{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T00:15:23Z","timestamp":1782951323119,"version":"3.54.5"},"reference-count":46,"publisher":"Public Library of Science (PLoS)","issue":"10","license":[{"start":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T00:00:00Z","timestamp":1730332800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:p>Preventing wind erosion and dust storms has always been a major concern in arid and semi-arid areas because of their negative effects on the environment. This study aims to utilize remote sensing and machine learning techniques to model, monitor, and predict the risk of wind erosion in Northeast Iran. Through an examination of relevant studies, a comprehensive review was conducted, leading to the identification of eight remote sensing indicators that exhibited the highest correlation with field data. These indicators were subsequently employed to model the risk of wind erosion in the study area. Various methods including Random Forest (RF), Support Vector Machine (SVM), Gradient Boosting Machine (GBM), and Generalized Linear Models (GLM) were employed to carry out the modeling process. The final method utilized a weighted average of the model, and the SDM statistical package was used to combine different approaches to decrease uncertainty when modeling and monitoring wind erosion in the area. The modeling results indicated that in 2008, the RF model performed the best (AUC = 0.92, TSS = 0.82, and Kappa = 0.96), while in 2023, the GBM model showed superior performance (AUC = 0.95, TSS = 0.79, and Kappa = 0.95). Therefore, the utilization of an ensemble model emerged as an effective approach to reduce uncertainty during the modeling process. By employing the ensemble model, the outcomes obtained accurately depicted an elevated intensity of wind erosion in the northeastern regions of the study area by 2023. Furthermore, considering the climatic scenarios and projected land use changes, it is anticipated that wind erosion intensity will experience a 23% increase in the central and southern parts of the study area by 2038. By taking into account the reliable results of the ensemble model, which offers reduced uncertainty, it becomes feasible to implement effective planning, optimal management, and appropriate measures to mitigate the progression of wind erosion.<\/jats:p>","DOI":"10.1371\/journal.pone.0308854","type":"journal-article","created":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T17:39:22Z","timestamp":1730396362000},"page":"e0308854","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":5,"title":["Enhancing wind erosion risk assessment through remote sensing techniques"],"prefix":"10.1371","volume":"19","author":[{"given":"Abdolhossein","family":"Boali","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-8553-8575","authenticated-orcid":true,"given":"Narges","family":"Kariminejad","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7177-8117","authenticated-orcid":true,"given":"Mohsen","family":"Hosseinalizadeh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2024,10,31]]},"reference":[{"key":"pone.0308854.ref001","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1016\/j.geodrs.2017.03.003","article-title":"Digital soil mapping of sand content in arid western India through geostatistical approaches.","volume":"9","author":"P Santra","year":"2017","journal-title":"Geoderma Reg [Internet]."},{"key":"pone.0308854.ref002","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.aeolia.2012.10.001","article-title":"A history of Wind Erosion Prediction Models in the United States Department of Agriculture: The Wind Erosion Prediction System (WEPS).","volume":"10","author":"LE Wagner","year":"2013","journal-title":"Aeolian Res [Internet]."},{"issue":"9","key":"pone.0308854.ref003","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3390\/rs15092404","article-title":"Quantitative Evaluation of Soil Water and Wind Erosion Rates in Pakistan","volume":"15","author":"X Yang","year":"2023","journal-title":"Remote Sens"},{"key":"pone.0308854.ref004","doi-asserted-by":"crossref","first-page":"164605","DOI":"10.1016\/j.scitotenv.2023.164605","article-title":"Synergistic soil, land use, and climate influences on wind erosion on the Colorado Plateau: Implications for management","volume":"893","author":"TW Nauman","year":"2023","journal-title":"Sci Total Environ [Internet]."