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遥感技术与应用  2015, Vol. 30 Issue (4): 667-676    DOI: 10.11873/j.issn.1004-0323.2015.4.0667
模型与反演     
ASAR GM后散时间序列数据估算黑河上游地表土壤水分
董淑英1,2,3,晋锐1,3,亢健1,2,李大治1,2
(1.中国科学院寒区旱区环境与工程研究所,甘肃 兰州 730000;
2.中国科学院大学,北京 100049;
3.中国科学院黑河遥感试验研究站,甘肃 兰州 730000)
Estimation of High\|resolution Soil Moisture by Using ENVISAT/ASAR Global Mode Backscattering in the Upper Reaches of Heihe River Basin
Dong Shuying1,2,3,Jin Rui1,3,Kang Jian1,2,Li Dazhi1,2
( 1.Cold and Arid Regions Environment and Engineering Research Institute,
Chinese Academy of Sciences,Lanzhou 730000,China;
2.University of Chinese Academy of Sciences,Beijing 100049,China;
3.Heihe Remote Sensing Experimental Research Station,Cold and Arid Regions Environmental and
Engineering Research Institute,Chinese Academy of Sciences,Lanzhou 730000,China)
 全文: PDF(9816 KB)  
摘要:

利用2008~2011年的ENVISAT/ASAR 全球监测模式(GM)数据,采用时间序列变化检测算法,估算地表相对土壤水分,并利用Van Genuchten方法将相对土壤水分转换为绝对土壤水分,最终获得研究区内的土壤体积含水量。利用阿柔冻融观测站2008~2011年10 cm土壤水分数据验证,均方根误差为0.11 cm3/cm3;利用八宝河流域无线传感器网络的36个WATERNET节点2013~2014年的4 cm体积含水量月均值进行空间分布的间接比较检验,估算月均值的均方根误差在0.03~0.11 cm3/cm3的节点有19个,在0.11~0.16 cm3/cm3的节点有15个,大于0.16 cm3/cm3的有2个。另外考虑遥感数据和算法(暂未考虑土壤容重、土壤残余含水量的不确定性)对估算结果的影响,体积含水量最大估计误差范围为0.03~0.12 cm3/cm3,研究区内91.77%的像元小于0.06 cm3/cm3

关键词: ENVISAT/ASAR GM时间序列变化检测算法土壤水分黑河上游    
Abstract:

The change detection method is adopted to estimate the relative soil moisture by using ENVISAT/ASAR global mode data with 1 km resolution in the upper reaches of Heihe River Basin.Then the relative soil moisture is convert to absolute soil moisture by the Van Genuchten formula based on the soil bulk.The comparison analysis and validation during the period from 2008 to 2011 by using the 10 cm observations at A’rou freeze/thaw observation station,show that the root mean square error (RMSE) of the estimated volumetric soil moisture from ASAR is 0.11 cm3/cm3.The indirect validation in the spatial domain by using the mean values of observations at 36 WATERNET nodes,shows that there are 19 nodes which RMSE range from 0.03 cm3/cm3 to 0.11 cm3/cm3,there are 15 nodes which RMSE range from0.11 cm3/cm3 to 0.16 cm3/cm3,and there are 2 nodes which RMSE range from 0.16 cm3/cm3 to 0.19 cm3/cm3.The theoretical maximum estimation errors of volumetric soil moisture range from 0.03 cm3/cm3 to 0.12 cm3/cm3,and that 91.77% of grids is below 0.06 cm3/cm3,the result also shows that the perform of this algorithm at flat topography is better than the mountains.

Key words: ENVISAT/ASAR    Change detection method    Soil moisture    Heihe River Basin
收稿日期: 2014-09-18 出版日期: 2015-09-22
:  TP 79  
基金资助:

中国科学院西部行动计划三期项目(KZCX2-XB3-15,91125001),国家自然科学基金项目(41471357)资助。

通讯作者: 晋锐(1979-),女,山西临汾人,副研究员,主要从事水文遥感、微波遥感、数据同化及无线传感器网络研究。Email:jinrui@lzb.ac.cn。   
作者简介: 董淑英(1988-),女,河南濮阳人,硕士研究生,主要从事土壤水分微波遥感研究。Email:dongshuying@lzb.ac.cn。
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引用本文:

董淑英,晋锐,亢健,李大治. ASAR GM后散时间序列数据估算黑河上游地表土壤水分[J]. 遥感技术与应用, 2015, 30(4): 667-676.

Dong Shuying,Jin Rui,Kang Jian,Li Dazhi. Estimation of High\|resolution Soil Moisture by Using ENVISAT/ASAR Global Mode Backscattering in the Upper Reaches of Heihe River Basin. Remote Sensing Technology and Application, 2015, 30(4): 667-676.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2015.4.0667        http://www.rsta.ac.cn/CN/Y2015/V30/I4/667

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