The physical structure of vegetation is very important in ecosystem processes. Structure is related to carbon and biomass accumulation, growth dynamics and succession. Biophysical parameters such as tree height, stand and canopy density, crown width and the underlying topography are needed to allow an understanding of ecological processes such as forest productivity, hydrology and land surface-climate interactions. On a global scale forest biomass and surface topography are poorly known and are one of the moisture gently needed factors to allow better estimation of surface processes that affect human well being and sustainability of current ecosystem management practises.
On the light of this, the main objectives of this research are to investigate, derive and develop techniques to better retrieve biophysical parameters (aboveground biomass, surface roughness) through the fusion of Lidar vegetation canopy profiles and optical data, namely bi-directional reflectance distribution function (BRDF). This will be achieved through the development of a vegetation canopy model that combines Lidar 3D canopyprofiles and BRDF data to estimate accurate biophysical parameters. Emphasis will be put on functional relationships. A particular effort will be made to optimise combinationsof di fferent data types to gain maximum synergy. For example polarimetrie SARinterferometry will be compared with Lidar.
Fields of science
- natural sciencescomputer and information sciencessoftware
- natural sciencesearth and related environmental scienceshydrology
- natural sciencesphysical sciencesastronomyplanetary sciencesplanetary geology
- natural sciencesbiological sciencesecologyecosystems
- natural sciencesphysical sciencesopticslaser physics
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