Linking canopy texture to 3D forest structure and .. (FOTOFor2)
Linking canopy texture to 3D forest structure and above-ground biomass at regional to continental scales in dense tropical forests
Start date: Jul 1, 2010,
End date: Jun 30, 2012
The assessment and monitoring of tropical forest structure and biomass is becoming an important economic and political stake of this century, notably because of the importance of this ecosystem in the carbon cycle. Recent progress may open the way to the large scale monitoring of tropical forests, thanks to VHR optical remote sensing data. We demonstrated the feasibility of a textural characterization of the canopy at the scale of the Amazon basin. Local tests in French Guiana showed that canopy texture correlated to mean trunk diameter, mean tree height and even biomass. Evidence is indeed emerging, for the existence of general scaling laws in tropical forest (e.g. the WBE metabolic theory), linking forests’ structural (among which crown sizes) and dynamical parameters. This progress calls for an ambitious validation program, (i) to test the large scale stability of scaling laws linking apparent crown sizes (observable on VHR imagery) and other structural and dynamical parameters measurable on the ground; and (ii) to understand how the physical signals interact with forest structure to produce canopy texture. The present mobility project, hosted at UMR AMAP in Montpellier, also involves several research labs in the South of France, in the UK as well as actors from the private sector. For (i), we propose a large scale study across Central Africa of the allometry rules linking canopy texture and forest structure and biomass. Relationships with forest dynamics/productivity will be investigated from existing permanent plots. Canopy total height will be assessed using large footprint space borne LIDAR. For (ii), canopy texture will be obtained from 3D models of forest of known structural properties, either obtained via individual based models or measured via airborne small footprint LIDAR. Interaction with physical signals will be modelled to produce canopy texture images under controlled acquisition conditions.
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