{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T23:10:58Z","timestamp":1790118658172,"version":"4.0.1"},"reference-count":37,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2022,7,2]],"date-time":"2022-07-02T00:00:00Z","timestamp":1656720000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"the National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2019YFA0607101"],"award-info":[{"award-number":["2019YFA0607101"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"the National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["42171379"],"award-info":[{"award-number":["42171379"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"the National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["42101379"],"award-info":[{"award-number":["42101379"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"the National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["XDA19040500"],"award-info":[{"award-number":["XDA19040500"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"the National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["20210101396JC"],"award-info":[{"award-number":["20210101396JC"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"the National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["20200301014RQ"],"award-info":[{"award-number":["20200301014RQ"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"the National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2017277"],"award-info":[{"award-number":["2017277"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"the National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2021227"],"award-info":[{"award-number":["2021227"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the National Natural Science Foundation of China","award":["2019YFA0607101"],"award-info":[{"award-number":["2019YFA0607101"]}]},{"name":"the National Natural Science Foundation of China","award":["42171379"],"award-info":[{"award-number":["42171379"]}]},{"name":"the National Natural Science Foundation of China","award":["42101379"],"award-info":[{"award-number":["42101379"]}]},{"name":"the National Natural Science Foundation of China","award":["XDA19040500"],"award-info":[{"award-number":["XDA19040500"]}]},{"name":"the National Natural Science Foundation of China","award":["20210101396JC"],"award-info":[{"award-number":["20210101396JC"]}]},{"name":"the National Natural Science Foundation of China","award":["20200301014RQ"],"award-info":[{"award-number":["20200301014RQ"]}]},{"name":"the National Natural Science Foundation of China","award":["2017277"],"award-info":[{"award-number":["2017277"]}]},{"name":"the National Natural Science Foundation of China","award":["2021227"],"award-info":[{"award-number":["2021227"]}]},{"name":"the Strategic Priority Research Program of the Chinese Academy of Sciences","award":["2019YFA0607101"],"award-info":[{"award-number":["2019YFA0607101"]}]},{"name":"the Strategic Priority Research Program of the Chinese Academy of Sciences","award":["42171379"],"award-info":[{"award-number":["42171379"]}]},{"name":"the Strategic Priority Research Program of the Chinese Academy of Sciences","award":["42101379"],"award-info":[{"award-number":["42101379"]}]},{"name":"the Strategic Priority Research Program of the Chinese Academy of Sciences","award":["XDA19040500"],"award-info":[{"award-number":["XDA19040500"]}]},{"name":"the Strategic Priority Research Program of the Chinese Academy of Sciences","award":["20210101396JC"],"award-info":[{"award-number":["20210101396JC"]}]},{"name":"the Strategic Priority Research Program of the Chinese Academy of Sciences","award":["20200301014RQ"],"award-info":[{"award-number":["20200301014RQ"]}]},{"name":"the Strategic Priority Research Program of the Chinese Academy of Sciences","award":["2017277"],"award-info":[{"award-number":["2017277"]}]},{"name":"the Strategic Priority Research Program of the Chinese Academy of Sciences","award":["2021227"],"award-info":[{"award-number":["2021227"]}]},{"name":"the Science and Technology Development Program of Jilin Province, China","award":["2019YFA0607101"],"award-info":[{"award-number":["2019YFA0607101"]}]},{"name":"the Science and Technology Development Program of Jilin Province, China","award":["42171379"],"award-info":[{"award-number":["42171379"]}]},{"name":"the Science and Technology Development Program of Jilin Province, China","award":["42101379"],"award-info":[{"award-number":["42101379"]}]},{"name":"the Science and Technology Development Program of Jilin Province, China","award":["XDA19040500"],"award-info":[{"award-number":["XDA19040500"]}]},{"name":"the Science and Technology Development Program of Jilin Province, China","award":["20210101396JC"],"award-info":[{"award-number":["20210101396JC"]}]},{"name":"the Science and Technology Development Program of Jilin Province, China","award":["20200301014RQ"],"award-info":[{"award-number":["20200301014RQ"]}]},{"name":"the