{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T02:50:33Z","timestamp":1775011833390,"version":"3.50.1"},"reference-count":86,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,3,16]],"date-time":"2022-03-16T00:00:00Z","timestamp":1647388800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Key R&amp;D Program of China","award":["Grant No. 2021YFB3900501"],"award-info":[{"award-number":["Grant No. 2021YFB3900501"]}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["Grant No. 41890854 and Grant No. 41901354"],"award-info":[{"award-number":["Grant No. 41890854 and Grant No. 41901354"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Rocky desertification is one of the most critical ecological and environmental problems in areas underlain by carbonate rocks globally. Land cover and land use in the region affects large-scale ecosystem processes on a global scale, and many Earth system models rely on accurate land cover information. Therefore, it is important to evaluate current global land cover products and to understand the differences between them, and the findings of these studies can provide guidance to different researchers when using or making land cover products. Whereas there are many studies on the assessment of coarser resolution land cover products, there are few studies on the assessment of higher resolution land cover products (10 m). In order to provide guidance for users of 10 m data, this paper uses the rock deserted southwest region of China as the experimental area. We analyzed the consistency and accuracy of the FROM-GLC, ESA WorldCover 10 and ESRI products using spatial pattern consistency, absolute accuracy assessment of three validation samples, and analyzed their intrinsic relationships among classification systems, classification methods, and validation samples. The results show that (1) the overall accuracy of the FROM-GLC product is the highest, ranging from 49.47 to 62.42%; followed by the overall accuracy of the ESA product, ranging from 45.13 to 64.50%; and the overall accuracy of the ESRI product is the lowest, between 39.03 and 61.94%. (2) The consistency between FROM-GLC and ESA is higher than the consistency between other products, with an area correlation coefficient of 0.94. Analysis of the spatial consistency of the three products shows that the proportion of perfectly consistent areas is low at 44.89%, mainly in areas with low surface heterogeneity and more homogeneous cover types. (3) Across the study area, the main land cover types such as forest and water bodies were the most consistent across the three product species, while the grassland, shrubland, and bareland were lower. All products showed high accuracy in homogeneous areas, with local accuracy varied in other areas, especially at high altitudes in the central and western regions. Therefore, land cover users cannot use these products directly when conducting relevant studies in rocky desertification areas, as their use may introduce serious errors.<\/jats:p>","DOI":"10.3390\/ijgi11030202","type":"journal-article","created":{"date-parts":[[2022,3,16]],"date-time":"2022-03-16T22:09:58Z","timestamp":1647468598000},"page":"202","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":46,"title":["Consistency Analysis and Accuracy Assessment of Three Global Ten-Meter Land Cover Products in Rocky Desertification Region\u2014A Case Study of Southwest China"],"prefix":"10.3390","volume":"11","author":[{"given":"Jun","family":"Wang","sequence":"first","affiliation":[{"name":"The Second Monitoring and Application Center, China Earthquake Administration, Xi\u2019an 710054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1643-8480","authenticated-orcid":false,"given":"Xiaomei","family":"Yang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6776-2910","authenticated-orcid":false,"given":"Zhihua","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongbin","family":"Cheng","sequence":"additional","affiliation":[{"name":"The Second Monitoring and Application Center, China Earthquake Administration, Xi\u2019an 710054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9598-4350","authenticated-orcid":false,"given":"Junmei","family":"Kang","sequence":"additional","affiliation":[{"name":"The Second Monitoring and Application Center, China Earthquake Administration, Xi\u2019an 710054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongtao","family":"Tang","sequence":"additional","affiliation":[{"name":"The Second Monitoring and Application Center, China Earthquake Administration, Xi\u2019an 710054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan","family":"Li","sequence":"additional","affiliation":[{"name":"The