Table of Contents

1. Introduction to Geospatial Technology

   • Overview of GIS, remote sensing, and their applications

   • Historical development and evolution of geospatial technology

   • Principles of spatial data, coordinate systems, and map projections

   • Types of spatial data (vector and raster) and data models

2. GIS Software and Tools

• Introduction to GIS software

• Basics of GIS interface and functionality

3. Data Acquisition and Sources

• Data collection methods (GPS, remote sensing, surveys)

• Sources of geospatial data (open data, commercial sources)

4. Georeferencing

• Introduction

• Load Data

• Set Coordinate System

• Add Control Points

• Rectification

5. Digitization

• Introduction

• Shapefile and Geodatabase

• Vectorization: Point, line and polygon features

• File extensions in shapefile

• Editing and advanced editing tools

• Components in a shapefile

• Attribute table and data creation

6. Components of Map

• Map layouts

• Title

• Legend

• Scale and Cartographic Scale

• North Arrow/Compass Rose

• Grid Lines and Coordinates

• Borders and boundaries, geographic features

• Labels and Annotations

• Insets

• Grid reference, data sources and credits

7. Thematic Maps

• Choropleth Maps

• Proportional Symbol Maps

• Dot Density Maps

• Isopleth Maps

• Flow Maps

• Heat Maps

• Thematic Line Maps

• 3D Thematic Maps

8. Spatial Analysis in GIS

   • Proximity Analysis

   • Near Analysis

   • Spatial Join

   • Network Analysis

   • Interpolation

   • Density Analysis

   • Hotspot Analysis

9. Data Transformation and Conversion

• Vector to Raster

• Raster to Vector

• Coordinate System Transformation

• Merging and Splitting Data

• Attribute Data Transformation

• Data Extraction and Data Export

• Extraction of spatial data from excel sheets

• Conversion and editing of GPS data

10. Web Mapping

• Collection and Preparation of Geographic Data

• Web Map Libraries

• Base maps

• Overlay Layers

• Interactivity

• Geocoding and Search

• Data Sharing and Collaboration

11. Introduction to Remote Sensing

• Principles of remote sensing

• Electromagnetic spectrum and sensors.

• Types of remote sensing platforms (satellites, aerial photography).

12. Image Interpretation and Classification

• Visual interpretation of remotely sensed imagery.

• Image classification techniques (supervised and unsupervised)

• Normalized Difference Vegetation Index (NDVI)

• Normalized Difference Water Index (NDWI)

• Normalized Difference Built-up Index (NDBI)

• Land Surface Temperature (LST)

• Snow Cover Index

• Burnt Area Index

• Geological Indexes

13. Digital Image Processing

• Radiometric Correction

• Brightness and Contrast Adjustment

• Histogram Equalization

• Dynamic Range Adjustment

• Geometric Transformation

• Image Registration

• Orthorectification

• Noise Reduction

• Pan-sharpening

14. Terrain Analysis

• Introduction

• Digital Elevation Model (DEM)

• Contour Mapping

• Slope Analysis

• Aspect Analysis

• Visibility Analysis

• Terrain Change Detection

• Terrain Classification

• Geological Transformation Analysis

• Line of Sight Analysis

• Terrain Profile and Cross-Section Analysis

• Terrain-based Suitability Analysis

15. Advanced Spatial Analysis

• Hot spot analysis

• Cluster analysis

• Spatial interpolation techniques

16. Hydrology Analysis

• Introduction

• Importance of Hydrology in water resource management and environmental studies

• Implementation of tools for watershed management

• Watershed concept and characteristics

• Types of watersheds

• GIS Data Sources and Data Acquisition

• Topographic Data Processing

• Flow Accumulation

• Flow Direction

• Stream Network Analysis

• Watershed delineation

• Morphometric Analysis

• Flood Risk Assessment using GIS Tools

• Predictive Modeling

17. 3D Visualization and Analysis

• 3D modeling

• Terrain visualization

• Viewshed analysis

• 3D interpolation

18. Time Series Analysis

• Time-series data handling and analysis

• Change detection over time

• Trend analysis

• Seasonal decomposition

19. Remote Sensing Applications

• Environmental monitoring

• Land cover classification and change detection

• Remote sensing in agriculture

• Forestry and urban planning

20. LiDAR Data Processing

• Introduction to LiDAR data

• LiDAR data acquisition methods

• LiDAR point cloud processing

• Digital Surface Model (DSM) generation

• Digital Terrain Model (DTM) generation

• LiDAR-based feature extraction

21. Python Programming

• Introduction to Python

• Python as a programming language

• Setting up a Python development environment

22. Basic Python Concepts

• Variables, data types, and operators

• Control structures (if statements, loops)

• Functions and libraries

23. Working with Geospatial Data in Python

• Introduction to geospatial libraries

• Reading and writing geospatial data formats

24. Geospatial Visualization in Python

• Accessing and manipulating geospatial data with Python

• Creating maps and plots using Python libraries

25. Specialized Applications

• Hydrological modeling and analysis

• Environmental impact assessment

• Disaster management and emergency response

• Agricultural monitoring and precision farming

• Public health GIS

26. Project Work

• Define Project Objectives

• Select Topic and Geographic Area

• Data Collection and Preparation

• Project Design and Workflow

• Spatial Analysis

• Analysis Results and Interpretation

• Documentation and Submission

CAREER OPPORTUNITIES

GIS Analyst | GIS Engineer | GIS Project Manager | GIS Technician | GIS Associate | GIS Consultant | GIS Specialist