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A geographic information system (GIS) is a technical system which is supported by computer software and hardware systems. It focuses on the geographical information related to the whole or part of the earth’s surface. It is used for collecting, storing, managing, calculating, analyzing, displaying, and describing geographical information. It has inherent advantages in processing geographic data and plays an indispensable role in the sustainable detection of natural resources, natural disaster risk management, urban sustainable development planning, etc. With the continuous development of technology, the integration of GIS with emerging technologies such as big data, cloud services, and artificial intelligence creates new geographic information systems and entirely new development directions. The GIS architecture is of great value for the efficient execution of GIS systems. In this process, as the organizational form of GIS systems, the GIS architecture is also constantly evolving with the intersection and integration of GIS and other technologies. This research reviews a large amount of literature on component technologies, 3D technologies, cloud computing, big data, artificial intelligence, and so on, at home and abroad and analyzes and elaborates on the current development status and trends of GIS software architecture. It discusses in detail the characteristics and future development directions of different GIS software architectures in different periods and makes delicate descriptions of their hierarchical features. This study aims to summarize the advantages and disadvantages of architectures in different stages, the interactivity from the user’s perspective. On this basis, it studies the development trends of GIS integrated with big data and artificial intelligence, summarizes the laws and experience of the evolution of its system architecture, and analyzes the technological drivers of each evolution and their impact on GIS applications. Reviewing the evolution history of GIS frameworks is expected to provide guiding references for more efficient GIS system architecture research in the future.

The Beas sub basin falling under the Indus basin in Northern India is experiencing notable changes due to human interventions since the rise of civilization in the Indus valley. The incessant anthropogenic pressure, infrastructural development, deforestation and encroachment have made the sub basin more vulnerable to land degradation, erosion and landslides. Thus this study attempts to classify the watersheds based on morphometric characteristics and prioritize the watersheds for sub basin management as a whole so that restoration process can concentrate on the high risk prone watersheds. In this study ALOS PALSAR DEM of 12.5 meters was used to extract the drainage network, watershed, catchment sub basin and basin boundary complemented by topographic and hydrological maps. The study analyses 49 morphometric parameters under categories like linear, areal and relief characteristics. The result classifies the erosion capacity of total 4126 streams with the cumulative length of 12,287.51 km over a sub basin area of 19,338.8 Km2. The morphometric parameters were integrated for each watershed and compound factor was given to rank vulnerability in the GIS environment. The results depicted that sub watershed numbers 2, 6, 12, 16 were high risk prone and underlined as an area which requires immediate attention for soil water conservation measures.

Rapid development of science and technology makes GIS technology widely used in China, especially in ecological environment evaluation. Application of GIS technology can not only deeply, scientifically and systematically study the elements in different environments, but also improve the standardization and reliability of environmental evaluation research. By using the common application of GIS in various ecological environment evaluations, this paper studies its ecological environment evaluation in western region.

The main objective of the Portuguese project “CONVERTE-Biomass Potential for Energy” is to support the transition to a low-carbon economy, identifying biomass typologies in mainland Portugal, namely agri-forest waste, energy crops and microalgae. Therefore, the aim was to design and construct a georeferenced (mapping) database for mainland Portugal, to identify land availability for the implementation of energy crops and microalgae cultures, and to locate agricultural and forestry production areas (including their residues) with potential for sustainable exploitation for energy. The ArcGIS software was used as a Geographic Information System (GIS) tool, introducing the data corresponding to the type of soil, water needs and edaphoclimatic conditions in shapefile and raster data type, to assess the areas for the implantation of the biomass of interest. After analysing the data of interest in each map in ArcGIS, the intersection of all maps is presented, suggesting adequate areas and predicting biomass productions for the implementation of each culture in mainland Portugal. Under the conditions of the study, cardoon (72 kha, 1085 kt), paulownia (81 kha, 26 kt) and microalgae (29 kha, 1616 kt) presented the greater viability to be exploited as biomass to energy in degraded and marginal soils.

