The Forward Sortation Area Boundary File depicts the boundaries of forward sortation areas (FSAs) derived from postal codes captured from federal census questionnaires. This is based on census dissemination areas. The file is periodically updated, following the federal census which is currently mandated every 5 years (2011, 2016, 2021...). More information is available at: Forward Sortation Area Boundary File

Looking for a detailed FSA- or 3-digit postal code map of Canada? With Spotzi, you can explore this Canadian FSA boundaries data in our dashboards for free. Create a free account and unlock access to our powerful dashboard to analyze, segment, and target areas like never before.

Access the map instantly without payment or commitment. By registering a free Spotzi account, you also get access to advanced tools: radius filters, drivetime filters, build heatmaps, and even export postcode selections to use in your next marketing campaign. It's the easiest way to turn location data into action – no technical skills required.

No data experience needed – just results. Start using Canada our free boundary data to drive your next marketing move.

The 2011 Census Forward Sortation Area (FSA) Boundary File depicts the boundaries of 1,621 forward sortation areas (identified by the first three characters of the postal code) derived from postal codesOM captured from the 2011 Census of Population questionnaires.Through analysis of the postal codesOM reported by census households, a single FSA was assigned to each dissemination block based on the most frequently reported FSA for the dissemination block. Unreported dissemination blocks were assigned an FSA based on proximity to reported dissemination blocks in the same province or territory or nearest Canada Post Corporation delivery installation.The 2011 Census FSA Boundary File provides a framework for mapping and spatial analysis. It is available in two types: cartographic and digital. The cartographic boundary file depicts the 2011 FSAs with the shoreline of the major land mass of Canada and its coastal islands. The digital boundary file depicts the full extent of the 2011 FSAs, including the coastal water area.

IMPORTANT NOTICE This item has moved to a new organization and entered Mature Support on February 3rd, 2025. This item is scheduled to be Retired and removed from ArcGIS Online on June 27th, 2025. We encourage you to switch to using the item on the new organization as soon as possible to avoid any disruptions within your workflows. If you have any questions, please feel free to leave a comment below or email our Living Atlas Curator (livingatlascurator@esri.ca) The new version of this item can be found here The 2011 Census Forward Sortation Area (FSA) Boundary File depicts the boundaries of 1,621 forward sortation areas (identified by the first three characters of the postal code) derived from postal codesOM captured from the 2011 Census of Population questionnaires.Through analysis of the postal codesOM reported by census households, a single FSA was assigned to each dissemination block based on the most frequently reported FSA for the dissemination block. Unreported dissemination blocks were assigned an FSA based on proximity to reported dissemination blocks in the same province or territory or nearest Canada Post Corporation delivery installation.The 2011 Census FSA Boundary File provides a framework for mapping and spatial analysis. It is available in two types: cartographic and digital. The cartographic boundary file depicts the 2011 FSAs with the shoreline of the major land mass of Canada and its coastal islands. The digital boundary file depicts the full extent of the 2011 FSAs, including the coastal water area.

Edmonton Forward Sortation Area (FSA) data provided by Statistics Canada (see https://www12.statcan.gc.ca/census-recensement/2011/geo/bound-limit/bound-limit-2016-eng.cfm).

Adapted from Census Forward Sortation Area Boundary File, 2016 Census. Statistics Canada Catalogue no. 92-179-X, 2021-02-05. This does not constitute an endorsement by Statistics Canada of this product.

The changes made to the original Statistics Canada data are as follows:

1) The data has been filtered to include only those FSAs with boundaries that are wholly or partially within Edmonton's city boundary, or touch that boundary. 2) The boundaries have been reprojected to LL-WGS84 (required by Socrata). 3) A multipolygon geometry attribute has been created to facilitate mapping.

Access to these data files and dissemination of data retrieved from them is restricted to current faculty, staff or students employed by, or studying at UBC. Users must also abide by the DMTI License Agreement. This product is designed to be installed on a Windows based computer system. To install, download package.zip and Arcview.zip to a temporary directory. Uncompress package.zip using WinZip or a similar utility. Run TMSetup.exe to complete the installation. If you require data only, they are contained in Arcview.zip A list of all the files is contained in the file FileList (below). DMTI Spatial's FSA boundaries have been developed using CanMap, Canada's #1 precision based street map data product. The FSA boundaries encompass the six digit postal code points starting with the FSA designation. DMTI Spatial's FSA boundaries include multi-polygon regions where appropriate (i.e. two or more polygons which form one region or entity in the database), reflecting the complexity inherent in FSA geography. Features Coverage: Nationwide Projection: Unprojected latitude, longitude Datum: NAD83

2016 Census - Boundary files - Forward Sortation Areas (FSA) CanadaDownloaded from Statistics Canada: https://www12.statcan.gc.ca/census-recensement/2011/geo/bound-limit/bound-limit-2016-eng.cfm

The most complete and up-to-date Canadian postal code database for accurate customer profiling, direct marketing optimization, precise territory management, and serviceability insights. Postal Code Suite offers six digit postal code polygons so you can visualize postal code boundaries on a map. Each zip package includes Multiple Enhanced Postal Codes, Forward Sortation Areas, Local Delivery Units and topographic layers, for the province/territory, as well as Canada wide layers for area codes, capital cities, provincial boundaries, municipal boundaries, topographic boundaries, time zones and water layers.

