100+ datasets found
  1. a

    Check List for GIS Ambassadors

    • edu.hub.arcgis.com
    Updated Sep 20, 2022
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    Education and Research (2022). Check List for GIS Ambassadors [Dataset]. https://edu.hub.arcgis.com/documents/9510e8c9d06c44b487aaa39efccd5131
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    Dataset updated
    Sep 20, 2022
    Dataset authored and provided by
    Education and Research
    Description

    A check list of items to discuss with the teacher to make sure you have all the information required before your GIS Ambassador support session.

  2. d

    Geospatial Data from the Alpine Treeline Warming Experiment (ATWE) on Niwot...

    • search.dataone.org
    • data.ess-dive.lbl.gov
    • +2more
    Updated Jul 7, 2021
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    Fabian Zuest; Cristina Castanha; Nicole Lau; Lara M. Kueppers (2021). Geospatial Data from the Alpine Treeline Warming Experiment (ATWE) on Niwot Ridge, Colorado, USA [Dataset]. http://doi.org/10.15485/1804896
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    Dataset updated
    Jul 7, 2021
    Dataset provided by
    ESS-DIVE
    Authors
    Fabian Zuest; Cristina Castanha; Nicole Lau; Lara M. Kueppers
    Time period covered
    Jan 1, 2008 - Jan 1, 2012
    Area covered
    Description

    This is a collection of all GPS- and computer-generated geospatial data specific to the Alpine Treeline Warming Experiment (ATWE), located on Niwot Ridge, Colorado, USA. The experiment ran between 2008 and 2016, and consisted of three sites spread across an elevation gradient. Geospatial data for all three experimental sites and cone/seed collection locations are included in this package. ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Geospatial files include cone collection, experimental site, seed trap, and other GPS location/terrain data. File types include ESRI shapefiles, ESRI grid files or Arc/Info binary grids, TIFFs (.tif), and keyhole markup language (.kml) files. Trimble-imported data include plain text files (.txt), Trimble COR (CorelDRAW) files, and Trimble SSF (Standard Storage Format) files. Microsoft Excel (.xlsx) and comma-separated values (.csv) files corresponding to the attribute tables of many files within this package are also included. A complete list of files can be found in this document in the “Data File Organization” section in the included Data User's Guide. Maps are also included in this data package for reference and use. These maps are separated into two categories, 2021 maps and legacy maps, which were made in 2010. Each 2021 map has one copy in portable network graphics (.png) format, and the other in .pdf format. All legacy maps are in .pdf format. .png image files can be opened with any compatible programs, such as Preview (Mac OS) and Photos (Windows). All GIS files were imported into geopackages (.gpkg) using QGIS, and double-checked for compatibility and data/attribute integrity using ESRI ArcGIS Pro. Note that files packaged within geopackages will open in ArcGIS Pro with “main.” preceding each file name, and an extra column named “geom” defining geometry type in the attribute table. The contents of each geospatial file remain intact, unless otherwise stated in “niwot_geospatial_data_list_07012021.pdf/.xlsx”. This list of files can be found as an .xlsx and a .pdf in this archive. As an open-source file format, files within gpkgs (TIFF, shapefiles, ESRI grid or “Arc/Info Binary”) can be read using both QGIS and ArcGIS Pro, and any other geospatial softwares. Text and .csv files can be read using TextEdit/Notepad/any simple text-editing software; .csv’s can also be opened using Microsoft Excel and R. .kml files can be opened using Google Maps or Google Earth, and Trimble files are most compatible with Trimble’s GPS Pathfinder Office software. .xlsx files can be opened using Microsoft Excel. PDFs can be opened using Adobe Acrobat Reader, and any other compatible programs. A selection of original shapefiles within this archive were generated using ArcMap with associated FGDC-standardized metadata (xml file format). We are including these original files because they contain metadata only accessible using ESRI programs at this time, and so that the relationship between shapefiles and xml files is maintained. Individual xml files can be opened (without a GIS-specific program) using TextEdit or Notepad. Since ESRI’s compatibility with FGDC metadata has changed since the generation of these files, many shapefiles will require upgrading to be compatible with ESRI’s latest versions of geospatial software. These details are also noted in the “niwot_geospatial_data_list_07012021” file.

