Transition
   •   Production

Phase 1 Planning
Planning is the first phase of software development. In this phase the client give the details and
concepts of his/her software and we plan the requirement of resources, time & budget of the
proposed development.

Phase 2 - Requirements Analysis
The requirements analysis phase is concerned with capturing the requirements of the package.
The requirements review is a meeting with the aim of discussing these requirements. The final
output of this phase is a formal requirements document (Software Requirement Specification),
which aims to freeze the requirements at this point and will serve as input to the design phase.
Phase 3 - Design & Development
The design phase is concerned with design of the software. Things to keep in mind are things
like quality, flexibility (code reuse, future addition of features/functionality) etc. The final output
of this phase is a formal design document (Software Design Document), which aims to freeze the
design at this point and will serve as input to the coding phase. It serves as secondary function as
a reference document for the code and can be particularly useful for developers that should work
on the code in the future.
Phase 4 - Implementation
The implementation phase involves the actual coding/programming of the software.
The output of this phase is typically the library, executables and User Manuals and additional
software documentation.
Phase 5 - Testing and Integration

                                                  36
The testing phase is concerned with the validation and verification of the software Unit testing is
done on units and integration testing is done by including this package/unit together with other
packages/units and testing them all together.
Phase 6 - Evaluation
Release the pilot of the product and client evaluates the product. If he /she require modification
in the product he suggest it and we do it within a very short span of time.
Phase 7 - Release
The Release phase involves the packaging of all sub-packages, together with all relevant
documentation in a suitable format for distribution.
Phase 8 - Recycle
In case of log term projects, the release phase is the staring point of recycling of the project, but
in short term projects release phase is the point of sign off too.

THE SDLC WATERFALL
Small to medium database software projects are generally broken down into six stages:
• Project
• Planning
• Requirements
• Definition
• Design
• Development
• Integration
• & Test
• Installation & Acceptance

The relationship of each stage to the others can be roughly described as a waterfall, where the
outputs from a specific stage serve as the initial inputs for the following stage. During each stage,
additional information is gathered or developed, combined with the inputs, and used to produce
the stage deliverables. It is important to note that the additional information is restricted in scope;
“new ideas” that would take the project in directions not anticipated by the initial set of high-
level requirements are not incorporated into the project. Rather, ideas for new capabilities or
features that are out-of-scope are preserved for later consideration. After the project is
completed, the Primary Developer Representative (PDR) and Primary End-User Representative
(PER), in concert with other customer and development team personnel develop a list of
recommendations for enhancement of the current software.




                                                  37
Lecture: Shailendra Suman
Global Positioning System (GPS)
Exercise/Practical

The Global Positioning System (GPS) was designed for military applications. Its primary
purpose was to allow soldiers to keep track of their position and to assist in guiding weapons to
their targets. The satellites were built by Rockwell International and were launched by the U.S.
Air Force. The entire system is funded by the U.S. government and controlled by the U.S.
Department of Defense. The total cost for implementing the system was over $12 billion.

A GPS satellite. The GPS constellation of satellites consists of at least 24 satellites – 21 primary
satellites and 3 orbiting spares. They orbit the earth at an altitude of 17,500 KM (10,900 miles)
at a speed of 1.9 miles per second between 60°N and 60°S latitude. Each satellite weighs 1900
lbs and is 17 feet (5.81 meters) wide with solar panels extended. The satellites orbit the earth
twice a day. This guarantees that signals from six of the satellites can be received from any point
on earth at almost any time.

GPS Satellites
The GPS Operational Constellation consists of 24 satellites that orbit the Earth in very precise

                                                38
orbits twice a day. GPS satellites emit continuous navigation signals.

Receivers and Satellites
GPS units are made to communicate with GPS satellites (which have a much better view of the
Earth) to find out exactly where they are on the global scale of things.

GPS Signals

Each GPS satellite transmits data that indicates its location and the current time. All GPS
satellites synchronize operations so that these repeating signals are transmitted at the same
instant.

Satellite frequencies
• L1 (1575.42 MHz): Mix of Navigation Message, coarse-acquisition (C/A) code and
   encrypted precision P(Y) code, plus the new L1C on future Block III satellites.
• L2 (1227.60 MHz): P(Y) code, plus the new L2C code on the Block IIR-M and newer
   satellites since 2005.
• L3 (1381.05 MHz): Used by the Nuclear Detonation (NUDET) Detection System Payload
   (NDS) to signal detection of nuclear detonations and other high-energy infrared events. Used
   to enforce nuclear test ban treaties.
• L4 (1379.913 MHz): Being studied for additional ionospheric correction.
• L5 (1176.45 MHz): Proposed for use as a civilian safety-of-life (SoL) signal (see GPS
   modernization). This frequency falls into an internationally protected range for aeronautical
   navigation, promising little or no interference under all circumstances. The first Block IIF
   satellite that would provide this signal is set to be launched in 2010

   •   GPS and remote sensing imagery are primary GIS data sources, and are very important
       GIS data sources.
   •   GPS data creates points (positions), polylines, or polygons
   •   Remote sensing imagery and aerial photos are used as major basis map in GIS
   •   Information digitized or classified from imagery are GIS layers




                                               39
Space Segment
The nominal GPS Operational Constellation consists of 24 satellites that orbit the earth in 12
hours. There are often more than 24 operational satellites as new ones are launched to replace
older satellites. The satellite orbits repeat almost the same ground track (as the earth turns
beneath them) once each day. The orbit altitude is such that the satellites repeat the same track
and configuration over any point approximately each 24 hours (4 minutes earlier each day).
There are six orbital planes, with nominally four SVs (Satellite Vehicles) in each, equally spaced
(60 degrees apart), and inclined at about fifty-five degrees with respect to the equatorial plane.
This constellation provides the user with between five and eight SVs visible from any point on
the earth.

Control Segment
The Master Control facility is located at Schriever Air Force Base (formerly Falcon AFB) in
Colorado. These monitor stations measure signals from the SVs which are incorporated into
orbital models for each satellites. The models compute precise orbital data (ephemeris) and SV
clock corrections for each satellite. The Master Control station uploads ephemeris and clock data
to the SVs. The SVs then send subsets of the orbital ephemeris data to GPS receivers over radio
signals.

User Segment
The GPS User Segment consists of the GPS receivers and the user community. GPS receivers
convert SV signals into position, velocity, and time estimates. GPS receivers are used for
navigation, positioning, time dissemination, and other research.


