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Novel techniques for biomass change mapping by an EU project

We are pleased to present the goals, contents, progress and opportunities of the EU research project The Advanced Techniques for Forest Biomass and Biomass Change Mapping Using Novel Combination of Active Remote Sensing Sensors (Advanced_SAR) on this webpage. Welcome!



In this project we seek to establish the leading position in forest biomass and biomass change mapping and significantly contribute to the creation of the market growth in precision forestry business, which would benefit all forest owners in the EU. The project will also contribute to enhancing of the competitiveness of the European industry by closing the gap between research and business. Read more about our work here

More information: Juha Hyyppä: juha.coelasr(at)gmail.com / Mika.Karjalainen(at)nls.fi


Latest news

Advanced SAR project reviewed (28.3.2017)

Advanced SAR project at the 2nd GlobBiomass User Workshop (2.2.2017)

FGI-Tomoradar development and first results published in MDPI Remote Sensing (10.1.2017)

INSPIRE conference in Barcelona (31.10.2016)

FGI's AkhkaR3 in action (22.8.2016)

Dragon symposium in Wuhan, China (11.7.2016)

Testing FGI-Tomoradar in Evo, Finland (6.6.2016)

New deliverable available online (2.5.2016)

Forest map from the TanDEM-X (22.4.2016)

2nd reporting period progress reviewed (19.4.2016)

Publications from Advanced_SAR team updated (13.4.2016)

New video on deriving forest biomass with Mobile Laser Scanning (MLS) available (31.3.2016)

New deliverables (19.10.2015)

Publications from Advanced_SAR team updated (11.8.2015)

Advanced_SAR work reviewed (2.6.2015)

Advanced_SAR research results presented in the 36th International symposium on Remote Sensing of Environment (29.5.2015)

Mapping forests using SAR satellite imagery has potential for cost-effective wide area forest inventories (14.4.2015)

First year progress reviewed (24.11.2014)

New deliverables (13.10.2014)

Advanced_SAR research present in Dragon Symposium, China (13.6.2014)

The research leading to these results has received funding from the European Community's Seventh Framework Programme ([FP7/2007-2013]) under grant agreement no 606971