Now includes bridge to the 2016 census.

This is the Zenodo archive for the manuscript "Likely community transmission of COVID-19 infections between neighboring, persistent hotspots in Ontario, Canada" (Mucaki EJ, Shirley BC and Rogan PK. F1000Research 2021, 10:1312, DOI: 10.12688/f1000research.75891.1). This study aimed to produce community-level geo-spatial mapping of patterns and clusters of symptoms, and of confirmed COVID-19 cases, in near real-time in order to support decision-making. This was accomplished by area-to-area geostatistical analysis, space-time integration, and spatial interpolation of COVID-19 positive individuals. This archive will contain data and image files from this study, which were too numerous to be included in the manuscript for this study. It also provides all program files pertaining to the Geostatistical Epidemiology Toolbox (Geostatistical analysis software package to be used in ArcGIS), as well as all other scripts described in this manuscript and other software developed (cluster, outlier, streak identification and pairing)..

We also provide a guide which provides a general description of the contents of the four sections in this archive (Documentation_for_Sections_of_Zenodo_Archive.docx). If you have any intent to utilize the data provided in Section 3, we greatly advise you to review this document as it describes the output of all geostatistical analyses performed in this study in detail.

Data Files:

Section 1. "Section_1.Tables_S1_S7.Figures_S1_S11.zip"

This section contains all additional tables and figures described in the manuscript "Likely community transmission of COVID-19 infections between neighboring, persistent hotspots in Ontario, Canada". Additional tables S1 to S7 are presented in an Excel document. These 7 tables provide summary statistics of various geostatistical tests described in the study (“Section 1 – Tables S1-S4”) and lists all identified single and paired high-case cluster streaks (“Section 1 – Tables S5-S7”). This section also contains 11 additional figures referred to in the manuscript (“Section 1 – Figures S1-S11”) both individually and within a Word document which describes them.

Section 2. "Section_2.Localized_Hotspot_Lists.zip"

All localized hotspots (identified through kriging analysis) were catalogued for each municipality evaluated (Hamilton, Kitchener/Waterloo, London, Ottawa, Toronto, Windsor/Essex). These files indicate the FSA in which the hotspot was identified, the date in which it was identified (utilizing 3-day case data at the postal code level), the amount of cases which occurred within the FSA within these 3 dates, the range of cases interpolated by kriging analysis (between 5-10, 10-15, 15-20, 20-25, 25-30, 30-35, 35-40, 40-50, >50), and whether or not the FSA was deemed a hotspot by Gi* relative to the rest of Ontario on any of the three dates evaluated. Please see Section 4 for map images of these localized hotspots.

Section 3. "Section_3.All-Data_Files.Kriging_GiStar_Local_and_GlobalMorans.2020_2021"

Section 3 – All output files from the geostatistical tests performed in this study are provided in this section. This includes the output from Ontario-wide FSA-level Gi* and Cluster and Outlier analyses, and PC-level Cluster and Outlier, Spatial Autocorrelation, and kriging analysis of 6 municipal regions. It also includes kriging analysis of 7 other municipal regions adjacent to Toronto (Ajax, Brampton, Markham, Mississauga, Pickering, Richmond Hill and Vaughan). This section also provides data files from our analyses of stratified case data (by age, gender, and at-risk condition). All coordinates presented in these data files are given in “PCS_Lambert_Conformal_Conic” format. Case values between 1-5 were masked (appear as “NA”).

Section 4. "Section_4.All_Map_Images_of_Geostat_Analyses.zip"

Sets of image files which map the results of our geostatistical analyses onto a map of Ontario or within the municipalities evaluated (Hamilton, Kitchener/Waterloo, London, Ottawa, Toronto, Windsor/Essex) are provided. This includes: Kriging analysis (PC-level), Local Moran's I cluster and outlier analysis (FSA and PC-level), normal and space-time Gi* analysis, and all images for all analyses performed on stratified data (by age, gender and at-risk condition). Kriging contour maps are also included for 7 other municipal regions adjacent to Toronto (Ajax, Brampton, Markham, Mississauga, Pickering, Richmond Hill and Vaughan).

Software:

This Zenodo archive also provides all program files pertaining to the Geostatistical Epidemiology Toolbox (Geostatistical analysis software package to be used in ArcGIS), as well as all other scripts described in this manuscript. This geostatistical toolbox was developed by CytoGnomix Inc., London ON, Canada and is distributed freely under the terms of the GNU General Public License v3.0. It can be easily modified to accommodate other Canadian provinces and, with some additional effort, other countries.

This distribution of the Geostatistical Epidemiology Toolbox does not include postal code (PC) boundary files (which are required for some of the tools included in the toolbox). The PC boundary shapefiles used to test the toolbox were obtained from DMTI (https://www.dmtispatial.com/canmap/) through the Scholar's Geoportal at the University of Western Ontario (http://geo2.scholarsportal.info/). The distribution of these files (through sharing, sale, donation, transfer, or exchange) is strictly prohibited. However, any equivalent PC boundary shape file should suffice, provided it contains polygon boundaries representing postal code regions (see guide for more details).

Software File 1. "Software.GeostatisticalEpidemiologyToolbox.zip"

The Geostatistical Epidemiology Toolbox is a set of custom Python-based geoprocessing tools which function as any built-in tool in the ArcGIS system. This toolbox implements data preprocessing, geostatistical analysis and post-processing software developed to evaluate the distribution and progression of COVID-19 cases in Canada. The purpose of developing this toolbox is to allow external users without programming knowledge to utilize the software scripts which generated our analyses and was intended to be used to evaluate Canadian datasets. While the toolbox was developed for evaluating the distribution of COVID-19, it could be utilized for other purposes.

The toolbox was developed to evaluate statistically significant distributions of COVID-19 case data at Canadian Forward Sortation Area (FSA) and Postal Code-level in the province of Ontario utilizing geostatistical tools available through the ArcGIS system. These tools include: 1) Standard Gi* analysis (finds areas where cases are significantly spatially clustered), 2) spacetime based Gi* analysis (finds areas where cases are both spatially and temporally clustered), 3) cluster and outlier analysis (determines if high case regions are an regional outlier or part of a case cluster), 4) spatial autocorrelation (determines the cases in a region are clustered overall) and, 5) Empirical Bayesian Kriging analysis (creates contour maps which define the interpolation of COVID-19 cases in measured and unmeasured areas). Post-processing tools are included that import these all of the preceding results into the ArcGIS system and automatically generate PNG images.

This archive also includes a guide ("UserManual_GeostatisticalEpidemiologyToolbox_CytoGnomix.pdf") which describes in detail how to set up the toolbox, how to format input case data, and how to use each tool (describing both the relevant input parameters and the structure of the resultant output files).

Software File 2: “Software.Additional_Programs_for_Cluster_Outlier_Streak_Idendification_and_Pairing.zip"

In the manuscript associated with this archive, Perl scripts were utilized to evaluate postal code-level Cluster and Outlier analysis to identify significantly, highly clustered postal codes over consecutive periods (i.e., high-case cluster “streaks”). The identified streaks are then paired to those in close proximity, based on the neighbors of each postal code from PC centroid data ("paired streaks"). Multinomial logistic regression models were then derived in the R programming language to measure the correlation between the number of cases reported in each paired streak, the interval of time separating each streak, and the physical distance between the two postal codes. Here, we provide the 3 Perl scripts and the R markdown file which perform these tasks:

“Ontario_City_Closest_Postal_Code_Identification.pl”

Using an input file with postal code coordinates (by centroid), this program identifies the nearest neighbors to all postal codes for a given municipal region (the name of this region is entered on the command line). Postal code centroids were calculated in ArcGIS using the “Calculate Geometry” function against DMTI postal code boundary files (not provided). Input from other sources could be used, however, as long as the input includes a list of coordinates with a unique label associated with a particular municipality.

The output of this program (for the same municipal region being evaluated) is required for the following two Perl scripts:

“Local_Morans_Analysis.Recurrent_Clustered_PC_Identifier.pl”

This program uses the output of postal code-level Cluster and Outlier analysis for a municipality (these files are available in a second Zenodo archive: doi.org/10.5281/zenodo.5585812) and the output from “Ontario_City_Closest_Postal_Code_Identification.pl” (for the same municipal region) as input to identify high-case clustered postal codes that occur consecutively over a course of several dates (referred to as high-case cluster “streaks”). The script allows for a single day in which the PC was either not clustered or did not meet the minimum case count threshold of ≥ 6 cases within the 3-day sliding window (i.e. if