Unit I:

Physical properties of Sea water, density of sea water, density parameters, specific volume anomaly, Temperature, Salinity, Cholorinity and their determination, distribution of temperature, salinity and density in space and time, The oceanic Mixed Layer and Thermocline, Sea level variation, acoustical and optical properties of sea water, Formation and classification of water masses, T-S diagram and Water masses of the world ocean.

Concept of fluid, Continum model, Lagrange and Eulerian description of fluid flow, continuity, momentum and energy equations, boundary layer theory, turbulent flow, Inertial

State of the atmosphere; Main constituents of dry air, Vertical thermal structure of the atmosphere; Standard atmosphere; Hydrostatic equilibrium; Weather and its phenomena – Winds, cyclones, precipitation, hydrologic cycle; Surface weather and vertical structure;

Elements of radiative transfer in atmosphere- Basic quantities, Blackbody radiation – basic laws -  Radiative transfer equation, Physics of Gaseous absorption, emission, Scattering, Solar radiation and surface reflection; Radiation balance;

Role of remote sensing in agriculture and soil– SpectralSignatures of vegetation and vegetation/soil indices - application in agriculture: Crop production forecasting, assessment and monitoring of crop growth, damage - Cropping Systems Analysis. Spectral signatures of soil – estimation of nutrient, soil moisture content - passive and active remote sensing methods National missions on agriculture and soil; production forecast (FASAL) Crop Identification Technology Assessment for Remote Sensing (CITARS) NBSS mapping.

Image Formation Models, Monocular imaging system, Orthographic & Perspective Projection , Camera model and Camera calibration , 3D scanning, 3D from RGBD data, Binocular imaging systems Image Processing and Feature Extraction, point cloud processing, Triangulation and partitioning, range search, Structure from motion, Shape Representation and Segmentation , Deformable curves and surfaces , Snakes and active contours , Fourier and wavelet descriptors, , Multiresolution analysis (wavelets, curvelets, countourlets, shearlets ), Object recognition, Hough transforms and other simple object r

Reflectance spectroscopy, dimensionality reduction, feature selection, subspace modelling, endmember extraction, hyperspectral band ratios and vegetation indices, hyperspectral classification methods, target detection, spectral unmixing, spectral libraries, applications of hyperspectral remote sensing

Passive and active microwave radiometry,  radar equation, range and azimuth resolutions, concept of SAR, SAR image distortions, radar image interpretation, microwave scattering of land surface, SAR interferometry, Polarimetric SAR,  

Remote sensing data calibration, reflectance, radiance conversion, spectral reflectance and materials properties, deterministic methods, statistical, empirical methods, physically based methods, estimation of geophysical variables, forest growing stock, LST / SST, soil moisture, snow melt and runoff prediction, crop yield, rainfall,  ocean chlorophyll and productivity, validation and spatial scaling

Development of global surveying techniques, positioning and navigation with satellites, Reference systems: coordinate systems, time systems, satellite orbits: orbit description, orbit determination, orbit dissemination, satellite signalsGPS – reference systems, GPS services, GPS segments, GPS signal structure,  GLONASS - reference systems, GLONASS segments, GLONASS signal structure,  Galileo - reference systems, Galileo services, Galileo segments, Galileo signal structure, IRNSS - signals, services and segments, satellite based augmentation systems (SBAS) - GAGAN, WAAS, EGNOS, MSA

Data types and models – Input / output techniques in GIS (spatial and non-spatial) – editing –Topology – database structure – Spatial analysis of vector and raster data models – Network analysis, optimization of path, time and cost, routing and events, facility location, hydrological analysis –interpolation methods  – multidimensional (MD) data -  spatial representation of data -  object hierarchy -  MD  structure: k-d tree, Point quadtree  – construction and dynamic & kinetic data structure -  topology of 3D data – terrain data acquisition and input –