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我国温度植被旱情指数TVDI的应用现状及问题简述 被引量:45

Introduction of Application of Temperature Vegetation Dryness Index in China
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摘要 植被指数和地表温度是2类常见的遥感干旱监测方法,它们分别利用植被受旱时植被指数降低和植被冠层温度升高这2种重要的生理表现来监测干旱。但植被指数对干旱指示具有一定滞后性,地表温度监测干旱时易受土地背景等影响。基于特征空间的温度植被旱情指数(TVDI)综合了植被指数和地表温度监测干旱的特点,物理意义明确,克服部分单独使用植被指数或地表温度的缺点,是目前干旱研究和业务应用中使用最广的遥感干旱指数之一。本文介绍了TVDI的原理、计算方法、应用中的改进及TVDI干旱监测方法,旨在为TVDI的研究及应用提供一些参考。 Reducing of vegetation index and rising of surface temperature are two kinds of important physiological performance of plants when they are under severe drought stress,so remote -drought indices based on vegetation index(VI)and land surface temperature (LST)are commonly used in drought monitoring.Indices based on vegetation index are difficult to exclude the influence of irrigation, pest and the flood disasters,and due to their larger lag time,they are difficult to monitor drought events which occurred suddenly.The land surface temperature is rising rapidly under the condition of water deficiency,so the indices based on land surface temperature (LST)can detect drought events,but it can’t distinguish water stress conditions under different vegetation cover and it’s easy to be influenced by the surface heat exchange and soil background temperature.The temperature vegetation drought index(TVDI)based on spectral feature space combined the vegetation index and land surface temperature,its physical meaning is more definite and it is well defined.TVDI could overcoming the deficiency of using VI and LST only,there for it is widely used to estimate evapotranspiration and soil moisture.For well understanding the application situation of TVDI in our country and the method to calculate and improve it,this paper expounded the principle of TVDI firstly,and then gave a detail introduce about the calculation and improving methods as well as the way of monitoring drought based on TVDI,etc.The aim is to offer some reference for the calculation and application of TVDI.
出处 《干旱气象》 2014年第1期128-134,共7页 Journal of Arid Meteorology
基金 公益性行业(气象)科研专项项目(GYHY201006023) 国家科技支撑计划(2009BAC53B02) 科技部农业科技成果转化资金项目(2011GB24160005) 农业部948项目(2011-G9)共同资助
关键词 特征空间 计算 改进 TVDI NDVI-LST spectral feature space TVDI calculate improvement
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