Monitoring Drought Using Temperature/Vegetation Drought Index Based on Remote Sensing Images

ZHAO Lihua; DU Peijun; PANG Yunfeng; ZHANG Huapeng

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Monitoring Drought Using Temperature/Vegetation Drought Index Based on Remote Sensing Images

- Monitoring Drought Using Temperature/Vegetation Drought Index Based on Remote Sensing Images
- Bulletin of Soiland Water Conservation Vol. 29, Issue 4, Pages: 110-114(2010)
- 作者机构：
  
  1. 中国矿业大学测绘与空间信息工程研究所,江苏,徐州,221116
  2. 国土环境与灾害监测国家测绘局重点实验室,江苏,徐州,221116
  3. 龙口矿业集团生产处, 山东龙口,265700
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2010
- 稿件说明：
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ZHAO Lihua, DU Peijun, PANG Yunfeng, et al. Monitoring Drought Using Temperature/Vegetation Drought Index Based on Remote Sensing Images[J]. Bulletin of Soiland Water Conservation, 2010, 29(4): 110-114.
DOI：

ZHAO Lihua, DU Peijun, PANG Yunfeng, et al. Monitoring Drought Using Temperature/Vegetation Drought Index Based on Remote Sensing Images[J]. Bulletin of Soiland Water Conservation, 2010, 29(4): 110-114. DOI：

摘要

利用LandsatTM/ETM+数据

以徐州市郊为研究区

获取归一化植被指数(NDVI)、土壤调整植被指数(SAVI)和地表温度(Ts)信息

分别构建NDVI—Ts和SAVI—Ts特征空间

依据这两个特征空间计算出研究区2001年4月3日和2007年5月14日的温度植被旱情指数TVDI(NDVI)和TVDI(SA-VI)

并分别与地表温度(Ts)和降水量进行了相关评价。结果表明

TVDI可用于实现大范围的干旱监测

SAVI能够修正NDVI对土壤背景的敏感

基于SAVI的反演结果明显优于基于NDVI的反演结果

能够有效地运用于干旱监测。

Abstract

Taking Xuzhou City as a study case

normalized difference vegetation index (NDVI)

soil-adjusted vegetation index(SAVI)

and land surface temperature(LST) are derived from Landsat TM/ETM+ remotely sensed data and then used to monitor drought status. The spatial characteristics of the vegetation indices and LST are built

by which the temperature vegetation dryness index (TVDI) is calculated from the remote sensing images obtained on April 3

2001 and May 14

2007. The analyses of TVDI

LST

and rainfall show that TVDI can be used to monitor drought largely and the result of TVDI based on SAVI is better than that based on NDVI.

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Related Institution

Key Laboratory for Restoration and Reconstruction of Degraded Ecosystem in NorthwesternChina of the Ministry of Education,Ningxia University,,Ninxia

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International Research Institute of Ningxia University and Shimane University,Ningxia University,,Ninxia

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Institute of Lanzhou Arid Meteorology of the China Meteorological Administration, Key Laboratory ofArid Climate Change and Reducing Disaster of Gansu Province, and Key Open Laboratory of Climatic Change and Disaster Reduction

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