Assessing wildfire susceptibility in Iran: Leveraging machine learning for geospatial analysis of climatic and anthropogenic factors

Assessing wildfire susceptibility in Iran: Leveraging machine learning for geospatial analysis of climatic and anthropogenic factors

This study investigates the multifaceted factors influencing wildfire risk in Iran, focusing on the interplay between climatic conditions and human activities. Utilizing advanced remote sensing, geospatial information system (GIS) processing techniques such as cloud computing, and machine learning a...

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Bibliographic Details
Main Authors: Ehsan Masoudian, Ali Mirzaei, Hossein Bagheri
Format: Article
Language:English
Published: Elsevier 2025-03-01
Series:Trees, Forests and People
Subjects:
Wildfire
Machine learning
Climate
Human activity
Remote sensing
Cloud computing
Online Access:http://www.sciencedirect.com/science/article/pii/S2666719325000020

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http://www.sciencedirect.com/science/article/pii/S2666719325000020

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