A review of machine learning applications in wildfire science and management
Artificial intelligence has been applied in wildfire science and management since the 1990s,
with early applications including neural networks and expert systems. Since then, the field …
with early applications including neural networks and expert systems. Since then, the field …
Tamm Review: Management of mixed-severity fire regime forests in Oregon, Washington, and Northern California
Increasingly, objectives for forests with moderate-or mixed-severity fire regimes are to
restore successionally diverse landscapes that are resistant and resilient to current and …
restore successionally diverse landscapes that are resistant and resilient to current and …
A new metric for quantifying burn severity: the relativized burn ratio
Satellite-inferred burn severity data have become increasingly popular over the last decade
for management and research purposes. These data typically quantify spectral change …
for management and research purposes. These data typically quantify spectral change …
Assessing transferability of ecological models: an underappreciated aspect of statistical validation
Ecologists have long sought to distinguish relationships that are general from those that are
idiosyncratic to a narrow range of conditions. Conventional methods of model validation and …
idiosyncratic to a narrow range of conditions. Conventional methods of model validation and …
The utility of Random Forests for wildfire severity map**
Reliable fire severity map** is a vital resource for fire scientists and land management
agencies globally. Satellite derived pre-and post-fire differenced severity indices (∆ FSI) …
agencies globally. Satellite derived pre-and post-fire differenced severity indices (∆ FSI) …
Evaluating and comparing Sentinel 2A and Landsat-8 Operational Land Imager (OLI) spectral indices for estimating fire severity in a Mediterranean pine ecosystem of …
The main purpose of this study is to explore the relationship between three field-based fire
severity indices (Composite Burn Index-CBI, Geometrically structure CBI, weighted CBI) and …
severity indices (Composite Burn Index-CBI, Geometrically structure CBI, weighted CBI) and …
High-severity fire: evaluating its key drivers and map** its probability across western US forests
SA Parks, LM Holsinger, MH Panunto… - Environmental …, 2018 - iopscience.iop.org
Wildland fire is a critical process in forests of the western United States (US). Variation in fire
behavior, which is heavily influenced by fuel loading, terrain, weather, and vegetation type …
behavior, which is heavily influenced by fuel loading, terrain, weather, and vegetation type …
Both topography and climate affected forest and woodland burn severity in two regions of the western US, 1984 to 2006
Fire is a keystone process in many ecosystems of western North America. Severe fires kill
and consume large amounts of above‐and belowground biomass and affect soils, resulting …
and consume large amounts of above‐and belowground biomass and affect soils, resulting …
Wildland fire as a self‐regulating mechanism: the role of previous burns and weather in limiting fire progression
Theory suggests that natural fire regimes can result in landscapes that are both self‐
regulating and resilient to fire. For example, because fires consume fuel, they may create …
regulating and resilient to fire. For example, because fires consume fuel, they may create …
Mean composite fire severity metrics computed with Google Earth Engine offer improved accuracy and expanded map** potential
Landsat-based fire severity datasets are an invaluable resource for monitoring and research
purposes. These gridded fire severity datasets are generally produced with pre-and post-fire …
purposes. These gridded fire severity datasets are generally produced with pre-and post-fire …