Short-term course/Internship programme

for UG, PG, and Research scholars on

Remote Sensing and Geographical Information System (RS-GIS 2025)

Objectives 

Objective of the programme: The Centre of Remote Sensing and Disaster Management (CRS- DM), School of Civil Engineering, KIIT Deemed to be University aims to provide participants with a comprehensive understanding of the fundamentals of Remote Sensing and Geoinformatics, including data acquisition, processing, analysis, and visualization through one- month training programme to students via online mode.

Overview

Unlock the power of Remote Sensing and GIS with our intensive short-term course! Dive into the world of satellite imaging, spatial analysis, and GIS, and discover how to harness these cutting-edge technologies to solve real-world problems. From environmental monitoring to urban planning, our course will equip you with the skills and knowledge to excel in this rapidly growing field. With hands-on training and expert instruction, you’ll gain a competitive edge in the job market and open doors to exciting career opportunities. Students will learn the principles and applications of remote sensing and GIS, including data acquisition, processing, analysis, and visualization.

Who can attend

UG and PG students of KIIT, other institutions, Scientists, Researchers, Urban planners, natural resource managers, environmental Monitoring expert etc.

Duration

30 Days for Summer Research Internship for UG/PG / Research Scholars

Course Fees

Course fee for students is Rs.4000/-

Batch Size

Minimum – 30

Certification

KIIT Certification

Resource Person

  1. Faculty form KIIT/Other Renowned Institute
  2. Industry Expert

Mode of Teaching

The training programme will be carried out in online mode by using any platform. To attend this class the following is needed:

  • Uninterrupted high speed internet connection
  • Laptop/desktop
  • Free software resources

 

Tentative Content of Programme

Day Topics
Day 1 Introduction to Remote Sensing, Basics of remote sensing, Types of satellite imagery
Day 2 Introduction to GIS, Fundamentals of GIS, Spatial data types
Day 3 Data Visualization, Creating maps and, visualizations
Day 4 Remote Sensing Data Basics, Understanding satellite data, Image display and enhancement
Day 5 GIS Data Basics, Understanding vector and raster data
Remote Sensing and DIP (Days 6-10)
Day 6 Satellite Imagery Interpretation, Understanding image characteristics, Visual interpretation
Day 7 Image Enhancement, Techniques
Day 8 Band Combinations and Indices Understanding band combinations Calculation of Different Indices (NDVI/NDWI/NDBI etc.)
Day 9 Change Detection Basics Identifying changes in images
Day 10 Image Classification Basics Supervised and unsupervised classification
GIS Fundamentals (Days 11-15)
Day 11 Vector Data Analysis Buffering and overlay analysis Vector data Digitization and editing and removal of error Encoding Attribute data and Joining process
Day 12 Input Excel data in Arc –GIS (GPS point) DEM Modelling Hydrological Analysis using DEM data
Day 13 Interpolation method IDW, Krigging etc. Fishnet creation KML to Shapefile creation
Day 14 Spatial Data Editing Editing vector data
Day 15 GIS Data Integration and Project Development Integrating different data sources Individual Project Development
Google Earth Engine (GEE) Applications
Day 16 Introduction to GEE and JavaScript Essentials Introduction to Google Earth Engine Fundamentals of Remote Sensing, Complete Guide to JavaScript for Earth Engine
Day 17 Image and Feature Collection Handling Filtering and Accessing Image Collections Creating Mosaics and Composites Importing Raster and Vector Data
Image Clipping Techniques Working with Feature Collections
Day 18 Image Analysis and Time-Series Processing Understanding Earth Engine Objects Calculating Remote Sensing Indices (NDVI, NDWI, NDBI, BI, EMBI, etc.)
Performing Computations on Image Collections (e.g., Area, Date) Using Reducers for Data Aggregation Generating NDVI Time-Series Charts
Day 19 Visualization and Exporting Cloud Masking Techniques Visualizing Terrain Data (Elevation, Hill shade, Slope using NASA SRTM) Designing Map Layouts (Adding Legends, Titles) Exporting Data and Maps from Earth Engine
Day 20 Image Classification and Accuracy Assessment Unsupervised Raster Classification Basic Supervised Classification Introduction to Machine Learning in Earth Engine Land Use and Land Cover (LULC) Mapping Performing Accuracy Assessment Enhancing Classification Results Exporting Classified Maps Area Calculation of Classified Outputs
Final Project and Certification (Days 21-25)
Day 21
Day 22
Day 23
Day 24
Day 25 Final Project and Certification

Hands on training will be provided through Arc-Map, ERDAS Imagine
Target Audience

  • Students and professionals in the field of remote sensing and geo-spatial science

  • Researchers and scientists

  • Urban planners, natural resource managers, and environmental monitoring
    professionals

Prerequisites

  • Basic knowledge of geography, computer science, and statistics
  • Familiarity with Remote Sensing and Geoinformatics concepts and software

Course Outcomes

  • Understand the principles and applications of remote sensing and geo-spatial science
  • Develop skills in spatial analysis and visualization
  • Apply remote sensing and geo-spatial science to real-world problems
  • Enhance career opportunities in remote sensing and geo-spatial science

 

Course Coordinator

Dr. Rakesh Ranjan Thakur

Professor (Assistant-II), SCE, KIIT, DU
Email : rakesh.thakurfce@kiit.ac.in