Science and Technology Development Program of Jilin Province, China","award":["2017277"],"award-info":[{"award-number":["2017277"]}]},{"name":"the Science and Technology Development Program of Jilin Province, China","award":["2021227"],"award-info":[{"award-number":["2021227"]}]},{"name":"the Youth Innovation Promotion Association of Chinese Academy of Sciences","award":["2019YFA0607101"],"award-info":[{"award-number":["2019YFA0607101"]}]},{"name":"the Youth Innovation Promotion Association of Chinese Academy of Sciences","award":["42171379"],"award-info":[{"award-number":["42171379"]}]},{"name":"the Youth Innovation Promotion Association of Chinese Academy of Sciences","award":["42101379"],"award-info":[{"award-number":["42101379"]}]},{"name":"the Youth Innovation Promotion Association of Chinese Academy of Sciences","award":["XDA19040500"],"award-info":[{"award-number":["XDA19040500"]}]},{"name":"the Youth Innovation Promotion Association of Chinese Academy of Sciences","award":["20210101396JC"],"award-info":[{"award-number":["20210101396JC"]}]},{"name":"the Youth Innovation Promotion Association of Chinese Academy of Sciences","award":["20200301014RQ"],"award-info":[{"award-number":["20200301014RQ"]}]},{"name":"the Youth Innovation Promotion Association of Chinese Academy of Sciences","award":["2017277"],"award-info":[{"award-number":["2017277"]}]},{"name":"the Youth Innovation Promotion Association of Chinese Academy of Sciences","award":["2021227"],"award-info":[{"award-number":["2021227"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Wetlands provide various ecosystem services to urban areas, which are crucial for sustainable urban management. With intensified urbanization, there has been marked loss of urban natural wetland, degradation, and related urban disasters in the past several decades. Rapid and accurate mapping of urban wetland extent and change is thus critical for improving urban planning toward sustainability. Here, we have developed a rapid method for continuous mapping of urban wetlands (MUW) by combining automatic sample migration and the random forest algorithm (SM&amp;RF), the so-called MUW_SM&amp;RF. Using time series Landsat images, annual training samples were generated through spectral angular distance (SAD) and time series analysis. Combined with the RF algorithm, annual wetland maps in urban areas were derived. Employing the Google Earth Engine platform (GEE), the MUW_SM&amp;RF was evaluated in four metropolitan areas in different geographical and climatic regions of China from 1990 to 2020, including Tianjin, Hangzhou, Guangzhou, and Wuhan. In all four study areas, the generated annual wetland maps had an overall accuracy of over 87% and a Kappa coefficient above 0.815. Compared with previously published datasets, the urban wetland areas derived using the MUW_SM&amp;RF approach achieved improved accuracy and thus demonstrated its robustness for rapid mapping of urban wetlands. Urban wetlands in all four cities had variable distribution patterns and showed significantly decreased trends in the past three decades. The annual urban wetland data product generated by the MUW_SM&amp;RF can provide invaluable information for sustainable urban planning and management, so as for assessment related to the United Nation\u2019s sustainable development goals.<\/jats:p>","DOI":"10.3390\/rs14133191","type":"journal-article","created":{"date-parts":[[2022,7,4]],"date-time":"2022-07-04T20:59:18Z","timestamp":1656968358000},"page":"3191","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":40,"title":["Annual Wetland Mapping in Metropolis by Temporal Sample Migration and Random Forest Classification with Time Series Landsat Data and Google Earth Engine"],"prefix":"10.3390","volume":"14","author":[{"given":"Ming","family":"Wang","sequence":"first","affiliation":[{"name":"Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3101-9153","authenticated-orcid":false,"given":"Dehua","family":"Mao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yeqiao","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Natural Resources Sciences, University of Rhode Island, Kingston, RI 02881, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaishan","family":"Song","sequence":"additional","affiliation":[{"name":"Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hengqi","family":"Yan","sequence":"additional","affiliation":[{"name":"College of Geography and Ocean Sciences, Yanbian University, Yanji 133002, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4548-899X","authenticated-orcid":false,"given":"Mingming","family":"Jia","sequence":"additional","affiliation":[{"name":"Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9865-8235","authenticated-orcid":false,"given":"Zongming","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China"},{"name":"National Earth System Science Data Center of China, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2302","DOI":"10.1038\/s41467-020-15788-7","article-title":"Mapping global urban land for the 21st century with data-driven simulations and Shared Socioeconomic Pathways","volume":"11","author":"Gao","year":"2020","journal-title":"Nat. Commun."