Project 2: Manipulating and Summarizing Attribute Data
Sachin Chand
The goal of project two is to provide visual displays that illustrate the damage caused by tornadoes in Oklahoma on May 3rd, 1999. Seventeen counties in Central Oklahoma were affected by the tornadoes. We begin by adjusting projection information for our data and learn the difference between the "define projection" and the "project tool". The difference being that define projection does not alter the coordinates of the data. Instead, it identifies a coordinate system with the data. The project tool on the other hand actually changes the coordinates of the data to a projected coordinate system. Next we learn the process of joins and relates. We use joins to add additional information to our feature data by joining the feature attribute tables to a secondary table based on the common values of a field in each table. We learn to add fields to tables and populate these fields using values from existing populated fields(housing density based on the housing units field divided by the square mile field) or calculating new data (area) using the calculate geometry tool. Using the projected data and the field values we've calculated, we are able to produce the thematic maps below that illustrate the damage caused by the tornadoes. Additionally, we use census tract data to produce a population density map. To accomplish this, we join table "demography" to the census tract attribute table. We do this because the census tract attributes do not have population density or population attributes. It does have area information(sq. miles). We create and calculate a new population density field that is a value of population (from the demography table) / sq. mile (from the census tract attribute table). As might be expected, this maps show the highest population densities in areas which received the most damage from the tornadoes.
Figure 1. Housing density for the 17 Central Oklahoma Counties affected by Tornadoes in May of 1999. The County with the highest density is Oklahoma County, shown in the darkest shaded color of the color ramp. Created in ESRI ArcMap 9.2. NAD 1983 StatePlane Oklahoma North Fips 3501 (Feet).
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Figure 2. Total number of properties damaged in the 17 Central Oklahoma Counties affected by Tornadoes in May of 1999. The County with the most number of properties damaged is Oklahoma. This is consistent with figure 1 that shows Oklahoma County also having the highest housing density. Created in ESRI ArcMap 9.2. NAD 1983 StatePlane Oklahoma North Fips 3501 (Feet).
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Figure 3. Total number of properties destroyed in the 17 Central Oklahoma Counties affected by Tornadoes in May of 1999. Oklahoma County, shaded in the darkest color of the color ramp, shows the highest number of properties destroyed. Created in ESRI ArcMap 9.2. NAD 1983 StatePlane Oklahoma North Fips 3501 (Feet).
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Figure 4. Total dollar value of properties destroyed in the 17 Central Oklahoma Counties affected by Tornadoes in May of 1999. Oklahoma County shows the highest dollar amount of properties destroyed. This is consistent with figure 3 showing number of properties destroyed. We can see a correlation between number of properties destroyed and dollar value of properties destroyed. Created in ESRI ArcMap 9.2. NAD 1983 StatePlane Oklahoma North Fips 3501 (Feet).
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Figure 5. Total dollar value per squarel mile of property destroyed by the Tornadoes of May, 1999 in 17 Central Oklahoma Counties. This map closely resembles figure 4 which shows the total dollar values, not the total dollar values per square mile. This thematic map is based on a short integer field that was added and calculated by dividing the dollar amount field by the square mileage field. Created in ESRI ArcMap 9.2. NAD 1983 StatePlane Oklahoma North Fips 3501 (Feet).
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Figure 6. Housing density per Census Tract in the 17 Central Oklahoma Counties affected by Tornadoes in May of 1999. The Census Tracts in Oklahoma County stand out to the viewer as having the highest population densities. While level 4 and 5 tornadoes left longer gound trails in other counties, Oklahoma County incurred the highest damage and destruction. By viewing the maps, we might deduce that one reason for this was Oklahoma County had the highest population and housing densities. Created in ESRI ArcMap 9.2. NAD 1983 StatePlane Oklahoma North Fips 3501 (Feet).
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Figure 7. Inset map of Oklahoma County Census Tracts. This County had the highest population and housing density. Not surprisingly, it also sustained the highest damage and destruction by the tornadoes. This inset map gives a more intimate perspective of the densely (relatively) populated census tracts. Created in ESRI ArcMap 9.2. NAD 1983 StatePlane Oklahoma North Fips 3501 (Feet).
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