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Wetland Use Intensity Rwanda 2020

<p>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 surface reflectance 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. The dataset provided is calculated from bi-monthly composites from July 2019 to June 2021 to form a pseudo-year 2020 and covers the East African country of Rwanda.</p> <p>The GEE code is available in the supplementary materials of (please cite when using the dataset):</p> <p>Steinbach, S., Hentschel, E., Hentze, K., Rienow, A., Umulisa, V., Zwart, S.J., Nelson, A., 2023. Automatization and evaluation of a remote sensing-based indicator for wetland health assessment in East Africa on national and local scales. <em>Ecological Informatics</em> <em>75</em>, 102032. <a href="https://doi.org/10.1016/j.ecoinf.2023.102032">https://doi.org/10.1016/j.ecoinf.2023.102032</a></p> <p>The research was supported by the project Copernicus-based Detection and Monitoring of tropical Wetlands (DeMo-Wetlands), which was funded by the German Federal Ministry for Economic Affairs and Energy (grant no. 50EE1537).</p>

ShareScore

32/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
16
Reuse readiness
8
Engagement
0

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