M.Tech I Year I Semester (R17)
knowing the principles to extract, managing and design the spatial elements
from the acquired remote sensing data.
at the end of the course the student will able to learn to Analyse the basic
components of GIS, Classify the maps, coordinate systems and projections, process spatial and attribute data and prepare thematic maps, Identify and rectify mapping inaccuracies and to formulate and solve geospatial problems
Introduction to GIS, Spatial Analysis – Spatial Elements, Spatial Measurement Level, Spatial Location and Reference, Spatial Patterns, Geographic Data Collection, Populations and Sampling Schemes, Making Inferences from Samples. The Language of Spatial Thinking, Map Scale, Map Characteristics, Map Projections, Grid Systems for Mapping, The Cartographic Process, Map Symbolism, Map Abstraction and Cartographic Databases, Thematic maps and associated common problems
Cartographic and GIS Data Structures – Review of the Maps an Abstraction of space, Computer Database Structures for Managing Data, Hierarchical Data Structures, Network Systems, Relational Database Management Systems, Graphic Representation of Entitle and Attributes, GIS Data Models for Multiple Coverage, Raster Models, Compact Storing of Raster Data, Vector Models, A Vector Model to Represent Surfaces, Hybrid and Integrated Systems.
GIS Data Input – The Input Subsystem, Input Devices, Raster, Vector, Reference Frameworks and Transformations, Map Preparation and the Digitizing Process, Methods of Vector Input, Method of Raster Input, Remote Seeing as a Special Case of Raster Data Input, External Databases.
Data Storage and Editing – Storage of GIS Databases, Editing the GIS Database, Detecting and Editing Errors of Different Types, Entity Errors: Vector, Attribute Errors: Raster and Vector, Dealing with Projection Change, Joining Adjacent Coverage : Edge Matching, Conflation and Rubber Sheeting, Templating.
GIS Design and Implementation – GIS Design, Internal and External GIS Design Questions, The Software Engineering Approach, System Design Principles, System Development Waterfall Model, A Structured Designed Model, Technical Design Methodology, The Spiral Model. Rapid Prototyping Database Design Study Area, Scale, Resolution, and Level of Detail, Classification, Coordinate System and Projection, Selecting a System, Verification and Validation.
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