Case09A-One Level Spatial Clustering

Chapter 9 Regionalization Methods and Application in Analysis of Cancer Data

Case study 9 in this chapter analyzes variations of breast cancer rates across various constructed regions in Louisiana. Part 1 introduces several one-level regionalization methods such as SCHC, SKATER, AZP, Max-P and REDCAP methods Part 2 implements various clustering indicators. Part 3 illustrates the implementation of Mixed-Level Regionalization (MLR) method, which decomposes areas of large population and merges areas of small population simultaneously to derive regions with comparable population size. The case study is developed from the research reported in Mu et al. (2015). The construction of new regions enables us to map reliable cancer rates.
The data used in this project is provided the zip file LA_Mixtracts.zip under the folder Louisiana, which includes 1,132 census tracts in Louisiana.

Case 9A: one-level regionalization methods

Computational Methods and GIS Applications in Social Science - Lab Manual
Lingbo Liu, Fahui Wang

External resources

• GitHub for Geospatial Analytics
• GitHub for Workbook Issue Report