Modelling, mapping and monitoring of forest cover changes, using support vector machine, kernel logistic regression and naive bayes tree models with optical remote sensing data.

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第一作者： Aqil,Tariq

第一单位： State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, 430079, Hubei, China.

作者： Aqil,Tariq ^[1] ; Yan,Jiango ^[1] ; Qingting,Li ^[2] ; Jianwei,Gao ^[3] ; Linlin,Lu ^[4] ; Walid,Soufan ^[5] ; Khalid F,Almutairi ^[5] ; Muhammad,Habib-Ur-Rahman ^[6]

作者单位： State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, 430079, Hubei, China. ^[1] Airborne Remote Sensing Center, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China. ^[2] Institute of Spacecraft Application System Engineering, China Academy of Space Technology, Beijing, 100094, China. ^[3] Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China. ^[4] Plant Production Department, College of Food and Agriculture Sciences, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia. ^[5] Institute of Crop Science and Resource Conservation (INRES), Crop Science, University of Bonn, 53115, Bonn, Germany. ^[6]

关键词 Change detection Forest cover KLR, Kernel Logistic Regression Kernel logistic regression LULC, Landuse land cover Landsat NBT, Naive Bayes Tree Naive bayes tree SVM, Support Vector Machine Support vector machine

DOI 10.1016/j.heliyon.2023.e13212

PMID 36785833

发布时间 2023-02-15

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2023年9卷2期

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Modelling, mapping and monitoring of forest cover changes, using support vector machine, kernel logistic regression and naive bayes tree models with optical remote sensing data.

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Modelling, mapping and monitoring of forest cover changes, using support vector machine, kernel logistic regression and naive bayes tree models with optical remote sensing data.

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