Datasets and Maps
We do our best to make data publicly available. You can find our public datasets on the Beap Lab Dataverse (https://dataverse.harvard.edu/dataverse/beaplab). If you have questions please do not hesitate to reach out.
Below you will find some descriptions of datasets were have helped create or are in the process of developing.
The Public Transport Accessibility Index (PTAI) was calculated based on the method described by Saghapour, 2016 to measure the access level to public transport for each census tract in different metropolitan areas of Canada. This approach consists of two main procedures. The first of them relates to the distances from points of interest and their closest stops/stations. The second one includes walking catchments and CTs population densities proportions calculations. The PTAI was calculated for each census tract. In addition, the access level was calculated for each DA. In this case, the proportions between population densities in different geographic levels were not considered.
- Saghapour T et al. “Public transport accessibility in metropolitan areas: A new approach incorporating population density.” Journal of Transport Geography, 2016, vol. 54, pp. 273–285. Web
This measure for the computation of a multi-dimensional, nationwide urban sprawl index for Canada at a small-area level (i.e., Census Tract, CT) was developed using robust spatial statistical modelling. It fills the gap that a comprehensive urban sprawl index at a fine spatial scale is missing in Canada. It includes urban sprawl indicators along four dimensions: density, mix use, street connectivity, and centering. These dimensions have been widely used in the urban sprawl/compactness studies in North America [1,2].
- Ewing R et al. “Relationship between urban sprawl and physical activity, obesity, and morbidity – Update and refinement.” Health and Place, 2014, vol. 26, pp. 118–126. Web
- Ewing R et al. “Relationship between urban sprawl and physical activity, obesity, and morbidity.” American Journal of Health Promotion, 2003, vol. 18, iss. 1, pp. 47–57. Web
Canadian Active Living Environments (Can-ALE) Dataset
The Can-ALE dataset is a geographic-based set of measures characterizing the active living environments (often referred to as ‘walkability’) of Canadian communities. The data is provided at the dissemination area level. By using geography conversion tools such as the Postal Code Conversion File (PCCF+) it is possible to link Can-ALE measures to individual-level health data from national-level survey platforms (e.g., National Population Health Survey, Canadian Community Health Survey) or to local-level data, such as travel surveys (e.g., Transportation Tomorrow Survey, Montreal Origin-Destination Survey). A version of Can-ALE prelinked to postal codes is available from CANUE.
Neighborhood Active Living Potential (NALP) Measure
There is growing recognition that the neighbourhoods we live in affect our health. Neighborhood observation is an increasingly popular method to measure neighborhood environments because it captures observable properties of the environment not captured in census data. NALP is a stable and reliable neighborhood observation measure, has utility in multiple cities, and captures three essential elements of neighborhoods: activity friendliness, safety, and density of destinations.