1. Remote Sensing and Digital Image Processing (Code: CUAS2020) (2-2-0) 45 Hours
1.1 Basic Concept of Remote Sensing (4+6) Hours
Introduction of Remote Sensing: Principles of RS and its Type; Energy sources and Radiation principles, Pixel, DN value, Energy equation; EMR and Spectrum; EMR interaction with Atmosphere; scattering, Absorption, Atmospheric window, Black body radiation; EMR interaction with earth surface features, reflection, absorption, emission and transmission, Spectral signature; Interaction with vegetation, soil, water bodies; Advantage of RS over conventional method, Limitation, Ideal remote sensing.
- Installation of Image Processing software’s
- Download satellite data from GLOVIS / Earth Explorer / Bhuvan etc.
- Layer stacking
- LUT and Image Subset
- Spectral Signature mapping (soil,vegetation,water)
1.2 Digital Image (2+3) Hours
Data acquisition: Procedure, Reflectance and Digital numbers; Intensity, Reference data, Ground truth, Analog to digital conversion, FCCs, TCC, Platforms and sensors; orbits ,types, Resolutions; Image Interpretation; visual- Interpretation keys.
- FCCs and TCC
- Image Interpretation
1.3 Satellite Information and Principles (2+3) Hours
Land observation satellites, characters and applications; PSLV, GSLV, Satellite, Platform Types; LANDSAT series; IRS series; IKONOS Series; QUICKBIRD series; Weather/Meteorological satellites; INSAT series, NOAA, Applications, Marine observation satellites; OCEANSAT
- Image filtering and Band ratioing
1.4 Image Acquisition and Format (2+4) Hours
Digital Image Processing; Export and import, Data formats; BSQ, BIL, BIP, Run length encoding, Image Compression Data products.
- Export and Import
- Subset using AOI
1.5 Image Processing (3+4) Hours
IMAGE RECTIFICATION; Preprocessing and Post processing Geometric distortion; sources and causes for distortion, rectification, GCP, Resampling, Image registration; Radiometric distortion; sources and causes, atmospheric correction
Practice: (Spectral Python and ENVI)
- Geometric correction
- Radiometric correction
- Atmospheric correction
1.6 Image Classification (4+4) Hours
IMAGE CLASSIFICATION; Classification techniques, types, Supervised and Un-supervised; Principal Component Analysis (PCA); Image Enhancement; Accuracy assessment.
- PCA analysis (spectral Python and ENVI)
- NDVI, DVI, NDWI calculation
- Image classification in Spectral angel Mapper
- MNF Ratoing
- Supervised Classification(spectral Python and ENVI)
- Un-supervised Classification(spectral Python and ENVI)
- Image Enhancement( ENVI)
- Accuracy Assessment(ENVI)
1.7 Remote Sensing and Its application (3+4) Hours
Microwave RS and its application; Thermal RS and its application; Optical RS and its application; Sensor and its types.
Practice:Using Spectral Python
- Application of microwave remote sensing (Structural Trend line mapping)
- Application of thermal remote sensing and case study(Land surface Temp.estimation)
- Application of optical remote sensing and case study
2. Geospatial Technology and its Application (Code: CUAS2021)(2-2-0) 45 Hours
2.1 GIS &Cartography (2+4) Hours
Components of GIS, Types of Data in GIS, Scale Application of GIS, Advantage and limitation of GIS. History and development of Cartography; Definition, scope and concepts of cartography, Characteristics of Map; Categories of maps, Methods of mapping, relief maps, thematic maps.
1.Symbology (generalization, symbology, and coloureffect, change symbology and use transparency in creative ways) using GRASS and QGIS
Geo-referencing (Map to Image and Image to Image), Projection, Data base creation: Digitization using Point, line and polygon, Edit, Clip, Intersect, Union, Merge, Join and subset. Attribute table editing
2.Google Earth (Convert Shape file to KML Format and KML File to shape file, Import data into Google earth, Bhuvan view, Extract data From Google Earth, Extract Point Data, Extract Polygon data, Extract line data, overlaying an image into Google earth)
2.2 Data analysis tools(2+4) Hours
Raster data spatial analysis, Network analysis, Vector operations and analysis, Data editing, Primary and secondary data. Data model and data structure, Geodatabase and metadata, GIS data model, Overlay analysis, Network modeling, Data Structure Models, Spatial interpolation; measurement and analysis methods, Advantage and disadvantage
- Linking of spatial and Non-spatial data and queries, Joining tabular data with the feature attribute data, Non-spatial query, Spatial query, Spatial join, Vector based spatial analysis, Raster based spatial data analysis
- Buffering and Creation of Contour
- Network Analysis
2.3 Multi-criteria analysis and decision making (3+4) Hours
Principles and elements of multiple-criteria decision making, Classification of Multiple-criteria Decision Problem: Multi-objective Vs Multi-attribute, Decision Alternatives and constraints, Criterion weighting, Decision rules, Multiple-criteria decision making in spatial data analysis.
Introduction to AHP, Basic Principles of AHP, Effect Table, Pair Wise comparison, Consistency, Weightage, performance score, Case studies involving AHP
- Mapping accident locations using Linear Referencing technique.
- Preparation of raster layers for Multicriteria Analysis
- Solving a spatial problem using Multicriteria Analysis (Spatial AHP)
2.4 Digital Elevation Model (DEM) (2+4) Hours
Concept of DEM, Various techniques to generate DEM, Importance of spatial resolution to DEM, Integration of DEM to satellite data, Common derivatives of DEM, Slope, Aspects, TIN, Sources of DEM, Laminations and future of DEM.
- Google earth to DEM, 3D Map preparation, Contour to DEM, TIN and Aspect
- DEM based surface Hydrology modeling,
- LiDAR classification, DEM from LiDAR
2.5 Geospatial Technology for Water resources Engineering (3+4) Hours
Watershed, types, divide catchment, command area, stream types, Drainage network, different pattern; morphometric analysis, Bifurcation ratio analysis; Assessment of Groundwater potential zones and Groundwater mapping; Site selection for recharge structures, Hydrogeological Mapping GIS applications to ground water studies.
- Mapping of catchment, command area
- Drainage network analysis
- Morphometric analysis
- Mapping of Groundwater potential zones
2.6 Geospatial Technology for Environmental Engineering (3+4) Hours
Monitoring atmosphere constituents; air pollution, industrial activity, modeling using GIS, Resource development in remote areas, Impacts of anthropogenic activity, Solid Waste management; Water Pollution, Shortest path Identification, Network analysis.
- Air pollution mapping
- Solid waste management
- Water pollution
2.7 Web GIS (3+4) Hours
FOSS and its use in web mapping; Designing web services and web maps, storing and processing spatial data with FOSS, Drawing and querying maps on the server with WMS, Putting layers together with a web mapping API, Drawing vector layers with the browser.
- Designing web services and web maps
- Drawing and querying maps on the server with WMS
- Putting layers together with a web mapping API