资源简介

摘要： 以黄土高原半干旱区定西为试验区,利用Radarsat-2/SAR和MODIS数据,将由MODIS NDVI估算的植被含水量(VWC)应用到微波散射Water-Cloud模型中校正植被的影响。采用交叉极化(VV/VH)组合方案对植被覆盖下土壤水分的反演进行初步探讨,结果表明:在植被影响校正前,模型反演土壤水分值出现明显低估现象;校正植被影响后,相关系数R由0.13提高到0.44,且通过α=0.01的显著性检验,标准差SD由5.02降低到4.30,有效提高了模型反演土壤水分的准确度。卫星反演的研究区土壤含水量大部分介于10%~30%之间,与实地考察情况一致,较好地反映出区域土壤湿度分布信息。表明,光学和微波协同遥感反演对于提高农田土壤水分遥感反演精度具有较大的应用潜力。 关键词： Radarsat-2;  SAR;  MODIS;  植被;  Water-Cloud模型;  土壤水分     Abstract: Radarsat-2/SAR and MODIS optical remote sensing data were used to retrieve soil moisture in Dingxi,which was located in the semi-arid region of the Loess Plateau,China.Based on the Normalized Difference Vegetation Index (NDVI) extracted from MODIS data,then estimated crop Vegetation Water Content (VWC) were applied to the Water-Cloud model to separate the contribution of the vegetation scattering and absorption.Using the cross polarization (VV/VH) combination model retrieve the soil moisture of crop covering under the preliminary discussion.The results have shown:Before the effect of vegetation removal,the value of model retrieved soil moisture was significantly under estimation.After separation of vegetation effect,the correlation coefficient R increased from 0.13 to 0.44,and it was through the test of significance of α=0.01;The standard deviation SD reduced from 5.02 to 4.30,which effectively improved the accuracy of model retrieved soil moisture.Most of soil moisture content was between 10％~30％in the study area,which was consistent with the field situation,and can better reflect the regional distribution of soil moisture information.This study showed that optical and microwave remote sensing data has the larger applacation potential in improoing the accuracy of soil moisture readings in agricutural fields.

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