Second Monitoring and Application Center, China Earthquake Administration, Xi\u2019an 710054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zongpan","family":"Bian","sequence":"additional","affiliation":[{"name":"The Second Monitoring and Application Center, China Earthquake Administration, Xi\u2019an 710054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhuoli","family":"Bai","sequence":"additional","affiliation":[{"name":"The Second Monitoring and Application Center, China Earthquake Administration, Xi\u2019an 710054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Karra, K., Kontgis, C., Statman-Weil, Z., Mazzariello, J.C., Mathis, M., and Brumby, S.P. (2021, January 11\u201316). Global land use\/land cover with Sentinel 2 and deep learning. Proceedings of the 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Brussels, Belgium.","DOI":"10.1109\/IGARSS47720.2021.9553499"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"343","DOI":"10.3389\/fpls.2019.00343","article-title":"Ecosystem services related to carbon cycling\u2013modeling present and future impacts in boreal forests","volume":"10","author":"Holmberg","year":"2019","journal-title":"Front. Plant Sci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"512","DOI":"10.1111\/gcb.13443","article-title":"Land management: Data availability and process understanding for global change studies","volume":"23","author":"Erb","year":"2017","journal-title":"Glob. Chang. Biol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1111\/geb.12501","article-title":"Big data for forecasting the impacts of global change on plant communities","volume":"26","author":"Franklin","year":"2017","journal-title":"Glob. Ecol. Biogeogr."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"150241","DOI":"10.1098\/rsos.150241","article-title":"Big data integration shows Australian bush-fire frequency is increasing significantly","volume":"3","author":"Dutta","year":"2016","journal-title":"R. Soc. Open Sci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"3289","DOI":"10.1080\/014311697217099","article-title":"The IGBP-DIS global 1km land cover data set, DISCover: First results","volume":"18","author":"Loveland","year":"1997","journal-title":"Int. J. Remote Sens."},{"key":"ref_7","unstructured":"Hansen, M., DeFries, R., Townshend, J., and Sohlberg, R. (1998). Land Cover Classification Ferived from AVHRR, The Global Land Cover Facility."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1959","DOI":"10.1080\/01431160412331291297","article-title":"GLC2000: A new approach to global land cover mapping from Earth observation data","volume":"26","author":"Bartholome","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1016\/j.rse.2009.08.016","article-title":"MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets","volume":"114","author":"Friedl","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_10","unstructured":"Defourny, P., Schouten, L., Bartalev, S., Bontemps, S., Cacetta, P., De Wit, A., Di Bella, C., G\u00e9rard, B., Giri, C., and Gond, V. (2009, January 4\u20138). Accuracy assessment of a 300 m global land cover map: The GlobCover experience. Proceedings of the 33rd International Symposium on Remote Sensing of Environment, Sustaining the Millennium Development Goals, Stresa, Italy."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1016\/j.isprsjprs.2014.09.002","article-title":"Global land cover mapping at 30 m resolution: A POK-based operational approach","volume":"103","author":"Chen","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Buchhorn, M., Lesiv, M., Tsendbazar, N.-E., Herold, M., Bertels, L., and Smets, B. (2020). Copernicus global land cover layers\u2014Collection 2. Remote Sens., 12.","DOI":"10.3390\/rs12061044"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1729","DOI":"10.1080\/01431161.2017.1410298","article-title":"Spatial patterns of the United States National Land Cover Dataset (NLCD) land-cover change thematic accuracy (2001\u20132011)","volume":"39","author":"Wickham","year":"2018","journal-title":"Int. J. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"324","DOI":"10.1515\/geo-2020-0014","article-title":"Inconsistency distribution patterns of different remote sensing land-cover data from the perspective of ecological zoning","volume":"12","author":"Sui","year":"2020","journal-title":"Open Geosci."