Wireless Sensor Network of Typical Land Surface Parameters and Its Preliminary Applications for Coarse-Resolution Remote Sensing Pixel
How to obtain the “truth” of land surface parameter as reference value to validate the remote sensing retrieved parameter in heterogeneous scene and coarse-resolution pixel is one of the most challenging topics in environmental studies. In this paper, a distributed sensor network system named CPP-WS...
Main Authors: | , , , , , , , , , , , , , , , |
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Format: | Article |
Language: | English |
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SAGE Publishing
2016-04-01
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Series: | International Journal of Distributed Sensor Networks |
Online Access: | https://doi.org/10.1155/2016/9639021 |
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doaj-1dcc759b0d604622b3351d53df81ca6d |
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record_format |
Article |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Baocheng Dou Jianguang Wen Xiuhong Li Qiang Liu Jingjing Peng Qing Xiao Zhigang Zhang Yong Tang Xiaodan Wu Xingwen Lin Dongqin You Hua Li Li Li Yelu Zeng Erli Cai Jialin Zhang |
spellingShingle |
Baocheng Dou Jianguang Wen Xiuhong Li Qiang Liu Jingjing Peng Qing Xiao Zhigang Zhang Yong Tang Xiaodan Wu Xingwen Lin Dongqin You Hua Li Li Li Yelu Zeng Erli Cai Jialin Zhang Wireless Sensor Network of Typical Land Surface Parameters and Its Preliminary Applications for Coarse-Resolution Remote Sensing Pixel International Journal of Distributed Sensor Networks |
author_facet |
Baocheng Dou Jianguang Wen Xiuhong Li Qiang Liu Jingjing Peng Qing Xiao Zhigang Zhang Yong Tang Xiaodan Wu Xingwen Lin Dongqin You Hua Li Li Li Yelu Zeng Erli Cai Jialin Zhang |
author_sort |
Baocheng Dou |
title |
Wireless Sensor Network of Typical Land Surface Parameters and Its Preliminary Applications for Coarse-Resolution Remote Sensing Pixel |
title_short |
Wireless Sensor Network of Typical Land Surface Parameters and Its Preliminary Applications for Coarse-Resolution Remote Sensing Pixel |
title_full |
Wireless Sensor Network of Typical Land Surface Parameters and Its Preliminary Applications for Coarse-Resolution Remote Sensing Pixel |
title_fullStr |
Wireless Sensor Network of Typical Land Surface Parameters and Its Preliminary Applications for Coarse-Resolution Remote Sensing Pixel |
title_full_unstemmed |
Wireless Sensor Network of Typical Land Surface Parameters and Its Preliminary Applications for Coarse-Resolution Remote Sensing Pixel |
title_sort |
wireless sensor network of typical land surface parameters and its preliminary applications for coarse-resolution remote sensing pixel |
publisher |
SAGE Publishing |
series |
International Journal of Distributed Sensor Networks |
issn |
1550-1477 |
publishDate |
2016-04-01 |
description |
How to obtain the “truth” of land surface parameter as reference value to validate the remote sensing retrieved parameter in heterogeneous scene and coarse-resolution pixel is one of the most challenging topics in environmental studies. In this paper, a distributed sensor network system named CPP-WSN was established to capture the spatial and temporal variation of land surface parameters at coarse-resolution satellite pixel scale around the Huailai Remote Sensing Station, which locates in the North China Plain. The system consists of three subnetworks that are RadNet, SoilNet, and VegeNet. Time series observations of typical land surface parameters, including UVR, PAR, SWR, LWR, albedo, and land surface temperature (LST) from RadNet, multilayer soil moisture and soil temperature from SoilNet, and fraction of vegetation cover (FVC), clumping index (CI), and leaf area index (LAI) from VegeNet, have been obtained and shared on the web. Compared with traditional single-point measurement, the “true” reference value of coarse pixel is obtained by averaging or representativeness-weighted averaging the multipoint measurements acquired using the sensor network. The preliminary applications, which validate several remote sensing products with CPP-WSN data, demonstrate that a high quality ground “truth” dataset has been available for remote sensing as well as other applications. |
url |
https://doi.org/10.1155/2016/9639021 |