  3. c

    GIS Data Viewer New

    • opendata.co.cumberland.nc.us
    • hub.arcgis.com
    Updated Nov 14, 2019
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    Cumberland County, NC (2019). GIS Data Viewer New [Dataset]. https://opendata.co.cumberland.nc.us/maps/d203e928181d46658f26fb3b5947921c
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    Dataset updated
    Nov 14, 2019
    Dataset authored and provided by
    Cumberland County, NC
    Area covered
    Description

    The Cumberland County GIS Data Viewer provides the general public with parcel, zoning, hydrology, soils, utilities and topographic data. You can search for a specific address, street name, parcel number (PIN), or by the owner's name.

  4. M

    Status of Free and Open Public Geospatial Data from Minnesota Counties

    • gisdata.mn.gov
    • data.wu.ac.at
    fgdb, gpkg, html +3
    Updated Apr 24, 2025
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    Geospatial Information Office (2025). Status of Free and Open Public Geospatial Data from Minnesota Counties [Dataset]. https://gisdata.mn.gov/dataset/bdry-mn-county-open-data-status
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    printable_map, jpeg, fgdb, html, shp, gpkgAvailable download formats
    Dataset updated
    Apr 24, 2025
    Dataset provided by
    Geospatial Information Office
    Area covered
    Minnesota
    Description

    This map shows the free and open data status of county public geospatial (GIS) data across Minnesota. The accompanying data set can be used to make similar maps using GIS software.

    Counties shown in this dataset as having free and open public geospatial data (with or without a policy) are: Aitkin, Anoka, Becker, Beltrami, Benton, Big Stone, Carlton, Carver, Cass, Chippewa, Chisago, Clay, Clearwater, Cook, Crow Wing, Dakota, Douglas, Grant, Hennepin, Hubbard, Isanti, Itasca, Kittson, Koochiching, Lac qui Parle, Lake, Lyon, Marshall, McLeod, Meeker, Mille Lacs, Morrison, Mower, Norman, Olmsted, Otter Tail, Pipestone, Polk, Pope, Ramsey, Renville, Rice, Scott, Sherburne, Stearns, Steele, Stevens, St. Louis, Traverse, Waseca, Washington, Wilkin, Winona, Wright and Yellow Medicine.

    To see if a county's data is distributed via the Minnesota Geospatial Commons, check the Commons organizations page: https://gisdata.mn.gov/organization

    To see if a county distributes data via its website, check the link(s) on the Minnesota County GIS Contacts webpage: https://www.mngeo.state.mn.us/county_contacts.html

  5. c

    Interactive GIS Mapping Tool – Fully Appropriated Stream Systems (FASS) in...

    • gis.data.ca.gov
    • hub.arcgis.com
    • +2more
    Updated Apr 5, 2021
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    California Water Boards (2021). Interactive GIS Mapping Tool – Fully Appropriated Stream Systems (FASS) in California [Dataset]. https://gis.data.ca.gov/maps/6e9e2a7727ab46f8b76244cff111a4ee
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    Dataset updated
    Apr 5, 2021
    Dataset authored and provided by
    California Water Boards
    Area covered
    Description

    This mapping tool provides a representation of the general watershed boundaries for stream systems declared fully appropriated by the State Water Board. The boundaries were created by Division of Water Rights staff by delineating FASS critical reaches and consolidating HUC 12 sub-watersheds to form FASS Watershed boundaries. As such, the boundaries are in most cases conservative with respect to the associated stream system. However, users should check neighboring FASS Watersheds to ensure the stream system of interest is not restricted by other FASS listings. For more information regarding the Declaration of Fully Appropriated Stream Systems, visit the Division of Water Rights’ Fully Appropriated Streams webpage. How to Use the Interactive Mapping Tool: If it is your first time viewing the map, you will need to click the “OK” box on the splash screen and agree to the disclaimer before continuing. Navigate to your point of interest by either using the search bar or by zooming in on the map. You may enter a stream name, street address, or watershed ID in the search bar. Click on the map to identify the location of interest and one or more pop-up boxes may appear with information about the fully appropriated stream systems within the general watershed boundaries of the identified location. The information provided in the pop-up box may include: (a) stream name, (b) tributary, (c) season declared fully appropriated, (d) Board Decisions/Water Right Orders, and/or (e) court references/adjudications. You may toggle the FAS Streams reference layer on and off to find representative critical reaches associated with the FASS Watershed layer. Please note that this layer is for general reference purposes only and ultimately the critical reach listed in Appendix A of Water Rights Order 98-08 and Appendix A together with any associated footnotes controls. Note: A separate FAS Watershed boundary layer was created for the Bay-Delta Watershed. The Bay-Delta Watershed layer should be toggled on to check if the area of interest is fully appropriated under State Water Board Decision 1594.

