Journal of Remote Sensing (Jan 2023)

Explicitly Reconstructing RAMI-V Scenes for Accurate 3-Dimensional Radiative Transfer Simulation Using the LESS Model

  • Kun Zhou,
  • Donghui Xie,
  • Jianbo Qi,
  • Zhixiang Zhang,
  • Xinyu Bo,
  • Guangjian Yan,
  • Xihan Mu

DOI
https://doi.org/10.34133/remotesensing.0033
Journal volume & issue
Vol. 3

Abstract

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Radiative transfer (RT) simulation based on reconstructed 3-dimensional (3D) vegetation scenarios can promote the validation and development of various retrieval algorithms to monitor the growing states of vegetation in large-scale, multi-angular, and multi-sensor ways. The radiation transfer model intercomparison (RAMI) has made great contributions to providing abstract and actual 3D vegetation scenarios, and to the benchmarking of RT models under developed evaluation systems. To date, RAMI has been updated to the fifth phase (RAMI-V). In this study, we try to implement explicit conversion from all the RAMI-V scenes to generic structural models in the Wavefront OBJ format. These reconstructed scenes are applied in the LESS RT model to probe the ability of its RT solvers to simulate all sorts of remote sensing observations and radiative budget, including the bidirectional reflectance factor (BRF), albedo, fraction of photosynthetically active radiation absorbed by vegetation, and threshold hemispherical photograph (THP). BRF simulations fully explain angle effects as well as variation and robustness of the normalized difference vegetation index. Energy conservation is well validated between simulated absorption and albedo. The gap fraction derived from THP is analyzed in directional and total situations. In addition, this paper guides us how to simplify basic geometries and tune the illumination resolution (0.02 is optimal) to balance the simulation accuracy and efficiency. The generic structural models and reliable simulation results can be referenced by other RT models and retrieval algorithms.