Abstract
Abstract. The natural resources of Ethiopian high-altitude ecosystems are commonly perceived as increasingly threatened by devastating land-use practices owing to decreasing lowland resources. Quantified time-series data of the course of land-use cover changes are still needed. Very-high-resolution digital data on the historical landscape over recent decades are needed to determine the impacts of changes in afro-alpine ecosystems. However, digital elevation models (DEMs) and orthomosaics do not exist for most afro-alpine ecosystems of Africa. We processed the only available and oldest historical aerial photographs for Ethiopia and any afro-alpine ecosystem. Here, we provide a DEM and an orthomosaic image for the years 1967 and 1984 for the Bale Mountains in Ethiopia, which comprise the largest afro-alpine ecosystem in Africa. We used 298 historical aerial photographs captured in 1967 and 1984 for generating DEMs and orthomosaics with a structure-from-motion multi-view stereo photogrammetry workflow along an elevation gradient from 977 to 4377 m above sea level (a.s.l.) at very high spatial resolutions of 0.84 m and 0.98 m for the years 1967 and 1984, respectively. The structure-from-motion multi-view stereo photogrammetry workflow, employed with Agisoft Metashape, represents a modern approach that combines computer vision and photogrammetry. This method proves useful for reconstructing DEMs and orthomosaics from historical aerial photographs, with a focus on high spatial resolution. To validate the accuracy of the reconstructed DEMs, ground control points gathered through GPS measurements were used, resulting in root mean square error (RMSE) values of 3.55 m for the year 1967 and 3.44 m for the year 1984. Our datasets can be used by researchers and policymakers for watershed management, as the area provides water for more than 30 million people, landscape management, detailed mapping, and analysis of geological and archaeological features as well as natural resources, analyses of geomorphological processes, and biodiversity research. All the datasets are available online at https://doi.org/10.5281/zenodo.7271617 (Muhammed et al., 2022a) for all the inputs used and at https://doi.org/10.5281/zenodo.7269999 (Muhammed et al., 2022b) for the results obtained (very-high-resolution DEMs and orthomosaics) for both the years 1967 and 1984.
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