{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T01:58:21Z","timestamp":1761789501945,"version":"build-2065373602"},"reference-count":65,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2018,12,7]],"date-time":"2018-12-07T00:00:00Z","timestamp":1544140800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41401370"],"award-info":[{"award-number":["41401370"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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\u20132015). 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.<\/jats:p>","DOI":"10.3390\/s18124319","type":"journal-article","created":{"date-parts":[[2018,12,10]],"date-time":"2018-12-10T03:36:41Z","timestamp":1544413001000},"page":"4319","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Quantifying Short-Term Urban Land Cover Change with Time Series Landsat Data: A Comparison of Four Different Cities"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6135-9442","authenticated-orcid":false,"given":"Hongsheng","family":"Zhang","sequence":"first","affiliation":[{"name":"Institute of Space and Earth Information Science, The Chinese University of Hong Kong, New Territories, Hong Kong 999077, China"},{"name":"Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen 518000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5149-9495","authenticated-orcid":false,"given":"Ting","family":"Wang","sequence":"additional","affiliation":[{"name":"Institute of Space and Earth Information Science, The Chinese University of Hong Kong, New Territories, Hong Kong 999077, China"},{"name":"Hubei Geomatics Information Center, Hubei Bureau of Surveying, Mapping and Geoinformation, Wuhan 430000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuhan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Space and Earth Information Science, The Chinese University of Hong Kong, New Territories, Hong Kong 999077, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yiru","family":"Dai","sequence":"additional","affiliation":[{"name":"Institute of Space and Earth Information Science, The Chinese University of Hong Kong, New Territories, Hong Kong 999077, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiangjie","family":"Jia","sequence":"additional","affiliation":[{"name":"Institute of Space and Earth Information Science, The Chinese University of Hong Kong, New Territories, Hong Kong 999077, China"},{"name":"Jiangsu Academy of Science and Technology for Development, Nanjing 210042, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chang","family":"Yu","sequence":"additional","affiliation":[{"name":"Institute of Space and Earth Information Science, The Chinese University of Hong Kong, New Territories, Hong Kong 999077, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gang","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of Space and Earth Information Science, The Chinese University of Hong Kong, New Territories, Hong Kong 999077, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yinyi","family":"Lin","sequence":"additional","affiliation":[{"name":"Institute of Space and Earth Information Science, The Chinese University of Hong Kong, New Territories, Hong Kong 999077, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hui","family":"Lin","sequence":"additional","affiliation":[{"name":"Institute of Space and Earth Information Science, The Chinese University of Hong Kong, New Territories, Hong Kong 999077, China"},{"name":"Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen 518000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Cao","sequence":"additional","affiliation":[{"name":"School of Computer Science, South China Normal University, Guangzhou 510631, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,12,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1016\/j.rse.2013.06.003","article-title":"Balancing misclassification errors of land cover classification maps using support vector machines and Landsat imagery in the Maipo river basin (central chile, 1975\u20132010)","volume":"137","author":"Puertas","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"16083","DOI":"10.1073\/pnas.1211658109","article-title":"Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools","volume":"109","author":"Seto","year":"2012","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1016\/S0959-3780(01)00007-3","article-title":"The causes of land-use and land-cover change: Moving beyond the myths","volume":"11","author":"Lambin","year":"2001","journal-title":"Glob. Environ. Chang."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.rse.2011.02.030","article-title":"Remote sensing of impervious surfaces in the urban areas: Requirements, methods, and trends","volume":"117","author":"Weng","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"661","DOI":"10.1080\/01431160310001654950","article-title":"A global analysis of urban reflectance","volume":"26","author":"Small","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_6","first-page":"259","article-title":"Landsat 8 vs. Landsat 5: A comparison based on urban and pen-urban land cover mapping","volume":"35","author":"Poursanidis","year":"2015","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/0034-4257(95)00233-2","article-title":"An assessment of several linear change detection techniques for mapping forest mortality using multitemporal Landsat TM data","volume":"56","author":"Collins","year":"1996","journal-title":"Remote Sens. