中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 烟台海岸带研究所
  3. 中国科学院烟台海岸带研究所
  4. 中科院海岸带环境过程与生态修复重点实验室
  5. 海岸带信息集成与综合管理实验室
Estimation of BRDF model kernel weights under an a priori knowledge-aided constraint

文献类型：期刊论文

作者Tian, Xinpeng2,3; Gao, Zhiqiang2,3; Liu, Qiang1,4,5; Wang, Yueqi2,3; Li, Xiuhong1,4,5
刊名REMOTE SENSING LETTERS
出版日期2021-02-01
卷号12期号:2页码:146-155
ISSN号2150-704X
DOI10.1080/2150704X.2020.1823036
通讯作者Gao, Zhiqiang(zqgao@yic.ac.cn)
英文摘要The reflectance anisotropy of land surface serves as an important bridge between surface biophysical parameters and remote sensing observations. It can characterize by the linear kernel-driven bidirectional reflectance distribution function (BRDF), which is the combination of several kernel functions and kernel weights. These kernel weights can be estimated by remote sensing; however, the stability of current kernel weights products is still challenging, especially in urban areas with complex aerosol properties and heterogeneous surfaces. In this paper, we propose a method for robust estimation of kernel weights from the Moderate Resolution Imaging Spectroradiometer (MODIS) surface spectral reflectance products (MxD09GA) data based on the constrained least-squares method (CLSM) and a priori knowledge. The kernel weights data were obtained by the CLSM from 2014 to 2017 in Beijing region of China. Validations were carried out using the MxD09GA and BRDF/Albedo products (MCD43A1). The results show that the time series of kernel weights by the CLSM show small variability over different land cover types. The kernel weights estimated by the CLSM can clearly show the phenological signal and fitting ability of surface spectral reflectance is better than that of the MCD43A1 products in Beijing urban area. Experimental results demonstrate that the CLSM has the potential for the robust estimation of kernel weights in urban areas.
资助项目National Natural Science Foundation of China[41876107] ; NSFC-Shandong joint fund project[U1706219] ; Key Deployment Project of Centre for Ocean Mega-Research of Science, Chinese Academy of Science[COMS2019J02] ; Key Research Program of Frontier Science, Chinese Academy of Sciences[ZDBS-LY-7010] ; National Key Research and Development Program[2016YFA0600102] ; Open Fund of CAS Key Laboratory of Marine Ecology and Environmental Sciences[KLMEES202005] ; National Key Research and Development Program of China[2016YFA0600102]
WOS研究方向Remote Sensing ; Imaging Science & Photographic Technology
语种英语
WOS记录号WOS:000609535800001
资助机构National Natural Science Foundation of China ; NSFC-Shandong joint fund project ; Key Deployment Project of Centre for Ocean Mega-Research of Science, Chinese Academy of Science ; Key Research Program of Frontier Science, Chinese Academy of Sciences ; National Key Research and Development Program ; Open Fund of CAS Key Laboratory of Marine Ecology and Environmental Sciences ; National Key Research and Development Program of China
源URL[http://ir.yic.ac.cn/handle/133337/27411]  
专题烟台海岸带研究所_海岸带信息集成与综合管理实验室
烟台海岸带研究所_中科院海岸带环境过程与生态修复重点实验室
通讯作者Gao, Zhiqiang
作者单位1.Beijing Normal Univ, State Key Lab Remote Sensing Sci, Beijing, Peoples R China
2.Chinese Acad Sci, Shandong Key Lab Coastal Environm Proc, Yantai Inst Coastal Zone Res, Yantai, Peoples R China
3.Chinese Acad Sci, CAS Key Lab Coastal Environm Proc & Ecol Remediat, Yantai Inst Coastal Zone Res, Yantai, Peoples R China
4.Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing, Peoples R China
5.Beijing Normal Univ, Coll Global Change & Earth Syst Sci, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Tian, Xinpeng,Gao, Zhiqiang,Liu, Qiang,et al. Estimation of BRDF model kernel weights under an a priori knowledge-aided constraint[J]. REMOTE SENSING LETTERS,2021,12(2):146-155.
APA Tian, Xinpeng,Gao, Zhiqiang,Liu, Qiang,Wang, Yueqi,&Li, Xiuhong.(2021).Estimation of BRDF model kernel weights under an a priori knowledge-aided constraint.REMOTE SENSING LETTERS,12(2),146-155.
MLA Tian, Xinpeng,et al."Estimation of BRDF model kernel weights under an a priori knowledge-aided constraint".REMOTE SENSING LETTERS 12.2(2021):146-155.

入库方式： OAI收割

来源：烟台海岸带研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。