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

Abstract

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 ¼ 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).

Assessing Burned Areas in Wildfires and Prescribed Fires with Spectral Indices and SAR Images in the Margalla Hills of Pakistan

“…The region is not used as pasture and is regularly affected by fires [29]. The climate of the region is subtropical; the average maximum summer temperature is 34.3 • C [4,5,30], and total annual precipitation is, on average, 1200 mm [28,31,32], the majority of which falls in July and August. Accordingly, the fire season occurs between May and July, when the temperatures are warmest and before the beginning of the monsoonal rains [4,5,13,33].…”

“…The climate of the region is subtropical; the average maximum summer temperature is 34.3 • C [4,5,30], and total annual precipitation is, on average, 1200 mm [28,31,32], the majority of which falls in July and August. Accordingly, the fire season occurs between May and July, when the temperatures are warmest and before the beginning of the monsoonal rains [4,5,13,33]. Lightning and the hot and dry weather during the summer months combined with the dry conditions in the autumnal months of September and October after the monsoon season are the natural and primary causes for the ignition and spread of wildfires, while anthropogenic causes coming in second place in reports of past fire incidents [34][35][36].…”

“…Wildfires are a common natural occurrence in many environments and constitute a vital component for their management. However, fires of high severity that cause devasting impacts over large areas have recently been documented, notably in the United States of America, the Mediterranean region, Australia, and Pakistan [1][2][3][4][5], bringing into question the effectiveness of current management practices, as these severe wildfires lead to an undesirable alteration and degradation of the landscape [6]. Many variables influence the severity of a fire, including elevation, slope and aspect [7], weather and climatic conditions [8], the structural characteristics of the forest, such as the density of trees and their diameter [9], and the history of fires in the area [10].…”

Quantitative Analysis of Forest Fires in Southeastern Australia Using SAR Data

“…Wildfires are a global agent for environmental change [1,2], and prescribed burning is an important strategy to minimize the harmful impact of wildfires globally [3]. Prescribed burning has proven effective in various regions, including Southern Europe [4], North America [5,6], and Australia [7][8][9]. In order to meet particular environmental protection targets, controlled fires are required for prescribed burning.…”

A Synthesis of Spatial Forest Assessment Studies Using Remote Sensing Data and Techniques in Pakistan

“…[69], who used Landsat 5 TM, Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and SPOT-5 High-Resolution Visible (HRV) imageries to temporally map the western Himalayan subalpine conifer and subtropical pine forests in Swat and Shangla districts of the former NWFP. The forest cover in the Shangla district was 539 km 2 , as calculated through the GFW data set.…”