Woody cover mapping in the savanna ecosystem of the Kruger National Park using Sentinel-1 C-Band time series data
The savanna ecosystems in South Africa, which are predominantly characterised by woody vegetation (e.g. shrubs and trees) and grasslands with annual phenological cycles, are shaped by ecosystem processes such as droughts, fires and herbivory interacting with management actions. Therefore, monitoring...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
AOSIS
2020-08-01
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| Series: | Koedoe: African Protected Area Conservation and Science |
| Subjects: | |
| Online Access: | https://koedoe.co.za/index.php/koedoe/article/view/1621 |
| Summary: | The savanna ecosystems in South Africa, which are predominantly characterised by woody vegetation (e.g. shrubs and trees) and grasslands with annual phenological cycles, are shaped by ecosystem processes such as droughts, fires and herbivory interacting with management actions. Therefore, monitoring of the intra- and inter-annual vegetation structure dynamics is one of the essential components for the management of complex savanna ecosystems such as the Kruger National Park (KNP). To map the woody cover in the KNP, data from European Space Agency’s (ESA) Copernicus Sentinel-1 radar satellite (C-Band vertical–vertical [VV]/vertical–horizontal [VH]) for the years 2016 and 2017, at 10 m spatial resolution and repeated acquisitions every 12 days, were utilised. A high-resolution light detection and ranging (LiDAR) data set was reclassified to produce woody cover percentages and consequently used for calibration and validation. Woody cover estimation for different spatial resolutions was carried out by fitting a random forest (RF) model. Model accuracy was assessed via spatial cross-validation and revealed an overall root mean squared error (RMSE) of 22.8% for the product with a spatial resolution of 10 m and improved with spatial averaging to 15.8% for 30 m, 14.8% for 50 m and 13.4% for 100 m. In addition, the product was validated against a second LiDAR data set, confirming the results of the spatial cross-validation of the model. The methodology of this study is designed for savanna vegetation structure mapping based on height estimates by using open-source software and open-access data, to allow for a continuation of woody cover classification and change monitoring in these types of ecosystems.
Conservation implications: Information about the state and changes in woody cover are important for park management and conservation efforts. Both increasing (e.g. because of atmospheric carbon fertilisation) and decreasing (e.g. because of elephant impact) woody cover patterns will have cascading effects on other ecosystem processes such as fire and herbivory. |
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| ISSN: | 0075-6458 2071-0771 |