GEOG 483 Project 2
Manipulating Attribute data to create a Thematic
Troy M. Snoke
Without a means of smartly viewing data, the information is lost in the numbers. Project
two required us to extract the intelligence from tables and shapefiles, and display the data
into a simple to read map. A data set of Oklahoma tornados from May 3rd 1999 was
provided as raw data. The complexity of the project started with the commonizing of the
projection and datum. The raw shapefiles had no projection and required the NAD 83
Stateplane Oklahoma FIP 3501 (feet) North coordinate system. To make database tables
intelligent, a common data attribute or “key” is needed to tie the databases together. As a
field collector and as an analyst this is the most important point to make the “key”. Time
is easiest data point key to collect and tie data together. An example is the Navy collects
seawater conductivity, temperature and time data from one sensor on a ship. And another
shipboard sensor collects GPS position and time. The two data sets can be married at a
later point into a single dataset using a relationship. This importance of the common key
makes collected GIS data smart data.
The criteria for completion of the project required the generation of five maps for the raw
database tables. The database tables lacked the fidelity of the required output but did
contain data that could be queried and extracted to display the required information. All
maps were created with ESRI ARCMAP 9.2.
The first thematic map is a map displaying the property damage. A single attribute
containing damages could not been found in the data sets but the databases contained
property damages delineated by type of dwelling and either damaged or destroyed. A
simple summing of the fields into a new field produced the results displayed in figure 1.
Counties with property damage
Map is color-coded with the 17 counties that received damage also the F scale or Fujita
scale is displayed depicting the tornado intensity as well as the path the tornadoes. (King,
Property destroyed (in numbers) Map
This map required the creation of a new attribute that is the sum of all types of dwelling
that are conceded a total loss or destroyed. Figure 2 displays the number of properties
destroyed by the May 3 1999 tornado.
Total number of properties destroyed by county
Property destroyed (in dollars) Map
Figure 3 is a thematic map displaying cost of property-destroyed that each counties that
received. A new attribute was created and populated with the summing of the total
values (in dollars) of all dwellings.
Property destroyed (in dollars) by County
Housing units density Map
Figure 4 displays the density as defined by the total dwelling types: single family, mobile
home, and apartments, divided by the area per county (in square miles). The intensity or
F scale is displayed to detail the path is each tornado.
Housing density (in units per square miles)
Housing density by Census data Map
Figure 5 shows the effects of the tornadoes displayed by 2000 Census counts. The
density is not bound by the county and depicts a more real life display of dispersion of
population. A relationship was established between two data sets with a key of the FIPS
(Federal Information Processing Standards) codes and tract data. (Census data 2007)
Census Population Density
As the GIS analyst you need to know how to display the data for the intended effect.
This final product drives the collection and data mining. All three phases of the analyst
are interlaced and must contain overlap in order to be relevant. Without this overlap the
data cannot be harvested for other products, this is the beauty of GIS, data only requires
one field to match to create a relationship.
King, Beth (2007). Geography 483, Lesson 2 The Pennsylvania State University World
Campus Certificate Program in GIS. Accessed October 21, 2007.
U.S. Census Bureau (2007)
http://www.esri.com/data/download/census2000_tigerline/index.html. Accessed October