Creating a Heatmap using QGIS - Revision history

Smitch: /* Introduction */ fixed wording

2021-10-13T11:29:19Z

Introduction: fixed wording

Kathleen: /* Methodology */

2021-10-02T02:19:36Z

Methodology

Kathleen: /* Limitations */

2021-10-02T01:18:37Z

Limitations

Kathleen: /* Result */

2021-10-02T01:12:36Z

Result

Kathleen: /* Methodology */

2021-10-02T01:06:33Z

Methodology

Kathleen: /* Methodology */

2021-10-02T01:02:12Z

Methodology

Kathleen: /* Methodology */

2021-10-02T01:00:04Z

Methodology

Kathleen: /* Methodology */

2021-10-02T00:50:59Z

Methodology

Kathleen: /* Methodology */

2021-10-02T00:35:24Z

Methodology

Kathleen: /* Methodology */

2021-10-02T00:31:54Z

Methodology

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 == Introduction ==
-Heatmaps are of one the best visualization tools for dense point data. Heatmap is an interpolation technique that is useful in determining density of input features. Heatmaps are most commonly used to visualize crime data, traffic incidents, housing density etc. The density is calculated based on the number of points in a location, with larger numbers of clustered points resulting in larger values. Heatmaps allow easy identification of “hotspots” and clustering of points. QGIS has a heatmap renderer that can be used to style a point layer and a Processing algorithm Heatmap (Kernel Density Estimation) that can be used to create a raster from a point layer.
+Heatmaps are one of the best visualization tools for dense point data. Heatmapping is an interpolation technique that is useful in determining density of input features. Heatmaps are most commonly used to visualize crime data, traffic incidents, housing density etc. The density is calculated based on the number of points in a location, with larger numbers of clustered points resulting in larger values. Heatmaps allow easy identification of “hotspots” and clustering of points. QGIS has a heatmap renderer that can be used to style a point layer and a processing algorithm Heatmap (Kernel Density Estimation) that can be used to create a raster from a point layer.
 == Purpose ==

@@ Line 79: / Line 79: @@
 <br><nowiki>6. </nowiki> Unselect the “MCI 2014 to 2019” layer and you should now see all Break and Entry cases for 2019 in Toronto.
 <br><nowiki>7. </nowiki> Next, we would be making the heatmap. Right click on the “BreakEntry2019” layer and select “Properties”.
-<br><nowiki>8. </nowiki> Click on '''Layer styling Panel''' (or Symbology if your using version later than 3.10.10) and change the symbology from “Single symbol” to “Heatmap”.
+<br><nowiki>8. </nowiki> Click on '''Layer styling Panel''' (or Symbology if you are using a version later than 3.10.10) and change the symbology from “Single symbol” to “Heatmap”.
 <br><nowiki>9. </nowiki> Next you need to choose a '''Radius'''. This parameter determines the circular neighborhood around each point where that point will have an influence. This value will largely depend on the type of your input data. For our data, let’s assume a crime incident will have an influence upto "5 kilometers" from the location. Notice that the current project CRS is set to EPSG: 3857 in the bottom-right corner. This CRS has a unit of meter, so we should specify 5000 meters as the radius. Remember to use "Map Units"
 <br><nowiki>10. </nowiki> Change the colour ramp to “Reds” and under “Layer Rendering” change the Opacity to “55%” and click '''Ok'''.

@@ Line 120: / Line 120: @@
 * Heatmaps can often be misinterpreted. Heat maps express clusters, and one can look at a map and think there is no crime except at the hotspot zone which is wrong
 * Using real crime data might alter one's perception of a city which may or may not be misleading.
+* Street names, cities and other detailed information of the area are not shown on the map.
 * The Heatmap Render does not produce a legend or values used to calculate for the heatmap. And the interpolation tool “Heatmap (Kernel Density Estimation)” produces a heatmap that is not visually appealing.

