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Spatial Data Analysis with Python
Song Gao
Email: sgao@geog.ucsb.edu
UCSB BROOM CENTER

Goals of Workshop
1. Introduction to the batch processing in ArcGIS;
2. Introduce the Python scripting language and its
application in ArcGIS;
3. Become familiar with several methods for writing,
and running geoprocessing scripts using Python;
4. Apply Python scripts to automate a GIS workflow;
5. Solve your own domain problem using Python.

1. Introduction
Primary Data Types
vector: point, line, polygon
raster: continuous (e.g. elevation) or
discrete surfaces (e.g. land use type)
Common Data Storage Formats
vector: shapefile, geodatabase feature
tables (.dbf, .xlsx), KML, GeoJSON
raster: ASCII, GeoTIFF, JPEG2000

Why Spatial?
Discussion: What kinds of spatial variables can you think of
for determining the house prices in cities?

Geographically Weighted Regression (GWR)
Discussion: What kinds of spatial variables can you think of
for determining the house prices in cities?
A local form of linear regression used to model spatially varying relationships
Fotheringham, Stewart A., Chris Brunsdon, and Martin Charlton. Geographically
Weighted Regression: the analysis of spatially varying relationships. John Wiley & Sons,
2002.
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