                                               40
Coordinate System and Height
   • GPS use the WGS 84 as datum
   • Various coordinate systems are available for chosen
   • GPS height (h) refers to ellipsoid surface, so it is a little difference from the real
      topographic height (H). the difference is the geoid height (N), the approximate Mean Sea
      Level. Some newer GPS units now provide the H by using the equation H=h-N (N from a
      globally defined geoid – Geoid99)


Lecture: Shailendra Suman
Principles of Remote Sensing (RS)
• To be of greatest value, the original remotely sensed data must usually be calibrated in two
   distinct ways:
• It should be geometrically (x,y,z) and radiometrically (e.g, to percent reflectance) calibrated
   so that remotely sensed data obtained on different dates can be compared with one another.
• The remotely sensed data must usually be calibrated (compared) with what is on the ground
   in terms of biophysical (e.g., leaf-area-index, biomass) or cultural characteristics (e.g., land
   use/cover, population density).
• Fieldwork is necessary to achieve both of these objectives . Thus, a person who understands
   how to collect meaningful field data about the phenomena under investigation is much more
   likely to use the remote sensing science wisely.

Remote Sensing
Definition: “The measurement or acquisition of information of some property of an object or
phenomenon, by a recording device that is not in physical or intimate contact with the object or
phenomenon under study” (Colwell, 1997).

Remote sensing data collection
ASPRS adopted a combined formal definition of photogrammetry and remote sensing as
(Colwell, 1997): “the art, science, and technology of obtaining reliable information about
physical objects and the environment, through the process of recording, measuring and
interpreting imagery and digital representations of energy patterns derived from non-contact
sensor systems”.

A remote sensing instrument collects information about an object or phenomenon within the
instantaneous-field-of-view (IFOV) of the sensor system without being in direct physical contact
with it. The sensor is located on a suborbital or satellite platform.

Remote sensing is the science (and to some extent, art) of acquiring information about the Earth's
surface without actually being in contact with it. This is done by sensing and recording reflected
or emitted energy and processing, analyzing, and applying that information.




                                                41
Elements of a Remote Sensing System
• Information User
• Area or scene of interest
• Sensing Device
• Data Recorder
• Information Production System
• Information Delivery System

A remote sensing system
• Energy source (EMR)
• Platform
• Sensor
• Data recording / Transmission
• Ground receiving station
• Data processing
• Expert interpretation / data users

Types of sensors
• CAMERA
• SCANNER
• RADAR

Scanning systems can be used on both aircraft and satellite platforms and have essentially the
same operating principles. A scanning system used to collect data over a variety of different
wavelength ranges is called a multispectral scanner (MSS), and is the most commonly used
scanning system. There are two main modes or methods of scanning employed to acquire
multispectral image data
   • Across-track scanning

                                             42
   •   Along-track scanning

ACROSS-TRACK SCANNER: scan the Earth in a series of lines. The lines are oriented
perpendicular to the direction of motion of the sensor platform (i.e. across the swath). Each line
is scanned from one side of the sensor to the other, using a rotating mirror (A). As the platform
moves forward over the Earth, successive scans build up a two-dimensional image of the Earth´s
surface.




The incoming reflected or emitted radiation is separated into several spectral components that are
detected independently. The UV, visible, near-infrared, and thermal radiation are dispersed into
their constituent wavelengths.

A bank of internal detectors (B), each sensitive to a specific range of wavelengths, detects and
measures the energy for each spectral band and then, as an electrical signal, they are converted to
digital data and recorded for subsequent computer processing.

The IFOV (C) of the sensor and the altitude of the platform determine the ground resolution cell
viewed (D), and thus the spatial resolution. The angular field of view (E) is the sweep of the
mirror, measured in degrees, used to record a scan line, and determines the width of the imaged

                                                43
swath (F).

Satellites, because of their higher altitude need only to sweep fairly small angles (10-20º) to
cover a broad region. Because the distance from the sensor to the target increases towards the
edges of the swath, the ground resolution cells also become larger and introduce geometric
distortions to the images. Also, the length of time the IFOV "sees" a ground resolution cell as the
rotating mirror scans (called the dwell time), is generally quite short and influences the design of
the spatial, spectral, and radiometric resolution of the sensor.

ALONG -TRACK SCANNER: It uses the forward motion of the platform to record successive
scan lines and build up a two-dimensional image, perpendicular to the flight direction. Along
track scanners use a linear array of detectors (A) located at the focal plane of the image (B)
formed by lens systems (C), which are "pushed" along in the flight track direction.




Each individual detector measures the energy for a single ground resolution cell (D) and thus the
size and IFOV of the detectors determines the spatial resolution of the system. A separate linear
array is required to measure each spectral band or channel. For each scan line, the energy
detected by each detector of each linear array is sampled electronically and digitally recorded.

There are two types of scanners, black and white and multispectral. The scanners are MADE UP
OF CHARGE COUPLE DEVICES AND/OR MIRRORS and OUTPUT AS GOOD AS CCD
SENSITIVITY
The TECHNIQUES used to capture data are either WHISK BROOM or PUSH BROOM

A PUSHBROOM SCANNER HAS AN ARRAY OF CCDs
CAPABLE OF ACCEPTING REFLECTED ENERGY FROM WHOLE OF A SCAN LINE
SIMULTANE-OUSLY




                                                44
Types of resolution
• SPATIAL - Discrimination by Distance
• SPECTRAL - Discrimination by Wave length
• RADIOMETRIC - Discrimination by energy levels
• TEMPORAL - Discrimination by Time

SPATIAL RESOLUTION
IT IS THE ABILITY OF A SENSOR TO DISCRIMINATE BETWEEN TWO NEARBY
OBJECTS ON THE SURFACE OF THE EARTH. IT DEPENDS ON
• SENSOR SPEC - PIXEL SIZE/FOCAL LENGTH
• THE DISTANCE BETWEEN THE OBJECTS
- TEXTURAL/CONTRAST BETWEEN OBJECTS
• SIZE OF THE OBJECTS
- “REFLECTANCE” OF THE OBJECTS IN RELATION TO THE SURROUNDING AREA

GROUND SEGMENT
• DATA ACQUISITION
• SATELLITE CONTROL
• ERROR CORRECTIONS
• DISSEMINATION

Advantages of Remote Sensing
• Remote sensing is unobtrusive if the sensor passively records the EMR reflected or emitted
  by the object of interest. Passive remote sensing does not disturb the object or area of
  interest.
• Remote sensing devices may be programmed to collect data systematically, such as within a
  9 × 9 in. frame of vertical aerial photography. This systematic data collection can remove the
  sampling bias introduced in some in situ investigations.
• Under controlled conditions, remote sensing can provide fundamental biophysical
  information, including x,y location, z elevation or depth, biomass, temperature, and moisture
  content.
• Remote sensing–derived information is now critical to the successful modeling of numerous
  natural (e.g., water-supply estimation; eutrophication studies; nonpoint source pollution) and
  cultural (e.g., land-use conversion at the urban fringe; water-demand estimation; population
  estimation) processes.

