68 datasets found
  1. a

    Imperial Irrigation Service District Boundary

    • hub.arcgis.com
    Updated Jul 1, 2015
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    URSpatial (2015). Imperial Irrigation Service District Boundary [Dataset]. https://hub.arcgis.com/datasets/09e260e5f9f54b48b9b84fbe42da9a3b
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    Dataset updated
    Jul 1, 2015
    Dataset authored and provided by
    URSpatial
    Area covered
    Description

    Imperial Irrigation Service District Boundary. Linework digitized from map posted on IID web site. http://www.iid.com/power/power-servicemap.html It was then corrected based on review from agency personnel.

  2. c

    Balancing Authority Areas

    • gis.data.ca.gov
    • data.cnra.ca.gov
    • +6more
    Updated Mar 4, 2020
    + more versions
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    California Energy Commission (2020). Balancing Authority Areas [Dataset]. https://gis.data.ca.gov/documents/07c4d7253138472782716db5ff4cf62a
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    Dataset updated
    Mar 4, 2020
    Dataset authored and provided by
    California Energy Commission
    License

    https://www.energy.ca.gov/conditions-of-usehttps://www.energy.ca.gov/conditions-of-use

    Description

    Map of the eight balancing authority areas in California:- BANC: Balancing Authority of Northern California- CalISO: California Independent System Operator- IID: Imperial Irrigation District- LADWP: Los Angeles Department of Water & Power- PacWest: PacifiCorp West- NV Energy- TID: Turlock Irrigation District- WALC: Western Area Lower Colorado

  3. f

    Proportion of bats with significant tonotopic, IID and azimuth maps.

    • plos.figshare.com
    xls
    Updated Jun 1, 2023
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    Stuart Yarrow; Khaleel A. Razak; Aaron R. Seitz; Peggy Seriès (2023). Proportion of bats with significant tonotopic, IID and azimuth maps. [Dataset]. http://doi.org/10.1371/journal.pone.0087178.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Stuart Yarrow; Khaleel A. Razak; Aaron R. Seitz; Peggy Seriès
    License

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

    Description

    Results of map detection analysis of pallid bat data. Each table cells shows the number of bats in which significant maps were detected/total number of bats from which data were available. The ‘any measure’ row shows the number of bats where significant topography was detected by at least one measure. Each column relates to a given tuning property (e.g. frequency) and group of neurons (e.g. cells from the EI cluster). The ‘all cell groups’ column gives combined detection rates for each measure across all maps in all animals; this is a coarse indication of the relative power of the measures.

  4. A

    ‘Department of Recreation and Parks' GIS Map of Park Boundaries’ analyzed by...

    • analyst-2.ai
    Updated Feb 12, 2022
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2022). ‘Department of Recreation and Parks' GIS Map of Park Boundaries’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-department-of-recreation-and-parks-gis-map-of-park-boundaries-74ed/71443988/?iid=000-197&v=presentation
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    Dataset updated
    Feb 12, 2022
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘Department of Recreation and Parks' GIS Map of Park Boundaries’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/1b7e59b2-a5cb-4ba0-bb8e-bc4ef8c45007 on 12 February 2022.

    --- Dataset description provided by original source is as follows ---

    The Department of Recreation and Parks' GIS map of park boundaries in the City of Los Angeles.

    --- Original source retains full ownership of the source dataset ---

  5. A

    ‘Zoning Map Index: Quartersection’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Aug 5, 2020
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2020). ‘Zoning Map Index: Quartersection’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-zoning-map-index-quartersection-8ae3/01e31eb8/?iid=000-691&v=presentation
    Explore at:
    Dataset updated
    Aug 5, 2020
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘Zoning Map Index: Quartersection’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/828cae4e-07f2-44a0-bf64-4305585bfd57 on 27 January 2022.

    --- Dataset description provided by original source is as follows ---

    Shapefile of zoning quartersection map index. Grid to determine which zoning quartersection map relates to specific areas of NYC.

    A sectional index grid to determine which Zoning Map refers to specific areas of New York City. Zoning maps show the boundaries of zoning districts throughout the city. The maps are regularly updated after the City Planning Commission and the City Council have approved proposed zoning changes. The set of 126 maps, which are part of the Zoning Resolution, are displayed in 35 sections. Each section is identified by a number from 1 to 35 and is further divided into one to four quarters, each identified by a letter a, b, c or d (map 8d or 33c for example). Each map covers an area of approximately 8,000 feet (north/south) by 12,500 feet (east/west).

