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Indian Institute of Technology Roorkee

Remote Sensing Essentials

Indian Institute of Technology Roorkee and NPTEL via Swayam


The proposed course provides basic understanding about satellite based Remote Sensing and Digital Image Processing technologies. Presently, remote sensing datasets available from various earth orbiting satellites are being used extensively in various domains including in civil engineering, water resources, earth sciences, transportation engineering, navigation etc. Google Earth has further made access to high spatial resolution remote sensing data available to non-experts with great ease. Knowledge of Digital Image Processing of satellite data allows to process raw satellite images for various applications.

INTENDED AUDIENCE : Under- / Post-graduate engineering and post graduate science students / PhD candidates PREREQUISITES : Remote Sensing / Geoinformatics companies, e.g NIIT, ESRI India, Leica Geoinformatics, MapmyIndia etc INDUSTRY SUPPORT : ONGC, OIL, GSI and others


COURSE LAYOUT Week 1 : Rudiments of remote sensing and advantages Historical Perspective of development of remote sensing technology EM spectrum, solar reflection and thermal emission remote sensing Interaction of EM radiation with atmosphere including atmospheric scattering, absorption and emission Interaction mechanisms of EM radiation with ground, spectral response curves Week 2 : Laws of Radiation and their relevance in Remote Sensing Basis of remote sensing image representation Various Remote Sensing Platforms Multi-spectral scanners and imaging devices Significant characteristics of LANDSAT, SPOT, Sentinel etc. Week 3 : Prominent characteristics of IRS, Cartosat, ResourceSat etc. Unmanned Aerial Vehicle / Drone Passive Microwave Remote Sensing Image characteristics and different resolutions in Remote Sensing Different techniques of Image acquisition Week 4 : Importance of digital image processing Digital, Image Processing Software, Basic image enhancement techniques Colour representations and transforms, Image Histograms and statistics Week 5 : Atmospheric errors and corrections, Geometric transformations /Georeferencing Technique, Digital Image Processing Software – Demonstration Image enhancement techniques –I Image enhancement techniques –II Week 6 : Digital Image Processing Software – Demonstration, Spatial filtering techniques, Frequency based filtering techniques, Digital Image Processing Software – Demonstration, Unsupervised image classification and density slicing techniques Week 7 : Supervised image classification techniques and limitations, Digital Image Processing Software - Demonstration, LiDAR Technique and applications, False Topographic Phenomena and correction techniques, Mosaicking, subsets, sub-sampling techniques and applications Week 8 : High Spatial Resolution Satellite Images and limitations, Multispectral transforms: scatter plot, principal component analysis and decorrelation stretch, Basic Image Compression techniques and different image file formats, Hyperspectral Remote Sensing, Digital Image vs Digital Photograph Week 9 : NDVI and other indices, Image merging techniques, Radar Images interpretation and applications, SAR Interferometry (InSAR) Technique-01,SAR Interferometry (InSAR) Technique-02 Week 10 : Remote Sensing integration with GIS and GPS,Principles of image interpretation Remote Sensing of Moon and Mars, image interpretation of different geological landforms, rock types and structures Application of Remote Sensing in Fog studies Week 11 :Integrated applications of RS and GIS in groundwater studies-01. Integrated applications of RS and GIS in groundwater studies-02, Applications of Remote Sensing in Earthquake Studies, Remote Sensing Applications in Urban Infrastructure, Digital photogrammetry for generation of Digital Elevation Models using Stereo Pairs Week 12 :Google Earth and its utilization, Integration of satellite images with Digital Elevation Models and generation of 3D perspective , Fire detection (straw / Parali burning/ Forest Fire), Different sources of free satellite images, Limitations and Future of Remote Sensing Techniques

Taught by

Prof. Arun K. Saraf

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