Limitations of Remote Sensing
• The greatest limitation is that it is often oversold. Remote sensing is not a panacea that
   provides all the information needed to conduct physical, biological, or social science
   research. It provides some spatial, spectral, and temporal information of value in a manner
   that we hope is efficient and economical.
• Human beings select the appropriate remote sensing system to collect the data, specify the
   various resolutions of the remote sensor data, calibrate the sensor, select the platform that
   will carry the sensor, determine when the data will be collected, and specify how the data are
   processed. Human method-produced error may be introduced as the remote sensing
   instrument and mission parameters are specified.

                                               45
•       Powerful active remote sensor systems that emit their own electromagnetic radiation (e.g.,
        LIDAR, RADAR, SONAR) can be intrusive and affect the phenomenon being investigated.
        Additional research is required to determine how intrusive these active sensors can be.
•        Remote sensing instruments may become uncalibrated, resulting in uncalibrated remote
        sensor data.
•        Remote sensor data may be expensive to collect and analyze. Hopefully, the information
        extracted from the remote sensor data justifies the expense.

Advantages of using satellite RS
Remotely sensed data acquired by the Earth observation satellites provides a number of benefits
for studying the Earth's surface, including:
• continuous acquisition of data
• regular revisit capabilities (resulting in up-to-date information)
• broad regional coverage
• good spectral resolution (including infra-red bands)
• good spatial resolution
• ability to manipulate/enhance digital data
• ability to combine satellite digital data with other digital data
• cost effective data
• map-accurate data
• possibility of stereo viewing
• large archive of historical data

Disadvantages
• Remote sensing has various issues
      – Can be expensive
      – Can be technically difficult
      – NOT direct

Remote Sensing Data Collection
There are two fundamental ways to obtain digital imagery:
- acquire remotely sensed imagery in an analog format (often referred to as hard-copy) and
   then convert it to a digital format through the process of digitization, and
- acquire remotely sensed imagery already in a digital format, such as that obtained by the
   Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor system.

Landsat ETM+ spectral bands
 Band          Wavelengths (µm)                             Ground resolution (m)
    1                  0.45–0.515 (blue)                    30

    2                  0.525–0.605 (green)                  30
    3                  0.63–0.69 (red)                      30
    4                  0.75–0.90 (near infrared)            30


                                                   46
 5                  1.55–1.75 (SWIR)                       30
 6                  10.4–12.5 (thermal infrared)           60
 7                  2.09–2.35 (SWIR)                       30
 Pan                0.52–0.90                              15


Lecture: Dr. Shalini Singh
ERDAS IMAGINE
Exercise/Practical

The ERDAS IMAGINE system incorporates the functions of both image processing and GIS.
These functions include importing, viewing, altering, and analyzing raster and vector data sets. It
is a complete Image Processing and GIS package and employs a graphical user interface for:
• Reference imagery to the earth’s surface
• Measure imagery to collect vector, point and area data and create digital terrain models
• Analyze the results to draw conclusions about the processes and activities affecting your area
     of study
• Present imagery and geospatial information in 2D and 3D environments
• Update GIS with accurate geospatial data
• Directly read over 50 formats
• Import / export over 100 formats
• Geometrically correct to hundreds of map projections
• Single-frame orthorectification
• Rapidly reproject from one projection to another
• Mosaic images
• Image to image registration
• Resampling nearest neighbor
• Radiometric correction
• Striping and banding
• Atmospheric correction
• Linear stretching


     Week 4: 7th – 11th February 2011

Lecture: Shailendra Suman
Space Segment Consideration (continued from week 3)
Thermal Infrared Remote Sensing (continued from week 3)

Lecture: Ritesh Kumar, “ M. Tech. Remote Sensing”, Birla Institute of Technology (BIT)
Mesra, Ranchi
Active microwave (RADAR)

                                                47
Passive and Active Remote Sensing Systems
Passive remote sensing systems record electromagnetic energy that is reflected (e.g., blue, green,
red, and near-infrared light) or emitted (e.g., thermal infrared energy) from the surface of the
Earth. There are also active remote sensing systems that are not dependent on the Sun’s
electromagnetic energy or the thermal properties of the Earth.
Active remote sensors create their own electromagnetic energy that 1) is transmitted from the
sensor toward the terrain (and is largely unaffected by the atmosphere), 2) interacts with the
terrain producing a backscatter of energy, and 3) is recorded by the remote sensor’s receiver.

The most widely used active remote sensing systems include:
• Active microwave (RADAR), based on the transmission of longwavelength microwaves (e.g., 3
– 25 cm) through the atmosphere and then recording the amount of energy back-scattered from
the terrain;
• LIDAR, which is based on the transmission of relatively shortwavelength laser light (e.g., 0.90
mm) and then recording the amount of light back-scattered from the terrain; and
• SONAR, which is based on the transmission of sound waves through a water column and then
recording the amount of energy back-scattered from the bottom or from objects within the water
column.

Sending and Receiving a Pulse of Microwave
EMR - System Components
• The pulse of electromagnetic radiation sent out by the transmitter through the antenna is of a
specific wavelength and duration (i.e., it has a pulse length measured in microseconds, m sec).
• The wavelengths are much longer than visible, near-infrared, mid-midinfrared, or thermal
infrared energy used in other remote sensing systems.
Therefore, microwave energy is usually measured in centimeters rather than micrometers.
• The unusual names associated with the radar wavelengths (e.g., K, Ka, Ku, X, C, S, L, and P)
are an artifact of the original secret work on radar remote sensing when it was customary to use
the alphabetic descriptor instead of the actual wavelength or frequency.

