R 15 - COURSE STRUCTURE (CBCS) FOR PG PROGRAMMES M.TECH (SIT) 2015 I YEAR, I SEMESTER Code COURSE TITLE INT. EXT. MARKS L P C SIT – 1.1 Core Course I Digital Image Processing 25 75 4 - 4 SIT – 1.2 Core Course II Basics of Remote Sensing 25 75 4 - 4 SIT – 1.3 Core Course II Fundamentals of GIS & Database 25 75 4 - 4 SIT – 1.4 Core Elective I Elective* 25 75 4 - 4 SIT – 1.5 Core Elective II Elective* 25 75 4 - 4 SIT – 1.6 Open Elective I Photogrammetry 25 75 4 - 4 SIT – 1.7 Laboratory I SIT LAB – I (GIS) 25 75 - 4 2 SIT – 1.8 Seminar I Seminar 50 - - 4 2 Total 24 8 28 Electives*: 1. Web Technologies 2. Concepts of big data – Geo statistics 3. Object oriented concepts and Spatial Databases I YEAR, II SEMESTER Code COURSE INT. MARKS EXT. MARKS L P C SIT – 2.1 Core Course IV Advanced Digital Image Processing 25 75 4 - 4 SIT – 2.2 Core Course V Satellite Geodesy 25 75 4 - 4 SIT – 2.3 Core Course VI Remote Sensing Applications 25 75 4 - 4 SIT – 2.4 Core Elective III Electives* 25 75 4 - 4 SIT – 2.5 Core Elective IV Electives* 25 75 4 - 4 SIT – 2.6 Open Elective II GIS Analysis and Applications 25 75 4 - 4 SIT –2.7 Laboratory II SIT LAB – II (DIP) 25 75 - 4 2 SIT – 2.8 Seminar II Seminar 50 - - 4 2 Total 24 8 28
Electives*: Visual C#.NET Mobile GIS technologies and applications Geospatial and customization Remote Sensing and GIS for infrastructure & Utilities Planning and Management Note: 1 session of theory = 1hr 40 minutes = 2 periods 1 session of practical = 3 hrs 20 minutes = 4 periods II Year, I SEMESTER Sl. No Subject INT. EXT. MARKS L P C 1 Comprehensive viva voce - 100 - - 4 2 Project Work Review I 50 - - 24 12 Total 24 16 II Year, II SEMESTER Sl. No Subject INT. MARKS EXT. L P C 1 Project Work Review II 50 - - 8 4 2 Project Evaluation (Viva-Voce) - 150 - 16 12 Total 24 16 SIT – 1.1- DIGITAL IMAGE PROCESSING Unit - I: Sources and Characteristics of Remote Sensing Images Characteristics of digital image data, spatial data sources, Types of spatial data resolutions- spatial, spectral, radiometric, temporal and angular. Data acquisition & storage - data formats. Image processing systems- IDRISI, ILWIS, ERDAS Imagine, ENVI, e-Cognition etc. Unit - II: Image Preprocessing
Image Analysis, Classification and change Detection in Remote Sensing . Mortan J.Century Taylor and Francis, 2007. SIT – 1.2 –BASICS OF REMOTE SENSING Unit - I: Fundamentals Definition – Scope - chronological development – Energy sources – Electro Magnetic Spectrum Energy matter interactions: in atmosphere – atmospheric windows, with earth surface features- spectral reflectance patterns. Factors affecting remote sensing Spectral response pattern. Resolution: Spatial, Spectral, Temporal, Radiometric & Angular Resolution. Platforms: of Platforms. Advantages and limitations of satellite remote sensing. Unit - II: Satellites and Sensors Major satellite programs of the world - Geostationary satellites and their orbits: sensor characteristics and their applications. Earth observation satellites : coarse, medium and high resolution satellites - LANDSAT, SPOT, IRS, IKONOS , Quick bird, World View and other recent satellites – scanning and orbiting mechanisms – Elements of image interpretation. Unit - III: Thermal Remote Sensing Thermal infrared radiation-Radiant flux – heat transfer – thermal properties of materials – emissivity – thermal inertia-heat capacity. Thermal IR detection and imaging – characteristics of TIR images. Factors controlling IR survey – applications. Unit - IV: Microwave Remote Sensing Concept, side looking airborne system (SLAR) – components, – range and azimuth resolution – Real aperture and Synthetic aperture systems, geometry of radar images; Image characteristics: wavelength, surface roughness, orientation, moisture content, polarization, look direction and look angle, physical properties, electrical properties: dielectric constant, Topographic factors, layover, fore shortening, radar shadow, corner reflection Unit - V: Hyper Spectral Remote Sensing Concept of hyper spectral remote sensing, Hyperion /HYSI, Hyper spectral data, Image cube, Hyper spectral data analysis, spectral library, Application of Hyper spectral data. TEXT BOOKS