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"4173","DOI":"10.3390\/rs6054173","article-title":"Water feature extraction and change detection using multitemporal Landsat imagery","volume":"6","author":"Rokni","year":"2014","journal-title":"Remote Sens."},{"key":"ref_9","first-page":"1333","article-title":"Wetland landscape spatio-temporal degradation dynamics using the new Google Earth Engine cloud-based platform: Opportunities for non-specialists in remote sensing","volume":"59","author":"Alonso","year":"2016","journal-title":"Trans. ASABE"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1787","DOI":"10.1080\/014311600209742","article-title":"Wetland change detection on the Kafue Flats, Zambia, by classification of a multitemporal remote sensing image dataset","volume":"21","author":"Munyati","year":"2000","journal-title":"Int. J. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"5767","DOI":"10.1080\/01431160802060912","article-title":"Modelling spatial-temporal change of Poyang lake using multitemporal Landsat imagery","volume":"29","author":"Hui","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"17","DOI":"10.3389\/feart.2017.00017","article-title":"Exploring Google earth engine platform for Big Data Processing: Classification of multi-temporal satellite imagery for crop mapping","volume":"5","author":"Shelestov","year":"2017","journal-title":"Front. Earth Sci."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1016\/j.rse.2016.02.016","article-title":"Mapping paddy rice planting area in northeastern Asia with Landsat 8 images, phenology-based algorithm and Google Earth Engine","volume":"185","author":"Dong","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Roodposhti, M.S., Aryal, J., and Bryan, B.A. (2018). A novel algorithm for calculating transition potential in cellular automata models of land-use\/cover change. Environ. Modell. Softw., in press.","DOI":"10.1016\/j.envsoft.2018.10.006"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"3359","DOI":"10.1109\/JSTARS.2015.2428306","article-title":"A relative density ratio-based framework for detection of land cover changes in MODIS NDVI time series","volume":"9","author":"Anees","year":"2016","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"852","DOI":"10.1109\/TGRS.2005.843569","article-title":"Use of the Bradley-Terry model to quantify association in remotely sensed images","volume":"43","author":"Stein","year":"2005","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"452","DOI":"10.1109\/TIP.2002.999678","article-title":"An adaptive semiparametric and context-based approach to unsupervised change detection in multitemporal remote-sensing images","volume":"11","author":"Bruzzone","year":"2002","journal-title":"IEEE Trans. Image Process."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1016\/0034-4257(80)90021-8","article-title":"Monitoring land-cover change by principal component analysis of multitemporal Landsat data","volume":"10","author":"Byrne","year":"1980","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.rse.2015.06.007","article-title":"A 30-year (1984\u20132013) record of annual urban dynamics of Beijing city derived from Landsat data","volume":"166","author":"Li","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1296","DOI":"10.1016\/j.proenv.2010.10.140","article-title":"LUCC and landscape pattern variation of wetlands in warm-rainy Southern China over two decades","volume":"2","author":"Song","year":"2010","journal-title":"Procedia Environ. Sci."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1985","DOI":"10.1080\/01431160110075532","article-title":"Monitoring land-use change in the Pearl River Delta using Landsat TM","volume":"23","author":"Seto","year":"2002","journal-title":"Int. J. Remote Sens."},{"key":"ref_22","first-page":"46","article-title":"Measures of spatio-temporal accuracy for time series land cover data","volume":"41","author":"Tsutsumida","year":"2015","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"308","DOI":"10.1016\/j.foreco.2007.08.017","article-title":"Analysis of land-cover\/use change dynamics in Manica Province in Mozambique in a period of transition (1990\u20132004)","volume":"254","author":"Jansen","year":"2008","journal-title":"For. Ecol Manag."