Application of remote sensing and machine learning algorithms for forest fire mapping in a Mediterranean area

•Five new ensemble models were developed for forest fire susceptibility modeling.•10 conditioning factors were considered in this study.•RF-FR ensemble model outperformed SVM-FR, MLP-FR, CART-FR and LR-FR models. Forest fire disaster is currently the subject of intense research worldwide. The develo...

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Bibliographic Details
Published in:	Ecological indicators Vol. 129; p. 107869
Main Authors:	Mohajane, Meriame, Costache, Romulus, Karimi, Firoozeh, Bao Pham, Quoc, Essahlaoui, Ali, Nguyen, Hoang, Laneve, Giovanni, Oudija, Fatiha
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.10.2021 Elsevier
Subjects:	Forest fire forest fires forests Hybrid machine learning algorithm hybrids inventories land use Mediterranean area Mediterranean region Morocco prediction rain regression analysis Remote sensing risk temperature wind speed Morocco Mediterranean region Mediterranean area Forest fire Remote sensing Hybrid machine learning algorithm
ISSN:	1470-160X, 1872-7034
Online Access:	Get full text
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