ArcGIS Pro (1.5 Months - Basic to Advanced)
Module 1: Introduction to GIS and ArcGIS Pro
1.1 What is GIS? (Concept, components, and applications)
1.2 The ArcGIS Pro Environment and Interface
1.3 Starting Your First Project (APRX Project Structure, folder management)
1.4 Geospatial Data Models (Vector, Raster, Attribute Data)
1.5 Basic Data Management (File Geodatabases, Catalog Pane)
Module 2: Spatial Referencing and Coordinate Systems
2.1 Understanding the Earth’s Coordinate System (Latitude, longitude, Datum)
2.2 Projections in ArcGIS Pro (Geographic vs. Projected CRS)
2.3 Working with Projections (Defining, Reprojecting data, BUTM/Custom CRS)
Module 3: Data Visualization and Symbology
3.1 Layer Symbology (Graduated colors, unique value maps, symbol styles)
3.2 Labeling Features and Arcade Expressions (Advanced labeling techniques)
3.3 Data Exploration and Querying (Attribute table, selection, Definition Queries)
3.4 Transparency and Blending Modes for Cartography (Using blending modes for advanced map design)
Module 4: Data Preparation and Digitizing
4.1 Georeferencing Raster Data (Control points, adjustment, saving)
4.2 Digitizing and Editing (Creating new features, editing tools, snapping)
4.3 Data Management in ArcGIS Pro (Importing, exporting, organizing datasets)
Module 5: Geoprocessing and Spatial Analysis
5.1 Introduction to Geoprocessing (Clip, Merge, Dissolve, Buffer, Intersect)
5.2 Table Operations and Joins (Attribute joins and spatial joins, field calculation)
5.3 Spatial Queries and Selections (Select by location, Extract by mask)
5.4 Zonal and Raster-Based Analysis (Zonal statistics, Raster Calculator basics)
Module 6: Remote Sensing and LULC Analysis
6.1 Introduction to Remote Sensing (Satellite imagery and spectral bands)
6.2 Spectral Indices (NDVI, MNDWI, NDBI, SAVI, SMI, NDMI etc. calculation using Raster Functions)
6.3 Land Use / Land Cover (LULC) Classification (Supervised and Unsupervised Classification)
6.4 Accuracy Assessment and Validation
Module 7: Advanced Spatial Analysis and Modeling
7.1 Hydrology and Terrain Analysis (DEMs, Slope, Aspect, Watershed delineation)
7.2 Multi-Criteria Overlay Analysis
7.3 Interpolation and Surface Analysis
Module 8: Map Layout and Presentation
8.1 Map Layout Preparation (Creating layouts, inserting map frames)
8.2 Map Design and Exporting (Title, legend, scale bar, high-resolution formats)
8.3 Map Series Creation (Automating the production of multiple maps)
Module 9: Project and Reporting
9.1 Project Report Preparation (Interpreting analysis results, writing reports)
9.2 Final Project Work (Guided project completion)
Module 10: Career and Professional Development
10.1 Portfolio Building (Organizing project files and creating presentation-ready maps)
10.2 GIS Career Pathways (Job types, tips for thesis and research writing)
Module 11: 20 Guided Projects (Video lecture)
10.1 Urban and Regional Planning
Project 1: Urban Planning and Climate Analysis.
Project 2: Civil Engineering Project.
10.2 Land Use and Environmental Management
Project 3: Land Use and Land Cover Mapping.
Project 4: Environmental Planning and Management Project.
Project 5: Mapping of afforestation and Deforestation.
Project 6: Change detection Project.
Project 7: Forest Fragmentation Project.
Project 8: Prediction Map
10.3 Water and Hydrology
Project 9: Water Resources / Hydrology Project.
Project 10: Ground Water Studies Project.
Project 11: River Morphology and Erosion Analysis.
10.4 Infrastructure and Disaster
Project 12: Transport Planning Project.
Project 13: Disaster Science and management Project.
10.5 Pollution and Health
Project 14: Air Pollution Project.
Project 15: Water Pollution Project.
