ABOUT THE COURSE: In today’s world – the flow of information especially digital information has become the critical ingredient for success in any activity. That is why, the period we live in is often referred to as an information age. It is a simple fact that everything human beings do, do takes place at a certain location on the earth – it has a geographic component. The digital information revolution of the late twentieth century has allowed this spatial information to be more easily accessed, analyzed and used than ever before. This led to the development of SIS as a discipline and emergence of GIS as a core of digital technology.Traditionally, the discipline of Geography dealt with spatial description and analysis. Now in the era of multi-disciplinary approach, students, researchers, professionals from different disciplines find their way into the emerging discipline of GIS making it popular. The rapid expansion and popularization of GIS means that now Spatial Science is not just for the specialists, but for every-one, but these users have different requirements. The present Course is an attempt to provide basic fundamentals of Space oriented training for students and professionals.The course is designed to provide in-depth explanations of key concepts and topics which are easy to follow and understand. It also contains wide range of highly effective and explanatory lab-work for additional informations.INTENDED AUDIENCE: This course is designed for professionals, students, and researchers who wish to gain practical skills in spatial data science using open source GIS software. It is suitable for individuals from diverse backgrounds, including all domains of science, engineering,, architecture, life sciences and social sciences with spatial iinformation is a must for planning – development and monitoring of resources and their distributionINDUSTRY SUPPORT: The course is designed incorporating of NEP 2020 considering recent developments in the field and the need for skilled workforce. Especially with govt. initiatives e.g. Smart cities, SWAMITVA, AMRUT, etc. and in sectors particularly transport, logistics, supply chain management; policy changes like de-regulating geospatial data have tremendously increased its adoption and scope.
Overview
Syllabus
Week 1:Human cognition of the spatial world, Sensing and perceiving the world, Cognitive maps, Spatial learning and interpretation of maps
Week 2:Defining a map, types, space representation concepts, features and properties, Map projections, Georeferencing.
Week 3:Information organization and data structure, Data and information, Geographic data and spatial information. The relationship perspective of information organization.
Week 4:Fundamental concepts of data, Spatial – non spatial data, Database management system. Spatial data formats – raster and vector, Choice between raster and vector.
Week 5:Spatial Query and Analysis – Types of spatial analysis
Week 6:Queries and reasoning, Measurements and Transformations and their application in spatial science.
Week 7:Lab Work SIS functional capabilities Data capture, Data storage
Week 8:Lab Work SIS functional capabilities Data structures, Data management,
Week 9:Lab Work SIS functional capabilities Data retrieval, Data analysis, Data display etc using open access GIS software.
Week 10:Project Module: SIS Project Design and Management: Problem identification, the rich picture, Designing a data model, Conceptual and physical data model, Cartographic modeling. Project Design – Objective, Database design, Database automation, Database management, Data analysis, Presentation of results.
Week 11:Project Module: SIS Project Design and Management: Conceptual and physical data model, Cartographic modeling. Project Design – Objective, Database design,
Week 12:Project Module: SIS Project Design and Management: Database automation, Database management, Data analysis, Presentation of results.
Week 2:Defining a map, types, space representation concepts, features and properties, Map projections, Georeferencing.
Week 3:Information organization and data structure, Data and information, Geographic data and spatial information. The relationship perspective of information organization.
Week 4:Fundamental concepts of data, Spatial – non spatial data, Database management system. Spatial data formats – raster and vector, Choice between raster and vector.
Week 5:Spatial Query and Analysis – Types of spatial analysis
Week 6:Queries and reasoning, Measurements and Transformations and their application in spatial science.
Week 7:Lab Work SIS functional capabilities Data capture, Data storage
Week 8:Lab Work SIS functional capabilities Data structures, Data management,
Week 9:Lab Work SIS functional capabilities Data retrieval, Data analysis, Data display etc using open access GIS software.
Week 10:Project Module: SIS Project Design and Management: Problem identification, the rich picture, Designing a data model, Conceptual and physical data model, Cartographic modeling. Project Design – Objective, Database design, Database automation, Database management, Data analysis, Presentation of results.
Week 11:Project Module: SIS Project Design and Management: Conceptual and physical data model, Cartographic modeling. Project Design – Objective, Database design,
Week 12:Project Module: SIS Project Design and Management: Database automation, Database management, Data analysis, Presentation of results.
Taught by
Prof. Shahab Fazal, Prof. Saleha Jamal
