🔹 Module 1: Introduction to Geospatial Technologies

• Concept & evolution of GIS and Remote Sensing
• Application domains: Agriculture, Forestry, Water, Disaster, Urban Planning
• Core components of GIS: Hardware, Software, Data, People, Methods
• Data types and formats: Vector, Raster, Tabular

🔹 Module 2: Coordinate Systems & Data Models

• Datum, projections, coordinate reference systems (WGS84, UTM)
• Understanding file formats: SHP, GeoJSON, KML, TIF, CSV
• Coordinate transformation and reprojection for agricultural mapping

🔹 Module 3: Data Acquisition & Sources

• Field survey data collection using GPS/DGPS/RTK
• Satellite datasets for agriculture (Sentinel-2, Landsat, MODIS, Bhuvan)
• Open data portals: USGS Earth Explorer, FAO GeoNetwork, NRSC Bhuvan
• Integration of KML and CSV data into GIS projects

🔹 Module 4: Georeferencing & Base Mapping

• Aligning cadastral and topographic maps
• Setting up coordinate systems and control points
• Accuracy checks for agricultural boundary mapping

🔹 Module 5: Spatial Data Digitization & Editing

• Manual digitization of agricultural plots, irrigation canals, and soil types
• Attribute table creation and management
• Topological corrections and editing tools in QGIS/ArcGIS

🔹 Module 6: Cartography & Map Layout Design

• Map design principles for agriculture-based themes
• Map elements: Title, Legend, North Arrow, Scale Bar
• Exporting high-quality maps for reports and presentations

🔹 Module 7: Thematic & Analytical Mapping

• Soil type, crop type, and irrigation mapping
• NDVI, NDWI, and LSWI index generation and analysis
• Buffer and proximity analysis for resource distribution
• Change detection in crop cover and agricultural expansion

🔹 Module 8: Fundamentals of Remote Sensing

• Electromagnetic spectrum and spectral reflectance of crops
• Satellite sensors and agricultural applications (Landsat, Sentinel, PlanetScope)
• Passive vs Active sensors (SAR for soil moisture monitoring)
• Resolution concepts: spatial, temporal, spectral