    All previously released versions of this data are available at BYTES of the BIG APPLE- Archive

    --- Original source retains full ownership of the source dataset ---

  6. SYIP Approved Projects

    • data.virginia.gov
    • odgavaprod.ogopendata.com
    • +4more
    Updated Jul 15, 2025
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    Datathon 2025 (2025). SYIP Approved Projects [Dataset]. https://data.virginia.gov/dataset/syip-approved-projects1
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    arcgis geoservices rest api, htmlAvailable download formats
    Dataset updated
    Jul 15, 2025
    Dataset provided by
    Virginia Department Of Transportation
    Authors
    Datathon 2025
    Description

    VDOT"s Six Year Improvement Plan approved projects. Contains both linear projects data as well as a point layer representing the summary of both point and line projects. In the summary layer, linear projects are converted to points based on the centroid of the line and are combined with the normal point projects into a single dataset.

    Spatial data is intended to highlight mappable projects in the SYIP but may not include all records due to unique business circumstances. The data included in this layer is produced, owned, and managed by VDOT - Infrastructure Investment Division (IID). Please coordinate with IID if this data is to be used or altered for the creation of derivative work products, linked to various technology solutions, or to support other efforts outside of expected tasks in support of Six-Year Improvement Program management and/or development.

    Official SYIP site: https://syip.virginiadot.org/Pages/allProjects.aspx#

  7. A

    ‘Topographical Bureau Maps’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Aug 5, 2020
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2020). ‘Topographical Bureau Maps’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-topographical-bureau-maps-60f0/39e5ea41/?iid=002-127&v=presentation
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    Dataset updated
    Aug 5, 2020
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘Topographical Bureau Maps’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/3b482e9d-dd23-4331-8c7a-e323f533874a on 27 January 2022.

    --- Dataset description provided by original source is as follows ---

    This list contains information on maps maintained by the topographical bureau

    --- Original source retains full ownership of the source dataset ---

  8. A

    ‘Waterfront Access Map Data: Shapefile’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Aug 5, 2020
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2020). ‘Waterfront Access Map Data: Shapefile’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-waterfront-access-map-data-shapefile-0f35/f773c750/?iid=001-298&v=presentation
    Explore at:
    Dataset updated
    Aug 5, 2020
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘Waterfront Access Map Data: Shapefile’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/a5e3009c-e042-4033-8973-c4de0294345d on 27 January 2022.

    --- Dataset description provided by original source is as follows ---

    The Waterfront Access Map (WAM) data contains information about waterfront areas accessible to the public that are either publicly owned or on private property. The Waterfront Public Access Areas (WPAA)s data contains privately owned waterfront zoning lots where publicly accessible open space is provided to and along the shoreline for public enjoyment. The Publicly Owned Waterfront data contains City, State, and Federally owned public parks and facilities that provide waterfront parkland and open space for public enjoyment. Data for WPAA footprints and access points, human powered boat launches and saltwater fishing access are also included. All Waterfront Access Map (WAM) datasets are featured on the NYC DCP Waterfront Access Map

    All previously released versions of this data are available at BYTES of the BIG APPLE- Archive

    --- Original source retains full ownership of the source dataset ---

  9. f

    Summary of the final binomial iid models fits.

    • plos.figshare.com
    xlsx
    Updated Feb 4, 2025
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    Jean Artois; Timothée Vergne; Lisa Fourtune; Simon Dellicour; Axelle Scoizec; Sophie Le Bouquin; Jean-Luc Guérin; Mathilde C. Paul; Claire Guinat (2025). Summary of the final binomial iid models fits. [Dataset]. http://doi.org/10.1371/journal.pone.0316248.s004
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    xlsxAvailable download formats
    Dataset updated
    Feb 4, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Jean Artois; Timothée Vergne; Lisa Fourtune; Simon Dellicour; Axelle Scoizec; Sophie Le Bouquin; Jean-Luc Guérin; Mathilde C. Paul; Claire Guinat
    License

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

    Description

    In this study, we present a comprehensive analysis of the key spatial risk factors and predictive risk maps for HPAI infection in France, with a focus on the 2016–17 and 2020–21 epidemic waves. Our findings indicate that the most explanatory spatial predictor variables were related to fattening duck movements prior to the epidemic, which should be considered as indicators of farm operational status, e.g., whether they are active or not. Moreover, we found that considering the operational status of duck houses in nearby municipalities is essential for accurately predicting the risk of future HPAI infection. Our results also show that the density of fattening duck houses could be used as a valuable alternative predictor of the spatial distribution of outbreaks per municipality, as this data is generally more readily available than data on movements between houses. Accurate data regarding poultry farm densities and movements is critical for developing accurate mathematical models of HPAI virus spread and for designing effective prevention and control strategies for HPAI. Finally, our study identifies the highest risk areas for HPAI infection in southwest and northwest France, which is valuable for informing national risk-based strategies and guiding increased surveillance efforts in these regions.

  10. t

    Infill Incentive District - ZT

    • gisdata.tucsonaz.gov
    Updated May 30, 2017
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    City of Tucson (2017). Infill Incentive District - ZT [Dataset]. https://gisdata.tucsonaz.gov/datasets/cotgis::infill-incentive-district-zt/about
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    Dataset updated
    May 30, 2017
    Dataset authored and provided by
    City of Tucson
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    Status: UPDATED occasionally using ArcMap Contact: Allen Scully for dissolved version: allen.scully@tucsonaz.govJesse Reyes for original, non-dissolved data. City of Tucson Development Services, 520-837-6963, Jesse.Reyes@tucsonaz.gov Intended Use: For map display. Supplemental Information: An overlay zone typically imposes a set of requirements in addition to those laid out by the underlying zoning regulations in the Land Use Code (LUC). The exact boundaries of the IID overlay are identified on the official zoning maps kept on file in the offices of the Planning and Development Services Department and the City Clerks. Changes triggered by Mayor and Council amendments to Land Use Code. Links:http://www.tucsoncommercial.com/images/Tucson_Zoning_Summary.pdfhttp://cms3.tucsonaz.gov/sites/default/files/imported/maps/city/infillincentivedistmaterial.pdf 6/6/2011 - BAE - deleted IIS_CODE field, not used and was getting out of sync with the NAME fieldDecember 2010 - J. Reyes added subdistrict polygon 10/05/2010 - split into two subdistricts per ordinance 10841 03/23/2010 - Name change. Formerly known as infill_incentive 09/15/2009 - Modified per direction from mayor and council09/09/2009 - Modified as per ordinance 10710 10/24/2006 - Defined by resolution 204487

  11. A

    ‘DVS Resource Map’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Jan 27, 2022
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2022). ‘DVS Resource Map’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-dvs-resource-map-880d/2e37487f/?iid=002-698&v=presentation
    Explore at:
    Dataset updated
    Jan 27, 2022
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘DVS Resource Map’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/6c0f7f5d-d099-45ee-abbc-ea00d6650162 on 27 January 2022.

    --- Dataset description provided by original source is as follows ---

    Assistance requests for services, care, or resources supported via phone, in-person, postal mail or electronic mail. Assistance and support involve connecting City veterans and their families to a coordinated network of public, private and non-profit organizations.

    --- Original source retains full ownership of the source dataset ---

  12. Power of various dependence tests in a unidirectionally coupled logistic map...

    • plos.figshare.com
    xlsx
    Updated Sep 13, 2024
    + more versions
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    Alex E. Yuan; Wenying Shou (2024). Power of various dependence tests in a unidirectionally coupled logistic map process. [Dataset]. http://doi.org/10.1371/journal.pbio.3002758.s004
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    xlsxAvailable download formats
    Dataset updated
    Sep 13, 2024
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Alex E. Yuan; Wenying Shou
    License

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

    Description

    Power of various dependence tests in a unidirectionally coupled logistic map process.

  13. A

    ‘2015 Dialysis BSI TABLE MAP’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Nov 12, 2021
    + more versions
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2021). ‘2015 Dialysis BSI TABLE MAP’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-2015-dialysis-bsi-table-map-608c/cbf956a6/?iid=004-363&v=presentation
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    Dataset updated
    Nov 12, 2021
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘2015 Dialysis BSI TABLE MAP’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/04de959f-39da-4547-8026-29dab05c6cb4 on 12 November 2021.

