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introgis [2018/10/22 13:38]
qcbs [Exercise 1 - Digitizing and map display]
introgis [2018/10/22 16:18]
qcbs [Exercice 3 - Interpolation and raster manipulation with QGIS]
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 **Step 10**: Save the changes and exit editing mode. Note that only the new columns that were created are really part of the BBS_Routes_QC table. Now remove the join (from the Properties menu) to remove the yearly observations. If you see a series of NULL values in the newly computed columns, close the attribute table and open it again. ​ **Step 10**: Save the changes and exit editing mode. Note that only the new columns that were created are really part of the BBS_Routes_QC table. Now remove the join (from the Properties menu) to remove the yearly observations. If you see a series of NULL values in the newly computed columns, close the attribute table and open it again. ​
  
-**Step 11**: You will now create a continuous interpolated surface showing the distribution of ovenbirds for each period. Make sure that the map canvas uses the same CRS as that of the BBS_Routes_QC ​file. Find IDW Interpolation under the Processing Toolbox menu. Specify BBS_Routes_QC as the input vector layer and choose the column corresponding to the earliest period as the interpolation attribute field. You need to define the number of columns, number of rows and Extent to obtain an output raster with a resolution of 2km x 2km *exactly* so that you can include most of the points (you can exclude points in Northern Quebec), but without extending too much outside of the extent covered by the points. Don't hesitate to use a calculator and the image below: ​+**Step 11**: You will now create a continuous interpolated surface showing the distribution of ovenbirds for each period. Make sure that the map canvas uses the same CRS as that of the BBS_Routes_QC ​layer. Find IDW Interpolation under the Processing Toolbox menu. Specify BBS_Routes_QC as the input vector layer and choose the column corresponding to the earliest period as the interpolation attribute field. You need to define the number of columns, number of rows and Extent to obtain an output raster with a resolution of 2km x 2km *exactly* so that you can include most of the points (you can exclude points in Northern Quebec), but without extending too much outside of the extent covered by the points. Don't hesitate to use a calculator and the image below: ​
  
 {{:​raster_res.png?​200x140|}} {{:​raster_res.png?​200x140|}}
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 <​file>​ <​file>​
-r.mapcalc "​distance_nowater=((region_hydrique-1)*-1)*distance_routes" ​+r.mapcalc ​expression="​distance_nowater=((region_hydrique-1)*-1)*distance_routes" ​
 </​file>​ </​file>​
 (change the layer names accordingly) (change the layer names accordingly)
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 **Step 14**: Identify the patch with the largest area. Find the GRASS Shell in the list of functions and write the following command: ​ **Step 14**: Identify the patch with the largest area. Find the GRASS Shell in the list of functions and write the following command: ​
 <​file>​ <​file>​
-r.mapcalc "​Largest_patch=if(Step_12 ​ == ID, 1, null())" ​+r.mapcalc ​expression="​Largest_patch=if(Step_12 ​ == ID, 1, null())" ​
 </​file>​ </​file>​
 where you replace ID with the ID of the largest patch, and Step_12 with the name that you gave to the raster in Step 12. This will have created a raster map named Largest_patch in which the largest patch is isolated with a value of 1. You can now display this raster and change the Symbology to view the isolated patch. where you replace ID with the ID of the largest patch, and Step_12 with the name that you gave to the raster in Step 12. This will have created a raster map named Largest_patch in which the largest patch is isolated with a value of 1. You can now display this raster and change the Symbology to view the isolated patch.