{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T14:52:11Z","timestamp":1770907931550,"version":"3.50.1"},"reference-count":72,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2018,10,14]],"date-time":"2018-10-14T00:00:00Z","timestamp":1539475200000},"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":["41601406"],"award-info":[{"award-number":["41601406"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the Strategic Priority Research Program of the Chinese Academy of Sciences","award":["XDA19040500"],"award-info":[{"award-number":["XDA19040500"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Dynamics of surface water is of great significance to understand the impacts of global changes and human activities on water resources. Remote sensing provides many advantages in monitoring surface water; however, in large scale, the efficiency of traditional remote sensing methods is extremely low because these methods consume a high amount of manpower, storage, and computing resources. In this paper, we propose a new method for quickly determining what the annual maximal and minimal surface water extent is. The maximal and minimal water extent in the year of 1990, 2000, 2010 and 2017 in the Middle Yangtze River Basin in China were calculated on the Google Earth Engine platform. This approach takes full advantage of the data and computing advantages of the Google Earth Engine\u2019s cloud platform, processed 2343 scenes of Landsat images. Firstly, based on the estimated value of cloud cover for each pixel, the high cloud covered pixels were removed to eliminate the cloud interference and improve the calculation efficiency. Secondly, the annual greenest and wettest images were mosaiced based on vegetation index and surface water index, then the minimum and maximum surface water extents were obtained by the Random Forest Classification. Results showed that (1) the yearly minimal surface water extents were 14,751.23 km2, 14,403.48 km2, 13,601.48 km2, and 15,697.42 km2, in the year of 1990, 2000, 2010, and 2017, respectively. (2) The yearly maximal surface water extents were 18,174.76 km2, 20,671.83 km2, 19,097.73 km2, and 18,235.95 km2, in the year of 1990, 2000, 2010, and 2017, respectively. (3) The accuracies of surface water classification ranged from 86% to 93%. Additionally, the causes of these changes were analyzed. The accuracy evaluation and comparison with other research results show that this method is reliable, novel, and fast in terms of calculating the maximal and minimal surface water extent. In addition, the proposed method can easily be implemented in other regions worldwide.<\/jats:p>","DOI":"10.3390\/rs10101635","type":"journal-article","created":{"date-parts":[[2018,10,15]],"date-time":"2018-10-15T03:43:01Z","timestamp":1539574981000},"page":"1635","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":147,"title":["Long-Term Surface Water Dynamics Analysis Based on Landsat Imagery and the Google Earth Engine Platform: A Case Study in the Middle Yangtze River Basin"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4737-0717","authenticated-orcid":false,"given":"Chao","family":"Wang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"},{"name":"Collaborative Innovation Center of Geospatial Technology, Wuhan 430079, China"}]},{"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"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3521-9972","authenticated-orcid":false,"given":"Nengcheng","family":"Chen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"},{"name":"Collaborative Innovation Center of Geospatial Technology, Wuhan 430079, China"}]},{"given":"Wei","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"},{"name":"Collaborative Innovation Center of Geospatial Technology, Wuhan 430079, China"}]}],"member":"1968","published-online":{"date-parts":[[2018,10,14]]},"reference":[{"key":"ref_1","unstructured":"United Nations Educational, Scientific and Cultural Organization (2018, July 19). The UN World Water Development Report 2015, Water for a Sustainable World. Available online: http:\/\/www.unesco.org\/new\/en\/natural-sciences\/environment\/water\/wwap\/wwdr\/2015-water-for-a-sustainable-world\/."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Carroll, M., Wooten, M., DiMiceli, C., Sohlberg, R., and Kelly, M. (2016). Quantifying surface water dynamics at 30 m spatial resolution in the north american high northern latitudes 1991\u20132011. Remote Sens., 8.","DOI":"10.3390\/rs8080622"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Goldblatt, R., You, W., Hanson, G., and Khandelwal, A.K. (2016). Detecting the boundaries of urban areas in india: A dataset for pixel-based image classification in google earth engine. Remote Sens., 8.","DOI":"10.3390\/rs8080634"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1672\/1","article-title":"Vegetation patterns resulting from spatial and temporal variability in hydrology, soils, and trampling in an isolated basin marsh, new hampshire, USA","volume":"25","author":"Koning","year":"2005","journal-title":"Wetlands"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1016\/j.ecolind.2009.05.006","article-title":"Terrestrial birds as indicators of agricultural-induced changes and associated loss in conservation value of mediterranean wetlands","volume":"10","author":"Robledano","year":"2010","journal-title":"Ecol. Indic."