基于L波段的裸土区土壤水分微波遥感反演研究  

Soil Moisture Inversion Research in Bare Region Based on L-band Radar Data

作　　者：蒋金豹[1] 张玲[1] 崔希民[1] 孙灏[2] 

机构地区：[1]中国矿业大学(北京)地球科学与测绘工程学院,北京100083 [2]北京师范大学资源学院,北京100875

出　　处：《土壤》2014年第2期361-365,共5页Soils

基　　金：国际科技合作项目(2010DFA32920)资助

摘　　要：以北京市大兴区为研究区,探讨利用ALOS/PALSAR数据反演裸土土壤水分的方法。由于PALSAR的后向散射系数主要与土壤水分及地表粗糙度有关,本研究使用AIEM理论模型计算地表的同极化后向散射系数,Oh半经验模型计算交叉极化的后向散射系数;由分析可知,同极化与交叉极化的差异不随土壤水分的变化而变化,仅随地表粗糙度的增加而减少,为此可建立后向散射系数与粗糙度之间的函数关系。本文利用BP神经网络算法反演研究区的裸土土壤水分含量,并利用实测数据对反演结果进行验证,结果表明估测裸土土壤水分含量误差为0.035 m3/m3,相对误差为13.9%。因此,可以利用L波段主动微波遥感反演裸土土壤水分含量,且具有较高的精度。本研究成果可为农业灌溉、灾害监测、环境评估等提供信息支持,具有重要的现实意义与应用价值。The paper discussed the method of soil moisture inversion using the ALOS/PALSAR data whose study region was Daxing area in Beijing. For ALOS/PALSAR data, co-polarization backscattering coefficient was calculated using the AIEM model, and the Oh model was used to describe the characteristics of cross-polarization scattering. According to backscatting data, the difference between co-polarization backscattering coefficient and cross-polarization backscattering coefficient didn＇t change with the soil moisture, so we can build the functional relations between backscattering coefficient and roughness parameters. The bare soil moisture was retrieved using BP neutral network, and the simulated data was used to validate the accuracy of the model. The result showed that the estimated soil moisture error was 0.035 m3/m3, and the relative error was 13.9%. So L-band radar data can be used to inverse soil moisture in the bare region. The research result could provide information for agricultural irrigation, disaster monitoring and environmental assessment.

关 键 词：PALSAR 裸土区 土壤水分 反演 

分 类 号：P237[天文地球—摄影测量与遥感]