    --- Dataset description provided by original source is as follows ---

    Combined bloodstream infections at dialysis centers

    --- Original source retains full ownership of the source dataset ---

  14. California Electric Balancing Authority Areas (Retired)

    • data.cnra.ca.gov
    • data.ca.gov
    • +7more
    Updated Aug 3, 2021
    + more versions
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    California Energy Commission (2021). California Electric Balancing Authority Areas (Retired) [Dataset]. https://data.cnra.ca.gov/dataset/california-electric-balancing-authority-areas-retired
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    arcgis geoservices rest api, csv, gdb, geojson, kml, zip, txt, html, gpkg, xlsxAvailable download formats
    Dataset updated
    Aug 3, 2021
    Dataset authored and provided by
    California Energy Commissionhttp://www.energy.ca.gov/
    License

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

    Area covered
    California
    Description
    A balancing authority is responsible for operating a transmission control area. It matches generation with load and maintains consistent electric frequency of the grid, even during extreme weather conditions or natural disasters. The California Independent System Operator (CAISO) is the largest of about 38 balancing authorities in the western interconnection coordinating council (WECC), handling an estimated 35 percent of the electric load in the west. CAISO manages 80 percent of the load in California and a small portion of Nevada.

    The main balancing authorities in California are:
  15. t

    BIOGRID CURATED DATA FOR PUBLICATION: Yeast two-hybrid map of Arabidopsis...

    • thebiogrid.org
    zip
    Updated May 1, 2007
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    BioGRID Project (2007). BIOGRID CURATED DATA FOR PUBLICATION: Yeast two-hybrid map of Arabidopsis TFIID. [Dataset]. https://thebiogrid.org/71732/publication/yeast-two-hybrid-map-of-arabidopsis-tfiid.html
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    zipAvailable download formats
    Dataset updated
    May 1, 2007
    Dataset authored and provided by
    BioGRID Project
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    Protein-Protein, Genetic, and Chemical Interactions for Lawit SJ (2007):Yeast two-hybrid map of Arabidopsis TFIID. curated by BioGRID (https://thebiogrid.org); ABSTRACT: General transcription factor IID (TFIID) is a multisubunit protein complex involved in promoter recognition and is fundamental to the nucleation of the RNA polymerase II transcriptional preinitiation complex. TFIID is comprised of the TATA binding protein (TBP) and 12-15 TBP-associated factors (TAFs). While general transcription factors have been extensively studied in metazoans and yeast, little is known about the details of their structure and function in the plant kingdom. This work represents the first attempt to compare the structure of a plant TFIID complex with that determined for other organisms. While no TAF3 homolog has been observed in plants, at least one homolog has been identified for each of the remaining 14 TFIID subunits, including both TAF14 and TAF15 which have previously been shown to be unique to either yeast or humans. The presence of both TAFs 14 and 15 in plants suggests ancient roles for these proteins that were lost in metazoans and fungi, respectively. Yeast two-hybrid interaction assays resulted in a total of 65 binary interactions between putative subunits of Arabidopsis TFIID, including 26 contacts unique to plants. The interaction matrix of Arabidopsis TAFs is largely consistent with the three-lobed topological map for yeast TFIID, which suggests that the structure and composition of TFIID have been highly conserved among eukaryotes.

  16. A

    ‘Map of NYCHA Community Facilities’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Feb 13, 2022
    + more versions
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2022). ‘Map of NYCHA Community Facilities’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-map-of-nycha-community-facilities-8011/e9a58e8a/?iid=003-994&v=presentation
    Explore at:
    Dataset updated
    Feb 13, 2022
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘Map of NYCHA Community Facilities’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/069edd40-5431-4bc8-9ffa-b22615e76a80 on 13 February 2022.

    --- Dataset description provided by original source is as follows ---

    Locations of the Community Operations facilities as of September 2015.

    --- Original source retains full ownership of the source dataset ---

  17. A

    ‘Sea Level Rise Maps (2050s 500-year Floodplain)’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Jul 24, 2013
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2013). ‘Sea Level Rise Maps (2050s 500-year Floodplain)’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-sea-level-rise-maps-2050s-500-year-floodplain-930c/74e90c24/?iid=002-407&v=presentation
    Explore at:
    Dataset updated
    Jul 24, 2013
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘Sea Level Rise Maps (2050s 500-year Floodplain)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/acc7cedb-cb11-47e6-93bb-265ddb2575f7 on 13 February 2022.