Primary Advantages of RADAR - Remote Sensing of the Environment
Active microwave energy penetrates clouds and can be an all-weather remote sensing system.
• Synoptic views of large areas, for mapping at 1:25,000 to 1:400,000; cloud-shrouded countries
may be imaged.
• Coverage can be obtained at user-specified times, even at night.
• Permits imaging at shallow look angles, resulting in different perspectives that cannot always
be obtained using aerial photography.
• Senses in wavelengths outside the visible and infrared regions of the electromagnetic spectrum,
providing information on surface roughness, dielectric properties, and moisture content.

May penetrate vegetation, sand, and surface layers of snow.
• Has its own illumination, and the angle of illumination can be controlled.
• Enables resolution to be independent of distance to the object, with the Secondary




                                               48
Advantages of RADAR Remote Sensing of the Environment
• size of a resolution cell being as small as 1 x 1 m.
• Images can be produced from different types of polarized energy (HH, HV, VV, VH).
• May operate simultaneously in several wavelengths (frequencies) and thus has multi-
  frequency potential.
• Can measure ocean wave properties, even from orbital altitudes.
• Can produce overlapping images suitable for stereoscopic viewing and radargrammetry.
• Supports interferometric operation using two antennas for 3-D mapping.

Radar Nomenclature
• Nadir
• Azimuth flight direction
• Range (near and far)
• Depression angle (g)
• Look angles (f)
• Incidence angle (q)
• Altitude above-ground-level, H
• Polarization

Azimuth Direction
• The aircraft travels in a straight line that is called the azimuth flight direction.
• Pulses of active microwave electromagnetic energy illuminate Azimuth Direction strips of
   the terrain at right angles (orthogonal) to the aircraft’s direction of travel, which is called the
   range or look direction.
• The terrain illuminated nearest the aircraft in the line of sight is called the near-range. The
   farthest point of terrain illuminated by the pulse of energy is called the far-range.

Range Direction
• The range or look direction for any radar image is the direction of the radar illumination that
   is at right angles to the direction the aircraft or spacecraft is traveling.
• Generally, objects that trend (or strike) in a direction that is orthogonal (perpendicular) to the
   range or look direction are enhanced much more than those objects in the terrain that lie
  parallel to the look direction. Consequently, linear features that appear dark or are
   imperceptible in a radar image using one look direction may appear bright in another radar
   image with a different look direction.


Lecture: Dr. Shalini Singh
ArcGIS
Introduction to Image Interpretation
Digital Image Processing
Digital Image Enhancement
Digital Image Classification
ERDAS Imagine
Practicals on Image to image registration, Re-sampling nearest neighbor, striping and
banding, Atmospheric correction, Classification, Image manipulation, Spectral

                                                 49
Enhancement, Radiometric Correction, Modeler using ERDAS
Remote Sensing and Data Collection


Lecture: Dr. Shalini Singh
Digital image Processing and Classification
Linear Stretching
Change Detection
Exercise/Practical

Lecture: Nishant Sinha - Project Manager: Pitney Bowes Business Insight (MapInfo)
Principal Component Analysis (PCA)
Exercise/Practical

PCA is often used as a method of data compression. It allows redundant data to be compacted
into fewer bands – that is the dimensionality of the data is reduced. The bands of PCA data are
non-correlated and independent and are more interpretable than the source data.

Principal Component Analysis (PCA)
• A statistical techniques frequently used in signal processing for data dimension reduction or
    data decorrelation
• Linear transformation technique related to Factor Analysis
• For given set of Image bands, new set of images produced known as Components
• Principal Component Characteristics
• Statistical abstraction of the variability inherent in the original band set
• Uncorrelated with one another
• Ordered in terms of amount of variance they explain from the original band
• Reduces dimensionality of data by keeping most significant parts of data

Application of PCA
  Means of Data compaction
          For multispectral set, first two or three components explain virtually all of the original
          reflectance values
          Later components can be rejected to decrease volume of data with no appreciable loss
          of information
  Used as noise removal technique
          Later components of PCA dominated by noise effects and hence can be excluded
          thereby removing noise artifacts
• Used as stripe removal technique


   Week 5: 14th – 19th February 2011

Lecture: Dr. Shalini Singh
Digital Image classification
Exercise/Practical
                                                50
Digital Image classification
   Multispectral classification is the process of sorting pixels into a finite number of individual
   classes, or categories of data, based on their data file values. If a pixel satisfies a certain set
   of criteria , the pixel is assigned to the class that corresponds to that criteria.
   Multispectral classification may be performed using a variety of algorithms
   Hard classification using supervised or unsupervised approaches.
    Classification using fuzzy logic, and/or
    Hybrid approaches often involving use of ancillary information.

Digital image classification is used in
• grouping of similar features
• separation of dissimilar ones
• assigning class label to pixels
• resulting in manageable size of classes

Classification methods
Manual
   • visual interpretation
   • combination of spectral and spatial information
Computer assisted
   • mainly spectral information
Stratified
   • using GIS functionality to incorporate
   • knowledge from other sources of information

Uses
• To translate continuous variability of image data into map patterns that provide meaning to
   the user.
• To obtain insight in the data with respect to ground cover and surface characteristics.
• To find anomalous patterns in the image data set.

Advantages
• Cost efficient in the analyses of large data sets
• Results can be reproduced
• More objective then visual interpretation
• Effective analysis of complex multi-band (spectral) interrelationships




                                                 51
Image classification methods




•   It is also important for the analyst to realize that there is a fundamental difference between
    information classes and spectral classes.
•   * Information classes are those that human beings define.
•   * Spectral classes are those that are inherent in the remote sensor data and must be identified
    and then labeled by the analyst.

There are two types of classifications, supervised and unsupervised.

Supervised image classification
• The identity and location of some of the land cover types such as urban, agriculture, wetlands
   are known a priori through a combination of field work and experience.
• The analyst attempts to locate specific sites in the remotely sensed data that represent
   homogenous examples of these known land cover types known as training sites.
• Multivariate statistical parameters are calculated for these training sites.
• Every pixel both inside and outside the training sites is evaluated and assigned to the class of
   which it has the highest likelihood of being a member.

Unsupervised image classification
• The identities of land cover types to be specified as classes within a scene are generally not

                                                52
    known a priori because ground reference information is lacking or surface features within the
    scene are not well defined.
•   The computer is required to group pixels with similar spectral characteristics into unique
    clusters according to some statistically determined criteria.
•   Analyst then combine the spectral clusters into information classes.