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Wang, J., Sui, L., Yang, X., Wang, Z., Ge, D., Kang, J., Yang, F., Liu, Y., and Liu, B. (2019). Economic globalization impacts on the ecological environment of inland developing countries: A case study of Laos from the perspective of the land use\/cover change. Sustainability, 11.","DOI":"10.3390\/su11143940"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Kang, J., Sui, L., Yang, X., Wang, Z., Huang, C., and Wang, J. (2019). Spatial pattern consistency among different remote-sensing land cover datasets: A case study in Northern Laos. ISPRS Int. J. Geo-Inf., 8.","DOI":"10.3390\/ijgi8050201"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"850","DOI":"10.1126\/science.1244693","article-title":"High-resolution global maps of 21st-century forest cover change","volume":"342","author":"Hansen","year":"2013","journal-title":"Science"},{"key":"ref_18","first-page":"207","article-title":"Comparison and relative quality assessment of the GLC2000, GLOBCOVER, MODIS and ECOCLIMAP land cover data sets at the African continental scale","volume":"13","author":"Roujean","year":"2011","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Wang, J., Sui, L., Yang, X., Wang, Z., Liu, Y., Kang, J., Lu, C., Yang, F., and Liu, B. (2019). Extracting Coastal Raft Aquaculture Data from Landsat 8 OLI Imagery. Sensors, 19.","DOI":"10.3390\/s19051221"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Kang, J., Sui, L., Yang, X., Liu, Y., Wang, Z., Wang, J., Yang, F., Liu, B., and Ma, Y. (2019). Sea Surface-Visible Aquaculture Spatial-Temporal Distribution Remote Sensing: A Case Study in Liaoning Province, China from 2000 to 2018. Sustainability, 11.","DOI":"10.3390\/su11247186"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1016\/j.scib.2019.03.002","article-title":"Stable classification with limited sample: Transferring a 30-m resolution sample set collected in 2015 to mapping 10-m resolution global land cover in 2017","volume":"64","author":"Chen","year":"2019","journal-title":"Sci. Bull."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/0034-4257(91)90048-B","article-title":"A review of assessing the accuracy of classifications of remotely sensed data","volume":"37","author":"Congalton","year":"1991","journal-title":"Remote Sens. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/j.isprsjprs.2018.04.002","article-title":"A review of accuracy assessment for object-based image analysis: From per-pixel to per-polygon approaches","volume":"141","author":"Ye","year":"2018","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/S0034-4257(01)00295-4","article-title":"Status of land cover classification accuracy assessment","volume":"80","author":"Foody","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1016\/j.rse.2012.09.005","article-title":"Spatial analysis of remote sensing image classification accuracy","volume":"127","author":"Comber","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"3539","DOI":"10.1016\/j.rse.2011.08.016","article-title":"Comparison and assessment of coarse resolution land cover maps for Northern Eurasia","volume":"115","author":"Pflugmacher","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Gao, Y., Liu, L., Zhang, X., Chen, X., Mi, J., and Xie, S. (2020). Consistency analysis and accuracy assessment of three global 30-m land-cover products over the European Union using the Lucas dataset. Remote Sens., 12.","DOI":"10.3390\/rs12213479"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Congalton, R.G., and Green, K. (2019). Assessing the Accuracy of Remotely Sensed Data: Principles and Practices, CRC Press.","DOI":"10.1201\/9780429052729"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1016\/j.apgeog.2017.03.019","article-title":"Comparison of input data with different spatial resolution in landscape pattern analysis\u2014A case study from northern latvia","volume":"83","author":"Rendenieks","year":"2017","journal-title":"Appl. Geogr."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2752","DOI":"10.1080\/01431161.2014.890305","article-title":"Comparing global land-cover products\u2013implications for geoscience applications: An investigation for the trans-boundary Mekong Basin","volume":"35","author":"Kuenzer","year":"2014","journal-title":"Int. J. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1080\/01431160902893451","article-title":"Evaluation of four remote sensing based land cover products over China","volume":"31","author":"Ran","year":"2010","journal-title":"Int. J. