摘要
改进温度植被干旱指数(Temperature Vegetation Dryness Index,TVDI)并明确TVDI的农业干旱等级阈值,对提高TVDI指数监测农业干旱能力有重要意义。利用近19 a的MODIS(Moderate Resolu⁃tion Imaging Spectro-radiometer,MODIS)遥感数据,基于单时次和多时次方法构建NDVI(Normalized Difference Vegetation Index,NDVI)-LST(Land Surface Temperature,LST)、EVI(Enhanced Vegetation In⁃dex,EVI)-LST、RVI(Ratio Vegetation Index,RVI)-LST、SAVI(Soil-Adjusted Vegetation Index,SAVI)-LST等几种特征空间,讨论TVDI计算方法,分析TVDI在甘肃省农业干旱监测中的适用性,并明确甘肃省夏季TVDI农业干旱分级标准。结果表明:(1)基于多时次方法构建的SAVI-LST特征空间TVDI更适合甘肃省农业干旱监测,其对土壤相对湿度(Relative Soil Moisture,RSM)拟合的均方根误差(Root Mean Squared Error,RMSE)和平均绝对误差(Mean Absolute Error,MAE)比NDVI-LST特征空间TVDI对RSM拟合的RMSE和MAE下降1%~5%;(2)TVDI适用于夏季甘肃省半干旱区、半湿润区、湿润区等非干旱区浅层10、20 cm土壤深度的农业干旱监测,RMSE和MAE约15.6%和12.6%,拟合误差湿润区<半湿润区<半干旱区;(3)利用TVDI与RSM线性关系确定的TVDI农业干旱等级更有利于提高TVDI监测农业干旱的准确性。
Improving the Temperature Vegetation Dryness Index(TVDI)and clarifying the agricultural drought grade threshold of TVDI is of great significance for improving the ability of TVDI to monitor agricultural drought.Based on MODIS(Moderate Resolution Imaging Spectroradiometer)remote sensing data in the past 19 years,several feature spaces are constructed by using the single-time and multi-time methods,including NDVI(Normalized Difference Vegetation Index)-LST(Land Surface Temperature),EVI(Enhanced Vegetation Index)-LST,RVI(Ratio Vegetation Index)-LST,and SAVI(Soil Adjusted Vegetation Index)-LST.The calculation methods of TVDI are discussed,the applicability of TVDI for agricultural drought monitoring in Gansu Province is analyzed,and classification standards for summer TVDI agricultural drought in Gansu Province are clarified.The research results are as follows:1)The TVDI cal-culated from the SAVI-LST feature space is more suitable for agricultural drought monitoring in Gansu Province.The root mean squared error(RMSE)and mean absolute error(MAE)of its fitting relative soil moisture(RSM)decreased by 1%–5%compared with the RMSE and MAE of RSM fitted by NDVI-LST feature space TVDI for RSM,which is used more commonly.2)TVDI is suitable for agricultural drought monitoring at shallow depths of 10 and 20 cm in non-arid areas such as semi-arid,semi-humid and humid areas in Gansu Province in summer.The RMSE and MAE are approximately 15.6%and 12.6%,and the fitting errors in humid areas are the least,and they are less in semi-humid areas than in semi-arid areas they are the largest.3)Compared to TVDI drought grades divided by 0.2 intervals and TVDI with uncertain classification criteria,the TVDI agricultural drought grade determined by the linear relation-ship between TVDI and RSM is more conducive to improving the accuracy of TVDI monitoring agricultural drought.
作者
沙莎
王丽娟
王小平
胡蝶
张良
SHA Sha;WANG Lijuan;WANG Xiaoping;HU Die;ZHANG Liang(Institute of Arid Meteorology,CMA,Key Laboratory of Arid Climate Change and Reducing Disaster of Gansu Province,Key Laboratory of Arid Climate Change and Disaster Reduction of CMA,Lanzhou 730020,China)
出处
《干旱气象》
2024年第1期27-38,共12页
Journal of Arid Meteorology
基金
甘肃省气象局气象科学技术研究项目(ZcZd2022-26)
国家自然科学基金项目(42075120、42105131、41875020)
干旱气象科学研究基金项目(IAM201816)共同资助。
关键词
温度植被干旱指数
干旱监测
多时次方法
土壤相对湿度
temperature vegetation dryness index
drought monitoring
multi-time method
relative soil moisture
