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Recent developments in estimating land surface biogeophysical variables from optical remote sensing

Department of Geography, University of Maryland, College Park, MD 20742, USA, sliang{at}geog.umd.edu

Earth system models and many other applications require biogeophysical variables, and remote sensing is the only means by which to estimate them at the appropriate spatial and temporal scales. Developing advanced inversion methods to solve ill-posed multidimensional nonlinear inversion problems is critical and very challenging. This article reviews state-of-the-art algorithms for estimating land surface biogeophysical variables in optical remote sensing (from the visible to the thermal infrared spectrum) to stimulate the development of new algorithms and to utilize existing ones.

Key Words: atmospheric correction • data assimilation • genetic algorithm • look-up table • neural network • reflectance modelling • remote sensing • vegetation index.

Progress in Physical Geography, Vol. 31, No. 5, 501-516 (2007)
DOI: 10.1177/0309133307084626


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