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A METHOD FOR SPATIAL UPSCALING OF GROUND LAI MEASUREMENTS TO THE REMOTELY SENSED PRODUCT PIXEL GRID

文献类型：会议论文

作者Xu Baodong1,2,3; Li Jing1,3; Liu Qinhuo1,3; Zeng Yelu1,2,3; Yin Gaofei; Fan Weiliang1,3; Zhao Jing1,3
出版日期2016
会议日期JUL 10-15, 2016
会议地点Beijing
关键词Spatial upscaling Leaf Area Index Ground measurements Validation
DOI10.1109/IGARSS.2016.7729912
页码3528-3531
国家PEOPLES R CHINA
英文摘要Leaf area index (LAI) is a critical parameter in many terrestrial ecosystem models. Continuous LAI measurements from global sites are an important dataset for the validation of remotely sensed LAI products. However, the spatial scale mismatch between the site measurement and the product pixel grid hinders the utilization of multi-temporal ground LAI measurements. In this study, a pragmatic method is presented for spatial upscaling of ground LAI measurements to the product pixel grid. The method is divided into three parts: retrieving high-resolution LAI maps, spatial representativeness grading and spatial upscaling. The proposed method was applied to the Jarvselja site in the VALERI project. Results show that this method can reduce the scale mismatch error between the site measurement and the product pixel grid well. Moreover, this method has the potential to be applied to global site LAI measurements, which consequently can improve the reliability of LAI product validation.
产权排序3
会议录2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS)
会议录出版者IEEE
会议录出版地NEW YORK
语种英语
ISSN号2153-6996
ISBN号978-1-5090-3332-4
WOS记录号WOS:000388114603138
源URL[http://ir.imde.ac.cn/handle/131551/35228]  
专题中国科学院水利部成都山地灾害与环境研究所
通讯作者Xu Baodong
作者单位1.State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, 100101, China;
2.University of Chinese Academy of Sciences, Beijing, 100049, China;
3.Joint Center for Global Change Studies (JCGCS), Beijing; 100875, China
推荐引用方式
GB/T 7714		 Xu Baodong,Li Jing,Liu Qinhuo,et al. A METHOD FOR SPATIAL UPSCALING OF GROUND LAI MEASUREMENTS TO THE REMOTELY SENSED PRODUCT PIXEL GRID[C]. 见:. Beijing. JUL 10-15, 2016.

入库方式： OAI收割

来源：成都山地灾害与环境研究所

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