Exploring Clustering In QGIS

Purpose

The purpose of this project is to explore the capabilities of open source software such as QGIS. QGIS is one of the many open source softwares we have used in GEOM 4008. In this tutorial which I am writing in 2021, I will be going into vector analysis tools in QGIS which are used to create clusters. I will go step by step going through the Density Based and K-means methods of clustering and I will give the results of my findings.

Introduction

The use of clusters is a practical tool in GIS, it can help group vector data points into separate clusters or groups which the amount is fully configurable by the user. This can be helpful if you have a vast area and you want to divide a task into multiple areas and divide and conquer to accomplish a certain goal. The option is given in ArcPro and while it may have a bigger collection of clustering options, QGIS still has clustering capabilities which are DBSCAN(density based) and K-Means. We will be using the newest version of QGIS at the time of tutorial, version 3.22. The most important part for the start of the project is downloading the latest version, getting the proper data and proper projections which I will go step by step in detailing below. The scope of my project will be going as a City of Ottawa official that wants to investigate incidents(vehicle, bicycle, etc...) and he feels the city is too big and the goal of this tutorial will be on how we can designate multiple smaller areas for him to work with.

Data

The data that we will be using will be in two forms. Referencing data so we can visualize where we are and data we will use for the clustering.

Referencing

• The Roads dataset
• The Wards dataset

Clustering

• The Traffic Collisions by Location in 2013 dataset