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Seto, K.C., Fragkias, M., G\u00fcneralp, B., and Reilly, M.K. (2011). A Meta-Analysis of Global Urban Land Expansion. PLoS ONE, 6.","DOI":"10.1371\/journal.pone.0023777"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2886","DOI":"10.1111\/gcb.12553","article-title":"Urban expansion dynamics and natural habitat loss in China: A multiscale landscape perspective","volume":"20","author":"He","year":"2014","journal-title":"Glob. Chang. Biol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1108\/IJDRBE-11-2011-0042","article-title":"Urban wetlands and disaster resilience of Colombo, Sri Lanka","volume":"5","author":"Hettiarachchi","year":"2014","journal-title":"Int. J. Disaster Resil. Built Environ."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"744","DOI":"10.1672\/0277-5212(2004)024[0744:VUWARO]2.0.CO;2","article-title":"Valuing urban wetlands: A review of non-market valuation studies","volume":"24","author":"Boyer","year":"2004","journal-title":"Wetlands"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1315","DOI":"10.1016\/j.scitotenv.2018.07.236","article-title":"Wetland areas\u2019 direct contributions to residents\u2019 well-being entitle them to high cultural ecosystem values","volume":"646","author":"Pedersen","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1763","DOI":"10.1080\/01431161.2015.1024895","article-title":"Understanding urban wetland dynamics: Cross-scale detection and analysis of remote sensing","volume":"36","author":"Ji","year":"2015","journal-title":"Int. J. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"550","DOI":"10.1016\/j.scitotenv.2018.04.009","article-title":"Conversions between natural wetlands and farmland in China: A multiscale geospatial analysis","volume":"634","author":"Mao","year":"2018","journal-title":"Sci. Total Environ."},{"key":"ref_9","first-page":"535","article-title":"Monitoring loss and recovery of mangrove forests during 42 years: The achievements of mangrove conservation in China","volume":"73","author":"Jia","year":"2018","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.isprsjprs.2020.03.020","article-title":"National wetland mapping in China: A new product resulting from object-based and hierarchical classification of Landsat 8 OLI images","volume":"164","author":"Mao","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1717","DOI":"10.1080\/01431160902926608","article-title":"Monitoring the change of urban wetland using high spatial resolution remote sensing data","volume":"31","author":"Zhou","year":"2010","journal-title":"Int. J. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"378","DOI":"10.1080\/20964471.2019.1690404","article-title":"A generalized supervised classification scheme to produce provincial wetland inventory maps: An application of Google Earth Engine for big geo data processing","volume":"3","author":"Amani","year":"2019","journal-title":"Big Earth Data"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2784","DOI":"10.1080\/01431161.2018.1433343","article-title":"Implementation of machine-learning classification in remote sensing: An applied review","volume":"39","author":"Maxwell","year":"2018","journal-title":"Int. J. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.isprsjprs.2016.01.011","article-title":"Random forest in remote sensing: A review of applications and future directions","volume":"114","author":"Belgiu","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1016\/j.isprsjprs.2020.01.010","article-title":"The migration of training samples towards dynamic global land cover mapping","volume":"161","author":"Huang","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"112670","DOI":"10.1016\/j.rse.2021.112670","article-title":"A novel automatic phenology learning (APL) method of training sample selection using multiple datasets for time-series land cover mapping","volume":"266","author":"Li","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"112285","DOI":"10.1016\/j.rse.2021.112285","article-title":"Rapid, robust, and automated mapping of tidal flats in China using time series Sentinel-2 images and Google Earth Engine","volume":"255","author":"Jia","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1016\/j.isprsjprs.2017.06.013","article-title":"Change detection using landsat time series: A review of frequencies, preprocessing, algorithms, and applications","volume":"130","author":"Zhu","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.rse.2016.12.001","article-title":"Monitoring of wetland inundation dynamics in the Delmarva