Digital Earth Pacific Annual Surface Reflectance Composite (Sentinel-2, GeoMAD, 10 m)

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.

This dataset provides annual radar-based composite imagery derived from Sentinel-1 observations across the Pacific region. Sentinel-1 carries a C-band Synthetic Aperture Radar (SAR), which acquires data day and night and in all weather conditions, so the composite is independent of cloud cover. Multi-temporal Sentinel-1 backscatter observations (VV and VH polarisations) are aggregated into annual geometric median composites, along with median absolute deviation measures (emad, smad and bcmad) and a count of observations. The dataset is available annually from 2017 and supports monitoring of land, water, and environmental change.

GeoMAD is the Digital Earth Africa (DE Africa) surface reflectance geomedian and triple Median Absolute Deviation data service. It is a cloud-free composite of satellite data compiled over specific timeframes. The geomedian component combines measurements collected over the specified timeframe to produce one representative, multispectral measurement for every pixel unit of the African continent. The end result is a comprehensive dataset that can be used to generate true-colour images for visual inspection of anthropogenic or natural landmarks. The full spectral dataset can be used to develop more complex algorithms. For each pixel, invalid data is discarded, and remaining observations are mathematically summarised using the geomedian statistic. Flyover coverage provided by collecting data over a period of time also helps scope intermittently cloudy areas. Variations between the geomedian and the individual measurements are captured by the three Median Absolute Deviation (MAD) laye[...]

The Sentinel-2 mission is part of the European Union Copernicus programme for Earth observations. Sentinel-2 consists of twin satellites, Sentinel-2A (launched 23 June 2015) and Sentinel-2B (launched 7 March 2017). The two satellites have the same orbit, but 180 apart for optimal coverage and data delivery. Their combined data is used in the Digital Earth Africa Sentinel-2 product. Together, they cover all Earth's land surfaces, large islands, inland and coastal waters every 3-5 days. Sentinel-2 data is tiered by level of pre-processing. Level-0, Level-1A and Level-1B data contain raw data from the satellites, with little to no pre-processing. Level-1C data is surface reflectance measured at the top of the atmosphere. This is processed using the Sen2Cor algorithm to give Level-2A, the bottom-of-atmosphere reflectance (Obregon et al, 2019). Level-2A data is the most ideal for research activities as it allows further analysis without applying additional atmospheric corrections. Digi[...]