53 datasets found
  1. a

    Highest Education Completed is Associate's Degree

    • hub.arcgis.com
    Updated May 19, 2020
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    Welcome to the City of Corona GIS System (2020). Highest Education Completed is Associate's Degree [Dataset]. https://hub.arcgis.com/maps/9b7449303e104a5d93e9bd8c8666dbce
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    Dataset updated
    May 19, 2020
    Dataset authored and provided by
    Welcome to the City of Corona GIS System
    Area covered
    Description

    This webmap displays the percent of population 25 years and over whose highest education completed is associate's degree. This webmap also contains the following layers: City of Corona Limits, State Boundary, County Boundary and Tract Boundary.

  2. d

    GIS Data for Geologic and Structure Map of the Choteau 1 x 2 Degree...

    • catalog.data.gov
    • data.usgs.gov
    Updated Jul 6, 2024
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    U.S. Geological Survey (2024). GIS Data for Geologic and Structure Map of the Choteau 1 x 2 Degree Quadrangle, Western Montana [Dataset]. https://catalog.data.gov/dataset/gis-data-for-geologic-and-structure-map-of-the-choteau-1-x-2-degree-quadrangle-western-mon
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    Dataset updated
    Jul 6, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Western Montana, Choteau, Montana
    Description

    The data release for the geologic and structure map of the Choteau 1 x 2 degree quadrangle, western Montana, is a Geologic Map Schema (GeMS)-compliant version that updates the GIS files for the geologic map published in U.S. Geological Survey (USGS) Miscellaneous Investigations Series Map I-1300 (Mudge and others, 2001). The updated digital data present the attribute tables and geospatial features (lines and polygons) in the format that meets GeMS requirements. This data release presents geospatial data for the geologic map that is published as two plates. Minor errors, such as mistakes in line decoration or differences between the digital data and the map image, are corrected in this version. The database represents the geology for the 4.2 million acre, geologically complex Choteau 1 x 2 degree quadrangle, at a publication scale of 1:250,000. The map covers primarily Lewis and Clark, Teton, Powell, Missoula, Lake, and Flathead Counties, but also includes minor parts of Cascade County. These GIS data supersede those in the report: Mudge, M.R., Earhart, R.L., Whipple, J.W., Harrison, J.E., Munts, S.R., and Silkwood, J.T., 2001, Geologic and structure map of the Choteau 1 x 2 degree quadrangle, western Montana: a digital database: U.S. Geological Survey Miscellaneous Investigations Series Map I-1300, version 1.0, 38 p., scale 1:250,000, https://pubs.er.usgs.gov/publication/i1300.

  3. a

    College Map

    • hub.arcgis.com
    • catalog.data.gov
    Updated Mar 15, 2017
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    National Center for Education Statistics (2017). College Map [Dataset]. https://hub.arcgis.com/items/54c1339972ad4b1eb347047c7ca3e616
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    Dataset updated
    Mar 15, 2017
    Dataset authored and provided by
    National Center for Education Statistics
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    Finding Schools is now easier than ever with the College Map, the first geographic search tool published by IPEDS (Integrated Postsecondary Education Data System) providing access to over 7,000 certificate, undergraduate and graduate-level schools. This all-in-one tool enables students, parents and counselors to filter potential programs for location, major, tuition and more. Including both certificate-level programs and advanced degrees, this public application makes the often overwhelming process of school searching simple, and it’s available on mobile devices.Once the results are narrowed down, users can share their lists on social media or download in excel format. Additionally, the College Map integrates with the College Navigator, a research based search tool providing data from the complete list of IPEDS Survey indicators.All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

  4. E

    Fifteen Degree Lat/Long Grid (World Coverage)

    • ecaidata.org
    Updated Oct 4, 2014
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    ECAI Clearinghouse (2014). Fifteen Degree Lat/Long Grid (World Coverage) [Dataset]. https://ecaidata.org/dataset/ecaiclearinghouse-id-209
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    Dataset updated
    Oct 4, 2014
    Dataset provided by
    ECAI Clearinghouse
    Area covered
    World
    Description

    A fifteen degree grid in latitude and longitude covering the entire world

  5. d

    GIS Data (ver. 2) for Geologic Terranes of the Hailey 1 x 2 Degrees...

