A review on status, implications and recent trends of forest fire management

Abstract

Forest fire spread out in an area having combustible material in the summer season with high temperature. It burns the area and looks like a misery. Forest fire is one of the factors that severely affects the forest biodiversity. Burning actions in a forest affects not only flora and fauna but also soil properties changed due to the forest fire. In summer season on sloppy topography forest fire originates in tropical forests. While in coniferous forests, forest fire outbreaks during the resin extraction activities. More than 350 million hectares (ha) was estimated to be affected by vegetation fires globally. In India about 55% of forest area is prone to the fire. Fires can be natural or man- made, but manmade fire affects mostly. Several forest types and areas are more susceptible to forest fires because of suitable weather, topography and inflammable material. Forest fires adversely affect the soil, water, flora and fauna and disrupt the ecological functions. The new advances in fire control are remote sensing and GIS where real time information can be gathered about the fire break and immediate follow can be done. The chemicals (as borate, ammonium sulfate and ammonium biphosphate) are used for fire control and various other types of fire retardants are used to keep the fire under control. Forest fire changes the composition of vegetation, extinction of species, development of the various adaptations in unwanted plants. Nutrient cycle and soils are affected. Frequent forest fire events cause global warming. Forest fire needed to be controlled at initial stage and the large fires should not be allowed to occur, the modern techniques of monitoring, detection and control must be used for avoiding the large fires happenings.

Remote Sensing for Assessing the Ecological and Socio-Economic Impacts of Forest Fire Severity in Kozan District, Turkey

“…There is a need for effective methods for fire risk assessments because wildfires have a significant impact on socioeconomic and environmental aspects, even at a local spatial scale. This will allow for the use of proactive control measures for environmental management (Attri et al, 2020;Moreira et al, 2011;Sari, 2022). This study evaluated the effects of vegetation, topographic factors (elevation, slope, and aspect), and population density on burn severity (Fig.…”

“…Generally speaking, the majority of Mediterranean-type vegetation has a long history of forest degradation due to human-caused fires (Naveh, 1975;Türkmen & Düzenli, 2011) and environmental factors (Attri et al, 2020;Ganteaume et al, 2013). The General Directorates of Forestry in Turkey have been recording wildfires since 1937.…”

“…The remote sensing approach for burned area detection for active and post-fires activities (Lentile et al, 2006) is now well recognized by the scientific community (Chuvieco, 2003;Chuvieco et al, 2020;Chuvieco et al, 2010;Kurbanov et al, 2017). Multi-temporal remote sensing data can provide Spatio-temporal observations (before, during, and after) of the wildfires which can potentially be used for fire detection, damage assessment, and mitigation planning efficiently and cost-effectively (Attri et al, 2020).…”

Forest Fire Recognition Based on Feature Extraction from Multi-View Images

“…Heyns et al [20] integrated traditional recognition method with neural network: AdaBoost and local binary pattern (LBP) were employed to initially recognize the images and extract the candidate regions for flames; Then, the features were extracted from the candidate regions and classified by the CNN. Attri et al [21] applied the deep belief network (DBN) to recognize flames. Considering the volume difference between fire images and normal images, Cuomo et al [22] trained residual network (ResNet) [23] with biased data, and recognized flames with the trained network.…”

“…Suppose X(i,j) is an element corresponding to the i-th image and j-th flame feature. Then, the dynamic feature based on that matrix can be described by mean and mean squared error (MSE) [21]:…”