| 综合利用光学、微波遥感数据反演土壤湿度研究 |
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| 引用本文： | 鲍艳松,刘良云,王纪华.综合利用光学、微波遥感数据反演土壤湿度研究[J].北京师范大学学报(自然科学版),2007,43(3):228-233. |
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| 作者姓名： | 鲍艳松 刘良云 王纪华 |
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| 作者单位： | 南京信息工程大学遥感学院,210044,南京;国家农业信息化工程技术研究中心,100089,北京;北京师范大学地理学与遥感科学学院,遥感科学国家重点实验室,环境遥感与数字城市北京市重点实验室,100875,北京;国家农业信息化工程技术研究中心,100089,北京 |
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| 基金项目： | 国家高技术研究发展计划(863计划) |
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| 摘 要： | 基于ASAR-APP和TM影像数据,研究了小麦覆盖地表的土壤湿度反演方法.首先,利用冠层后向散射模型MIMICS(michigan microwave canopy scattering),分析了第二入射角模式(IS2)2种极化组分散射对总散射的贡献,确定了土壤湿度反演的最佳极化模式;其次,分析了植被微波单次散射、植被层双程透过率与NDVI之间的关系,建立了单次散射及双程透过率模型,然后,结合IS2入射角模式ASAR数据,建立土壤湿度反演模型.最后,基于模拟数据和获取的ASAR、TM影像数据,利用半经验模型反演土壤湿度.研究结果表明:IS2_HH模式土壤散射在总散射中贡献更大,该数据更适合土壤湿度反演;植被微波单次散射、双程透过率与NDVI有很好的线性关系,可以利用线性模型建立它们之间的关系;半经验模型能够较好地反演土壤湿度,反演和实测的土壤湿度相关系数为0.75,均方根误差为5.07%.
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| 关 键 词： | 土壤湿度 ASAR TM MIMICS模型 |
| 修稿时间： | 2007-02-06 |
SOIL MOISTURE ESTIMATION BASED ON OPTICAL AND MICROWAVE REMOTE SENSING DATA |
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| Bao Yansong,Liu Liangyun,Wang Jihua.SOIL MOISTURE ESTIMATION BASED ON OPTICAL AND MICROWAVE REMOTE SENSING DATA[J].Journal of Beijing Normal University(Natural Science),2007,43(3):228-233. |
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| Authors: | Bao Yansong Liu Liangyun Wang Jihua |
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| Institution: | 1. School of Remote Sensing, Nanjing University of Information Science and Technology, 210044, Nanjing, China; 2.National Engineering Research Center for Information Technology in Agriculture, 100089, Beijing, China; 3.School of Geography and Remote Sensing Science, State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and the Institute of Remote Sensing Applications of Chinese Academy of Seiences; Beijing Key Laboratory of Enviromental Remote Sensing and City Digitalization, Beijing Normal University; 100875, Beijing, China |
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| Abstract: | Soil moisture is an important parameter for agricultural,meteorological and hydrographic studies.This article is focused on wheat field soil moisture estimation methodology based on ASAR-APP and TM data.Firstly,the MIMICS(michigan microwave canopy scattering model) is used to analyze the contribution of component backscattering on total backscattering at HH and VV polarization to confirm the optimal polarization mode.Secondly,the relationship between NDVI and single backscattering,transmittance of vegetation is studied,and single backscattering and transmittance are built.Thirdly,the soil moisture inversion model is built by combining ASAR and TM data.Finally,the model is used to estimate soil moisture.The research result shows that:(1) soil backscattering contribution is dominant in total backscattering at IS2_HH mode,therefore,the mode data are optimal for soil moisture estimation;(2) there is a linear relationship between NDVI and vegetation single backscattering,transmittance;(3) the soil moisture estimation results show that the soil moisture RMSE is 0.05,the correlation is 0.75 between estimation and measurement soil water content. |
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| Keywords: | ASAR TM |
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