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Quantitative Methods in Remote Sensing

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

Satellite based positioning and LiDAR Remote Sensing

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

Advanced GIS

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 –

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