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This B.A./B.Sc. (Honours) course in Spatial Information Technology
provides a comprehensive introduction to the theory, principles, and
applications of spatial data handling, analysis, and visualization. The
course begins with the fundamentals of spatial information, its historical
development, and the core components of Spatial Information Technology (SIT)
and Geographic Information Systems (GIS). Students will explore the role of
SIT in decision-making and critically evaluate its benefits and limitations.
The curriculum delves into the nature of geospatial data, including its
types, sources, and structures, emphasizing the importance of coordinate
systems, projections, and data transformation. Students will gain practical
skills in data registration, error assessment, and interpolation techniques.
The course covers data modeling concepts, thematic mapping, and database
management, including creation, query, and retrieval. A significant portion of the course is dedicated to spatial analysis
techniques such as map layering, overlay analysis, digitization, and network
analysis. Students will also learn about data output and visualization
methods, data standards, and metadata management. The integration of remote
sensing with GIS is explored, providing students with a holistic
understanding of geospatial technologies. Practical skills are developed through hands-on sessions focusing on
GIS software (QGIS), topological modeling, and automation and scripting. The
course culminates in examining the diverse applications of SIT in urban
planning, environmental monitoring, agriculture, transportation, public
health, disaster management, e-governance, and utility services. Emerging
trends in spatial information technology, including AI, ML, IoT, and WebGIS,
along with ethical considerations, are also addressed. This course equips students with the essential knowledge and skills to
effectively manage, analyze, and apply spatial information technology in
various professional and research domains. |
| Course Status : | Upcoming |
| Course Type : | Core |
| Language for course content : | English |
| Duration : | 16 weeks |
| Category : |
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| Credit Points : | 5 |
| Level : | Undergraduate |
| Start Date : | 05 Jan 2026 |
| End Date : | 26 Apr 2026 |
| Enrollment Ends : | 28 Feb 2026 |
| Exam Date : | |
| Translation Languages : | English |
| NCrF Level : | 4.5 |
Lecture 1: Concept and Definition of Spatial Information
Lecture 2: Historical Development of SIT
Lecture 3: Components of SIT
Lecture 4: Role of SIT in Decision Making
Lecture 5: Benefits and Limitations
Lecture 6: Spatial vs. Aspatial Technologies
Lecture 7: GIS as a Multidisciplinary Tool
Lecture 8: Overview of GIS Software
Lecture 9: Understanding Geospatial Data
Lecture 10: Types of Spatial Data
Lecture 11: Overview and Process of Remote Sensing
Lecture 12: Remote Sensing platform and sensor
Lecture 13: Global Positioning Systems
Lecture 14: Data Structures in GIS
Lecture 15: Web-based Spatial Data Sources
Lecture 16: Coordinate Systems and Projections
Lecture 17: Data Registration and Transformation
Lecture 18: Sources of Errors in Spatial Data
Lecture 19: Interpolation Techniques
Lecture 20: Data Modelling Concepts
Lecture 21: Thematic Mapping and Classification
Lecture 22: Database Concepts
Lecture 23: Database Creation
Lecture 24: Query and Data Retrieval
Lecture 25: Map Layering and Overlay
Lecture 26: Digitization and Map Input
Lecture 27: Data Output and Visualization
Lecture 28: Data Standards and Metadata
Lecture 29: Image analysis and interpretation
Lecture 30: Remote Sensing Integration
Lecture 31: Hands-on: GIS Software Basics
Lecture 32: Information Retrieval
Lecture 33: Topological Modeling
Lecture 34: Spatial Network Analysis
Lecture 35: Overlay Analysis
Lecture 36: Spatial Interpolation and Surface Analysis
Lecture 37: Data Output Formats and Layout
Lecture 38: Automation and Scripting Part I
Lecture 39: Automation and Scripting Part II
Lecture 40: Data Sharing and Interoperability
Lecture 41: Spatial Statistics
Lecture 42: Urban Planning and Infrastructure
Lecture 43: Environmental Monitoring
Lecture 44: Agriculture and Land Use
Lecture 45: Transportation and Logistics
Lecture 46: Public Health and Epidemiology
Lecture 47: Climate and Disaster Applications
Lecture 48: E-Governance and Utility Services
Lecture 49: Recent Trends in Spatial Information Technology
Lecture 50: Role of spatial technology for decision support
Lecture 51: Land Use/Land Cover (LULC) Analysis
Lecture 52: Environmental Monitoring - AQI Mapping
Lecture 53: Change Detection in Vegetation Cover
Lecture 54: Transport Optimization GIS Modelling
Lecture 55: GIS Application in Public health
Lecture 56: Multi-Hazard Risk Assessment
Burrough, P. A., & McDonnell, R. A. (1998). Principles of Geographical Information Systems. Oxford University Press.
Longley, P. A., Goodchild, M. F., Maguire, D. J., & Rhind, D. W. (2015). Geographic Information Systems and Science. Wiley.
Lillesand, T., Kiefer, R. W., & Chipman, J. (2019). Remote Sensing and Image Interpretation. John Wiley & Sons.
Heywood, I., Cornelius, S., & Carver, S. (2011). An Introduction to Geographical Information Systems. Pearson Education.
Tomlinson, R. F. (2019). Thinking About GIS: Geographic Information System Planning for Managers. ESRI Press.
NASA Earth Observatory – Remote Sensing Basics
USGS Earth Explorer – Download satellite imagery and geospatial data.
Esri GIS Fundamentals – Overview of GIS concepts and applications.
National Remote Sensing Centre (NRSC), India – Indian resource for remote sensing and satellite data.
OpenStreetMap – Collaborative mapping platform offering free spatial data.
Dr. Nileshkumar P. Chaudhari is
a seasoned academician with 10 years of teaching experience in subjects related
to Geography Subject. He holds a Ph.D. and an GSET in his field of expertise. His
professional development includes participation in over one FIP, four
International and National Conference and one Faculty Development Programs on
Geospatial Technology and three paper presented. showcasing her commitment to
continual learning and excellence in education.
Dr. Nileshkumar P. Chaudhari has also made significant contributions to academic literature, having published six research papers in UGC CARE-listed and Peer-review journals and five Books with ISBN No on geography subject. Beyond academia, he actively engages in motivational speaking, delivering impactful sessions aimed at inspiring and empowering his audience.
His blend of scholarly achievements and motivational prowess makes her a distinguished figure in her domain.
Course Certificate
·
Weightage: 70% of the final result
·
Minimum Passing Criteria: 40%
2. Internal
Assessment:
·
Weightage: 30% of the final result
·
Minimum Passing Criteria: 40%
Calculation of IA Marks:
Out of all graded weekly assessments/assignments, the top
50% of assignments shall be considered for the calculation of the final
Internal Assessment marks.
All students who obtain 40% marks in the internal assessment
and 40% marks in the end-term proctored exam separately will be eligible for
the SWAYAM Credit Certificate.
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