Spatial Databases Data Collection by mercy2beans108

VIEWS: 7 PAGES: 27

									Spatial Databases:
Data Collection

Spring, 2007
Ki-Joune Li
     PNU                                           STEM



    Why Data Collection?

   The cheapest way to build spatial DB
        Get existing databases, but
        Check if the requirements be satisfied
              Metadata: Description of Data


        Data Migration vs. Interoperability

   Legacy Problem
        Building an Information System
              No more entirely new system
              Integration with Existing systems
        Integration with existing DB

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     PNU                                                                STEM



    Integration with Existing Databases

   Data Migration
        Copy from existing DB

                              Existing System         New System



                                                   Copy from
                                Existing DB                    New DB
                                                   Legacy DB



                              Legacy System           New System

        Procedure
              Survey on existing DB: Data Clearinghouse
              Metadata
              Conversion from existing databases
              Integration of several databases: Mismatch Problem
                                                                               3
     PNU                                                                 STEM



    Geo-Data Clearinghouse

   Geo-Data Clearinghouse
        Clearinghouse: financial services company that provides
         clearing and settlement services for financial transactions.
         (in Wikipedia.com)
        Collection of Geospatial Data Servers
              Collection of metadata Not data itself.
              Providing a single interface to browse metadata of several servers
        Z39.50 protocol and client


   Example: FGDC in USA
        (http://clearinghouse1.fgdc.gov/)


                                                                                    4
 PNU                                                                              STEM



Metadata for Geospatial Data: ISO 19115

 • Title, and Alternative title, Originator, Abstract, and Data
 • Frequency of update
 • Presentation type
 • Access constraint, Use constraints
 • Topic category
 • Bounding coordinates, and extent
 • Spatial reference system, and resolution
 • Supply media, and data format
 • Supplier and Additional information source
 • Date of update of metadata
 • Sample of the dataset
 • Dataset reference date, and language
 • Vertical extent information
 • Spatial representation type
 • Lineage                                                Some items are mandatory and
 • Online resource                                             others are optional

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     PNU                                                           STEM



    Generalization: Conversion of spatial data

   Conversion from
        Large-Scale Spatial DB to Small-Scale Spatial DB
        Cartographic Aspect vs. DB Aspect
              Cartographic viewpoint: To make maps more visible
              DB viewpoint: To reduce the size of data


   Six Generalization Operators
        Simplification
        Elimination
        Translation (Cartographic Purpose)
        Aggregation
        Collapse
        Exaggeration (Cartographic Purpose)
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     PNU                                                 STEM



    Simplification

   Simplification (Line Simplification)
        Elimination of internal nodes from a polyline
        To minimize the loss of accuracy
        Example: which point to remove




   Douglas-Peucker Algorithm
        A greedy algorithm

                                                                7
     PNU                                                                   STEM



    Elimination

   Eliminate spatial objects not satisfying given conditions
        Example
              Eliminate *
               From Buildings
               Where area < 100 m2


   Propagation of Elimination
        Elimination may destroy cardinality condition
        Example: What to do in this case ?

                                           1..1
                                District                 District_Office
                                                  1..1



                                                                                  8
     PNU                                                           STEM



    Aggregation

   Aggregate a set of spatial objects into a large object
                                          B
                               A                   Aggregation
                                                    - With Boundary
                                       Apartment
                                                    - Without Boundary
                                   C
                                        Complex




        Definition of the boundary of aggregated object ?


   Aggregation of Non-Spatial Data
        Example: Number of Habitants in the apartment complex
        Sum, Max, or Average
                                                                          9
     PNU                                                              STEM



    Collapse

   Reduction of Dimensionality
        From 2-D to 1-D (from surface to line)
        From 2-D to 0-D (from surface to point)
        Very Rarely from 1-D to 0-D


   Example



           Surface in 1/1,000 Map              Line in 1/50,000 Map


   Computation of collapsed objects
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     PNU                                                           STEM



    Topological Issues in Generalization

   Example
                            Left Side




                                                         Right Side
                                                    Topologically Incorrect
   How to Correct it
        No drop vertex if  Topological Inconsistency
        Translation of the object with problem




                                                                           11
     PNU                                                                 STEM



    Topological Issues in Generalization

   Another Example


                                                 A
              A                                      B
                        Collapse to point
                   B
                                                  A contains B
       B contains A                          A is equal to B at least


                  R(B, A)  RG(B, A)

              What is the correct topology after the collapse ?