  6. Nest Check Data VOL

    • gis-fws.opendata.arcgis.com
    • hub.arcgis.com
    Updated May 13, 2021
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    U.S. Fish & Wildlife Service (2021). Nest Check Data VOL [Dataset]. https://gis-fws.opendata.arcgis.com/datasets/nest-check-data-vol
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    Dataset updated
    May 13, 2021
    Dataset provided by
    U.S. Fish and Wildlife Servicehttp://www.fws.gov/
    Authors
    U.S. Fish & Wildlife Service
    Area covered
    Earth
    Description

    Volunteer plover surveyors can use this form to report sightings and counts of piping plovers, observations of birds viewed on nest from a distance, sightings of banded individuals, and other observations.

  7. l

    CalOES NG9-1-1 GIS Data Quality Control Plan April 18, 2022

    • data.lacounty.gov
    • geohub.lacity.org
    • +1more
    Updated Jul 19, 2022
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    County of Los Angeles (2022). CalOES NG9-1-1 GIS Data Quality Control Plan April 18, 2022 [Dataset]. https://data.lacounty.gov/documents/ddb6c8e2e41b4990ba38e0bbe93e343a
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    Dataset updated
    Jul 19, 2022
    Dataset authored and provided by
    County of Los Angeles
    Description

    GIS quality control checks are intended to identify issues in the source data that may impact a variety of9-1-1 end use systems.The primary goal of the initial CalOES NG9-1-1 implementation is to facilitate 9-1-1 call routing. Thesecondary goal is to use the data for telephone record validation through the LVF and the GIS-derivedMSAG.With these goals in mind, the GIS QC checks, and the impact of errors found by them are categorized asfollows in this document:Provisioning Failure Errors: GIS data issues resulting in ingest failures (results in no provisioning of one or more layers)Tier 1 Critical errors: Impact on initial 9-1-1 call routing and discrepancy reportingTier 2 Critical errors: Transition to GIS derived MSAGTier 3 Warning-level errors: Impact on routing of call transfersTier 4 Other errors: Impact on PSAP mapping and CAD systemsGeoComm's GIS Data Hub is configurable to stop GIS data that exceeds certain quality control check error thresholdsfrom provisioning to the SI (Spatial Interface) and ultimately to the ECRFs, LVFs and the GIS derivedMSAG.

  8. k

    County GIS Websites

    • hub.kansasgis.org
    Updated Jan 15, 2016
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    Kansas State Government GIS (2016). County GIS Websites [Dataset]. https://hub.kansasgis.org/maps/cb09444bb8f24698843f46a47f2d3e3f
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    Dataset updated
    Jan 15, 2016
    Dataset authored and provided by
    Kansas State Government GIS
    Area covered
    Description

    Shows links to Kansas county websites, GIS websites, and parcel search websites where available. Some parcel search websites are password protected. Data is updated as new or corrected information is found or reported. Please report any updated or erroneous links to dasc@ku.edu. The full Kansas geospatial catalog is administered by the Kansas Data Access & Support Center (DASC) and can be found at the following URL: https://hub.kansasgis.org/

  9. m

    Massachusetts Interactive Property Map

    • gis.data.mass.gov
    • submitgisdata.mass.gov
    • +1more
    Updated Oct 1, 2014
    + more versions
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    MassGIS - Bureau of Geographic Information (2014). Massachusetts Interactive Property Map [Dataset]. https://gis.data.mass.gov/datasets/massachusetts-interactive-property-map
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    Dataset updated
    Oct 1, 2014
    Dataset authored and provided by
    MassGIS - Bureau of Geographic Information
    Area covered
    Massachusetts
    Description

