Geo Computing 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-II scheme and its subjects refer to Geo Professional Elective-II syllabus scheme. The detailed syllabus of geo computing is as follows.
Course Objectives:
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Unit I
INTRODUCTION AND PYTHON FUNDAMENTALS Understanding geospatial data formats and file organization – Programming basics & Python core concepts – Functions – Flow control.
Unit II
PYTHON ADVANCED CONCEPTS Introduction to numpy, Containers – Copies, Reading and Writing files& Python system access -Classes and objects – Plotting with Python.
Unit III
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Unit IV
ADVANCED GIS ALGORITHMS Vector Data Algorithms (Spatial data clustering) – Raster Data Algorithms ( classification, change detection) – Network Data Algorithms (shortest path, centrality) – Geospatial Big Data Visualization Methods and Tools – Spatiotemporal Data Analytics
Unit V
OPEN-SOURCE GEOSPATIAL BIG DATA ANALYSIS AND APPLICATIONS Machine learning and deep Learning for remote sensing imagery analytics – Tensor flow – LiDAR Point Cloud analytics – GPS Trajectory Data analytics – Textual Documents analytics.
Course Outcomes:
- On completion of the course, the student is expected to
- Be familiar with major geospatial vector and raster file formats and specifications for spatial reference coordinate systems.
- Have used and be comfortable with online resources that support geocomputing and programming in the GIS profession.
- Learn newly developed GIS computation tools/libraries and platforms.
- Understand the concepts of raster, vector and data analytics
- Do ML/DL data analytics for imagery, LiDAR and GPS
Text Books:
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Reference Books:
- Yang, Chaowei, and Qunying Huang. Spatial cloud computing: a practical approach. CRC Press, 2013.
- Geron, Aurelien. Hands-on machine learning with Scikit-Learn and TensorFlow: concepts, tools, and techniques to build intelligent systems. O’Reilly Media, Inc., 2017.
- Richert, Willi. Building machine learning systems with Python. Packt Publishing Ltd, 2013.
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.