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基于植被指数和土地表面温度的干旱监测模型
引用本文:王鹏新,WAN Zheng-ming,龚健雅,李小文,王锦地.基于植被指数和土地表面温度的干旱监测模型[J].地球科学进展,2003,18(4):527-533.
作者姓名:王鹏新  WAN Zheng-ming  龚健雅  李小文  王锦地
作者单位:1. 北京师范大学遥感与GIS研究中心,资源与环境科学系,北京,100875;北京师范大学遥感与GIS研究中心,环境遥感与数字城市北京市重点实验室,北京,100875
2. Institute for Computational Earth System Science, University of California, Santa Barbara, CA 93106, USA
3. 武汉大学测绘遥感信息工程国家重点实验室,湖北,武汉,430079
基金项目:国家重点基础研究发展规划项目"地球表面时空多变要素的定量遥感理论与应用"(编号:G2000077900),USNASA项目(ContractNAS5-31370)资助.
摘    要:干旱是一种周期性发生的自然现象,其发生过程中有关参数如地表覆盖度、温度和土壤表层含水量等可以通过遥感的途径进行定量反演,而这些参数客观地反映了地表的综合特征。综述了运用遥感反演产品---土地表面温度和归一化植被指数在干旱监测中的应用前景和进展,分析了距平植被指数、条件植被指数、条件温度指数和归一化温度指数等干旱监测方法的优缺点,在前人研究的基础上,提出了条件植被温度指数的干旱监测模型,探讨了其应用前景。

关 键 词:干旱监测  遥感  土地表面温度  归一化植被指数
文章编号:1001-8166(2003)04-0527-07
收稿时间:2002-07-12
修稿时间:2002年7月12日

ADVANCES IN DROUGHT MONITORING BY USING REMOTELY SENSED NORMALIZED DIFFERENCE VEGETATION INDEX AND LAND SURFACE TEMPERATURE PRODUCTS
Wang Pengxin,Wan Zhengming,Gong Jianya,Li Xiaowen,Wang Jindi.ADVANCES IN DROUGHT MONITORING BY USING REMOTELY SENSED NORMALIZED DIFFERENCE VEGETATION INDEX AND LAND SURFACE TEMPERATURE PRODUCTS[J].Advance in Earth Sciences,2003,18(4):527-533.
Authors:Wang Pengxin  Wan Zhengming  Gong Jianya  Li Xiaowen  Wang Jindi
Institution:1. Research Center for Remote Sensing and Department of Geography,Beijing Normal University;2. Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities,Beijing  100875,China;3. Institute for Computational Earth System Science,University of California,Santa Barbara,CA  93106,USA;4. National Laboratory for Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University,Wuhan  430079,China
Abstract:Drought is a slow-onset natural disaster, an insidious, creeping phenomenon;it occurs in virtually all climatic regimes. Land surface parameters, such as land cover, land surface temperature and soil surface moisture can be retrieved by using remote sensing techniques during the period of drought occurrence. The advances and prospects of applying remotely sensed normalized difference vegetation index(NDVI) and land surface temperature(LST) products for monitoring drought are reviewed. The advantages and disadvantages of NDVI and LST based drought monitoring models are analyzed. Anomaly vegetation index(AVI), vegetation condition index(VCIW) and temperature condition index(TCI) are NDVI or LST based drought monitoring approaches, and study NDVI or LST differences between NDVI or LST values at a specific period of a year and their multi-year's averages or maximum and minimum values at the specific period. It is promising to develop drought monitoring approaches which integrate NDVI and LST products. These approaches are based on the correlation between NDVI and LST and have more physical interpretations than those of using NDVI or LST products alone. The ratio of LST and NDVI is a simple approach, the disadvantage of this approach is that it is difficult to obtain quantitative indices for describing drought intensity. We develop a drought monitoring approach called vegetation temperature condition index (VTCI), and verify that VTCI is a near-real time drought monitoring approach. VTCI is not only related to NDVI changes, but also related to land surface temperature changes. It is defined as the ratio of LST differences among pixels with the same NDVI value in a sufficiently large study area, the numerator is the difference between maximum LST of the pixels and LST of one pixel, the denominator is the difference between maximum and minimum LST of the pixels. VTCI is lower for drought and higher for wet conditions.
Keywords:Drought monitoring  Remote sensing  Land surface temperature  Normalized difference vegetation index  Vegetation temperature condition index
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