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"418","DOI":"10.1038\/nature20584","article-title":"High-resolution mapping of global surface water and its long-term changes","volume":"540","author":"Pekel","year":"2016","journal-title":"Nature"},{"key":"ref_7","first-page":"135","article-title":"Monitoring the dynamics of surface water fraction from modis time series in a mediterranean environment","volume":"66","author":"Li","year":"2018","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1038\/scientificamerican0168-54","article-title":"Remote sensing of natural resources","volume":"218","author":"Colwell","year":"1968","journal-title":"Sci. Am."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/S0034-4257(70)80014-1","article-title":"Some comments on reflectance measurements of wet soils","volume":"1","author":"Planet","year":"1970","journal-title":"Remote Sens. Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1080\/02626668909491360","article-title":"Role of satellite remote sensing for monitoring of surface water resources in an arid environment","volume":"34","author":"Sharma","year":"1989","journal-title":"Hydrol. Sci. J."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1038\/359373a0","article-title":"The hydrological cycle and its influence on climate","volume":"359","author":"Chahine","year":"1992","journal-title":"Nature"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"745","DOI":"10.1175\/1520-0450(1995)034<0745:TRSOSS>2.0.CO;2","article-title":"Thermal remote sensing of surface soil water content with partial vegetation cover for incorporation into climate models","volume":"34","author":"Gillies","year":"1995","journal-title":"J. Appl. Meteorol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1006\/jema.1996.0077","article-title":"Estimation of surface water quality changes in response to land use change: Application of the export coefficient model using remote sensing and geographical information system","volume":"48","author":"Mattikalli","year":"1996","journal-title":"J. Environ. Manag."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Kite, G., and Pietroniro, A. (2000). Remote sensing of surface water. Remote Sensing in Hydrology and Water Management, Springer.","DOI":"10.1007\/978-3-642-59583-7_10"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1111\/1467-8306.93105","article-title":"Water storage of the central amazon floodplain measured with gis and remote sensing imagery","volume":"93","author":"Alsdorf","year":"2003","journal-title":"Ann. Assoc. Am. Geogr."},{"key":"ref_16","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_17","first-page":"589","article-title":"A study on information extraction of water body with the modified normalized difference water index (mndwi)","volume":"5","year":"2005","journal-title":"J. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Alsdorf, D.E., Rodriguez, E., and Lettenmaier, D.P. (2007). Measuring surface water from space. Rev. Geophys., 45.","DOI":"10.1029\/2006RG000197"},{"key":"ref_19","unstructured":"Salomon, J., Hodges, J.C., Friedl, M., Schaaf, C., Strahler, A., Gao, F., Schneider, A., Zhang, X., El Saleous, N., and Wolfe, R.E. (2004, January 20\u201324). Global Land-Water Mask Derived from Modis Nadir Brdf-Adjusted Reflectances (Nbar) and the Modis Land Cover Algorithm. Proceedings of the 2004 IEEE International Geoscience and Remote Sensing Symposium, 2004. IGARSS\u201904, Anchorage, AK, USA."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Carroll, M.L., and Loboda, T.V. (2017). Multi-decadal surface water dynamics in north american tundra. Remote Sens., 9.","DOI":"10.3390\/rs9050497"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1016\/j.rse.2015.11.003","article-title":"Water observations from space: Mapping surface water from 25 years of landsat imagery across australia","volume":"174","author":"Mueller","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1080\/17538947.2015.1026420","article-title":"A global, high-resolution (30-m) inland water body dataset for 2000: First results of a topographic\u2013spectral classification algorithm","volume":"9","author":"Feng","year":"2016","journal-title":"Int. J. Digit. Earth"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1016\/j.rse.2016.02.040","article-title":"Reconstructing semi-arid wetland surface water dynamics through spectral mixture analysis of a time series of landsat satellite images (1984\u20132011)","volume":"177","author":"Halabisky","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2227","DOI":"10.5194\/hess-20-2227-2016","article-title":"Modeling 25 years of spatio-temporal surface water and inundation dynamics on large river basin scale using time series of earth observation data","volume":"20","author":"Heimhuber","year":"2016","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1016\/j.rse.2016.02.034","article-title":"Surface water extent dynamics from three decades of seasonally continuous landsat time series at subcontinental scale in a semi-arid region","volume":"178","author":"Tulbure","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Pham-Duc, B., Prigent, C., and Aires, F. (2017). Surface water monitoring within cambodia and the vietnamese mekong delta over a year, with sentinel-1 sar observations. Water, 9.","DOI":"10.3390\/w9060366"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1080\/17538940701782577","article-title":"Water resource applications with radarsat-2\u2014A preview","volume":"1","author":"Brisco","year":"2008","journal-title":"Int. J. Digit. Earth"},{"key":"ref_28","first-page":"171","article-title":"Study on the automatic extraction of water body information from spot- 5 images using decision tree algorithm","volume":"31","author":"Deng","year":"2005","journal-title":"J. Zhejiang Univ. (Agric. Life Sci.)"