基于Sentinel-1的绿洲区域尺度土壤水分微波建模研究
投稿时间:2016-05-30  最后修改时间:2016-09-08  点此下载全文
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作者单位E-mail
王娇 新疆大学资源与环境科学学院 / 绿洲生态教育部重点实验室 308372426@qq.com 
丁建丽 新疆大学资源与环境科学学院 / 绿洲生态教育部重点实验室 wangjiao_ygddd@qq.com 
基金项目:国家自然科学(U1303381, 41261090, 41130531, 41161063);教育部新世纪优秀人才支持计划(NCET-12-1075);教育部长江学者计划创新团队计划(IRT1180);新疆研究生科研创新项目(XJGRI2014022)
中文摘要:土壤水分是制约我国西北干旱区生态环境和可持续发展的主要问题。因此,针对这一地区下垫面特征开展高效区域性的土壤水分监测,对于干旱区水热传输/能量平衡方面的研究具有重要意义。本文根据最新Sentinel-1雷达系统参数及研究区地表参数特点,采用AIEM模型进行数值模拟分析,建立了稀疏植被覆被下地表微波散射特征数据库,并在此基础上构建干旱区土壤水分反演经验模型,为今后Sentinel-1雷达数据在干旱区大尺度、短周期内的区域土壤水分定量监测模拟奠定基础。研究结果表明, 1)AIEM模型能较准确描述干旱区地表微波散射特征,其中不同入射角和不同极化方式下,后向散射系数对土壤含水量(Mv)、组合地表粗糙度(Zs)的响应分别呈明显对数相关,且相较交叉和HH极化方式而言,VV极化对土壤水分响应更敏感,最优响应区间范围为Mv 0~30%、Zs 0~0.06cm。2)初探Sentinel-1雷达数据预处理方法,其中GammaMAP滤波效果去噪较好,基于Sentinel-1影像构建的土壤水分经验模型对于提取土壤水分空间分布信息与研究区同期野外实际情况具有良好的一致性,符合四月渭-库地区春旱期土壤水分时空分布特征。3)对于0-10cm表层土壤水分,实测值同模拟值之间相关系数达到了0.76,符合区域尺度土壤水分建模的精度要求。表明该模型对于干旱区绿洲区域尺度土壤水分提取具有适用性。
中文关键词:Sentinel-1  AIEM模型  微波遥感  土壤水分
 
Microwave modeling of soil moisture in Oasis regional scale based on Sentinel-1 radar images
Abstract:Soil moisture is a major problem that restricts the ecological environment and sustainable development of arid area in Northwest China. Therefore, it is important to carry out effective regional soil moisture monitoring,which is of great significance to the research of water heat transfer / energy balance in arid area. According to the latest Sentinel-1 radar system parameters and the surface characteristic parameters of the study area,we established a database of surface microwave scattering characteristics under the sparse vegetation cover condition by AIEM model. On the basis of AIEM model numerical simulation analysis, soil moisture inversion experience model was constructed. For future sentinel-1 radar data in the large scale arid region, within a short period of regional soil moisture quantitative monitoring simulation lay the foundation. The results showed that: 1) Compared with other model, the AIEM model can more accurately describe the surface microwave scattering characteristics in arid area. Under the different incident angles and different polarization mode, the backscatter coefficient response of soil moisture (Mv) and the composite surface roughness (Zs) have obvious logarithmic correlation respectively. Compared with the cross-polarization and HH polarization, soil moisture response of VV polarization is more sensitive, the optimal response range for Mv 0~30%, Zs 0~0.06cm. 2) On the one hand, GammaMAP filtering has better denoising effect in the sentinel-1 radar data preprocessing. On the other hand, the spatial distribution of soil moisture extracted from sentinel-1 images has good consistency with the same period field actual situation in the study area. In April, the soil moisture spatio-temporal distrbution of Weigan-Kuqa river basin showed spring drought characteristics. 3) For 0-10cm surface soil moisture, the correlation coefficient between the measured value and simulated value reached 0.76, which meets the accuracy requirements of the regional scale soil moisture retrieval. It shows that this model is suitable for the extraction of soil moisture in the arid area of a certain regional scale.
keywords:Sentinel-1  AIEM model  Microwave remote sensing  Soil moisture
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