Project 16: Soil based Project.
Project 17: Public Health Project.
10.6 Advanced Thematic Projects
Project 18: Social Science Project etc.
Google Earth Engine (1.5 Months - Basic to Advanced)
Module 1: Introduction to Google Earth Engine
Introduction to Remote Sensing: A brief overview of remote sensing principles.
Introduction to Earth Engine: What is GEE? Its capabilities and applications.
Setting Up the Environment:
Creating a GEE account.
Introduction to the GEE Code Editor.
Setting up the JavaScript APIs.
Client vs. Server Objects:
Understanding the client-server architecture in GEE.
How the server executes your code.
Data Management & Import:
Importing raster and vector data from GEE datasets.
Uploading and importing data from local storage.
Google Earth Pro:
Location Extraction and study area definition.
Creating points, lines, and polygons.
Exporting and importing data between platforms.
Module 2: Working with Images & Collections
Working with Image & Feature Collections:
Filtering and displaying images from collections (e.g., Landsat, Sentinel, MODIS).
Image Processing:
Creating composites and annual image composites.
Band combinations for visualization and analysis.
Data Export:
Exporting raster data (e.g., satellite imagery).
Exporting vector data (e.g., shapefiles).
Module 3: Raster Data Analysis & Basic Workflows
Calculating Indices:
Normalized Difference Vegetation Index NDVI, NDBI, MNDWI, SAVI, and others.
Image Pre-processing:
How to remove cloud and haze from satellite imagery (Landsat, Sentinel).
Workflow Operations:
Import, filter, reduce, clip, and display raster data.
Module 4: Advanced Data Visualization & Statistics
Time-series Charts:
Creating monthly and annual time-series charts for various indices (e.g., NDVI, NDWI).
Calculating Statistics:
Calculating average, maximum, and minimum values in a specific region.
Extracting pixel values at specific geolocations.
Module 5: Land Use Land Cover (LULC) Analysis
LULC Classification:
Creating LULC maps using supervised classification.
Using Random Forest classifiers.
LULC using unsupervised algorithms (MODIS).
Improving Classification:
Hyperparameter tuning for improving model accuracy.
Accuracy Assessment:
Checking LULC accuracy (Kappa, Producer’s & Consumer’s accuracy).
Post-processing & Visualization:
Calculating area for each LULC class.
Exporting LULC maps for use in Research papers (e.g., with ArcGIS Pro).
Module 6: Environmental Monitoring
Land Surface Temperature (LST):
Calculating LST using Landsat and MODIS data.
Monitoring the Urban Heat Island (UHI).
Monitoring UFTVI (Urban Thermal Field Variance Index).
Air Quality Monitoring:
Calculating key parameters (CO, NO2, SO2, CH4, AOD, PM2.5).
Creating Density Maps.
Soil Moisture:
Calculating Soil Moisture Index, Profile Soil Moisture.
Calculating average Profile Soil Moisture, Root-zone Soil Moisture in GEE.
Module 7: Digital Elevation Model (DEM) Analysis
Introduction to DEMs: Understanding Digital Elevation Models.
DEM Visualization:
Creating hillshade, aspect and slope maps using NASA SRTM datasets.
Exporting DEM Products:
Exporting the generated maps for further use.
Module 8: Change Detection
Introduction to Change Detection: Principles of change detection analysis.
NDVI & LULC Change Detection:
NDVI change detection.
Class-wise LULC change detection.
Specific Applications:
Extracting dense vegetation using thresholding techniques.
Monitoring urban development and growth.
Calculating the area of LULC transitions.
Flood Mapping:
Flood mapping using Sentinel-1 SAR imagery.