    • catalog.data.gov
    • data.usgs.gov
    • +2more
    Updated Jul 6, 2024
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    U.S. Geological Survey (2024). GIS Data (ver. 2) for Geologic Terranes of the Hailey 1 x 2 Degrees Quadrangle and the Western Part of the Idaho Falls 1 x 2 Degrees Quadrangle, South-Central Idaho [Dataset]. https://catalog.data.gov/dataset/gis-data-ver-2-for-geologic-terranes-of-the-hailey-1-x-2-degrees-quadrangle-and-the-wester
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    Dataset updated
    Jul 6, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Idaho Falls, Idaho
    Description

    The data release for the geologic terranes of the Hailey 1 x 2 degrees quadrangle and the western part of the Idaho Falls 1 x 2 degrees quadrangle, south-central Idaho is a Geologic Map Schema (GeMS)-compliant version that updates the GIS files for the geologic map published in U.S. Geological Survey (USGS) Bulletin 2064-A (Worl and Johnson, 1995). The updated digital data present the attribute tables and geospatial features (lines and polygons) in the format that meets GeMS requirements. This data release presents the geologic map as shown on the plate and captured in geospatial data for the published map. Minor errors, such as mistakes in line decoration or differences between the digital data and the map image, are corrected in this version. The database represents the geology for the 6.1 million-acre, geologically complex Hailey quadrangle and the western part of the Idaho Falls quadrangle, at a publication scale of 1:250,000. The map covers primarily Blaine, Camas, Custer and Elmore Counties, but also includes minor parts of Ada, Butte, Gooding, Lincoln, and Minidoka Counties. These GIS data supersede those in the interpretive report: Worl, R.G. and Johnson, K.M., 1995, Geology and mineral deposits of the Hailey 1 degree x 2 degrees quadrangle and the western part of the Idaho Falls 1 degree x 2 degrees quadrangle, south-central Idaho - an overview: U.S. Geological Survey, Bulletin 2064-A, scale 1:250,000, https://pubs.usgs.gov/bul/b2064-a/.

  6. MGCP Vector - 1 degree grids

    • hurricane-nga.opendata.arcgis.com
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    Updated Sep 13, 2017
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    National Geospatial-Intelligence Agency (2017). MGCP Vector - 1 degree grids [Dataset]. https://hurricane-nga.opendata.arcgis.com/datasets/5f9d874cc77940ba8a3f7e0e463502ea
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    Dataset updated
    Sep 13, 2017
    Dataset authored and provided by
    National Geospatial-Intelligence Agencyhttp://www.nga.mil/
    Area covered
    Description

    MGCP Cells - LINKS for download of 1 degree cell sized regions of MGCP vector data. Data is in an ESRI shape file format.Multinational Geospatial Co-production Program (MGCP) datasets covering the 1°x1° degree cells.United Kingdom and CanadaApproved for Public Release

  7. Regression analysis for the degree of human impact.

    • plos.figshare.com
    xls
    Updated Jun 2, 2023
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    Linda See; Alexis Comber; Carl Salk; Steffen Fritz; Marijn van der Velde; Christoph Perger; Christian Schill; Ian McCallum; Florian Kraxner; Michael Obersteiner (2023). Regression analysis for the degree of human impact. [Dataset]. http://doi.org/10.1371/journal.pone.0069958.t006
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    xlsAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Linda See; Alexis Comber; Carl Salk; Steffen Fritz; Marijn van der Velde; Christoph Perger; Christian Schill; Ian McCallum; Florian Kraxner; Michael Obersteiner
    License

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

    Description

    Regression analysis for the degree of human impact.

  8. Raw 1/10th Degree Data (All)

    • climate-center-lincolninstitute.hub.arcgis.com
    • climate.esri.ca
    • +23more
    Updated Aug 16, 2022
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    Esri (2022). Raw 1/10th Degree Data (All) [Dataset]. https://climate-center-lincolninstitute.hub.arcgis.com/datasets/esri2::active-hurricanes-cyclones-and-typhoons?layer=10
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    Dataset updated
    Aug 16, 2022
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Earth
    Description

    Raw 1/10th Degree Wind Force Probability data for all wind speeds.

