摘要
土壤水分的时空分布是水文、气象等领域研究的重要参数。微波遥感因其全天时、全天候对地观测以及较强的穿透能力成为土壤水分反演的重要手段。该文以风沙滩地区为研究区,利用AIEM模型模拟雷达后向散射系数与粗糙度、土壤水分之间的关系,提出一种新的组合粗糙度参数S3/L,以法向菲涅尔反射系数代替土壤水分,建立了雷达后向散射系数与组合粗糙度、法向菲涅尔反射系数Г0的经验关系,利用Radarsat-2C波段双极化(VV、HH)数据构建了土壤水分反演模型。经实测数据验证,模型反演结果与实测值有着良好的相关性(R^2=0.8541),平均绝对误差为4.95%,均方根误差为6.00%。与以往同一区域的研究成果相比,该文提出的反演模型精度较高,更适合于风沙滩地区土壤水分的反演。研究结果可为该地区的水循环及水环境评价研究提供支持。
The temporal and spatial distribution of soil moisture is an important parameter in research of hydrology,meteorology and other fields.Microwave remote sensing has become an important method in soil moisture retrieval because of its full day,allweather observation and strong penetrating abilities.In order to achieve soil moisture retrieval of blown-sand region,a new combined roughness parameter（S3/L）was proposed in this paper.The relationship between backscattering coefficient,the combined roughness as well as backscattering coefficient and soil moisture were simulated based on AIEM（Advanced Integral Equation Model）.In addition,soil moisture was replaced by the Fresnel reflection coefficientΓ0.Then an empirical relationship between the backscattering coefficient and the combined roughness,the Fresnel reflection coefficientΓ0was eventually developed.This relationship was established in the case of multiple incidence angles.In this circumstances,the inversion result was a function of the Fresnel reflection coefficientΓ0rather than soil moisture.By using the soil dielectric constantεand the Dobson model,the Fresnel reflection coefficientΓ0can be converted to soil moisture.Soil moisture retrieval model was established based on Radarsat-2C-band dual polarization（VV,HH）data.The validation revealed that the estimated soil moisture had a good correlation with the observed values（R2=0.8541）.The averaged absolute error and the root mean square error（RMSE）were 4.95% and6.00% respectively.Compared with previous research,the results present a higher accuracy and more suitable for soil moisture retrieval in this area.The research can provide support for the study of the water cycle and water environment evaluation.
出处
《地理与地理信息科学》
CSCD
北大核心
2016年第3期34-38,共5页
Geography and Geo-Information Science
基金
国家自然科学基金项目(41272246
41371220)
教育部科学技术研究重点项目(108183)
中央高校基本科研业务费专项资金项目(2013G3272013)
