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Data · dataset · 2022

Toronto Land Use Spatial Data - parcel-level - (2019-2021)

Listed in Borealis and Agri-environmental Research Data Dataverse — shown once because both records carry DOI 10.5683/sp3/1vmjag

Description

Please note that this dataset is not an official City of Toronto land use dataset. It was created for personal and academic use using City of Toronto Land Use Maps (2019) found on the City of Toronto Official Plan website at toronto.ca/city-government/planning-development/official-plan-guidelines/official-plan/official-plan-maps-copy, along with the City of Toronto parcel fabric (Property Boundaries) found at open.toronto.ca/dataset/property-boundaries/ and Statistics Canada Census Dissemination Blocks level boundary files (2016).

The property boundaries used were dated November 11, 2021. Further detail about the City of Toronto's Official Plan, consolidation of the information presented in its online form, and considerations for its interpretation can be found at toronto.ca/city-government/planning-development/official-plan-guidelines/official-plan/ Data Creation Documentation and Procedures Software Used The spatial vector data were created using ArcGIS Pro 2.9.0 in December 2021.

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PDF File Conversions Using Adobe Acrobat Pro DC software, the following downloaded PDF map images were converted to TIF format. 9028-cp-official-plan-Map-14_LandUse_AODA.pdf 9042-cp-official-plan-Map-22_LandUse_AODA.pdf 9070-cp-official-plan-Map-20_LandUse_AODA.pdf 908a-cp-official-plan-Map-13_LandUse_AODA.pdf 978e-cp-official-plan-Map-17_LandUse_AODA.pdf 97cc-cp-official-plan-Map-15_LandUse_AODA.pdf 97d4-cp-official-plan-Map-23_LandUse_AODA.pdf 97f2-cp-official-plan-Map-19_LandUse_AODA.pdf 97fe-cp-official-plan-Map-18_LandUse_AODA.pdf 9811-cp-official-plan-Map-16_LandUse_AODA.pdf 982d-cp-official-plan-Map-21_LandUse_AODA.pdf Georeferencing and Reprojecting Data Files The original projection of the PDF maps is unknown but were most likely published using MTM Zone 10 EPSG 2019 as per many of the City of Toronto's many datasets.

They could also have possibly been published in UTM Zone 17 EPSG 26917 The TIF images were georeferenced in ArcGIS Pro using this projection with very good results. The images were matched against the City of Toronto's Centreline dataset found here The resulting TIF files and their supporting spatial files include: TOLandUseMap13.tfwx TOLandUseMap13.tif TOLandUseMap13.tif.aux.xml TOLandUseMap13.tif.ovr TOLandUseMap14.tfwx TOLandUseMap14.tif TOLandUseMap14.tif.aux.xml TOLandUseMap14.tif.ovr TOLandUseMap15.tfwx TOLandUseMap15.tif TOLandUseMap15.tif.aux.xml TOLandUseMap15.tif.ovr TOLandUseMap16.tfwx TOLandUseMap16.tif TOLandUseMap16.tif.aux.xml TOLandUseMap16.tif.ovr TOLandUseMap17.tfwx TOLandUseMap17.tif TOLandUseMap17.tif.aux.xml TOLandUseMap17.tif.ovr TOLandUseMap18.tfwx TOLandUseMap18.tif TOLandUseMap18.tif.aux.xml TOLandUseMap18.tif.ovr TOLandUseMap19.tif TOLandUseMap19.tif.aux.xml TOLandUseMap19.tif.ovr TOLandUseMap20.tfwx TOLandUseMap20.tif TOLandUseMap20.tif.aux.xml TOLandUseMap20.tif.ovr TOLandUseMap21.tfwx TOLandUseMap21.tif TOLandUseMap21.tif.aux.xml TOLandUseMap21.tif.ovr TOLandUseMap22.tfwx TOLandUseMap22.tif TOLandUseMap22.tif.aux.xml TOLandUseMap22.tif.ovr TOLandUseMap23.tfwx TOLandUseMap23.tif TOLandUseMap23.tif.aux.xml TOLandUseMap23.tif.ov Ground control points were saved for all georeferenced images.

