1. GIS Tutorial 1
Lecture 9
Spatial Analysis

2. Outline Proximity buffers Site suitability example Basic apportionment
Advanced apportionment
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3. Lecture 9
Proximity buffers
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4. Proximity buffers Points Lines
Circular buffers with user supplied radius
Lines
Looks like worm based on line feature
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5. Proximity buffers Polygons
Extends polygons outward and rounds off corners
Created by assigning a buffer distance around polygon
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6. Point buffer example Polluting company buffers Added schools
Added population
Data from U.S. Census and EPA website
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7. Point buffer example Crimes near schools 7
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8. Line buffer example Businesses within .25 miles of a selected street
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9. Select features in buffer
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10. Spatial join to count Join business points to buffer polygon 10
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11. Polygon buffer example
Parcels within 150′ of selected property
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12. Select features in buffer
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13. Polygon buffer example
River buffer to analyze environmental conditions, flooding, etc.
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14. Lecture 9
SITE Suitability
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15. Locate new police station
Criteria
Must be centrally located in each car beat (within a 0.33-mile radius buffer of car beat centroids)
Must be in retail/commercial areas (within 0.10 mile of at least one retail business)
Must be within 0.05 mile of major streets
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16. Starting map
Lake Precinct of the Rochester, New York, Police Department
Police car beats
Retail business points
Street centerlines
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17. Create car beat centroids
XY centroids for police beats
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18. Buffer car beat centroids
.33 mile buffer
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19. Buffer retail businesses
0.1 mile buffer
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20. Select major streets Select by attribute 20
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21. Buffer major streets 0.05 mile buffer 21
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22. Intersect buffers Can only intersect two at a time
Car beat and businesses
Streets
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23. Site suitability result
Map showing possible sites for police station
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24. Lecture 9
Basic apportionment
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25. Apportionment example
Population by voting district
You want to know the population of a voting district but only have census tracts
Voting districts and census tracts are not contiguous
Approximate the population of voting using census tracts and blocks
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26. Population by voting district
Start with census tracts
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27. Population by voting district
Overlay voting districts (not contiguous with tracts)
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28. Population by voting district
Better to use block centroids for population
Smaller than tracts
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29. Spatially join centriods
Join centroids to voting districts
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30. Other simple apportionments
Population by
Neighborhoods
Zip Codes
Historic sites
Others?
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31. Census data to apportion
Short form SF1 data (tract, block group, block)
Population
Age
Race
Housing Units
Others?
Long form SF3 data (tract and block group)
Educational attainment
Income
Poverty status
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32. Advanced apportionment
Lecture 9
Advanced apportionment
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33. Advanced Apportionment
Chapter 9 example
Police want to know the number of under-educated persons in their car beats
Under-educated data is located SF3 tables, census tracts or block groups (not car beat polygons)
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34. Data to apportion Car beats Census tracts Beats and tracts
Not contiguous
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35. Beats and tracts zoomed
Tracts clearly cut across beats
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36. Tract attribute table Tracts contain undereducated data
No high school degree
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37. Math of apportionment
Simple census data (e.g. population) is not a problem
Can use block centroids
Problem
Block centroids don’t contain undereducated population
Tracts contain this information
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38. Math of apportionment Tract 360550002100 Car beats 261 and 251
Let’s take a look at one example. Above is a close-up of tract , which is split between car beats 261 and 251. Tract has 205 people aged 25 or older with less than a high school education. For short, let’s call this the undereducated population. How can we divide those 205 undereducated persons between car beats 261 and 251?
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39. Math of apportionment One approach
Assume that the target population is uniformly distributed across the tract
You could split undereducated population up by the fraction of the area of the tract in each car beat
What if, however, the tract has a cemetery, park, or other unoccupied areas? Then the apportionment could have sizable errors
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40. Math of apportionment A better approach
Use a block-level, short-form census attribute as the basis of apportionment
Assume that the long-form attribute of interest is uniformly distributed across the short-form population (accounts for unoccupied areas)
One limitation of the block-level data is that the break points for age categories do not match those of the educational attainment data (persons 25 or older)
The best that can be done with the block data is to tabulate persons aged 22 or older
Close enough for approximation
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41. Math of apportionment
Tract has 39 block centroids that span 2 beats
Of the 26 blocks making up the tract, the 13 that lie in car beat 261 have 1,177 people aged 22 or older.