       Clustering algorithm
        User defined cluster parameters
        Class mean vectors are arbitrarily
       set by algorithm (iteration 0)
        Class allocation of feature vectors
        Compute new class mean vectors
        Class allocation (iteration 2)
        Re-compute class mean vectors
        Iterations continue until convergence threshold has been reached
        Final class allocation
       Cluster statistics reporting

Supervised vs. Unsupervised Training
• In supervised training, it is important to have a set of desired classes in mind, and then create
   the appropriate signatures from the data.
• Supervised classification is usually appropriate when you want to identify relatively few
   classes, when you have selected training sites that can be verified with ground truth data, or
   when you can identify distinct, homogeneous regions that represent each class.
• On the other hand, if you want the classes to be determined by spectral distinctions that are
   inherent in the data so that you can define the classes later, then the application is better
   suited to unsupervised training. Unsupervised training enables you to define many classes
   easily, and identify classes that are not in contiguous, easily recognized regions.


Lecture: Vinay Shankar Prasad Sinha
GIS Modeling, ArcGIS3.3 and ArcGIS, Arctoolbox and ArcCatalog
Exercise/Practical

GIS Data Model

The hard part of GIS analysis is figuring out which tools to use to solve your GIS problem.

POINT THEMES
A point is a GIS feature that has no length or area. It has a specific X,Y coordinate and attribute
information associated with that location point.

POINT THEMES
A point is a GIS feature that has no length or area. It has a specific X,Y coordinate and attribute
information associated with that location point.



                                                53
LINE THEMES
A line or arc is a GIS feature that has length but no width.

 Since the GIS stores each arc as a series of X,Y vertices, it can easily estimate the length of each
stream arc. The GIS computes the length of each stream arc in the same units as your GIS
coordinate system. And since each stream arc has a unique stream#, the GIS can determine
spatial relationships among arcs. As a user, you can store information about each stream in the
arc attribute table. Information could be quantities (stream pH), categories (stream class),
character strings (stream name), and dates (month/day/year). Each arc is composed of a series of
X, Y coordinates called vertices .

NETWORK THEMES
A network is a special type of line theme consisting of connected arcs such as streets, utility
lines, or stream networks.

DYNAMIC SEGMENTATION
Sometimes important line information is not available in X, Y coordinates, but instead is
recorded as measurements along lines such as mileage along a road, meters along a transect, etc.
This type of information can be translated into a GIS by using a technique called Dynamic
Segmentation. The technique allows for segmentation of arcs into sections without changing the
arc-node structure of a line theme.

POLYGON THEMES
A polygon is a GIS feature that has an area and a perimeter.
 A polygon attribute table has a special record for an artificial polygon called the universe
polygon . The universe polygon has an area that is the sum of the area of all polygons in the
theme. It is always assigned a negative sign because it is an artificial polygon that is used by the
GIS in computations.

GRID THEMES
Grids are grid cells with a fixed number of rows and columns that have several tables associated
with them. Grids that are common in GIS include digital elevation and land cover grids.

IMAGE THEMES
Images are special grids typically derived from some remote sensing device like a satellite
sensor, a digital camera, or a desktop scanner. Examples of images commonly used in remote
sensing include digital orthos, satellite imagery, and scanned maps.

TOOLS FOR MANAGING GIS FEATURES
There are several generic tools that are applicable to managing points, lines, polygons, grids, and
images. They are as follows:
   • LIST—List the contents of any GIS table.
   • COPY—Makes a new copy theme from any point, line, polygon, or grid theme.
   • APPEND—Appends 2 or more point, line, or polygon themes.
   • KILL—Deletes a user-specified point, line, polygon, or grid theme.
   • RENAME—Renames a user-specified point, line, polygon, or grid theme.

                                                 54
   •   DESCRIBE—Tells the user information about a point, line, polygon, grid, or image
       theme.

TOOLS FOR BUILDING ATTRIBUTE TABLES
The following generic tools can be used for creating tables associated with GIS themes.
BUILD
• Builds an attribute table for a point, line, or polygon theme.
BUILDVAT
• Builds a value attribute table for an integer grid theme.
BUILDSTA
• Builds a statistics table for a grid theme.


Lecture: Nimesh Dagur

MapInfo
Exercise and practical

Info Professional is a powerful Microsoft Windows–based mapping and geographic analysis
application. Designed to easily visualise the relationships between data and geography.

MapInfo Professional expands location intelligence:




Example Maps
   • Discover trends hidden in spreadsheets and charts
   • Gain new understanding of your customers and markets

                                               55
   •   Perform powerful data analysis and calculations
   •   Create custom maps and content for analysis

Use geographic insights to innovate business processes
   • Manage location-based assets, people and property
   • Optimize service and sales territories for greater efficiencies
   • Deploy networks, infrastructure and utilities with confidence
   • Map resources, plan logistics and prepare for emergencies
Works and plays well with existing IT infrastructure
   • Designed and tested with Windows operating systems
   • Imports and exports data in a wide variety of formats
   • Easily customized to meet your specific needs

Data access
MapInfo Professional provides built-in support to access and view a variety of data formats
directly. This means you will be able to view your Microsoft Excel, Microsoft Access or database
data, such as Oracle, Microsoft SQL Server as well as many other file formats, directly out of the
box. You can also view images of virtually any format. This capability ensures that MapInfo
Professional will fit into your current IT structure directly with no additional cost.

Data creation & editing
MapInfo Professional provides many CAD data creation and editing tools as well as the ability to
edit your tabular data such as values and names. This means you don’t have to switch between
applications. Make all your changes for maps and data in one application and save time and
effort.




                                               56
Display




Thematic Map
Map display options are one of the great strengths of MapInfo Professional. You can instantly
shade/change style or mark territories (using any symbol, graduated symbols, charts
or graphs), boundaries, highways, fiber lines or points based on any tabular data values through a
simple wizard. You can also aggregate values using statistical or any math functions to associate
a symbol or a color to a point or a region based on a calculated value. For example, shade the
sales territories based on number of customers. Trends based on geography reveal themselves,
patterns become clear and better decisions with impact are imminent.

Data & map publishing
Sharing your results in industry formats is often as critical as the information itself. In today's IT
environment, the need to have multiple publishing options is critical to meaningful
communication between applications. MapInfo Professional provides a spectrum of options for
this purpose. From the ability to export data to any format, to publishing large maps with legends
and charts, MapInfo Professional seamlessly integrates across applications. In addition, MapInfo
Professional is Web-enabled. Publish static or interactive maps through easy-to-use wizards.
Share the results in a format that best fits your needs.



