Automatization and evaluation of a remote sensing-based indicator for wetland health assessment in East Africa on national and local scales

To avoid wetland degradation and promote sustainable wetlands use, decision-makers and managing institutions need quantified and spatially explicit information on wetland ecosystem condition for policy development and wetland management. Remote sensing holds a significant potential for wetland mapping, inventorying, and monitoring. The Wetland Use Intensity (WUI) indicator, which is not specific to a particular crop and which requires little ancillary data, is based on the Mean Absolute Spectral Dynamics (MASD), which is a cumulative measure of reflectance change across a time series of optical satellite images. It is sensitive to the compound effects of land cover changes caused by different agricultural practices, flooding or burning. The more frequent and intrusive management practices are on the land cover, the stronger the WUI signal. WUI thus serves as a surrogate indicator to measure pressure on wetland ecosystems. We developed a new and automated approach for WUI calculation that is implemented in the Google Earth Engine (GEE) cloud computing environment. Its automatic calculation, use of regular Sentinel-2 derived time series, and automatic cloud and cloud shadow masking renders WUI applicable for wetland management and produces high quality results with minimal user requirements, even under cloudy conditions. For the first time, we quantitatively tested the capacity of WUI to contribute to wetland health assessment in Rwanda on the national and local scale. On the national scale, we analyzed the discriminative power of WUI between different wetland management categories. On the local scale, we evaluated the possible contribution of WUI to a wetland ecosystem health scoring system. The results suggest that the adapted WUI indicator is informative, does not overlap with existing indicators, and is applicable for wetland management. The possibility to measure use intensity reliably and consistently over time with satellite data is useful to stakeholders in wetland management and wetland health monitoring, and can complement established field-based wetland health assessment frameworks.