The other 13 blocks in car beat 251 have 1,089 such people for a total of 2,266 for the tract.
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42. Math of apportionment
Apportionment assumes that the fraction of undereducated people aged 25 or older is the same as that for the general population aged 22 or older
This fraction, called the weight, is 1,177 ÷ 2,266 = For the other car beat, the weight is 1,089 ÷ 2,266 = 0.481
Thus, we estimate the contribution of tract to car beat 261’s undereducated population to be (1,177 ÷ 2,266) × 205 = 106. For car beat 251, it is (1,089 ÷ 2,266) × 205 = 99
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43. Math of apportionment
Eventually, by apportioning all tracts, we can sum up the total undereducated population for car beats 261 and 251
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44. Lecture 9
Background steps
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45. Background steps 1.) Download census data
Download census block and tract polygons from the census Web sites for the county containing the administrative area polygons
Download the short-form census data for blocks that are the basis of apportionment, in this case the population of age 22 and greater
Download the long-form census attribute(s) at the tract level that you wish to apportion to the administrative area, in this case the population aged 25 or greater with less than high school education
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46. Background steps 2.) Create new tract layer
That intersects administrative boundaries
If a tract is only partially inside the administrative area, you must include the entire tract for apportionment to work correctly
An example tract is the southerly-most tract in Tutorial9-3.mxd
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47. Background steps 3.) Prepare block centroids
Create a new centroid point layer for blocks
Clip the centroids with the new intersected tract layer
Join census short-form data to the clipped block centroids
This is the layer that is the basis for apportionment
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48. Background steps
4.) Sum the short-form census attributes in age categories to create Age22Plus in the clipped block centroids table
This step is unique to this problem
Also, this table has a new TractID attribute which concatenates FIPSSTCO & TRACT2000 to create an ID matching the Tracts map layer
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49. Background steps
5.) In the attribute table for block centroids, sum the field for persons aged 22 or older by TractID to create a new table, SumAge22Plus. This table provides the denominator for the weight used in apportionment
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50. Lecture 9
Apportionment steps
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51. Apportionment steps
1.)Intersect tracts and car beats to create new polygons that each have a tract ID and car beat number
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52. Apportionment steps
2.) Spatially join the new layer of tracts and car beats with the block centroids to assign all the tract attributes (including the attribute of interest: undereducated population) and car beat attributes to each block’s centroid
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53. Apportionment steps
2.)
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54. Apportionment steps
3.) Join SumAge22Plus to block centroids to make the apportionment weight denominator, total population aged 22 or older by tract, available to each block centroid
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55. Apportionment steps 3.) Export the join as a precaution 55
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56. Apportionment steps
4.) For each block centroid, create new fields to store apportionment weight and apportioned undereducated population values, then calculate these values
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57. Apportionment steps 4.) Calculate values 57
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58. Apportionment steps
5.) Sum the apportionment weights by tract as a check for accuracy (they should sum to 1.0 for each tract)
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59. Apportionment steps
5.) Each tract that is totally within car beats will have weights summing to 1. Those partially within car beats sum to less than 1
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60. Apportionment steps 5.) Sum the undereducated population per car beat
The extra row with no beat value is of no consequence, because it will not join to the car beats table in the next steps.
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61. Join apportionment results
The last task is to join the table containing undereducated population by car beat to the car beats layer, then symbolize the data for map display
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62. Finished map
There is some variation in the undereducated population in Lake Precinct car beats, but not a great deal. You can see that assault offenses tend to be in car beats or on the boundary of car beats with high undereducated populations.
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63. Summary Proximity buffers Site suitability example Basic apportionment
Advanced apportionment
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