@@ Line 97: / Line 97: @@
 <br>For the first Map:
 # Deselect the new Heatmap layer.
-## [[File:O.jpg|thumb|center|Fig 10. Layers selected for map 1]]
+## [[File:O.jpg|thumb|center|Figure 10. Layers selected for Map 1]]
-# On the Toolbar Click on '''Project''' and then '''New Print Layout'''.
+# On the Toolbar, click on '''Project''' and then '''New Print Layout'''.
 # Name the Layout and click '''Ok'''.
 # On the Toolbar, click '''Add Item''' and select '''Add Map'''. Create the extent for the map on the layout.
@@ Line 105: / Line 105: @@
 For the Second Map:
 # Reselect the new Heatmap layer.
-# Move the “Toronto Neighbourhood” layer above the new “Heatmap” layer and reduce its Opacity to “50%” by right-clicking and the '''properties''' and then “Layer Rendering”.
+# Move the “Toronto Neighbourhood” layer above the new “Heatmap” layer and reduce its Opacity to “50%” by right-clicking and the '''Properties''' and then “Layer Rendering”.
-## [[File:P.jpg|thumb|center|Fig 11. Layers selected for map 2]]
+## [[File:P.jpg|thumb|center|900px|Figure 11. Layers selected for Map 2]]
-# On the Toolbar Click on '''Project''' and then '''New Print Layout'''.
+# On the Toolbar, Click on '''Project''' and then '''New Print Layout'''.
 # Name the Layout and click '''Ok'''.
 # On the Toolbar, click '''Add Item''' and select '''Add Map'''. Create the extent for the map on the layout.
 # Add a North Arrow, Scale Bar, Title and Legend.
 # Export as PDF or Image.
-[[File:Break&Entry 2019.jpg|thumb|center|Fig 12. Heatmap Using GQIS Renderer]]
+[[File:Break&Entry 2019.jpg|thumb|center|900px|Figure 12. Heatmap Using GQIS Renderer]]
-[[File:Break&Entry 2019 2.jpg|thumb|center|Fig 13. Heatmap using Heatmap (KDE) Interpolation tool]]
+[[File:Break&Entry 2019 2.jpg|thumb|center|900px|Figure 13. Heatmap using Heatmap (KDE) Interpolation tool]]
 ==Limitations ==

@@ Line 89: / Line 89: @@
 <br>Pixel Size: X: 50, Y: 50
 <br>Leave everything else as is.
-[[File:Ljkb.jpg|thumb|right|800px|Figure 8. Input for heatmap.]]
+[[File:Ljkb.jpg|thumb|right|500px|Figure 8. Input for heatmap.]]
 <br><nowiki>12. </nowiki> Your screen should look like this (Figure 9). Click on Layer Styling Panel and change “Singleband gray” to “Singleband pseudocolor”. Change colour ramp to “Reds”. Then '''Apply'''.
 [[File:Nf.jpg|thumb|center|1000 px|Figure 9. Interpolation Heatmap tool]]

