Difference between revisions of "Volume 1 Appendix B"

Revision as of 20:29, 18 June 2010

Processes for Producing the Community Distribution Model Regions' Mapping Layers

The Community Distribution Model (CDM) maps in this report, and the population density data sets used to create Figure 11 , were generated using the Microsoft Access CDM database and ESRI ArcView GIS software. The process involved four steps which are explained here. Note that steps 1-3 are interdependent, and were repeated in iterative fashion to achieve the final results.

Step 1

A field called "REGION" was included in the "BAPTISM " table of the CDM Microsoft ACCESS database. Using locational techniques described in Chapter IV, an attempt was made to assign each named individual to a local region. Eventually, 31,363 of the 32,381 baptized tribal Indian people (i.e., 97%) were assigned to a region (assignments were not made for 1,018 records of people from the "Tulares").

Step 2

A separate table was created in the CDM database, called "REGIONS" It contained one record for each region listed in the BAPTISM table. In this table, fields were added that provided information about specific regional groups, such as rancheria names, languages spoken in the region, and Caltrans District (See Appendix A, Table A-1).

Step 3

The regions were reproduced as mapped polygons on a GIS map layer using ESRI ArcView. The layer was prepared as follows:

• Initial regional boundaries were digitized by hand as a polyline shapefile in the GIS, with the 1:500,000 USGS California base map as an underlying reference. Concurrently, a point was centrally digitized in each region and its unique name was entered in the point shapefile’s attribute table. Where regions would be spatially discontiguous in the completed polygon shapefile (e.g., due to intervening areas of open water), each area was given a duplicate label point.
• Boundary lines were subjected to a smoothing procedure to eliminate small irregularities in the digitized lines.
• A coastline shapefile that represented the Pacific coast and large estuaries was then merged with those smoothed lines.
• These lines were then subjected to standard "clean" and "build" procedures to generate polygons
• Region-name attributes were applied from the point shapefile.
• The polygons were then subjected to a standard "dissolve" procedure on the region-name attribute, so that discontiguous polygons with the same region name were merged into a single, multi-part shape.
• The area of each region in square miles was then calculated by an ArcView algorithm.
• Apart from digitizing in the first step, this procedure was automated via an ESRI ArcToolbox model (titled "Build areas").

Step 4

The completed polygon shapefile was linked to the ACCESS database using the common region-name attribute. Among other things, this allowed population densities to be calculated as follows:

• The GIS-calculated area of each region was copied from the GIS layer’s attribute table into a dedicated field in the ACCESS database REGIONS TABLE.
• The total number of adults baptized in each region was calculated from the CDM ACCESS database by summing up the number of baptisms for individuals over 14 years of age that had been assigned to each region. (A very small number of these were adjusted by adding adults baptized at Mission San Luis Obispo, outside the model’s southern boundary.)
• The resulting baptized adult population for a region was then divided by a regional mortality factor to generate an inferred pre-mission adult population. That inferred adult population was multiplied by two to produce an inferred total population (it is assumed that "adults" over 14 years of age and children under 15 would have represented equal portions of normal pre-mission populations).
• Population density was then calculated by dividing these adjusted population estimates by the total area of each region
• The resultant population density was listed for each region in a field in the ACCESS database REGIONS TABLE.

The population mortality factor, often different from one region to another, is key to the resulting inferred population density. Table B-1 shows the results for the Bay Area Analytical Zone.

Step 5

The completed polygon shapefile data in the GIS system were combined with data from the ACCESS database to generate the maps expressing various kinds of qualities and groupings of regions. For instance, population density information from the ACCESS database REGIONS TABLE was imported into an ESRI ArcMap document and used to create the color-coded density values shown in Figures 10 and 11.

Step 6

Near-finished ArcView maps were exported to Adobe Illustrator for final production.