Landsat Geometric Median and Absolute Deviations (GeoMAD) over the Pacific.

The Geometric Median and Absolute Deviations (GeoMAD) product is a cloud-free annual mosaic that uses a more robust method of determining the median observation than a simple median. Along with the median observation, the GeoMAD produces three measures of variance, or absolute deviations, which helps to understand how the data over the time period changes. For example, some areas, such as desert, will change very little. Whereas crop land will change more. All ofthese values are useful in understand what is happening in the area covered by the GeoMAD.

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[...]

This joint NASA/USGS program provides the longest continuous space-based record of Earth’s land in existence. Every day, Landsat satellites provide essential information to help land managers and policy makers make wise decisions about our resources and our environment. Data is provided for Landsats 1, 2, 3, 4, 5, 7, 8, and 9 (excludes Landsat 6). As of June 28, 2023 (announcement), the previous single SNS topic `arn:aws:sns:us-west-2:673253540267:public-c2-notify` was replaced with three new SNS topics for different types of scenes.

The Landsat Analysis Ready Data (ARD) created by the Global Land Analysis and Discovery Lab (GLAD) at the University of Maryland serves as a spatially and temporally consistent input for land cover mapping and change detection at global to local scales. The GLAD ARD represents a 16-day time series of globally consistent, tiled Landsat normalized surface reflectance from 1997 to the present operationally updated every 16 days. Only data from 2020 to present available on the AWS, older data is available through the UMD API.

Digital Earth Africa (DE Africa) provides free and open access to a copy of Landsat Collection 2 Level-2 products over Africa. These products are produced and provided by the United States Geological Survey (USGS). The Landsat series of Earth Observation satellites, jointly led by USGS and NASA, have been continuously acquiring images of the Earth’s land surface since 1972. DE Africa provides data from Landsat 5, 7 and 8 satellites, including historical observations dating back to late 1980s and regularly updated new acquisitions. New Level-2 Landsat 7 and Landsat 8 data are available after 15 to 27 days from acquisition. See Landsat Collection 2 Generation Timeline for details. USGS Landsat Collection 2 was released early 2021 and offers improved processing, geometric accuracy, and radiometric calibration compared to previous Collection 1 products. The Level-2 products are endorsed by the Committee on Earth Observation Satellites (CEOS) to be Analysis Ready Data for Land (CARD4L)[...]

The Harmonized Landsat Sentinel-2 (HLS) project provides consistent surface reflectance (SR) and top of atmosphere (TOA) brightness data from a virtual constellation of satellite sensors. The Operational Land Imager (OLI) is housed aboard the joint NASA/USGS Landsat 8 and Landsat 9 satellites, while the Multi-Spectral Instrument (MSI) is mounted aboard Europe’s Copernicus Sentinel-2A, Sentinel-2B, and Sentinel-2C satellites. The combined measurement enables global observations of the land every 2–3 days at 30-meter (m) spatial resolution. The HLS project uses a set of algorithms to obtain seamless products from OLI and MSI that include atmospheric correction, cloud and cloud-shadow masking, spatial co-registration and common gridding, illumination and view angle normalization, and spectral bandpass adjustment. The HLSL30 product provides 30-m Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR) and is derived from Landsat 8/9 OLI data products.[...]