Remote sensing for mapping ecosystem services to support evaluation of ecological restoration interventions in an arid landscape

Considerable efforts and resources are being invested in integrated conservation and restoration interventions in rural arid areas. Empirical research for quantifying ecosystem services – nature’s benefits to people – is essential for evaluating the range of benefits of ecological restoration and to support its use in natural resource management. Satellite remote sensing (RS) can be used to monitor interventions, especially in large and remote areas. In this study we used field measurements, RS-based information from Sentinel-2 imagery together with soil and terrain data, to estimate ecosystem service supply and evaluate integrated ecological restoration interventions. We based our research on the arid, rural landscape of the Baviaanskloof Hartland Bawarea Conservancy, South Africa, where several integrated interventions have been implemented in areas where decades of small livestock farming has led to extensive land degradation. Interventions included i) long term livestock exclusion, ii) revegetating of degraded areas, iii) a combination of these two, and iv) essential oil production as alternatives to goat and sheep farming. We assessed six ecosystem services linked to the objectives of the interventions: erosion prevention, climate regulation, regulation of water flows, provision of forage, biomass for essential oil production, and the sense of place through presence of native species. We first estimated the ecosystem service supply based on field measurements. Secondly, we explored the relationships between ecosystem services quantities derived from the field measurements with 13 Sentinel-2 indices and four soil and terrain variables. We then selected the best fitting model for each ecosystem service. Finally, we compared the supply of ecosystem services between intervened and non-intervened sites. Results showed that models based on Sentinel-2 indices, combined with slope information, can estimate ecosystem services supply in the study area even when the levels of field-based ecosystem services supplies are low. The RS-based models can assess ecosystem services more accurately when their indicators mainly depend on green vegetation, such as for erosion prevention and provision of forage. The agricultural fields presented high variability between plots on the provision of ecosystem services. The use of Sentinel-2 vegetation indices and terrain data to quantify ecosystem services is a first step towards improving the monitoring and assessment of restoration interventions. Our results showed that in the study area, livestock exclusion lead to a consistent increase in most ecosystem services.