Forest Roads Rindbach

1. Forest Roads The “Forest Roads” dataset bundles geospatial data, field surveys, and reproducible QGIS scripts for the mapping, analysis, and assessment of forest roads (example area: Rindbach, Upper Austria). It includes the road centerline and surfaces, a segmentation into 5-m sections with slope classes, curve sections with computed minimum curvature radius, and an inventory of bridges and culverts, condition surveys, and bearing-capacity measurements under dry and wet conditions (CSV tables bearing_dry/bearing_wet, bridges, culverts, condition). A GeoPackage serves as the central data hub; the accompanying README files document data structure, definitions, and assumptions. The dataset is intended to support planning, maintenance, and assessment activities of forest road networks - for example, analyses of curve radii and gradients, drainage sizing and placement, trafficability under different conditions, and teaching & research. Two included QGIS Python scripts enable reproducing the curve analysis (calculation of point radii and aggregation into curve sections) and deriving cross-sections from a centerline and a digital terrain model (DTM) with export to CSV. The datasets contain GNSS measurements (without post-processing); coordinate reference use UTM Zone 33N (EPSG:32633). Notes on accuracy, limitations, parameters, and correct interpretation of variables are summarized in the READMEs. In total, the deposit comprises 13 files: 5 READMEs, 5 CSV datasets, 1 GeoPackage, 2 QGIS scripts providing all building blocks to reproduce the analyses and adapt them to additional forest road sections. 2. Photogrammetry (supplementary data) The ZIP folder photogrammetry contains a SfM-derived GeoTIFF raster (a 10 cm/pixel DTM for the example section) together with the original source images used to generate it. Image acquisition followed the protocol documented in the Model Catchment Rindbach final report: Platform & cameras: Two action cameras (GoPro HERO7 Black) mounted at the rear of a VW van, 1.85 m above ground, centered on the vehicle. Viewing geometry: Two fixed view angles toward the road surface, approx. 5° and 55°. Capture rate & speed: Images recorded every 0.5 s (≈ 2 Hz) at a target speed of ~10 km/h to ensure dense overlap. Camera settings: ISO 800–1600, white balance 6000 K, no exposure compensation, linear FOV. Scaling & georeferencing: Printed markers were placed on the road prior to acquisition for scale; at least one marker per section (start or end point) was surveyed to align the model with existing geodata. Processing: Images were processed using Structure-from-Motion in Agisoft Metashape, producing a 3D point cloud and a raster product suitable for subsequent analysis. For the overall Rindbach campaign (context): 25,300 images covering 28.01 km were acquired. As an example, a 3.84 km section was captured with 2,995 images. 2,985 of these were successfully processed to a point cloud of ~1.10 million points, from which a 10 cm/pixel DTM was generated. Note: The ZIPs provided cover not all of the data described in the final report (e.g. drone flights). For additional processed sections, raw image sets and further information or data, please contact the authors.