                                                 57
Specifications
Supported Operating Systems:
   • Windows® 7
   • Windows® Vista
   • Windows® XP
   • Windows® 2008 Server
   • Windows® 2008 Server with Citrix® XenApp
Supported Databases:
XY – i.e. Databases that store point data as X & Y numeric columns:
   • Microsoft Access 2003 & 2007
   • Microsoft SQL Server 2005/2008
   • Microsoft SQL Server 2008 XY on a spatialized DB
   • Oracle Spatial 11G, 10Gr2 (10.2.0.3)
   • PostgreSQL 8.3 with PostGIS 1.3
Spatial – Databases that store map data as objects including: points lines and regions
   • SQL Server 2005 with SpatialWare 4.9
   • SQL Server 2008 (also called SQL Server Spatial)
   • SQL Server 2008 (also called SQL Server Spatial) with SpatialWare 4.9.2
   • Oracle Spatial 11G, 10Gr2
   • PostgreSQL 8.3 with PostGIS 1.3
MS Office Data Types:
   • MS Office 2003 – MS Excel (.XLS) & MS Access (.MDB)
   • MS Office 2007 – MS Excel (.XLSX) and MS Access (.MCCDB)


   Week 6: 21st – 25th February 2011

Lecture: Nimesh Dagur
Application GIS - RDBMS (SQL) – Oracle 9i
Exercises/Practical

SQL Overview covered
Oracle Database uses the SQL (Structured Query Language) database language to store and
retrieve data. It includes the following categories of SQL statements:
DDL (Data Definition Language)
Used to create, alter, or drop database objects, such as schemas, tables, columns, views, and
sequences. For example, statements that use the commands,ALTER, CREATE, DROP, GRANT,
and REVOKE.
DML (Data Manipulation Language)
Used to query and manipulate data in existing schema objects. For example, statements that use
the commands, SELECT, INSERT, UPDATE, and DELETE.
TCL (Transaction Control Language)
These statements manage changes made in DML statements. For example, statements that use
the commands, COMMIT, ROLLBACK, and SAVEPOINT.

                                             58
Pseudocolumns
Values generated from commands that behave like columns of a table but are not actually stored
in the table. Oracle Database supports the LEVEL and ROWNUM pseudo columns.
Functions
Operate on data to transform or aggregate it. For example, TO_DATE to transform a date column
into a particular format, and SUM to total all values for a column.

Lecture: Nimesh Dagur
Introduction to Programming using Visual Studio 2005
Exercise/Practical

   •   Visual Basic .NET (VB.NET) is an object-oriented computer language that can be
       viewed as an evolution of Microsoft's Visual Basic (VB) implemented on the Microsoft
       .NET framework.
   •   A programme is an organized list of instructions that, when executed, causes the
       computer to behave in a predetermined manner. Without programs, computers are
       useless.
   •   A programming language is a language used to write computer programs, which involve
       a computer performing some kind of computation or algorithm and possibly control
       external devices such as printers, robots and so on.
   •   Programming languages differ from natural languages in that natural languages are only
       used for interaction between people, while programming languages also allow humans to
       communicate instructions to machines
   •   programming languages differ from most other forms of human expression in that they
       require a greater degree of precision and completeness.


Types of programming Languages




   •   Microsoft .NET (pronounced "dot net") is a software component that runs on the
       Windows operating system.
                                             59
   •    .NET provides tools and libraries that enable developers to create Windows software
       much faster and easier.
   •   .NET benefits end-users by providing applications of higher capability, quality and
       security


   Week 7: 28th February – 5th March 2011

Lecture: Nimesh Dagur
Loop, Object Oriented Concepts
Exercise/Practical
Accessing Databases

Accessing Databases

   •  Visual Basic 2005 applications often manipulate data that come from relational databases.
      To do this, your application needs to interface with relational database software such as
      Microsoft Access, Microsoft SQL Server, Oracle, or Sybase.
   • Basically, a database consists of one or more large complex files that store data in a
      structured format.
   • The database engine, in your case Microsoft Access, manages the file or files and the data
      within those files.
Microsoft Access Objects
   • A Microsoft Access database file, which has an extension of mdb, contains tables,
      queries, forms, reports, pages, macros, and modules, which are referred to as database
      objects.
   • Tables: A table contains a collection of data, which is represented by one or more
      columns and one or more rows of data. Columns are typically referred to as fields in
      Microsoft Access, and the rows are referred to as records.
   • Each field in a table represents an attribute of the data stored in that table
   • A record in a table contains a collection of fields that form a complete set of attributes of
      one instance of the data stored in that table.
Connections, Data adapters, and Datasets:
   • VB 2005 uses ADO.NET as primary tool for data access and data manipulation.
   • For accessing a database we should have a connection to the database which requires
      creating a connection object.
   • A connection object contains a connection string that stores the name of data
      provider,name of database, user name and password for connecting to the database.
   • A data provider is used for establishing a connection with the database,accessing data
      from the database, and executing the command for data retrieval and data manipulation.

   •   A Data Adapter object works like a interface between a data source (database) and a
       dataset.
   •   A dataset can be termed as a logical connection of data.
   •   A dataset object follows a disconnected architecture it means it establishes a connection
       with the database ,retrieves the data, and then closes the connection with the database

                                               60
   •   Data contained in the dataset can be displayed in any data display controls such as data
       grid view, comboBox, or textbox etc.


Developing Application for Web Based GIS – the following software was used for this lecture,
MapGuide, Microsoft Visual Basic 2005,
Web GIS             MapGuide Studio (AutoDesk)
Desktop GIS         MapWindowGIS

MapWindowGIS and MapGuide studio (MapGuide Mastro) are SDK tools used for the
development in dot Net, VB.Net and C#. The RDBMS used are SQL Server, MySQl,
PostgreSQL and Oracle. MapGuide Studio is used for building maps that can be published on the
web.


   Week 8: 7th – 11th March 2011

Lecturer: Amjad Khan
Developing Application for Web Based GIS (continuation from week 7)
Tasks: How to fill colour of line, polygon; Find, query, theme
MapGuide and WebGIS
Exercise/Practical


Lecture: Amjad Khan
MapGuide and WebGIS
Exercise/Practical

MapGuide is a software platform for distributing spatial data over the Internet or on an intranet.
There are two versions of The MapGuide: MapGuide Open Source, and Autodesk MapGuide
Enterprise.

