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All (3) ((3 results))

• 1. Sustainable Development Goals: Goal 9, Industry, Innovation and Infrastructure

  Articles and reports: 11-637-X202200100009

  Description:

  As the ninth goal outlined in the 2030 Agenda for Sustainable Development, Canada and other UN member states have committed to build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation by 2030. This 2022 infographic provides an overview of indicators underlying the ninth Sustainable Development Goal in support of industry, innovation and infrastructure, and the statistics and data sources used to monitor and report on this goal in Canada.

  Release date: 2022-12-13

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• 2. Canada's Core Public Infrastructure Survey: Interactive Dashboard

  Data Visualization: 71-607-X2021002

  Description:

  This interactive dashboard provides access to data from Canada's Core Public Infrastructure Survey (CCPI) by province and territory and by type of asset. Data on the inventory, year of construction or acquisition, condition and asset management strategies for nine core public infrastructure categories are presented in interactive charts.

  Release date: 2022-10-28

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• 3. Building Type Classification from Street-view Imagery using Convolutional Neural Networks

  Articles and reports: 18-001-X2021003

  Description:

  Micro-level information on buildings and physical infrastructure is increasing in relevance to social, economic and environmental statistical programs. Alternative data sources and advanced analytical methods can be used to generate some of this information. This paper presents how multiple convolutional neural networks (CNNs) are finetuned to classify buildings into different types (e.g., house, apartment, industrial) using their street-view images. The CNNs use the structure of the façade in the building’s image for classification. Multiple state-of-the-art CNNs are finetuned to accomplish the classification task. The trained models provide a proof of concept and show that CNNs can be used to classify buildings using their street-view imagery. The training and validation performance of the trained CNNs are measured. Furthermore, the trained CNNs are evaluated on a separate test set of street-view imagery. This approach can be used to augment the information available on openly accessible databases, such as the Open Database of Buildings.

  Release date: 2022-01-21

Data (1) ((1 result))

• 1. Canada's Core Public Infrastructure Survey: Interactive Dashboard

  Data Visualization: 71-607-X2021002

  Description:

  This interactive dashboard provides access to data from Canada's Core Public Infrastructure Survey (CCPI) by province and territory and by type of asset. Data on the inventory, year of construction or acquisition, condition and asset management strategies for nine core public infrastructure categories are presented in interactive charts.

  Release date: 2022-10-28

Analysis (2) ((2 results))

• 1. Sustainable Development Goals: Goal 9, Industry, Innovation and Infrastructure

  Articles and reports: 11-637-X202200100009

  Description:

  As the ninth goal outlined in the 2030 Agenda for Sustainable Development, Canada and other UN member states have committed to build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation by 2030. This 2022 infographic provides an overview of indicators underlying the ninth Sustainable Development Goal in support of industry, innovation and infrastructure, and the statistics and data sources used to monitor and report on this goal in Canada.

  Release date: 2022-12-13

  ---

• 2. Building Type Classification from Street-view Imagery using Convolutional Neural Networks

  Articles and reports: 18-001-X2021003

  Description:

  Micro-level information on buildings and physical infrastructure is increasing in relevance to social, economic and environmental statistical programs. Alternative data sources and advanced analytical methods can be used to generate some of this information. This paper presents how multiple convolutional neural networks (CNNs) are finetuned to classify buildings into different types (e.g., house, apartment, industrial) using their street-view images. The CNNs use the structure of the façade in the building’s image for classification. Multiple state-of-the-art CNNs are finetuned to accomplish the classification task. The trained models provide a proof of concept and show that CNNs can be used to classify buildings using their street-view imagery. The training and validation performance of the trained CNNs are measured. Furthermore, the trained CNNs are evaluated on a separate test set of street-view imagery. This approach can be used to augment the information available on openly accessible databases, such as the Open Database of Buildings.

  Release date: 2022-01-21

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