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... Visit https://dataone.org/datasets/sha256%3A3e3f055bf6281f979484f847d0ed5eeb96143a369592149328c370fe5776742b for complete metadata about this dataset.
Improving access to TRCA’s data and information will provide transparency into the decision making process and will improve accountability while increasing the public’s understanding and engagement with the organization [Toronto and Region Conservation Authority]
https://www.ontario.ca/page/open-government-licence-ontariohttps://www.ontario.ca/page/open-government-licence-ontario
Zoom in on the map above and click your area of interest to determine which package(s) you require for download.
A three-dimensional raster data set which represents a continuous elevation surface. This data set encompasses the Greater Toronto Area (GTA) and the surrounding area from Niagara to Lake Simcoe and the Kawartha Highlands to Port Hope. The Digital Elevation Model (DEM) data is organized into 20km x 20km tiles with a spatial resolution of 5m.
This data is intended to be used for pre-engineering survey and design as well as the production of planimetric mapping at differing accuracies.
This data is intended for GIS and remote sensing application that require a high resolution, high accuracy elevation model.
The source data for the GTA 2002 DEM can be found in the Ontario Mass Points and Breaklines.
Product Packages
GTA 2002 DEM - North East GTA 2002 DEM - North West GTA 2002 DEM - South West
Additional Documentation
GTA DEM 2002 - User Guide (Word)
GTA 2002 DEM Tile Index (.Zip)
Status
Completed: Production of the data has been completed
Maintenance and Update Frequency
Not planned: there are no plans to update the data
Contact
Ontario Ministry of Natural Resources - Geospatial Ontario, geospatial@ontario.ca
Datasets from the City of Toronto Open Data - Data Catalogue. Date: June 6, 2014 (Neighbourhoods) and December 17, 2014 (Demographics) Website: http://www.toronto.ca/demographics/neighbourhoods.htm and http://www1.toronto.ca/wps/portal/contentonly?vgnextoid=4482904ade9ea410VgnVCM10000071d60f89RCRD Contact: Open Data Team, opendata@toronto.ca
This data was collected for planning and mapping purposes and includes all intersections within the City of Toronto. This data set is limited to the City of Toronto geographical boundary. It is a GIS file and works best when you open it with GIS software and overlay it with the City of Toronto Street Centreline.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
The Digital Elevation Model (DEM) data is organized into 20km x 20km tiles with a spatial resolution of 5m. This data is intended to be used for pre-engineering survey and design as well as the production of planimetric mapping at differing accuracies. This data is intended for GIS and remote sensing application that require a high resolution, high accuracy elevation model. Official GEO title: Greater Toronto Area digital elevation model 2002 *[DEM]: Digital Elevation Model
This data was collected for planning and mapping purposes and includes all intersections within the City of Toronto. This data set is limited to the City of Toronto geographical boundary. It is a GIS file and works best when you open it with GIS software and overlay it with the City of Toronto Street Centreline.
Discover Barrie GeoHub Site is a centralized starting point to access all spatial and related information about the City of Barrie. From here navigate yourself around the City of Barrie through interactive web mapping applications, view static maps of the City, download and leverage GIS data in the Open Data page and use City information in our own applications by downloading it through connecting in the Web Services page, The City of Barrie is situated in the heart of Central Ontario, a premier waterfront community on Lake Simcoe, conveniently located an hour north of Toronto. Visit barrie.ca for more information or contact Service Barrie at 705-726-4242 or ServiceBarrie@barrie.caDO NOT DELETE OR MODIFY THIS ITEM. This item is managed by the ArcGIS Hub application. To make changes to this site, please visit https://hub.arcgis.com/admin/sites
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
The High Resolution Digital Elevation Model (HRDEM) product is derived from airborne LiDAR data (mainly in the south) and satellite images in the north. The complete coverage of the Canadian territory is gradually being established. It includes a Digital Terrain Model (DTM), a Digital Surface Model (DSM) and other derived data. For DTM datasets, derived data available are slope, aspect, shaded relief, color relief and color shaded relief maps and for DSM datasets, derived data available are shaded relief, color relief and color shaded relief maps. The productive forest line is used to separate the northern and the southern parts of the country. This line is approximate and may change based on requirements. In the southern part of the country (south of the productive forest line), DTM and DSM datasets are generated from airborne LiDAR data. They are offered at a 1 m or 2 m resolution and projected to the UTM NAD83 (CSRS) coordinate system and the corresponding zones. The datasets at a 1 m resolution cover an area of 10 km x 10 km while datasets at a 2 m resolution cover an area of 20 km by 20 km. In the northern part of the country (north of the productive forest line), due to the low density of vegetation and infrastructure, only DSM datasets are generally generated. Most of these datasets have optical digital images as their source data. They are generated at a 2 m resolution using the Polar Stereographic North coordinate system referenced to WGS84 horizontal datum or UTM NAD83 (CSRS) coordinate system. Each dataset covers an area of 50 km by 50 km. For some locations in the north, DSM and DTM datasets can also be generated from airborne LiDAR data. In this case, these products will be generated with the same specifications as those generated from airborne LiDAR in the southern part of the country. The HRDEM product is referenced to the Canadian Geodetic Vertical Datum of 2013 (CGVD2013), which is now the reference standard for heights across Canada. Source data for HRDEM datasets is acquired through multiple projects with different partners. Since data is being acquired by project, there is no integration or edgematching done between projects. The tiles are aligned within each project. The product High Resolution Digital Elevation Model (HRDEM) is part of the CanElevation Series created in support to the National Elevation Data Strategy implemented by NRCan. Collaboration is a key factor to the success of the National Elevation Data Strategy. Refer to the “Supporting Document” section to access the list of the different partners including links to their respective data.
