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Proceedings Paper

Analysis on vegetation changes of Maqu alpine wetlands in the Yellow River source region
Author(s): Lin Chu; Chong Huang; Gaohuan Liu; Qingsheng Liu; Jun Zhao
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Paper Abstract

The Maqu alpine wetlands have irreplaceable function in maintaining ecological balance and conserving biodiversity to the upriver regions of the Yellow River. In last 30 years, Global warming causes significant changes in vegetation. However, the Maqu alpine wetland is undergoing a degradation caused by warming and drying climate. Aim of this study is to investigate the vegetation changes for a better understanding the consequence of climate variations to the wetland degradation. Based on the Landsat TM images of 2000 and 2010, the landscape pattern changes were analyzed by classification statistics, dynamic transfer matrix and landscape pattern indices. Based on the MOD11A2 and MOD13A2 data from 2000 to 2010, NDVI and land surface temperature (LST) dataset were extracted. NDVI time-series data processed with S-G filtering method was used to find temporal and spatial variation characteristics, and linear trend was analyzed by ordinary least squares regression method. NDVI and LST were used to construct Ts-NDVI feature space, and then TVDI was obtained to explore changes of soil moisture. Relationship between climate variations and wetland degradation were found by ordinary least squares regression method. Results indicated that both wetland area and landscape heterogeneity decreased. Annual NDVI presented fluctuated decreasing trend and there was strong spatial heterogeneity in patterns of NDVI change. Annual TVDI proved to have an increasing trend which showed the drought gradually intensified. “Warming and drought” climate appear to be critical factors contributing to wetland degradation. Precipitation has a stronger correlation rather than temperature.

Paper Details

Date Published: 8 November 2014
PDF: 9 pages
Proc. SPIE 9260, Land Surface Remote Sensing II, 92602O (8 November 2014); doi: 10.1117/12.2068521
Show Author Affiliations
Lin Chu, Institute of Geographic Sciences and Natural Resources Research (China)
Univ. of Chinese Academy of Sciences (China)
Chong Huang, Institute of Geographical Sciences and Natural Resources Research (China)
Gaohuan Liu, Institute of Geographic Sciences and Natural Resources Research (China)
Qingsheng Liu, Institute of Geographical Sciences and Natural Resources Research (China)
Jun Zhao, Office of Dongying Municipal Government (China)

Published in SPIE Proceedings Vol. 9260:
Land Surface Remote Sensing II
Thomas J. Jackson; Jing Ming Chen; Peng Gong; Shunlin Liang, Editor(s)

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