Exploring Clustering In QGIS - Revision history

Jenniferdolan: /* Required Software */

2026-10-06T19:57:35Z

Required Software

Jenniferdolan: /* Future Work */

2026-10-05T18:19:21Z

Future Work

Jenniferdolan: /* Conclusion */

2026-10-05T18:18:37Z

Conclusion

Jenniferdolan: /* Conclusion */

2026-10-05T18:17:37Z

Conclusion

Jenniferdolan: /* Interpreting Results */

2026-10-05T18:06:04Z

Interpreting Results

Jenniferdolan: /* Interpreting Results */

2026-10-05T18:05:35Z

Interpreting Results

Jenniferdolan: /* Symbology */

2026-10-05T18:03:05Z

Symbology

Jenniferdolan: /* Projection */

2026-10-05T17:57:49Z

Projection

Jenniferdolan: /* Required Datasets */

2026-10-05T17:55:52Z

Required Datasets

Jenniferdolan: /* Required Software */

2026-10-05T17:54:58Z

Required Software

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 To run this analysis, it is best to have the latest version of QGIS.
-*If you have an old version, I would start by deleting that one before proceeding to further steps as having two versions of QGIS is not necessary and takes space on the hard drive.
+*If you have an old version, it is recommended to delete this before proceeding to further steps as having two versions of QGIS is not necessary and takes space on the hard drive.
 *Click on this [https://qgis.org/en/site/forusers/download.html link] and you will see many options on operating systems you can download QGIS on.

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 == Future Work ==
-There definitely is a lot of future work in terms of the potential of something like this. You can add more components and maybe include some other GIS tools such as network analysis to calculate the most cost affective ways to investigate those areas(less gas consumption is better and could save city money). Use interpolation to maybe predict possible incidences of accidents. Future work more from a QGIS perspective is to include more methods of clustering as well. There is a lot that can be done around vector points that contain location data but that would be more suited for a separate tutorial not to overwhelm a user.
+There definitely is a lot of future work in terms of the potential of something like this. You can add more components and maybe include some other GIS tools such as network analysis to calculate the most cost affective ways to investigate those areas (less gas consumption is better and could save city money). Use interpolation to maybe predict possible incidences of accidents. Future work more from a QGIS perspective is to include more methods of clustering as well. There is a lot that can be done around vector points that contain location data but that would be more suited for a separate tutorial not to overwhelm a user.
 == References ==

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 == Conclusion ==
-The clustering methods in QGIS are very useful and relatively easy to use as shown in this tutorial. If there is a need for something to be divided, clustering performs well with vector data, making it an effective tool to use. Whether you are investigating collision trends or assigning door-to-door sales representative using house locations, these QGIS tools have incredible potential in terms of urban planning or any purposes where discrete divisions are required. While it may not be as advanced and intricate as other tools, such as ArcGIS Pro, QGIS is a great alternative to complete these tasks for its open source and easily accessible nature.
+These clustering methods in QGIS are invaluable and relatively easy to use as shown in this tutorial. If there is a need for something to be divided, clustering performs well with vector data, making it an effective tool to use. Whether you are investigating collision trends or assigning door-to-door sales representative using house locations, these QGIS tools have incredible potential in terms of urban planning or any purposes where discrete divisions are required. While it may not be as advanced and intricate as other tools, such as ArcGIS Pro, QGIS is a great alternative to complete these tasks for its open source and easily accessible nature.
 == Future Work ==

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 == Conclusion ==
-The clustering methods in QGIS are very useful and relatively easy to use as shown in this tutorial. When using vector point data and there is a need for something to be divided, I think clustering does a good job at determining areas in which we can divide some tasks and for that it makes it an effective tool to use. I will say that the DBSCAN clustering method is incredibly particular and has given me some trouble to understand how it works. However, the solution to that issue which I have described is very straightforward and it is important to really follow the steps to use the tool. Doesn't matter if it's trying to investigate collisions or divide areas of garbageman using h
+The clustering methods in QGIS are very useful and relatively easy to use as shown in this tutorial. If there is a need for something to be divided, clustering performs well with vector data, making it an effective tool to use. Whether you are investigating collision trends or assigning door-to-door sales representative using house locations, these QGIS tools have incredible potential in terms of urban planning or any purposes where discrete divisions are required. While it may not be as advanced and intricate as other tools, such as ArcGIS Pro, QGIS is a great alternative to complete these tasks for its open source and easily accessible nature.
-ouse locations, that tool has incredible potential in terms of urban planning or any purposes where we would need to divide and conquer. It might not be as pronounced as the tool we have for ArcGIS but it is importantly a good open source alternative that will do the job when other more expensive software is not widely available.
 == Future Work ==

