7 datasets found
  1. B

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

    • borealisdata.ca
    • dataone.org
    Updated Feb 23, 2023
    + more versions
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    Marcel Fortin (2023). Toronto Land Use Spatial Data - parcel-level - (2019-2021) [Dataset]. http://doi.org/10.5683/SP3/1VMJAG
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 23, 2023
    Dataset provided by
    Borealis
    Authors
    Marcel Fortin
    License

    Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
    License information was derived automatically

    Area covered
    Toronto
    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 https://www.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 https://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 https://www.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. 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...

  2. a

    Toronto Zoning per Neighbourhood

    • edu.hub.arcgis.com
    Updated Jul 7, 2015
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    Education and Research (2015). Toronto Zoning per Neighbourhood [Dataset]. https://edu.hub.arcgis.com/maps/af06159170914808983959df6163fc86
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    Dataset updated
    Jul 7, 2015
    Dataset authored and provided by
    Education and Research
    Area covered
    Description
  3. a

    ZONING HEIGHT

    • edu.hub.arcgis.com
    Updated Apr 3, 2019
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    Education and Research (2019). ZONING HEIGHT [Dataset]. https://edu.hub.arcgis.com/datasets/zoning-height
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    Dataset updated
    Apr 3, 2019
    Dataset authored and provided by
    Education and Research
    Area covered
    Description

    This dataset contains data that are part of the Zoning By-law 569-2013, was approved by Council but it is still subject to an Ontario Municipal Board (OMB) hearing for final approval.The Zoning By-law team is responsible for the revising the city-wide zoning bylaw. Zoning bylaws regulate the use, size, height, density and location of buildings on properties and affect every property in the City.Data Source: Open Data Toronto: https://www.toronto.ca/city-government/data-research-maps/open-data/open-data-catalogue/#8fef077c-9a14-e922-0c57-f390cd68b8a0Data Owner: City PlanningCurrency (as of upload): September 2014

  4. g

    Ottawa and Toronto | gimi9.com

    • gimi9.com
    Updated Apr 21, 2012
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    (2012). Ottawa and Toronto | gimi9.com [Dataset]. https://gimi9.com/dataset/ca_85b6ef22-d013-52e4-87fd-26bb57899499/
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    Dataset updated
    Apr 21, 2012
    Area covered
    Ottawa, Toronto
    Description

    Contained within the 3rd Edition (1957) of the Atlas of Canada is a map that shows a map with four condensed maps of the cities Toronto and Ottawa. The first two maps show the extent and classification of land use circa 1955 for both Toronto and Ottawa. For Toronto, stages of urban growth are shown for periods ranging from 1793 to 1955 and for Ottawa, the periods range from 1826 to 1955. The urban growth maps represent the expansion of areas occupied by structures, yet the small open areas classified as parks and playgrounds on the land-use maps are also included. These two remaining maps show the extent and classification of land use for both of these cities. The classifications for land-use maps were separated into: Industrial buildings; Industrial yards; Commercial buildings; Commercial yards; Railways and their installations; Institutional buildings; Residential buildings; Cemeteries; Dominantly farm land; Vacant land. In areas classified as dominantly farm land, vacant land includes forested areas, swamps, bogs and all large areas not put to specific agricultural use.

  5. Ottawa and Toronto

    • open.canada.ca
    • datasets.ai
    jpg, pdf
    Updated Mar 14, 2022
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    Natural Resources Canada (2022). Ottawa and Toronto [Dataset]. https://open.canada.ca/data/en/dataset/85b6ef22-d013-52e4-87fd-26bb57899499
    Explore at:
    pdf, jpgAvailable download formats
    Dataset updated
    Mar 14, 2022
    Dataset provided by
    Ministry of Natural Resources of Canadahttps://www.nrcan.gc.ca/
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Area covered
    Toronto, Ottawa
    Description

