https://github.com/giswqs/depression-analysis-toolbox

An ArcGIS toolbox for identifying nested depressions in digital elevation models (DEMs)
https://github.com/giswqs/depression-analysis-toolbox

digital-elevation-model geospatial gis image-processing lidar python remote-sensing

Last synced: 2 months ago
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An ArcGIS toolbox for identifying nested depressions in digital elevation models (DEMs)

• Host: GitHub
• URL: https://github.com/giswqs/depression-analysis-toolbox
• Owner: giswqs
• Created: 2019-07-12T20:34:51.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2019-07-13T01:11:05.000Z (over 5 years ago)
• Last Synced: 2024-11-02T12:33:52.343Z (2 months ago)
• Topics: digital-elevation-model, geospatial, gis, image-processing, lidar, python, remote-sensing
• Language: Python
• Homepage: https://doi.org/10.6084/m9.figshare.8866178
• Size: 2.72 MB
• Stars: 12
• Watchers: 2
• Forks: 9
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Depression-Analysis-Toolbox

This repository contains an ArcGIS toolbox and associated Python scripts for delineating nested depressions in digital elevation models (DEMs).

## References

* **Wu, Q.**, Liu, H., Wang, S., Yu, B., Beck, R., & Hinkel, K. (2015). A localized contour tree method for deriving geometric and topological properties of complex surface depressions based on high-resolution topographic data. _International Journal of Geographical Information Science_, 29(12), 2041-2060. 

* **Wu, Q.**, & Lane, C. R. (2016). Delineation and quantification of wetland depressions in the Prairie Pothole Region of North Dakota. _Wetlands_, 36(2), 215-227. 

* **Wu, Q.**, Deng, C., & Chen, Z. (2016). Automated delineation of karst sinkholes from LiDAR-derived digital elevation models. _Geomorphology_, 266, 1-10.