Ravine & Natural Feature Protection area and limit as regulated by City of Toronto Municipal Code Chapter 658 - Ravine & Natural Feature Protection. Please note: Dataset is limited to the City of Toronto geographical boundary. Dataset works best if you open it with GIS/CAD software and reference these layers: City of Toronto Street Centreline, Address Points and Property Boundaries. If your original design drawing has been created without a coordinate system, you will need to reference the city's datasets and then move, scale and/or rotate your data to line up with the property limits for the property you are working with.
Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
License information was derived automatically
Data used to make the Disappearing Rivers web map. Includes historical maps, and GIS data for digitized rivers. This data, and the webmap, were developed through a partnership between the Lost Rivers project, and Geohistory-Géohistoire Canada. More information about the web-mapping project is available here.
This dataset includes all break and enter occurrences by reported date and related offences since 2014.Break and Enter DashboardDownload DocumentationThis data is provided at the offence and/or victim level, therefore one occurrence number may have several rows of data associated to the various MCIs used to categorize the occurrence.The downloadable datasets display the REPORT_DATE and OCC_DATE fields in UTC timezone.This data does not include occurrences that have been deemed unfounded. The definition of unfounded according to Statistics Canada is: “It has been determined through police investigation that the offence reported did not occur, nor was it attempted” (Statistics Canada, 2020).**The dataset is intended to provide communities with information regarding public safety and awareness. The data supplied to the Toronto Police Service by the reporting parties is preliminary and may not have been fully verified at the time of publishing the dataset. The location of crime occurrences have been deliberately offset to the nearest road intersection node to protect the privacy of parties involved in the occurrence. All location data must be considered as an approximate location of the occurrence and users are advised not to interpret any of these locations as related to a specific address or individual.NOTE: Due to the offset of occurrence location, the numbers by Division and Neighbourhood may not reflect the exact count of occurrences reported within these geographies. Therefore, the Toronto Police Service does not guarantee the accuracy, completeness, timeliness of the data and it should not be compared to any other source of crime data.By accessing these datasets, the user agrees to full acknowledgement of the Open Government Licence - Ontario.In accordance with the Municipal Freedom of Information and Protection of Privacy Act, the Toronto Police Service has taken the necessary measures to protect the privacy of individuals involved in the reported occurrences. No personal information related to any of the parties involved in the occurrence will be released as open data. ** Statistics Canada. 2020. Uniform Crime Reporting Manual. Surveys and Statistical Programs. Canadian Centre for Justice Statistics.
Debbie Verduga and Gaya Ganesan, Toronto Police ServiceThe Toronto Police Service promotes the use of crime and traffic open data through academic engagement at all levels of education. The service’s Public Safety Data Portal is a great resource for a wide range of users including students, teachers, researchers, media and all members of the public for accessing public safety information. Users can download open datasets for analysis related to crimes and traffic collisions, visualize information though interactive dashboards and view web-mapping applications.This session is suitable for both beginners and advanced users of ArcGIS.
