Modeling the susceptibility of an uneven-aged broad-leaved forest to snowstorm damage using spatially explicit machine learning
Snowstorms are disturbance agents that have received relatively little research attention
rather than significant disturbances that they pose to forest ecosystems. In this study, we …
rather than significant disturbances that they pose to forest ecosystems. In this study, we …
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 …
Understanding municipal solid waste production and diversion factors utilizing deep-learning methods
Y Zhao, H Li - Utilities Policy, 2023 - Elsevier
We propose a hybrid deep learning neural network model for accurately calculating
municipal solid waste (MSW) production and diversions with socioeconomic and …
municipal solid waste (MSW) production and diversions with socioeconomic and …
Forest fire forecasting using fuzzy logic models
A Nebot, F Mugica - Forests, 2021 - mdpi.com
In this study, we explored hybrid fuzzy logic modelling techniques to predict the burned area
of forest fires. Fast detection is crucial for successful firefighting, and a model with an …
of forest fires. Fast detection is crucial for successful firefighting, and a model with an …
Modelling wildfire susceptibility in Belize's ecosystems and protected areas using machine learning and knowledge-based methods
SD Chicas, J Østergaard Nielsen, MC Valdez… - Geocarto …, 2022 - Taylor & Francis
Wildfires are serious threats to Belize's protected areas and ecosystems. In Belize the spatial
variability of wildfire susceptibility and influencing factors at a national scale are poorly …
variability of wildfire susceptibility and influencing factors at a national scale are poorly …
Integrating Support Vector Machines with Different Ensemble Learners for Improving Streamflow Simulation in an Ungauged Watershed
Streamflow simulation, particularly in ungauged watersheds, poses a significant challenge
in surface water hydrology. The estimation of natural river and streamflow has been a …
in surface water hydrology. The estimation of natural river and streamflow has been a …
Vegetation vulnerability to hydrometeorological stresses in water-scarce areas using machine learning and remote sensing techniques
The quantitative understanding of vegetation vulnerability as a major example of terrestrial
ecosystems under hydrometeorological stress is essential for environmental risk …
ecosystems under hydrometeorological stress is essential for environmental risk …
Landslide susceptibility mapping using single machine learning models: a case study from Pithoragarh District, India
Landslides are one of the most devastating natural hazards causing huge loss of life and
damage to properties and infrastructures and adversely affecting the socioeconomy of the …
damage to properties and infrastructures and adversely affecting the socioeconomy of the …
Effects of different sampling strategies for unburned label selection in machine learning modelling of wildfire occurrence probability
The selection of unburned labels is a crucial step in machine learning modelling of wildfire
occurrence probability. However, the effect of different sampling strategies on the …
occurrence probability. However, the effect of different sampling strategies on the …
MODIS-FIRMS and ground-truthing-based wildfire likelihood mapping of Sikkim Himalaya using machine learning algorithms
P Banerjee - Natural hazards, 2022 - Springer
Wildfires in limited extent and intensity can be a boon for the forest ecosystem. However,
recent episodes of wildfires of 2019 in Australia and Brazil are sad reminders of their heavy …
recent episodes of wildfires of 2019 in Australia and Brazil are sad reminders of their heavy …