},{"key":"ref_24","first-page":"1895","article-title":"Quantification of impervious surface in the Snohomish water resources inventory area of western Washington from 1972\u20132006","volume":"112","author":"Powell","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1016\/j.rse.2012.03.029","article-title":"Exurban development derived from Landsat from 1986 to 2009 surrounding the district of Columbia, USA","volume":"124","author":"Lookingbill","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.rse.2012.10.025","article-title":"Urban growth of the Washington, DC\u2013Baltimore, MD metropolitan region from 1984 to 2010 by annual, Landsat-based estimates of impervious cover","volume":"129","author":"Sexton","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2015.12.027","article-title":"Characterizing the magnitude, timing and duration of urban growth from time series of Landsat-based estimates of impervious cover","volume":"175","author":"Song","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"746","DOI":"10.1080\/17538947.2013.781241","article-title":"Seasonal effects of impervious surface estimation in subtropical monsoon regions","volume":"7","author":"Zhang","year":"2014","journal-title":"Int. J. Digit. Earth"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1016\/j.isprsjprs.2016.01.003","article-title":"Annual dynamics of impervious surface in the Pearl River Delta, China, from 1988 to 2013, using time series Landsat imagery","volume":"113","author":"Zhang","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"4807","DOI":"10.1080\/01431160802665926","article-title":"Estimating impervious surfaces using linear spectral mixture analysis with multitemporal ASTER images","volume":"30","author":"Weng","year":"2009","journal-title":"Int. J. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1393","DOI":"10.14358\/PERS.73.12.1393","article-title":"Seasonal sensitivity analysis of impervious surface estimation with satellite imagery","volume":"73","author":"Wu","year":"2007","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"3537","DOI":"10.1080\/01431161.2018.1444290","article-title":"Annual dynamics of impervious surfaces at city level of Pearl River Delta metropolitan","volume":"39","author":"Xu","year":"2018","journal-title":"Int. J. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.rse.2015.04.019","article-title":"Land surface phenology along urban to rural gradients in the US Great Plains","volume":"165","author":"Walker","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2004GL020137","article-title":"The footprint of urban climates on vegetation phenology","volume":"31","author":"Zhang","year":"2004","journal-title":"Geophys. Res. Lett."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"829","DOI":"10.1007\/s00477-012-0680-z","article-title":"Multi-city sustainable regional urban growth simulation-MSRUGS: A case study along the mid-section of Silk Road of China","volume":"28","author":"Xie","year":"2014","journal-title":"Stoch. Environ. Res. Risk Assess."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1016\/j.landurbplan.2013.08.008","article-title":"Assessing and comparing relationships between urban environmental stewardship networks and land cover in Baltimore and Seattle","volume":"120","author":"Romolini","year":"2013","journal-title":"Landsc. Urban Plan."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1016\/j.rse.2005.08.006","article-title":"Land cover classification and change analysis of the Twin Cities (Minnesota) Metropolitan Area by multitemporal Landsat remote sensing","volume":"98","author":"Yuan","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Bauer, M.E., Yuan, F., and Sawaya, K.E. (2004). Multi-temporal Landsat image classification and change analysis of land cover in the Twin Cities (Minnesota) Metropolitan area. Analysis of Multi-Temporal Remote Sensing Images, World Scientific.","DOI":"10.1142\/9789812702630_0041"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1127\/0941-2948\/2006\/0130","article-title":"World map of the K\u00f6ppen-Geiger climate classification updated","volume":"15","author":"Kottek","year":"2006","journal-title":"Meteorol. Musikz."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1080\/1573062X.2015.1086008","article-title":"Water governance and the quality of water services in the city of Melbourne","volume":"14","year":"2017","journal-title":"Urban Water J."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"567","DOI":"10.1016\/j.jtrangeo.2010.03.003","article-title":"Concentration and the formation of multi-port gateway regions in the European container port system: An update","volume":"18","author":"Notteboom","year":"2010","journal-title":"J. Transp. Geogr."},{"key":"ref_42","first-page":"831","article-title":"The Landsat program: Its origins, evolution, and impacts","volume":"63","author":"Lauer","year":"1997","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"2796","DOI":"10.1109\/TGRS.2004.839083","article-title":"Landsat-7 ETM+ on-orbit reflective-band radiometric characterization","volume":"42","author":"Scaramuzza","year":"2004","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1016\/S0034-4257(00)00169-3","article-title":"Classification and change detection using Landsat TM data: When and how to correct atmospheric effects?","volume":"75","author":"Song","year":"2001","journal-title":"Remote Sens. Environ."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"755","DOI":"10.1109\/TGRS.1990.573015","article-title":"Classification accuracy for the MOS-1 MESSR data before and after the atmospheric correction","volume":"28","author":"Kawata","year":"1990","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"799","DOI":"10.1080\/01431168408948861","article-title":"Derivation of atmospheric correction procedures for Landsat MSS with particular reference to urban data","volume":"5","author":"Forster","year":"1984","journal-title":"Int. J. Remote Sens."