Remote Sensing of Biomass - Principles and Applications by T. Fatoyinbo

By T. Fatoyinbo

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IPCC (2003). Good Practice Guidance for Land Use, Land Use Change and Forestry. Institute for Global Environmental Strategies (IGES) for the Intergovernmental Panel on Climate Change. html accessed May 2009. , Heath, L. and Birdsey, R. (2003). National-Scale Biomass Estimators for United States Tree Species, Forest Science, 49(1): 12-35. , Heath, L. and Birdsey, R. (2004). Comprehensive database of diameter-based regressions for North American tree species, United States Department of Agriculture, Forest Service.

Suárez (Editors), Proceedings of SilviLaser 2008: 8th international conference on LiDAR applications in forest assessment and inventory, Edinburgh, UK. ISBN: 978-0-85538774-7. Los, S. , Rosette, J. A. , North, P. R. , Suárez, J. , Hill, R. A. , Chasmer, L. , Mahoney, C. and Berni, J. A. J. (2011). Vegetation height products between 60° S and 60° N from ICESat GLAS data, Geosci. Model Dev. 5194/gmdd-4-2327-2011. , Hyyppä, H. and Vehmas, M. (2004). Estimation of timber volume and stem density based on scanning laser altimetry and expected tree size distribution functions, Remote Sensing of Environment, 90(3): 319-330.

The most remarkable advantage is perhaps the one due to the ability of microwaves to penetrate into semi-transparent media, which makes lower wavelength (L-Band and P-Band, typically) SARs capable of acquiring data almost independently of weather conditions and vegetation density. Conversely, the most relevant drawback is that the three dimensional (3D) reconstruction of the imaged objects requires the exploitation of multiple (at least two, but preferable many) images acquired from different points of view, and hence multiple passes over the scene to be investigated.

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