The M.Tech. in Geoinformatics prepares students to harness geospatial technologies for understanding, monitoring, and managing the Earth’s dynamic systems. The programme combines Geographic Information Systems (GIS), Remote Sensing, Earth Observation, spatial analytics, and geospatial data science with emerging technologies such as Artificial Intelligence, machine learning, cloud computing, and advanced visualization techniques.
Students gain hands-on experience in satellite image processing, spatial modelling, geospatial databases, environmental monitoring, and decision-support systems using industry-standard tools and real-world datasets. Through research-driven learning and industry engagement, graduates develop the expertise required to address challenges in urban planning, environmental sustainability, disaster management, natural resource monitoring, agriculture, defence, and smart infrastructure development.
Eligibility Criteria
- B.Tech./B.E. equivalent in Civil Engineering / Computer Science / allied branches or M.Sc./M.Tech. or equivalent in Geology / Geophysics / Earth Sciences / allied branches or Master’s Degree in Geography with 10+2 in Science with an aggregate of 60%.
- Valid score in GATE , PGCET or any other state entrance exam.
Chanakya Edge / Highlights
- Strong foundation in GIS, Remote Sensing, Earth Observation, spatial analytics, geospatial databases, and geospatial data modelling.
- Curriculum aligned with emerging domains such as Geospatial AI, digital twins, satellite analytics, smart cities, climate modelling, and spatial decision-support systems.
- Limited memory-based assessments, with evaluation focused on geospatial analysis, satellite data interpretation, spatial modelling, and research-oriented projects.
- Hands-on learning through satellite image processing, GIS workflows, Earth observation analytics, field-based studies, and geospatial application development.
- Exposure to real-world datasets from satellite missions, Earth observation platforms, and geospatial information systems.
- Opportunities to work on interdisciplinary projects involving environmental monitoring, infrastructure planning, agriculture, disaster management, and spatial intelligence.
- Strong integration with Artificial Intelligence, Machine Learning, Computer Vision, Remote Sensing, and Earth Observation research.
- Access to High Performance Computing (HPC) resources supporting large-scale geospatial analysis and advanced modelling applications.
Credit Structure
Code | Course Type | Phased across Semesters | No. of Courses | Credits |
PC | Professional Core | I & II | 9 | 34 |
PE | Professional Elective | I & II | 4 | 12 |
PL | Professional Lab | I & II | 4 | 8 |
PW | Project Work and/or Internship | III & IV | – | 26 |
TOTAL | 14 or 15 | 80 | ||
Collaborations & Partnerships
IN-SPACe
- Professional workshops
- Deployment of Earth Observation payload
GalaxEye
- Radar Research Lab
- Earth Observation, Synthetic Aperture Radar (SAR), and advanced geospatial applications
These collaborations provide opportunities for research projects, industry mentorship, workshops, and exposure to emerging developments in Earth observation, remote sensing, geospatial intelligence, and space-based applications.