@@ Line 80: / Line 80: @@
 <br><nowiki>7. </nowiki> Next, we would be making the heatmap. Right click on the “BreakEntry2019” layer and select “Properties”.
 <br><nowiki>8. </nowiki> Click on '''Layer styling Panel''' (or Symbology if your using version later than 3.10.10) and change the symbology from “Single symbol” to “Heatmap”.
-<br><nowiki>9. </nowiki> Next you need to choose a '''Radius'''. This parameter determines the circular neighborhood around each point where that point will have an influence. This value will largely depend on the type of your input data. For our data, let’s assume a crime incident will have an influence upto "5 kilometers" from the location. Notice that the current project CRS is set to EPSG: 3857 in the bottom-right corner. This CRS has a unit of meter, so we should specify 5000 meters as the radius.
+<br><nowiki>9. </nowiki> Next you need to choose a '''Radius'''. This parameter determines the circular neighborhood around each point where that point will have an influence. This value will largely depend on the type of your input data. For our data, let’s assume a crime incident will have an influence upto "5 kilometers" from the location. Notice that the current project CRS is set to EPSG: 3857 in the bottom-right corner. This CRS has a unit of meter, so we should specify 5000 meters as the radius. Remember to use "Map Units"
 <br><nowiki>10. </nowiki> Change the colour ramp to “Reds” and under “Layer Rendering” change the Opacity to “55%” and click '''Ok'''.
-<br>You should see a change in the map.
+<br>You should see a change in the map like the screenshot below (Figure 7).
-[[File:Kljb.jpg|thumb|center|Figure 7. Heatmap settings for B&E in 2019]]
+[[File:Kljb.jpg|thumb|center|1000px|Figure 7. Heatmap settings for B&E in 2019]]
-<br><nowiki>11. </nowiki> Next, we are going to do some Spatial Interpolation. On the Toolbar click on Processing then Toolbox. Search “Heatmap”, and select “Heatmap (Kernel Density Estimation)”
+<br><nowiki>11. </nowiki> Next, we are going to do some Spatial Interpolation. On the Toolbar click on '''Processing''' then Toolbox. Search “Heatmap”, and select “Heatmap (Kernel Density Estimation)”
 <br>Point Layer: BreakEntry2019 (or whatever you named your layer)
 <br>Radius: 5000 metres
 <br>Pixel Size: X: 50, Y: 50
 <br>Leave everything else as is.
-[[File:Ljkb.jpg|thumb|right|Fig 8. Input for heat map]]
+[[File:Ljkb.jpg|thumb|right|1000px|Figure 8. Input for heatmap.]]
 <br><nowiki>12. </nowiki> Your screen should look like this. Click on Layer Styling Panel and change “Singleband gray” to “Singleband pseudocolor”. Change colour ramp to “Reds”. Then '''Apply'''.
 [[File:Nf.jpg|thumb|center|Fig 9. Interpolation Heatmap tool]]

@@ Line 72: / Line 72: @@
   Meaning it covers everything past “B&E”. ie. “B&E”, “B&E - M/Veh To Steal Firearm”, “B&E Out”, etc.)
   Your statement should look like this: “occurren_1” = 2019 AND “offence” like ‘B&E%’
-After all of this, click Select Features. And you should see certain points on the map selected, though it may be hard to visualize.
+After all of this, click '''Select Features'''. And you should see certain points on the map selected, though it may be hard to visualize.
 <br>Be careful of the syntax and formatting as the tool is case sensitive. For more information about how Expressions work, check out this link (https://docs.qgis.org/2.18/en/docs/user_manual/working_with_vector/expression.html)
 <br><nowiki>4. </nowiki> Right click on the “MCI 2014 to 2019” layer and click on “Export” then “Save Selected Features As...”
-[[File:Fdf.jpg|thumb|center|Fig 6. Save selected features as..]]
+[[File:Fdf.jpg|thumb|center|1000px|Figure 6. Save selected features as..]]
-<br><nowiki>5. </nowiki> Change the Format to “ESRI Shapefile” and set the File name as “BreakEntry2019” (or whatever you prefer) and then click '''Ok'''. Leave everything else the same.
+<br><nowiki>5. </nowiki> Change the Format to “ESRI Shapefile” and set the File name as “BreakEntry2019” (or whatever you prefer) and then click '''Ok'''. Leave everything else the same. if the file shows an error, check the location of where the output will be saved to.
 <br><nowiki>6. </nowiki> Unselect the “MCI 2014 to 2019” layer and you should now see all Break and Entry cases for 2019 in Toronto.
 <br><nowiki>7. </nowiki> Next, we would be making the heatmap. Right click on the “BreakEntry2019” layer and select “Properties”.
-<br><nowiki>8. </nowiki> Click on “Layer styling Panel” and change the symbology from “Single symbol” to “Heatmap”.
+<br><nowiki>8. </nowiki> Click on '''Layer styling Panel''' (or Symbology if your using version later than 3.10.10) and change the symbology from “Single symbol” to “Heatmap”.
-<br><nowiki>9. </nowiki> Next you need to choose a Radius. This parameter determines the circular neighborhood around each point where that point will have an influence. This value will largely depend on the type of your input data. For our data, let’s assume a crime incident will have an influence upto 5 Kilometers from the location. Notice that the current project CRS is set to EPSG: 3857 in the bottom-right corner. This CRS has a unit of meter, so we should specify 5000 meters as the radius.
+<br><nowiki>9. </nowiki> Next you need to choose a '''Radius'''. This parameter determines the circular neighborhood around each point where that point will have an influence. This value will largely depend on the type of your input data. For our data, let’s assume a crime incident will have an influence upto "5 kilometers" from the location. Notice that the current project CRS is set to EPSG: 3857 in the bottom-right corner. This CRS has a unit of meter, so we should specify 5000 meters as the radius.
 <br><nowiki>10. </nowiki> Change the colour ramp to “Reds” and under “Layer Rendering” change the Opacity to “55%” and click '''Ok'''.
 <br>You should see a change in the map.
-[[File:Kljb.jpg|thumb|center|Fig 7. Heatmap settings for b&e in 2019]]
+[[File:Kljb.jpg|thumb|center|Figure 7. Heatmap settings for B&E in 2019]]
 <br><nowiki>11. </nowiki> Next, we are going to do some Spatial Interpolation. On the Toolbar click on Processing then Toolbox. Search “Heatmap”, and select “Heatmap (Kernel Density Estimation)”
 <br>Point Layer: BreakEntry2019 (or whatever you named your layer)

@@ Line 62: / Line 62: @@
 Here we would be creating feature layers from the MCI layer and creating the heatmaps.
 <br>For the '''Break and Entry''', 2019 shapefile:
-<br><nowiki>1. </nowiki> On the Toolbar, click on '''Select Features by Expression'''. It could be in the top row of the Toolbar (shown below in Figure 4) or on top of the "Browser" section on your left.
+<br><nowiki>1. </nowiki> Click on the MCI layer, then on the Toolbar click on '''Select Features by Expression'''. It could be in the top row of the Toolbar (shown below in Figure 4) or on top of the "Browser" section on your left.
-[[File:Djv.jpg|thumb|center|700px|Figure  4. To find "Select Features by Expression"]]
+[[File:Djv.jpg|thumb|center|1000px|Figure  4. To find "Select Features by Expression"]]
 <br><nowiki>2. </nowiki> Click on “Fields and Values” and select “occurren_1”, then put an “=” and type 2019.
   (This means we are narrowing the data to 2019 only.)
-[[File:Egfr.jpg|frame|center|Fig 5. Select by Expression for 2019 B&E]]
+[[File:Egfr.jpg|frame|center|Figure 5. Select by Expression for 2019 B&E]]
 <nowiki>3. </nowiki> Next type “And”, and click “offence”, then type “like” and finally type “ ‘B&E%’ ”.
   (The “And” joins the first statement with the second statement”. The second statement narrows down offence to Break and Entry.
@@ Line 72: / Line 72: @@
   Meaning it covers everything past “B&E”. ie. “B&E”, “B&E - M/Veh To Steal Firearm”, “B&E Out”, etc.)
   Your statement should look like this: “occurren_1” = 2019 AND “offence” like ‘B&E%’
-After all this click Select Features. And you should see certain points on the map selected, though it may be hard to visualize.
+After all of this, click Select Features. And you should see certain points on the map selected, though it may be hard to visualize.
 <br>Be careful of the syntax and formatting as the tool is case sensitive. For more information about how Expressions work, check out this link (https://docs.qgis.org/2.18/en/docs/user_manual/working_with_vector/expression.html)
 <br><nowiki>4. </nowiki> Right click on the “MCI 2014 to 2019” layer and click on “Export” then “Save Selected Features As...”