Peninsula using Landsat time-series imagery from 1985 to 2011","volume":"190","author":"Jin","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Mananze, S., P\u00f4\u00e7as, I., and Cunha, M. (2020). Mapping and Assessing the Dynamics of Shifting Agricultural Landscapes Using Google Earth Engine Cloud Computing, a Case Study in Mozambique. Remote Sens., 12.","DOI":"10.3390\/rs12081279"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.rse.2017.06.031","article-title":"Google Earth Engine: Planetary-scale geospatial analysis for everyone","volume":"202","author":"Gorelick","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1441","DOI":"10.1080\/01431160117207","article-title":"Monitoring urban expansion with remote sensing in China","volume":"22","author":"Ji","year":"2001","journal-title":"Int. J. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"727","DOI":"10.1007\/s11769-018-0988-9","article-title":"Urban Expansion in China Based on Remote Sensing Technology: A Review","volume":"28","author":"Zhang","year":"2018","journal-title":"Chin. Geogr. Sci."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Ottinger, M., Clauss, K., and Kuenzer, C. (2017). Large-Scale Assessment of Coastal Aquaculture Ponds with Sentinel-1 Time Series Data. Remote Sens., 9.","DOI":"10.3390\/rs9050440"},{"key":"ref_25","first-page":"723","article-title":"Land cover changes of China from 2000 to 2010","volume":"34","author":"Wu","year":"2014","journal-title":"Quat. Sci."},{"key":"ref_26","first-page":"41","article-title":"The tasselled cap\u2014A graphic description of the spectral-temporal development of agricultural crops as seen by Landsat","volume":"159","author":"Kauth","year":"1976","journal-title":"LARS Symp."},{"key":"ref_27","first-page":"198","article-title":"Method for wetland type extraction using remote sensing combing object-oriented and tasseled cap transformation","volume":"33","author":"Luo","year":"2017","journal-title":"Trans. Chin. Soc. Agric. Eng."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/0034-4257(79)90013-0","article-title":"Red and photographic infrared linear combinations for monitoring vegetation","volume":"8","author":"Tucker","year":"1979","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1080\/01431160304987","article-title":"Use of normalized difference built-up index in automatically mapping urban areas from TM imagery","volume":"24","author":"Zha","year":"2003","journal-title":"Int. J. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1425","DOI":"10.1080\/01431169608948714","article-title":"The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features","volume":"17","author":"McFeeters","year":"1996","journal-title":"Int. J. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"3025","DOI":"10.1080\/01431160600589179","article-title":"Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery","volume":"27","author":"Xu","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1109\/TSMC.1979.4310076","article-title":"A threshold selection method from gray-level histograms","volume":"9","author":"Otsu","year":"1979","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1016\/j.oceano.2017.03.005","article-title":"An improved Otsu method for oil spill detection from SAR images","volume":"59","author":"Yu","year":"2017","journal-title":"Oceanologia"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"2473","DOI":"10.3390\/rs3112473","article-title":"A New Approach to Change Vector Analysis Using Distance and Similarity Measures","volume":"3","author":"Gillespie","year":"2011","journal-title":"Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1080\/01431160412331269698","article-title":"Random forest classifier for remote sensing classification","volume":"26","author":"Pal","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Phan, T.N., Kuch, V., and Lehnert, L.W. (2020). Land Cover Classification using Google Earth Engine and Random Forest Classifier\u2014The Role of Image Composition. Remote Sens., 12.","DOI":"10.3390\/rs12152411"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"111676","DOI":"10.1016\/j.jenvman.2020.111676","article-title":"Smart solutions for smart cities: Urban wetland mapping using very-high resolution satellite imagery and airborne LiDAR data in the City of St. John\u2019s, NL, Canada","volume":"280","author":"Mahdianpari","year":"2021","journal-title":"J. Environ. Manag."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/13\/3191\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:42:13Z","timestamp":1760139733000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/13\/3191"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,2]]},"references-count":37,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2022,7]]}},"alternative-id":["rs14133191"],"URL":"https:\/\/doi.org\/10.3390\/rs14133191","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,7,2]]}}}