Share Email Print
cover

Proceedings Paper

Application of MODIS time series data for drought assessment in East China
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Drought is one of the major environmental disasters in China, so it is very important to detect and monitor drought periodically at large scale for decision making. This study focuses on combining information from visible, near infrared, and short wave infrared channels of MODIS to improve sensitivity to drought severity. Significant correlations have been found between NDVI/NMDI values and precipitation/soil moisture data in individual stations. It was confirmed that both NDVI and NMDI indices could be used to monitor drought in the study area at a regional scale. However, NMDI had a slightly higher correlation with soil moisture or precipitation than NDVI, which suggests that NMDI variations can be a good indicator of water changes and in turn, the drought conditions in individual stations in the study area. Results from analysis of time series NDVI and NDWI data over the study area also indicate that NMDI was more sensitive than NDVI to drought conditions. Future efforts are being need to more fully exploit the potential of NMDI as an active drought-monitoring tool for different geographic regions, climates, and multiple spatial scales.

Paper Details

Date Published: 12 August 2010
PDF: 8 pages
Proc. SPIE 7809, Remote Sensing and Modeling of Ecosystems for Sustainability VII, 78090P (12 August 2010); doi: 10.1117/12.858184
Show Author Affiliations
Chaoshun Liu, East China Normal Univ. (China)
Joint Lab. for Environmental Remote Sensing and Data Assimilation (China)
Runhe Shi, East China Normal Univ. (China)
Joint Lab. for Environmental Remote Sensing and Data Assimilation (China)
Wei Gao, East China Normal Univ. (China)
Joint Lab. for Environmental Remote Sensing and Data Assimilation (China)
Colorado State Univ. (United States)
Zhiqiang Gao, Colorado State Univ. (United States)
Institute of Geographic Sciences and Natural Resources Research (China)


Published in SPIE Proceedings Vol. 7809:
Remote Sensing and Modeling of Ecosystems for Sustainability VII
Wei Gao; Thomas J. Jackson; Jinnian Wang, Editor(s)

© SPIE. Terms of Use
Back to Top