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高砾石地表全极化SAR土壤水分反演方法

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我国西部戈壁荒漠地区含有大量砾石,这些区域土壤含水量的精准反演对我国西北地区生态和气象环境监测、植树造林及水利工程建设等均具有重要意义.然而,现有的SAR 土壤水分反演模型均假设土壤由细颗粒物组成,并未考虑砾石的影响.对此,本文提出了一种利用全极化SAR遥感数据反演高砾石地表土壤水分的方法.首先,将高砾石地表后向散射建模为地面造成的面散射和砾石造成的体散射两部分;对于面散射,使用高级积分方程模型(AIEM)及Oh模型进行土壤水分反演,对于体散射,则使用致密介质辐射传输模型(DMRT)进行反演;最后,将两部分的反演结果进行加权求和,作为最终的土壤水分反演结果.利用内蒙古自治区乌海市野外土壤水分实测数据及ALOS-2全极化SAR数据对本文方法进行精度评价,并与现有的土壤水分反演方法进行比较,结果表明,本文方法(R2=0.60)比现有方法(R2=0.35)的反演精度有显著的提高.
Soil moisture inversion for high gravel surface with polarimetric SAR imagery
There is a large amount of gravel in the Gobi and desert areas in western China.Accurate inversion of soil water con-tent in these areas is of great significance for ecological and meteorological environment monitoring,afforestation and water conservancy project construction in northwest China.However,existing SAR soil moisture inversion models assume that soil is composed of fine particulate matter,without considering the influence of gravel.In this paper,a new method for soil moisture inversion on high gravel surface using polarimetric SAR(PolSAR)data is proposed.First,the backscattering of high gravel surface is modeled as surface scattering caused by ground and volume scattering caused by gravel.For surface scattering,the advanced integral equation model(AIEM)and Oh model are used for soil moisture inversion.For volume scattering,the dense medium radiative transfer(DMRT)model is used to invert soil moisture.Finally,the weighted summation of the inversion re-sults of the two parts is used as the final inversion result.The inversion accuracy of soil moisture inversion model was evaluated by using the field soil moisture measured data and ALOS-2 PolSAR data in Wuhai city,and compared with the commonly used soil moisture inversion methods.The results showed that the accuracy of this method was significantly improved when it was applied to the soil moisture inversion on high gravel surface(traditional soil moisture retrieval method:R2=0.35;new meth-od:R2=0.60).

soil water contentsoil moisturehigh gravel surfaceAIEM modelDMRT modelpolarimetric SAR

郎丰铠、何苏颖、邱奥深、时洪涛、郑南山

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中国矿业大学江苏省资源环境时空信息工程高校重点实验室,江苏徐州 221116

中国矿业大学环境与测绘学院,江苏徐州 221116

土壤水分 土壤湿度 高砾石地表 AIEM模型 DMRT模型 全极化SAR

2024

测绘学报
中国测绘学会

测绘学报

CSTPCD北大核心
影响因子:1.602
ISSN:1001-1595
年,卷(期):2024.53(11)