An analytical four-component directional brightness temperature model for crop and forest canopies
BIAN, Zunjian
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
Joint Center for Global Change Studies
College of Resources and Environment
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
Joint Center for Global Change Studies
College of Resources and Environment
CAO, Biao
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
LI, Hua
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
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State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
BIAN, Zunjian
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
Joint Center for Global Change Studies
College of Resources and Environment
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
Joint Center for Global Change Studies
College of Resources and Environment
CAO, Biao
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
LI, Hua
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
DU, Yongming
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
XIAO, Qing
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
LIU, Qinhuo
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
Joint Center for Global Change Studies
College of Resources and Environment
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State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
Joint Center for Global Change Studies
College of Resources and Environment
Langue
en
Article de revue
Ce document a été publié dans
Remote Sensing of Environment. 2018, vol. 209, p. 731-746
Elsevier
Résumé en anglais
Measurements of surface thermal infrared (TIR) radiance that are made to extract temperatures display strong directional anisotropy effects. Directional brightness temperature (BT) models that describe this anisotropic ...Lire la suite >
Measurements of surface thermal infrared (TIR) radiance that are made to extract temperatures display strong directional anisotropy effects. Directional brightness temperature (BT) models that describe this anisotropic behavior of TIR emissions can be applied to separate component temperatures using multi-angle observations. The surface temperature differences that occur between sunlit and shaded areas and the leaf clumping phenomenon jointly affect the directional signatures of out-of-canopy directional BTs. However, these factors are not fully considered in existing directional BT models. This paper therefore extends the FR97 analytical model to 1) a four-component scene containing sunlit and shaded soil and leaves by incorporating the effective emissivity values of the sunlit and shaded parts and 2) row-planted crop and forest canopies by introducing a leaf clumping index. The proposed model was assessed using a synthetic dataset that was generated by the Thermal Radiosity-Graphics Combined Model (TRGM) under various conditions. The evaluation results indicated that the proposed model performed as well as the Scattering by Arbitrarily Inclined Leaves (4SAIL) model over continuous canopies with root mean squared errors (RMSEs) lower than 0.3 degrees C. Over non-continuous crops and forests, the behavior of the proposed model displayed improved agreement with the TRGM with RMSEs lower than 0.65 degrees C. The proposed model also displayed a robust performance over both the maize and pine canopies, which was evaluated against the directional anisotropy of measured datasets that were collected at the Huailai remote sensing test site and the Institut National de la Recherche Agronomique (INRA), respectively. From these points, the proposed model has potential for component temperature inversion and rapid assessment of TIR angular effects.< Réduire
Mots clés en anglais
directional brightness temperature model
FR97
directional anisotropy
leaf clumping index
Origine
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