3 datasets found
  1. f

    A Personalized Activity-based Spatiotemporal Risk Mapping Approach to...

    • figshare.com
    tiff
    Updated Mar 18, 2021
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    Jing Li; Xuantong Wang; Hexuan Zheng; Tong Zhang (2021). A Personalized Activity-based Spatiotemporal Risk Mapping Approach to COVID-19 Pandemic [Dataset]. http://doi.org/10.6084/m9.figshare.13517105.v1
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    tiffAvailable download formats
    Dataset updated
    Mar 18, 2021
    Dataset provided by
    figshare
    Authors
    Jing Li; Xuantong Wang; Hexuan Zheng; Tong Zhang
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The datasets used for this manuscript were derived from multiple sources: Denver Public Health, Esri, Google, and SafeGraph. Any reuse or redistribution of the datasets are subjected to the restrictions of the data providers: Denver Public Health, Esri, Google, and SafeGraph and should consult relevant parties for permissions.1. COVID-19 case dataset were retrieved from Denver Public Health (Link: https://storymaps.arcgis.com/stories/50dbb5e7dfb6495292b71b7d8df56d0a )2. Point of Interests (POIs) data were retrieved from Esri and SafeGraph (Link: https://coronavirus-disasterresponse.hub.arcgis.com/datasets/6c8c635b1ea94001a52bf28179d1e32b/data?selectedAttribute=naics_code) and verified with Google Places Service (Link: https://developers.google.com/maps/documentation/javascript/reference/places-service)3. The activity risk information is accessible from Texas Medical Association (TMA) (Link: https://www.texmed.org/TexasMedicineDetail.aspx?id=54216 )The datasets for risk assessment and mapping are included in a geodatabase. Per SafeGraph data sharing guidelines, raw data cannot be shared publicly. To view the content of the geodatabase, users should have installed ArcGIS Pro 2.7. The geodatabase includes the following:1. POI. Major attributes are locations, name, and daily popularity.2. Denver neighborhood with weekly COVID-19 cases and computed regional risk levels.3. Simulated four travel logs with anchor points provided. Each is a separate point layer.

  2. a

    Disappearing Heritage

    • agic-symposium-maps-and-apps-agic.hub.arcgis.com
    Updated Aug 19, 2023
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    AZGeo Data Hub (2023). Disappearing Heritage [Dataset]. https://agic-symposium-maps-and-apps-agic.hub.arcgis.com/datasets/azgeo::disappearing-heritage
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    Dataset updated
    Aug 19, 2023
    Dataset authored and provided by
    AZGeo Data Hub
    Description

    In the 1910s, Mexican migration into Phoenix increased due to a number of factors such as a need for laborers, and the Mexican Revolution. Most of these immigrants were working class during the 1920s.

    There was quite a bit of divide between the white population and other races, and because of this Mexicans generally could not purchase property north of Van Buren, even if they could afford it. Mexican children even knew it was best not to cross Van Buren unless they had work to do on the other side. There were even several rules and restrictions on where Mexicans could buy property.

    Despite this, Mexican immigrants made distinct neighborhoods, and took pride in them. They were loyal to their barrios. But as Phoenix has grown and urbanized, many of these neighborhoods have been demolished to make way for new growth, and their history might soon be forgotten. But if immediate action is taken, it may be possible to save this Disappearing Heritage before it is too late.The included bibliography has all the data, articles, and images used. Here's the link just in case, but it is in the Story Map and under the Terms of Use section: https://docs.google.com/document/d/1Lz4QB4kK0wQD7hwCA8OMxaHS4ix6TgDgCLXOH9STYbo/edit?usp=sharing

  3. a

    Priest Shortage Top 10 Zoom Story Map

    • catholic-geo-hub-cgisc.hub.arcgis.com
    • hub.arcgis.com
    Updated Oct 9, 2019
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    burhansm2 (2019). Priest Shortage Top 10 Zoom Story Map [Dataset]. https://catholic-geo-hub-cgisc.hub.arcgis.com/maps/5104d880f5d34539b79ddab2556a39aa
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    Dataset updated
    Oct 9, 2019
    Dataset authored and provided by
    burhansm2
    License

    Attribution-NoDerivs 4.0 (CC BY-ND 4.0)https://creativecommons.org/licenses/by-nd/4.0/
    License information was derived automatically

