[PDF][PDF] Role of machine learning algorithms in forest fire management: A literature review
Forest fire disasters are recently getting lots of attention due to climate change globally.
Globally, climate changes are rapidly changing the fire patterns on Earth. Effective fire …
Globally, climate changes are rapidly changing the fire patterns on Earth. Effective fire …
Forest fire susceptibility prediction based on machine learning models with resampling algorithms on remote sensing data
This study predicts forest fire susceptibility in Chaloos Rood watershed in Iran using three
machine learning (ML) models—multivariate adaptive regression splines (MARS), support …
machine learning (ML) models—multivariate adaptive regression splines (MARS), support …
Evaluation of Landsat image compositing algorithms
We proposed a new image compositing algorithm (MAX-RNB) based on the maximum ratio
of Near Infrared (NIR) to Blue band (RNB), and evaluated it together with nine other …
of Near Infrared (NIR) to Blue band (RNB), and evaluated it together with nine other …
Near-real-time monitoring of land disturbance with harmonized Landsats 7–8 and Sentinel-2 data
Land disturbance can increase carbon emissions, cause detrimental environmental impacts,
and threaten human life and property. Monitoring land disturbance in near-real-time is …
and threaten human life and property. Monitoring land disturbance in near-real-time is …
[HTML][HTML] Uni-temporal multispectral imagery for burned area map** with deep learning
Accurate burned area information is needed to assess the impacts of wildfires on people,
communities, and natural ecosystems. Various burned area detection methods have been …
communities, and natural ecosystems. Various burned area detection methods have been …
Spatio-temporal patterns of wildfires in Siberia during 2001–2020
O Tomshin, V Solovyev - Geocarto International, 2022 - Taylor & Francis
Siberia is one of the most fire-prone regions of northern Eurasia and also the region with the
greatest warming in the Eastern Hemisphere over the last decades. In this study …
greatest warming in the Eastern Hemisphere over the last decades. In this study …
Improved fire severity map** in the North American boreal forest using a hybrid composite method
LM Holsinger, SA Parks, LB Saperstein… - Remote Sensing in …, 2022 - Wiley Online Library
Fire severity is a key driver sha** the ecological structure and function of North American
boreal ecosystems, a biome dominated by large, high‐intensity wildfires. Satellite‐derived …
boreal ecosystems, a biome dominated by large, high‐intensity wildfires. Satellite‐derived …
Spatial analysis and machine learning prediction of forest fire susceptibility: a comprehensive approach for effective management and mitigation
M Mishra, R Guria, B Baraj, AP Nanda… - Science of The Total …, 2024 - Elsevier
Forest fires (FF) in tropical seasonal forests impact ecosystem. Addressing FF in tropical
ecosystems has become a priority to mitigate impacts on biodiversity loss and climate …
ecosystems has become a priority to mitigate impacts on biodiversity loss and climate …
Satellite-based ensemble intelligent approach for predicting forest fire: a case of the Hyrcanian forest in Iran
A machine learning-based approach is applied to simulate and forecast forest fires in the
Golestan province in Iran. A dataset for no-fire, medium confidence (MC) fire events, and …
Golestan province in Iran. A dataset for no-fire, medium confidence (MC) fire events, and …
Evaluating a new relative phenological correction and the effect of sentinel-based earth engine compositing approaches to map fire severity and burned area
AI Silva-Cardoza, DJ Vega-Nieva, J Briseño-Reyes… - Remote Sensing, 2022 - mdpi.com
The remote sensing of fire severity and burned area is fundamental in the evaluation of fire
impacts. The current study aimed to:(i) compare Sentinel-2 (S2) spectral indices to predict …
impacts. The current study aimed to:(i) compare Sentinel-2 (S2) spectral indices to predict …