A CANOPY RADIATIVE TRANSFER MODEL SUITABLE FOR HETEROGENEOUS AGRO-FORESTRY SCENES

被引:1
|
作者
Zeng, Yelu [1 ,2 ,3 ]
Li, Jing [1 ,2 ]
Liu, Qinhuo [1 ,2 ]
Yin, Gaofei [1 ,4 ]
Xu, Baodong [1 ,3 ]
Fan, Weiliang [1 ]
Zhao, Jing [1 ]
机构
[1] Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China
[2] Joint Ctr Global Change Studies, Beijing 100875, Peoples R China
[3] Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
[4] Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu 610041, Peoples R China
基金
中国国家自然科学基金;
关键词
Landscape heterogeneity; Canopy structure; Radiative transfer; Hemispherical-directional reflectance factor (HDRF); Agro-forestry system; LEAF-AREA INDEX; REFLECTANCE;
D O I
10.1109/IGARSS.2016.7729945
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Landscape heterogeneity is a common natural phenomenon but is seldom considered in current radiative transfer models for predicting the surface reflectance. This paper developed an analytical Radiative Transfer model for heterogeneous Agro-Forestry scenes (RTAF). The scattering contribution of the non-boundary regions can be estimated from the SAILH model as homogeneous canopies, whereas that of the boundary regions is calculated based on the bidirectional gap probability by considering the interactions and mutual shadowing effects among different patches. The multiangular airborne observations and Discrete Anisotropic Radiative Transfer (DART) model simulations were used to validate and evaluate the RTAF model over an agro-forestry scene in Heihe River Basin, China. The results suggest the RTAF model can accurately simulate the hemisphericaldirectional reflectance factors (HDRFs) of the heterogeneous scenes in the red and near-infrared (NIR) bands. The boundary effect can significantly influence the angular distribution of the HDRFs and consequently enlarge the HDRF variations between the backward and forward directions. Compared with the widely used dominant cover type (DCT) and spectral linear mixture (SLM) models, the RTAF model reduced the maximum relative error from 25.7% (SLM) and 23.0% (DCT) to 9.8% in the red band, and from 19.6% (DCT) and 13.7% (SLM) to 8.7% in the NIR band. The RTAF model provides a promising way to improve the retrieval of biophysical parameters (e. g. leaf area index) from remote sensing data over heterogeneous agro-forestry scenes.
引用
收藏
页码:3648 / 3651
页数:4
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