Inversion of the PROSAIL model to estimate leaf area index of maize, potato, and sunflower fields from unmanned aerial vehicle hyperspectral data
作者： Si-Bo Duan , Zhao-Liang Li , Hua Wu , Bo-Hui Tang , Lingling Ma
DOI: 10.1016/J.JAG.2013.05.007
关键词:
摘要: Leaf area index (LAI) is a key variable for modeling energy and mass exchange between the land surface atmosphere. Inversion of physically based radiative transfer models most established technique estimating LAI from remotely sensed data. This study aims to evaluate suitability PROSAIL model estimation three typical row crops (maize, potato, sunflower) unmanned aerial vehicle (UAV) hyperspectral was estimated using look-up table (LUT) on inversion model. The evaluated against in situ measurements. results indicated that LUT-based suitable these crops, with root mean square error (RMSE) approximately 0.62 m(2) m(-2), relative RMSE (RRMSE) 15.5%. Dual-angle observations were also used estimate proved be more accurate than single-angle observations, an 0.55 m(-2) RRMSE 13.6%. demonstrate additional directional information improves performance estimation. (C) 2013 Elsevier B.V. All rights reserved.
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