High-resolution dataset (2017-2023) of physical-geographical predictors for machine learning modelling of fluvial flooding: the Gidra river case, Slovakia

This data article releases geospatial predictor files for a section of the Gidra River (western Slovakia). Based on the last cycle of the Preliminary Flood Risk Assessment from 2024 in Slovakia, the past fluvial floods and, especially, the flash flood from 7 June 2011 affected the studied river section and the Píla municipality significantly. These facts resulted in including the studied Gidra River section to critical river sections for the occurrence of fluvial floods. The collection comprises seven single-band rasters on a common 1 m grid: slope, Topographic Wetness Index, Stream Power Index, Height Above the Nearest Drainage, Euclidean distance from river, surface roughness, and Normalized Difference Vegetation Index. Source inputs are the LiDAR digital elevation model (DMR 5.0, resolution: 1 m) from 2017 and aerial orthophotos (resolution: 0.15 m) from 2023. All layers are georeferenced to a single CRS, co-registered to identical extent and transform, and provided as GeoTIFFs with documented units, no data, and datatypes. Processing relied on ArcGIS 10.2.2 software and Python for alignment and quality checks. Additional tables supply per-file inventory and descriptive statistics (min/mean/max/std) to enable automated validation and integration into geographic information system (GIS) and modelling workflows. The dataset is designed for reuse in flood-related and terrain-vegetation analyses, including feature engineering, benchmarking, and training of machine-learning (ML) models that require uniform, high-resolution predictors.