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1080\/01431160010006917","article-title":"Analytical algorithms for lake water tsm estimation for retrospective analyses of tm and spot sensor data","volume":"23","author":"Dekker","year":"2002","journal-title":"Int. J. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1016\/j.rse.2003.04.006","article-title":"Extending satellite remote sensing to local scales: Land and water resource monitoring using high-resolution imagery","volume":"88","author":"Sawaya","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1331","DOI":"10.13031\/trans.59.11608","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_32","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_33","unstructured":"(2018, August 21). Earth Engine Code Editor. Available online: https:\/\/code.earthengine.google.com\/."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Trianni, G., Angiuli, E., Lisini, G., and Gamba, P. (2014, January 13\u201318). Human settlements from landsat data using google earth engine. Proceedings of the 2014 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Quebec City, QC, Canada.","DOI":"10.1109\/IGARSS.2014.6946715"},{"key":"ref_35","first-page":"36","article-title":"Mapping woody vegetation clearing in Queensland, Australia from landsat imagery using the google earth engine","volume":"1","author":"Johansen","year":"2015","journal-title":"Remote Sens. Appl. Soc. Environ."},{"key":"ref_36","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_37","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/j.isprsjprs.2017.07.011","article-title":"A mangrove forest map of China in 2015: Analysis of time series landsat 7\/8 and sentinel-1a imagery in google earth engine cloud computing platform","volume":"131","author":"Chen","year":"2017","journal-title":"Int. J. Photogramm. Remote Sens."},{"key":"ref_38","first-page":"199","article-title":"Multitemporal settlement and population mapping from landsat using google earth engine","volume":"35","author":"Patel","year":"2015","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_39","unstructured":"(2018, July 17). Surface Water Changes (1985\u20132016). Available online: http:\/\/aqua-monitor.deltares.nl."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"810","DOI":"10.1038\/nclimate3111","article-title":"Earth\u2019s surface water change over the past 30 years","volume":"6","author":"Donchyts","year":"2016","journal-title":"Nat. Clim. Chang."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1248","DOI":"10.1016\/j.jenvman.2010.12.007","article-title":"Lake area changes in the middle Yangtze region of China over the 20th century","volume":"92","author":"Du","year":"2011","journal-title":"J. Environ. Manag."},{"key":"ref_42","unstructured":"(2018, January 23). Notice of the National Development and Reform Commission on Issuing the Development Plan for the City Cluster along the Middle Yangtze River Basin, Available online: http:\/\/www.ndrc.gov.cn\/zcfb\/zcfbtz\/201504\/t20150416_688229.html."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1016\/j.geomorph.2006.03.017","article-title":"On the river\u2013lake relationship of the middle Yangtze reaches","volume":"85","author":"Yin","year":"2007","journal-title":"Geomorphology"},{"key":"ref_44","unstructured":"(2018, January 15). Overview of the Yangtze River, Available online: http:\/\/www.cjw.gov.cn\/zjzx\/cjyl\/."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"479","DOI":"10.1623\/hysj.50.3.479.65022","article-title":"Trends in frequency of precipitation extremes in the Yangtze river basin, China: 1960\u20132003\/tendances d\u2019\u00e9volution de la fr\u00e9quence des pr\u00e9cipitations extr\u00eames entre 1960 et 2003 dans le bassin versant du fleuve Yangtze (chine)","volume":"50","author":"Su","year":"2005","journal-title":"Hydrol. Sci. J."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/S0169-555X(01)00106-4","article-title":"Yangtze river of China: Historical analysis of discharge variability and sediment flux","volume":"41","author":"Chen","year":"2001","journal-title":"Geomorphology"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1016\/j.jhydrol.2013.03.049","article-title":"Large-scale hydrodynamic modeling of the middle Yangtze river basin with complex river\u2013lake interactions","volume":"492","author":"Lai","year":"2013","journal-title":"J. Hydrol."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Liu, D., and Chen, N. (2017). Satellite monitoring of urban land change in the middle Yangtze river basin urban agglomeration, China between 2000 and 2016. Remote Sens., 9.","DOI":"10.3390\/rs9111086"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.jhydrol.2005.11.029","article-title":"Analysis of spatial distribution and temporal trend of reference evapotranspiration and pan evaporation in Changjiang (Yangtze river) catchment","volume":"327","author":"Xu","year":"2006","journal-title":"J. Hydrol."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1016\/j.ecolmodel.2015.07.022","article-title":"Ecological footprint analysis for urban agglomeration sustainability in the middle stream of the Yangtze river","volume":"318","author":"Gu","year":"2015","journal-title":"Ecol. Model."