{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T14:21:45Z","timestamp":1775744505343,"version":"3.50.1"},"reference-count":40,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2024,8,22]],"date-time":"2024-08-22T00:00:00Z","timestamp":1724284800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2020YFA0608404"],"award-info":[{"award-number":["2020YFA0608404"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["41101006"],"award-info":[{"award-number":["41101006"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["20210302124032"],"award-info":[{"award-number":["20210302124032"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Nature Science Foundation of China","doi-asserted-by":"publisher","award":["2020YFA0608404"],"award-info":[{"award-number":["2020YFA0608404"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Nature Science Foundation of China","doi-asserted-by":"publisher","award":["41101006"],"award-info":[{"award-number":["41101006"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Nature Science Foundation of China","doi-asserted-by":"publisher","award":["20210302124032"],"award-info":[{"award-number":["20210302124032"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Foundation of Shanxi Province","award":["2020YFA0608404"],"award-info":[{"award-number":["2020YFA0608404"]}]},{"name":"Natural Science Foundation of Shanxi Province","award":["41101006"],"award-info":[{"award-number":["41101006"]}]},{"name":"Natural Science Foundation of Shanxi Province","award":["20210302124032"],"award-info":[{"award-number":["20210302124032"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Machine learning methods have improved in recent years and provide increasingly powerful tools for understanding landscape evolution. In this study, we used the random forest method based on Google Earth Engine to evaluate the desertification dynamics in northern China from 1995 to 2020. We selected Landsat series image bands, remote sensing inversion data, climate baseline data, land use data, and soil type data as variables for majority voting in the random forest method. The method\u2019s average classification accuracy was 91.6% \u00b1 5.8 [mean \u00b1 SD], and the average kappa coefficient was 0.68 \u00b1 0.09, suggesting good classification results. The random forest classifier results were consistent with the results of visual interpretation for the spatial distribution of different levels of desertification. From 1995 to 2000, the area of aeolian desertification increased at an average rate of 9977 km2 yr\u22121, and from 2000 to 2005, from 2005 to 2010, from 2010 to 2015, and from 2015 to 2020, the aeolian desertification decreased at an average rate of 2535, 3462, 1487, and 4537 km2 yr\u22121, respectively.<\/jats:p>","DOI":"10.3390\/rs16163100","type":"journal-article","created":{"date-parts":[[2024,8,22]],"date-time":"2024-08-22T11:14:41Z","timestamp":1724325281000},"page":"3100","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Aeolian Desertification Dynamics from 1995 to 2020 in Northern China: Classification Using a Random Forest Machine Learning Algorithm Based on Google Earth Engine"],"prefix":"10.3390","volume":"16","author":[{"given":"Caixia","family":"Zhang","sequence":"first","affiliation":[{"name":"Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, No. 320, West Donggang Road, Lanzhou 730000, China"}]},{"given":"Ningjing","family":"Tan","sequence":"additional","affiliation":[{"name":"Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, No. 320, West Donggang Road, Lanzhou 730000, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Jinchang","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of Loess Plateau, Shanxi University, Taiyuan 030006, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,8,22]]},"reference":[{"key":"ref_1","unstructured":"UNCCD (1994). United Nations: Convention to Combat Desertification in Those Countries Experiencing Serious Drought and\/or Desertification, Particularly in Africa. International Legal Materials, Cambridge University Press."},{"key":"ref_2","first-page":"2","article-title":"The concept of desertification and the differentiation of its development","volume":"4","author":"Zhu","year":"1984","journal-title":"J. Desert Res."},{"key":"ref_3","first-page":"145","article-title":"Concept, cause and control of desertification in China","volume":"18","author":"Zhu","year":"1998","journal-title":"Quat. Sci."},{"key":"ref_4","first-page":"209","article-title":"Study on sandy desertification in China\u20141. Definition of sandy desertification and its connotation","volume":"23","author":"Wang","year":"2003","journal-title":"J. Desert Res."