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Sensors 2018, 18(12), 4319; https://doi.org/10.3390/s18124319

Quantifying Short-Term Urban Land Cover Change with Time Series Landsat Data: A Comparison of Four Different Cities

1
Institute of Space and Earth Information Science, The Chinese University of Hong Kong, New Territories, Hong Kong 999077, China
2
Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen 518000, China
3
Hubei Geomatics Information Center, Hubei Bureau of Surveying, Mapping and Geoinformation, Wuhan 430000, China
4
Jiangsu Academy of Science and Technology for Development, Nanjing 210042, China
5
School of Computer Science, South China Normal University, Guangzhou 510631, China
*
Author to whom correspondence should be addressed.
Received: 30 October 2018 / Revised: 16 November 2018 / Accepted: 4 December 2018 / Published: 7 December 2018
(This article belongs to the Section Remote Sensors)
Full-Text   |   PDF [7762 KB, uploaded 7 December 2018]   |  

Abstract

Short-term characteristics of urban land cover change have been observed and reported from satellite images, although urban landscapes are mainly influenced by anthropogenic factors. These short-term changes in urban areas are caused by rapid urbanization, seasonal climate changes, and phenological ecological changes. Quantifying and understanding these short-term characteristics of changes in various land cover types is important for numerous urban studies, such as urbanization assessments and management. Many previous studies mainly investigated one study area with insufficient datasets. To more reliably and confidently investigate temporal variation patterns, this study employed Fourier series to quantify the seasonal changes in different urban land cover types using all available Landsat images over four different cities, Melbourne, Sao Paulo, Hamburg, and Chicago, within a five-year period (2011–2015). The overall accuracy was greater than 86% and the kappa coefficient was greater than 0.80. The R-squared value was greater than 0.80 and the root mean square error was less than 7.2% for each city. The results indicated that (1) the changing periods for water classes were generally from half a year to one and a half years in different areas; and, (2) urban impervious surfaces changed over periods of approximately 700 days in Melbourne, Sao Paulo, and Hamburg, and a period of approximately 215 days in Chicago, which was actually caused by the unavoidable misclassification from confusions between various land cover types using satellite data. Finally, the uncertainties of these quantification results were analyzed and discussed. These short-term characteristics provided important information for the monitoring and assessment of urban areas using satellite remote sensing technology. View Full-Text
Keywords: seasonal; urban land cover; remote sensing; Landsat; impervious surface seasonal; urban land cover; remote sensing; Landsat; impervious surface
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Zhang, H.; Wang, T.; Zhang, Y.; Dai, Y.; Jia, J.; Yu, C.; Li, G.; Lin, Y.; Lin, H.; Cao, Y. Quantifying Short-Term Urban Land Cover Change with Time Series Landsat Data: A Comparison of Four Different Cities. Sensors 2018, 18, 4319.

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