Optimal Nodes Selectiveness from WSN to Fit Field Scale Albedo Observation and Validation in Long Time Series in the Foci Experiment Areas, Heihe
文献类型：期刊论文
| 作者 | Wu, Xiaodan1; Xiao, Qing1; Wen, Jianguang1; Liu, Qiang1; You, Dongqin1; Dou, Baocheng1; Tang, Yong1; Li, Xiaowen1 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2015 |
| 卷号 | 7期号:11页码:273-281 |
| 关键词 | coarse scale albedo heterogeneous long time series validation |
| 通讯作者 | Xiao, Q (reprint author), Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, 20A Datun Rd, Beijing 100101, Peoples R China. |
| 英文摘要 | To evaluate and improve the quality of land surface albedo products, validation with ground measurements of albedo is crucial over the spatially and temporally heterogeneous land surface. One of the essential steps for satellite albedo product validation is coarse scale observation technique development with long time ground-based measurements. In this paper, the optimal nodes were selected from the wireless sensor network (WSN) to perform observation at large scale and in longer time series for validation of albedo products. The relative difference is used to analyze the spatiotemporal representativeness of each node. The random combination method is used to assess the number of required sites (NRS) and then to identify the most representative combination (MRC). On this basis, an upscaling transform function with different weights for each node in the MRC, which are calculated with the ordinary least squares (OLS) linear regression method, is used to upscale WSN node albedo from point scale to the field scale. This method is illustrated by selecting the optimal nodes and upscaling surface albedo from point observation to the field scale in the Heihe River basin, China. Primary findings are: (a) The method of reducing the number of observations without significant loss of information about surface albedo at field scale is feasible and effective; (b) When only few sensors are available, the most representative locations in time and space should be the first priority; when a number of sensors are available in the heterogeneous land surface, it is preferable to install them in different land surface, rather than the most representative locations; (c) The most representative combination (MRC) combined with the upscaling weight coefficients can give a robust estimate of the field mean surface albedo. These efforts based on ground albedo observations promote the chance to use point information for validation of coarse scale albedo products. Moreover, a preliminary validation of the MODIS (Moderate Resolution Imaging Spectroradiometer) albedo product was performed as the tentative application for upscaling predictions. |
| 研究领域[WOS] | Remote Sensing |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:000366185200022 |
| 源URL | [http://ir.ceode.ac.cn/handle/183411/38072]  |
| 专题 | 遥感与数字地球研究所_SCI/EI期刊论文_期刊论文 |
| 作者单位 | 1.[Wu, Xiaodan 2.Xiao, Qing 3.Wen, Jianguang 4.You, Dongqin 5.Dou, Baocheng 6.Tang, Yong] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China 7.[Wu, Xiaodan] Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China 8.[Wen, Jianguang] Joint Ctr Global Change Studies, Beijing 100875, Peoples R China 9.[Liu, Qiang 10.Li, Xiaowen] Beijing Normal Univ, Coll Global Change & Earth Syst Sci, Beijing 100875, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wu, Xiaodan,Xiao, Qing,Wen, Jianguang,et al. Optimal Nodes Selectiveness from WSN to Fit Field Scale Albedo Observation and Validation in Long Time Series in the Foci Experiment Areas, Heihe[J]. REMOTE SENSING,2015,7(11):273-281. |
| APA | Wu, Xiaodan.,Xiao, Qing.,Wen, Jianguang.,Liu, Qiang.,You, Dongqin.,...&Li, Xiaowen.(2015).Optimal Nodes Selectiveness from WSN to Fit Field Scale Albedo Observation and Validation in Long Time Series in the Foci Experiment Areas, Heihe.REMOTE SENSING,7(11),273-281. |
| MLA | Wu, Xiaodan,et al."Optimal Nodes Selectiveness from WSN to Fit Field Scale Albedo Observation and Validation in Long Time Series in the Foci Experiment Areas, Heihe".REMOTE SENSING 7.11(2015):273-281. |
入库方式： OAI收割
来源：遥感与数字地球研究所
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