Context

With a population just short of 3 million people, the city of Toronto is the largest in Canada, and one of the largest in North America (behind only Mexico City, New York and Los Angeles). Toronto is also one of the most multicultural cities in the world, making life in Toronto a wonderful multicultural experience for all. More than 140 languages and dialects are spoken in the city, and almost half the population Toronto were born outside Canada.It is a place where people can try the best of each culture, either while they work or just passing through. Toronto is well known for its great food.

Content

This dataset was created by doing webscraping of Toronto wikipedia page . The dataset contains the latitude and longitude of all the neighborhoods and boroughs with postal code of Toronto City,Canada.

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

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.

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...

This dataset tracks annual distribution of students across grade levels in Toronto City School District and average distribution per school district in Ohio

Context

This dataset is used to find the best neighborhood to open a new gym in Toronto city. The data was collected the neighborhood profile data https://open.toronto.ca/dataset/neighbourhood-profiles/ and the crime data https://open.toronto.ca/dataset/neighbourhood-crime-rates/ and the venues information was obtained from Foursquare API.

Content

Total population: The population for each neighborhood of Toronto city during 2016. number of educated people: The number of educated people per neighborhood. number of 15-45: The number of population aged from 15 to 45. number of employers: The number of employers per neighborhood. long_latt: The longitudes and latitudes for each neighborhood. number of gyms: The number of gyms in each neighborhood. number of venues: The number of venues in each neighborhood.

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.

This dataset tracks annual diversity score from 1991 to 2023 for Toronto City School District vs. Ohio

1961 census tract boundary files and attribute data tables for the City of Toronto. Note that the City of Toronto boundaries did not extend as far as they do in this dataset. The boundaries do, however, correspond to the current boundaries of the City of Toronto in 2012.

Introduction

Inspired by Tree Equity Scores (TES) created by American Forests, the provided dataset compares city-maintained tree coverage in Toronto with neighbourhood demographic data. Their work is instrumental for discussing how urban centres manage the impacts of climate change equitably, specifically regarding the prevalence of urban heat islands. This dataset aims to begin discussions similar to TES in Canada, currently lacking local research.

Data Sources

Trees: Collected from Toronto's fantastic open data portal here.

Demographics: 2016 Statistics Canada data for Toronto Neighbourhoods, again provided by Toronto's open data here.

Methods

Tree data and neighbourhood data were both cleaned before merging. Since the tree data is only segregated by ward, QGIS used to place the available coordinates of each tree in its respective neighbourhood using available boundary data. Once each tree was placed in a neighbourhood, all trees need to be summarized to represent the entire neighbourhood. Though this loses a lot of valuable insight and not all trees are created equal, the Count Characteristic represents a tally of all trees in the neighbourhood, Trunk Sums is the aggregate of all diameter breast height (DBH) measures, followed by each measured divided by the area of the neighbourhood. Again, there is no perfect summary of all trees, and our methods are open to improvement.

Limitations

Though the tree data is updated regularly, the neighbourhood demographic data is from the 2016 census, and neighbourhood composition/ tree placements would have shifted between this temporal gap. This dataset will be updated with 2021 census data when the same formats are available. The new data will also shift the scope and need remapping, as now instead of the 2016 140 neighbourhoods, Toronto has been further divided into 158 neighbourhoods for the new census.

Counts and Sums of DBH were also taken to be broadly representative of tree cover, but trees of different sizes and species would not represent the cover they actually provide. The tree data also only includes trees near streets maintained by the city. It does not include privately maintained streets or public parks, furthering our estimations from accurate measures of neighbourhood tree cover. However, it is an interesting measure of publicly funded/actively maintained tree coverage (other than parks), or the tree coverage of common commercial/residential areas.

The 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

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

This dataset contains unit density profiles of Social Housing in the City of Toronto for the 140 neighbourhoods that make up the City of Toronto. For Reference Period 2014: Social housing units including Toronto Community Housing Corporation locations, Housing Connections locations, non-profits and co-op developments participating in the Social Housing Wait List.

The infographic, entitled TORONTO. Your city. Your facts. Take a look!, is designed to inform readers about Statistics Canada survey collection in the Toronto and surrounding areas by presenting a selection of household survey data for the Census Metropolitan Area of Toronto. The purpose of this infographic is to encourage residents in the Toronto and surrounding areas to participate in Statistics Canada's surveys when they are selected.