This dataset includes all theft over occurrences by reported date and related offences since 2014.Theft Over DashboardDownload DocumentationThis data is provided at the offence and/or victim level, therefore one occurrence number may have several rows of data associated to the various MCIs used to categorize the occurrence.The downloadable datasets display the REPORT_DATE and OCC_DATE fields in UTC timezone.This data does not include occurrences that have been deemed unfounded. The definition of unfounded according to Statistics Canada is: “It has been determined through police investigation that the offence reported did not occur, nor was it attempted” (Statistics Canada, 2020).**The dataset is intended to provide communities with information regarding public safety and awareness. The data supplied to the Toronto Police Service by the reporting parties is preliminary and may not have been fully verified at the time of publishing the dataset. The location of crime occurrences have been deliberately offset to the nearest road intersection node to protect the privacy of parties involved in the occurrence. All location data must be considered as an approximate location of the occurrence and users are advised not to interpret any of these locations as related to a specific address or individual.NOTE: Due to the offset of occurrence location, the numbers by Division and Neighbourhood may not reflect the exact count of occurrences reported within these geographies. Therefore, the Toronto Police Service does not guarantee the accuracy, completeness, timeliness of the data and it should not be compared to any other source of crime data.By accessing these datasets, the user agrees to full acknowledgement of the Open Government Licence - Ontario.In accordance with the Municipal Freedom of Information and Protection of Privacy Act, the Toronto Police Service has taken the necessary measures to protect the privacy of individuals involved in the reported occurrences. No personal information related to any of the parties involved in the occurrence will be released as open data. ** Statistics Canada. 2020. Uniform Crime Reporting Manual. Surveys and Statistical Programs. Canadian Centre for Justice Statistics.
Summary of the City of Toronto Zoning, summarized by neighbourhood. Courtesy of the City of Toronto Open Data team (opendata@toronto.ca) Zoning: http://www1.toronto.ca/wps/portal/contentonly?vgnextoid=5a9923e69b4a6410VgnVCM10000071d60f89RCRD&vgnextchannel=1a66e03bb8d1e310VgnVCM10000071d60f89RCRD Neighbourhoods: http://www1.toronto.ca/wps/portal/contentonly?vgnextoid=04b489fe9c18b210VgnVCM1000003dd60f89RCRD&vgnextchannel=1a66e03bb8d1e310VgnVCM10000071d60f89RCRD
This dataset includes all Persons in Crisis (PIC) calls for service attended (CFSA) from 2014 which includes the following Event Types: Attempt Suicide, Person in Crisis, Elopee, Overdose and Threaten Suicide. To protect the privacy of individuals involved in Calls for Service, these Event Types have been aggregated into Person in Crisis calls (Person in Crisis, Elopee), Suicide-related calls (Attempt Suicide, Threaten Suicide), and Overdose calls. This dataset includes only events that were attended by an officer of the Toronto Police Service (TPS), but excludes events attended by TPS members in Parking, Marine, Court or Primary Report Intake Management and Entry (PRIME). This dataset is queried based on event date.The downloadable datasets display the EVENT_DATE field in UTC timezone.Note: Fields have been included for both the old 140 City of Toronto Neighbourhoods structure as well as the new 158 City of Toronto Neighbourhoods structure.
