Welcome to the lidar package¶
lidar is Python package for delineating the nested hierarchy of surface depressions in digital elevation models (DEMs). It is particularly useful for analyzing high-resolution topographic data, such as DEMs derived from Light Detection and Ranging (LiDAR) data.
- GitHub repo: https://github.com/giswqs/lidar
- Documentation: https://lidar.gishub.org
- PyPI: https://pypi.org/project/lidar
- Conda-forge: https://anaconda.org/conda-forge/lidar
- Open in Colab: https://gishub.org/lidar-colab
- Free software: MIT license
Wu, Q., (2021). lidar: A Python package for delineating nested surface depressions from digital elevation data. Journal of Open Source Software, 6(59), 2965, https://doi.org/10.21105/joss.02965
Wu, Q., Lane, C.R., Wang, L., Vanderhoof, M.K., Christensen, J.R., & Liu, H. (2019). Efficient Delineation of Nested Depression Hierarchy in Digital Elevation Models for Hydrological Analysis Using Level-Set Method. Journal of the American Water Resources Association. https://doi.org/10.1111/1752-1688.12689 (PDF)
lidar is a Python package for delineating the nested hierarchy of surface depressions in digital elevation models (DEMs). In traditional hydrological modeling, surface depressions in a DEM are commonly treated as artifacts and thus filled and removed to create a depressionless DEM, which can then be used to generate continuous stream networks. In reality, however, surface depressions in DEMs are commonly a combination of spurious and actual terrain features. Fine-resolution DEMs derived from Light Detection and Ranging (LiDAR) data can capture and represent actual surface depressions, especially in glaciated and karst landscapes. During the past decades, various algorithms have been developed to identify and delineate surface depressions, such as depression filling, depression breaching, hybrid breaching-filling, and contour tree method. More recently, a level-set method based on graph theory was proposed to delineate the nested hierarchy of surface depressions. The lidar Python package implements the level-set method and makes it possible for delineating the nested hierarchy of surface depressions as well as elevated terrain features. It also provides an interactive Graphical User Interface (GUI) that allows users to run the program with minimal coding.
Statement of Need¶
The lidar package is intended for scientists and researchers who would like to integrate surface depressions into hydrological modeling. It can also facilitate the identification and delineation of depressional features, such as sinkholes, detention basins, and prairie potholes. The detailed topological and geometric properties of surface depressions can be useful for terrain analysis and hydrological modeling, including the size, volume, mean depth, maximum depth, lowest elevation, spill elevation, perimeter, major axis length, minor axis length, elongatedness.
State of the Field¶
Currently, there are a few open-source Python packages that can perform depression filling on digital elevation data, such as RichDEM and whitebox, the Python frontend for WhiteboxTools. However, there are no Python packages offering tools for delineating the nested hierarchy of surface depressions and catchments as well as simulating inundation dynamics. The lidar Python package is intended for filling this gap.
- Smoothing DEMs using mean, median, and Gaussian filters.
- Extracting depressions from DEMs.
- Filtering out small artifact depressions based on user-specified minimum depression size.
- Generating refined DEMs with small depressions filled but larger depressions kept intact.
- Delineating depression nested hierarchy using the level-set method.
- Delineating mount nested hierarchy using the level-set method.
- Computing topological and geometric properties of depressions, including size, volume, mean depth, maximum depth, lowest elevation, spill elevation, perimeter, major axis length, minor axis length, elongatedness, eccentricity, orientation, and area-bbox-ratio.
- Exporting depression properties as a csv file.