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"P\u00e9rez-Hoyos, A., Rembold, F., Kerdiles, H., and Gallego, J. (2017). Comparison of global land cover datasets for cropland monitoring. Remote Sens., 9.","DOI":"10.3390\/rs9111118"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Kang, J., Wang, Z., Sui, L., Yang, X., Ma, Y., and Wang, J. (2020). Consistency analysis of remote sensing land cover products in the tropical rainforest climate region: A case study of Indonesia. Remote Sens., 12.","DOI":"10.3390\/rs12091410"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Liang, L., Liu, Q., Liu, G., Li, H., and Huang, C. (2019). Accuracy evaluation and consistency analysis of four global land cover products in the Arctic region. Remote Sens., 11.","DOI":"10.3390\/rs11121396"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"2538","DOI":"10.1016\/j.rse.2007.11.013","article-title":"Some challenges in global land cover mapping: An assessment of agreement and accuracy in existing 1 km datasets","volume":"112","author":"Herold","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.earscirev.2014.01.005","article-title":"Rocky desertification in Southwest China: Impacts, causes, and restoration","volume":"132","author":"Jiang","year":"2014","journal-title":"Earth Sci. Rev."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1002\/ldr.1102","article-title":"Assessing spatial-temporal evolution processes of karst rocky desertification land: Indications for restoration strategies","volume":"24","author":"Bai","year":"2013","journal-title":"Land Degrad. Dev."},{"key":"ref_38","first-page":"84","article-title":"Rocky desertification in southwest karst region and its comprehensive management","volume":"44","author":"Jiang","year":"2008","journal-title":"China Geol. Surv. Bur. Karst Groundw. Desertif. Res. Pap. China"},{"key":"ref_39","first-page":"81","article-title":"Rock desertification in the subtropical karst of south China","volume":"108","author":"Daoxian","year":"1997","journal-title":"Z. Geomorphol."},{"key":"ref_40","unstructured":"Yassoglou, N. (2000). History of desertification in the European Mediterranean. Indicators for Assessing Desertification in the Mediterranean, Proceedings of the International Seminar, Porto Torres, Italy, 18\u201320 September 1998, Nucleo Ricerca Desertificazion, University of Sassari."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"4","DOI":"10.5038\/1827-806X.28.1.4","article-title":"Land use and human impact in the Dinaric karst","volume":"28","author":"Gams","year":"1999","journal-title":"Int. J. Speleol."},{"key":"ref_42","first-page":"20","article-title":"Soil erosion and rocky desertification controlled by karst environment in Guizhou Province","volume":"1","author":"Cao","year":"2009","journal-title":"Soil Water Conserv. China"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Rubio, J., Safriel, U., Daussa, R., Blum, W., and Pedrazzini, F. (2009). Water Scarcity, Land Degradation and Desertification in the Mediterranean Region: Environmental and Security Aspects, Springer Science & Business Media.","DOI":"10.1007\/978-90-481-2526-5"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1002\/ldr.592","article-title":"Karst rocky desertification in southwestern China: Geomorphology, landuse, impact and rehabilitation","volume":"15","author":"Wang","year":"2004","journal-title":"Land Degrad. Dev."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"727","DOI":"10.1007\/s10040-007-0259-9","article-title":"Impact of land use change on groundwater quality in a typical karst watershed of southwest China: A case study of the Xiaojiang watershed, Yunnan Province","volume":"16","author":"Jiang","year":"2008","journal-title":"Hydrogeol. J."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1016\/j.habitatint.2014.07.009","article-title":"Environmental effects of land-use\/cover change caused by urbanization and policies in Southwest China Karst are\u2014A case study of Guiyang","volume":"44","author":"Liu","year":"2014","journal-title":"Habitat Int."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1002\/ldr.591","article-title":"How types of carbonate rock assemblages constrain the distribution of karst rocky desertified land in Guizhou Province, PR China: Phenomena and mechanisms","volume":"15","author":"Wang","year":"2004","journal-title":"Land Degrad. Dev."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"528","DOI":"10.1038\/nature01675","article-title":"Impact of urbanization and land-use change on climate","volume":"423","author":"Kalnay","year":"2003","journal-title":"Nature"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"639","DOI":"10.1038\/s41586-018-0411-9","article-title":"Global land change from 1982 to 2016","volume":"560","author":"Song","year":"2018","journal-title":"Nature"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"554","DOI":"10.1038\/s41586-020-03138-y","article-title":"Global and regional drivers of land-use emissions in 1961\u20132017","volume":"589","author":"Hong","year":"2021","journal-title":"Nature"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"102926","DOI":"10.1016\/j.scs.2021.102926","article-title":"Surface urban heat island intensity in five major cities of Bangladesh: Patterns, drivers and trends","volume":"71","author":"Dewan","year":"2021","journal-title":"Sustain. Cities Soc."