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M-SC in Geographical Information System Gis at University of Mysore
Mysuru, Karnataka
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About the Specialization
What is Geographical Information System (GIS) at University of Mysore Mysuru?
This Geographical Information System (GIS) program at the University of Mysore focuses on equipping students with advanced skills in geospatial technologies. It addresses the growing demand for spatial analysis and data management across various Indian industries, including urban planning, environmental management, and disaster response. The program emphasizes practical application and theoretical knowledge essential for navigating complex spatial challenges.
Who Should Apply?
This program is ideal for graduates in Science, Engineering, or Computer Applications seeking entry into the rapidly expanding geospatial domain. It also caters to working professionals in fields like urban development, agriculture, or environmental science who wish to upskill in spatial data analysis, and career changers aiming to transition into the technology-driven GIS industry.
Why Choose This Course?
Graduates of this program can expect diverse career paths in India as GIS Analysts, Remote Sensing Specialists, Urban Planners, Data Scientists, or Project Managers. Entry-level salaries typically range from INR 3-6 LPA, growing significantly with experience. The skills acquired align with certifications in Esri, QGIS, and other industry-standard platforms, fostering strong growth trajectories in Indian IT and consulting firms.
Student Success Practices
Foundation Stage
Master GIS and Remote Sensing Fundamentals- (Semester 1-2)
Dedicate time to thoroughly understand the core concepts of Cartography, GIS, and Remote Sensing. Practice extensively with open-source software like QGIS and GRASS GIS, along with proprietary tools if available, to solidify theoretical knowledge with practical skills. Focus on data acquisition, projection systems, and basic spatial analysis.
Tools & Resources
QGIS Tutorials, Esri Academy (free courses), NPTEL lectures on GIS/RS, Online datasets for practice
Career Connection
A strong foundation is critical for all entry-level GIS roles, enabling quick adaptation to diverse projects and tools required by employers.
Develop Python Programming Skills for Geospatial- (Semester 1-2)
Build a solid foundation in Python programming, specifically focusing on libraries relevant to geospatial analysis like GeoPandas, Rasterio, Shapely, and Folium. Work on small projects to automate mapping tasks, data cleaning, and spatial operations. Participate in coding challenges on platforms like HackerRank or LeetCode.
Tools & Resources
Python documentation, GeoPandas documentation, Automate the Boring Stuff with Python, GeeksforGeeks for coding practice
Career Connection
Proficiency in Python is highly valued in advanced GIS and Geo-data science roles, offering a competitive edge for jobs in analytics and development.
Engage in Peer Learning and Academic Groups- (Semester 1-2)
Form study groups with classmates to discuss complex topics, share insights, and collaborate on assignments. Actively participate in departmental seminars, workshops, and guest lectures. This fosters a deeper understanding of the curriculum and exposes students to current industry trends and research.
Tools & Resources
Departmental seminars, Student clubs, Online forums like Stack Exchange GIS
Career Connection
Networking and collaborative skills are essential for team-based projects in professional environments. Peer learning enhances problem-solving abilities and communication.
Intermediate Stage
Undertake Mini-Projects and Internships- (Semester 3)
Seek out mini-projects within the department or external internships with GIS consultancies, government bodies (e.g., state remote sensing applications centres), or NGOs. Focus on applying advanced topics like spatial databases, web GIS, or advanced remote sensing to real-world problems. Document all project work thoroughly.
Tools & Resources
Internshala, LinkedIn, University placement cell for opportunities
Career Connection
Practical experience through internships is invaluable for placements, demonstrating direct applicability of skills to potential employers and building a professional network.
Specialize in a Niche Area and Build a Portfolio- (Semester 3)
Identify a specific area of interest within GIS, such as Urban GIS, Environmental GIS, Disaster Management, or Machine Learning for GIS. Dive deeper into this area through elective courses, certifications, and self-learning. Create a digital portfolio showcasing projects, analyses, and visualizations.
Tools & Resources
Specialized online courses (Coursera, Udemy), GitHub for project showcasing, Personal website/blog
Career Connection
A specialized portfolio highlights expertise and passion, making you a more attractive candidate for targeted roles and advanced positions in your chosen niche.
