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基于热红外的四种土壤含水量估算方法对比
Estimation of surface soil moisture based on thermal remote sensing: Intercomparison of four methods

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杨永民 1,2   邱建秀 3   苏红波 1   田静 1   张仁华 1  
文摘 基于遥感的区域土壤水分反演是流域水资源规划管理、农作物灌溉制度制定、区域旱情监测、农作物估产等方面的基础.本文对四种可见光/热红外土壤水分反演方法进行评估对比,这四种土壤水分估算方法包括基于温度植被干旱指数( TVDI)的土壤水分估算方法和三种基于蒸散比/潜在蒸散比的土壤水分估算方法( EFM1,EFM2和EFM3) .基于以上四种土壤水分估算方法,本文使用ASTER数据估算了黑河流域中游地区的土壤水分状况,使用研究区内生态水文无线传感器网络和流域水文气象观测站点的土壤水分观测对四个模型进行了验证评估.结果表明,TVDI方法因其干、湿边确定的经验性,会导致土壤水分估算的误差.而基于蒸散比/潜在蒸散比的土壤水分估算方法会在一定程度改善TVDI方法估算的经验性.通过蒸散比/潜在蒸散比的三种方法对比显示基于EFM1和EFM3方法优于EFM2方法.此外,基于热红外的土壤水分估算方法都需要土壤参数信息,土壤参数的不确定性会导致土壤水分估算的误差,高精度的土壤参数会改善基于热红外的土壤水分估算方法的精度.
其他语种文摘 Remote sensing-based estimation of soil moisture is crucial in many aspects including basinscale water resource management,irrigation scheduling,regional scale drought monitoring and crop yield forecasting. In this study,we evaluate the potential of visible /thermal-infrared remote sensing in soil moisture estimation,by assessing the TVDI-based method and three categories of methods based on evaporative fraction /potential evaporation ratio ( EFM1,EFM2 and EFM3) . In combination with ASTER data set,soil moisture in middle reach of the Heihe River Basin is predicted by the above-mentioned four methods and validated by the ground-based measurements from eco-hydrological wireless sensor network and hydro meteorological observation network in the middle reach of Heihe river basin. Results indicate that uncertainties arise from the empiricism of the TVDI-based method in the process of determining dry and wet edges. On the other hand,the evaporation fraction /potential evaporation ratio methods can to some degree reduce the uncertainties,and among the three methods,EFM1 and EFM3 outperform EFM2. In addition,the thermal-infrared based methods require accurate soil parameters to reproduce the variation of soil moisture.
来源 红外与毫米波学报 ,2018,37(4):459-467,476 【核心库】
DOI 10.11972/j.issn.1001-9014.2018.04.014
关键词 热红外遥感 ; 土壤水分 ; 黑河流域中游
地址

1. 中国科学研究院地理科学与资源研究所, 中国科学院陆地水循环及地表过程重点实验室, 北京, 100101  

2. 中国水利水电科学研究院防洪抗旱减灾工程技术中心, 北京, 100038  

3. 中山大学地理科学与规划学院, 广东省城市化与地理环境空间模拟重点实验室, 广东, 广州, 510275

语种 中文
文献类型 研究性论文
ISSN 1001-9014
学科 自动化技术、计算机技术
基金 中国科学院地理科学与资源研究所中国科学院陆地水循环及地表过程重点实验室基金 ;  国家自然科学基金 ;  中国水利水电科学研究院专项 ;  广东省自然科学基金 ;  中央高校基本科研业务费专项资金
文献收藏号 CSCD:6313405

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引证文献 6

1 张智韬 基于无人机多光谱遥感的玉米根域土壤含水率研究 农业机械学报,2019,50(7):246-257
CSCD被引 17

2 马腾 考虑地表粗糙度改进水云模型反演西班牙农田地表土壤含水率 农业工程学报,2019,35(24):129-135
CSCD被引 5

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