BIPE: A Bi-Layer Predictive Ensemble Framework for Forest Fire Susceptibility Mapping in Germany
Forest fires diminish forests’ ecological services, including carbon sequestration, water retention, air cooling, and recreation, while polluting the environment and endangering habitats. Despite considerable economic advancements, firefighting strategies remain less than optimal. This paper introdu...
Saved in:
Main Authors: | Ling Hu, Volker Hochschild, Harald Neidhardt, Michael Schultz, Pegah Khosravani, Hadi Shokati |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2024-12-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-4292/17/1/7 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Enhancing forest fire susceptibility mapping in Xichang City, China using DBSCAN-based non-fire point selection integrated with deep neural network
by: Lingxiao Xie, et al.
Published: (2025-12-01) -
Performance Assessment of Individual and Ensemble Learning Models for Gully Erosion Susceptibility Mapping in a Mountainous and Semi-Arid Region
by: Meryem El Bouzekraoui, et al.
Published: (2024-12-01) -
Determination of Fire Damage and Fire Susceptible Areas Using Remote Sensing and Geographic Information Systems: A Case Study Aydıncık (Mersin) District, Türkiye
by: Fatih Ocak, et al.
Published: (2024-07-01) -
Evaluating the Impact of Recursive Feature Elimination on Machine Learning Models for Predicting Forest Fire-Prone Zones
by: Ali Rezaei Barzani, et al.
Published: (2024-11-01) -
Conceptual Framework of an Effective Decision Support System in Forest Fire Management
by: Kadir Alperen Coşkuner, et al.
Published: (2020-07-01)