    To access parcel information:Enter an address or zoom in by using the +/- tools or your mouse scroll wheel. Parcels will draw when zoomed in.Click on a parcel to display a popup with information about that parcel.Click the "Basemap" button to display background aerial imagery.From the "Layers" button you can turn map features on and off.Complete Help (PDF)Parcel Legend:Full Map LegendAbout this ViewerThis viewer displays land property boundaries from assessor parcel maps across Massachusetts. Each parcel is linked to selected descriptive information from assessor databases. Data for all 351 cities and towns are the standardized "Level 3" tax parcels served by MassGIS. More details ...Read about and download parcel dataUpdatesV 1.1: Added 'Layers' tab. (2018)V 1.2: Reformatted popup to use HTML table for columns and made address larger. (Jan 2019)V 1.3: Added 'Download Parcel Data by City/Town' option to list of layers. This box is checked off by default but when activated a user can identify anywhere and download data for that entire city/town, except Boston. (March 14, 2019)V 1.4: Data for Boston is included in the "Level 3" standardized parcels layer. (August 10, 2020)V 1.4 MassGIS, EOTSS 2021

  10. d

    References Check In Map Index 3

    • catalog.data.gov
    • data.oregon.gov
    Updated Jan 31, 2025
    + more versions
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    State of Oregon (2025). References Check In Map Index 3 [Dataset]. https://catalog.data.gov/dataset/references-check-in-map-index-3
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    Dataset updated
    Jan 31, 2025
    Dataset provided by
    State of Oregon
    Description

    SLIDO-4.5 is an Esri ArcGIS version 10.7 file geodatabase which can be downloaded here: https://www.oregon.gov/dogami/slido/Pages/data.aspx The geodatabase contains two feature datasets (a group of datasets within the geodatabase) containing six feature classes total, as well as two raster data sets, one individual table, and two individual feature classes. The original studies vary widely in scale, scope and focus which is reflected in the wide range of accuracy, detail, and completeness with which landslides are mapped. In the future, we propose a continuous update of SLIDO. These updates should take place: 1) each time DOGAMI publishes a new GIS dataset that contains landslide inventory or susceptibility data or 2) at the end of each winter season, a common time for landslide occurrences in Oregon, which will include recent historic landslide point data. In order to keep track of the updates, we will use a primary release number such as Release 4.0 along with a decimal number identifying the update such as 4.5.

  11. V

    Norfolk Open GIS Data

    • odgavaprod.ogopendata.com
    • data.norfolk.gov
    html
    Updated Jan 7, 2019
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    City of Norfolk (2019). Norfolk Open GIS Data [Dataset]. https://odgavaprod.ogopendata.com/dataset/norfolk-open-gis-data
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    htmlAvailable download formats
    Dataset updated
    Jan 7, 2019
    Dataset provided by
    data.norfolk.gov
    Authors
    City of Norfolk
    Description

    The City of Norfolk Open GIS Data Site. This site contains various spatial data that can be used by anyone with an interest in geographic information systems (GIS) data for their applications. The City’s datasets are updated regularly and can be downloaded or accessed for free from this site. If you don’t see a particular dataset you are looking for, please check back often, as we will be providing additional data to the site in the future.

  12. c

    Cuyahoga County GIS Web Mapping

    • geospatial.gis.cuyahogacounty.gov
    Updated Mar 30, 2017
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    Cuyahoga County (2017). Cuyahoga County GIS Web Mapping [Dataset]. https://geospatial.gis.cuyahogacounty.gov/datasets/cuyahoga-county-gis-web-mapping
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    Dataset updated
    Mar 30, 2017
    Dataset authored and provided by
    Cuyahoga County
    Area covered
    Cuyahoga County
    Description

    Web-based GIS mapping application.Contains all available GIS and mapping resources for Cuyahoga County.Use the application to explore data using the available search, identify, and query tools; markup the map with the drawing tools; export the map to a geo-referenced image file; print the map to PDF with a custom title and include a legend and scale.View the 'Help Guide' for FAQs, tool tips, and additional information about the application and the data.

  13. d

    Lake County, IL Monthly Check Register

    • catalog.data.gov
    • data.amerigeoss.org
    • +3more
    Updated Mar 29, 2025
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    Lake County Illinois GIS (2025). Lake County, IL Monthly Check Register [Dataset]. https://catalog.data.gov/dataset/lake-county-il-monthly-check-register-5467e
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    Dataset updated
    Mar 29, 2025
    Dataset provided by
    Lake County Illinois GIS
    Area covered
    Illinois, Lake County
    Description

    Link to Lake County, IL website.

