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.
Qualitative geographic information systems (GIS) have come a long way since the original call from critical GIS scholars in the 1990s. The invention of the geoweb as well as big data sources for ...qualitative information have enabled qualitative GIS to actually be implemented. Academic researchers are now grappling with how best to engage with and use qualitative spatial data. Our focus is on using qualitative data from social media sources. We review the process of collecting and analyzing patterns based on qualitative spatial data using methods from GIScience as well as new techniques from computational linguistics. We review these methods through the lens of critical qualitative GIScience. We reflect critically on the ethics associated with implementation of social qualitative data. Qualitative GIS has reached a critical juncture where the data, methods, and tools have enabled new questions to be asked that were previously not possible to pose. In this article we look to provide guidance and clarity for researchers engaging with geo-social and spatial qualitative data.
Arsenic (As) and antimony (Sb) often co-occur in floodplain depositional environments that are contaminated by legacy mining activities. However, the distribution of As and Sb throughout floodplains ...is not uniform, adding complexity and expense to management or remediation processes. Identifying floodplain morphology predictor variables that help quantify and explain As and Sb spatial distribution on floodplains is useful for management and remediation. We developed As and Sb risk maps estimating concentration and availability at a coastal floodplain wetland impacted by upper-catchment mining. Significant predictors of As and Sb concentrations included i) distance from distributary channel-wetland intersection and ii) elevation. Distance from channel explained 53 % (P < 0.01) and 28 % (P < 0.01), while elevation explained 42 % (P < 0.01) and 47 % (P < 0.01) of the variability in near-total Sb and As respectively. As had a higher extractability than Sb across all tested soil extractions, suggesting that As is more environmentally available. As and Sb dry mass estimates to a depth of 0.1 m scaled to the lower coastal Macleay floodplain ranged from 113–192 tonnes and 14–24 tonnes respectively. Landscape-scale modelling of metalloid distribution, informed by morphology variables, presented here may be a useful framework for the development of risk maps in other regions impacted by contaminated upper-catchment sediments.
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•We examine drivers of As and Sb spatial variability in floodplain wetland sediments.•Wetland elevation and distance from channel help to predict As and Sb distribution.•Integrating these landscape morphology components aids model prediction accuracy.•As is more environmentally available than Sb based on selective soil extractions.
India, with 80 % energy demand reliant on fossil fuels, is the world's third-largest greenhouse gas emitter, necessitating a shift from fossil fuels to renewable energy. While solar and wind ...production has grown, geothermal energy remains untapped despite enormous prospects in the country. In this regard, India's first regional-scale geothermal potential (GP) map has been prepared using a GIS based on a multi-criteria decision analysis technique. Five thematic layers (geology, fault, heat flow, thermal spring, and earthquake epicenter) have been used to calculate GP index, which is divided into high, moderate, and low categories. The result shows that most geothermal drilling sites are distributed in the high GP category zone, showing high efficacy. Further, a joint study of the geothermal surface and reservoir temperature with the present study shows that the northern and western parts of India have significant potential for geothermal exploration. Our result also reveals that the projected CO2 emissions are approximately 2.6 gigatons (which is lower than other energy sources) for an output of 10 GW using geothermal energy in the next 75 years. This study can enhance geothermal prospect identification, cutting exploration costs, and site selection, and contributing to multiple UN Sustainable Development Goals.
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