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.
Open Source GIS Mitasova, Helena; Neteler, Markus
2008, 2007
eBook
With this third edition of Open Source GIS: A GRASS GIS Approach, we enter the new era of GRASS6, the first release that includes substantial new code developed by the International GRASS Development ...Team. The dramatic growth in open source software libraries has made the GRASS6 development more efficient, and has enhanced GRASS interoperability with a wide range of open source and proprietary geospatial tools. Thoroughly updated with material related to the GRASS6, the third edition includes new sections on attribute database management and SQL support, vector networks analysis, lidar data processing and new graphical user interfaces. All chapters were updated with numerous practical examples using the first release of a comprehensive, state-of-the-art geospatial data set.
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.
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Dostopno za:
BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The information required for construction quantities surveying is not only generated by various participants in different construction phases but also stored in different forms including graphics, ...text, tables, or various combinations of the three. To report a bill of quantities (BOQ), the project manager has to continuously excerpt information from various resources and record it on papers. Without adequate staff and time, this repetitive and tedious process is difficult for the project manager to handle properly and thus reduces the effectiveness and the accuracy of the quantities surveying process which creates problems during the design, tender, and construction supervision of construction projects for designers and contractors practicing because receipts are based upon actual quantities, such variations have an obvious impact on the contractor’s cash flow, once the actual quantities frequently vary from the estimated quantities listed in the BOQ. Hence, automation quantity surveying system has been developed by using GIS to extract the data required for the quantity of different components of any construction project from AutoCAD drawings (spatial data), to report a BOQ after querying, manipulation, and analyzing these data. The system has been implemented on the construction project of Al khawarizmy College at Baghdad University in Baghdad. The main results of using this system are automatic generation a bill of quantity (BOQ) directly from design drawing, with overcome to design changing, accurate, fast, and effective method for estimating the quantities, fewer errors in cost estimating, and better documentation for continuously reusing information in all construction phases. The accuracy of GIS quantities had been proved by comparing these quantities with the quantities of site surveying. Then determining the accuracy percentage (A%) of GIS quantities which equals (98.85%), and the regression line that equals 0.999. These values mean; there are big correlation between the estimated quantities by GIS and the quantities of site surveying.
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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