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kntu_geomatics_logo-transformed

Bachelor's KNTU Geomatic Engineering Codes

This repo contains a collection of codes and scripts developed for various courses in the Geomatic Engineering program at KNTU. The primary goal is to provide students with useful resources to aid their studies and projects.

Courses Included

1. Analytical Photogrammetry

  • In this course, codes related to coordinate system transformations and 2D and 3D equations such as Multi Quadric, Point Wise and DLT are available in MATLAB .

2. Applications Of Photogrammetry

  • In this course, codes for photogrammetry Cases 1 to 4 are available in MATLAB for the adjustment and correction of network coordinates.
    • Case 1 : Approximate
    • Case 2 : Adjustmet & Intersection
    • Case 3 : Adjustmet with Control points
    • Case 4 : Adding Geodetic observations

3. Geomatic Geodesy

  • In this course, two projects on Datum transformation for coordinate determination and Gnomic projection are available in MATLAB .

4. Geospatial Information System (GIS)

  • In this course, an Extension for selecting and displaying a layer in ArcGIS has been written in Python using Arcpy .

5. Image Processing

  • In this course, three labs are available in a Python notebook for tasks such as histogram equalization, change detection, and frequency domain analysis in aerial image processing.

6. Jeodetic

  • In this course, MATLAB codes for correcting the Z0 error of the total station and plotting graphs of pressure, temperature, and water vapor parameters are available.

7. Numerical Analysis

  • In this course, numerical solutions for several equations using methods such as Newton-Raphson are provided in C++ .

8. Remote Sensing (RS)

  • In this course, codes for Spatial filters and Histogram analysis of images are available in a Python notebook .

9. Spatial Analysis

  • In this course, codes for various Spatial analyses such as buffering, distance, classification, and intersection are available in Python . Additionally, SQL codes for spatial queries in PostGIS, along with their data, are also provided.

I hope these projects are immensely helpful to you and that you learn something valuable from my codes. Feel free to contribute and share your improvements!