1 results listed
In general, it is seen that the fire data is presented as the amount of the area burned
and the number of fires in time. Flammable material loads in forests, behavior patterns and
models of flammable materials according to climatic conditions etc. works are carried out
rapidly. All these studies aim to manage the process after the fire. There is a need to work on
measures to be taken in order to prevent the occurrence of fire. For this purpose; socioeconomic
factors that cause fires should be determined in regions where forest fire is common.
The elimination of these factors will minimize the occurrence of forest fires. In Turkey;
considering that 89% of the forest fires are caused by human beings, the importance of socioeconomic
studies in these regions is increasing. In the studies to determine the socio-economic
factors that cause forest fires; In some period, some studies such as multiple regression,
correlation, factor analysis etc. were conducted among some socio-economic data determined
according to the conditions of the region and / or fire numbers in the given period. In all these
studies a time section / part was taken into consideration. Materials and Methods; First time in
Turkey with this work; the relationship between the number of forest areas and forest fire
counts and the socio-economic variables determined by considering a certain period of time
was analyzed together with time and space. In the forest fires in the years 1980-1990-2000 in
Antalya Forest Regional Directorate for twelve governmental forest enterprises, the
relationship between the number of forest areas and fire numbers and 25 socio-economic
variables were determined. These data were analyzed by panel data analysis or Time Series
Cross Section Regression (TSCSREG) analysis method.
Variables with no effect in analysis and at the same time the variables / criteria that were
derived from each other were taken into consideration and these criteria were eliminated by
multiple linkage analysis (multiple linear analysis, multiple collinearity analysis) and reduced to 12 variables. Analysis of burned forest areas and selected socio-economic variables; It was
tested by Fuller and Battese Methods in the scope of TSCSREG Analysis.
Conclusion: In the analysis of the amount of burned forest areas and selected socio-economic
variables; A strong relationship between forest fires and selected socio-economic variables
shows that the value of R2 is 90.18%. The value of R2 is 70.19%. It shows that there is a
relationship between the numbers of fires and the socio-economic variables selected.
International Data Science & Engineering Symposium
IDSES
Ufuk COŞGUN