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doaj-1dcc759b0d604622b3351d53df81ca6d2020-11-25T03:28:29ZengSAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772016-04-011210.1155/2016/9639021Wireless Sensor Network of Typical Land Surface Parameters and Its Preliminary Applications for Coarse-Resolution Remote Sensing PixelBaocheng Dou0Jianguang Wen1Xiuhong Li2Qiang Liu3Jingjing Peng4Qing Xiao5Zhigang Zhang6Yong Tang7Xiaodan Wu8Xingwen Lin9Dongqin You10Hua Li11Li Li12Yelu Zeng13Erli Cai14Jialin Zhang15 State Key Laboratory of Remote Sensing Science, The Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences and Beijing Normal University, No. 20 North, DaTun Road, ChaoYang District, Beijing 100101, China State Key Laboratory of Remote Sensing Science, The Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences and Beijing Normal University, No. 20 North, DaTun Road, ChaoYang District, Beijing 100101, China State Key Laboratory of Remote Sensing Science, The Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences and Beijing Normal University, No. 20 North, DaTun Road, ChaoYang District, Beijing 100101, China State Key Laboratory of Remote Sensing Science, The Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences and Beijing Normal University, No. 20 North, DaTun Road, ChaoYang District, Beijing 100101, China Institute of Remote Sensing and GIS, Peking University, Beijing 100871, China State Key Laboratory of Remote Sensing Science, The Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences and Beijing Normal University, No. 20 North, DaTun Road, ChaoYang District, Beijing 100101, China State Key Laboratory of Remote Sensing Science, The Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences and Beijing Normal University, No. 20 North, DaTun Road, ChaoYang District, Beijing 100101, China State Key Laboratory of Remote Sensing Science, The Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences and Beijing Normal University, No. 20 North, DaTun Road, ChaoYang District, Beijing 100101, China State Key Laboratory of Remote Sensing Science, The Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences and Beijing Normal University, No. 20 North, DaTun Road, ChaoYang District, Beijing 100101, China State Key Laboratory of Remote Sensing Science, The Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences and Beijing Normal University, No. 20 North, DaTun Road, ChaoYang District, Beijing 100101, China State Key Laboratory of Remote Sensing Science, The Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences and Beijing Normal University, No. 20 North, DaTun Road, ChaoYang District, Beijing 100101, China State Key Laboratory of Remote Sensing Science, The Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences and Beijing Normal University, No. 20 North, DaTun Road, ChaoYang District, Beijing 100101, China State Key Laboratory of Remote Sensing Science, The Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences and Beijing Normal University, No. 20 North, DaTun Road, ChaoYang District, Beijing 100101, China State Key Laboratory of Remote Sensing Science, The Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences and Beijing Normal University, No. 20 North, DaTun Road, ChaoYang District, Beijing 100101, China College of Global Change and Earth System Science, Beijing Normal University, No. 19 Xinjiekou Wai Street, Haidian District, Beijing 100875, China College of Global Change and Earth System Science, Beijing Normal University, No. 19 Xinjiekou Wai Street, Haidian District, Beijing 100875, ChinaHow to obtain the “truth” of land surface parameter as reference value to validate the remote sensing retrieved parameter in heterogeneous scene and coarse-resolution pixel is one of the most challenging topics in environmental studies. In this paper, a distributed sensor network system named CPP-WSN was established to capture the spatial and temporal variation of land surface parameters at coarse-resolution satellite pixel scale around the Huailai Remote Sensing Station, which locates in the North China Plain. The system consists of three subnetworks that are RadNet, SoilNet, and VegeNet. Time series observations of typical land surface parameters, including UVR, PAR, SWR, LWR, albedo, and land surface temperature (LST) from RadNet, multilayer soil moisture and soil temperature from SoilNet, and fraction of vegetation cover (FVC), clumping index (CI), and leaf area index (LAI) from VegeNet, have been obtained and shared on the web. Compared with traditional single-point measurement, the “true” reference value of coarse pixel is obtained by averaging or representativeness-weighted averaging the multipoint measurements acquired using the sensor network. The preliminary applications, which validate several remote sensing products with CPP-WSN data, demonstrate that a high quality ground “truth” dataset has been available for remote sensing as well as other applications.https://doi.org/10.1155/2016/9639021 |