Forest fire monitoring using spatial-statistical and Geo-spatial analysis of factors determining forest fire in Margalla Hills, Islamabad, Pakistan

The objective of this study is to adopt a methodology for analysing spatial patterns of danger of forest fire at Margalla Hills, Islamabad, Pakistan. The work is concentrated on burnt areas using Landsat data and to classify forest fire severity with different parameters (climatic, vegetation, topography and human activities). In addition to these four variables, the extent of the burned areas was measured. Statistical analysis at each fire scene was used to measure the effect on the variables. To calculate the fire severity ratio correlated to each variable, logistic and stepwise regressions were used. The results showed that the burned areas have increased at a rate of 25.848 ha/day (R (2) = 0.98) if the number of total days since the start of fire has increased. As a result, forest density, distance to roads, average quarterly maximum temperature and average quarterly mean wind speed were highly correlated with the fire severity. Only average quarterly maximum temperature and forest density affected the size of the burnt areas. Prediction maps indicate that 53% of forests are in the very low severity level (0.25-0.45), 25% in the low level (0.45-0.65) and 22% in high and very high levels (>0.65).

Automated summary

This study aims to analyze the spatial patterns of forest fire danger in Margalla Hills, Islamabad, Pakistan. The research focused on burnt areas, using Landsat data to classify the severity of forest fires based on various parameters. The results showed a correlation between forest density, distance to roads, maximum temperature, wind speed, and fire severity levels. Prediction maps indicated a distribution of forests in different severity levels.