**7. References**


30 Will-be-set-by-IN-TECH

The correct identification of physical models for such two SMs has been shown to be subject to an ambiguity, mostly associated with the possibility that depolarized contributions occur at the ground level as well. Furthermore, the correct retrieval of volume top height has been shown not to constitute a meaningful tool for model validation, being substantially invariant to the choice of the solution for volume scattering. In this framework it is then clear that tomographic imaging represents a most valuable tools for the assesment of physical models of the forest structure, as it allows to *see* what kind of vertical structure is actually associated

I wish to acknowledge insights and valuable discussions with Prof. Fabio Rocca, Prof. Andrea Monti Guarnieri, and eng. Mauro Mariotti d'Alessandro at Politecnico di Milano. I also wish to thank to Dr. Malcom Davidson (ESA), Dr. Irena Hajnsek (DLR), Dr. Kostas Papathanassiou (DLR), Dr. Fabrizio Lombardini (Universitè di Pisa), Prof. Lars Ulander (FOI), Dr. Pascale Dubois-Fernandez (ONERA), Dr. Thuy Le Toan (CESBIO) with whom I have discussed many

[1] J. C. Curlander and R. N. McDonough, *Synthetic aperture radar: systems and signal*

[2] G. Franceschetti and R. Lanari, Eds., *Synthetic Aperture Radar processing*. CRC Press,

[3] F. Rocca, "Synthetic aperture radar: A new application for wave equation techniques,"

[4] R. Bamler, "A comparison of range-Doppler and wave-number domain SAR focusing algorithms," *IEEE Transactions on Geoscience and Remote Sensing*, vol. 30, no. 4, pp.

[5] R.-S. Wu and M.-N. Toksᅵz, "Diffraction tomography and multisource holography

[6] A. Reigber and A. Moreira, "First demonstration of airborne SAR tomography using multibaseline l-band data," *IEEE Trans. on Geoscience and Remote Sensing*, pp. 2142–2152,

[7] R. Bamler and P. Hartl, "Synthetic aperture radar interferometry," *Inverse Problems*,

[8] F. Ulaby, K. McDonald, K. Sarabandi, and M. Dobson, "Michigan microwave canopy scattering models (mimics)," *Geoscience and Remote Sensing Symposium, 1988. IGARSS '88. Remote Sensing: Moving Toward the 21st Century., International*, vol. 2, pp. 1009–1009, Sep

[9] G. Smith-Jonforsen, L. Ulander, and X. Luo, "Low vhf-band backscatter from coniferous forests on sloping terrain," *Geoscience and Remote Sensing, IEEE Transactions on*, vol. 43,

[10] L. Thirion, E. Colin, and C. Dahon, "Capabilities of a forest coherent scattering model applied to radiometry, interferometry, and polarimetry at p- and l-band," *Geoscience and*

[11] Y.-C. Lin and K. Sarabandi, "Electromagnetic scattering model for a tree trunk above a tilted ground plane," *Geoscience and Remote Sensing, IEEE Transactions on*, vol. 33, no. 4,

*Remote Sensing, IEEE Transactions on*, vol. 44, no. 4, pp. 849–862, April 2006.

*processing*. New York: John Wiley & Sons, Inc, 1991.

*Stanford Exploration Project Report*, vol. SEP-56, pp. 167–189, 1987.

applied to seismic imaging," *Geophysics*, vol. 52, pp. 11–+, Jan. 1987.

with the chosen model.

**6. Acknowledgment**

**7. References**

1999.

of the results within this chapter.

706–713, Jul. 1992.

vol. 14, pp. R1–R54, 1998.

no. 10, pp. 2246–2260, Oct. 2005.

pp. 1063–1070, Jul 1995.

Sep. 2000.

1988.


**3** 

*France* 

**Biomass Prediction in Tropical Forests:** 

*1Institut de Recherche pour le Développement (IRD), UMR AMAP 2Institut National de la Recherche Agronomique (INRA), UMR AMAP* 

Christophe Proisy1, Nicolas Barbier1, Michael Guéroult2, Raphael Pélissier1,

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

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

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

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

and physicists and the importance of combined measurements of forest properties.

**1. Introduction** 

with all the vegetation strata.

remains expensive.

Jean-Philippe Gastellu-Etchegorry3, Eloi Grau3 and Pierre Couteron1

**The Canopy Grain Approach** 

*3Université Paul Sabatier, UMR CESBIO* 