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"106674","DOI":"10.1016\/j.catena.2022.106674","article-title":"The dominant driving factors of rocky desertification and their variations in typical mountainous karst areas of southwest China in the context of global change","volume":"220","author":"Guo","year":"2023","journal-title":"Catena"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"106728","DOI":"10.1016\/j.catena.2022.106728","article-title":"Environmental sensitivity assessment of land desertification in the Hexi Corridor, China","volume":"220","author":"Shao","year":"2023","journal-title":"Catena"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"152925","DOI":"10.1016\/j.scitotenv.2022.152925","article-title":"Assessment of environmentally sensitive areas to desertification in the Blue Nile Basin driven by the MEDALUS-GEE framework","volume":"815","author":"Elnashar","year":"2022","journal-title":"Sci. Total Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"107386","DOI":"10.1016\/j.ecolind.2021.107386","article-title":"Path analysis model to identify and analyse the causes of aeolian desertification in Mu Us Sandy Land, China","volume":"124","author":"Feng","year":"2021","journal-title":"Ecol. Indic."},{"key":"ref_9","first-page":"1351","article-title":"Remote sensing analysis on aeolian desertification trends in northern China during 1975\u20132010","volume":"31","author":"Wang","year":"2011","journal-title":"J. Desert Res."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"793","DOI":"10.1007\/s12665-009-0075-8","article-title":"Driving forces behind land use and cover change in the Qinghai-Tibetan Plateau: A case study of the source region of the Yellow River, Qinghai Province, China","volume":"59","author":"Song","year":"2009","journal-title":"Environ. Earth Sci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/j.geomorph.2009.06.003","article-title":"Assessment of aeolian desertification trends from 1975\u2019s to 2005\u2019s in the watershed of the Longyangxia Reservoir in the upper reaches of China\u2019s Yellow River","volume":"112","author":"Yan","year":"2009","journal-title":"Geomorphology"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"3123","DOI":"10.1007\/s12665-015-4350-6","article-title":"Monitoring and analysis of aeolian desertification dynamics from 1975 to 2010 in the Heihe River Basin, northwestern China","volume":"74","author":"Song","year":"2015","journal-title":"Environ. Earth Sci."},{"key":"ref_13","first-page":"9","article-title":"Determination of land degradation causes in Tongyu County, Northeast China via land cover change detection","volume":"12","author":"Gao","year":"2010","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.catena.2006.10.002","article-title":"Processes and mechanisms of desertification in northern China during the last 30 years, with a special reference to the Hunshandake Sandy Land, eastern Inner Mongolia","volume":"71","author":"Yang","year":"2007","journal-title":"Catena"},{"key":"ref_15","first-page":"100745","article-title":"Monitoring long-term land use, land cover change, and desertification in the Ternata oasis, Middle Draa Valley, Morocco","volume":"26","author":"Moumane","year":"2022","journal-title":"Remote Sens. Appl. Soc. Environ."},{"key":"ref_16","first-page":"6","article-title":"Nonsupervising digital classification and GIS in the dynamic monitoring of soil desertification application","volume":"20","author":"Mao","year":"2005","journal-title":"J. Northwest For. Univ."},{"key":"ref_17","first-page":"12","article-title":"Primary study on the multi-layer remote sensing information extraction of desertification land types by using decision tree technology","volume":"20","author":"Wang","year":"2000","journal-title":"J. Desert Res."},{"key":"ref_18","first-page":"1","article-title":"Qualified evaluating on the remote sensing of desertification\u2014A case study of Erdos region","volume":"43","author":"Ma","year":"2007","journal-title":"J. Lanzhou Univ. (Nat. Sci.)"},{"key":"ref_19","first-page":"58","article-title":"An artificial neural network method for the information of desertification extraction","volume":"33","author":"Qiao","year":"2004","journal-title":"Acta Geod. Cartogr. Sin."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"107908","DOI":"10.1016\/j.ecolind.2021.107908","article-title":"Monitoring desertification in Mongolia based on Landsat images and Google Earth Engine from 1990 to 2020","volume":"129","author":"Meng","year":"2021","journal-title":"Ecol. Indic."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"115400","DOI":"10.1016\/j.geoderma.2021.115400","article-title":"Assessment of desertification using modified MEDALUS model in the north Nile Delta, Egypt","volume":"405","author":"Abuzaid","year":"2022","journal-title":"Geoderma"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2374","DOI":"10.1016\/j.scitotenv.2018.09.374","article-title":"Dynamic monitoring of aeolian desertification based on multiple indicators in Horqin Sandy Land, China","volume":"650","author":"Duan","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_23","first-page":"101750","article-title":"Spatiotemporal evolution of desertification based on integrated remote sensing indices in Duolun County, Inner Mongolia","volume":"70","author":"Bai","year":"2022","journal-title":"Geoecol. Inform."