Automated terrain roughness assessment using UAV-derived data

Grube, Gunta and Talbot, Bruce and Grigolato, Stefano (2026) Automated terrain roughness assessment using UAV-derived data. [Data Collection]

Collection description

This data collection supports the study “Automated terrain roughness assessment using remotely sensed data.” It includes manual field measurements of surface obstacles, UAV-derived orthomosaics and digital elevation models, and final grid-based terrain roughness results used for validation and analysis.

DOI:	10.25430/researchdata.cab.unipd.it.00001723
Keywords:	terrain roughness, UAV, remote sensing, photogrammetry
Subjects:	Life Sciences > Applied Life Sciences, Biotechnology and Molecular and Biosystems engineering: Applied plant and animal sciences; forestry; food sciences; applied biotechnology; environmental, and marine biotechnology; applied bioengineering; biomass, biofuels; biohazard > Applied plant sciences (including crop production, plant breeding, agroecology, forestry, soil biology)
Department:	Departments > Dipartimento di Territorio e sistemi agro-forestali (TESAF)
Depositing User:	Gunta Grube
Date Deposited:	07 Jan 2026 07:18
Last Modified:	07 Jan 2026 07:18
Creators/Authors:	Creators Email ORCID Grube, Gunta gunta.grube@unipd.it orcid.org/0000-0001-5124-373X Talbot, Bruce bruce@sun.ac.za orcid.org/0000-0003-1935-5429 Grigolato, Stefano stefano.grigolato@unipd.it orcid.org/0000-0002-2089-3892
Type of data:	Mixed
Research funder:	Marie SkłodowskaCurie Actions of the main programme ‘‘Excellent Science’’, project Skill-For.Action
Grant number:	956355
Collection period:	From To 2023 UNSPECIFIED
Geographic coverage:	Jonkershoek timber plantation, Western Cape Province, South Africa
Bounding Area:	North Latitude East Longitude South Latitude West Longitude -33.971 -33.973 18.946 18.943
Data collection method:	Data were collected through a single field campaign and low-altitude UAV surveys. Manual field measurements of rock obstacles (height and circumference) were used as reference data. UAV imagery was acquired using a multirotor drone and processed via photogrammetry to generate orthomosaics, digital elevation models, and point clouds for terrain roughness analysis.
Data processing and preparation activities:	UAV images were processed using structure-from-motion photogrammetry to generate orthomosaics, digital elevation models, and dense point clouds. Segmented obstacle polygons and point cloud data were used to derive grid-based terrain roughness indicators. Manual field measurements were used for validation and comparison. Final datasets were aggregated to a 3 × 3 m grid in UTM Zone 32S. The full roughness calculation code is not yet publicly available.
Resource language:	English
Metadata language:	English
Publisher:	Research Data Unipd
Related publications:	https://doi.org/10.1080/14942119.2025.24... (Publisher)
Date:	6 January 2026
Copyright holders:	The Author
URI:	https://researchdata.cab.unipd.it/id/eprint/1723
Additional details Additional details Creators/Authors: Creators Email ORCID Grube, Gunta gunta.grube@unipd.it orcid.org/0000-0001-5124-373X Talbot, Bruce bruce@sun.ac.za orcid.org/0000-0003-1935-5429 Grigolato, Stefano stefano.grigolato@unipd.it orcid.org/0000-0002-2089-3892 Type of data: Mixed Research funder: Marie SkłodowskaCurie Actions of the main programme ‘‘Excellent Science’’, project Skill-For.Action Grant number: 956355 Collection period: From To 2023 UNSPECIFIED Geographic coverage: Jonkershoek timber plantation, Western Cape Province, South Africa Bounding Area: North Latitude East Longitude South Latitude West Longitude -33.971 -33.973 18.946 18.943 Data collection method: Data were collected through a single field campaign and low-altitude UAV surveys. Manual field measurements of rock obstacles (height and circumference) were used as reference data. UAV imagery was acquired using a multirotor drone and processed via photogrammetry to generate orthomosaics, digital elevation models, and point clouds for terrain roughness analysis. Data processing and preparation activities: UAV images were processed using structure-from-motion photogrammetry to generate orthomosaics, digital elevation models, and dense point clouds. Segmented obstacle polygons and point cloud data were used to derive grid-based terrain roughness indicators. Manual field measurements were used for validation and comparison. Final datasets were aggregated to a 3 × 3 m grid in UTM Zone 32S. The full roughness calculation code is not yet publicly available. Resource language: English Metadata language: English Publisher: Research Data Unipd Related publications: https://doi.org/10.1080/14942119.2025.24... (Publisher) Date: 6 January 2026 Copyright holders: The Author Last Modified: 07 Jan 2026 07:18

Available Files

Data

1_Manual_rock_measures.xlsx 1_Manual_rock_measures.xlsx 1_Manual_rock_measures.xlsx Visible to: Anyone Content type: Data Description: Manual field measurements of rock obstacles (height and circumference) used to validate UAV-based terrain roughness assessment results by comparing field observations with UAV-derived estimates. Metadata Revision: 2 Mime-Type: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet License: Creative Commons: Attribution 4.0 File size: 12kB

Site1_DEM.tif Site1_DEM.tif Site1_DEM.tif Visible to: Anyone Content type: Data Description: High-resolution digital elevation model (DEM) derived from UAV photogrammetry for the study site, used to calculate surface height variations and terrain roughness metrics. Data are provided in UTM zone 32S. Metadata Revision: 2 Mime-Type: image/tiff License: Creative Commons: Attribution 4.0 File size: 234MB

Departmental metadata

Site1_orthomosaic.tif Site1_orthomosaic.tif Site1_orthomosaic.tif Visible to: Anyone Content type: Additional metadata Description: UAV orthomosaic of the study site, generated from overlapping aerial imagery and used for visual interpretation, obstacle identification, and spatial reference in terrain roughness assessment. Data are provided in UTM zone 32S. Metadata Revision: 2 Mime-Type: image/tiff License: Creative Commons: Attribution 4.0 File size: 1GB

Other

Roughness_grid.csv Roughness_grid.csv Roughness_grid.csv Visible to: Anyone Description: Spatial grid dataset of terrain roughness results aggregated per grid cell, including obstacle-based roughness metrics and final roughness classification. Derived from UAV data and provided as multipolygon geometries in UTM zone 32. Metadata Revision: 2 Mime-Type: text/plain License: Creative Commons: Attribution 4.0 File size: 133kB