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地球科学进展  2003, Vol. 18 Issue (4): 527-533    DOI: 10.11867/j.issn.1001-8166.2003.04.0527
王鹏新1,2,Wan Zhengming3,龚健雅4,李小文1,2,王锦地1,2
1.北京师范大学遥感与GIS研究中心,资源与环境科学系;2.环境遥感与数字城市北京市重点实验室,北京 100875;3.Institute for Computational Earth System Science,University of California,Santa Barbara,CA 93106,USA ;4. 武汉大学测绘遥感信息工程国家重点实验室,湖北 武汉 430079
Wang Pengxin1,2,Wan Zhengming3,Gong Jianya4,Li Xiaowen1,2,Wang Jindi1,2
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
 全文: PDF(135 KB)  


关键词: 干旱监测遥感土地表面温度归一化植被指数    

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.

Key words: Drought monitoring    Remote sensing    Land surface temperature    Normalized difference vegetation index    Vegetation temperature condition index.
收稿日期: 2002-07-12 出版日期: 2003-08-01
:  Q15  

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);US NASA项目(ContractNAS5-31370)资助.

通讯作者: 王鹏新     E-mail:
作者简介: 王鹏新(1965-),男,陕西省礼泉县人,博士后,主要从事遥感技术在农业中的应用研究
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王鹏新,Wan Zhengming,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.



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