
Proceedings Paper
A method for monitoring land-cover disturbance using satellite time series imagesFormat | Member Price | Non-Member Price |
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Paper Abstract
Land cover disturbance is an abrupt ecosystem change that occurs over a short time period, such as flood, fire, drought
and deforestation. It is crucial to monitor disturbances for rapid response. In this paper, we propose a time series analysis
method for monitoring of land-cover disturbance with high confidence level. The method integrates procedures including
(1) modeling of a piece of history time series data with season-trend model and (2) forecasting with the fitted model and
monitoring disturbances based on significance of prediction errors. The method is tested using 16-day MODIS NDVI
time series to monitor abnormally inundated areas of the Tongjiang section of Heilongjiang River of China, where had
extreme floods and bank break in summer 2013. The test results show that the method could detect the time and areas of
disturbances for each image with no detection delay and with high specified confidence level. The method has few
parameters to be specified and less computation complexity so that it could be developed for monitoring of land-cover
disturbance on large scales.
Paper Details
Date Published: 8 November 2014
PDF: 6 pages
Proc. SPIE 9260, Land Surface Remote Sensing II, 926038 (8 November 2014); doi: 10.1117/12.2068929
Published in SPIE Proceedings Vol. 9260:
Land Surface Remote Sensing II
Thomas J. Jackson; Jing Ming Chen; Peng Gong; Shunlin Liang, Editor(s)
PDF: 6 pages
Proc. SPIE 9260, Land Surface Remote Sensing II, 926038 (8 November 2014); doi: 10.1117/12.2068929
Show Author Affiliations
Zengguang Zhou, Institute of Remote Sensing and Digital Earth (China)
Univ. of Chinese Academy of Sciences (China)
Ping Tang, Institute of Remote Sensing and Digital Earth (China)
Univ. of Chinese Academy of Sciences (China)
Ping Tang, Institute of Remote Sensing and Digital Earth (China)
Zheng Zhang, Institute of Remote Sensing and Digital Earth (China)
Univ. of Chinese Academy of Sciences (China)
Univ. of Chinese Academy of Sciences (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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