Combining remote sensing and 3D forest modelling to improve tropical forests monitoring of greenhouse gases emissions

Project Summary

Deforestation and forest degradation is considered the second largest source of global anthropogenic greenhouse gases (GHG) emissions. While there is a pressing need to go beyond satellite-based land-use and land-cover change (LULCC) survey to accurately monitor carbon stocks in the tropics, there is still no operational integrated framework to achieve this goal. In particular, much uncertainty comes from the difficult evaluation of forest degradation impact, which doesn't entail forest conversion. 3DForMod project aims at integrating advances in 3D forest modelling and very-high-resolution remote sensing technology to improve monitoring of forest aboveground biomass, especially in tropical countries that have signed the Paris Agreement. Our final goal is to supply stakeholders and decision-makers with reliable and accessible information on vegetation carbon stocks in forest territories along with simple predictive, GIS-based models on the consequences of forest degradation in terms of GHG emissions. The consortium of partners allows covering all steps that need to be considered to rigorously scale-up aboveground carbon estimates from tree to forest plot and region. We shall combine: advanced Terrestrial Laser Scanning technology to derive massive tree volume data (WP1) for allometry development without employing destructive harvesting (WP2); 3D forest modelling to link remote sensing information to ground data in order to improve capability of high-resolution satellite data to estimate biomass (WP3) and detect changes and emissions related to forest degradation for regional up-scaling (WP4); collaboration with developing country forest monitoring agencies for integrating project results into their national REDD+ monitoring system and related capacity building with international partners (WP5).

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The Team

Project Management Unit

Raphaël Pélissier, Tropical Forest Ecology, IRD-AMAP lab, Montpellier University, France (coordinator)
Martin Herold, Geoinformation Science and Remote Sensing, Wageningen University and Research, The Netherlands
Pasi Raumonen, Applied Mathematics, Tampere University of Technology, Finland

Project Advisory Board

Jerôme Chave, Tropical Forest Biodiversity, University of Toulouse, France
Uta Berger, Forest Biometrics and Forest System Analysis, Dresden University of Technology, Germany

IRD-AMAP Team, France

Gaëlle Viennois, Geomatics and Remote Sensing

Grégoire Vincent, Tropical Forest Ecology and Remote Sensing
• Jérôme Pérez, Data Management
Maxime Réjou-Méchain, Tropical Forest Ecology and Remote Sensing
Nicolas Barbier, Tropical Forest Ecology and Remote Sensing
Olivier Martin-Ducup , Forest Science
Philippe Verley, Computer Science
Pierre Couteron, Tropical Forest Ecology and Remote Sensing
Pierre Ploton , Tropical Forest Ecology and Remote Sensing
Raphaël Pélissier, Tropical Forest Ecology
Thierry Fourcaud, Applied Mathematics

WUR Team, The Netherlands

Alvaro Lau Sarmiento, Tropical Forest Ecology and Remote Sensing
Harm Bartholomeus, Ecology and Remote Sensing
Martin Herold, Geoinformation Science and Remote Sensing

TUT Team, Finland

Pasi Raumonen, Applied Mathematics

ENS Yaoundé Team, Cameroon

Bonaventure Sonké, Ecology and Systematics
Stéphane Momo Takoudjou, Tropical Forest Ecology and T-LiDAR Remote Sensing

Collaborative Stakeholders

Guyana Forestry Commission
• National REDD+ Coordination Unit, Cameroon
Foundation for Forest Management and Production Control, Suriname

Supportive Bodies

Centre for International Forestry Research
FAO Global Observatory for Forest and Land Cover Dynamics
ESA Biomass mission