This notebook will walk you through some basic techniques for spatial analysis and visualization in the CyberGIS-Jupyter environment. We will use CDC county-level Social Vulnerability Index (SVI) data to examine the characteristics of SVI and whether they are spatially autocorrelated.
Specifically, this notebook includes functions for
- Changing coordinate systems,
- Creating Choropleth maps, and
- Conducting Moran's I and Local Indicators of Spatial Association (LISA).
├── Getting_Start_with_CyberGISX_AAG2023.ipynb
├── LICENSE
├── README.md
└── data
├── SVI2020_US_county.cpg
├── SVI2020_US_county.dbf
├── SVI2020_US_county.prj
├── SVI2020_US_county.sbn
├── SVI2020_US_county.sbx
├── SVI2020_US_county.shp
├── SVI2020_US_county.shp.xml
├── SVI2020_US_county.shx
└── state_lookup.csv