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News

New GEP services from CNRS-EOST for landslide detection and mapping using Artificial Intelligence

Interested in a rapid landslide detection after major triggering events such as large earthquakes or heavy rains? Interested in the creation of landslide inventory maps as an input to susceptibility and hazard quantification? The new GEP services ALADIM-S2 and ALADIM-VHR are for you!

 

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Observing Siberian wildfires with Forestry TEP

It is not unusual to have wildfires in Siberia in the dry months of the summer. But this year, hot and dry weather combined with strong winds have fuelled fires to such an extent that a state of emergency has been declared in many parts of Siberia. Forestry TEP provides excellent means to monitor the progress and effects of the fires with direct access to satellite data and a variety of image processing tools available.

 

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Utilizing Forestry TEP’s processing capabilities to create cloudless views of the world

Terramonitor is utilizing Forestry TEP (F-TEP) to process satellite imagery for their cloud free mosaic products. Access to the F-TEP services is arranged through a Representational State Transfer (REST) Application Programming Interface (API), allowing smooth connection between the two systems.

 

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Forest monitoring tools for dry tropical areas

The Satellite Monitoring for Forest Management (SMFM) project is developing tools for monitoring tropical dry forests and supporting countries to develop their Earth Observation (EO) capacity. The users in tropical countries can access and run the SMFM tools implemented on Forestry TEP (F-TEP) using online interface.

 

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Arbonaut using F-TEP to monitor land use

It happens quite often that you hear the claim that in our era of science and technology, the common man lives amid an overwhelming information flow. With satellites and space technology, we no longer have white areas on the map, in the same way as there was for great explorers some few hundred years ago.

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How space technology can support hazard and risk mapping in Indonesia

Last November, INDRA has joined the GEP Early Adopters Programme, in order to perform EO Data Exploitation activities, with the aim to deliver feedback and improved awareness about the GEP capabilities. Performed as part of the EO4SD DRR 2 project (‘Earth Observation for Sustainable Development – Disaster Risk Reduction’), such activities on GEP correspond to a foreseen period of use at least up to 2021.

 

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JRC Global Surface Water dataset is available in HEP!

The European Commission’s Joint Research Centre developed the JRC Global Surface Water dataset in the framework of the Copernicus Programme. This maps the location and temporal distribution of water surfaces at the global scale over the past 32 years and provides statistics on the extent and change of those water surfaces. It can be added to Thematic Apps on Hydrology TEP.

 

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Discriminate Urban and Rural Settlements

One of the relevant topics in the Urban field of the study is what constitutes Rural Settlement, Urban Settlement and Metropolitan Settlements. In the application provided by TEP Urban for an initial 10 countries, you can select different thresholds for what does it mean for a settlement to be Rural, Urban or Metropolitan.

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Post processing tools made available to screen EO data also allow to make nice images using Sentinel-2

The on-demand Band Combination 8 processing service COMBI provides RGB composites from user defined bands of single or multiple data products from a broad range of EO missions. All bands are in their native format e.g. no radiometric correction is applied thus can serve only for fast screening of the data, not for further processing. We are sharing nice results using time series of Sentinel-2 images of the Copernicus programme.

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Sentinel-2 outperformed Landsat 8 in forest variable estimation

In a recent paper, published in Remote Sensing of Environment we compared the performance of Sentinel-2 and Landsat 8 satellites in the estimation of forest variables in Finland. The variables were stem volume (V), stem diameter (D), tree height (H) and basal area (G), and their species-wise components for pine (Pine), spruce (Spr) and broadleaved (BL) trees. We compared the S2 and L8 performances using twelve different test setups including different Sentinel-2 and Landsat 8 band combinations and pixel resolutions, and using two different modelling methods. They also identified the best predictive image bands for each test setup.

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VIDEO
Coastal TEP is a continuing project dedicated to the observation of coastal environment and resources.