This dataset represents the extent and location of surface depressions derived from the 10-m resolution dataset from the 3D Elevation Program (3DEP). The levet-set algorithm available through the lidar Python package was used the process the DEM and delineate surface depressions at the HU8 watershed scale.
First, create a conda environment with the required packages:
If you are using Google Colab, you can uncomment the following to install the packages and restart the runtime after installation.
The dataset was derived from the 10-m resolution dataset from the 3D Elevation Program (3DEP) at HU8 watershed scale. The results were then merged at the HU2 watershed scale. Below is a map of the National Hydrography Dataset (NHD) watershed boundary structure.
The script below can be used to access the data using DuckDB. The script uses the duckdb Python package.
Find out the total number non-floodplain wetlands in the selected watershed:
Alternatively, you can use the aws cli to access the data directly from the S3 bucket:
To visualize the data, you can use the leafmap Python package with the lonboard backend. The script below shows how to visualize the data.
The depression dataset has two variations: all_dep
and nfp_dep
. The all_dep
dataset contains all depressions, while the nfp
dataset contains non-floodplain depressions.
Find out the total number of surface depression in the contiguous United States (CONUS):
Calculate some descriptive statistics of all surface depressions:
Find out the total number non-floodplain depressions in the contiguous United States (CONUS):
Calculate some descriptive statistics of non-floodplain surface depressions: