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GIS Projects

In this section, there are projects that I have done in the field of GIS. The scope of the projects, the questions to be answered, the purpose and the software information on which it is applied are included in the explanations.

Traffic Density Detection with YOLO Algorithm

The YOLO algorithm was used in the traffic camera records of the Istanbul Metropolitan Municipality and the vehicle count was made. Traffic density maps at different time intervals were created with vehicle number data. PostgreSQL, QGIS and Python were used in the project.

 

This project was selected as the 1st in our faculty.

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Route Analysis

The aim was to create the most efficient and shortest route for the distributor to distribute to the regions where the pharmacies in the given pharmacy list are located (TSP Problem).

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The following tools were used for this process: "Mean Center", "Central Feature", Feature Class to Feature Class". Also, "Network Analyst" extension was used.

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In addition, Model (in model builder) and python script was created.

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Accesibility Analysis

The aim was to answer the following question: "What is the proportion of the rural population having access to all-season roads within a walking?" In addition, "How this population is spread over the Istanbul city?"

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The following tools were used for this process: "Reclassify", "Create Fishnet", "Make Feature Layer", "Identity", "Buffer", "Intersect", "Symmetrical Difference".

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Spatial Analysis in QGIS
(Rail Transportation Network - Population)

Geospatial database was designed using OpenStreetMap data in the QGIS. The database contains 3 geospatial data and 1 non-geospatial data (From Turkey Statistics Institution).

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In addition, 2 attribute queries and 3 spatial queries were done with cause-effect explanations. SQL commands of the queries were also written.

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Regression Analysis

The aim was to answer the following questions: "Is there any relationship with population, land use and transportation?", "If yes, is this relationship meaningful, linear or can it be described quantitatively?". In addition, "Could this relationship is shown spatially?"

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The following tools were used for this process: "Hot Spot Analysis", "Ordinary Least Squares", "Spatial Autocorrelation", "Geographically Weighted Regression".

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