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水稻多组分双向反射模型的研究
引用本文:申广荣,王人潮. 水稻多组分双向反射模型的研究[J]. 应用生态学报, 2003, 14(3): 394-398
作者姓名:申广荣  王人潮
作者单位:1. 上海交通大学农业生态学院,上海,201113;浙江大学农业遥感与信息技术应用研究所,杭州,310029
2. 浙江大学农业遥感与信息技术应用研究所,杭州,310029
基金项目:国家自然科学基金资助项目 (4 0 1710 6540 2 710 78)
摘    要:利用1999-2000年的水稻田间试验实测光谱数据,对水稻不同生长期特性建立的水稻多组分双向反向模型进行了一些主要因子的敏感性分析及模型模拟值与实测值的比较分析。结果表明,考虑水稻冠层叶、茎干、穗等作用及水稻不同生长期特点的水稻多组分双向反向模型,能较好地反映水稻多组分反向光谱的角度分布特征,较准确地模拟水稻不同条件下水稻的自然方向反向系数和冠层"热点"效应的非对称性分布。得到了薄层水体和土壤背景的一次反向辐射以及在冠层内部、薄层水体和土壤表面相互间的多次反向辐射随水稻各组分平均倾角的变化规律,冠层双向反向率随叶面积指数LAI的变化特征。

关 键 词:多角度遥感 多组分双向反射模型 叶面积指数 水稻
文章编号:1001-9332(2003)03-0394-05
修稿时间:2001-01-15

A study on multicomponent bidirectional reflectance model for rice
SHEN Guangrong ,,WANG Rencao. A study on multicomponent bidirectional reflectance model for rice[J]. The journal of applied ecology, 2003, 14(3): 394-398
Authors:SHEN Guangrong     WANG Rencao
Affiliation:School of Agriculture and Biology, Shanghai Jiaotong University, Shanghai 201101, China. shenguangrong@163.net
Abstract:In this paper, the bidirectional reflectance factor (BRF) of rice measured in field experiment in 1999 and 2000 was compared with the BRF computed from the rice multicomponent bidirectional reflectance model that based on the radiative transfer theory, rice canopy geometric structural factors and different characteristics of the different growth period for rice in detail. The contribution of some sensitive factors such as the average inclination angle of all components belonged to rice and LAI was accurately specified. The results showedthat the rice multicomponent bidirectional reflectance model described above could basically simulate the angular distribution characteristic of reflectance spectrum of rice canopies, and the different peak point of the hotspot effect of rice canopies reached under different conditions. In addition, the regulation of the first order scattering reflectance by soil and water and the multiple scattering reflectance by foliage, stem, fringe and soil changing with the average inclination angle of all components, as well as the contribution of LAI to BRF were analyzed. All of these laid a foundation to monitor rice growth and estimate its yield. Meanwhile, it also implied that some rice canopy parameters could be accurately estimated by the model through selecting the suitable image bands.
Keywords:Multiangle remote sensing   Multicomponent bidirectional reflectance distribution model   Leaf area index   Rice.
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