## 4 Discussion
By analyzing demographic and socioeconomic information, researchers can gain insights into the vulnerability of different population segments to fire hazards [54; 55; 56]. For instance, certain age groups or socioeconomic categories may face higher risks during fire events, necessitating the identification of vulnerable groups for targeted intervention strategies and emergency response plans [44; 58]. However, in this study, the use of outdated census data from 2011 poses a limitation, as significant changes in population distribution and building characteristics might have occurred since then. To address this limitation and ensure more accurate assessments in the future, the plan involves updating the data with more recent census information. Including data from other studies, such as population demographics and socioeconomic information, can bring valuable insights to fire risk assessments. Unfortunately, data availability for the Greek territory posed a challenge, and as a result, this research did not integrate this specific type of data into the fire risk assessment. Furthermore, handling missing data is a common challenge in data-driven research, and it requires innovative techniques and alternative data sources to improve the completeness and accuracy of the dataset, particularly in areas with limited accessibility or missing data from the sources used in the study. In this study, the use of satellite imagery and remote sensing data proved valuable in filling the gaps and enhancing the spatial information of the study area. By employing these techniques, significant insights into land use, building characteristics, and population density were gained, particularly in areas with limited accessibility or missing data from the used sources. Moreover, the fire exposure layer is a crucial component of fire risk assessment that combines land value and land use data with remote sensing information. This layer provides valuable insights into the potential impact of fire incidents on different areas based on their economic and land use characteristics. By integrating land value data (EUR/m2) with land use information, decision-makers can better understand the potential financial losses and resource allocation required in the event of a fire. In cases where there is missing land value information for certain building blocks, neighboring data were leveraged to estimate the missing values [59]. This study employed an approach that involved using landscape characteristics derived from remote sensing data and the land value information of the closest neighboring building blocks with available data. Nevertheless, a comprehensive and accurate assessment of the financial aspect of fire risk necessitates the integration of multiple datasets encompassing various economic factors. These datasets typically include information such as gross domestic product (GDP), reconstruction/repair costs, housing insurance data, financial expenses during the reconstruction period (including indirect expenses), tourism statistics, and business and industry data, among others. Unfortunately, these essential datasets were not available for the specific area of interest, thus impeding their incorporation into the assessment. The significance of these data in providing a more complete financial perspective on fire risk is widely recognized. However, due to their unavailability within the study area, their inclusion was not feasible. Despite this constraint, this study contributes valuable insights into the broader understanding of fire risk assessment. Future research endeavors may benefit from obtaining access to these datasets, which could enhance the overall depth and scope of fire risk assessments. In addition, updating risk layers with field data offers several advantages in terms of improving the accuracy and granularity of fire risk assessments. By incorporating real-world observations from the field, the assessment becomes more precise and context-specific, providing valuable insights into the vulnerability of specific areas to fire incidents.