    --- Dataset description provided by original source is as follows ---

    This is the 500-Year Floodplain for the 2050s based on FEMA's Preliminary Work Map data and the New York Panel on Climate Change's 90th Percentile Projects for Sea-Level Rise (31 inches). Please see the Disclaimer PDF for more information. Data Provided by the Mayor's Office of Long-Term Planning and Sustainability (OLTPS) on behalf of CUNY Institute for Sustainable Cities (CISC) and the New York Panel on Climate Change (NPCC).

    --- Original source retains full ownership of the source dataset ---

  18. A

    ‘Sea Level Rise Maps (2050s 100-year Floodplain)’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Jul 24, 2013
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2013). ‘Sea Level Rise Maps (2050s 100-year Floodplain)’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-sea-level-rise-maps-2050s-100-year-floodplain-0d93/822ee510/?iid=002-244&v=presentation
    Explore at:
    Dataset updated
    Jul 24, 2013
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘Sea Level Rise Maps (2050s 100-year Floodplain)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/2b2c6d74-7abf-4d03-b6a9-f6e54185271d on 13 February 2022.

    --- Dataset description provided by original source is as follows ---

    This is the 100-Year Floodplain for the 2050s based on FEMA's Preliminary Work Map data and the New York Panel on Climate Change's 90th Percentile Projects for Sea-Level Rise (31 inches). Please see the Disclaimer PDF for more information. Data Provided by the Mayor's Office of Long-Term Planning and Sustainability (OLTPS) on behalf of CUNY Institute for Sustainable Cities (CISC) and the New York Panel on Climate Change (NPCC).

    --- Original source retains full ownership of the source dataset ---

  19. A

    ‘Bicycle Routes Across New York State: Map’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Jul 13, 2013
    + more versions
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2013). ‘Bicycle Routes Across New York State: Map’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-bicycle-routes-across-new-york-state-map-db8d/d05bf3fb/?iid=004-884&v=presentation
    Explore at:
    Dataset updated
    Jul 13, 2013
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Area covered
    New York
    Description

    Analysis of ‘Bicycle Routes Across New York State: Map’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/f6c866cc-ab80-4042-97bc-2db2f6e8682a on 12 February 2022.

    --- Dataset description provided by original source is as follows ---

    Bicycle routes and recreational activities allowed on the route within New York State - https://www.dot.ny.gov/display/programs/bicycle. This list includes both on- and off-road bicycle routes and even includes information on surface type as well as other types of recreational activities allowed on the route.

    --- Original source retains full ownership of the source dataset ---

  20. A

    ‘Weather Stations Used to Compile the Mean Annual Precipitation Map for...

    • analyst-2.ai
    Updated Nov 12, 2021
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2021). ‘Weather Stations Used to Compile the Mean Annual Precipitation Map for Idaho’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-weather-stations-used-to-compile-the-mean-annual-precipitation-map-for-idaho-b28a/20e07bc0/?iid=005-826&v=presentation
    Explore at:
    Dataset updated
    Nov 12, 2021
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Area covered
    Idaho
    Description

    Analysis of ‘Weather Stations Used to Compile the Mean Annual Precipitation Map for Idaho’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/1ba4ff80-aa37-40c6-84c8-e65da2913256 on 12 November 2021.

    --- Dataset description provided by original source is as follows ---

    This data set reflects National Weather Service (NWS) and National Resources Conservation Service (NRCS) stations for the state of Idaho. There are 213 stations in this data set and these are the stations used to compile the mean annual precipitation map for Idaho which was created by Myron Molnau.

    Source data for this web service can be downloaded from https://insideidaho.org/data/ago/ics/weatStns_id_ics.zip.

    Related data set: Precipitation for Idaho; Mean Annual (1961-90)

    --- Original source retains full ownership of the source dataset ---

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Close
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URSpatial (2015). Imperial Irrigation Service District Boundary [Dataset]. https://hub.arcgis.com/datasets/09e260e5f9f54b48b9b84fbe42da9a3b

Imperial Irrigation Service District Boundary

Explore at:
Dataset updated
Jul 1, 2015
Dataset authored and provided by
URSpatial
Area covered
Description

Imperial Irrigation Service District Boundary. Linework digitized from map posted on IID web site. http://www.iid.com/power/power-servicemap.html It was then corrected based on review from agency personnel.

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