基于随机森林模型的青海高原土壤水分反演技术研究  

Study on Soil Moisture Retrieval Technology Using Random Forest Model over Qinghai Plateau

作　　者：陈国茜 杨耀晨[1,2] 李素雲 周秉荣 张娟[1,2] 赵梦凡[1,2] CHEN Guoqian;YANG Yaocheng;LI Suyun;ZHOU Bingrong;ZHANG Juan;ZHAO Mengfan(Key Laboratory of Disaster Prevention and Mitigation in Qinghai province,Xining,Qinghai Province 810001,China;Qinghai Institute of Meteorological Science,Xining,Qinghai Province 810001,China)

机构地区：[1]青海省防灾减灾重点实验室,青海西宁810001 [2]青海省气象科学研究所,青海西宁810001

出　　处：《遥感技术与应用》2024年第6期1417-1428,共12页Remote Sensing Technology and Application

基　　金：青海省科技计划项目“基于遥感图像超分辨率技术的油菜地土壤水分监测”(2021-ZJ-739);国家自然科学基金项目“气候变化背景下关键水热过程对青海高寒草地生态系统结构和功能的影响研究”(U21A2021)。

摘　　要：土壤水分的准确、快速获取在区域干旱与洪涝灾害监测预报预警中发挥着关键作用。静止气象卫星具有高频次观测特性,为实时获取大范围土壤水分信息提供了一种有效手段。以Himawari-8/9静止气象卫星反射率和亮温、植被指数和亮温指数、地形特性、土壤属性、植被状况和时空信息为输入特征,以地面实测土壤水分为期望输出特征,基于随机森林模型构建了青海高原土壤水分反演模型,并对模型进行了独立站点检验和干旱过程时空变化检验。结果表明:模型在2022年青海省河南县土壤水分遥感检验场和互助遥感干旱野外验证场的相关系数分别为0.899、0.740,均方根误差分别为0.062、0.044 m^(3)·m^(-3),平均绝对误差分别为0.048、0.035 m^(3)·m^(-3);对2021年7月海东市互助干旱过程及2022年8月玉树藏族自治州囊谦县干旱过程的土壤水分变化趋势的估算结果与实际相符。研究所构建的随机森林模型可较好地满足青海高原土壤水分遥感实时监测的业务服务需求。The accurate and rapid acquisition of soil moisture plays an important role in monitoring,forecasting and warning of regional drought and flood disasters.The high-frequency observation feature of geostationary meteorological satellites provides an effective method for real-time acquisition of large-scale soil moisture information.The reflectance and brightness temperature data of Himawari-8/9,vegetation indices and brightness temperature indices conducted by Himawari-8/9,geographical data,soil data,vegetation status and spatio-temporal information were taken as input features,and the measured soil moisture was taken as expected output feature.A random forest model of soil moisture over Qinghai Plateau was established,and its accuracy was evaluated through independent site testing and spatio-temporal variation analysis of drought processes.The results showed that,the correlation coefficients of Henan soil moisture remote sensing test field and Huzhu remote sensing drought field in 2022 were 0.899 and 0.740,the root mean square errors were 0.062 and 0.044 m^(3)·m^(-3),and the mean absolute errors were 0.048 and 0.035 m^(3)·m^(-3).In the Huzhu drought process of July 2021,and the Nangqian drought process of August 2022,the variation trend of estimated soil moisture was consistent with the reality.So,the random forest model of soil moisture can meet the real-time monitoring requirement of soil moisture over Qinghai Plateau.

关 键 词：土壤水分 随机森林 青海高原 Himawari-8/9 

分 类 号：P942.1[天文地球—自然地理学]