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SILVA

Satellite-Based Inspection of Large Vegetated Areas

The main objective of SILVA is to detect forest disturbances in near real-time with daily updates in a high spatial resolution of 20 m for the entire area of Switzerland. In addition, annual re-analysis data on forest height and disturbances will be provided for economic and political interpretation. All this information will be directly accessible via multiple services for interested parties.


This project is realized in the framework of the MdP Call for Proposal 2020 (Mesures de Positionnement) by the Swiss Space Center.


Partners: ETH Zurich EcoVision Lab, Swiss Federal Research Institute WSL

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SILVA: Welcome

News

SILVA Accepted for Funding by Swiss Space Center

October 2020

SILVA (Satellite-based Inspection of Large Vegetated Areas) was accepted for funding by the Swiss Space Center. Together with the WSL and the ETH EcoVision Lab, ExoLabs will develop EO-based risk-, damage- and value maps for forests.

SILVA: Nachrichten

Partners

ExoLabs

Main industrial partner

ExoLabs mission is to provide state-of-the-art and user-friendly EO products and services across various spatial and temporal scales.


The team of ExoLabs is entrepreneurial and agile, developing innovative solutions and achieving high performance to meet the broad range of their clients’ needs by using leading-edge technology and best practices.

WSL

Main Research partner

The Swiss Federal Institute for Forest, Snow and Landscape is the main point of contact for applied research in the field of forest management and provides an operational forest monitoring network, survey data, extensive expertise and process understanding.

ETH Zurich
EcoVision Lab

Research partner

ETHZ EcoVision has a strong background in developing deep learning approaches for satellite image interpretation. 

Examples include counting trees of sub-pixel size at a species-specific level in Sentinel 2 satellite images at country- scale and learning aerial image segmentation from online maps.

SILVA: Our Team
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