},{"issue":"2","key":"pone.0308854.ref005","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1080\/1747423X.2011.560292","article-title":"Degradation of soils as a result of long-term human-induced transformation of the environment in Iran: An overview","volume":"7","author":"I Emadodin","year":"2012","journal-title":"J Land Use Sci"},{"key":"pone.0308854.ref006","first-page":"815","article-title":"Assessment of environmentally sensitive areas to desertification in the Blue Nile Basin driven by the MEDALUS-GEE framework","author":"A Elnashar","year":"2022","journal-title":"Sci Total Environ"},{"key":"pone.0308854.ref007","doi-asserted-by":"crossref","first-page":"254","DOI":"10.1016\/j.jhydrol.2017.12.039","article-title":"Effect of Dam operation on monthly and annual trends of flow discharge in the Qom Rood Watershed","volume":"557","author":"H Yaghmaei","year":"2018","journal-title":"Iran. J Hydrol [Internet]."},{"issue":"1","key":"pone.0308854.ref008","first-page":"68","article-title":"Measurement and prediction of soil erosion in dry field using portable wind erosion tunnel. Biosyst Eng","volume":"118","author":"SW Hong","year":"2014","journal-title":"Internet]"},{"key":"pone.0308854.ref009","doi-asserted-by":"crossref","first-page":"114171","DOI":"10.1016\/j.jenvman.2021.114171","article-title":"Predicting wind erosion rate using portable wind tunnel combined with machine learning algorithms in calcareous soils, southern Iran","volume":"304","author":"M Mina","year":"2022","journal-title":"J Environ Manage [Internet]."},{"key":"pone.0308854.ref010","first-page":"106011","article-title":"Monitoring desertification processes using ecological indicators and providing management programs in arid regions of Iran. Ecol Indic","volume":"111","author":"M Akbari","year":"2020","journal-title":"Internet]"},{"key":"pone.0308854.ref011","first-page":"129","article-title":"Monitoring desertification in Mongolia based on Landsat images and Google Earth Engine from 1990 to 2020","author":"X Meng","year":"2021","journal-title":"Ecol Indic"},{"key":"pone.0308854.ref012","first-page":"405","article-title":"Assessment of desertification using modified MEDALUS model in the north Nile Delta, Egypt","author":"AS Abuzaid","year":"2022","journal-title":"Geoderma"},{"key":"pone.0308854.ref013","doi-asserted-by":"crossref","first-page":"111250","DOI":"10.1016\/j.ecolind.2023.111250","article-title":"Flood susceptibility mapping to improve models of species distributions.","volume":"157","author":"E Ebrahimi","year":"2023","journal-title":"Ecol Indic [Internet]"},{"issue":"1","key":"pone.0308854.ref014","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1016\/j.apr.2020.08.029","article-title":"Evaluation of machine learning models for predicting the temporal variations of dust storm index in arid regions of Iran.","volume":"12","author":"Z Ebrahimi-Khusfi","year":"2021","journal-title":"Atmos Pollut Res [Internet]."},{"issue":"4","key":"pone.0308854.ref015","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1080\/21580103.2019.1667880","article-title":"Assessing environmentally sensitive land to desertification using MEDALUS method in Mongolia.","volume":"15","author":"EJ Lee","year":"2019","journal-title":"Forest Sci Technol"},{"issue":"6","key":"pone.0308854.ref016","article-title":"Air pollution prediction using long short-term memory (LSTM) and deep autoencoder (DAE) models","volume":"12","author":"T Xayasouk","year":"2020","journal-title":"Sustain"},{"key":"pone.0308854.ref017","first-page":"251","article-title":"Mapping horizontal and vertical urban densification in Denmark with Landsat time-series from 1985 to 2018: A semantic segmentation solution","author":"THK Chen","year":"2020","journal-title":"Remote Sens Environ"},{"key":"pone.0308854.ref018","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":"M Belgiu","year":"2016","journal-title":"ISPRS Journal of Photogrammetry and Remote