  14. Point, polygon, or marker? In search of the best geographic entity for...

    • data.europa.eu
    unknown
    Updated Dec 18, 2020
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    Zenodo (2020). Point, polygon, or marker? In search of the best geographic entity for mapping Cultural Ecosystem Services using the online PPGIS tool, "My Green Place." [Dataset]. https://data.europa.eu/data/datasets/oai-zenodo-org-4347404?locale=ga
    Explore at:
    unknown(19899)Available download formats
    Dataset updated
    Dec 18, 2020
    Dataset authored and provided by
    Zenodohttp://zenodo.org/
    License

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

    Description

    Excel files include the raw database and the processed data that led to the quadrat analyses. The "Matrix_raw data" file includes the raw data as downloaded from the server. This data was cleaned and organized for its posterior use. "Quadrat analyzes "file includes all the quadrat analyses resulting in each research question in the paper except question four. Question 4 can be seen in the file "Water analysis_Blaarmeersen." All excel files come with a "CODE" tab that describes each of the codes used, their meaning, and ways that were calculated where necessary. Two zip files include all the GIS files. The first one includes the GIS files from which "Matrix_raw data" was built from. The second folder includes the resulting maps from the quadrat analyses. In order to visualize them as in the paper, configure the symbology tab at the GIS software in quantile and the categories number, as shown in the paper. The production of the files in the "GIS_Processed data" folder was done via a repetitive line of commands in ArcGIS pro. The same process was followed for each one of the quadrat analysis described in the paper. Refer to "Reproduction commands and parameters.pdf" for further information.

  15. d

    Property Check

    • catalog.data.gov
    Updated Sep 1, 2022
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    Lake County Illinois GIS (2022). Property Check [Dataset]. https://catalog.data.gov/dataset/property-check-470ce
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    Dataset updated
    Sep 1, 2022
    Dataset provided by
    Lake County Illinois GIS
    Description

    {{description}}

  16. d

    Datasets for Computational Methods and GIS Applications in Social Science

    • search.dataone.org
    Updated Sep 25, 2024
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    Fahui Wang; Lingbo Liu (2024). Datasets for Computational Methods and GIS Applications in Social Science [Dataset]. http://doi.org/10.7910/DVN/4CM7V4
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    Dataset updated
    Sep 25, 2024
    Dataset provided by
    Harvard Dataverse
    Authors
    Fahui Wang; Lingbo Liu
    Description

