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  4. Monitoring Short-Term Ecological Changes for Desertification and Vegetation Dynamics Using MODIS Imagery in Inner Mongolia, China
 
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Monitoring Short-Term Ecological Changes for Desertification and Vegetation Dynamics Using MODIS Imagery in Inner Mongolia, China

Date Issued
2008
Date
2008
Author(s)
Chiu, Hsien-Hao
URI
http://ntur.lib.ntu.edu.tw//handle/246246/179694
Abstract
Desertification is an environmental problem of major importance in arid environments. Remote sensing has been an efficient technique and comprehensively applied in researching detailed analyses of spatial distribution and surface changing for the phenomenon of desertification.n this study, we examined the spatial and temporal ecological progress of IMAR in north China between Beijing and the Gobi desert. 2000~2006 biweekly/1 km resolution vegetation indices products, derived from MODIS instrument on Terra, were downloaded from Earth Observing System Data Gateway website. After cloud removal process, MVC method was adopted to produce annual MSAVI map, which conservatively estimate desertification condition. Furthermore, by using correlation analysis, this paper present studies on the relationship between climate, human activity and MSAVI in county-based.n the research, it shows that desertification is not an unconvertible retrogression of surface greenness, and the contour of isolated MSAVI values oscillated year by year. During the study duration, we did not detect significant vegetation degradation, but apparent vibration of biomass. Comparing with the 7 images we found the desert area shrunk and spread acutely. In regression analysis, it indicated that annual accumulated precipitation is the principal effective factor and showed higher positive correlation than every human activity factor in spatial distribution and temporal change. The results would provide authorities for arid region management and decision making.
Subjects
desertification
vegetation index
MODIS
IMAR
GIS
SDGs

[SDGs]SDG13

Type
thesis
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ntu-97-P95228001-1.pdf

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(MD5):775355f78396e2dae42a929bb8059af3

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