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Zoom in on the map above and click your area of interest or use the Tile Index linked below to determine which package(s) you require for download.The DTM data is available in the form of 1-km by 1-km non-overlapping tiles grouped into packages for download.This dataset is a compilation of lidar data from multiple acquisition projects, as such specifications, parameters and sensors may vary by project. See the detailed User Guide linked below for additional information. You can monitor the availability and status of lidar projects on the Ontario Lidar Coverage map on the Ontario Elevation Mapping Program hub page. Now also available through a web service which exposes the data for visualization, geoprocessing and limited download. The service is best accessed through the ArcGIS REST API, either directly or by setting up an ArcGIS server connection using the REST endpoint URL. The service draws using the Web Mercator projection. For more information on what functionality is available and how to work with the service, read the Ontario Web Raster Services User Guide. If you have questions about how to use the service, email Geospatial Ontario (GEO) at geospatial@ontario.ca.Service Endpointshttps://ws.geoservices.lrc.gov.on.ca/arcgis5/rest/services/Elevation/Ontario_DTM_LidarDerived/ImageServer https://intra.ws.geoservices.lrc.gov.on.ca/arcgis5/rest/services/Elevation/Ontario_DTM_LidarDerived/ImageServer (Government of Ontario Internal Users)Additional Documentation Ontario DTM (Lidar-Derived) - User Guide (DOCX) OMAFRA Lidar 2016-2018 - Cochrane - Additional Contractor Metadata (PDF)OMAFRA Lidar 2016-2018 - Peterborough - Additional Contractor Metadata (PDF)OMAFRA Lidar 2016-2018 - Lake Erie - Additional Contractor Metadata (PDF)CLOCA Lidar 2018 - Additional Contractor Metadata (PDF)South Nation Lidar 2018-19 - Additional Contractor Metadata (PDF)OMAFRA Lidar 2022 - Lake Huron - Additional Contractor Metadata (PDF)OMAFRA Lidar 2022 - Lake Simcoe - Additional Contractor Metadata (PDF)Huron-Georgian Lidar 2022-23 - Additional Contractor Metadata (Word)Kawartha Lakes Lidar 2023 - Additional Contractor Metadata (Word)Sault Ste Marie Lidar 2023-24 - Additional Contractor Metadata (Word)Thunder Bay Lidar 2023-24 - Additional Contractor Metadata (Word)Timmins Lidar 2024 - Additional Contractor Metadata (Word) Ontario DTM (Lidar-Derived) - Tile Index (SHP) Ontario Lidar Project Extents (SHP)OMAFRA Lidar DTM 2016-2018 - Cochrane - Breaklines (SHP)OMAFRA Lidar DTM 2016-2018 - Peterborough - Breaklines (SHP)OMAFRA Lidar DTM 2016-2018 - Lake Erie - Breaklines (SHP)CLOCA Lidar DTM 2018 - Breaklines (SHP)South Nation Lidar DTM 2018-19 - Breaklines (SHP)Ottawa-Gatineau Lidar DTM 2019-20 - Breaklines (SHP)OMAFRA Lidar DTM 2022 - Lake Huron - Breaklines (SHP)OMAFRA Lidar DTM 2022 - Lake Simcoe - Breaklines (SHP)Eastern Ontario Lidar DTM 2021-22 - Breaklines (SHP)Muskoka Lidar DTM 2018 - Breaklines CGVD2013 (SHP) / CGVD28 (SHP)Muskoka Lidar DTM 2021 - Breaklines CGVD2013 (SHP) / CGVD28 (SHP)Muskoka Lidar DTM 2023 - Breaklines CGVD2013 (SHP) / CGVD28 (SHP)DEDSFM Huron-Georgian Bay 2022-23 - Breaklines (SHP)DEDSFM Kawartha Lakes 2023 - Breaklines (SHP)DEDSFM Sault Ste Marie 2023-24- UTM16 - Breaklines (SHP)DEDSFM Sault Ste Marie 2023-24- UTM17 - Breaklines (SHP)DEDSFM Sudbury 2023-24 - Breaklines (SHP)DEDSFM Thunder Bay 2023-24 - Breaklines (SHP)DEDSFM Timmins 2024 - Breaklines (SHP)Product PackagesDownload links for the Ontario DTM (Lidar-Derived) (Word)Projects:LEAP 2009GTA 2014-18OMAFRA 2016-18CLOCA 2018South Nation CA 2018-19Muskoka 2018-23York-Lake Simcoe 2019Ottawa River 2019-20Ottawa-Gatineau 2019-20Lake Nipissing 2020Hamilton-Niagara 2021Huron Shores 2021Eastern Ontario 2021-22OMAFRA Lake Huron 2022OMAFRA Lake Simcoe 2022Belleville 2022Digital Elevation Data to Support Flood Mapping 2022-26Huron-Georgian Bay 2022-23Kawartha Lakes 2023Sault Ste Marie 2023-24Sudbury 2023-24Thunder Bay 2023-24Timmins 2024Cataraqui 2024Greater Toronto Area Lidar 2023StatusOn going: Data is continually being updatedMaintenance and Update FrequencyAs needed: Data is updated as deemed necessaryContactOntario Ministry of Natural Resources - Geospatial Ontario, geospatial@ontario.ca
This dataset includes all assault occurrences by reported date and related offences since 2014.Assault DashboardDownload DocumentationThis data is provided at the offence and/or victim level, therefore one occurrence number may have several rows of data associated to the various MCIs used to categorize the occurrence.The downloadable datasets display the REPORT_DATE and OCC_DATE fields in UTC timezone.This data does not include occurrences that have been deemed unfounded. The definition of unfounded according to Statistics Canada is: “It has been determined through police investigation that the offence reported did not occur, nor was it attempted” (Statistics Canada, 2020).**The dataset is intended to provide communities with information regarding public safety and awareness. The data supplied to the Toronto Police Service by the reporting parties is preliminary and may not have been fully verified at the time of publishing the dataset. The location of crime occurrences have been deliberately offset to the nearest road intersection node to protect the privacy of parties involved in the occurrence. All location data must be considered as an approximate location of the occurrence and users are advised not to interpret any of these locations as related to a specific address or individual.NOTE: Due to the offset of occurrence location, the numbers by Division and Neighbourhood may not reflect the exact count of occurrences reported within these geographies. Therefore, the Toronto Police Service does not guarantee the accuracy, completeness, timeliness of the data and it should not be compared to any other source of crime data.By accessing these datasets, the user agrees to full acknowledgement of the Open Government Licence - Ontario.In accordance with the Municipal Freedom of Information and Protection of Privacy Act, the Toronto Police Service has taken the necessary measures to protect the privacy of individuals involved in the reported occurrences. No personal information related to any of the parties involved in the occurrence will be released as open data. ** Statistics Canada. 2020. Uniform Crime Reporting Manual. Surveys and Statistical Programs. Canadian Centre for Justice Statistics.
