基于高分三号卫星合成孔径雷达数据的农田土壤水分反演  

Retrieval of soil moisture based on Gaofen-3(GF-3)satellite synthetic aperture radar data over agricultural fields

作　　者：张琳琳 雷志斌 王莉萍 孟庆岩 曾江源 ZHANG Linlin;LEI Zhibin;WANG Liping;MENG Qingyan;ZENG Jiangyuan(State Key Laboratory of Remote Sensing Science,Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100101,China;University of Chinese Academy of Sciences,Beijing 100049,China;Key Laboratory of Earth Observation of Hainan Province,Hainan Aerospace Information Research Institute,Sanya 572029,Hainan,China;School of Earth Sciences and Resources,China University of Geosciences(Beijing),Beijing 100083,China;Center for Urban Governance Studies of Zhejiang Province,Hangzhou International Urbanology Research Center,Hangzhou 310000,Zhejiang,China)

机构地区：[1]中国科学院空天信息创新研究院,遥感科学国家重点实验室,北京100101 [2]中国科学院大学,北京100049 [3]海南空天信息研究院,海南省地球观测重点实验室,海南三亚572029 [4]中国地质大学(北京),地球科学与资源学院,北京100083 [5]杭州国际城市学研究中心浙江省城市治理研究中心,浙江杭州310000

出　　处：《浙江大学学报（农业与生命科学版）》2024年第2期209-220,共12页Journal of Zhejiang University:Agriculture and Life Sciences

基　　金：遥感科学国家重点实验室开放基金项目(OFSLRSS202208);国家自然科学基金项目(42201384);中国科学院青年创新促进会项目(2023139,Y2022050)。

摘　　要：土壤水分是农作物生长的基本条件,本研究基于高分三号卫星C波段合成孔径雷达数据,提出新的土壤水分反演算法,并获取区域尺度8 m空间分辨率的农田区土壤水分。首先,通过PROSAIL模型、实测植被冠层含水量、Landsat-8光学数据优选光学植被水分指数,计算水云模型参数并获得土壤直接后向散射系数;其次,利用高级积分方程模型模拟雷达后向散射影响机制,采用雷达影像高低入射角特性计算地表组合粗糙度;最后,利用高分三号卫星同极化雷达数据反演农田区土壤水分,并基于实测数据开展精度验证。结果表明:土壤水分反演值与野外实测值具有良好一致性,垂直极化下反演精度更高,其决定系数为0.5956,均方根误差为0.0415 m3/m3。本研究成果可为我国自主研发的高分三号卫星获取高分辨率土壤水分信息提供算法参考。Soil moisture is the basic condition for crop growth.A new retrieval algorithm for soil moisture was proposed based on C-band synthetic aperture radar(SAR)data from Gaofen-3(GF-3)satellite,and soil moisture of agricultural fields with a regional scale spatial resolution of 8 m was obtained.First,the algorithm selected the optical vegetation water index based on PROSAIL model,measured vegetation canopy water content and Landsat-8 optical data.The parameters of water cloud model were calculated,and soil direct backscattering coefficients were obtained.Second,the radar backscattering influence mechanism was simulated using an advanced integral equation model(AIEM),and the combined roughness of soil surface was calculated based on the characteristics of radar data at high and low incidence angles.Finally,soil moisture was retrieved using co-polarization radar data from GF-3 satellite over agricultural fields,and this was verified with measured data.The results showed that there was a high consistency between the measured soil moisture and estimated soil moisture,and vertical-vertical(VV)polarization exhibited higher retrieval accuracy,with a determination coefficient of 0.5956 and a root mean square error of 0.0415 m3/m3.The results can provide algorithmic references for the GF-3 satellite to obtain high-resolution soil moisture information.

关 键 词：土壤水分 高分三号卫星 雷达遥感 地表粗糙度 

分 类 号：P237[天文地球—摄影测量与遥感]