},{"key":"ref_24","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_25","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_26","doi-asserted-by":"crossref","first-page":"108288","DOI":"10.1016\/j.ecolind.2021.108288","article-title":"Impact of climate change on plant species richness across drylands in China: From past to present and into the future","volume":"132","author":"Sun","year":"2021","journal-title":"Ecol. Indic."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2999","DOI":"10.1016\/j.rse.2008.02.011","article-title":"Evaluation of Random Forest and Adaboost tree-based ensemble classification and spectral band selection for ecotope mapping using airborne hyperspectral imagery","volume":"112","author":"Chan","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1111\/2041-210X.13729","article-title":"A multimodel random forest ensemble method for an improved assessment of Chinese terrestrial vegetation carbon density","volume":"14","author":"Wang","year":"2021","journal-title":"Methods Ecol. Evol."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Tian, Y., Li, Y., Wang, D., Tao, J., Yang, Y., Lin, J., Zhang, Q., and Wu, L. (2022). Machine learning algorithm for estimating karst rocky desertification in a peak-cluster depression basin in southwest Guangxi, China. Sci. Rep., 12.","DOI":"10.1038\/s41598-022-21684-5"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Ayala-Izurieta, J.E., M\u00e1rquez, C.O., Garc\u00eda, V.J., Recalde-Moreno, C.G., Rodr\u00edguez-Llerena, M.V., and Dami\u00e1n-Carri\u00f3n, D.A. (2017). Land cover classification in an ecuadorian mountain geosystem using a random forest classifier, spectral vegetation indices, and ancillary geographic data. Geosciences, 7.","DOI":"10.3390\/geosciences7020034"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Kelsey, E.N., Gunn, G.E., Shiklomanov, N.I., Engstrom, R.N., and Streletskiy, D.A. (2018). Land cover change in the lower Yenisei River using dense stacking of landsat imagery in Google Earth Engine. Remote Sens., 10.","DOI":"10.3390\/rs10081226"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1007\/s11769-020-1119-y","article-title":"A synthesizing land-cover classification method based on Google Earth Engine: A case study in Nzhelele and Levhuvu Catchments, South Africa","volume":"30","author":"Zeng","year":"2020","journal-title":"Chin. Geogr. Sci."},{"key":"ref_33","first-page":"881","article-title":"Analysis of mangrove annual changes in Guangdong Province during 1986\u20132018 based on Google Earth Engine","volume":"40","author":"Wang","year":"2020","journal-title":"Trop. Geogr."},{"key":"ref_34","first-page":"203","article-title":"Spatial-temporal changes of sandy desertified land during last 5 decades in Northern China","volume":"59","author":"Wang","year":"2004","journal-title":"Acta Geogr. Sin."},{"key":"ref_35","unstructured":"World Meteorological Organization (2017). WMO Guidelines on the Calculation of Climate Normals, World Meteorological Organization."},{"key":"ref_36","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_37","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.rse.2017.05.024","article-title":"Using the 500m MODIS land cover product to derive a consistent continental scale 30m Landsat land cover classification","volume":"197","author":"Zhang","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1016\/j.geosus.2022.06.001","article-title":"Desertification in the Mu Us Sandy Land in China: Response to climate change and human activity from 2000 to 2020","volume":"3","author":"Wang","year":"2023","journal-title":"Geogr. Sustain."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"107925","DOI":"10.1016\/j.agrformet.2020.107925","article-title":"Spatio-temporal assessment of beech growth in relation to climate extremes in Slovenia-An integrated approach using remote sensing and tree-ring data","volume":"287","author":"Decuyper","year":"2020","journal-title":"Agric. For. Meteorol."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"5103","DOI":"10.1175\/JCLI-D-21-0325.1","article-title":"Vegetation greening, extended growing seasons, and temperature feedbacks in warming temperate grasslands of China","volume":"35","author":"Shen","year":"2022","journal-title":"J. Clim."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/16\/3100\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T15:41:28Z","timestamp":1760110888000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/16\/3100"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,22]]},"references-count":40,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2024,8]]}},"alternative-id":["rs16163100"],"URL":"https:\/\/doi.org\/10.3390\/rs16163100","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8,22]]}}}