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     PNU                                                                  STEM



    Topological Issues in Generalization

   Another Example

                    Road
                                                               Road
       Buildings        A
                                                   Buildings      A
            B1              B2

            B3              B4       Aggregation
                                                       B



           R(B, A)= Disjoint                           R(B, A)= Overlap

                    R(B, A)  RG(B, A)
                   Is it correct ?



                                                                                 13
     PNU                                                           STEM



    Mismatch Problems

   Mismatches
        Integration of several databases from different sources
        Adjacent Maps
              Different Accuracy
              Different Dates of Creation
        Different Maps
              Different Ground Control Points
              Different Accuracy
              Etc.




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     PNU                                      STEM



    Example: Topographic Map and Cadastral Map

   Example


                                      Topographic Map




      Cadastral Map




                                                        15
 PNU                                                            STEM



Example


                                     Find the nearest manhole
                                     or pole to Building P




       Building DBA   Manhole DBB   Pole DBC



                                                                       16
 PNU                                                              STEM



Example


                                       Find the nearest manhole
                                       or pole to Building P
                A

                     B




       Building DB       Manhole DB   Pole DB



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   PNU                                                                 STEM



Example


result of the query                         Find the nearest manhole
                                            or pole to Building P
                      A

                          B




         Building DB          Manhole DB   Pole DB




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   PNU                                                                    STEM



Example


result of the query

                      A
                                           adjust the building position
                          B
    the correct answer




         Building DB          Manhole DB   Pole DB




                                                                                 19
 PNU                                                              STEM



Example


result of the query                    Find the nearest manhole
                                       or pole to Building P




               the correct answer




       Building DB       Manhole DB   Pole DB




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     PNU                                                   STEM



    Elastic Map Transformation: Rubber Sheeting

   Elastic transformation of objects in each spatial
    database.

             Spatial Query
                                                   Consistent Spatial
                                                          Databases


                             Transformed   Transformed
               Building DB   Manhole DB      Pole DB


     Reference Spatial
     DB
     or Base Map             Manhole DB      Pole DB
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  PNU                                                                      STEM

Elastic Map Transformation
by Delaunay Triangulation

Procedure
1. Select sets of Control Point Pair on MapRef and another MapA, respectively.
2. Delaunay Triangulation with Control Points on MapRef.
3. Triangular Transformation, for each Point p on MapA.

                       Corresponding Pair of Triangles




        MapRef           Control Points on the Reference Map            MapA

                         Corresponding Control Points on
                         Other Maps
                                                                                  22
 PNU                                                                                   STEM



Triangular Transformation

       q1(u1, v2 )                                          p1(x1,y2 )
                     q (u, v )

                                                                    p (x, y )
                                 q3(u3, v3 )
 q2(u2, v2 )
                                                   p2(x2, y2 )           p3(x3, y3 )
            Triangle on MapRef

               (u,v) = (a1u1+a2u2+a3u3, a1v1+a2v2+a3v3)

               where     a1 = b {(y2 – y3)x + (x3 – x2)y + x2 y3 – x3 y2 }
                         a2 = b {(y3 – y1)x + (x1 – x3)y + x3 y1 – x1 y3 }
                         a3 = b {(y1 – y2)x + (x2 – x1)y + x1 y2 – x2 y1 }
                         b = (x1 y2 + x2 y3 + x3 y1 – (x2 y1 + x3 y2 + x1 y3 ))-1


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 PNU                               STEM



Elastic Map Transformation : Example




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 PNU                               STEM



Elastic Map Transformation : Example




Control Points




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     PNU                                           STEM



    Mismatched between Adjacent Maps

   Examples
                                           Shift




               Discontinuity


                           Disappearance



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     PNU                                                            STEM



    Edge Matching

   Rules                                            Pivot Object
        Priority on More Recent Data
        Respect of Pivot Objects
        Respect of Predefined Constraints
              e.g. Building should be rectangular




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