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/0034-4257(77)90005-0","article-title":"The effect of the atmosphere on the classification of satellite observations to identify surface features","volume":"6","author":"Fraser","year":"1977","journal-title":"Remote Sens. Environ."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/S0034-4257(95)00196-4","article-title":"Identifying terrestrial carbon sinks: Classification of successional stages in regenerating tropical forest from Landsat TM data","volume":"55","author":"Foody","year":"1996","journal-title":"Remote Sens. Environ."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"989","DOI":"10.1080\/01431168908903939","article-title":"Digital change detection techniques using remotely-sensed data","volume":"10","author":"Singh","year":"1989","journal-title":"Int. J. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"024008","DOI":"10.1088\/1748-9326\/9\/2\/024008","article-title":"Expansion and growth in Chinese cities, 1978\u20132010","volume":"9","author":"Schneider","year":"2014","journal-title":"Environ. Res. Lett."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"2607","DOI":"10.1080\/01431161.2012.748992","article-title":"Finer resolution observation and monitoring of global land cover: First mapping results with Landsat TM and ETM+ data","volume":"34","author":"Gong","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"689","DOI":"10.1016\/j.rse.2012.06.006","article-title":"Monitoring land cover change in urban and pen-urban areas using dense time stacks of Landsat satellite data and a data mining approach","volume":"124","author":"Schneider","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1016\/j.rse.2013.07.008","article-title":"Estimating deforestation in tropical humid and dry forests in Madagascar from 2000 to 2010 using multi-date Landsat satellite images and the random forests classifier","volume":"139","author":"Grinand","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_54","unstructured":"Jensen, J.R. (2007). Introductory Digital Image Processing: A Remote Sensing Perspective, Pearson Education Ltd.. [3rd ed.]."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1146","DOI":"10.1080\/01431161.2012.718459","article-title":"Feature extraction for high-resolution imagery based on human visual perception","volume":"34","author":"Zhang","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Vapnik, V. (1995). The Nature of Statistical Learning Theory, Springer-Verlag.","DOI":"10.1007\/978-1-4757-2440-0"},{"key":"ref_57","unstructured":"Vapnik, V. (1998). Statistical Learning Theory, Wiley."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1016\/j.apgeog.2013.02.005","article-title":"Identification of land cover\/land use changes in the greater area of the Preveza peninsula in Greece using Landsat satellite data","volume":"40","author":"Kolios","year":"2013","journal-title":"Appl. Geogr."},{"key":"ref_59","first-page":"148","article-title":"A comparison study of impervious surfaces estimation using optical and SAR remote sensing images","volume":"18","author":"Zhang","year":"2012","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"284","DOI":"10.1109\/LGRS.2016.2628406","article-title":"GA-SVM algorithm for improving land-cover classification using SAR and optical remote sensing data","volume":"14","author":"Sukawattanavijit","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.rse.2013.10.028","article-title":"Improving the impervious surface estimation with combined use of optical and SAR remote sensing images","volume":"141","author":"Zhang","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/j.isprsjprs.2010.11.001","article-title":"Support vector machines in remote sensing: A review","volume":"66","author":"Mountrakis","year":"2011","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_63","first-page":"1671","article-title":"Assessing Landsat classification accuracy using discrete multivariate-analysis statistical techniques","volume":"49","author":"Congalton","year":"1983","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"4407","DOI":"10.1080\/01431161.2011.552923","article-title":"Death to kappa: Birth of quantity disagreement and allocation disagreement for accuracy assessment","volume":"32","author":"Pontius","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"743","DOI":"10.1002\/qre.1425","article-title":"Nonlinear profile monitoring of reflow process data based on the sum of sine functions","volume":"29","author":"Fan","year":"2013","journal-title":"Qual. Reliab. Eng. Int."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/12\/4319\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:31:58Z","timestamp":1760196718000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/12\/4319"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,12,7]]},"references-count":65,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2018,12]]}},"alternative-id":["s18124319"],"URL":"https:\/\/doi.org\/10.3390\/s18124319","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2018,12,7]]}}}