The EOSure project is examining how to better understand and improve quality assurance of the end-to-end Earth Observation (EO) supply chain, from upstream EO satellite data providers to downstream end users who use products and services based on EO data. EOSure news Telespazio
Most of the largest cities experience profound changes due to urbanization and hence, city administrations are facing challenges in order to safeguard high quality urban growth despite increasingly tight spatial resources. Modifications in the built up environment increase the temperature of cities compared to their surroundings and are more prone to excess heat. Moreover, climate …
Development of AI based methods to classify herds of different animals based on the spatial distribution patterns adopted within different herd species. AI based pattern recognition methods based on distribution patterns of animals within a herd detected in EO imagery.
A key indication of the performance of earth observation is how easy, quick and affordable it is to collect fresh imagery of a location. This underpins the viability of value-added services and the credibility of the sector right across markets. It is our contention that fresh image collection rates poorly in this regard, particularly in …
The TRIDENT project pursued rapid prototyping of a Satellite Earth Observation (SatEO) pre-operational application dedicated to the monitoring of ship recycling laws (and notably the EU Ship Recycling Regulation). During the first phase of the project the needs and requirements of the ship recycling community have been collected and, accordingly, a prototype architecture has been …
The goal of Pixstart is to establish a new EO-based service dedicated to the foresters, denoted Woodwatch. This new service will help them to optimize their forest management thanks to ingestion of satellite derived maps into dedicated GIS environments. The present project will consist of developing the scientific part (algorithms) of the Woodwatch service. The …
The main objective of this activity is to develop an automated Sentinel-based service for remote and regular monitoring of subsoil use in open-cast mining areas with a monthly update frequency and 0.5 ha minimum detectable area to support control of subsoil use and detection of possible illegal mining. The main natural resources located under the …
The project created a service platform providing reliable information on changes in built-up areas, derived from Sentinel-2 data in a fully automatic manner using image classification algorithms. These algorithms, selected for the tool, are successfully operated and validated in other Land Cover mapping activities conducted by the consortium partners. Results of the image classification contributed …
The SeasFire project, funded by the ESA, is taking an innovative approach to predicting seasonal wildfire patterns in Europe. SeasFire uses cutting-edge technology, such as modern deep learning models and Earth Observation data, to explore the spatio-temporal connections between atmospheric conditions and fire regimes to gain valuable insights into predicting potential wildfires. The project aligns …
Hyperspectral imaging can capture hundreds of images acquired for narrow and continuous spectral bands across the electromagnetic spectrum, hence can allow us to precisely analyze the materials that are present in a scene of interest. However, the large volume of hyperspectral images (HSIs) makes their manual analysis and transfer very costly and time-expensive, especially when …
