High-resolution digital elevation models and orthomosaics generated from historical aerial photographs (since the 1960s) of the Bale Mountains in Ethiopia
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 the recent decades are needed for determining 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, to the best of our knowledge, for any afro-alpine ecosystem. Here, we provide both DEM and orthomosaic images 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 Structure from Motion Multi View Stereo Photogrammetry along an elevation gradient from 977 to 4377 m above sea level (asl) at spatial resolutions of 0.84 m and 0.98 m for the years 1967 and 1984, respectively. Our datasets can be used by researchers and policymakers for (1) watershed management, as the area provides water for more than 30 million people; (2) landscape management; (3) detailed mapping and analysis of geological and archaeological features, as well as natural resources; (4) analyses of geomorphological processes; and (5) biodiversity research.
Mohammed Ahmed Muhammed et al.
Status: open (until 06 Apr 2023)
- RC1: 'Comment on essd-2022-363', Anonymous Referee #1, 08 Mar 2023 reply
Mohammed Ahmed Muhammed et al.
High-resolution digital elevation models and orthomosaics of the Bale Mountains in Ethiopia https://zenodo.org/record/7269999
High-resolution digital elevation models and orthomosaics of the Bale Mountains in Ethiopia https://zenodo.org/record/7271617
Mohammed Ahmed Muhammed et al.
Viewed (geographical distribution)
The paper is well written and comprehensible, the data sets listed in the paper are accessible online and complete. However, in its current form the paper requires major revisions in order to accommodate the standards of the ESSD journal.
The uniqueness of the paper lies in fact that historic aerial photographs for Ethiopia have been processed by modern methods of digital photogrammetry and thus, made available to a wide user community. For other parts of the world the same approach has been applied in manifold ways meaning that well established standard methods have been used in this study.
The motivation of the study presented in the introduction mainly focuses on thematic aspects, such as ecosystem, biodiversity, land use and climate change research in Ethiopia and the need for historic high-resolution spatial data (DEM and surface cover) for change and impact analysis. However, a profound assessment of globally available high-resolution satellite remote sensing data is missing. Such data include the KH-1 to KH-9 Corona (1960-1986), IRS (since 1995) and Digital Globe (since 1999) programs among others. The authors need to embed and compare their two snapshots in time (in)to a bigger time line and thus, demonstrate that their data spatially align to the globally available datasets in order to ensure data continuity in space and time which is listed as the first priority in using remote sensing data for biodiversity and related purposes (Tuner et al., 2015).
Moreover, the paper is missing a relevant case study demonstrating the value of the datasets for one of the significant purposes mentioned in the introduction. Just picking one case – volume difference at one section of a gravel road – is not sufficient for that. Such a case study also needs to include the comprehensible demonstration of alignment with other globally available high-resolution data sets.
Overall, the paper is written rather ‘minimalistic’ whereas most of the content is dedicated to standard technical descriptions (sections 2 and 3). The lack of more in-depth evaluation of the data is also reflected in the content and the quality of the figures as well as the results and discussions parts of the paper.
2.2 Data: From the description is unclear which data are used for accuracy assessment. The listed DEM data sets cannot be used for accuracy assessment since they are of much coarser spatial resolution. Later in the paper, the authors state the use of independent GCP’s for accuracy assessment. If this is the case, this information needs to be mentioned already in this section. The authors also need to consider using TanDEM-X DEM information (12,5 m resolution) in their study.
2.3.4 Ground control points: Have these GCP’s only be used for reference purposes or has a subset of them also be used for independent accuracy assessment of the resulting DEM’s? Such an approach using control information of significantly higher accuracy would be needed for a state-of-the-art accuracy assessment.
4 Results and discussion: Do the achieved accuracies represent internal accuracies or do they relate to external reference systems too? At this point it becomes evident that the methodological section 3 of the paper lacks a subsection describing the approach used for accuracy assessment in this study which would need to include the internal and the external accuracies as well as the alignment with other high-resolution data sets as already mentioned above. So far, there is only a very brief methodological description at beginning of section 4.2. The thematic discussion in section 4.1 is very minimal and needs to be extended (see comment under general remarks).
The quality assessment part proofs the high quality of the positional accuracy of the derived data sets. However, analysis of height accuracy seems to be missing and should be easy to perform using the available GCP’s. The further analysis of the quality of readily available DEM’s based on the same GCP’s is interesting but not an accuracy assessment related to the data sets derived in this study. However, these data sets could partly be used in order to analyze the alignment with external data. The current discussion between the different external DEM’s lacks clarity, the authors need to describe methodologically sound which parameters have been used in order to asses the accuracy of their data sets and the different external DEM’s. Moreover, RMS-errors of around 10 meters are not huge for DEM’s derived from medium resolution satellite data.