GI3511- Mapping Toolboxes Laboratory Syllabus Regulation 2021 Anna University

GI3511 Subject code deals with the semester V Subject Mapping Toolboxes Laboratory syllabus of Anna University 2021 Revised regulation syllabus of B.E Geo Informatics Engineering. It is provided based on the student’s point of view to prepare well for academic examinations.

In this article, we would like to discuss the GI3511 – Mapping Toolboxes Laboratory Syllabus. To get good marks in the academic examinations, need a certain guide to assist you with the chapter-wise syllabus right? We include the chapter-wise syllabus for students, to assist them simply. A clear picture of the syllabus in your mind helps to understand the topics from every unit or chapter.

Then you will get an idea of where to begin from the whole syllabus by separating the topics easy from hard topics. Having command of the subject syllabus makes it easy to revise the syllabus for examination and helps you to excel in academics. The following article will give you sufficient information regarding the syllabus. Don’t forget to share it with your friends.

If you want to know more about the syllabus of B.E Geo-Informatics Engineering connected to affiliated institutions under a four-year undergraduate degree program. We provide you with a detailed Year-wise, semester-wise, and Subject-wise syllabus in the following link B.E Geo-Informatics Engineering Syllabus Anna University, Regulation 2021. Hoping this information is useful to you.

Aim Of Concept:

  • To inculcate the experimental skills to use mapping tool boxes for geomatics applications.

GI3511- Mapping Toolboxes Laboratory Syllabus

Excercises:

  1. Introduction to MATLAB functions
  2. Loops in MATLAB
  3. Arithmetic operations in matrix
  4. Files and scripts
  5. 2D and 3D plotting using MATLAB
  6. MATLAB for transforms
  7. Image reading and writing using Matlab/Scilab
  8. Enhancements–histogram, filters using Matlab/Scilab
  9. Band rationing and normalization– NDVI,SAVI&NDWI using Matlab/Scilab
  10. PCA and Image fusion using Matlab/Scilab
  11. Supervised and unsupervised classification using Matlab/Scilab
  12. Classification using Neural Network and Fuzzy Logic using Matlab/Scilab

References:

  1. Holly Moore, “ MATLAB for Engineers” Third Edition – Pearson Publications,2012.
  2. Stephen J. Chapman, “MATLAB Programming for Engineers” Fourth Edition –Thomson learning, 2008.

Related Posts On Semester -V: