Wildfire response of forest species from multispectral LiDAR data. A deep learning approach with synthetic data-Reference-Cited by-同舟云学术

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Wildfire response of forest species from multispectral LiDAR data. A deep learning approach with synthetic data

Published:2024-07 Issue: Volume:81 Page:102612
ISSN:1574-9541
Container-title:Ecological Informatics
language:en
Short-container-title:Ecological Informatics

Author:

Comesaña-Cebral Lino,Martínez-Sánchez Joaquín,Suárez-Fernández Gabriel,Arias Pedro

Funder

Agencia Estatal de Investigacion

Gobierno de Espana Ministerio de Educacion Cultura y Deporte

Publisher

Elsevier BV

Reference68 articles.

1. Forest fuel type classification: review of remote sensing techniques, constraints and future trends;Abdollahi;J. Environ. Manag.,2023

2. Fusion of WorldView-2 and LiDAR data to map fuel types in the Canary Islands;Alonso-Benito;Remote Sens.,2016

3. 3D semantic parsing of large-scale indoor spaces;Armeni,2016

4. Fire models and methods to map fuel types: the role of remote sensing;Arroyo;For. Ecol. Manag.,2008

5. The role of plants in human health;Azizi;Br. J. Biol. Stud.,2023

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2. Meta Heuristic Image Optimisation in LiDAR Sensor Based on Cloud IoT Network and Deep Learning Algorithms;Remote Sensing in Earth Systems Sciences;2025-03-25

3. SAMFA: A Flame Segmentation Algorithm for Infrared and Visible Aerial Images in the Same Scene;Drones;2025-03-18

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