基于SAR的石漠化地区土壤剖面含水量最优反演模型研究
Received:June 27, 2017  Revised:December 27, 2017  点此下载全文
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Author NameAffiliationE-mail
YIN Chao School of Karst Science,Guizhou Normal University,Guiyang 997250278@qq.com 
ZHOU Zhong-fa School of Karst Science,Guizhou Normal University,Guiyang 2904462766@qq.com 
TAN Wei-Yi School of Karst Science,Guizhou Normal University,Guiyang  
Wang Ping State Engineering Technology Institute for Karst Desertification Control,Guiyang  
基金项目:国家自然科学基金项目(面上项目,重点项目,重大项目)
中文摘要:通过Sentinel-1A影像数据,运用水云模型提取土壤后向散射系数。并结合实测数据,利用拟合分析对不同深度土壤含水率进行建模,从而对土壤含水率进行反演。结果表明VH和VH+NDVI极化适用于浅层土壤和植被覆盖度低土壤含水率的反演;VV和VV+NDVI极化方式适用于较深土层和植被覆盖度较高区域的土壤含水率的反演。总体上,各土地利用类型反演效果较为理想,所选取的拟合模型R2范围为0.54 ~ 0.904, RMSE范围为2.13 ~ 9.25%。
中文关键词:Sentinel-1A  土壤含水率  土壤后向散射系数  极化方式  水云模型
 
Study on Soil Profile Water Content Optimal Inversion Model in Rocky Desertification Area Based on SAR
Abstract:The Sentinel-1A image data was used to extract soil backscattering coefficient by water cloud model. And combined with the measured data, the soil moisture content in different depths was modeled and inversed by fitting analysis. The results showed that the VH and VH+NDVI polarization applicable to shallow soil and low vegetation coverage area soil moisture content inversion. VV and VV+NDVI polarization were more suitable to estimate the soil moisture of deeper soil layer and high vegetation cover area. Generally, the inversion effect of each land use type was ideally. The R2 range of fitting mode was 0.54 ~ 0.904, and the RMSE range was 2.13 ~ 9.25%.
keywords:Sentinel-1A  soil moisture  soil backscattering coefficient  polarization  water cloud model
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Copyright:《Journal of Infrared And Millimeter Waves》