  9. f

    Consistency of response to degree of human impact.

    • plos.figshare.com
    xls
    Updated Jun 4, 2023
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    Linda See; Alexis Comber; Carl Salk; Steffen Fritz; Marijn van der Velde; Christoph Perger; Christian Schill; Ian McCallum; Florian Kraxner; Michael Obersteiner (2023). Consistency of response to degree of human impact. [Dataset]. http://doi.org/10.1371/journal.pone.0069958.t007
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Linda See; Alexis Comber; Carl Salk; Steffen Fritz; Marijn van der Velde; Christoph Perger; Christian Schill; Ian McCallum; Florian Kraxner; Michael Obersteiner
    License

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

    Description

    Consistency of response to degree of human impact.

  10. f

    PERM cases by degree level

    • froghire.ai
    Updated Apr 3, 2025
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    FrogHire.ai (2025). PERM cases by degree level [Dataset]. https://www.froghire.ai/major/Civil%20Engineering%3B%20Gis%20Graduate%20Program
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    Dataset updated
    Apr 3, 2025
    Dataset provided by
    FrogHire.ai
    Description

    This pie chart illustrates the distribution of degrees—Bachelor’s, Master’s, and Doctoral—among PERM graduates from Civil Engineering; Gis Graduate Program. It shows the educational composition of students who have pursued and successfully obtained permanent residency through their qualifications in Civil Engineering; Gis Graduate Program. This visualization helps to understand the diversity of educational backgrounds that contribute to successful PERM applications, reflecting the major’s role in fostering students’ career paths towards permanent residency in the U.S.

  11. u

    Utah Lat Long Grid One Degree

    • opendata.gis.utah.gov
    Updated Jan 14, 2020
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    Utah Automated Geographic Reference Center (AGRC) (2020). Utah Lat Long Grid One Degree [Dataset]. https://opendata.gis.utah.gov/datasets/utah-lat-long-grid-one-degree
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    Dataset updated
    Jan 14, 2020
    Dataset authored and provided by
    Utah Automated Geographic Reference Center (AGRC)
    License

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

    Area covered
    Description

    NOTE: This dataset is an older dataset that we have removed from the SGID and 'shelved' in ArcGIS Online. There may (or may not) be a newer vintage of this dataset in the SGID.

  12. f

    Regression analysis for the model Yi = a+bXi+εi, where Yi is the degree of...

    • plos.figshare.com
    xls
    Updated Jun 3, 2023
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    Linda See; Alexis Comber; Carl Salk; Steffen Fritz; Marijn van der Velde; Christoph Perger; Christian Schill; Ian McCallum; Florian Kraxner; Michael Obersteiner (2023). Regression analysis for the model Yi = a+bXi+εi, where Yi is the degree of human impact from the control data, Xi is the degree of human impact from the participants. [Dataset]. http://doi.org/10.1371/journal.pone.0069958.t003
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 3, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Linda See; Alexis Comber; Carl Salk; Steffen Fritz; Marijn van der Velde; Christoph Perger; Christian Schill; Ian McCallum; Florian Kraxner; Michael Obersteiner
    License

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

    Description

    Regression analysis for the model Yi = a+bXi+εi, where Yi is the degree of human impact from the control data, Xi is the degree of human impact from the participants.

  13. f

    Data from: Average salary

    • froghire.ai
    Updated Apr 6, 2025
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    FrogHire.ai (2025). Average salary [Dataset]. https://www.froghire.ai/major/Master%27S%20Degree%20In%20Geography%20With%20Concentration%20In%20Gis
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    Dataset updated
    Apr 6, 2025
    Dataset provided by
    FrogHire.ai
    Description

    Explore the progression of average salaries for graduates in Master'S Degree In Geography With Concentration In Gis from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Master'S Degree In Geography With Concentration In Gis relative to other fields. This data is essential for students assessing the return on investment of their education in Master'S Degree In Geography With Concentration In Gis, providing a clear picture of financial prospects post-graduation.

