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Modeling three-dimensional forest structures to drive canopy radiative transfer simulations of bidirectional reflectance factor
Authors:Wei Yang  Hideki Kobayashi  Xuehong Chen  Kenlo Nishida Nasahara  Rikie Suzuki  Akihiko Kondoh
Institution:1. Center for Environmental Remote Sensing, Chiba University, Chiba, Japan;2. Department of Environmental Geochemical Cycle Research, Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan;3. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, People’s Republic of China;4. Faculty of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Japan
Abstract:Three-dimensional (3-D) Monte Carlo-based radiative transfer (MCRT) models are usually used for benchmarking in intercomparisons of the canopy radiative transfer (RT) simulations. However, the 3-D MCRT models are rarely applied to develop remote sensing algorithms to estimate essential climate variables of forests, due mainly to the difficulties in obtaining realistic stand structures for different forest biomes over regional to global scales. Fortunately, some of important tree structure parameters such as canopy height and tree density distribution have been available globally. This enables to run the intermediate complexities of the 3-D MCRT models. We consequently developed a statistical approach to generate forest structures with intermediate complexities depending on the inputs of canopy height and tree density. It aims at facilitating applications of the 3-D MCRT models to develop remote sensing retrieval algorithms. The proposed approach was evaluated using field measurements of two boreal forest stands at Estonia and USA, respectively. Results demonstrated that the simulations of bidirectional reflectance factor (BRF) based on the measured forest structures agreed well with the BRF based on the generated structures from the proposed approach with the root mean square error (RMSE) and relative RMSE (rRMSE) ranging from 0.002 to 0.006 and from 0.7% to 19.8%, respectively. Comparison of the computed BRF with corresponding MODIS reflectance data yielded RMSE and rRMSE lower than 0.03 and 20%, respectively. Although the results from the current study are limited in two boreal forest stands, our approach has the potential to generate stand structures for different forest biomes.
Keywords:Bidirectional reflectance factor  remote sensing  forest structure  radiative transfer model
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