The collection of servers that process requests in MapGuide is called a site. You can divide the
processing load between two or more servers within the site. Each site shares a single resource
repository among its servers. The resource repository stores the resources that map authors use
to create maps, for example, pre-defined layers for features such as roads or land parcels. In the
diagram on the facing page, the site contains two servers, one of which is designated as the site
server. The site server contains the resource repository. It also connects to any database server or
servers. MapGuide Server provides seven services: Site, Resource, Drawing, Feature, Mapping,
Rendering, and Tile. If you are using a single server, that server performs all of these services. In
any case, the site server always runs the first two services, because they handle data access and
manage the resources for the site. However, if you have two or more servers, you can split off
the other services and allocate them to another server or servers. For example, the Mapping and
Rendering services are the most processor-intensive operations and can benefit from having a
dedicated server to handle them.


                                                 61
   •   The Mapping service creates the view of a map in response to requests from the clients.
   •   The Rendering service creates the final map image for the AJAX viewer from input
       provided by the Mapping service.

Lecture: Nimesh Dagur
Use of MapObjects and Microsoft Visual Studio .NET to build a simple mapping
application using the Visual Basic (VB) language
Exercise/Practical

The following was learnt under this topic:
   • Create a new Windows application in Visual Studio .NET, using toolbars and other
       controls standard in .NET.
   • Add vector and raster data to a map, and perform queries on the map data you added.
   • Control panning and zooming, display map layers based on scale
   • Draw simple graphics, and also dynamically display data.

MapObjects
• MapObjects is the mapping component software created by Environmental Systems Research
  Institute, Inc. (ESRI), to allow mapping functions to be included in applications developed in
  a variety of programming environments.
• MapObjects software is a set of mapping software components that lets you, the programmer,
  add dynamic mapping and geographic information system (GIS) capabilities to existing
  Windows applications or to build custom mapping and GIS solutions.
• MapObjects applications can be developed in any 32-bit programming environment that fully
  supports ActiveX,
• MapObjects comprises an ActiveX control called the Map control and a set of 46 ActiveX
  automation objects. It is for use in industry-standard programming environments such as
  Visual Basic, Visual C++, Delphi, PowerBuilder, and Visual Basic for Applications (VBA).
• ActiveX controls were originally called Object Linking and Embedding (OLE) controls
• An ActiveX automation control is a software component that lets you add specific
  functionality within an application that is an ActiveX container
• MapObjects is not for end users. It is strictly for people who are developing applications. As
  a developer, you can build applications based on MapObjects and deliver those programs to
  end users.

Loading MapObjects
• Once you’ve successfully installed MapObjects, the next step is to load MapObjects into a
   Visual Basic.NET project.

Adding a map control
• You can add one or more Map controls to any Visual Basic .NET form.

Adding a layer
• You can add layers to your map through the Map control’s Property Pages or by writing code.
• MapObjects has two kinds of layers: MapLayers, which display vector data, and
   ImageLayers, which display raster data.

                                              62
•   You will not see any map layers drawn in the Map control at design time. When you run your
    project (press F5), you’ll see the map layers displayed at their full extent.
•   If you don’t specify MapObjects symbol properties, such as color, size, and style, default
    symbol properties will be assigned for you.

Data sources for MapObjects
• Shapefiles: A shapefile is an ESRI data file format for storing geographic features in vector
   format. The shapefile format has represented map features by x,y coordinates
• ARC/INFO coverages: ARC/INFO coverages are topological data structures that store
   vector format geographic features. A coverage is stored as a directory because instead of a
   single file, a coverage is actually composed of a set of files, each of which contains
   information about a particular feature class (point, line, polygon, etc.).
• Spatial Database Engine(SDE) layers: A geographic feature in SDE consists of attributes
   and a geometric shape—point, line, or area. SDE stores geometric shapes as x,y coordinates.
   Points are recorded as a single x,y coordinate pair, lines as a series of ordered x,y
   coordinates, and areas as a series of x,y coordinates defining a set of line segments that have
   the same starting and ending point.


    Industrial visit

Two companies were visited and they are indicated below:

RAMTech Cooperation
Industrial excursion to RAMTech Cooperation involved in GIS and Remote Sensing. The
Company uses open source software and their front-end was developed using ASP.Net and PHP.
The Relational Database Management System (RDBMS) and other software they use are
PostgreSQL, PostGIS, MapServer, Google Map as base layer, open layer, ASP.Net, ArcGIS
Desktop 9.3 and GeoJSON (GeoJSON – JSON Geometry and feature description). RAMTech
Cooperation also uses Modeling to easy the computation and implementation of the project

MapMyIndia
www.mapmyindia.com
India’s best maps and GPS NAVI-TAINMENT experience
CE Info Systems (P) Ltd., a New Delhi-based ISO 9001-2000 Company founded in 1992, is
India's leader in premium quality digital map data and consumer navigation services. Since 1994,
through continuous field surveys and state-of-the-art mapping technology, the company has built
its proprietary MapmyIndia Maps, the most comprehensive, accurate, robust and reliable
navigable map dataset for all India. MapmyIndia is driving the Indian navigation industry by
providing internet, mobile and in-car navigation products to end consumers directly as well as in
partnership with leading international and national players.
The company has been providing GIS based enterprise solutions to over 500 leading corporate
and government organizations in every vertical. In 2004, MapmyIndia was short listed by
NASSCOM as a showcase company for IT innovation in India. Most recently, MapmyIndia's
Managing Director was elected by GPS Business News as the "World's GPS Businessman for
the year 2007" for driving the navigation industry in India.

                                               63
   Conclusion

The programme had 28 participants from 21 countries and only one participant from Zambia.
The courses sponsored by the Indian Government accept two participants from participating
countries. The programme run for 8 weeks.

The skills and knowledge gained will assist the Ministry of Agriculture and Cooperatives
(Department of Agriculture) in setting up the GIS laboratory and in development applications to
be use in GIS and Remote Sensing.

The need for information arises at all levels, from that of senior decision makers at the national
and international levels to the grass-roots and individual levels. Therefore the generation of the
base map and attachments of attributes not only help the administration but also to other
government and non-government organizations providing multiple usage of onetime effort. The
use of the front-end tool will help in improving the revenues as well as the services benefiting
time and economy.