  14. The regression analysis of predicting the degree of human impact by expert...

    • plos.figshare.com
    xls
    Updated May 31, 2023
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    Linda See; Alexis Comber; Carl Salk; Steffen Fritz; Marijn van der Velde; Christoph Perger; Christian Schill; Ian McCallum; Florian Kraxner; Michael Obersteiner (2023). The regression analysis of predicting the degree of human impact by expert and non-expert groups, when the regression is split into 2 simultaneous models. [Dataset]. http://doi.org/10.1371/journal.pone.0069958.t005
    Explore at:
    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Linda See; Alexis Comber; Carl Salk; Steffen Fritz; Marijn van der Velde; Christoph Perger; Christian Schill; Ian McCallum; Florian Kraxner; Michael Obersteiner
    License

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

    Description

    The regression analysis of predicting the degree of human impact by expert and non-expert groups, when the regression is split into 2 simultaneous models.

  15. d

    GIS Data for Selected Data from the Geologic Map of the Western Part of the...

    • catalog.data.gov
    Updated Jul 24, 2025
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    U.S. Geological Survey (2025). GIS Data for Selected Data from the Geologic Map of the Western Part of the Cut Bank 1 Degree x 2 Degrees Quadrangle, Northwestern Montana [Dataset]. https://catalog.data.gov/dataset/gis-data-for-selected-data-from-the-geologic-map-of-the-western-part-of-the-cut-bank-1-deg
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    Dataset updated
    Jul 24, 2025
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Description

    This U.S. Geological Survey (USGS) data release updates the digital geospatial database for the southern portion of the geologic map of the western part of the Cut Bank 1 degree x 2 degrees quadrangle, northwestern Montana (Harrison and others, 1998). Attribute tables and geospatial features (points, lines, and polygons) conform to the Geologic Map Schema (USGS NCGMP, 2020). The 899,246-acre map area represents the geology at a publication scale of 1:250,000. Minor errors, such as mistakes in line decoration or differences between the digital data and the map image, are corrected, and missing orientation points are included in this version. The map covers primarily Flathead, Glacier, Pondera, and Teton Counties, but also includes minor parts of Lake County. References: Harrison, J.E., Whipple, J.W., and Lidke, 1998, Geologic Map of the Western Part of the Cut Bank 1 degree x 2 degrees quadrangle, Northwestern Montana: U.S. Geological Survey Miscellaneous Investigations Series Map I-2593, version 1.0, 31 p., scale 1:250,000, https://ngmdb.usgs.gov/Prodesc/proddesc_13063.htm. U.S. Geological Survey National Cooperative Geologic Mapping Program, 2020, GeMS (Geologic Map Schema) - A standard format for the digital publication of geologic maps: U.S. Geological Survey Techniques and Methods, book 11, chap. B10, 74 p., https://doi.org//10.3133/tm11B10.

  16. f

    PERM cases by degree level

    • froghire.ai
    Updated Apr 6, 2025
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    FrogHire.ai (2025). PERM cases by degree level [Dataset]. https://www.froghire.ai/major/Master%27S%20Degree%20In%20Geography%20With%20Concentration%20In%20Gis
    Explore at:
    Dataset updated
    Apr 6, 2025
    Dataset provided by
    FrogHire.ai
    Description

    This pie chart illustrates the distribution of degrees—Bachelor’s, Master’s, and Doctoral—among PERM graduates from Master'S Degree In Geography With Concentration In Gis. It shows the educational composition of students who have pursued and successfully obtained permanent residency through their qualifications in Master'S Degree In Geography With Concentration In Gis. This visualization helps to understand the diversity of educational backgrounds that contribute to successful PERM applications, reflecting the major’s role in fostering students’ career paths towards permanent residency in the U.S.