Participate in Geospatial Competitions & Hackathons- (Semester 3)
Actively participate in GIS-focused hackathons, data challenges, and academic competitions organized by institutions or industry bodies. This provides opportunities to work under pressure, innovate, and network with professionals and peers. It also enhances problem-solving and critical thinking skills.
Tools & Resources
Kaggle, Devfolio, Industry-specific hackathons announced by Esri, ISRO
Career Connection
Winning or even participating in such events demonstrates initiative, practical skill application, and resilience, which are highly valued by employers for roles requiring innovative solutions.
Advanced Stage
Focus on Dissertation Research and Publication- (Semester 4)
Approach your Project Dissertation with a strong research mindset. Aim to contribute original work or solve a significant problem using GIS. Consider presenting your findings at conferences or publishing in relevant journals, even if it’s a local conference. This refines research and presentation skills.
Tools & Resources
University library resources, Scopus/Web of Science for journal search, Mentorship from faculty
Career Connection
A well-executed dissertation, potentially leading to publication, significantly boosts your profile for R&D roles, academic positions, or advanced technical roles requiring independent research capabilities.
Intensive Placement Preparation- (Semester 4)
Engage in rigorous preparation for campus placements. This includes mock interviews, aptitude test practice, resume building workshops, and perfecting presentation skills. Tailor your resume and interview answers to highlight your GIS project work, technical skills, and problem-solving abilities relevant to potential employers.
Tools & Resources
University placement cell services, Online aptitude platforms, LinkedIn for company research
Career Connection
Effective preparation is crucial for securing desired job offers. A polished resume and confident interview performance can make the difference in competitive placements.
Network with Industry Professionals and Alumni- (Semester 4)
Actively connect with GIS professionals, alumni, and industry leaders through LinkedIn, professional events, and university networking sessions. informational interviews can provide insights into career paths and job market trends. Building a robust network can open doors to opportunities beyond formal placements.
Tools & Resources
LinkedIn, Alumni association events, Professional conferences like FOSS4G India
Career Connection
A strong professional network is invaluable for long-term career growth, mentorship, and discovering hidden job opportunities in the dynamic geospatial industry.
Program Structure and Curriculum
Eligibility:
- B.Sc. degree in Geography / Geology / Computer Science / Statistics / Physics / Environmental Science / Electronics / Mathematics / Information Science / Computer Application / B.C.A. / B.E. / B.Tech. with minimum 45% marks in aggregate (40% for SC/ST/Cat-I candidates) from any recognized University or any other equivalent examination recognized by the University of Mysore.
Duration: 4 semesters / 2 years
Credits: 92 Credits
Assessment: Internal: 40%, External: 60%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| PGGIS101 | Cartography and Map Reading | Core (Hard Core) | 4 | History of Cartography, Map Scales and Projections, Topographical Maps and Interpretation, Remote Sensing and GPS Fundamentals, Thematic Mapping Techniques |
| PGGIS102 | Fundamentals of Remote Sensing | Core (Hard Core) | 4 | Electromagnetic Radiation Principles, Remote Sensing Platforms and Sensors, Image Acquisition and Resolution, Visual Image Interpretation, Digital Image Processing Basics |
| PGGIS103 | Introduction to GIS | Core (Hard Core) | 4 | GIS Components and Functions, Spatial Data Models (Raster and Vector), Georeferencing and Data Input, Spatial Data Analysis Techniques, GIS Applications and Case Studies |
| PGGIS104 | Programming in Python for GIS | Core (Hard Core) | 4 | Python Language Fundamentals, Data Structures and Control Flow, Functions, Modules, and Libraries, File Handling and Data Input/Output, Introduction to Python for Geospatial Analysis |
