Digital Earth Pacific Annual Shorelines (Landsat, 30 m)

Africa's long and dynamic coastline is subject to a wide range of pressures, including extreme weather and climate, sea level rise and human development. Understanding how the coastline responds to these pressures is crucial to managing this region, from social, environmental and economic perspectives. The Digital Earth Africa Coastlines (provisional) is a continental dataset that includes annual shorelines and rates of coastal change along the entire African coastline from 2000 to the present. The product combines satellite data from the Digital Earth Africa program with tidal modelling to map the typical location of the coastline at mean sea level for each year. The product enables trends of coastal erosion and growth to be examined annually at both a local and continental scale, and for patterns of coastal change to be mapped historically and updated regularly as data continues to be acquired. This allows current rates of coastal change to be compared with that observed in prev[...]

This dataset provides annual cloud-free composite imagery derived from Landsat surface reflectance observations across the Pacific region using geometric median and absolute deviation (GeoMAD) methods. The data are masked for cloud, shadows and other image artefacts using the associated pixel quality product to help provide as clear a set of observations as possible from which to calculate the medians. Along with the geometric median surface reflectance bands, the GeoMAD includes three measures of variability (Euclidean, spectral and Bray- Curtis median absolute deviations: emad, smad and bcmad) and a count of clear observations. The dataset is available annually from 2000 and supports monitoring of vegetation, land cover, and coastal environments.

Digital Earth Africa’s Monthly NDVI Anomaly service provides estimate of vegetation condition, for each caldendar month, against the long-term baseline condition measured for the month from 1984 to 2020 in the NDVI Climatology. A standardised anomaly is calculated by subtracting the long-term mean from an observation of interest and then dividing the result by the long-term standard deviation. Positive NDVI anomaly values indicate vegetation is greener than average conditions, and are usually due to increased rainfall in a region. Negative values indicate additional plant stress relative to the long-term average. The NDVI anomaly service is therefore effective for understanding the extent, intensity and impact of a drought.Abrupt and significant negative anomalies may also be caused by fire disturbance.

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 [...]