Analysis of forest fire and climate variability using Geospatial Technology for the State of Telangana, India

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Photo by Matt Palmer on Unsplash

Photo by Matt Palmer on Unsplash

Why is it important?

The dynamic changes in the regimes of forest fires are due to the severity of climate and weather factors. The aim of the study was to examine the trend of forest fires and to evaluate their relationship with climate parameters for the state of Telangana in India. The climate and forest fire data were used and uploaded to the GIS platform in a specified vector grid (spacing: 0.3° x 0.3°). The data were evaluated spatially and statistical methods were applied to examine any relationships. The study revealed that there was a 78% incidence of forest fires in the months of February and March. The overall forest fire hotspot analysis (January to June) of grids revealed that the seven highest forest fire grids retain fire events greater than 600 were found in the north east of Warangal, east of Khammam and south east of Mahbubnagar districts. The forest fire analysis significantly followed the month wise pattern in grid format. Ten grids (in count) showed a fire frequency greater than 240 in the month of March and of these, three grids (in count) were found to be common where the forest fire frequency was highest in the preceding month. Rapid seasonal climate/weather changes were observed which significantly enhanced the forest fire events in the month of February onwards. The solar radiation increased to 159% in the month of March when compared with the preceding month whereas the relative humidity decreased to 47% in the same month. Furthermore, the wind velocity was found to be highest (3.5 meter/sec.) in the month of February and precipitation was found to be lowest (2.9 mm) in the same month. The analysis of Cramer V coefficient (CVC) values for wind velocity, maximum temperature, solar radiation, relative humidity and precipitation with respect to fire incidence were found to be in increasing order and were in the range of 0.280 to 0.715. The CVC value for precipitation was found to be highest and equivalent to 0.715 and showed its strongest association/relationship with fire events. The significant increase in precipitation not only enhances the moisture in the soil but also in the dry fuel load lying on the forest floor which greatly reduces the fuel burning capacity of the forest. The predicted (2050) temperature anomalies data (RCP-6) for the month of February and March also showed a significant increase in temperature over those areas where forest fire events are found to be notably high in the present scenario which will certainly impact adversely on the future forest fire regime. Findings from this study have their own significance because such analyses/relationships have never be examined at the state level, therefore, it can help to fulfill the knowledge gap for the scientific community and the state forest department, and support fire prevention and control activities. There is a need to replicate this study in future by taking more climate variables which will certainly give a better understanding of forest fire events and their relationships with various parameters. The satellite remote sensing data and GIS have a strong potential to analyze various thematic datasets and in the visualization of spatial/temporal paradigms and thus significantly support the policy making framework.