Sensing"},{"issue":"1","key":"pone.0308854.ref019","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.tree.2006.09.010","article-title":"Ensemble forecasting of species distributions","volume":"22","author":"MB Ara\u00fajo","year":"2007","journal-title":"Trends Ecol Evol"},{"key":"pone.0308854.ref020","first-page":"82","article-title":"Cloud detection algorithm using SVM with SWIR2 and tasseled cap applied to Landsat 8","author":"PP Joshi","year":"2019","journal-title":"Int J Appl Earth Obs Geoinf"},{"key":"pone.0308854.ref021","article-title":"Fishing trip cost modeling using generalized linear model and machine learning methods\u2013A case study with longline fisheries in the Pacific and an application in Regulatory Impact Analysis","volume":"16","author":"HL Chan","year":"2021","journal-title":"PLoS One"},{"issue":"6","key":"pone.0308854.ref022","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":"JCW Chan","year":"2008","journal-title":"Remote Sens Environ"},{"issue":"4","key":"pone.0308854.ref023","doi-asserted-by":"crossref","first-page":"368","DOI":"10.1111\/ecog.01881","article-title":"Sdm: A reproducible and extensible R platform for species distribution modelling","volume":"39","author":"B Naimi","year":"2016","journal-title":"Ecography 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Sens"},{"key":"pone.0308854.ref027","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1016\/j.catena.2015.10.010","article-title":"Application of GIS-based data driven random forest and maximum entropy models for groundwater potential mapping: A case study at Mehran Region, Iran","volume":"137","author":"O Rahmati","year":"2016","journal-title":"Catena"},{"issue":"3\u20134","key":"pone.0308854.ref028","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1016\/j.enggeo.2005.02.002","article-title":"Landslide susceptibility mapping: A comparison of logistic regression and neural networks methods in a medium scale study, Hendek region (Turkey).","volume":"79","author":"E Yesilnacar","year":"2005","journal-title":"Eng Geol"},{"issue":"1","key":"pone.0308854.ref029","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1007\/s11069-012-0347-6","article-title":"Landslide susceptibility mapping using certainty factor, index of entropy and logistic regression models in GIS and their comparison at Mugling-Narayanghat road section in Nepal Himalaya.","volume":"65","author":"KC Devkota","year":"2013","journal-title":"Nat Hazards"},{"issue":"15","key":"pone.0308854.ref030","doi-asserted-by":"crossref","first-page":"1751","DOI":"10.1080\/00036846.2014.884706","article-title":"The impact of natural disasters on household income, expenditure, poverty and inequality: Evidence from Vietnam.","volume":"46","author":"AT Bui","year":"2014","journal-title":"Appl Econ"},{"issue":"8","key":"pone.0308854.ref031","doi-asserted-by":"crossref","first-page":"2880","DOI":"10.1080\/01431161.2018.1533661","article-title":"Analysis of remote sensing time-series data to foster ecosystem sustainability: use of temporal information entropy","volume":"40","author":"C Wang","year":"2019","journal-title":"Int J Remote Sens"},{"issue":"12","key":"pone.0308854.ref032","doi-asserted-by":"crossref","first-page":"1573","DOI":"10.1002\/ldr.3533","article-title":"Dynamic monitoring of desertification in Naiman Banner based on feature space models with typical surface parameters derived from LANDSAT images","volume":"31","author":"B Guo","year":"2020","journal-title":"L Degrad Dev"},{"issue":"8","key":"pone.0308854.ref033","doi-asserted-by":"crossref","DOI":"10.3390\/rs15082128","article-title":"A Random Forest-Based CA-Markov Model to Examine the Dynamics of Land Use\/Cover Change Aided with Remote Sensing and GIS.","volume":"15","author":"Z Zhang","year":"2023","journal-title":"Remote Sens"},{"key":"pone.0308854.ref034","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1016\/j.jhydrol.2012.02.040","article-title":"Comparison and evaluation of multiple GCMs, statistical downscaling and hydrological models in the study of climate change impacts on runoff","volume":"434\u2013435","author":"H Chen","year":"2012","journal-title":"J Hydrol [Internet]."