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"615","DOI":"10.1038\/s41467-022-28245-4","article-title":"Relative effects of land conversion and land-use intensity on terrestrial vertebrate diversity","volume":"13","author":"Semenchuk","year":"2022","journal-title":"Nat. Commun."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"2572","DOI":"10.1038\/s41598-020-59503-4","article-title":"Assessing the regional climate impact on terrestrial ecosystem over East Asia using coupled models with land use and land cover forcing during 1980\u20132010","volume":"10","author":"Cao","year":"2020","journal-title":"Sci. Rep."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"3733","DOI":"10.1002\/hyp.7792","article-title":"Precipitation and temperature trends for the Southwest China: 1960\u20132007","volume":"24","author":"Qin","year":"2010","journal-title":"Hydrol. Process."},{"key":"ref_55","first-page":"8067","article-title":"Ecosystem pattern variation from 2000 to 2010 in national nature reserves of China","volume":"37","author":"Zhang","year":"2017","journal-title":"Acta Ecol. Sin."},{"key":"ref_56","unstructured":"Di Gregorio, A. (2005). Land Cover Classification System: Classification Concepts and User Manual: LCCS, Food & Agriculture Organization."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"2816","DOI":"10.1016\/j.rse.2010.07.001","article-title":"A scalable approach to mapping annual land cover at 250 m using MODIS time series data: A case study in the Dry Chaco ecoregion of South America","volume":"114","author":"Clark","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_58","first-page":"403","article-title":"Evaluating the uncertainty of area estimates derived from fuuy land-cover classification","volume":"63","author":"Canters","year":"1997","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_59","first-page":"1449","article-title":"The determination of optimal threshold levels for change detection using various accuracy indexes","volume":"54","author":"Tung","year":"1988","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"170075","DOI":"10.1038\/sdata.2017.75","article-title":"A global dataset of crowdsourced land cover and land use reference data","volume":"4","author":"Fritz","year":"2017","journal-title":"Sci. Data"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"4795","DOI":"10.1080\/01431161.2014.930202","article-title":"Towards a common validation sample set for global land-cover mapping","volume":"35","author":"Zhao","year":"2014","journal-title":"Int. J. Remote Sens."},{"key":"ref_62","first-page":"742G749","article-title":"Accuracy Assessmentfor Regional Land Cover Remote Sensing Mapping Product Based on Spatial Sampling: A Case Study of Shanxi Province","volume":"17","author":"Wen","year":"2015","journal-title":"China"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1016\/j.envsoft.2011.11.015","article-title":"Geo-Wiki: An online platform for improving global land cover","volume":"31","author":"Fritz","year":"2012","journal-title":"Environ. Model. Softw."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"3907","DOI":"10.5194\/essd-13-3907-2021","article-title":"The 30 m annual land cover dataset and its dynamics in China from 1990 to 2019","volume":"13","author":"Yang","year":"2021","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1007\/s12665-012-2127-8","article-title":"Relationship between karst rocky desertification and its distance to roadways in a typical karst area of Southwest China","volume":"70","author":"Yang","year":"2013","journal-title":"Environ. Earth Sci."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"631","DOI":"10.1007\/s12665-013-2460-6","article-title":"Comparative studies of the distribution characteristics of rocky desertification and land use\/land cover classes in typical areas of Guizhou province, China","volume":"71","author":"Ying","year":"2014","journal-title":"Environ. Earth Sci."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"823","DOI":"10.1080\/01431160600746456","article-title":"A survey of image classification methods and techniques for improving classification performance","volume":"28","author":"Lu","year":"2007","journal-title":"Int. J. Remote Sens."