Raster Data Modelling detailed syllabus for Geoinformatics Engineering (Geo) for 2021 regulation curriculum has been taken from the Anna Universities official website and presented for the Geo students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below.
For Geoinformatics Engineering 5th Sem scheme and its subjects, do visit Geo 5th Sem 2021 regulation scheme. For Professional Elective-III scheme and its subjects refer to Geo Professional Elective-III syllabus scheme. The detailed syllabus of raster data modelling is as follows.
Course Objectives:
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Unit I
POINT BASED FUNCTION Image – properties – reading – color contrast – histogram – zooming and display -pan operations -pyramids – enhancements – transformation.
Unit II
NEIGHBORHOOD AND PROXIMITY ANALYSIS 8,4 D neighborhood – texture computation – GLCM – distance measurement – buffers (point,line,area).
Unit III
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Unit IV
MULTILAYER MODELING Image ratio – indices – normalization – segmentation – similarity measures – maximum likelihood classification.
Unit V
STATISTICAL METRICS Mean – mode – standard deviation – correlation -regression -covariance – kappa statistics -random sample selection.
Course Outcomes:
•On completion of the course, the student is expected to
- Acquaint with the raster data structure and its relevance in from pint based, neighbourhood based and region based geospatial .data analysis
- Understand the various raster based data modeling applied on the earth observation data for resource management
- Evaluate the procedures of spatial data handling using raster data model for solving resource management problems
- Acquire knowledge on the current development, issues methods and solutions in raster data analysis using earth observation data.
- Analyze critically and evaluate methods by applying the knowledge gained and to be a part of innovation and integration of geospatial data modeling
Text Books:
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Reference Books:
- Digital Image Processing, Rafael C. Gonzalez, Richard E. Woods , Pearson , Fourth edition, 2022.
- Concepts and Techniques in Geographic Information System, C.P Lo., Second Edition, 2016.
- Deep Learning with Python, Manning, Second Edition, 2021.
- Geocomputation with R, Jakub Nowosad, JannesMuenchow, and Robin Lovelace, First Edition, 2020.
- Advance Custom Raster Processing using Python, Jie Zhang, Hao. Available from:
Hu.https://www.esri.com/content/dam/esrisites/en-us/events/conferences/2020/developer-summit/advance-raster-processing-using-python.pdf
For detailed syllabus of all the other subjects of Geoinformatics Engineering 5th Sem, visit Geo 5th Sem subject syllabuses for 2021 regulation.
For all Geoinformatics Engineering results, visit Anna University Geo all semester results direct link.