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 Below is the result of Concave Hull polygons overlayed by points for the specific cluster. This output provides us with a baseline on how to identify regions where patrolling operations should be designated.
-Further analysis can be made to account for the cluster size of a specific region. For example, urban clusters have higher frequency of collisions occurring, thus assigning more patrol officers to these municipalities can account for this demand. Whereas rural locations such as North Gower can be under less surveillance.
+Further analysis can be made to account for the cluster size of a specific region. For example, urban clusters (e.g. Centretown) have higher frequency of collisions occurring, thus assigning more patrol officers to these municipalities can account for this demand. Whereas rural locations such as North Gower can be under less surveillance.
 [[File:CH_Results_blackpoints_map.png|none|900px|link=MediaWiki]]

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 ===Symbology===
+Symbology is a great visual method to understand and create distinction of map layers. It is recommended to try out various symbol combinations for all layers. This is exceptionally important at the end when analyzing our results and displaying them for an audience.
-We use symbology as a method of better reference. I would play around as you wish in the properties of the Wards, Collisions and Roads layer. To make sure there isn't too much colour similarities. I recommend to also do this post clustering as you will be classifying separate clusters with different colours. The next step will help us classify roads better.
 *Right click on the layer, go to '''Properties''', select '''Symbology''', and click '''OK''' once satisfied. Make sure to click '''Apply''' each time you change the symbology. [[File:SymbologyTab.png|none|600px|link=MediaWiki]]
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 *Repeat this for other roads by clicking '''+''' icon to add a new rule, type 'Other Roads' in '''Label''', and select '''Else''' as it's the other condition. In the '''Layers''' pane it should look something like this: [[File:RoadSeperation.png|none|300px|link=MediaWiki]]
 == Analysis ==

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 ===Projection===
-Projection is an important step for DBSCAN clustering, you may encounter problems if you do not do it this way. NAD83, specifically UTM zone 18, is an appropriate projection for this project as we are looking at a municipal problem, Ottawa traffic collisions. Projecting to a projection such as this one will be important considering we are dealing with distances when using the DBSCAN clustering.
+Projection is an important step for DBSCAN clustering, you may encounter problems if you do not do it this way. NAD83, specifically UTM zone 18, is an appropriate projection for this project as we are looking at a municipal problem, Ottawa traffic collisions. Projection is important as DBSCAN clustering relies on map distances.
-Important: All vector data should be projected that way.
+Tip: All vector data should be projected that way.
 To first orient yourself, we'll add Google Satellite basemap.
 *Select '''Plugins''', then '''Manage and Install Plugins...''', search "Basemaps", select '''Basemaps''' and '''Install'''. [[File:BasemapPlugin.png|none|600px|link=MediaWiki]]
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 *Choose a location in your project folder and name it. Ex: Traffic_Collisions2019_Reprojected.
 *On '''CRS''', click the world icon, search for "EPSG:2959" or "NAD83(CRSR) / UTM zone 18N", select it and press '''OK'''. [[File:Reprojecting_Layer.png|none|500px|link=MediaWiki]]
 ===Symbology===

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 === Required Datasets ===
-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.
+The data that we will be using will be in two forms: Referencing data so we can visualize where we are and vector data to use for clustering.
 Referencing

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 ===Required Software===
-To run this analysis, it is best to have the latest version of QGIS. I will detail the steps into getting the newest version.
+To run this analysis, it is best to have the latest version of QGIS.
 *If you have an old version, I would start by deleting that one before proceeding to further steps as having two versions of QGIS is not necessary and takes space on the hard drive.
-*Click on this [https://qgis.org/en/site/forusers/download.html link] and you will see many options on operating systems you can download QGIS on
+*Click on this [https://qgis.org/en/site/forusers/download.html link] and you will see many options on operating systems you can download QGIS on.
-*Select either the fastest (4.2.2) or the more stable (3.44.14) download depending on your preference and it should start downloading
+*Select either the fastest (4.2.2) or the more stable (3.44.14) download depending on your preference and it should start downloading.
-*Once it's done downloading add it to your hard drive(if not already done automatically) and you should be ready to use the open source software
+*Once it's done downloading, add it to your hard drive (if not already done automatically) and you are ready!
 === Required Datasets ===