Spatiotemporal Analysis of Forest Fires in Cyprus Using Earth Observation and Climate Data - Prodromou, Maria; Girtsou, Stella; Leventis, Georgios; Charalampous, Georgia; Apostolakis, Alexis; Tzouvaras, Marios; Mettas, Christodoulos; Giannopoulos, Giorgos; Kontoes, Charalampos; Hadjimitsis, Diofantos G. (My University, 2025)
Wildfire detection remains a critical challenge for authorities, with human activity being the leading cause. The historical conditions prevailing in burned forest areas require a comprehensive analysis at both the environmental and anthropogenic levels. This study presents a multidimensional dataset comprising data from 2008 to 2024 and integrating Earth observation data and anthropogenic, environmental, meteorological, topographic, and fire-related features. This study evaluates, through time series analysis, the impact of climate trends such as increased temperature in comparison with anthropogenic activities such as deliberate fires. Time series analysis reveals that although climatic conditions with increased temperature and reduced precipitation in Cyprus intensify the risk of fire, the presence of fire events is primarily due to deliberate actions. The findings of this study support national-scale fire modeling, offering a foundation for targeted prevention, early warning systems, and sustainable forest fire management strategies.
Keywords: wildfire risk prediction; time series analysis; machine learning; Earth observation; Cyprus