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TwitterAttribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
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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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TwitterIndex grid for Toronto Property Data Maps (PDM), 2013.
This series combines topography and parcel mapping, and provides a base for thematic mapping services and other published hardcopy products. Depicts the following features: building envelopes, building outlines, railway lines, major watercourses, municipal addresses, curbs, park names, street names, property lines, right of way, boundaries, etc.
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TwitterThe data layer shows the sign district designations of all properties in the City of Toronto - the sign bylaw regulations/permissions/restrictions that are applicable to each property in the city are based on its sign district designation. The data is used in conjunction with a City of Toronto map so that individual properties can be searched by address or through a zoom tool. The city provides this data to the public through an online mapping and search tool at: https://map.toronto.ca/maps/map.jsp?app=SignView_2
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TwitterToronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials, and transportation, it has played an important role in the city’s settlement and development. The river valley has changed dramatically in the years since European settlement, particularly during the late nineteenth and early twentieth century, when the Lower Don River was straightened and channelized and the huge marsh at its mouth drained and filled. Today, the Lower Valley forms the foundation for one of the most densely populated areas in Canada, outlining as it does the eastern portion of Toronto’s downtown core and radiating residential areas. This project documents historical changes in the landscape of the Don River Valley. Drawing from the wide range of geographical information available for the Don River watershed (and the Lower Don in particular), including historical maps, geological maps, fire insurance plans, planning documents, and city directories, the project uses Geographic Information Systems software to place, compile, synthesize and interpret this information and make it more accessible as geospatial data and maps. The project is a work in progress. To date, we have scanned several dozen historical maps of Toronto and the Don River watershed, and compiled the following geospatial datasets: 1) changes to the river channel and shoreline of Toronto harbour, 1858-1918; 2) industrial development in the Lower Don River Watershed, 1857-1951 (as points, and in some cases polygons); 3) historical mill sites in the Don River Watershed, 1825; 18524) land ownership in the watershed, 1860 and 1878; and 4) points of interest in the watershed. In the future, we hope to expand the project to include data from other Toronto area watersheds and other parts of the city. The project was conducted through a collaboration between Jennifer Bonnell, a doctoral student in the History of Education program at the University of Toronto's Ontario Institute for Studies in Education (OISE/UT) - now at York University in the History Department and Marcel Fortin, the Geographic Information Systems (GIS) and Map Librarian at the University of Toronto's Map and Data Library. Financial and in-kind support was provided by the Network in Canadian History and Environment (NiCHE) and the University of Toronto Libraries. Valuable research support for the Points of Interest pages came from Lost Rivers, a community-based urban ecology organization focused on building public awareness of the City's river systems. Jordan Hale, a University of Toronto Geography student conducted much of the digitization and database work.This project could not have been completed without their skilled assistance and dedication.
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TwitterAttribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
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This dataset is derived from the 2003 PDF map by the City of Toronto depicting building construction dates by parcels. The 2021 Toronto Parcels were used to attach the built date. Please Note: This is not an official City of Toronto dataset and should be used for reference, teaching and consultation purposes only and not for analysis
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TwitterExploring new ways to share information with each other is a cornerstone of improving the planning process. To do this it is essential to have city-wide data in accessible formats. A variety of 3D digital information and models exist but currently the data is not readily available to the general public. Providing a consistent city-wide 3D data source will link these digital city planning models and materials together and will allow us to imagine our city from different perspectives. The Open Data site will enable access to application developers, designers, urban planners and architects, and the public. Ideally this will enable the creation of a visual portal and access to a large collection of city building ideas. Further to the Open Government Licence, the Context Massing Model is being provided by City Planning on the Open Data website for information and illustrative purposes only. City Planning does not warranty the completeness, accuracy, content, or fitness for any precision purpose or use of context massing model for such purposes, nor are any such warranties to be implied or inferred with respect to Context Massing Model as furnished on the website. City Planning and the City are not liable for any deficiencies in the completeness, accuracy, content, or fitness for any particular purpose or use of Context Massing Model, or applications utilizing Context Massing Model, provided by any third party. Context Massing Model MUST BE VERIFIED BY THE USER FOR LEGAL OR OFFICIAL USE. Please use this Interactive Map to locate the 3D Massing tiles for SketchUp and AutoCAD format For further information visit the Urban Design web site A note on property assessments: MPAC (Municipal Property Assessment Corporation) holds copyright on many aspects of data around properties. The City of Toronto is unable to provide this data. From the MPAC website: MPAC 's range of services includes: Preparing annual Assessment Rolls for use by municipalities and the Province to calculate property and education taxes. Assessment Maps and Ontario Parcel (TM) In 2005, MPAC, the Ontario Government and Teranet Enterprises Inc. completed the Ontario Parcel(TM) - an ambitious project that brings assessment, ownership and land parcel data for almost 4.6 million properties into a standardized digital database. ... The Ontario Parcel(TM) is available to Ontario municipalities, public organizations and private businesses. Among other things, the Ontario Parcel(TM) data can be applied to property assessment and taxation, land registration, land use planning, land management and business planning. With the implementation of the Ontario Parcel (TM) and the digital mapping environment, MPAC no longer produces paper assessment maps. If you would like more information about the products and services available under the Ontario Parcel (TM), please visit the Ontario Parcel (TM) website at www.ontarioparcel.ca. You will need to contact MPAC directly for data that you may perceive as missing. MPAC website.
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TwitterThis 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
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TwitterDerived from: Toronto Harbour Commission land surveys and former City of Toronto property data maps available through the University of Toronto Data and Map Library; municipal property assessments from the City of Toronto Archives; land transfer agreements from the Archives of Ontario; as well as several data sources generously provided by Waterfront Toronto and the Toronto Port Authority. Full source information included as separate text file. Contact Gabriel Eidelman g.eidelman@utoronto.ca Department of Political Science, University of Toronto for further details. historical land use
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TwitterContains the boundary of the Town of Caledon and the Cities of Brampton and Mississauga, the three of which collectively constitute the Region of Peel. The Region of Peel has regional municipal jurisdiction within, and only within, the larger boundary; individual municipalities have jurisdiction within, and only within, their respective boundaries.There is a division of powers and responsibilities between these 3 municipalities, referred to by the Province as "lower tier municipalities", and the Region of Peel (referred to by the Province as an "upper tier municipality").A recent update to the data includes new land added along Lake Ontario near the boundary with Toronto.
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TwitterAttribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
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This map is part of the Map and Data Centre Collections, and is available for physical viewing under the call number C33 D04. Explore the item in our Library Catalogue: Collection Permalink Publication Date: 1893 Publisher Location: Toronto, Ont. Publisher: Toronto Lithographing Co. Geographic Area: London (Ont.) Map Theme: Business enterprises Description: Hand-drawn, colour map of London Ontario with inset drawings of the building fronts of local companies. Physical Size: 94 x 69 cm
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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...