Woody cover mapping in the savanna ecosystem of the Kruger National Park using Sentinel-1 C-Band time series data

Abstract

Savanna ecosystems are dominated by different densities of grasses and woody plants with inter-annual changes because of dry and wet seasons. They cover half of the African continent and around 20% of the global land surface and are of great significance for ecology (e.g. living environment) and economy (e.g. fuelwood, timber) (Kutsch et al. 2008; Main et al. 2016; Scholes & Walker 1993). The savanna ecosystems of South Africa are shaped by disturbance processes such as droughts, fire and herbivory (Druce et al. 2008; Scholes & Archer 1997; Stevens et al. 2016), as well as anthropogenic impacts like climate change (e.g. increase in atmospheric CO2) or management actions. It is therefore not surprising that these savannas have been undergoing various changes during the last decades (Buitenwerf et al. 2012; Skowno et al. 2016). Information about changes in woody cover and above-ground biomass (AGB) in national parks (e.g. Kruger National Park [KNP]) is important for park management and conservation efforts, as changes in woody cover are likely to have effects on other ecosystem patterns and processes. For example, an increase in woody cover will lead to a reduction in grass and herbaceous biomass (Berger et al. 2019), which will have cascading effects on herbivores (i.e. favouring browsers to grazers [Smit & Prins 2015]) and fire regimes (i.e. reducing fire frequency [Smit et al. 2012]). 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 intraand 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 crossvalidation 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.