| PGGIS105 | Fundamentals of GPS & GNSS | Elective (Soft Core) | 4 | GPS System Segments, Satellite Signal Structure and Measurements, GPS Positioning Modes, Sources of Errors in GPS, Introduction to GNSS and Applications |
| PGGIS106 | Introduction to Spatial Data Science | Elective (Open Elective) | 4 | Spatial Data Concepts and Types, Exploratory Spatial Data Analysis, Spatial Statistics Basics, Machine Learning for Spatial Data, Geo-visualization Techniques |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| PGGIS201 | Advanced Remote Sensing | Core (Hard Core) | 4 | Hyperspectral Remote Sensing, Radar and Lidar Technology, Thermal Remote Sensing, UAV-based Remote Sensing, Advanced Digital Image Processing |
| PGGIS202 | Spatial Database Management Systems | Core (Hard Core) | 4 | Database Management Concepts, Relational Database Management Systems (RDBMS), SQL for Spatial Data, Spatial Databases (e.g., PostGIS), Geodatabases and Data Integration |
| PGGIS203 | Geo-statistics | Core (Hard Core) | 4 | Spatial Autocorrelation, Variography and Semivariograms, Kriging and Spatial Interpolation, Spatial Sampling Designs, Application of Geostatistics in GIS |
| PGGIS204 | Web GIS | Core (Hard Core) | 4 | Web Mapping Technologies, Geospatial Web Services (WMS, WFS), Open Source Web GIS Frameworks (OpenLayers, Leaflet), Map Servers (GeoServer), Cloud-based GIS Platforms |
| PGGIS205 | Application of GIS in Urban Planning | Elective (Soft Core) | 4 | Urban Data Models and Management, Land Use and Land Cover Mapping, Site Suitability Analysis, Urban Infrastructure Management, GIS for Smart City Initiatives |
| PGGIS206 | Fundamentals of Drone Technology | Elective (Open Elective) | 4 | Types and Components of Drones (UAVs), Drone Operation and Regulations, Data Acquisition using Drones, Photogrammetry and Data Processing, Applications of Drone Technology in GIS |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| PGGIS301 | Disaster Management & GIS | Core (Hard Core) | 4 | Disaster Cycle and Risk Assessment, GIS for Hazard Mapping and Vulnerability Analysis, Early Warning Systems using GIS, Emergency Response and Management, Post-Disaster Assessment and Recovery |
| PGGIS302 | Machine Learning for GIS | Core (Hard Core) | 4 | Introduction to Machine Learning Algorithms, Supervised and Unsupervised Learning, Deep Learning Concepts for Geospatial Data, Image Classification and Object Detection, Spatial Prediction and Pattern Recognition |
| PGGIS303 | Project Dissertation – I | Core (Hard Core) | 4 | Research Problem Identification, Literature Review and Hypothesis Formulation, Methodology Design and Data Collection, Preliminary Data Analysis, Project Proposal and Presentation |
| PGGIS304 | Advanced Algorithms in GIS | Elective (Soft Core) | 4 | Network Analysis Algorithms, Spatial Optimization and Location Allocation, Route Planning and Vehicle Routing Problems, Terrain Analysis and Hydrological Modeling, Geospatial Big Data Analytics |
| PGGIS305 | Fundamentals of Climate Change & Sustainability | Elective (Open Elective) | 4 | Climate Science and Global Warming, Impacts of Climate Change, Climate Change Mitigation and Adaptation, Carbon Footprint and GHG Inventory, Sustainable Development Goals (SDGs) |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| PGGIS401 | Research Methodology | Core (Hard Core) | 4 | Defining Research Problem and Objectives, Research Design and Methods, Data Collection and Sampling Techniques, Statistical Analysis for Research, Scientific Report Writing and Ethics |
| PGGIS402 | Project Dissertation – II | Core (Hard Core) | 4 | Advanced Data Analysis and Interpretation, Results and Discussion, Thesis Writing and Documentation, Oral Presentation and Defense, Scientific Publication Principles |
| PGGIS403 | Remote Sensing in Agriculture | Elective (Soft Core) | 4 | Crop Monitoring and Health Assessment, Yield Prediction and Area Estimation, Soil Mapping and Fertility Analysis, Irrigation Management and Water Productivity, Precision Agriculture Applications |
| PGGIS404 | Urban and Regional Planning | Elective (Open Elective) | 4 | Theories of Urbanization and Planning, Regional Development Strategies, Master Plans and Zoning Regulations, Housing and Infrastructure Planning, Concepts of Smart Cities and Sustainable Urbanism |
