9_Lecture_Spatial_An..

GIS Tutorial 1

Lecture 9

Spatial Analysis

Outline



Proximity buffers



Calculate Area



Determine x,y values of centroids



Site suitability example



Basic apportionment



Advanced apportionment

GIS TUTORIAL 1 - Basic Workbook

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Lecture 9

PROXIMITY BUFFERS


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Proximity buffers



Points

 Circular buffers with user supplied radius



Lines

 Looks like worm based on line feature


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Proximity buffers



Polygons

 Extends polygons outward and rounds off corners

 Created by assigning a buffer distance around polygon


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Point buffer example



Polluting company buffers

 Added schools

 Added population

Buffering is located in ArcToolbox: Select Analysis Tools, Proximity, Buffer


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Point buffer example



Crimes near schools


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Line buffer example



Businesses within .25 miles of a selected street


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Select features in buffer


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Spatial join to count



Join business points to buffer polygon


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Polygon buffer example



Parcels within 150′ of selected property


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Select features in buffer


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Polygon buffer example



River buffer to analyze environmental conditions, flooding, etc.


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Lecture 9

CALCULATE AREA


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Area: Add the Field

•

Add area field in shapefile

•

Right click area field

•

Calculate Geometry

•

Select Property= Area and Units= Square miles or Sq Ft


Area: calculate the area

• Result is the area field is populated for each polygon feature


Lecture 9

DETERMINE X,Y VALUES OF CENTROIDS


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Polygon Centroids

•

Advanced calculations for finding polygon centroids

•

Added as an XY Data Layer


Point Centroid

•

Add x & y fields in shapefile

•

Right click x field

•

Calculate Geometry

•

Select Property= x Coordinate of Centroid and Units= Feet

•

Right click y field and repeat for y coordinate of centroid


Polygon Centroids

•

Export attributes as table

•

Add as XY Data:

File>Add Data> Add XY Data


Lecture 9

SITE SUITABILITY


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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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Starting map



Lake Precinct of the Rochester, New York,

Police Department

 Police car beats

 Retail business points

 Street centerlines


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Create car beat centroids



XY centroids for police beats


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Buffer car beat centroids



.33 mile buffer


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Buffer retail businesses



0.1 mile buffer


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Select major streets



Select by attribute


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Buffer major streets



0.05 mile buffer


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Intersect buffers



Can only intersect two at a time

 Car beat and businesses

 Streets


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Site suitability result



Map showing possible sites for police station


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Lecture 9

BASIC APPORTIONMENT


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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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Population by voting district



Start with census tracts


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

Overlay voting districts (not contiguous with tracts)


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

Better to use block centroids for population

 Smaller than tracts


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Spatially join centriods



Join centroids to voting districts


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Other simple apportionments



Population by

 Neighborhoods

 Zip Codes

 Historic sites

 Others?


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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

 Others?


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Lecture 9

ADVANCED APPORTIONMENT


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Advanced Apportionment



Chapter 9 example

 Police want to know the number of undereducated 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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Data to apportion



Car beats



Census tracts



Beats and tracts

 Not contiguous


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Beats and tracts zoomed



Tracts clearly cut across beats


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Tract attribute table



Tracts contain undereducated data

 No high school degree


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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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

Tract 360550002100



Car beats 261 and 251


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

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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

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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

Tract 360550002100 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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

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

= 0.519

. For the other car beat, the weight is

1,089 ÷ 2,266 = 0.481

 Thus, we estimate the contribution of tract

36055002100 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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

Eventually, by apportioning all tracts, we can sum up the total undereducated population for car beats 261 and 251


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Lecture 9

BACKGROUND STEPS


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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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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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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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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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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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Lecture 9

APPORTIONMENT STEPS


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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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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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2.)


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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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3.) Export the join as a precaution


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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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4.) Calculate values


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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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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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5.) Sum the undereducated population per car beat


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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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Finished map


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Summary



Proximity buffers



Site suitability example



Basic apportionment



Advanced apportionment


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GIS Tutorial 1

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