  17. f

    PERM cases by degree level

    • froghire.ai
    Updated Apr 3, 2025
    + more versions
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    FrogHire.ai (2025). PERM cases by degree level [Dataset]. https://www.froghire.ai/major/Geography%20Wemphasis%20In%20Geographic%20Information%20System%20Gis
    Explore at:
    Dataset updated
    Apr 3, 2025
    Dataset provided by
    FrogHire.ai
    Description

    This pie chart illustrates the distribution of degrees—Bachelor’s, Master’s, and Doctoral—among PERM graduates from Geography Wemphasis In Geographic Information System Gis. It shows the educational composition of students who have pursued and successfully obtained permanent residency through their qualifications in Geography Wemphasis In Geographic Information System Gis. This visualization helps to understand the diversity of educational backgrounds that contribute to successful PERM applications, reflecting the major’s role in fostering students’ career paths towards permanent residency in the U.S.

  18. c

    Percent of 25 or Older with a Bachelor's Degree or More 2020

    • geohub.cityoftacoma.org
    Updated May 24, 2021
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    City of Tacoma GIS (2021). Percent of 25 or Older with a Bachelor's Degree or More 2020 [Dataset]. https://geohub.cityoftacoma.org/datasets/ba99dac9103943ee8430839eea4d3a13
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    Dataset updated
    May 24, 2021
    Dataset authored and provided by
    City of Tacoma GIS
    License

    https://geohub.cityoftacoma.org/pages/disclaimerhttps://geohub.cityoftacoma.org/pages/disclaimer

    Area covered
    Description

    How did the City create the Equity IndexWorking with Ohio State University's Kirwan Institute of Race and Social Justice, the City complied the Equity/Opportunity Index to help facilitate data-driven decision-making processes and enable leaders to distribute resources better and plan to fund programs and services, minimize inequities and maximize opportunities.The indicators displayed in the Equity/Opportunity Index have been shown to have a direct correlation to equity. For more information, please reference the additional document on the evidence-based research determinant categories. The data is measured granularly by census block group.To just access the overall equity layer use this url: https://gis.cityoftacoma.org/arcgis/rest/services/General/Equity2020/MapServer/1 The list below comprise the Indicators per index: Accessibility Parks & Open SpaceVoter ParticipationHealthy Food Access IndexAverage Road QualityHome Internet AccessTransit Options & AccessVehicle AccessLivabilityTacoma Crime IndexESRI Crime IndexCost-Burdened HouseholdsAverage Life ExpectancyUrban Tree CanopyTacoma Nuisance IndexMedian Home ValueEducationAverage Student Test RateAverage Student Mobility4-Year High School Graduation RatePercent of 25+-Year-Olds with Bachelor's Degree or MoreEconomyJobs Index (availableness of good paying jobs)Median Household Income200% Below of the Poverty Line or LessUnemployment RateEnvironmental HealthEnvironmental ExposuresNOx- Diesel Emissions (Annual Tons/Km2)Ozone ConcentrationPM2.5 ConcentrationPopulations Near Heavy Traffic RoadwaysToxic Releases from Facilities (RSEI Model)Environmental EffectsLead Risk from Housing (%)Proximity to Hazardous Waste Treatment Storage and Disposal Facilities (TSDFs)Proximity to National Priorities List Facilities (Superfund Sites)Proximity to Risk Management Plan (RMP) FacilitiesWastewater DischargeWhat does Very High or Very Low Equity/Opportunity mean?Very High Equity/Opportunity represents locations that have access to better opportunities to succeed and excel in life. The indicators include high-performing schools, a safe environment, access to adequate transportation, safe neighborhoods, and sustainable employment. In contrast, Low Equity/Opportunity areas have more obstacles and barriers within the area. These communities have limited access to institutional or societal investments with limits their quality of life.Why is the North and West End labeled Red?When looking at data related to equity and social justice, we want to be mindful not to reinforce historical representations of low-income or communities of color as bad or negative. To help visualize the areas of high opportunity and call out the need for more equity, we chose to use red. We flipped the gradient to highlight disparities within the community. Besides, we refrained from using green or positive colors with referring to dominant communities (white communities).Can I download the full dataset and display other variables over the Equity Index?Yes, by downloading the file and uploading it to ArcGIS, you will be able to see all the indicators, Z-Scores, indices, and the index overall value. You can overlay other variables for further analysis and save the output into your database. If your team wants to add new indicators to the Equity Index, contact Bucoda Warren. Can I see additional or multiple map layers?Within the left navigation panel, you can aggregate the index layers by determinate social categories; Accessibility, Education, Economy, Livability and Environmental Health.

