Microsoft Word remote sensing-booklet doc



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Remote Sensing 2005

Course Outline: Introduction, Definitions, Key components, Functional 
Subsystem, Raster Data Model, Vector Data Model, Attribute Data Model, 
Data Acquisition Techniques, Data sources, Data capturing techniques 
and procedures, Data Transformation, Visualization of spatial data, 
Layers and Projections, Map Design: Symbols to Portray  Points , Lines 
and Volumes , Graphic Variables , Visual Hierarchy, 
Data Classification Graphic Approach , Mathematical Approach, Spatial 
Analysis: Overlay Analysis ,Spatial analysis, Neighborhood functions, 
Network and overlay analysis, buffering, Spatial data Quality: 
Components of Data Quality , Micro Level Components , Macro Level 
Components , Usage Components Sources Of Error , Accuracy, Project 
work. 
 
Lab Outline: Introduction to GIS Lab (hardware / software), 
Raster/Vector/Attribute Data Display, Scanning, Digitization, Coordinate 
based point mapping, Raster / Vector Conversion, Data layer integration 
and display of different projections, Map layout, Data Classification and 
Thematic Mapping, Handling with Topological Errors, Overlay and network 
analysis. 

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