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Wilson, A.M., and Jetz, W. (2016). Remotely sensed high-resolution global cloud dynamics for predicting ecosystem and biodiversity distributions. PLoS Biol., 14.","DOI":"10.1371\/journal.pbio.1002415"},{"key":"ref_52","unstructured":"(2018, January 16). Landsat Algorithms\u2014Google Earth Engine Api. Available online: https:\/\/developers.google.com\/earth-engine\/landsat."},{"key":"ref_53","unstructured":"(2018, July 20). SimpleCloudScore: An Example of Computing a Cloud-Free Composite. Available online: https:\/\/code.earthengine.google.com\/dc5611259d9ccab952526b3c2d05ce07."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Vleeshouwer, J., Car, N.J., and Hornbuckle, J. (2015). A Cotton Irrigator\u2019s Decision Support System and Benchmarking Tool Using National, Regional and Local Data, Springer International Publishing.","DOI":"10.1007\/978-3-319-15994-2_18"},{"key":"ref_55","first-page":"40","article-title":"A novel approach in monitoring land-cover change in the tropics: Oil palm cultivation in the Niger delta, Nigeria","volume":"147","author":"Okoro","year":"2016","journal-title":"DIE ERDE-J. Geog. Soc. Berl."},{"key":"ref_56","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_57","unstructured":"Stuhler, S., Leiterer, R., Joerg, P., Wulf, H., and Schaepman, M. (2018, September 21). Technical Report: Generating a Cloud-Free, Homogeneous Landsat-8 Mosaic of Switzerland Using Google Earth Engine. Available online: https:\/\/doi.org\/10.13140\/rg.2.1.2432.0880."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.rse.2017.04.003","article-title":"Obtaining rubber plantation age information from very dense landsat tm & etm + time series data and pixel-based image compositing","volume":"196","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_59","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_60","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.rse.2013.08.029","article-title":"Automated water extraction index: A new technique for surface water mapping using landsat imagery","volume":"140","author":"Feyisa","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1007\/BF00058655","article-title":"Bagging predictors","volume":"24","author":"Breiman","year":"1996","journal-title":"Mach. Learn."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_63","first-page":"18","article-title":"Classification and regression by randomforest","volume":"2","author":"Liaw","year":"2002","journal-title":"R News"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.isprsjprs.2010.08.003","article-title":"Predicting individual tree attributes from airborne laser point clouds based on the random forests technique","volume":"66","author":"Yu","year":"2011","journal-title":"Int. J. Photogramm. Remote Sens."},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Jia, M., Liu, M., Wang, Z., Mao, D., Ren, C., and Cui, H. (2016). Evaluating the effectiveness of conservation on mangroves: A remote sensing-based comparison for two adjacent protected areas in Shenzhen and Hong Kong, China. Remote Sens., 8.","DOI":"10.3390\/rs8080627"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"578","DOI":"10.1016\/j.isprsjprs.2008.04.002","article-title":"An object-based method for mapping and change analysis in mangrove ecosystems","volume":"63","author":"Conchedda","year":"2008","journal-title":"Int. J. Photogramm. Remote Sens."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"294","DOI":"10.1016\/j.patrec.2005.08.011","article-title":"Random forests for land cover classification","volume":"27","author":"Gislason","year":"2006","journal-title":"Pattern Recogn. Lett."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"2564","DOI":"10.1016\/j.rse.2011.05.013","article-title":"Object-oriented mapping of landslides using random forests","volume":"115","author":"Stumpf","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Deng, Y., Jiang, W.G., Tang, Z.H., Li, J.H., Lv, J.X., Chen, Z., and Jia, K. (2017). Spatio-temporal change of lake water extent in Wuhan urban agglomeration based on landsat images from 1987 to 2015. Remote Sens., 9.","DOI":"10.3390\/rs9030270"},{"key":"ref_70","unstructured":"Environmental Systems Research Institute (ESRI) (2008). ArcGIS 9.3, ESRI."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"1432","DOI":"10.1016\/j.scitotenv.2018.05.121","article-title":"Intensification of hydrological drought due to human activity in the middle reaches of the Yangtze river, China","volume":"637\u2013638","author":"Zhang","year":"2018","journal-title":"Sci. Total Environ."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"2644","DOI":"10.1002\/ldr.2939","article-title":"China\u2019s wetlands loss to urban expansion","volume":"29","author":"Mao","year":"2018","journal-title":"Land Degrad. Dev."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/10\/1635\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:25:33Z","timestamp":1760196333000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/10\/1635"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,10,14]]},"references-count":72,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2018,10]]}},"alternative-id":["rs10101635"],"URL":"https:\/\/doi.org\/10.3390\/rs10101635","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,10,14]]}}}