1. GIS Tools (Python-based) for Overlapping CSAs (Cancer Service Areas) in the USA:
Will be posted soon.
2. Data for Multiscale CSAs (Cancer Service Areas) in the USA:
If you use the GIS data from our paper: Wang, C., T. Onega, and F. Wang. 2022.
Multiscale analysis of cancer service areas in the United States. Spatial and Spatio-temporal Epidemiology 43: 100545, please cite it.
3. Data for 110 CSAs (Cancer Service Areas) in the USA:
If you use the data and/or tools from our paper: Wang, C., F. Wang, and T. Onega. 2022.
Delineation of cancer service areas anchored by major cancer centers in the United States. Cancer Research Communications 2 (5):380-389, please cite it.
4. Data and GIS Tools (Python and R-based) for the HSAs (Hospital Service Areas) Book:
If you use our GIS data and/or tools outlined on Page 4-6 in Chapter 1 of the book:
Wang, F. and C. Wang. 2022. GIS automated delineation of hospital service areas. Boca Raton, FL: CRC Press, please cite it. You can also watch Video Tutorial.
Note that the spatially constrained Leiden (ScLeiden) method, spatially constrained Louvain (ScLouvain) method, Dartmouth method, and other associated methods are programmed in the ArcToolbox "HSA Delineation Pro.tbx" under the zip file as well.
5. Data and GIS Tools (Python-based) for Estimating the Large Drive Time Matrix in the USA:
If you use the GIS data and/or tools from our paper: Hu, Y., C. Wang, R. Li, and F. Wang. 2020. Estimating a large drive time matrix between ZIP codes in the United States: A differential sampling approach. Journal of Transport Geography 86:102770, please cite it.
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