Spatial Analysis with Location Quotients

Geography 317                                                                                                                    February 8, 2013

 

Assignment 5: Spatial Analysis with Location Quotients

 

Purpose: This assignment teaches students to use ArcGIS to calculate and display location quotients to study spatial distributions and concentrations.

 

Substantive Purpose: In the first part of this assignment we will examine industrial specialization in Los Angeles County, California. In the second part of this assignment we will examine industrial specialization in King County, Washington, with additional emphasis on temporal changes and spatial distributions.

 

Location Quotients

Geographers use a variety of methods to display and assess spatial distributions. A key technique used by economic geographers it the location quotient.  However, location quotients have wide applicability. The location quotient (LQ) is an index for comparing an area’s share of a particular activity with the area’s share of some basic or aggregated phenomenon. LQs compare the distribution of an activity in an area to some standard. This emphasizes whether the activity is spatially concentrated or evenly distributed.  For example, economic geographers may ask whether manufacturing activity is more or less concentrated than total employment. Similarly, a biogeographer may use location quotients to determine if a particular species is clustered, or an environmental scientist may be interested in determining whether specific toxins are clustered compared to toxins in general (the standard or base values).

 

Following Burt and Barber (1996, p. 80) the location quotient for a given activity for area i is the ratio of the percentage of the total regional activity in area i to the percentage of the total base in area i. So, if Ai is equal to the level of the activity in area i and Bi is the level of the base, then

 

, this is often multiplied by 100.

 

A calculated LQ > 100 indicates area specialization or concentration.

A calculated LQ < 100 indicates an area has less than a share of a category.

A calculated LQ = 100 indicates a share in accordance with the share of a base category.

 

For example, zipcode X has the following values:

Zip code X                  County X

Professional services             8.7%                            5.5%

Manufacturing                       17.6%                          22.8%

 

To determine zipcode X’s specialization in professional services and manufacturing relative to the county we input the percentage employed into the following equation:

 

Professional services:                       (8.7/5.5) * 100 = 158

Manufacturing                       (17.6/22.8) * 100 = 77

 

In the example given the zip code X specializes in professional services (LQ=158) and not in manufacturing (LQ=77).

 

Part A: Industrial Activities in Los Angeles, County

 

In this part we will use ArcGIS to calculate location quotients for industrial sectors in Los Angeles County, California. We are trying to determine if the locations of industrial activities are spatially clustered.  We will use overlays and thematic mapping with graduated symbols. We will calculate location quotients within ArcGIS. Zipcode is the unit of spatial analysis.

 

Data and shape files: The files for this part of the assignment are contained in a zipfile called LAemploy. Within this zip file you will find La_zip_emp.shp, La_emp_cntr.shp, Lacity.shp, Lacnty.shp.

 

The data for this exercise are from the 1997 Economic Census for Los Angeles County, California. To perform the necessary calculations for the location quotient, the county total employment by sector is required. These figures are available in the following table.

 

 

 

Overview of the Analysis:1. Open layers, 2. compute LQs, 3. create graduated circle maps,

4. design a layout for map and print, 5. interpret findings.

 

Part A Procedure:

  1. Open arcmap starting with a new empty map.

 

  1. Add the following files: La_zip.emp.shp, La_emp_cntr.shp, Lacity.shp, Lacnty.shp.

 

  1. Make the polygons hollow on the layers for Lacity and Lacnty.

 

  1. Right click on La_emp_cntr and select Zoom to Layer.

 

  1. Open the attribute table for La_zip_emp.

 

  1. Note the file contains a field for zipcode and nine employment categories.

 

  1. Click Table options and add a field. We will use this field for the calculation of the LQ for manufacturing employment. Call this field LOC31, type to float, 16 for precision, and 0 for scale.

 

  1. Right click the LOC31 field and calculate (([CAT31]/[ZIP_TOTAL])/(0.280))*100 Note the 0.280 is provided from the table and represents the share of this category for the area.

 

  1. Repeat this procedure to calculate LOC## for the other industry types. You will need to change the numbers for the fields as well as the total in that industry for the county.

