five

Dataset of physical-geographical predictors

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NIAID Data Ecosystem2026-05-10 收录
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https://data.mendeley.com/datasets/bprmy76fdv
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The data represents a critical section of the Gidra River, which is located in the western part of Slovakia. The primary input for creating the physical-geographical predictors was the airborne laser scanned LiDAR digital elevation model (DMR 5.0) with a resolution of 1 m, provided by the Geodetic and Cartographic Institute, Bratislava as well as the orthophotos from 2023 (15 cm pixel). The dataset provides raw orthophoto map, LiDAR DEM and shapefile that were the basis for creating predictors. These predictors can be further used to train flood scenarios for predicting the fluvial flood extent as well as flow depth. Seven raster predictors for fluvial flood extent modelling at 1 m resolution were created from the orthophoto source file and LiDAR DEM: Height Above Nearest Drainage, Euclidean Distance to Drainage, Surface roughness, Stream Power Index, Topographic Wetness Index, Normalized Difference Vegetation Index, and Slope. The data repository has the following structure: - Orthophoto_Gidra.tif (aerial orthophoto, RGB+NIR), - DEM_Gidra.tif (elevation grid), - Shapefile_Gidra.shp (shapefile, LineString geometry), - HAND_Gidra.tif (Height Above Nearest Drainage), - EucDist_Gidra.tif (Euclidean distance to drainage), - Roughness_Gidra.tif (Manning’s n roughness), - SPI_Gidra.tif (Stream Power Index), - TWI_Gidra.tif (Topographic Wetness Index), - NDVI_Gidra.tif (Normalized Difference Vegetation Index), - Slope_Gidra.tif.
创建时间:
2025-11-03
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