    Area covered
    Description

    Priest Map Series {title at top of page}Data Developers: Burhans, Molly A., Cheney, David M., Emege, Thomas, Gerlt, R.. . “Priest Map Series {title at top of page}”. Scale not given. Version 1.0. MO and CT, USA: GoodLands Inc., Catholic Hierarchy, Environmental Systems Research Institute, Inc., 2019.Web map developer: Molly Burhans, October 2019Web app developer: Molly Burhans, October 2019GoodLands’ polygon data layers, version 2.0 for global ecclesiastical boundaries of the Roman Catholic Church:Although care has been taken to ensure the accuracy, completeness and reliability of the information provided, due to this being the first developed dataset of global ecclesiastical boundaries curated from many sources it may have a higher margin of error than established geopolitical administrative boundary maps. Boundaries need to be verified with appropriate Ecclesiastical Leadership. The current information is subject to change without notice. No parties involved with the creation of this data are liable for indirect, special or incidental damage resulting from, arising out of or in connection with the use of the information. We referenced 1960 sources to build our global datasets of ecclesiastical jurisdictions. Often, they were isolated images of dioceses, historical documents and information about parishes that were cross checked. These sources can be viewed here:https://docs.google.com/spreadsheets/d/11ANlH1S_aYJOyz4TtG0HHgz0OLxnOvXLHMt4FVOS85Q/edit#gid=0To learn more or contact us please visit: https://good-lands.org/The Catholic Leadership global maps information is derived from the Annuario Pontificio, which is curated and published by the Vatican Statistics Office annually, and digitized by David Cheney at Catholic-Hierarchy.org -- updated are supplemented with diocesan and news announcements. GoodLands maps this into global ecclesiastical boundaries. Admin 3 Ecclesiastical Territories:Burhans, Molly A., Cheney, David M., Gerlt, R.. . “Admin 3 Ecclesiastical Territories For Web”. Scale not given. Version 1.2. MO and CT, USA: GoodLands Inc., Environmental Systems Research Institute, Inc., 2019.Derived from:Global Diocesan Boundaries:Burhans, M., Bell, J., Burhans, D., Carmichael, R., Cheney, D., Deaton, M., Emge, T. Gerlt, B., Grayson, J., Herries, J., Keegan, H., Skinner, A., Smith, M., Sousa, C., Trubetskoy, S. “Diocesean Boundaries of the Catholic Church” [Feature Layer]. Scale not given. Version 1.2. Redlands, CA, USA: GoodLands Inc., Environmental Systems Research Institute, Inc., 2016.Using: ArcGIS. 10.4. Version 10.0. Redlands, CA: Environmental Systems Research Institute, Inc., 2016.Boundary ProvenanceStatistics and Leadership DataCheney, D.M. “Catholic Hierarchy of the World” [Database]. Date Updated: August 2019. Catholic Hierarchy. Using: Paradox. Retrieved from Original Source.Catholic HierarchyAnnuario Pontificio per l’Anno .. Città del Vaticano :Tipografia Poliglotta Vaticana, Multiple Years.The data for these maps was extracted from the gold standard of Church data, the Annuario Pontificio, published yearly by the Vatican. The collection and data development of the Vatican Statistics Office are unknown. GoodLands is not responsible for errors within this data. We encourage people to document and report errant information to us at data@good-lands.org or directly to the Vatican.Additional information about regular changes in bishops and sees comes from a variety of public diocesan and news announcements.

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Jing Li; Xuantong Wang; Hexuan Zheng; Tong Zhang (2021). A Personalized Activity-based Spatiotemporal Risk Mapping Approach to COVID-19 Pandemic [Dataset]. http://doi.org/10.6084/m9.figshare.13517105.v1

A Personalized Activity-based Spatiotemporal Risk Mapping Approach to COVID-19 Pandemic

Explore at:
tiffAvailable download formats
Dataset updated
Mar 18, 2021
Dataset provided by
figshare
Authors
Jing Li; Xuantong Wang; Hexuan Zheng; Tong Zhang
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

The datasets used for this manuscript were derived from multiple sources: Denver Public Health, Esri, Google, and SafeGraph. Any reuse or redistribution of the datasets are subjected to the restrictions of the data providers: Denver Public Health, Esri, Google, and SafeGraph and should consult relevant parties for permissions.1. COVID-19 case dataset were retrieved from Denver Public Health (Link: https://storymaps.arcgis.com/stories/50dbb5e7dfb6495292b71b7d8df56d0a )2. Point of Interests (POIs) data were retrieved from Esri and SafeGraph (Link: https://coronavirus-disasterresponse.hub.arcgis.com/datasets/6c8c635b1ea94001a52bf28179d1e32b/data?selectedAttribute=naics_code) and verified with Google Places Service (Link: https://developers.google.com/maps/documentation/javascript/reference/places-service)3. The activity risk information is accessible from Texas Medical Association (TMA) (Link: https://www.texmed.org/TexasMedicineDetail.aspx?id=54216 )The datasets for risk assessment and mapping are included in a geodatabase. Per SafeGraph data sharing guidelines, raw data cannot be shared publicly. To view the content of the geodatabase, users should have installed ArcGIS Pro 2.7. The geodatabase includes the following:1. POI. Major attributes are locations, name, and daily popularity.2. Denver neighborhood with weekly COVID-19 cases and computed regional risk levels.3. Simulated four travel logs with anchor points provided. Each is a separate point layer.

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