ANALYSIS OF THE RELATIONSHIP BETWEEN CONSECUTIVE DRY DAYS INDEX ON HOT SPOT GROWTH DUE TO FOREST FIRE (CASE STUDY: SOUTH SUMATRA AND WEST KALIMANTAN)

• Main Author: Azaria, Rafly
• Format: Final Project
• Language: Indonesia
• Subjects: Geologi, hidrologi & meteorologi
• Online Access: https://digilib.itb.ac.id/gdl/view/75672
• Institution: Institut Teknologi Bandung

The provinces of South Sumatra and West Kalimantan are provinces in Indonesia which are prone to forest and land fires which are closely related to meteorological factors. Extreme weather conditions where there is no rain for several consecutive days (CDD) can increase the growth of hotspots. However, the lack of further research regarding the linkage and effectiveness of the radius between CDD on the growth of hotspots due to forest fires is considered to be causing losses in the future. So this research was conducted to determine the relationship between CDD and hotspot growth. There are 2 daily rainfall observation data at the Sultan Mahmud Badaruddin II Meteorological Station, Palembang, South Sumatra and Nangapinoh Meteorological Station, Melawi Regency, West Kalimantan as well as Terra and Aqua satellite hotspot data with a confidence level above 80% for the period 1 January 2015 to 31 December 2019. The research method at this time was by calculating the frequency of each CDDs classification, a buffer analysis was carried out with a radius of 25 km, 50 km and 100 km from the meteorological station points and to see the density of hot spots, a kernel density heatmap was carried out. Furthermore, the calculation of the ratio between the hotspot frequencies at the time of the x-CDD will be calculated in the Pearson correlation. The Pearson correlation value obtained was seen at the significance level of each radius with the t-test approach. The results of this study show the growth of hotspots in both areas. Most of them are on peatlands. Statistically, the relationship between the CDD index and the growth of hot spots at 50 km and 100 km radius has a positive correlation and the strength of the relationship is very strong with a significance level smaller than the alpha value of 1%, so it can reject the null hypothesis. whereas for a radius of 25km it has a weak negative correlation value with a significance level greater than the alpha value of 1% and at a radius of 25km it cannot reject the null hypothesis. So the CDDs drought index is closely related to the growth of hotspots and is effective only at a radius of 50 km and 100 km.