},{"issue":"12","key":"pone.0308854.ref035","doi-asserted-by":"crossref","first-page":"2411","DOI":"10.1080\/01431160600554363","article-title":"Development of topsoil grain size index for monitoring desertification in arid land using remote sensing","volume":"27","author":"J Xiao","year":"2006","journal-title":"Int J Remote Sens"},{"issue":"3","key":"pone.0308854.ref036","first-page":"250","article-title":"Soil salinity modeling and mapping using remote sensing and GIS: The case of Wonji sugar cane irrigation farm, Ethiopia.","volume":"17","author":"E Asfaw","year":"2018","journal-title":"J Saudi Soc Agric Sci"},{"issue":"15","key":"pone.0308854.ref037","doi-asserted-by":"crossref","first-page":"2022","DOI":"10.1080\/09205071.2019.1661287","article-title":"Propagation measurements for a LoRa network in an urban environment.","volume":"33","author":"M Paredes","year":"2019","journal-title":"J Electromagn Waves Appl [Internet]"},{"issue":"1","key":"pone.0308854.ref038","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.asr.2017.11.038","article-title":"Desertification in the south Junggar Basin, 2000\u20132009: Part I. Spatial analysis and indicator retrieval.","volume":"62","author":"M Jiang","year":"2018","journal-title":"Adv Sp Res [Internet]."},{"key":"pone.0308854.ref039","doi-asserted-by":"crossref","first-page":"104682","DOI":"10.1016\/j.landusepol.2020.104682","article-title":"Land-use and land-cover change in Lake Ziway watershed of the Ethiopian Central Rift Valley Region and its environmental impacts.","volume":"96","author":"H Desta","year":"2020","journal-title":"Land use policy [Internet]."},{"issue":"3","key":"pone.0308854.ref040","first-page":"213","article-title":"Assessing Current Status of Desertification in the Sofikam\u2013Mangali Plain, Northwest of the Golestan Province","volume":"18","author":"F Honardoust","year":"2008","journal-title":"Water Soil Conserv"},{"issue":"1","key":"pone.0308854.ref041","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random Forests.","volume":"45","author":"L. Breiman","year":"2001","journal-title":"Mach Learn"},{"issue":"8","key":"pone.0308854.ref042","doi-asserted-by":"crossref","DOI":"10.3390\/land12081503","article-title":"Enhancing Wind Erosion Assessment of Metal Structures on Dry and Degraded Lands through Machine Learning","volume":"12","author":"M Terrados-Cristos","year":"2023","journal-title":"Land"},{"issue":"2","key":"pone.0308854.ref043","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1007\/s11749-016-0481-7","article-title":"A random forest guided tour","volume":"25","author":"G Biau","year":"2016","journal-title":"Test"},{"key":"pone.0308854.ref044","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1098\/rstb.2011.0178","article-title":"Incorporating uncertainty in predictive species distribution modelling","volume":"367","author":"CM Beale","year":"2012","journal-title":"Philosophical Transactions of the Royal Society B: Biological Sciences"},{"key":"pone.0308854.ref045","first-page":"180","article-title":"Surface soil hydraulic properties in four soil series under different land uses and their temporal changes","volume":"73","author":"X Zhou","year":"2008"},{"key":"pone.0308854.ref046","doi-asserted-by":"crossref","first-page":"104086","DOI":"10.1016\/j.jaridenv.2019.104086","article-title":"Assessing early warning for desertification hazard based on E-SMART indicators in arid regions of northeastern Iran","volume":"174","author":"M Akbari","year":"2020","journal-title":"J Arid Environ [Internet]."}],"container-title":["PLOS ONE"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0308854","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T17:39:39Z","timestamp":1730396379000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0308854"}},"subtitle":[],"editor":[{"given":"Bijay","family":"Halder","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2024,10,31]]},"references-count":46,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2024,10,31]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pone.0308854","relation":{},"ISSN":["1932-6203"],"issn-type":[{"value":"1932-6203","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,10,31]]}}}