- Random Forests for Wildfire Insurance Applications🔍
- Utilizing random forests imputation of forest plot data for landscape ...🔍
- Linking Forest Treatment to Insurance Benefits by Reducing Wildfire ...🔍
- A Comparative Analysis of Machine Learning Models for Wildfire ...🔍
- Training data requirements for fire severity mapping using Landsat ...🔍
- The utility of Random Forests for wildfire severity mapping🔍
- A review of machine learning applications in wildfire science and ...🔍
- A review of machine learning applications in wildfire science ...🔍
Random Forests for Wildfire Insurance Applications
Random Forests for Wildfire Insurance Applications - Variance Journal
While for land cover predictors, the percentage of each land type is computed for each 1∘/120×1∘/120 grid cell. The random forest models in ...
Utilizing random forests imputation of forest plot data for landscape ...
Landfire data was used in this project because is publicly available, offers seamless coverage of variables needed for fire models, and is consistent with other ...
Linking Forest Treatment to Insurance Benefits by Reducing Wildfire ...
Despite being a proven tool in mitigating wildfire risk, insurance pricing models don't currently recognize the value of forest restoration. The ...
A Comparative Analysis of Machine Learning Models for Wildfire ...
introduced support vector machine (SVM) for forest fire prediction in the northeast region of Portugal by utilizing temperature, relative ...
Training data requirements for fire severity mapping using Landsat ...
The random forest classifier had an overall accuracy of ~88% for wildfires and ~68% for prescribed burns across the study fires. The discrepancy in accuracy ...
The utility of Random Forests for wildfire severity mapping
... The random forest outputs several probabilistic results from decision trees to create a final decision for the algorithm (Bustillo Sánchez et al., 2021).
A review of machine learning applications in wildfire science and ...
... Insurance and the Western Partnership for Wildland Fire ... Factors influencing regional-scale wildfire probability in Iran: an application of Random Forest and ...
A review of machine learning applications in wildfire science ... - arXiv
are widely available as implemented libraries. 2.1.1 Random Forests. A Random Forest (RF) [Breiman, 2001] is an ensemble model composed of a ...
Early wildfire detection using different machine learning algorithms
The results showed that the random forest algorithm with optimum hyperparameters had the highest accuracy in classifying fire and non-fire samples (77.95% ...
Wildfire Destruction — A Random Forest Classification of Forest Fires
Wildfire Destruction — A Random Forest Classification of Forest Fires · Features, Exploratory Data Analysis, and Baselining · More options.
Wildfire risk adaptation: propensity of forestland owners to purchase ...
... decision to purchase wildfire insurance for their ... to buy wildfire insurance because hurricane-damaged forests rep- resent a higher fire risk.
Using GIS and Random Forests to identify fire drivers in a forest city ...
A FC usually refers to an urban area with high forest coverage and where forests ... ArcGIS software was applied to randomly generate 1000 non- ...
Wildfire Risk Reduction Buffers - Guy Carpenter
If adopted, the framework can enable the risk transfer chain and increase accessibility and affordability of fire insurance in areas that may currently be ...
Predictive analytics of insurance claims using multivariate decision ...
Random forests variable importance measures may still be a sensible means for variable selection in many applications, but may not be too reliable in other.
Forest-Fire-Risk Prediction Based on Random Forest and ... - MDPI
Forest fires are important factors that influence and restrict the development of forest ecosystems. In this paper, forest-fire-risk ...
WILDFIRE RESILIENCE INSURANCE - The Nature Conservancy
fires after the application of ecological forestry burn‑area reductions. ... in or adjacent to forests should pilot wildfire resilience insurance.
Spatial-Temporal Modeling of Wildfire Losses with Applications in ...
5 Source: https://www.state.sc.us/forest/firesign.htm. Page 7. Spatial-Temporal Modeling of Wildfire Losses with Applications in Insurance-Linked Securities ...
The Impact of Changing Wildfire Risk on California's Residential ...
Given current insurance regulations and the behavior of insurers and policyholders, our findings indicate that climate change could have a substantial impact on ...
Predicting forest fire vulnerability using machine learning ...
... decision trees, random forests, support vector machines, artificial neural networks, and others, have been used to estimate the risk of forest fires [7]. It ...
FSim-Wildfire Risk Simulation Software | Missoula Fire Sciences ...
Quantitative wildfire risk analysis requires complete geospatial coverage of fire impact probabilities and sizes. Wildfire simulation is the primary means ...