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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.
Aktau's Urban Evolution: A Satellite Perspective from 1988 to 2015
Explore the evolution of Aktau, Kazakhstan, through satellite images captured by Landsat 5 and 8.
Adam's Bridge Evolution: A Satellite Perspective from 2006 to 2018
Discover the evolution of Adam's Bridge, the land connection between India and Sri Lanka, through satellite images.
Karachi's Urban Evolution: A Satellite Perspective from 1989 to 2018
Discover the evolution of Karachi over 29 years through satellite images captured by Landsat 5 and 8.
Red Sea: A Satellite Perspective from 1984 to 2004
Explore Landsat 5 imagery showcasing the evolving landscapes along the coasts of Egypt, Sudan and Saudi Arabia by the Red Sea.
Florence's Urban Evolution: A Satellite Perspective from 1987 to 2015
Uncover Florence's evolution from 1987 to 2015 through Landsat 5 and 8 satellite images.
Saint Petersburg 25 Years in Satellite View
Discover the evolution of Saint Petersburg over 25 years through satellite images captured by Landsat 5 and 8.
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.
ERS SAR dataset over Izmit Earthquake (1999)
Discover ERS SAR dataset over Izmit Earthquake.
Discover Earth like never before: the HEDAVI tool
The Heritage Data Visualisation tool, or HEDAVI, enables the analysis of global spatio-temporal dynamics of natural and artificial environments, covering 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.
How satellite data empower sustainable urban growth
Earth observation is a vital tool for facilitating the sustainable development of the world's cities, helping to ensure that urban centres keep spurring collaboration, innovation and opportunity as they continue to expand.
New collections available: Cloud Free Landsat-5 TM and Landsat-7 ETM+ European and Mediterranean Countries
Two new data collections, Landsat-5 TM Cloud Free and Landsat-7 ETM Cloud Free collections, are available through the ESA Third Party Missions programme.
Landsat 5 TM European and Mediterranean Countries Cloud Free Collection
This dataset contains the cloud-free products from Landsat 5 Thematic Mapper collection acquired over Europe, North Africa and the Middle East; for each scene only one product is selected, with the minimal cloud coverage. The acquired Landsat TM scene covers approximately 183 x 172.8 km. A standard full scene is nominally centred on the intersection between a path and row (the actual image centre can vary by up to 100 m). The data are system corrected.
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.
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
Heritage data trains neural networks to detect urban sprawl
Using data from non-operational ESA remote sensing missions, researchers have trained a network of artificial neurons to recognise how cities change over decades. They hope this will help city planners reduce the impact that urbanisation has on the environment.
EO Summer School 3
ESA's series of summer schools, on Monitoring of the Earth System, aims to promote the exploitation of Earth observation data.