Sold by: Pacific Community (SPC)
Open data
|
Deployed on AWS
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.
Overview
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.
Features and programs
Open Data Sponsorship Program
This dataset is part of the Open Data Sponsorship Program, an AWS program that covers the cost of storage for publicly available high-value cloud-optimized datasets.
Pricing
This is a publicly available data set. No subscription is required.
Legal
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
AWS Data Exchange (ADX)
AWS Data Exchange is a service that helps AWS easily share and manage data entitlements from other organizations at scale.
Open data resources
Available with or without an AWS account.
- How to use
- To access these resources, reference the Amazon Resource Name (ARN) using the AWS Command Line Interface (CLI). Learn more
- Description
- Data access
- Resource type
- S3 bucket
- Amazon Resource Name (ARN)
- arn:aws:s3:::dep-public-data
- AWS region
- us-west-2
- AWS CLI access (No AWS account required)
- aws s3 ls --no-sign-request s3://dep-public-data/
Resources
Vendor resources
Support
Contact
Managed By
How to cite
Sentinel-2 Geometric Median and Absolute Deviations (GeoMAD) over the Pacific was accessed on DATE from https://registry.opendata.aws/dep-s2-geomads .
License
Digital Earth Pacific Data is available under the Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/
Similar products
![Landsat Geometric Median and Absolute Deviations (GeoMAD) over the [...]](https://d1ewbp317vsrbd.cloudfront.net/54ba96e0-f2c6-4d39-881e-aaf6927a5591.png)
The GeoMAD is derived from Landsat surface reflectance data.
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.
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
a land monitoring constellation of two satellites that provide high resolution
optical imagery and provide continuity for the current SPOT and Landsat missions.
The mission provides a global coverage of the Earth's land surface every 5 days,
making the data of great use in on-going studies. L1C data are available from
June 2015 globally. L2A data are available from November 2016 over Europe
region and globally since January 2017.
The Sentinel-2 mission is
a land monitoring constellation of two satellites that provide high resolution
optical imagery and provide continuity for the current SPOT and Landsat missions.
The mission provides a global coverage of the Earth's land surface every 5 days,
making the data of great use in ongoing studies.
This dataset is the same as the Sentinel-2
dataset, except the JP2K files were converted into Cloud-Optimized GeoTIFFs (COGs).
Additionally, SpatioTemporal Asset Catalog metadata has were in a JSON file
alongside the data, and a STAC API called Earth-search
is freely available to search the archive. This dataset contains all of the scenes in the
original Sentinel-2 Public Dataset and will grow as that does.
L2A data are available from April 2017 over wider Europe region and globally since December 2018.
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 (Obregón et al, 2019). Level-2A data is the most ideal for research activities as it allows further analysis without applying additional atmospheric corrections.
The[...]
![Digital Earth Africa Sentinel-2 Level-2A Surface Reflectance Collec[...]](https://d1ewbp317vsrbd.cloudfront.net/a9acb6de-788b-4ce0-8949-bf2169a28732.png)
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 (Obregón et al, 2019). Level-2A data is the most ideal for research activities as it allows further analysis without applying additional atmospheric corrections.
Dig[...]
Sentinel-2 L2A 120m mosaic is a derived product, which contains best pixel values for 10-daily periods, modelled by removing the cloudy pixels and then performing interpolation among remaining values. As there are some parts of the world, which have lengthy cloudy periods, clouds might be remaining in some parts. The actual modelling script is available here.