General scope of GIS Division
Geospatial information science (GIS) is the science and technology required for the generation, updating, storage, analysis, display and management of spatial information. In addition, it includes the application of spatial data and knowledge to solve different problems related to urban systems, environment, health, industries and so forth.
Several organizations are the producers of spatial data. Many others use spatial data for making their decision and carrying out their daily jobs. Graduates of GIS can be employed in such organizations. Alternatively, they can participate in private sector, in different fields related to the usage of spatial data.
GIS Division, as part of the faculty of Geodesy and Geomatics at K N Toosi University of Technology, consists of eight permanently-employed faculty members who are involved in different educational, research and consultancy, and administrative activities.
Educational objectives and activities of GIS Division
Staff members of the division try continuously to incorporate latest scientific and technical findings in GIS curriculum, while considering current domestic demands and needs. The main educational objectives of the division are:
· Education of engineers and researchers that can manage and use spatial data, in projects and activities of different organizations,
· Instruction of researchers and teaching-staff of other universities and research centers active in spatial data handling.
All courses offered by the division in postgraduate levels are:
· Geo-spatial information systems and spatial databases
· Quantitative spatial analysis in GIS
· Internet GIS and geo-web services
· Spatial decision making
· Application of computational intelligence in GIS
· Cloud computing and spatial big data
· Spatial data mining
· Spatial ontology and semantic web
· Distributed Geographical Information Systems
· Ubiquitous GIS and spatial data infrastructure
· Decentralized spatial computation
· Pervasive GIS and location based services
· Volunteered geographic information and location based social networks
· Spatial optimization using meta-heuristic methods
· LIS and smart urban management
· Spatial multi-criteria analysis and decision making
· Three-dimensional visualization and augmented reality
· Modeling and spatial optimization in GIS
· GIS and Environmental Modeling
· Spatial planning and land use planning
Research/consultancy objectives of GIS Division
The division’s research objectives can be summarized as follows:
· Developing fundamental and applied research and offering scientific consultation services related to spatial information needs of the community
· Promoting the national and international position of faculty and university in connection with spatial information science
· Introducing the value and paybacks of geospatial information and related expertise, when used for management and decision making in different applications. In this regard, the establishment of effective relationships with organizations, industry, experts and researchers from different disciplines is one of the main objectives of the division.
Research interests of GIS-division staff covers a wide range of subjects, including:
· Determining optimal locations for different land uses, facilities, service centers, etc.
· Development of spatial information systems, for alerting, managing, planning, responding and conducting rescue operations in natural disasters
· Design and development of mobile, internet and Ubi GIS systems for different applications
· Design and development of spatial tracking and navigation systems
· Generation of geo-spatial standards in national and organizational levels
· Usage of GIS for regional planning, land use planning and spatial planning
· Design and development of spatial decision support systems and models for the management of health, environment, natural resources, crime and security, facilities, traffic , urban development etc.
· Development of methods based on computational intelligence, optimization theories and data mining for solving spatio-temporal problems
· Spatial data infrastructure and interoperability issues