地球信息科学学报 ›› 2012, Vol. 14 ›› Issue (1): 32-40,48.doi: 10.3724/SP.J.1047.2012.00032

• 陆地表层系统模拟 • 上一篇    下一篇

2010年中国西南旱情的时空特征分析——基于MODIS数据归一化干旱指数

白开旭, 刘朝顺*, 施润和, 高炜   

  1. 华东师范大学 地理信息科学教育部重点实验室, 华东师范大学 中国科学院对地观测与数字地球科学中心 环境遥感与数据同化联合实验室, 上海 200062
  • 收稿日期:2011-04-27 修回日期:2011-12-23 出版日期:2012-02-25 发布日期:2012-02-24
  • 通讯作者: 刘朝顺(1980-),男,博士,主要从事陆面定量遥感。E-mail: csliu@re.ecnu.edu.cn E-mail:csliu@re.ecnu.edu.cn
  • 作者简介:白开旭(1987-),男,硕士研究生,主要研究方向为定量遥感。E-mail: kaixubai@gmail.com
  • 基金资助:

    国家自然科学基金项目(41101037);高等学校博士学科点专项科研基金资助课题(20100076120024);中央高校基本科研业务费专项(华东师范大学);地理信息科学教育部重点实验室主任基金。

Analysis of Spatio-temporal Characteristics of Drought in Southwest China in 2010 by Using MODIS-based Normalized Difference Drought Index

BAI Kaixu, LIU Chaoshun*, SHI Runhe, GAO Wei   

  1. Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Joint Laboratory for Environmental Remote Sensing and Data Assimilation, ECNU & CEODE, CAS, Shanghai 20062, China
  • Received:2011-04-27 Revised:2011-12-23 Online:2012-02-25 Published:2012-02-24

摘要: 近年来,干旱灾害频繁发生,对区域内农业生产和生态环境造成了极大的破坏。为了快速准确地获取大面积地表土壤水分信息用以评估地表受旱程度,本文以2010年年初中国西南大旱为例,运用MODIS可见光-红外波段数据以及像元可信度综合生成了归一化干旱指数(NDDI)。同时,结合研究区内地面气象站点实测的土壤湿度数据验证了NDDI对地表土壤湿度的敏感度。结果表明:相比于植被状态指数(VCI)干旱监测模型,NDDI能更加灵敏地对浅层地表干湿变化做出迅速响应。最后,本文利用NDDI分析了2010年年初中国西南大旱旱情发展的时空演变过程,宏观上重现了此次旱情的发展历程,并使用该指数统计了不同时间节点、不同干旱等级下的贵州省土地受旱面积。结果显示:2010年1月-2010年4月为贵州省旱情最为严重的4个月,平均受旱面积达103 352km2,最大受旱面积达132 257km2,占贵州省总面积的75%以上。同时,旱情等级为重旱的土地面积最大达到88 246 km2,占贵州全境土地面积的50%以上。

关键词: 归一化干旱指数, 时空演变, 干旱, MODIS, 土壤水分

Abstract: Drought has frequently brought huge damage to local agricultural production and ecological environment in China. In order to acquire large-scale land surface water information to assess drought severity quickly and accurately, normalized difference drought index (NDDI) was proposed which based on visible and near infrared band reflectance. In this paper, the spatio-temporal characteristics of drought in southwest China in 2010 was analysed using NDDI, with Yunnan, Guangxi and Guizhou provinces as the study area. Firstly, MODIS images were preprocessed and then normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were calculated with different bands data retrieved from MODIS reflectance product. Secondly, NDDI was calculated by using NDVI and NDWI. During this process, pixel reliability data acquired from MODIS product was introduced. The main purpose of this data was to eliminate noise such as clouds and ice or snow in NDDI calculation. Next, the correlation between NDDI and ground-based soil moisture was validated, also intercomparison between NDDI and vegetation condition index (VCI) was analysed. The result showed that NDDI was sensitive to ground soil moisture and demonstrated even quicker response to shallow surface drought severity than that of VCI. Finally, the spatio-temporal distribution of drought in southwest China in 2010 was reoccurred with NDDI index, and also land area with different drought severity was derived. The result showed that the period that suffered from most severe drought conditions lasted from January to April in 2010 in Guizhou Province, the maximum drought-stricken area was 132257 km2 and it occupied more than 75% of the total area of Guizhou Province. Meanwhile, the maximum area suffered from "heavy drought" was 88246 km2 and it occupied more than 50% of the total area of Guizhou Province.

Key words: soil moisture, normalized difference drought index, spatio-temporal characteristics, drought, MODIS