Digital Earth Pacific Mangrove Extent, Density, Change and Condition (Sentinel-2, 10 m)

The Global Mangrove Watch (GMW) dataset is a result of the collaboration between Aberystwyth University (U.K.), solo Earth Observation (soloEO; Japan), Wetlands International the World Conservation Monitoring Centre (UNEP-WCMC) and the Japan Aerospace Exploration Agency (JAXA). The primary objective of producing this dataset is to provide countries lacking a national mangrove monitoring system with first cut mangrove extent and change maps, to help safeguard against further mangrove forest loss and degradation. The Global Mangrove Watch dataset (version 2) consists of a global baseline map of mangroves for 2010 and changes from this baseline for six epochs i.e. 1996, 2007, 2008, 2009, 2015 and 2016. Annual maps are planned from 2018 and onwards. The dataset can be used to identify mangrove ecosystems and monitor changes in mangrove extent. This is important in applications such as quantifying ‘blue carbon’, mitigating risks from natural disasters, and prioritising restoration acti[...]

Synthetic Aperture Radar (SAR) sensor have the advantage of operating at wavelengths not impeded by cloud cover and can acquire data over a site during the day or night. The Sentinel-1 mission, part of the Copernicus joint initiative by the European Commission (EC) and the European Space Agency (ESA), provides reliable and repeated wide-area monitoring using its SAR instrument.Sentinel-1 Monthly Mosaics are analysis-ready product of individual Sentinel-1 acquisitions. Sentinel-1 monthly mosaics are generated from Radiometric Terrain Corrected (RTC) backscatter data, with variations from changing observation geometries mitigated. RTC images acquired within a calendar month are combined using a multitemporal compositing algorithm. This algorithm calculates a weighted average of valid pixels, assigning higher weights to pixels with higher local resolution (e.g., slopes facing away from the sensor). This local resolution weighting approach minimizes noise and improves spatial homogene[...]

Fractional cover (FC) describes the landscape in terms of coverage by green vegetation, non-green vegetation (including deciduous trees during autumn, dry grass, etc.) and bare soil. It provides insight into how areas of dry vegetation and/or bare soil and green vegetation are changing over time. The product is derived from Landsat satellite data, using an algorithm developed by the Joint Remote Sensing Research Program. Digital Earth Africa's FC service has two components. Fractional Cover is estimated from each Landsat scene, providing measurements from individual days. Fractional Cover Annual Summary (Percentiles) provides 10th, 50th, and 90th percentiles estimated independently for the green vegetation, non-green vegetation, and bare soil fractions observed in each calendar year (1st of January - 31st December). While the scene based Fractional Cover can be used to study dynamic processes, the annual summaries make it easier to analyse year to yea[...]

DE Africa's Sentinel-1 backscatter product is developed to be compliant with the CEOS Analysis Ready Data for Land (CARD4L) specifications. The Sentinel-1 mission, composed of a constellation of two C-band Synthetic Aperture Radar (SAR) satellites, are operated by European Space Agency (ESA) as part of the Copernicus Programme. The mission currently collects data every 12 days over Africa at a spatial resolution of approximately 20 m. Radar backscatter measures the amount of microwave radiation reflected back to the sensor from the ground surface. This measurement is sensitive to surface roughness, moisture content and viewing geometry. DE Africa provides Sentinel-1 backscatter as Radiometrically Terrain Corrected (RTC) gamma-0 (0) where variation due to changing observation geometries has been mitigated. The dual polarisation backcastter time series can be used in applications for forests, agriculture, wetlands and land cover classification. SAR's ability to 'see through' clouds [...]