Billions of radar images over the entire Amazon basin have been converted into a data cube and processed to help a dynamic detection of forest loss. This work, performed within the Sentinel-1 for Science: Amazonas project, uses a space-time data cube design (also known as StatCubes), where statistical information relevant to identify deforestation is extracted …
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 SDG Pathfinder project – EO for Sustainable Forest Management will develop and showcase in partnership with the custodian agency FAO innovative EO approaches to produce indicators on the sustainable management of natural, semi-natural and planted forests. It will benefit from improved data availability to support the SDG 15 Life on Land with the SDG …
The UN Decade on Ecosystem Restoration focus on the restoration of ecosystems on a large scale to achieve the United Nations sustainable development agenda in 2030. The PEOPLE Ecosystem Restoration project will develop innovative products and indicators determining and monitoring processes, both degradation and/or recovery. In several pilot sides in various ecosystems like boreal peatland …
The BiomAP project aims to Integrate active and passive microwave data towards a novel global record of aboveground biomass maps. This comprises an end-to-end assessment of active and passive microwave observations at coarse spatial resolution at the longest wavelengths available in space to generate global AGB estimates. This work will eventually provide a 5-years baseline, …
The main objective of the RepreSent project is to capitalize on the potential of artificial intelligence (AI) and Earth observation (EO) by exploiting the non-supervised learning paradigms. In this context, it is essential to come up with non-supervised learning-based solutions for impactful use cases that use unlabeled EO data. The project started on April 1st, …
QueryPlanet aims at democratizing the access of Artificial Intelligence to the Earth Observation community by developing open-tools for the creation of AI-ready EO dataset and use-cases that leverage such datasets to build global insights applications. Material and datasets develop under QueryPlanet are open-access. The project aims at providing open-source tools for the exploitation of Earth …
In the framework of the overall collaborative efforts with Africa, carried out with the strong involvement of the African Union Commission (AUC), for the first time in the ESRIN activities, two African Researchers have joined ESRIN in 2022: Dr. Wassim M. Baba and Dr Gladys Mosomtai. Wassim a post-doctoral researcher at the University Mohammed VI …
AI4SAR is an attempt to harness AI techniques for high-resolution, high-fidelity SAR data, both in time and spatially. It aims to process rapid-revisit SAR data and develop modular applications for high-frequency monitoring of Earth. The inherent complexity of the backscattered SAR signal presents a daunting challenge to data scientists and machine learning (ML) engineers, thereby increasing …
This post contains educational materials from the event Trans-Atlantic Training 2022 (TAT-9): A Changing Eastern Europe: New Challenges for Science and Capacity Building in Land Remote Sensing held in Prague, Czech Republic, from 05-09 September 2022. Access specific videos (click on ), presentation slides (click on ), and exercise data (click on ) from the …
