Theme SD3D - 3D structure and dynamics of tropical forests


The structure of tropical forests can be seen both as a response to environmental drivers, and as an indicator of these drivers and of environmental changes. In the context of increased anthropogenic and climatic pressures on ecosystems and biodiversity, it is crucial to capture the functional diversity of these forests through a better description of their structure. This is the key, for instance, to better assessment of the role of forests in biogeochemical transfers between land surfaces and the atmosphere (carbon source/sinks).

Scientific objectives

The main objective is to assess the current state of forests over broad and poorly known areas of the tropics. A secondary objective is to be able to trace past dynamics in some regions or forest types over a period of several years or decades to understand past changes. The long term overall goal is to build models that allow the prediction of future dynamics.


We build on our capacity to access field sites in the tropics and to acquire relevant data on forest structure. From the resulting historical databases at field sites, we will develop new measurement tools and models of the 3D structure and dynamics of tropical forest stands (mangroves and terra firme forests), to make it possible to render the complexity and heterogeneity of tropical forests at different spatial scales, and to interpret the observed changes. Given the spatial scales involved and the variety of environmental situations, field data need to be complemented by remote sensing tools. To this end, we develop research projects around radar, optical and lidar signals, and participate in the development of future satellite missions dedicated to forest monitoring.
In practice, at the level of individual (including large) trees, we work on improving measurement protocols for e.g. quantifying wood volume, or the shape, plasticity and porosity of tree crowns and foliage distribution. In parallel, at the stand or regional levels, we rely on these individual characteristics while trying to recover emergent system properties through, notably, the analysis of canopy structure.

Expected results

Fine scale maps of forest parameters and improved allometric models for biomass estimations that account for crown plasticity, or quantitative differences between major architectural types of tropical trees. With fine scale maps of terra firme or mangrove forests produced at different dates, it is possible to analyze the effect of environmental drivers. From there, analyses of the spatial diversity at landscape level or the assessment of ecosystem services (carbon and water cycles, wood production, coastal stability, etc.) will be pursued.

Scientific projects

Acronym Title Duration
3DFORMODCombining remote sensing and 3D forest modelling to improve tropical forests monitoring of GHC emissions2017 - 2020
STEMSpatial and temporal dynamics in mangrove carbon pools2016 - 2016
CARBOSHAREASIASharing experience on forest carbon stock assessment and mapping in South Asia2016 - 2017
BIOMAP Intégration de données spatialisées multi-échelles pour la cartographie des types de forêt et de la biomasse en Amapà et Guyane2015 - 2017
FORESTFully Optimised and Reliable Emissions Tool 2014 - 2016
INDESOINDESO project: Mangrove & Integrated Coastal Zone Management Application2013 - 2017
STEM-LEAFSTudies based on Experimental and Modelled wavefor for the LEAF (Lidar for Earth And Forests) mission2013 - 2016

Major publications

  • Bastin, J.-F., Barbier, N., Couteron, P., Adams, B., Shapiro, A., Bogaert, J., De Cannière, C., 2014. Aboveground biomass mapping of African forest mosaics using canopy texture analysis: towards a regional approach. Ecological Applications, 24 (8): 1984-2001. [Editor link]
  • Vincent, G., Sabatier, D., & Rutishauser, E., 2014. Revisiting a universal airborne light detection and ranging approach for tropical forest carbon mapping: scaling-up from tree to stand to landscape. Oecologia, 175 (2) : 439-443. [Editor link]
  • Nascimento Jr, W.R., Souza-Filho, P.W.M., Proisy, C., Lucas, R.M., & Rosenqvist, A., 2013. Mapping changes in the largest continuous Amazonian mangrove belt using object-based classification of multisensor satellite imagery. Estuarine, Coastal and Shelf Science, 117, 83-93. [Editor link]
  • Ploton, P., Pelissier, R., Proisy, C., Flavenot, T., Barbier, N., Rai, S.N., & Couteron, P., 2012. Assessing aboveground tropical forest biomass using Google Earth canopy images. Ecological Applications, 22, 993-1003. [Editor link]
  • Barbier, N., Proisy, C., Véga, C., Sabatier, D., & Couteron, P., 2011. Bidirectional texture function of high resolution optical images of tropical forest: An approach using LiDAR hillshade simulations. Remote Sensing of Environment, 115, 167-179. [Editor link]

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