This study provides a comprehensive overview of modern cartography innovations and emerging trends, highlighting the importance of geospatial representation in various fields. It discusses recent advancements in geospatial data collection techniques, including satellite and aerial imagery, Light Detection and Ranging (LiDAR) technology, and crowdsourcing. The research also investigates the integration of big data, machine learning, and real-time processing in Geographic Information Systems (GIS), as well as advances in geospatial visualization. In addition, it examines the role of cartography in addressing global challenges such as climate change, disaster management, and urban planning in line with the International Cartographic Association’s (ICA) perspectives. The study discusses the ethical considerations and challenges associated with modern cartography, including privacy, data security, and accessibility issues. Finally, it outlines future directions and opportunities in cartography, focusing on the potential applications of artificial intelligence, interdisciplinary collaborations, and open-source platforms. This discussion aims to emphasize the significance of continued research and development in cartography and encourage interdisciplinary collaboration for a better understanding of the world.

The effective management of cadastral systems in conflict-impacted communities is fraught with challenges, such as land disputes, insecure land tenure, and pervasive corruption. This study introduces a blockchain-based framework as a potential solution to these challenges, utilizing the technology's inherent strengths in decentralization, security, transparency, and immutability. It comprehensively analyzes the issues afflicting cadastral systems in conflict areas, explores blockchain technology's core principles and capabilities, and investigates its applicability in various aspects of land registry, property rights management, and administrative governance. In addition, the research discusses existing literature, illustrating the implementation of blockchain in cadastral systems and highlighting the observed benefits, such as enhanced efficiency, fraud prevention, and improved stakeholder collaboration. It examines the challenges and limitations associated with blockchain implementation, including technological complexities, legal and regulatory hurdles, and socio-cultural considerations. The study findings reveal future directions, emerging trends, and the importance of strategic collaborations, offering policy recommendations focused on innovation, capacity building, and stakeholder engagement for the successful integration of blockchain in cadastral systems of conflict-impacted communities.

Soil erosion remains a complex environmental phenomenon with broad implications for ecosystem stability and land management. The topographic wetness index (TWI), a commonly employed indicator in hydrological and geomorphological modeling, plays a crucial role in understanding how moisture distribution influences erosion potential. Despite its widespread use, TWI's theoretical grounding in multi-scale erosion assessment remains underexplored. Existing literature tends to focus on empirical applications at isolated spatial scales, often overlooking scale-sensitive behaviors and theoretical consistency. This study develops a conceptual framework for understanding the scale dependency of TWI in soil erosion modeling. It explores the assumptions underpinning TWI, its mathematical structure, and its interaction with scale-related processes by interacting with theoretical perspectives from geomorphology, hydrology, and spatial analysis. The study proposes a theoretical model for evaluating TWI's suitability across scales, identifying key factors that influence its performance. This framework aims to inform more robust and theoretically grounded applications of TWI in soil erosion assessment, paving the way for improved model transferability and sustainable land management practices.

Worldwide, flash floods are among the most unpredictable and hazardous hydrological phenomena, particularly in arid and semi-arid regions such as the Kingdom of Saudi Arabia, where sudden heavy rainfall follows prolonged periods of drought. This work presents an effective integrated model for flood hazard evaluation in the Hanefah Catchment, a socioeconomically vital area in the central part of Saudi Arabia that includes the capital city, Riyadh. Using high-resolution ALOS PALSAR 12.5 m Digital Elevation Model spatial data, we extracted and investigated indicative linear, areal, and relief morphometric keys of 64 sub-catchments. This paper employs a dual-method concept that integrates a multi-criteria ranking method and the El-Shamy approach in conjunction with morphotectonic analysis to model flood-susceptibility zones. Furthermore, this paper suggests a comparative assessment of low-cost morphometric models under data-scarce conditions, assessing the multi-criteria ranking method against El-Shamy’s approach, using the topographic position index (TPI) as an internal terrain scale benchmark. The ranking method successfully assigned 85.7% of the historically recorded flood locations to the high-hazard zone that covers ~24.22% of the Hanefah catchment. In contrast, the El-Shamy approach systematically underestimated flood susceptibility because regional tectonic activity increases bifurcation ratios, resulting in just ~42.9% of the historical floods being assigned to the high-hazard zone. The final results highlight the northern and northwestern parts of the catchment as high-hazard zones, characterized by high drainage density and steep relief. This study provides a refined, cost-effective model that aligns with the strategic objectives of Saudi Vision 2030 for sustainable water resources management and significant urban development.

Flash flood events are among the most critical hydrological hazards in arid and semi-arid regions, posing extreme threats to critical infrastructure, human safety, and sustainable development plans. This paper evaluates the flash flood susceptibility of the Al’Ataya catchment, a key watershed on the southern Red Sea coast, using an integrated geospatial analysis approach. To assess and quantify the flood hazard, we investigated 15 morphometric parameters for 24 particular sub-catchments within a sixth-order drainage system. Two complementary methods, the Morphometric Ranking Method and El-Shamy’s approach, were utilized to classify the catchment into different flood susceptibility levels. Results from the Ranking Method identified seven sub-catchments (SC-2, SC-3, SC-6, SC-7, SC-8, SC-9, and SC-19) as having high flood hazard levels, mainly driven by large watershed areas, steep slopes, and high relief ratios. In contrast, El-Shamy’s approach resulted in a different evaluation, identifying sub-catchments in Zone B (SC-23, SC-16, SC-17, SC-15, SC-6, SC-20) as high hazard sub-catchments due to the particular relationship between the bifurcation ratio parameter and the drainage density and stream frequency parameters. The integration of the two methods suggests that the susceptibility factor is controlled by the combined influence of a low drainage density and steep mountainous terrain draining toward the coastal zone. These results provide a spatial model for flood mitigation and early warning systems, supporting Saudi Vision 2030 through improvement to the development of southern urban centers such as Al’Ataya and Sabya.