Depression Analysis Toolbox

<p>This repository contains an ArcGIS toolbox and associated Python scripts for delineating nested depressions in digital elevation models (DEMs).</p><p><b>GitHub repository</b>: <a href="https://github.com/giswqs/Depression-Analysis-Toolbox">https://github.com/giswqs/Depression-Analysis-Toolbox</a></p><p><b>References</b>:</p><ul><li><p><b>Wu, Q.</b>, 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. <em>International Journal of Geographical Information Science</em>, 29(12), 2041-2060. <a href="https://doi.org/10.1080/13658816.2015.1038719" rel="nofollow">https://doi.org/10.1080/13658816.2015.1038719</a></p></li><li><p><b>Wu, Q.</b>, & Lane, C. R. (2016). Delineation and quantification of wetland depressions in the Prairie Pothole Region of North Dakota. <em>Wetlands</em>, 36(2), 215-227. <a href="https://doi.org/10.1007/s13157-015-0731-6" rel="nofollow">https://doi.org/10.1007/s13157-015-0731-6</a></p></li><li><p><b>Wu, Q.</b>, Deng, C., & Chen, Z. (2016). Automated delineation of karst sinkholes from LiDAR-derived digital elevation models. <i>Geomorphology</i>, 266, 1-10. <a href="https://doi.org/10.1016/j.geomorph.2016.05.006" target="_blank">https://doi.org/10.1016/j.geomorph.2016.05.006</a></p></li></ul>