Dataset
Sub-meter resolution digital elevation models and orthomosaics of the Kruger National Park, South Africa, v1.0, September-October 2018
Abstract
This dataset contains sub-meter resolution digital elevation models and orthomosaics of the Kruger National Park, South Africa, generated from aerial images captured by Digital Mapping Camera (DMC) during September and October 2018.
The use of digital elevation models has proven to be crucial in a large number of studies related to savanna ecosystem research. However, the insufficient spatial resolution of the input data is often considered to be a limiting factor when conducting local to regional ecosystem analysis. The elevation models and orthorectified imagery created in this dataset represent the first wall-to-wall digital elevation products of the Kruger National Park (KNP) in South Africa at 25 cm pixel posting. In the light of regular flight campaigns carried out by the South African government, the workflow of the presented data sets can be reused to create height models and orthorectified images of a vulnerable ecosystem in the future. Flight campaigns were carried out by GeoSpace International, Pretoria. Data processing and preparation as well as validation of the final products was carried out by Kai Heckel (Friedrich Schiller University Jena, Germany) with the strong support of all co-authors of the related study.
The methodology is described in the following publication:
Heckel, K.; Urban, M.; Bouffard, J.-S.; Baade, J.; Boucher, P.; Davies, A.; Hockridge, E.G.; Lück, W.; Ziemer, J.; Smit, I.; Jacobs, B.; Norris-Rogers, M.; Schmullius, C. (2021): The first sub-meter resolution digital elevation model of the Kruger National Park, South Africa. Koedoe.
Details
| Previous Info: |
No news update for this record
|
|---|---|
| Previously used record identifiers: |
No related previous identifiers.
|
| Access rules: |
Access to these data is available to any registered CEDA user. Please Login or Register for an account to gain access.
Use of these data is covered by the following licence: http://creativecommons.org/licenses/by/4.0/. When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record. |
| Data lineage: |
Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA). |
| Data Quality: |
Data was validated by the project team. For the validation of the vertical accuracy of the derived digital elevation models (DEMs) the authors used parameters as suggested by the American Society for Photogrammetry and Remote Sensing (ASPRS), Positional Accuracy Standards for Digital Geospatial Data. The validation of the horizontal accuracy of the orthorectified mosaics was carried out following the National Standard for Spatial Data Accuracy (NSSDA) standards. Details can be found in the related documnetation
|
| File Format: |
GEOtiff
|
Related Documents
Process overview
Computation Element: 1
| Title | Kruger DEM and Orthomosaics; semi-global matching |
| Abstract | In recent years, semi-global matching (SGM) approaches have proven to be among the most popular and successful algorithms in the fields of stereo vision and photogrammetry (Klette et al. 2011, Michael et al. 2013). To extract the height information from the aerial imagery, we used this matching approach, which utilizes intensity differences, mutual information (as the cost function) and an approximation of the global energy function that is being optimized path-wise (16 paths in this study) from all directions over the image. The cost function is significantly influenced by the use of penalty values, which were chosen based on performance tests and represent varying magnitudes of disparity changes. These variables have a strong impact on the matching performance and the robustness that is related to this processing step. The term 'semi-global arises from the combination of both global and local methods in a way that the complexity of the process is lowered and the quality of the matching is drastically improved. While the computation time for these global methods is often considerably higher, the overall performance increases compared to local matching algorithms. Further, pixel-wise calculated matching cost, contrary to the calculation along image paths, poses negative effects of insufficient correspondences related to low texture and ambiguity (Hirschmüller 2007). |
| Input Description | Kruger DEM and Orthomosaics - Flight campaign using multispectral camera. |
| Output Description | Kruder DEM and orthomosaics |
| Software Reference | None |
| Output Description | None |
No variables found.
Temporal Range
2018-09-01T00:00:00
2018-10-30T00:00:00
Geographic Extent
-22.3287° |
||
30.8882° |
32.0330° |
|
-25.5295° |