The files are the following: map13.txt map14.txt map15.txt map16.txt map17.txt map18.txt map19.txt map21.txt map22.txt map23.txt The City of Toronto's Property Boundaries shapefile, "property_bnds_gcc_wgs84.zip" were unzipped and also reprojected to EPSG 26917 (UTM Zone 17) into a new shapefile, "Property_Boundaries_UTM.shp" Mosaicing Images Once georeferenced, all images were then mosaiced into one image file, "LandUseMosaic20211220v01", within the project-generated Geodatabase, "Landuse.gdb" and exported TIF, "LandUseMosaic20211220.tif" Reclassifying Images Because the original images were of low quality and the conversion to TIF made the image colours even more inconsistent, a method was required to reclassify the images so that different land use classes could be identified.

Using Deep learning Objects, the images were re-classified into useful consistent colours. Deep Learning Objects and Training The resulting mosaic was then prepared for reclassification using the Label Objects for Deep Learning tool in ArcGIS Pro. A training sample, "LandUseTrainingSamples20211220", was created in the geodatabase for all land use types as follows: Neighbourhoods Insitutional Natural Areas Core Employment Areas Mixed Use Areas Apartment Neighbourhoods Parks Roads Utility Corridors Other Open Spaces General Employment Areas Regeneration Areas Lettering (not a land use type, but an image colour (black), used to label streets).

By identifying the letters, it then made the reclassification and vectorization results easier to clean up of unnecessary clutter caused by the labels of streets. Reclassification Once the training samples were created and saved, the raster was then reclassified using the Image Classification Wizard tool in ArcGIS Pro, using the Support Vector Machine Classifier method. The resulting reclassified image file, "LandUseClassifiedSupportVectorMethod20211220" (exported file "LandUseClassifiedSupportVectorMethod20211220.tif").

Vectorization The resulting reclassified image was then vectorized using the Raster to Polygon geoprocessing tool within ArcGIS Pro to create a vector file within the project geodatabase, "LandUseClassifiedRaster2Polygon20211220". Deleting unwanted classes All unwanted features classified "Class_name" = "Letters" were then deleted. Results were saved in a new file called "LandUseClassifiedRaster2PolygonLettersDeleted20211220" Spatial Overlays (spatial join) A spatial join was performed from the reprojected Property Boundaries layer, "Property_Boundaries_UTM" and the vector layer, "LandUseClassifiedRaster2PolygonLettersDeleted20211220".

The "Match Option" was set to "Largest Overlap". The resulting layer, "LandUseByParcel2019_2021v0120211221" was saved in the project geodatabase and exported to shapefile, "LandUseByParcel2019_2021v0120211221.shp" Census Land Use A second spatial join was performed on the "LanduseByParcel2019_2021v0120211221" feature layer to the Census of Canada Census Dissemination Blocks (2016) shapefile, "DLI_2016_Census_CBF_Eng_Nat_db.shp" The resulting layer, "LanduseByParcelsCensusIDs20211221", contains the land use category for every parcel in the City of Toronto as well as every larger census areas IDs and names each parcel falls within.

A bridge could therefore be built to create land use files for the city of Toronto at the following levels of Census of Canada Geographies: Dissemination Area Block (DBUID) Dissemination Area (DAUID) Census Tract (CTUID) Federal Electorial Districts (FEDUID) A new layer was created using this census information but with the unwanted "class_name", "NULL", "Utility Corridors" and "Roads" removed. The resulting layer was dissolved to the feature class, "LanduseParcelsMergedv0120220106" (exported to "LanduseParcelsMergedv0120220106.shp") by the "Class_name" attribute to provide large polygons of land use with which to spatially join to the Dissemination Block census boundary file.

This feature layer does not have the "class_name" values of "NULL", "Utility Corridors" and "Roads". The Census Dissemination block layer was then used in a spatial join using the "Match Option" set to "Largest overlap" to the "LanduseParcelsMergedv0120220106" layer to produce a Dissemination Block Census Boundary file with land use "class_name" attached. The file is called "DABlockWLandUseV0120220106" (exported to "DABlockWLandUseV0120220106.shp").

This Dissemination Block layer requires some further edits as the match is sometimes not always completely appropriate as the match appears to match the most parcels per block with a common class_name, rather than the largest amount of land taken up. See as an example DBUID 35204092002. The largest land use in the block is clearly "Institutional", but the operation assigned to the block area the class_name, "Neighbourhoods".

See images image01.jpg and image 02.jpg Symbolization Various ArcGIS Pro symbology format files are available (including for each shapefile), that match the colour of the original PDF maps.

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Provenance · 2 source records, 30 field assertions
SourceKeyLast seenRaw
Borealisdoi:10.5683/SP3/1VMJAG13 d agoJSON v1
Agri-environmental Research Data Dataversedoi:10.5683/SP3/1VMJAG11 d agoJSON v1
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