## 1 Introduction
Also, this analysis highlighted a strong correlation between a region's geographical location, its size, its population, and its susceptibility to specific natural disasters. For example, seismic activity was more prevalent in Asia, while storms were more common in the United States due to its diverse climate. Also, [PERSON] et al. [63] uncovered rising trends over time in both droughts and wildfires, with their spatial distribution increasingly shaped by the effects of climate change and human activities. The study's findings highlight how the economic damages from these disasters play a significant role in hindering the recovery process for the communities impacted. Furthermore, according to the 2023 annual report from the EM-DAT database [64], a total of 399 disasters were recorded, leading to 86,473 fatalities and impacting 93.1 million people globally. Among the most catastrophic events were the earthquake in Turkey and Syria and the severe drought in Indonesia, both of which had profound effects on human lives and the economies of the affected regions. A comprehensive review of the literature on various disasters reveals significant trends in their frequency, distribution, and impact, underscoring the need for enhanced preparedness and mitigation strategies worldwide [65; 63]. For example, a study examining the geospatial and temporal distribution of disasters revealed that floods have become more frequent in recent decades, with Asia and Africa experiencing the highest fatality rates [63]. The findings highlight the urgent need to enhance drainage infrastructure and flood protection measures in these vulnerable regions. In another study, [PERSON], [PERSON], [PERSON], [PERSON], and [PERSON] [65] developed a comprehensive framework for assessing global flood risks, validated using data from the EM-DAT database. The study employed a global hydrological model and downscaling techniques to estimate flood hazards and their impacts, which were then cross-verified with recorded flood events from EM-DAT. This methodology enabled a thorough evaluation of flood risks on a global scale, taking into account both present and future climate conditions [65]. Another study focused on utilizing the EM-DAT database to analyze global flood losses [66]. The researchers highlighted challenges in accurately capturing flood loss data, such as biased reporting and changes over time [66]. The study emphasized the critical importance of normalizing data to ensure reliable trend analysis and called for comprehensive and standardized flood data to improve disaster management efforts. On the other hand, using the EM-DAT database, one study compiled a detailed catalog and map of major flood disasters in Europe from 1950 to 2005 [67]. By providing a comprehensive overview of these events, the study significantly enhanced the understanding of flood risks, supporting more informed political and economic decisions for disaster mitigation [67]. These studies illustrate how the EM-DAT database plays a crucial role in providing vital data for analyzing flood patterns, which in turn support both global and regional flood risk assessments and inform disaster management strategies. Geospatial data are critical for understanding and analyzing the distribution of earthquakes. One particularly intriguing study explored mutual information and clustering analysis to visualize and examine global seismic data [68]. By categorizing seismic events according to their geographic location and magnitude, the study generated intuitive maps that revealed intricate relationships within earthquake data--relationships that are often missed by traditional mapping methods [68]. [PERSON] et al. [69] found that WEED, a tool developed to geocode and analyze historical disaster data from the EM-DAT database, including earthquakes, allows for precise geocoding by associating latitude and longitude coordinates with disaster events. This advancement facilitates the integration of disaster data with geophysical and geospatial variables for more detailed analysis.