Fire, a phenomenon occurs in most parts of the world and causes severe financial losses, even, irreparable damages. Many parameters are involved in the occurrence of a fire; some of which are constant over time (at least in a fire cycle), but the others are dynamic and vary over time. Unlike the earthquake, the disturbance of fire depends on a set of physical, chemical, and biological relations. Monitoring the changes to predict the occurrence of fire is efficient in forest management. Method: In this research, the Persian and English databases were structurally searched using the keywords of fire risk modeling, fire risk, fire risk prediction, remote sensing and the reviewed papers that predicted the fire risk in the field of remote sensing and geographic information system were retrieved. Then, the modeling and zoning data of fire risk prediction were extracted and analyzed in a descriptive manner. Accordingly, the study was conducted in 1995-2017. Findings: Fuzzy analytic hierarchy process (AHP) zoning method was more practical among the applied methods and the plant moisture stress measurement was the most efficient among the remote sensing indices. Discussion and Conclusion: The findings indicate that RS and GIS are effective tools in the study of fire risk prediction.

The hydroclimatological monitoring network in Haiti was inadequate before 2010 due to a lack of meteorological stations and inconsistent data recording. In the aftermath of the January 2010 earthquake, the monitoring network was reconstructed. In light of the prevailing circumstances and the mounting necessity for hydroclimatological data for water resource management at the national level, it is of paramount importance to leverage and optimize the limited available data to the greatest extent possible. The objective of this research is to develop regional equations that facilitate the transfer of climatic data from climatological stations to locations with limited or absent data. Physiographic and climatological characteristics are used to construct the hydrologic information transfer equations for sites with limited or no data. The validity of the regionalization techniques was assessed using cross-validation. The results enable estimation of hydrological events through the specific patterns of behavior of each region of the country, identified in cartography of homogeneous zones.

This study aims to investigate the relationship between internal and information integration within the supply chain (SCI-INTI and SCI-INFI), supply chain management (SCM) practices, and port operational performance (POP) in Oman’s container ports. Additionally, it explores the mediating role of SCM practices in the relationship between SCI-INTI, SCI-INFI, and POP in Oman. To meet the study’s objectives, a quantitative cross-sectional survey method was used. A total of 377 questionnaires were distributed to managers responsible for supply chain operations in the main departments at Sohar and Salalah ports, yielding 331 usable responses, with a response rate of 88 percent. The data collected were analyzed using partial least squares structural equation modeling (PLS-SEM). The results show that both internal and information integration within the supply chain have positive and statistically significant effects on the operational performance of Oman’s container ports (POP). Specifically, Supply Chain Integration with Internal Integration (SCI-INTI) significantly impacts POP (β = 0.249, t = 5.039, p < 0.001), and Supply Chain Integration with Information Integration (SCI-INFI) also significantly affects POP (β = 0.259, t = 4.966, p < 0.001). Additionally, SCI-INTI positively influences Supply Chain Management Practices (SCMP) (β = 0.381, t = 7.674, p < 0.001), as does SCI-INFI (β = 0.484, t = 9.878, p < 0.001). Furthermore, SCMP positively and significantly influences the operational performance of Oman’s container ports (β = 0.424, t = 7.643, p < 0.001). These findings contribute to the literature by emphasizing the significance of internal and information integration within the supply chain and SCM practices as strategic internal resources and capabilities that enhance operational performance in container ports. Understanding these elements enables decision-makers and policymakers within government port authorities and port operating companies to optimize internal resources and capabilities to improve port operational performance.

The rapid development of cities and urbanization in China has forced the growth of new channels for buying agricultural products. The purpose of this research is to examine how Internet of Things (IoT’s) technologies can digitize a traditional fresh food supply chain. Comparative and descriptive analysis methods are used to highlight the major pain points in the traditional supply chains and assess how digital transformation could help. We delve into every part of digital transformation, which includes establishing an information platform based on IoT and developing smart storage options. Our findings revealed that through end-to-end digital integration, supply chain efficiency is improved with shorter lead times and leaner inventories that yield reduced costs as well as fewer losses while ensuring product quality and traceability. In sum, such an approach would enhance sustainability within the fresh food value chain. As such, our article highlights key aspects of transitioning towards a digital environment in this sector for those planning similar ventures.

The idea of a smart city has evolved in recent years from limiting the city’s physical growth to a comprehensive idea that includes physical, social, information, and knowledge infrastructure. As of right now, many studies indicate the potential advantages of smart cities in the fields of education, transportation, and entertainment to achieve more sustainability, efficiency, optimization, collaboration, and creativity. So, it is necessary to survey some technical knowledge and technology to establish the smart city and digitize its services. Traffic and transportation management, together with other subsystems, is one of the key components of creating a smart city. We specify this research by exploring digital twin (DT) technologies and 3D model information in the context of traffic management as well as the need to acquire them in the modern world. Despite the abundance of research in this field, the majority of them concentrate on the technical aspects of its design in diverse sectors. More details are required on the application of DTs in the creation of intelligent transportation systems. Results from the literature indicate that implementing the Internet of Things (IoT) to the scope of traffic addresses the traffic management issues in densely populated cities and somewhat affects the air pollution reduction caused by transportation systems. Leading countries are moving towards integrated systems and platforms using Building Information Modelling (BIM), IoT, and Spatial Data Infrastructure (SDI) to make cities smarter. There has been limited research on the application of digital twin technology in traffic control. One reason for this could be the complexity of the traffic system, which involves multiple variables and interactions between different components. Developing an accurate digital twin model for traffic control would require a significant amount of data collection and analysis, as well as advanced modeling techniques to account for the dynamic nature of traffic flow. We explore the requirements for the implementation of the digital twin in the traffic control industry and a proper architecture based on 6 main layers is investigated for the deployment of this system. In addition, an emphasis on the particular function of DT in simulating high traffic flow, keeping track of accidents, and choosing the optimal path for vehicles has been reviewed. Furthermore, incorporating user-generated content and volunteered geographic information (VGI), considering the idea of the human as a sensor, together with IoT can be a future direction to provide a more accurate and up-to-date representation of the physical environment, especially for traffic control, according to the literature review. The results show there are some limitations in digital twins for traffic control. The current digital twins are only a 3D representation of the real world. The difficulty of synchronizing real and virtual world information is another challenge. Eventually, in order to employ this technology as effectively as feasible in urban management, the researchers must address these drawbacks.

This paper carries out an analysis and reflection on how technoscience reaches Geography through Geographic Information Technologies, how it impacts the production of geographic knowledge and how it derives in the possibility of digital experimentation in the discipline in an environment called geo-digital reality. It is shown that advances in GIT have allowed overcoming old limitations, enriching more and more the observations made by Geography, and it is also highlighted the promising future of digital experimentation in Geography through all the possibilities offered by current technological developments.