Geomatics and geospatial technologies

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All (15)

All (15) (0 to 10 of 15 results)

  • 1. Census of Environment Geospatial Explorer
    Data Visualization: 71-607-X2024003
    Description: The Census of Environment Geospatial Explorer is web GIS application that lets users visualize thematic maps of Statistics Canada data tables published in the context of the Census of Environment. The application reads statistical data from the Common Output Data Repository (CODR) using Statistics Canada Web Data Services (WDS) and joins them with geospatial data to build and display thematic maps to the user.
    Release date: 2024-03-22
  • 2. Applications related to geomatics or geospatial technologies, by industry and enterprise size
    Table: 27-10-0371-01
    Geography: Canada, Geographical region of Canada, Province or territory
    Frequency: Occasional
    Description: Survey of advanced technology, applications related to geomatics or geospatial technologies, by North American Industry Classification System (NAICS) and enterprise size for Canada and certain provinces, in 2022.
    Release date: 2023-07-28
  • 3. Spatial Access Measures
    Table: 27-26-0001
    Description: The Spatial Access Measures are a set of indicators that quantify the ease of reaching destinations of varying levels of attractiveness from an origin dissemination block. There are seven destination amenities which include educational and post-secondary educational facilities, health care facilities, places of employment, grocery stores, cultural and arts facilities, and sports and recreational facilities. For each amenity, there are four variants based on the transportation mode: access via public transit during peak hours, access via public transit during off-peak hours, access via cycling, and access via walking.
    Release date: 2023-07-17
  • 4. Use and purpose of Global Positioning System equipment on farms
    Table: 32-10-0207-01
    Geography: Canada, Province or territory
    Frequency: Occasional
    Description:

    Use of Global Positioning System (GPS) equipment and the application of the technology on agricultural operations, separated by field and forage farming operations, and by province, available every 5 years.

    Release date: 2023-02-17
  • 5. Field operations that used Global Positioning System as a tracking or guidance system
    Table: 32-10-0207-02
    Geography: Canada, Province or territory
    Frequency: Occasional
    Description:

    Types of field operations that were completed using Global Positioning System (GPS) equipment as a tracking or guidance system on agricultural operations, separated by field and forage farming operations, and by province, available every 5 years.

    Release date: 2023-02-17
  • 6. Targeted or varied application of fertilizer and pesticide using a Global Positioning System
    Table: 32-10-0207-03
    Geography: Canada, Province or territory
    Frequency: Occasional
    Description:

    Use of Global Positioning System (GPS) equipment to target or vary fertilizer and pesiticide application rates across a field and average percentage of cropland used by field and forage crop operations that received varied pesticide and fertilizer application, separated by field and forage farming operations, and by province, available every 5 years.

    Release date: 2023-02-17
  • 7. Canadian Statistical Geospatial Explorer Hub Archived
    Data Visualization: 71-607-X2020010
    Description: The Canadian Statistical Geospatial Explorer empowers users to discover geo enabled data holdings of Statistics Canada at various levels of geography including at the neighbourhood level. Users are able to visualize, thematically map, spatially explore and analyze, export and consume data in various formats. Users can also view the data superimposed on satellite imagery, topographic and street layers.
    Release date: 2023-01-24
  • 8. 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
  • 9. An Open-source System for Building-height Estimation using Street-view Images, Deep Learning, and Building Footprints
    Articles and reports: 18-001-X2020002
    Description:

    This paper presents an open-source system that was developed for automatic estimation of building height from street-view images using Deep Learning (DL), advanced image processing techniques, and geospatial data. The goal of the developed system is to ultimately be used to enrich the Open Database of Buildings (ODB), that was published by Statistics Canada, as a part of the Linkable Open Data Environment (LODE). Some of the obtained results for building-height estimation are presented. Some challenging cases and the scalability of the system are discussed as well.

    Release date: 2020-12-08
  • 10. A Brief Overview of the Canadian Statistical Geospatial Explorer
    19-22-0003
    Description: This webinar will provide you with an introduction to the Canadian Statistical Geospatial Explorer (CSGE). This interactive mapping tool was designed at Statistics Canada to give users the ability to explore our data, create custom maps and download geo-enabled data into users' own workflows. The CSGE allows users to visualize data at granular levels such as dissemination areas and other geographies like provinces/territories and health regions. The CSGE includes a range of COVID-19 relevant indicators on health, demographic profile and socio-economic conditions of the Canadian population, all derived from Statistics Canada data holdings.