Module 9: Guided Projects (Video Lecture)
Project 1: Prediction Mapping
Project 2: Forest Cover and Loss Estimation
Project 3: Change Detection (NDVI / LULC)
Project 4: Mangrove Forest Fragmentation Analysis
Project 5: Flood Mapping
Project 6: Land Surface Temperature
Project 7: Urban Heat Island Monitoring
Project 8: Monitoring Gold Mining Activity
Project 9: Identifying Land Use / Land Cover
Project 10: Groundwater Monitoring
Project 11: Surface Water Mapping
Project 12: Active Fire Monitoring
Project 13: Salinity via Remote Sensing
Project 14: Night-time Light Statistics
Project 15: Drought Monitoring using Different RS Indices
Project 16: Time-Series Analysis
Project 17: Monitoring Urban Development and Growth
Project 18: Terrain Analysis (DEM, Slope, Aspect, Hillshade)
Project 19: Monitoring Soil Moisture and Average Soil Profile
Project 20: Air Quality Monitoring (PM2.5, CO, NO2, SO2, CH4, Aerosol Index, Formaldehyde)
Project 21: Calculating Rainfall Deviation
QGIS (1.5 Months - Basic to Advanced)
Module 1: Introduction to GIS and QGIS Interface
Understanding GIS concepts, coordinate systems, and projections.
Navigating the QGIS interface (Toolbars, Panels, Map Canvas).
Installing plugins and managing core settings.
Module 2: Data Acquisition and Management
Working with Vector data (Shapefiles, GeoPackage) and Raster data (GeoTIFF, DEM).
Integrating XYZ tiles (Google Maps, OpenStreetMap).
Managing data sources and QGIS Browser panel.
Module 3: Coordinate Reference Systems (CRS) and Georeferencing
Deep dive into CRS, EPSG codes, and on-the-fly reprojection.
Georeferencing scanned maps and historical images using Control Points.
Module 4: Vector Data Editing and Attribute Management
Digitizing features (points, lines, polygons).
Attribute table management: Adding fields, calculating geometry, and field calculator expressions.
Joining external tables (CSV/Excel) to spatial data.
Module 5: Spatial Data Analysis (Vector)
Geoprocessing tools: Buffer, Clip, Intersection, Union, and Dissolve.
Performing spatial joins and selecting by location.
Module 6: Raster Analysis and Terrain Modeling
Working with Digital Elevation Models (DEM).
Deriving terrain products: Slope, Aspect, Hillshade, and Contours.
Raster Calculator for band math and index calculation.
Module 7: Advanced Visualization and Cartography
Thematic mapping (Graduated, Categorized, Rule-based symbology).
Using the Print Layout to create professional maps with scale bars, legends, and north arrows.
Exporting maps in various formats (PDF, PNG, SVG).
Module 8: Final Project and Automation
Integrating all modules into a mini-project (e.g., LULC mapping or suitability analysis).
Introduction to basic automation: Graphical Modeler.
Publishing data and next steps in advanced GIS/Remote Sensing.
Python for GIS (Free)
Module 1: Python Fundamentals for GIS
Introduction to Python and its role in GIS
Installing Anaconda & using Jupyter Notebook
Variables and Data Types (int, float, string, list)
Basic Operators
Input and Output
Simple hands-on practice exercises
Module 2: Control Structures & Functions
If–Else conditions
For Loop and While Loop
Basic problem-solving exercises
Creating and using Functions
Small GIS-related coding examples
Module 3: Working with Spatial Data (Introduction)
Review of Vector vs Raster data
Reading CSV files using Pandas
Working with coordinate data
Introduction to GeoJSON format
Basic attribute data filtering
Module 4: Essential Python Libraries for GIS
NumPy (basic array operations)
Pandas (data filtering and summarizing)
Creating simple charts using Matplotlib
Reading shapefiles using GeoPandas
Plotting a simple map
Module 5: Basic Spatial Analysis with Python
Attribute queries
Buffer concept (basic explanation with example)
Distance calculation using coordinates
Basic area calculation
Introduction to spatial join (concept + demo)
Module 6: Mini Project (Beginner–Intermediate Level)
Creating a map from CSV location data
Basic data cleaning
Attribute filtering
Generating a simple final map output
Organizing and exporting code
Portfolio Website Building
Several Video lectures will be provided for these topics!
Guideline for Jobs, Research & Freelancing
Several Video lectures will be provided for these topics!