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  • Easy visualisation of Earth observation data with new HEDAVI tool modes

    The Discover mode in HEDAVI showcases the usefulness of Earth Observation (EO) data in a variety of applications through a list of case-studies—so-called “stories”. The first new feature allows users to share links to the stories in HEDAVI. The second new feature allows them to export any image of a case-study from the Discover mode to the Explorer mode.

  • Earthquake in Izmit (Türkiye), August 1999

    Explore satellite images capturing the aftermath of the 1999 Izmit earthquake in Türkiye.

  • Development of the Saemangeum Dam (South Korea), 1987-2013

    See the transformation of the Saemangeum Dam in South Korea through satellite images from 1987 to 2013.

  • Development of Hong Kong International Airport, 1988-2010

    View the transformation of Hong Kong International Airport through satellite images documenting its development from 1988 to 2010.

  • Urban Evolution of Dubai: A Satellite Perspective from 1984 to 2017

    Explore the urban transformation of Dubai through satellite images spanning from 1984 to 2017.

  • HEDAVI Discover: a step-by-step guide

    The Heritage Data Visualisation tool (HEDAVI) is a platform developed by the French Science Consulting for Earth Observation group, VisioTerra, which allows users to freely access over 40 years of ESA Earth Observation Heritage data, Third Party Missions and some Copernicus data.

  • Cloud-free collections key for land monitoring

    Satellite imagery is a crucially important tool for monitoring the land, but cloud cover can often block parts of Earth’s surface from view, limiting subsequent analyses.

  • Full European Landsat data collection now available under the same catalogue

    The Full European Landsat data collection, from Landsat-1 to Landsat-8, is now available under the same catalogue

  • SLAP

    The SLAP (Systematic Landsat Archive Processing) project covers the MSS, TM and ETM+ products from Landsat missions 1 – 7, and is the first systematic reprocessing of the ESA Landsat archive.

  • HEDAVI

    The HEDAVI (HEritage DAta Visualisation) service enables users to discover a wealth of heritage data from ESA's ERS and Envisat missions, as well as from Landsat-5 and Landsat-7.

  • Satellite data allows real-time detection of potential fires

    A pilot Fire Detection Service, based on real-time processing of Landsat-8 data being assessed within the framework of ESA's Earthnet Programme.

  • FedEO

    FedEO is a data catalogue that provides a unique entry point to a number of scientific catalogues and services for, but not limited to, European and Canadian missions.

  • ESA PDGS DataCube

    ESA's DataCube is a data catalogue that enables multi-temporal and pixel-based access to a subset of data available from ESA

  • EO CAT

    EO CAT is a data catalogue, offering a Next Generation Earth Observation system designed to manage end-user Earth Observation services.

  • LANDSAT_Products_Description_Document.pdf

    This document acts as a User Guide to the Landsat MSS, TM and ETM+ archives, focussing more specifically on the Landsat TM and ETM+ products from the Kiruna, Maspalomas and Matera archives (including from the Matera, Fucino, Neustralitz, O’Higgins, Malindi, Libreville and Bishkek ground stations) that have been generated as part of the ESA archive bulk-reprocessing project.

  • Landsat-TM-ETM-CEOS-ESA-Products

    This document describes the standards used by ESA for the distribution of the TM and ETM+ (Thematic Mapper and Enhanced Thematic Mapper) optical sensor products.

  • Landsat Series

    The Landsat Series is the world's longest running system of satellites for moderate-resolution optical remote sensing for land, coastal areas and shallow waters.

  • LANDSAT Products Description Document.pdf

    LANDSAT products, algorithm and processing description document (MSS, TM and ETM+)

  • CEOS-IVOS Workshop on Inter-comparison of Large Scale Optical and Infrared Sensors

    The 2004 workshop was an opportunity to present and exchange experiences and knowledge from work on inter-comparing large scale optical sensors at different product levels.