                                               64
   APPENDICES



   Appendix 1: Course layout


Objectives
   • The purpose of the programme is to introduce to the participants about Geographic
       Information System & Remote Sensing concepts.
   • Contents Of The Course:
   • GIS
           o Fundamentals of GIS, Application GIS, Advance GIS, GIS Analysis, Application
              GIS Development using Map Objects.
   • Remote Sensing:
           o Concepts Of Remote Sensing, Principles of Remote sensing, Digital Image
              Processing Using ERDAS Imagine
   • Specialization Through Project Work

Scope of the course
At the end of the course, Students will be able:
    • To understand the GIS & Remote Sensing concepts.
    • To understand information relating to integration of GIS, Remote Sensing and
        Application software development.
    • To understand about Development of GIS Applications using Client/Server Architecture

Course Content

1. Fundamentals of GIS
    • Introduction to GIS
    • Mapping and GIS
    • Digital Representation of Geographic Data
    • Vector Based GIS
    • Thematic map Preparation
    • GIS Analysis

2. Application GIS
    • Non Spatial Database
    • Client server GIS

3. Advance GIS
    • Spatial Analysis and Modeling using ArcGIS
    • GIS Implementation and Project Management

                                             i
4. Concepts of Remote Sensing
    • Introduction to Remote Sensing (Optical, Thermal & Microwave)
    • Data acquisition (aircrafts and satellites)
    • Integration of GIS and Remote sensing

5. Principles of remote sensing
    • Multispectral Remote sensing (multispectral scanners: whiskbroom and push broom)
    • Hyper spectral Remote Sensing
       Analysis and interpretation of visual and digital remote sensing data

6. Digital Image Processing Using ERDAS Imagine (applications of remote sensing in land use
    \ land Cover)
    • Pre-processing corrections: Radiometric correction Geometric aspects
    • Introduction to DIP
    • Image Rectification and Restoration
    • Indices and Rationing
    • Image Classification
    • Post Classification Smoothing
    • Change Detection Analysis

7. Application Development Tools
    • VB.Net
    • ORACLE 9i
    • SQL

8. GIS Analysis
    • AutoCAD MAP
    • MAP Info
    • Arc View and Arc GIS

9. Non Spatial Database
    • Database Concepts
    • Relation between different tables
    • Linking of External non spatial database Geo Database.

10. APPLICATION GIS Development
    • Client/Server GIS using Oracle, VB.Net and Map Objects.
Project




                                             ii
    Appendix 2: list of Participants



       SPECIALIZED PROGRAMME ON APLICATION DEVELOPMENT
                                                                                CENTRE FOR DEVELOPMENT OF ADVANCED
       USING GIS & REMOTE SENSING- PARTICIPANTS. January-march
                                                                                      COMPUTING , NOIDA, INDIA.
                               2011


         COUNTRY              NAME                                       EMAIL                         FACEBOOK                    SKYPE
1     CUBA              Yoenis Pantoja      ypantojaz@uci.cu                yoenis.pantoja@gmail.com   Yoenis Pantoja Zaldivar
2     SOUTH AFRICA      Yashveer Ranchhod   yashman18@gmail.com                                        Yashveer Ranchhod           yashman18
      MAURITIUS
3     ISLAND            Devendra Ramjee     ramjeesona@hotmail.com                                                                 sonakum70
      MAURITIUS
4     ISLAND            Hembal Teckmun      hitecsatyam@yahoo.com
                        Elkym Alexander                                                                Elkym Alexander Mesa
5     COLOMBIA          Mesa Sanchez        ingelkym11@yahoo.es                                        Sanchez
                        Javier Manrique
6     COLOMBIA          Sanabria            javier.manrique.s@gmail.com                                Javier Manrique Sanabria
                        Gerson Solis
7     GUATEMALA         Gutierrez           gersao.g@gmail.com                                         Gerson Solis Gutierrez
8     PALESTINE         Jasim Asnaf         jrimawi@gmail.com                jrimawi@hotmail.com       jrimawi@gmail.com           jrimawi
                        Shakhnoza
9     UZBEKISTAN        Rakhmonkulova       rshakhnoza@yahoo.com             rshakhnoza@gmail.com      Shakhnoza Rakhmonkulova
                        Jacq
10    MADAGASCAR        RAMAROLAHY          quelin.ramarolahy@gmail.com                                Jacq RAMAROLAHY             jacq_man
      TRINIDAD AND
11    TOBAGO            Kevon Rose          rosekevon@hotmail.com                                      rosekevon@hotmail.com
      TRINIDAD AND
12    TOBAGO            Kevon Peters        kevonp@gmail.com                                           kevonp@gmail.com
13    MYANMAR           Mya Thandar Kyu     myathandarkyu@gmail.com                                    myathandarkyu@gmail.com
14    GRANADIAN         Fabian Purcell      fabpurcell@gmail.com
15    ANGOLA            Maria Helena Loa    marialoa2004@yahoo.com.br                                  marialoa2004@yahoo.com.br
                        Julius Francis
16    TANZANIA          Mpombo              kayoghas05@yahoo.com             mpombo@ifm.ac.tz
17    TUNISIA           Ouali Bechir        ouali.bechir@laposte.net

                                                                       iii
18   TUNISIA          Mehrez Mhamdi    mehrez.mhamdi@yahoo.fr
                      Charles Bwalya
19   ZAMBIA           Chisanga         cbchisanga@gmail.com                                                           cbchisanga
                      Norman Francis
20   UGANDA           Ntalo            normanntalo@yahoo.com
21   LAO              Bounmany Joh     bounmany_joh@hotmail.com
22   NEPAL            Sanjit Pradhan   sanjit_21576@hotmail.com                            sanjit_21576@hotmail.com
     PNG -Papua New
23   Guinea           Gregory John     gregoryjohn91@yahoo.com
24   AFGHANISTAN      Habib Rahman     habibrhr@yahoo.com
25   AFGHANISTAN      Qamar Zarifi     wafahamid_001@yahoo.com
                      Dad Mohammad
26   AFGHANISTAN      Hamid Zarifi     wafahamid_001@yahoo.com
27   AFGHANISTAN      Mirwaislatif     mirwaislatif@yahoo.com
                      Sudan Hassam
28   SUDAN            Mohammed         hasbayan@gmail.com          has_bayan@hotmail.com




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