    The webinar covers basic functionalities of the Canadian Statistical Geospatial Explorer such as: finding and exploring data; exporting data in various formats and bringing it into your workflow; customizing maps; and changing base maps (satellite imagery, topography, etc.) to view data in a different context.

    https://www.statcan.gc.ca/eng/services/webinars/19220003

    Release date: 2020-05-11
Data (12)

Data (12) (0 to 10 of 12 results)

  • 1. Census of Environment Geospatial Explorer
    Data Visualization: 71-607-X2024003
    Description: The Census of Environment Geospatial Explorer is web GIS application that lets users visualize thematic maps of Statistics Canada data tables published in the context of the Census of Environment. The application reads statistical data from the Common Output Data Repository (CODR) using Statistics Canada Web Data Services (WDS) and joins them with geospatial data to build and display thematic maps to the user.
    Release date: 2024-03-22
  • 2. Applications related to geomatics or geospatial technologies, by industry and enterprise size
    Table: 27-10-0371-01
    Geography: Canada, Geographical region of Canada, Province or territory
    Frequency: Occasional
    Description: Survey of advanced technology, applications related to geomatics or geospatial technologies, by North American Industry Classification System (NAICS) and enterprise size for Canada and certain provinces, in 2022.
    Release date: 2023-07-28
  • 3. Spatial Access Measures
    Table: 27-26-0001
    Description: The Spatial Access Measures are a set of indicators that quantify the ease of reaching destinations of varying levels of attractiveness from an origin dissemination block. There are seven destination amenities which include educational and post-secondary educational facilities, health care facilities, places of employment, grocery stores, cultural and arts facilities, and sports and recreational facilities. For each amenity, there are four variants based on the transportation mode: access via public transit during peak hours, access via public transit during off-peak hours, access via cycling, and access via walking.
    Release date: 2023-07-17
  • 4. Use and purpose of Global Positioning System equipment on farms
    Table: 32-10-0207-01
    Geography: Canada, Province or territory
    Frequency: Occasional
    Description:

    Use of Global Positioning System (GPS) equipment and the application of the technology on agricultural operations, separated by field and forage farming operations, and by province, available every 5 years.

    Release date: 2023-02-17
  • 5. Field operations that used Global Positioning System as a tracking or guidance system
    Table: 32-10-0207-02
    Geography: Canada, Province or territory
    Frequency: Occasional
    Description:

    Types of field operations that were completed using Global Positioning System (GPS) equipment as a tracking or guidance system on agricultural operations, separated by field and forage farming operations, and by province, available every 5 years.

    Release date: 2023-02-17
  • 6. Targeted or varied application of fertilizer and pesticide using a Global Positioning System
    Table: 32-10-0207-03
    Geography: Canada, Province or territory
    Frequency: Occasional
    Description:

    Use of Global Positioning System (GPS) equipment to target or vary fertilizer and pesiticide application rates across a field and average percentage of cropland used by field and forage crop operations that received varied pesticide and fertilizer application, separated by field and forage farming operations, and by province, available every 5 years.

    Release date: 2023-02-17
  • 7. Canadian Statistical Geospatial Explorer Hub Archived
    Data Visualization: 71-607-X2020010
    Description: The Canadian Statistical Geospatial Explorer empowers users to discover geo enabled data holdings of Statistics Canada at various levels of geography including at the neighbourhood level. Users are able to visualize, thematically map, spatially explore and analyze, export and consume data in various formats. Users can also view the data superimposed on satellite imagery, topographic and street layers.
    Release date: 2023-01-24
  • 8. Adoption of geomatics or geospatial technologies, by industry and enterprise size
    Table: 27-10-0290-01
    Geography: Canada, Province or territory
    Frequency: Occasional
    Description:

    Survey of advanced technology, adoption of geomatics or geospatial technologies, by type of technology, North American Industry Classification System (NAICS) and enterprise size for Canada and certain provinces, in 2014.

    Release date: 2016-02-12
  • 9. Purpose of using geomatics or geospatial technologies, by industry and enterprise size
    Table: 27-10-0291-01
    Geography: Canada, Province or territory
    Frequency: Occasional
    Description:

    Survey of advanced technology, purpose of using geomatics or geospatial technologies, by North American Industry Classification System (NAICS) and enterprise size for Canada and certain provinces, in 2014.

    Release date: 2016-02-12
  • 10. Alliances or collaborative arrangements related to geomatics or geospatial technologies, by industry and enterprise size
    Table: 27-10-0292-01
    Geography: Canada, Province or territory
    Frequency: Occasional
    Description:

    Survey of advanced technology, alliances or collaborative arrangements related to geomatics or geospatial technologies, by North American Industry Classification System (NAICS) and enterprise size for Canada and certain provinces, in 2014.

    Release date: 2016-02-12
Analysis (2)

Analysis (2) ((2 results))

  • 1. 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
  • 2. An Open-source System for Building-height Estimation using Street-view Images, Deep Learning, and Building Footprints
    Articles and reports: 18-001-X2020002
    Description:

    This paper presents an open-source system that was developed for automatic estimation of building height from street-view images using Deep Learning (DL), advanced image processing techniques, and geospatial data. The goal of the developed system is to ultimately be used to enrich the Open Database of Buildings (ODB), that was published by Statistics Canada, as a part of the Linkable Open Data Environment (LODE). Some of the obtained results for building-height estimation are presented. Some challenging cases and the scalability of the system are discussed as well.

    Release date: 2020-12-08
Reference (0)

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