An Area of Concern (AOC) is a location where environmental quality is degraded compared to other areas in the Great Lake Basin resulting in the impairment of beneficial uses. A total of 43 AOCs were identified as a result of Annex 2 of the Great Lakes Water Quality Agreement (GLWQA).The Canada-United States GLWQA identifies 14 beneficial uses that must be restored in order to remove the designation as an Area of Concern. A beneficial use is defined as the ability of living organisms (including humans) to use the Great Lakes Basin Ecosystem without adverse consequences. A Beneficial Use Impairment (BUI) is a condition that interferes with the enjoyment of a water use. Each BUI has a set of locally-defined delisting criteria that are specific, measurable, achievable, and scientifically-defensible. The Remedial Action Plan (RAP) is administered locally in accordance with the Canada-U.S. Great Lakes Water Quality Agreement (GLWQA) and the Canada-Ontario Agreement (COA). The RAP is an ongoing collaborative effort implemented by federal, provincial, and local governments as well as industry and public partners. There are 3 key stages of the RAP: Stage 1 is a detailed description of the environmental problem; Stage 2 identifies remedial actions and options; Stage 3 is the final document providing evidence that the beneficial uses have been restored and the AOC can be “delisted”. The Toronto and Region Area of Concern extends along the northern shoreline of Lake Ontario from the Rouge River in the east to Etobicoke Creek in the west. The 2000 km2 (200 000 ha) area includes the Toronto waterfront and 6 watersheds: Etobicoke Creek, Mimico Creek, Humber River, Don River, Highland Creek and Rouge River. The drainage basin of these watersheds makes the Area of Concern a study in contrasts: more than 40% of the area is still rural and contains one of the world’s largest natural parks in an urban/agricultural setting; at the same time, more than three million people live in the Area of Concern and the City of Toronto is in the centre of the most densely urbanized area in Canada. The Toronto region was designated as an AOC in 1986 because a review of available data indicated that water quality and environmental health were severely degraded. Several centuries of agriculture and urban development have dramatically reshaped the natural environment of the Toronto and Region AOC. Contaminants from stormwater runoff and melting snow from the area’s six watersheds create serious impacts in Lake Ontario. Overflows of stormwater mixed with raw sewage are a serious problem following heavy rains in the lower portions of the Don and Humber Rivers and along the waterfront. Spills, road runoff and chemical input to sewers from industries and residences also contribute to poor water quality. In the Toronto and Region AOC’s Remedial Action Plan (RAP) report, Clean Waters, Clear Choices: Recommendations for Action (1994) eight beneficial uses were identified as impaired and three were identified as requiring further assessment. For more information visit https://www.canada.ca/en/environment-climate-change/services/great-lakes-protection/areas-concern/toronto-region.html

This dataset tracks annual overall district rank from 2012 to 2023 for Toronto City School District

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

"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."

This dataset tracks annual total revenue from 1995 to 2023 for Toronto City School District

This data is only available to ministries of the Ontario Public Service (OPS) and their agencies, boards and commissions. By obtaining the imagery data described in this record, you accept the terms outlined in the Memorandum of Restricted Imagery Use. For more information and to order imagery products please refer to the Imagery Order Form. Collected by First Base Solutions Inc. under contracts with those municipal areas during 2009 and 2010. There is no specific date information associated with this product. Orthophotography resolution ranges from 10cm to 20cm in the Greater Toronto Area (GTA): Region of Peel (20 cm), Region of York (15 cm), City of Oakville (10 cm), City of Mississauga (15 cm), City of Brampton (10 cm) and south Durham Region (20 cm). The Province of Ontario does not distribute this data to the general public.Time of Capture: 2009 to 2010Coverage: Approximately 4,924 sq kmCanopy Coverage: Leaf-Off Available ProductsOrthorectified Tiles – 1km x 1km, 10 to 20cm, 8-bit, RGB in .TIFF format (approx. 72 to 287MB/tile) and a compressed format (approx. 1.35 to 4.5MB/tile)Greater Toronto Area (GTA) 2009 - Ortho Index (Shapefile)Imagery Order Form (.docx)Imagery User Guide (.docx) 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, imagery@ontario.ca