【摘要】 TVDI指数是一种将植被指数和地表温度相结合的土壤水分监测方法，以往学者多以归一化植被指数和地表温度来构建计算TVDI指数的特征空间。在前人研究基础上，利用归一化植被指数、增强型植被指数、比值植被指数、土壤调节植被指数、归一化水分指数等多种植被指数与地表温度及昼夜温差的不同组合来构建特征空间，尝试找到更加适合河南省进行土壤水分监测的特征空间组合。经过分析得到以下结论：(1)昼夜温差与植被指数构建的特征空间不能改进研究区TVDI指数对土壤水分的指示精度。(2)RVI＿b2b1-LST、RVI＿b2b7-LST、SAVI-LST、EVI-LST等特征空间计算的TVDI对河南省农地类型下垫面有较好的空间适用性，但反演值较实测值偏低。(3)TVDI指数在冬小麦扬花和灌浆成熟期(4-5月)有较好适用性，在冬小麦播种-越冬期的10月、1月有一定适用性，在夏玉米生长期(6-9月)适用性差。更多还原

【Abstract】 Temperature vegetation dryness index(TVDI) is a soil moisture monitoring method that combines vegetation index(VI) and surface temperature.Scholars previously used normalized differential vegetation index(NDVI) and land surface temperature(LST) to construct the feature space to calculate TVDI.On the basis of the previous studies, this paper uses the combinations of various VIs, such as NDVI,enhanced vegetation index(EVI),ratio vegetation index(RVI),soil adjusting vegetation index(SAVI),and normalized differential water index(NDWI),and land surface temperature and diurnal temperature difference to construct the feature space and tries to determine a feature space combination that is more suitable for soil moisture monitoring in Henan Province.After analysis, the following conclusions are drawn.(1)The feature space constructed by diurnal temperature difference and vegetation index can’t improve the indication accuracy of TVDI index for soil moisture in the study area.(2)The TVDI calculated by RVI＿b2b1-LST,RVI＿b2b7-LST,SAVI-LST,EVI-LST feature spaces have good spatial applicability to the underlying surface of agricultural land types in Henan Province.However, the inversion value is lower than the measured value.(3)TVDI index has good applicability in the flowering to grain filling and maturation period(April to May) of Winter Wheat, and has certain applicability in winter wheat seeding period(October) and overwintering period(January),but poor applicability in summer maize growing period(June to September).更多还原