基于MODIS时间序列数据的葡萄种植区土壤湿度估算与干旱监测  

Soil Moisture Estimation and Drought Monitoring in Grape Growing Areas based on Time Series Data of MODIS

作　　者：高溢 王一博 张霞 陶诗语 Yi GAO;Yibo WANG;Xia ZHANG;Shiyu TAO(Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100101,China;University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]中国科学院空天信息创新研究院,北京100101 [2]中国科学院大学,北京100049

出　　处：《遥感技术与应用》2024年第5期1237-1248,共12页Remote Sensing Technology and Application

基　　金：中国科学院战略性先导科技专项课题(XDA28080500);国家自然科学基金项目(42371360)。

摘　　要：土壤湿度(SM)是葡萄生长发育的重要参数,准确监测葡萄种植区SM有利于科学地指导田间灌溉等措施,进而促进葡萄品质、产量的提升。以陕西省泾阳县为典型研究区,基于2009~2016年MODIS反射率、地表温度、蒸散发等数据,计算归一化差异水分指数(NDWI)、植被供水指数(VSWI)、温度状态指数(TCI)、作物缺水指数(CWSI)等6个遥感指标,通过遥感指标对SM的敏感性分析优选指标,采用分类回归树(CART)算法构建SM的综合遥感模型,实现对葡萄关键生育期SM的8 d分辨率尺度估算与干旱监测。研究表明:NDWI、VSWI和CWSI能够更好地表征葡萄种植区SM时空变化情况,NDWI对SM变化响应最为及时,且相关性最高;利用优选NDWI、VSWI和CWSI 3个指标构建的SM综合估算模型,除121、169时相外,各时相R^(2)达0.6以上,葡萄果实膨大期各时相R^(2)均能达0.8以上;2009~2016年泾阳县葡萄种植区干旱多发生在葡萄开花期与果实膨大期。该研究可为葡萄种植区干旱监测提供方法参考。Soil Moisture(SM)is an important parameter for grape development,and accurate monitoring of SM in grape-growing areas is beneficial for scientifically guiding field irrigation and other measures,thereby promoting grape quality and yield.We took Jingyang County,Shaanxi Province as a typical study area,calculated six remote sensing indicators,including Normalized Difference Water Index(NDWI),Vegetation Supply Water Index(VSWI),Temperature Condition Index(TCI),Crop Water Stress Index(CWSI),etc.,based on MODIS reflectance,surface temperature,and evapotranspiration products from 2009 to 2016,preferentially selected indicators through sensitivity analysis of remote sensing indicators on SM,and constructed a comprehensive remote sensing model of SM using the classification regression tree(CART)algorithm to achieve 8-day resolution scale estimation and drought monitoring of SM at key growth stages of grape.The results showed that NDWI,VSWI and CWSI could better characterize the temporal and spatial variations of SM in the grape-growing area,and NDWI has the most timely response to SM changes and the highest correlation.The comprehensive estimation model of SM constructed using the three preferred NDWI,VSWI and CWSI indicators achieve an R^(2) of 0.6 or more for all time phases except 121 and 169,and an R^(2) of 0.8 or more for all time phases at mid-ripening stage.From 2009 to 2016,the drought in the grape-growing area of Jingyang County occurs mostly during the flowering stage and mid-ripening stage of grapes.This study can provide reference for drought monitoring in grape-growing areas.

关 键 词：葡萄 遥感干旱指标 土壤湿度 CART算法 反演模型 

分 类 号：S127[农业科学—农业基础科学] TP79[自动化与计算机技术—检测技术与自动化装置]