 

  1. Make a graduated symbol map for two industries of your choice using the LQ field. Use symbology, quantities, select graduated symbols, select your chosen value field, change classes to 4, click classify, manually change the range to the following meaningful categories: 0-100, 101-200, 201-300, 301 to maximum value.  Consider why these categories are meaningful.

 

  1. You can create your second map by right clicking on La_zip_emp  and click copy. Then click the Insert tab and select Data Frame. Now right-click New Data Frame and select Paste Layer(s). Copy and paste the three other layers from the above data frame. Remember to Zoom to Layer.

 

  1. Go to Layout view and make a layout to show two maps on one page. Be sure to label the maps appropriately. Save your map as a jpeg file (or a .png) to include with your assignment.

 

  1. Write a few paragraphs to discuss the spatial patterns of industry specialization in Los Angeles, County in 1997. Refer to your maps and use them as evidence for your ideas. Do your maps show spatial clustering of the industrial activities you have selected? Or, is this sector ubiquitous across LA County. Your report should compare the patterns and consider urban locations regarding center and periphery.

 

Part B: Industrial Activities in King County, 2001 to 2009

 

In this part we will use ArcGIS to calculate location quotients for industrial sectors in King County, Washington in 2001 and 2009. We are trying to determine if the location of industrial activities is spatially clusters, and if the spatial patterns have changed over time.  We will calculate location quotients within ArcGIS. Census tracts are the unit of spatial analysis.

 

Data and shape files: The files for this part of the assignment are contained in a zipfile called KingEmploy. Within this zip file you will find shape files for census tracts in King County and a database file for 2001 and 2009 providing the number employed by sectors of the industrial workforce.

(Note: You may prefer to use the shapefile from assignment 2 since it delineated the waters).

 

Data for industrial activities for King County is made available by the Puget Sound Regional Council at their website (www.psrc.org). Before proceeding with this part of the assignment, please visit to read about the following:

 

General employment data: http://www.psrc.org/data/employment

 

Specifically you need to acquaint yourself with the Covered Employment Estimates,

and the specific data files for 2001 and 2009 census tracts. Download and read these data files

for they contain the metadata and important summary figures.  http://www.psrc.org/data/employment/covered-emp

 

These files include employment figures for four counties in the Puget Sound Region. We will assess King County only, so the database files we will use are just a part of these master files.

 

Within the King County database we will use the major sector categories that combine NAICS categories as follows:

Construction and Resources (Const/Res): 11, 21, 23

Finance, Insurance and Real Estate (FIRE): 52, 53

Manufacturing: 31-33

Retail: 44, 45

Services: 51, 54-56, 61 (private-sector portion), 62, 71, 72, 81

Wholesale Trade, Transportation, and Utilities (WTU): 22, 42, 48, 49

Government: Public-sector employment, excluding education

Education: 61(public-sector portion).

 

Procedure: If you follow the methodology as outlined in Part A of this assignment, you can use ArcGIS to calculate location quotients for each of the 8 major sectors in King County. Calculate the location quotients for these eight sectors for 2001 and 2009 using ArcGIS.  (There is no need to merge them into one database, I find it more helpful to keep them separate).

 

 

 

Before you proceed, you will need to construct a table for 2001 and 2009 that is similar to the table listed above in Part A. This means you need to calculate the sector employment divided by the total county employment.  This information is available in the original Covered Employment datafiles you downloaded from the PSRC site.

 

Select four sectors. For each sector produce a page that has two maps, the top map should display the sector location quotients for 2001 and the bottom map should display the sector location quotients for 2009. Be sure to use graduated symbols and the same meaningful categories used in Part A. This means you will have eight maps in total, distributed across four pages.

 

Write a concise report to describe the spatial clustering of industrial activities across King County. Address also any significant changes in industrial location over time. Use your maps as evidence and refer to them within your report. Your report should compare the patterns and consider urban locations regarding center and periphery.

 

Summary of deliverables for assignment 5:  Due in class dropbox on Thursday, February 15, 2013.

From Part A. 2 maps and 1 short report.

From Part B. 8 maps, 2 tables and 1 report.

(The report from Part B is to be more substantial than the one from part A).

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