hand_module

HAND Plugin

HAND is a plugin for generating the Height Above Nearest Drainage (HAND) raster — the height above the nearest drainage point — from a Digital Elevation Model (DEM), watershed, flow direction raster, and drainage network. Additionally, it generates a flood-prone area map based on a user-defined threshold.

Description

The plugin computes the HAND raster, which represents, for each pixel of the DEM, the vertical difference between its elevation and the elevation of the nearest drainage pixel (the drainage network pixel to which it flows). This product is widely used in flood susceptibility analysis, hydrological modeling, and floodplain mapping.

Additionally, the plugin generates a flood-prone area map by classifying areas where HAND values are below the specified threshold as flood-prone.

Processing can be executed locally, by invoking Python/Fortran routines, or through a backend that receives the input files via HTTP and returns the resulting GeoTIFF.

Requirements

• QGIS 3.22+
• Python 3.9+ (compatible with QGIS/OSGeo4W)
• GDAL (≥ 3.8) with Python bindings (osgeo.gdal)
• NumPy
• The decimal separator must be a dot (.), not a comma (,).

Usage in QGIS

1. Launch the plugin through the menu: Plugins → HAND Plugin.
2. Select the input files:
   • Digital Elevation Model (DEM) — GeoTIFF raster (Data Type: Float)
   • Watershed — GeoTIFF raster (Data Type: Integer)
   • Flow Direction — GeoTIFF raster (Data Type: Integer)
   • Drainage Network — GeoTIFF raster (Data Type: Integer)
3. Specify output paths for the HAND raster and the flood-prone area map, and set the flood threshold (in meters).
4. Click the “Generate HAND” button.

The plugin will call the HAND routine developed in Fortran. Upon completion, two GeoTIFF files will be generated and automatically added to the current QGIS project:

• The HAND result (raster GeoTIFF, Data Type: Float)
• The flood-prone area map (raster GeoTIFF, Data Type: Byte), where areas below the threshold are classified as flood-prone.

License

MIT License
Copyright (c) 2025 João Vitor Lima & Adriano Paz

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