    Contained within the 3rd Edition (1957) of the Atlas of Canada is a map that shows a map with four condensed maps of the cities Toronto and Ottawa. The first two maps show the extent and classification of land use circa 1955 for both Toronto and Ottawa. For Toronto, stages of urban growth are shown for periods ranging from 1793 to 1955 and for Ottawa, the periods range from 1826 to 1955. The urban growth maps represent the expansion of areas occupied by structures, yet the small open areas classified as parks and playgrounds on the land-use maps are also included. These two remaining maps show the extent and classification of land use for both of these cities. The classifications for land-use maps were separated into: Industrial buildings; Industrial yards; Commercial buildings; Commercial yards; Railways and their installations; Institutional buildings; Residential buildings; Cemeteries; Dominantly farm land; Vacant land. In areas classified as dominantly farm land, vacant land includes forested areas, swamps, bogs and all large areas not put to specific agricultural use.

  6. u

    Ottawa and Toronto - Catalogue - Canadian Urban Data Catalogue (CUDC)

    • data.urbandatacentre.ca
    • beta.data.urbandatacentre.ca
    Updated Oct 1, 2024
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    (2024). Ottawa and Toronto - Catalogue - Canadian Urban Data Catalogue (CUDC) [Dataset]. https://data.urbandatacentre.ca/dataset/gov-canada-85b6ef22-d013-52e4-87fd-26bb57899499
    Explore at:
    Dataset updated
    Oct 1, 2024
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Area covered
    Canada, Toronto, Ottawa
    Description

    Contained within the 3rd Edition (1957) of the Atlas of Canada is a map that shows a map with four condensed maps of the cities Toronto and Ottawa. The first two maps show the extent and classification of land use circa 1955 for both Toronto and Ottawa. For Toronto, stages of urban growth are shown for periods ranging from 1793 to 1955 and for Ottawa, the periods range from 1826 to 1955. The urban growth maps represent the expansion of areas occupied by structures, yet the small open areas classified as parks and playgrounds on the land-use maps are also included. These two remaining maps show the extent and classification of land use for both of these cities. The classifications for land-use maps were separated into: Industrial buildings; Industrial yards; Commercial buildings; Commercial yards; Railways and their installations; Institutional buildings; Residential buildings; Cemeteries; Dominantly farm land; Vacant land. In areas classified as dominantly farm land, vacant land includes forested areas, swamps, bogs and all large areas not put to specific agricultural use.

  7. a

    Generalized Land Use 1954

    • hub.arcgis.com
    • data.peelregion.ca
    Updated Aug 7, 2014
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    Regional Municipality of Peel (2014). Generalized Land Use 1954 [Dataset]. https://hub.arcgis.com/maps/RegionofPeel::generalized-land-use-1954
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    Dataset updated
    Aug 7, 2014
    Dataset authored and provided by
    Regional Municipality of Peel
    License

    https://data.peelregion.ca/pages/licensehttps://data.peelregion.ca/pages/license

    Area covered
    Description

    The generalised land use was created from 1954 aerial imagery (2.5m) available from the University of Toronto map library (resource here). These images were georeferenced and areas were clipped out. While not as exact as newer GLU years, it provides a useful historical view of Peel County before its explosive growth in the following decades. The shoreline of Peel was cut along the shoreline as it was in the 1954 imagery, which predated some of the heavy industrial land uses that reshaped the shore (for example, Lakeview Generating Station). The outer boundary is also different than the present-day boundary, as there were various changes to the boundary when Peel County was converted into Peel Region in 1974 and subsequent land exchanges took place with neighbouring municipalities such as Orangeville and Halton.

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Marcel Fortin (2023). Toronto Land Use Spatial Data - parcel-level - (2019-2021) [Dataset]. http://doi.org/10.5683/SP3/1VMJAG

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

Explore at:
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Feb 23, 2023
Dataset provided by
Borealis
Authors
Marcel Fortin
License

Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
License information was derived automatically

Area covered
Toronto
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 https://www.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 https://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 https://www.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. 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...

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