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Article: Quantifying short-term urban land cover change with time series landsat data: A comparison of four different cities

TitleQuantifying short-term urban land cover change with time series landsat data: A comparison of four different cities
Authors
KeywordsLandsat
Urban land cover
Seasonal
Remote sensing
Impervious surface
Issue Date2018
Citation
Sensors (Switzerland), 2018, v. 18, n. 12, article no. 4319 How to Cite?
Abstract© 2018 by the authors. Licensee MDPI, Basel, Switzerland. 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.
Persistent Identifierhttp://hdl.handle.net/10722/277607
ISSN
2018 Impact Factor: 3.031
2020 SCImago Journal Rankings: 0.636
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorZhang, Hongsheng-
dc.contributor.authorWang, Ting-
dc.contributor.authorZhang, Yuhan-
dc.contributor.authorDai, Yiru-
dc.contributor.authorJia, Jiangjie-
dc.contributor.authorYu, Chang-
dc.contributor.authorLi, Gang-
dc.contributor.authorLin, Yinyi-
dc.contributor.authorLin, Hui-
dc.contributor.authorCao, Yang-
dc.date.accessioned2019-09-27T08:29:27Z-
dc.date.available2019-09-27T08:29:27Z-
dc.date.issued2018-
dc.identifier.citationSensors (Switzerland), 2018, v. 18, n. 12, article no. 4319-
dc.identifier.issn1424-8220-
dc.identifier.urihttp://hdl.handle.net/10722/277607-
dc.description.abstract© 2018 by the authors. Licensee MDPI, Basel, Switzerland. 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.-
dc.languageeng-
dc.relation.ispartofSensors (Switzerland)-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectLandsat-
dc.subjectUrban land cover-
dc.subjectSeasonal-
dc.subjectRemote sensing-
dc.subjectImpervious surface-
dc.titleQuantifying short-term urban land cover change with time series landsat data: A comparison of four different cities-
dc.typeArticle-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.3390/s18124319-
dc.identifier.pmid30544553-
dc.identifier.scopuseid_2-s2.0-85058422150-
dc.identifier.volume18-
dc.identifier.issue12-
dc.identifier.spagearticle no. 4319-
dc.identifier.epagearticle no. 4319-
dc.identifier.isiWOS:000454817100238-
dc.identifier.issnl1424-8220-

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