Predicting the number of wildfire suppressions and areas damaged by wildfires, Chiang Mai Province

Abstract

Chiang Mai Province is the province with the highest number of forest fires and damaged areas in the country, continuously from the fiscal year 1998 to 2023. In order to assess the future situation, data on the number of forest fire suppression times and areas damaged by forest fires were used to predict them with linear correlation analysis, time series regression analysis, and forecasting based on Gray Systems Theory.

            The results showed that the area damaged by forest fires per time of fire suppression is on average likely to increase to more than 20 rai per time. The number of times of forest fire suppression and the damaged area are highly correlated. (Pearson’s correlation 0.576, Spearman's rho correlation 0.645), and the number of forest fire suppressions tends to decrease (slope -39.071), while damaged area tends to increase (slope 489.85).  Forecasting with the GM (1,1) Error Periodic Correction model gave a percentage of absolute error (MAPE) of less than 10 percent, which is a good forecast with a lower value than the GM (1,1) model. Prediction for the fiscal year 2024: there will be 1,145 forest fire suppression events, with a damaged area of 43,966 rai.