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Proceedings Paper

Characterization of vegetation dynamics in Shihezi, Xinjiang using MODIS data
Author(s): Sha Song; Xianfeng Zhang; Quan Sun; Qing Lu
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Paper Abstract

The vegetation cover is a major feature for an ecological system, especially in arid and semi-arid areas. Percent vegetation cover (PVC) is an integrated index that can indicate vegetation community dynamics. This study aims to use MODIS and TM data to characterize the spatio-temporal dynamics of vegetation covers in Shihezi area, Xinjiang / China. The 16-day composite NDVI of the second half July of 2001 to 2008 was extracted from the MODIS bands. The land cover data was derived from TM data to get better spatial resolution. The dimidiate pixel model was applied to estimate the PVC and the PVC images were classified into five grade categories based on the value of each pixel, and the area for each category was also calculated. The results show that: 1) the area of the low vegetation covers and the middle vegetation covers in the study area in July 2008 reduced 9.18% and 18.53%, respectively with respect to that of 2001 while the area of high vegetation covers is 0.66 times bigger than that of 2001; 2) although the fluctuation of the vegetation covers was observed, the main trend indicates that the green vegetation cover has been recovered ecologically from 2001 to 2008; 3) the natural precipitation has larger impact on the sparsely vegetated areas with a correlation coefficient of 0.82 between the PVC and precipitation in the study area. Finally this case study also demonstrates the usefulness of the MODIS data in the monitoring of vegetation cover dynamics and ecological rehabilitation.

Paper Details

Date Published: 9 October 2009
PDF: 8 pages
Proc. SPIE 7471, Second International Conference on Earth Observation for Global Changes, 74710I (9 October 2009); doi: 10.1117/12.836289
Show Author Affiliations
Sha Song, Sichuan Agricultural Univ. (China)
Peking Univ. (China)
Xianfeng Zhang, Peking Univ. (China)
Quan Sun, Peking Univ. (China)
Qing Lu, State Oceanic Administration of China (China)

Published in SPIE Proceedings Vol. 7471:
Second International Conference on Earth Observation for Global Changes
Xianfeng Zhang; Jonathan Li; Guoxiang Liu; Xiaojun Yang, Editor(s)

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