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中国沙漠 ›› 2014, Vol. 34 ›› Issue (2): 527-534.DOI: 10.7522/j.issn.1000-694X.2013.00346

• 天气与气候 • 上一篇    下一篇

基于MODIS数据的青藏高原旱情监测研究

杨秀海1, 卓嘎, 罗布2   

  1. 1. 中国气象局成都高原气象研究所 拉萨分部, 西藏 拉萨 850000;
    2. 西藏高原大气环境科学研究所, 西藏 拉萨 850000
  • 收稿日期:2013-03-01 修回日期:2013-04-19 出版日期:2014-03-20 发布日期:2014-03-20
  • 作者简介:杨秀海(1965—),女,甘肃民勤人,理学学士,高级工程师,主要从事青藏高原天气气候及卫星遥感应用研究。Email:yxiuhai2005@yahoo.com.cn
  • 基金资助:
    中国气象局成都高原气象研究所专项项目(PMP2006004);公益性行业(气象)科研专项项目(GYHY201006054);2013年西藏自治区气象局局设项目“西藏干旱监测系统建设”;西藏自治区气象局高原遥感技术应用创新团队资助

Drought Monitoring in the Tibetan Plateau Based on MODIS Dataset

Yang Xiuhai1, Zhuoga, Luo Bu2   

  1. 1. Lhasa Branch of Chengdu Institute of Plateau Meteorology, China Meteorological Administration, Lhasa 850000, China;
    2. Tibet Institute of Plateau Atmospheric and Environmental Science, Lhasa 850000, China
  • Received:2013-03-01 Revised:2013-04-19 Online:2014-03-20 Published:2014-03-20

摘要: 本文利用温度植被旱情指数(TVDI)和植被供水指数(VSWI)分别对2009、2010年3—10月青藏高原土壤湿度状况进行监测分析,同时利用气象台站实测地面降水资料进行了验证。利用MODIS资料提取的归一化植被指数(NDVI)和地表温度(TS),构建NDVI-TS特征空间,依据该特征空间计算出的反映青藏高原土壤湿度的TVDI与同期累积降水相关性显著;VSWI计算过程简单,但所反映的土壤湿度与同期累积降水的相关性较差。因此,对青藏高原这种范围广、下垫面多变复杂区域而言,TVDI能够更好地反映土壤湿度状况,对干旱监测具有一定的科学意义。

关键词: 遥感, 干旱, 温度植被干旱指数, 植被供水指数

Abstract: This paper investigated the soil moisture condition in the Tibetan Plateau and compared the result with precipitation observation data from meteorological stations from March to October in 2009 and 2010 based on two indices, temperature-vegetation dryness index (TVDI) and vegetation supply water index (VSWI). Results showed that the TS-NDVI eigenspace obtained from MODIS satellite dataset could exhibit significant relationship between TVDI and precipitation in the Tibetan Plateau. But the relationship of soil moisture and precipitation was not significant although the calculation process of VSWI was quite simple. Therefore, TVDI could well describe the status of soil moisture for the region with abundant coverage and complex underlying surface such as the Tibetan Plateau which has certain scientific evidence for drought monitoring.

Key words: remote sensing, drought, temperature-vegetation dryness index, vegetation supply water index

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