  19. f

    PERM cases by degree level

    • froghire.ai
    Updated Apr 3, 2025
    + more versions
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    FrogHire.ai (2025). PERM cases by degree level [Dataset]. https://www.froghire.ai/major/Gis
    Explore at:
    Dataset updated
    Apr 3, 2025
    Dataset provided by
    FrogHire.ai
    Description

    This pie chart illustrates the distribution of degrees—Bachelor’s, Master’s, and Doctoral—among PERM graduates from Gis. It shows the educational composition of students who have pursued and successfully obtained permanent residency through their qualifications in Gis. This visualization helps to understand the diversity of educational backgrounds that contribute to successful PERM applications, reflecting the major’s role in fostering students’ career paths towards permanent residency in the U.S.

  20. u

    Climate Change Pressures Growing Degree Days (Map Service)

    • agdatacommons.nal.usda.gov
    • opendata.rcmrd.org
    • +3more
    bin
    Updated Oct 1, 2024
    + more versions
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    U.S. Forest Service (2024). Climate Change Pressures Growing Degree Days (Map Service) [Dataset]. https://agdatacommons.nal.usda.gov/articles/dataset/Climate_Change_Pressures_Growing_Degree_Days_Map_Service_/25974259
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    binAvailable download formats
    Dataset updated
    Oct 1, 2024
    Dataset authored and provided by
    U.S. Forest Service
    License

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

    Description

    Evaluating multiple signals of climate change across the conterminous United States during three 30-year periods (2010�2039, 2040�2069, 2070�2099) during this century to a baseline period (1980�2009) emphasizes potential changes for growing degree days (GDD), plant hardiness zones (PHZ), and heat zones. These indices were derived using the CCSM4 and GFDL CM3 models under the representative concentration pathways 4.5 and 8.5, respectively, and included in Matthews et al. (2018). Daily temperature was downscaled by Maurer et al.�(https://doi.org/10.1029/2007EO470006 at a 1/8 degree grid scale and used to obtain growing degree days, plant hardiness zones, and heat zones.�Each of these indices provides unique information about plant health related to changes in climatic conditions that influence establishment, growth, and survival. These data and the calculated changes are provided as 14 individual IMG files for each index to assist with management planning and decision making into the future. For each of the four indices the following are included: two baseline files (1980�2009), three files representing 30-year periods for the scenario CCSM4 under RCP 4.5 along with three files of changes, and three files representing 30-year periods for the scenario GFDL CM3 under RCP 8.5 along with three files of changes. Growing degree days address an important component to general patterns of plant growth by accumulating the degree days across the growing season. This metric provides a level of detail related to defining the growing season potential. Here, we evaluate the accumulation of growing degree days at or above 5 �C (41 �F), assuming that limited growth occurs below 5 �C.�Specifically, we calculate growing degree days by first calculating the average daily temperature, based on the maximum and minimum projected daily temperature. We then subtract 5 �C from each mean value and then accumulate the positive difference values for all days within each year. The mean GDD values for the conterminous United States during the baseline period ranged from less than 100 to over 7,000 degree days, increasing from north to south with highest values in the Florida panhandle, southern Texas, southwestern Arizona, and southeastern California. GDD projections throughout the century suggest a ubiquitous increase across the United States with slightly less change in the Northeast and much greater increases throughout the southern United States under the high scenario. Original data and associated metadata can be downloaded from this website:�https://www.fs.usda.gov/rds/archive/Product/RDS-2019-0001This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService For complete information, please visit https://data.gov.

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Welcome to the City of Corona GIS System (2020). Highest Education Completed is Associate's Degree [Dataset]. https://hub.arcgis.com/maps/9b7449303e104a5d93e9bd8c8666dbce

Highest Education Completed is Associate's Degree

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Dataset updated
May 19, 2020
Dataset authored and provided by
Welcome to the City of Corona GIS System
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Description

This webmap displays the percent of population 25 years and over whose highest education completed is associate's degree. This webmap also contains the following layers: City of Corona Limits, State Boundary, County Boundary and Tract Boundary.

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