Eloi Grau

Biomass prediction in tropical forests: the canopy grain approach

The challenging task of biomass prediction in dense and heterogeneous tropical forest requires a multi-parameter and multi-scale characterization of forest canopies. Completely different forest structures may indeed present similar above ground biomass (AGB) values. This is probably one of the reasons explaining why tropical AGB still resists accurate mapping through remote sensing techniques. There is a clear need to combine optical and radar remote sensing to benefit from their complementary responses to forest characteristics. Radar and Lidar signals are rightly considered to provide adequate measurements of forest structure because of their capability of penetrating and interacting with all the vegetation strata. However, signal saturation at the lowest radar frequencies is observed at the midlevel of biomass range in tropical forests (Mougin et al. 1999; Imhoff, 1995). Polarimetric Interferometric (PolInsar) data could improve the inversion algorithm by injecting forest interferometric height into the inversion of P-band HV polarization signal. Within this framework, the TROPISAR mission, supported by the Centre National d’Etudes Spatiales (CNES) for the preparation of the European Space Agency (ESA) BIOMASS program is illustrative of both the importance of interdisciplinary research associating forest ecologists and physicists and the importance of combined measurements of forest properties. Lidar data is a useful technique to characterize the vertical profile of the vegetation cover, (e.g. Zhao et al. 2009) which in combination with radar (Englhart et al. 2011) or optical (e.g. Baccini et al. 2008; Asner et al. 2011) and field plot data may allow vegetation carbon stocks to be mapped over large areas of tropical forest at different resolution scales ranging from 1 hectare to 1 km2. However, small-footprint Lidar data are not yet accessible over sufficient extents and with sufficient revisiting time because its operational use for tropical studies remains expensive. At the opposite, very-high (VHR) resolution imagery, i.e. approximately 1-m resolution, provided by recent satellite like Geoeye, Ikonos, Orbview or Quickbird as well as the forthcoming Pleiades becomes widely available at affordable costs, or even for free in certain regions of the world through Google Earth®. Compared to coarser resolution imagery with

DART: A 3D Model for Remote Sensing Images and Radiative Budget of Earth Surfaces

Modeling the radiative behavior and the energy budget of land surfaces is relevant for many scientific domains such as the study of vegetation functioning with remotely acquired information. DART model (Discrete Anisotropic Radiative Transfer) is developed since 1992. It is one of the most complete 3D models in this domain. It simulates radiative transfer (R.T.) in the optical domain: 3D radiative budget and remote sensing images (i.e., radiance, reflectance, brightness temperature) of vegetation and urban Earth surfaces, for any atmosphere, wavelength, sun/view direction, altitude and spatial resolution. It uses an innovative multispectral approach (flux tracing, exact kernel, discrete ordinate techniques) over the whole optical domain. Here, its potential is illustrated with the case of urban and tropical forest canopies. Moreover, three recent improvements in terms of functionality and operability are presented: account of Earth/Atmosphere curvature for oblique remote sensing measurements, importation of 3D objects simulated as the juxtaposition of triangles with the possibility to transform them into 3D turbid objects, and R.T. simulation in landscapes that have a continuous topography and landscapes that are non repetitive. Finally, preliminary results concerning two application domains are presented. 1) 2D distribution of the reflectance, brightness temperature and radiance measured by a geostationary satellite over a whole continent. 2) 3D radiative budget of natural and urban surfaces with a DART energy budget (EB) component that is being developed. This new model, called DARTEB, is intended to simulate the energy budget of land surfaces.

Simulating satellite waveform Lidar with DART model

DART model was extended for simulating satellite Lidar data of 3D Earth scenes with Monte Carlo based methods. 2 major modeling methods were developed. (1) Monte Carlo method for efficiently handling complex phase functions: once scattering directions with close occurrence probabilities are grouped within classes, a 1st random pulling gives the class of scattering directions, and a 2nd random pulling gives the scattering direction within the class. (2) A so-called RayCarlo method combines the classical Monte Carlo forward photon tracing method and the flux tracking method, which allows one to decrease computer time of classical Monte Carlo method by factors that can reach 108. Simulation results are very encouraging. Validation tests are being conducted.

Lidar radiative transfer modeling in the Atmosphere

DART model was extended for simulating satellite lidar signal of Earth-Atmosphere systems. The adopted approach combines Monte Carlo and flux tracking methods. It improves a lot signal to noise ratios of simulated waveforms. For accurate simulation of atmosphere photon tracing, the atmosphere modelling was modified for obtaining continuous vertical distribution of extinction coefficients. It leads to a much better accuracy than the use of atmosphere layers with constant extinction coefficients. This improvement is valid with any type of atmosphere, exponential or not.