This dataset includes all Homicides since 2004. Divisional association to each homicide is based on current Police Divisional Boundary. Divisional Boundary changes took effect in 2011. The downloadable datasets display the OCC_DATE fields in UTC timezone.Homicide DashboardDownload DocumentationThe dataset is intended to provide communities with information regarding public safety and awareness. The data supplied to the Toronto Police Service by the reporting parties is preliminary and may not have been fully verified at the time of publishing the dataset.The location of crime occurrences have been deliberately offset to the nearest road intersection node to protect the privacy of parties involved in the occurrence. All location data must be considered as an approximate location of the occurrence and users are advised not to interpret any of these locations as related to a specific address or individual.NOTE: Due to the offset of occurrence location, the numbers by Division and Neighbourhood may not reflect the exact count of occurrences reported within these geographies. Therefore, the Toronto Police Service does not guarantee the accuracy, completeness, timeliness of the data and it should not be compared to any other source of crime data.By accessing these datasets, the user agrees to full acknowledgement of the Open Government Licence - Ontario.In accordance with the Municipal Freedom of Information and Protection of Privacy Act, the Toronto Police Service has taken the necessary measures to protect the privacy of individuals involved in the reported occurrences. No personal information related to any of the parties involved in the occurrence will be released as open data.
This dataset includes all auto theft occurrences by reported date and related offences since 2014.Auto Theft DashboardDownload DocumentationThis data is provided at the offence and/or vehicle level, therefore one occurrence number may have several rows of data associated to the various MCIs used to categorize the occurrence.The downloadable datasets display the REPORT_DATE and OCC_DATE fields in UTC timezone.This data does not include occurrences that have been deemed unfounded. The definition of unfounded according to Statistics Canada is: “It has been determined through police investigation that the offence reported did not occur, nor was it attempted” (Statistics Canada, 2020).**The dataset is intended to provide communities with information regarding public safety and awareness. The data supplied to the Toronto Police Service by the reporting parties is preliminary and may not have been fully verified at the time of publishing the dataset. The location of crime occurrences have been deliberately offset to the nearest road intersection node to protect the privacy of parties involved in the occurrence. All location data must be considered as an approximate location of the occurrence and users are advised not to interpret any of these locations as related to a specific address or individual.NOTE: Due to the offset of occurrence location, the numbers by Division and Neighbourhood may not reflect the exact count of occurrences reported within these geographies. Therefore, the Toronto Police Service does not guarantee the accuracy, completeness, timeliness of the data and it should not be compared to any other source of crime data.By accessing these datasets, the user agrees to full acknowledgement of the Open Government Licence - Ontario.In accordance with the Municipal Freedom of Information and Protection of Privacy Act, the Toronto Police Service has taken the necessary measures to protect the privacy of individuals involved in the reported occurrences. No personal information related to any of the parties involved in the occurrence will be released as open data. ** Statistics Canada. 2020. Uniform Crime Reporting Manual. Surveys and Statistical Programs. Canadian Centre for Justice Statistics.
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... Visit https://dataone.org/datasets/sha256%3A3e3f055bf6281f979484f847d0ed5eeb96143a369592149328c370fe5776742b for complete metadata about this dataset.