},{"key":"ref_68","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_69","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1016\/j.isprsjprs.2017.01.016","article-title":"Accuracy assessment of seven global land cover datasets over China","volume":"125","author":"Yang","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"2317","DOI":"10.1007\/s11430-014-4919-z","article-title":"A multi-resolution global land cover dataset through multisource data aggregation","volume":"57","author":"Yu","year":"2014","journal-title":"Sci. China Earth Sci."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1109\/MGRS.2016.2540798","article-title":"Deep learning for remote sensing data: A technical tutorial on the state of the art","volume":"4","author":"Zhang","year":"2016","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"392","DOI":"10.1016\/j.rse.2010.09.010","article-title":"Hierarchical mapping of Northern Eurasian land cover using MODIS data","volume":"115","author":"Friedl","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/15481603.2019.1650447","article-title":"Land cover and land use classification performance of machine learning algorithms in a boreal landscape using Sentinel-2 data","volume":"57","author":"Abdi","year":"2020","journal-title":"GIScience Remote Sens."},{"key":"ref_74","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_75","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1017\/S0032247407006511","article-title":"Characterisation of Arctic treelines by LiDAR and multispectral imagery","volume":"43","author":"Rees","year":"2007","journal-title":"Polar Rec."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.rse.2011.11.023","article-title":"Subalpine zone delineation using LiDAR and Landsat imagery","volume":"119","author":"Wulder","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_77","first-page":"81","article-title":"Combining airborne laser scanning data and optical satellite data for classification of alpine vegetation","volume":"27","author":"Reese","year":"2014","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"084022","DOI":"10.1088\/1748-9326\/aad5d2","article-title":"Evidence of vegetation greening at alpine treeline ecotones: Three decades of Landsat spectral trends informed by lidar-derived vertical structure","volume":"13","author":"Bolton","year":"2018","journal-title":"Environ. Res. Lett."},{"key":"ref_79","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_80","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1016\/j.rse.2017.01.002","article-title":"Phenology-adaptive pixel-based compositing using optical earth observation imagery","volume":"190","author":"Frantz","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"8489","DOI":"10.3390\/rs70708489","article-title":"On the importance of training data sample selection in random forest image classification: A case study in peatland ecosystem mapping","volume":"7","author":"Millard","year":"2015","journal-title":"Remote Sens."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1016\/0034-4257(95)00142-5","article-title":"Global discrimination of land cover types from metrics derived from AVHRR pathfinder data","volume":"54","author":"DeFries","year":"1995","journal-title":"Remote Sens. Environ."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"465","DOI":"10.1016\/j.rse.2006.04.013","article-title":"Detecting leaf phenology of seasonally moist tropical forests in South America with multi-temporal MODIS images","volume":"103","author":"Xiao","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_84","first-page":"857","article-title":"Mapping seasonal flooding in forested wetlands using multi-temporal Radarsat SAR","volume":"67","author":"Townsend","year":"2001","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"5809","DOI":"10.1080\/01431160801958405","article-title":"Radar detection of wetland ecosystems: A review","volume":"29","author":"Henderson","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"4095","DOI":"10.1109\/JSTARS.2014.2302855","article-title":"Detecting China\u2019s urban expansion over the past three decades using nighttime light data","volume":"7","author":"Xiao","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/11\/3\/202\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:37:50Z","timestamp":1760135870000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/11\/3\/202"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,16]]},"references-count":86,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2022,3]]}},"alternative-id":["ijgi11030202"],"URL":"https:\/\/doi.org\/10.3390\/ijgi11030202","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,3,16]]}}}