The Census of Population is held across Canada every 5 years and collects data about age and sex, families and households, language, immigration and internal migration, ethnocultural diversity, Aboriginal peoples, housing, education, income, and labour. City of Toronto Neighbourhood Profiles use this Census data to provide a portrait of the demographic, social and economic characteristics of the people and households in each City of Toronto neighbourhood. The profiles present selected highlights from the data, but these accompanying data files provide the full data set assembled for each neighbourhood. For an interactive visualization of this data, visit the Neighbourhood Profiles webpage. In these profiles, "neighbourhood" refers to the City of Toronto's 158 social planning neighbourhoods. These social planning neighbourhoods were developed in the late 1990s by the City of Toronto to help government and community organizations with local planning by providing socio-economic data at a meaningful geographic area. The boundaries of these social planning neighbourhoods are consistent over time, allowing for comparison between Census years. Neighbourhood level indicators from sources other than the Census of Population are also available through the City's Wellbeing Toronto mapping application and here on the Open Data portal. Each data point in this file is presented for the City's 158 neighbourhoods or 140 neighbourhoods prior to April 2021. The data is sourced from a number of Census tables released by Statistics Canada. The general Census Profile is the main source table for this data. Data tables are available for the Census years of 2001, 2006, 2011, 2016, and 2021. For definitions of terms and concepts referenced in this data set, as well as limitations imposed by rounding, data suppression standards, and geometry, users should consult the reference materials produced by Statistics Canada for the 2016 Census or the 2021 Census. Please note that social planning neighbourhoods are not an official standard geography produced by Statistics Canada and the data herein is compiled by special request through the Community Data Program.

Neighbourhood Improvement Areas are specially-selected and designated neighbourhoods in the City of Toronto found to have inequities on several indicators of well-being. Currently 31 out of 140 neighbourhoods are designated as NIAs as part of the Toronto Strong Neighbourhoods 2020 (TSNS2020) project. This dataset superceded the previous 13 Priority Areas in April 2014. For further details please read the technical documentation found in the download package or visit www.toronto.ca/neighbourhoods. For a link to the older 13 Priority Areas used between 2005 and 2013, go here: Priority Investment Neighbourhoods Dataset is based on Statistics Canada's 2011 Census Tracts, as found in the Census Dictionary and Reference Geography Maps. Area of coverage is the city of Toronto only. Dataset is based on Centreline dataset. This dataset works best with datasets with the same projection.

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

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...

"Toronto’s 158 neighbourhoods are a microcosm of the city’s inhabitants, cultures and life. The primary purpose of the City-designated social planning neighbourhoods is to help City staff collect data, plan, analyze and forecast City services. While these neighbourhoods may not fully encompass every historical neighbourhood area, they do provide a way for planners and researchers to track information about them over time. The neighbourhood profiles were developed to help government and community agencies with their local planning, by providing socio-economic data at a meaningful geographic area. Unlike other geographies like wards or dissemination blocks, the boundaries of these social planning neighbourhoods change very infrequently over time, allowing researchers to perform longitudinal studies to see the changes in each area. Not all people define neighbourhoods the same way, but for the purposes of statistical reporting these neighbourhoods were defined based on Statistics Canada census tracts. For more information visit our About Toronto's Neighbourhoods page."

These profiles were developed to help government and community service agencies with their local planning, by providing socio-economic data at a meaningful geographic area. Not all people define “neighbourhoods” the same way. For the purposes of statistical monitoring however, these neighbourhoods were defined based on Statistics Canada census tracts. Census tracts include several city blocks and have on average about 4,000 people. Most service agencies have service areas that are defined by main streets, former municipal boundaries, or natural boundaries such as rivers. These service areas include several census tracts. It is not uncommon for service areas of community agencies to overlap. Choices about neighbourhood boundaries were made to make the data in the profiles useful to as many users as possible, and are not intended to be statements or judgements about where a neighbourhood starts or ends. The boundaries for these neighbourhoods were developed using the following criteria:

1) originally based on a Urban Development Services Residential Communities map, based on planning areas in former municipalities, and existing Public Health neighbourhood planning areas;

2) no neighbourhood be comprised of a single census tract;

3) minimum neighbourhood population of at least 7,000-10,000;

4) where census tracts were combined to meet criteria 2 or 3 above, they were joined with the most similar adjacent area according to % of the population living in low income households;

5) respecting existing boundaries such as service boundaries of community agencies, natural boundaries (rivers), and man-made boundaries (streets, highways, railway tracks);

6) maintaining neighbourhood areas small enough for service organizations to combine them to fit within their service area; and

7) the final number of neighbourhood areas be “manageable” for the purposes of data presentation and reporting.

"Toronto’s 158 neighbourhoods are a microcosm of the city’s inhabitants, cultures and life. The primary purpose of the City-designated social planning neighbourhoods is to help City staff collect data, plan, analyze and forecast City services. While these neighbourhoods may not fully encompass every historical neighbourhood area, they do provide a way for planners and researchers to track information about them over time.\r The neighbourhood profiles were developed to help government and community agencies with their local planning, by providing socio-economic data at a meaningful geographic area. Unlike other geographies like wards or dissemination blocks, the boundaries of these social planning neighbourhoods change very infrequently over time, allowing researchers to perform longitudinal studies to see the changes in each area. Not all people define neighbourhoods the same way, but for the purposes of statistical reporting these neighbourhoods were defined based on Statistics Canada census tracts. For more information visit our About Toronto's Neighbourhoods page."

This dataset includes the Crime Data by Neighbourhood. Counts are available for Assault, Auto Theft, Break and Enter, Robbery, Theft Over, Homicide and Shooting & Firearm Discharges. Data also includes the crime rate per 100,000 population calculated using the population estimates provided by Environics Analytics. Following the standard definition by StatsCan, crime rate is calculated as the crime count per 100,000 population* per year. This metric facilitates the comparisons of crime between geographic areas with different size of populations. Comparing to crime count, crime rate provides a fairer comparison of the crime over time by taking into account the change in population in the region. Note: Fields have been included for the new 158 City of Toronto Neighbourhoods structure *Population figures reflect only the resident population of a region. The temporary population such as the commuters and business patrons are not included.

Demographic, socioeconomic, environmental and health data for 140 neighbourhoods of the City of Toronto

The 13 Priority Investment Neighbourhoods are composed of neighbourhoods, neighbourhood areas (two or more joined neighbourhoods) and one special area (Kingston-Galloway) which is built out of Statistics Canada Dissemination Areas (DAs). More information on all the City's 140 neighbourhoods. In 2014, 31 out of 140 neighbourhoods are designated as NIAs as part of the Toronto Strong Neighbourhoods 2020 (TSNS2020) project. Check it out at: Neighbourhood Improvement Areas Boundaries of the 13 Priority Areas as designated throughout the City.