Table 4: Prediction of forest fire risks.

Reference, Year

Purpose

Data

Classifier/Predictor

Performance

Safi and Bouroumi [132]

Fire weather index prediction

Weather observations

NN

9% error rate

Oliveira, et al. [135]

Fire density

Environmental, demographic, infra-structure, socio-economic

RF

96% variance explained

Cortez and Moarias [136]

Fire weather index prediction

Weather observations

SVM

12.7% Error

Arpaci, et al. [138]

Fire prediction

Weather, topology, infra-structure, socio-economic

RF

78% Accuracy

Liang, et al. [139]

Wildfire scale Prediction

Weather and wildfire data

LSTM

90.9% Accuracy

Rodrigues and Riva [140]

Human caused wildfire occurrences

socio-economics and economic activity, Fire causing possibilities

LR, SVM, RF

AUC=0.746

Tien Bui, et al. [141]

Spatial Pattern of forest fires

Weather, vegetation and infrastructure

MARS-DFP

86.5% Accuracy

Qu, et al. [144]

Fire occurance forecasting

Weather data

Auto-sklearn framework

87% Accuracy