Oñate, V.; Orejarena-Rondón, A.F., and Restrepo, J.C., 2024. A simple approach to the risk assessment of strategic infrastructure on the Colombian Caribbean coast. Journal of Coastal Research, 40(4), 749–767. Charlotte (North Carolina), ISSN 0749-0208. Strategic infrastructure at risk was identified on the Colombian Caribbean coast. The risk approach consisted of an estimation of the main coastal hazards (coastal erosion, mean sea-level rise, and changes in wave energy flux) and the exposure level, as one of the most significant components of vulnerability, through multicriteria analysis and GISs. It identified 88 strategic coastal infrastructures that are at risk, located less than 250 m from the coastline, and belong to the energy, health, education, and transportation sectors. Of these, 34.1% are at a medium-high risk level, and 20.5% are classified as high-risk critical infrastructure. The analysis also revealed that anthropogenic interventions, such as sand mining, poorly designed hard coastal protection structures (groins, seawalls, and breakwaters), or damage to marine ecosystems, might have a relevant weight on the risk degree of critical infrastructure, highlighting the relevance of appropriate coastal protection measures for strategic infrastructure. This simplified approach aimed to contribute to the risk management of such essential elements and guarantee compliance with the predisaster stage of disaster risk management.

Considering the geographical location and climatic conditions of Iran, solar energy can provide a considerable portion of the energy demand for the country. This study develops a two-step framework. In the first step, the map of unsuitable regions is extracted based on the defined constraints. In the next step, in order to identify the suitability of different regions, 11 defined criteria, including solar radiation, average annual temperatures, distance from power transmission lines, distance from major roads, distance from residential area, elevation, slope, land use, average annual cloudy days, average annual humidity and average annual dusty days, are identified. The relative weights of defined criteria and sub-criteria are also determined applying fuzzy analytical hierarchy process (FAHP) technique. Next, by overlaying these criteria layers, the final map of prioritization of different regions of Iran for exploiting solar photovoltaic (PV) plants is developed. Based on Iran’s political divisions, investigation and analysis of the results have been presented for a total of 1057 districts of the country, where each district stands in one of the five defined classes of excellent, good, fair, low, and poor level. The obtained data indicate that 14.7% (237,920 km2), 17.2% (278,270 km2), 19.2% (311,767 km2), 11.3% (183,057 km2), 1.8% (30,549 km2) and 35.8% (580,264 km2) of Iran’s area are positioned as excellent, good, fair, low, poor and unsuitable areas, respectively. Moreover, Kerman, Yazd, Fars, Sisitan and Baluchestan, Southern Khorasan and Isfahan are included in the regions as the most excellent suitable provinces for exploiting solar PV plants.

As is well known, Italy's very consistent buildings stock has become the major field for real estate investments and for the related projects and actions. It is a heritage that is often barely known and extremely complex, whose management has until now been addressed in a rather casual and uninformed manner, with unsatisfactory and sometimes disastrous outcomes. The situation is worse in the case of buildings of particular historical, artistic and architectural value so frequent within the heritage of our country. This paper shows the findings of an ongoing research which is aimed at structuring the cognitive process and assessing enhancement and re-functionalisation scenarios of our historical and architectural heritage through the use and integration of information systems such as BIM and the GIS. The work led to the development of a workflow able to integrate the contribution of the HBIM and GIS methodologies in the structuring and management of a wide range of digital data and information useful for its management. The research, focused on “La Gran Torre di Oristano, is aimed at creating the best conditions for an integrated and multidisciplinary strategy of requalification and refunctionalisation of historical and architectural heritage.

Extreme precipitation trends and events are fundamental for the definition of the region’s climate and allow the subsequent analysis of the risk for the territory and the possible countermeasures. This study takes into account the Marche Region (Central Italy) with 128 rain gauges from 1921 to 2017. Initially, in order to obtain a rainfall overview, the dominant trend of the period 1921–2017 was evaluated. Initially, in order to obtain a rainfall overview, the dominant trend of the period 1921–2017 was evaluated. In addition, to obtain a comparable analysis, the average precipitations grouped in climatological standard normals were analyzed. Finally, the main purpose of the research was achieved by analyzing extreme events in the middle Adriatic side. In addition, forecasts of extreme precipitation events, with a return period of 100 years, were made using the theory of “generalized extreme value” (GEV). The innovation of this research is represented by the use of geostatistics to spatialize the variables investigated, through a clear and immediate graphic representation performed through GIS software. This study is a necessary starting point for the study of climate dynamics in the region, and it is also a useful tool for land use planning.