    Dataset for the textbook Computational Methods and GIS Applications in Social Science (3rd Edition), 2023 Fahui Wang, Lingbo Liu Main Book Citation: Wang, F., & Liu, L. (2023). Computational Methods and GIS Applications in Social Science (3rd ed.). CRC Press. https://doi.org/10.1201/9781003292302 KNIME Lab Manual Citation: Liu, L., & Wang, F. (2023). Computational Methods and GIS Applications in Social Science - Lab Manual. CRC Press. https://doi.org/10.1201/9781003304357 KNIME Hub Dataset and Workflow for Computational Methods and GIS Applications in Social Science-Lab Manual Update Log If Python package not found in Package Management, use ArcGIS Pro's Python Command Prompt to install them, e.g., conda install -c conda-forge python-igraph leidenalg NetworkCommDetPro in CMGIS-V3-Tools was updated on July 10,2024 Add spatial adjacency table into Florida on June 29,2024 The dataset and tool for ABM Crime Simulation were updated on August 3, 2023, The toolkits in CMGIS-V3-Tools was updated on August 3rd,2023. Report Issues on GitHub https://github.com/UrbanGISer/Computational-Methods-and-GIS-Applications-in-Social-Science Following the website of Fahui Wang : http://faculty.lsu.edu/fahui Contents Chapter 1. Getting Started with ArcGIS: Data Management and Basic Spatial Analysis Tools Case Study 1: Mapping and Analyzing Population Density Pattern in Baton Rouge, Louisiana Chapter 2. Measuring Distance and Travel Time and Analyzing Distance Decay Behavior Case Study 2A: Estimating Drive Time and Transit Time in Baton Rouge, Louisiana Case Study 2B: Analyzing Distance Decay Behavior for Hospitalization in Florida Chapter 3. Spatial Smoothing and Spatial Interpolation Case Study 3A: Mapping Place Names in Guangxi, China Case Study 3B: Area-Based Interpolations of Population in Baton Rouge, Louisiana Case Study 3C: Detecting Spatiotemporal Crime Hotspots in Baton Rouge, Louisiana Chapter 4. Delineating Functional Regions and Applications in Health Geography Case Study 4A: Defining Service Areas of Acute Hospitals in Baton Rouge, Louisiana Case Study 4B: Automated Delineation of Hospital Service Areas in Florida Chapter 5. GIS-Based Measures of Spatial Accessibility and Application in Examining Healthcare Disparity Case Study 5: Measuring Accessibility of Primary Care Physicians in Baton Rouge Chapter 6. Function Fittings by Regressions and Application in Analyzing Urban Density Patterns Case Study 6: Analyzing Population Density Patterns in Chicago Urban Area >Chapter 7. Principal Components, Factor and Cluster Analyses and Application in Social Area Analysis Case Study 7: Social Area Analysis in Beijing Chapter 8. Spatial Statistics and Applications in Cultural and Crime Geography Case Study 8A: Spatial Distribution and Clusters of Place Names in Yunnan, China Case Study 8B: Detecting Colocation Between Crime Incidents and Facilities Case Study 8C: Spatial Cluster and Regression Analyses of Homicide Patterns in Chicago Chapter 9. Regionalization Methods and Application in Analysis of Cancer Data Case Study 9: Constructing Geographical Areas for Mapping Cancer Rates in Louisiana Chapter 10. System of Linear Equations and Application of Garin-Lowry in Simulating Urban Population and Employment Patterns Case Study 10: Simulating Population and Service Employment Distributions in a Hypothetical City Chapter 11. Linear and Quadratic Programming and Applications in Examining Wasteful Commuting and Allocating Healthcare Providers Case Study 11A: Measuring Wasteful Commuting in Columbus, Ohio Case Study 11B: Location-Allocation Analysis of Hospitals in Rural China Chapter 12. Monte Carlo Method and Applications in Urban Population and Traffic Simulations Case Study 12A. Examining Zonal Effect on Urban Population Density Functions in Chicago by Monte Carlo Simulation Case Study 12B: Monte Carlo-Based Traffic Simulation in Baton Rouge, Louisiana Chapter 13. Agent-Based Model and Application in Crime Simulation Case Study 13: Agent-Based Crime Simulation in Baton Rouge, Louisiana Chapter 14. Spatiotemporal Big Data Analytics and Application in Urban Studies Case Study 14A: Exploring Taxi Trajectory in ArcGIS Case Study 14B: Identifying High Traffic Corridors and Destinations in Shanghai Dataset File Structure 1 BatonRouge Census.gdb BR.gdb 2A BatonRouge BR_Road.gdb Hosp_Address.csv TransitNetworkTemplate.xml BR_GTFS Google API Pro.tbx 2B Florida FL_HSA.gdb R_ArcGIS_Tools.tbx (RegressionR) 3A China_GX GX.gdb 3B BatonRouge BR.gdb 3C BatonRouge BRcrime R_ArcGIS_Tools.tbx (STKDE) 4A BatonRouge BRRoad.gdb 4B Florida FL_HSA.gdb HSA Delineation Pro.tbx Huff Model Pro.tbx FLplgnAdjAppend.csv 5 BRMSA BRMSA.gdb Accessibility Pro.tbx 6 Chicago ChiUrArea.gdb R_ArcGIS_Tools.tbx (RegressionR) 7 Beijing BJSA.gdb bjattr.csv R_ArcGIS_Tools.tbx (PCAandFA, BasicClustering) 8A Yunnan YN.gdb R_ArcGIS_Tools.tbx (SaTScanR) 8B Jiangsu JS.gdb 8C Chicago ChiCity.gdb cityattr.csv ...

  17. d

    Monthly Check Register

    • catalog.data.gov
    Updated Apr 5, 2025
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    Lake County Illinois GIS (2025). Monthly Check Register [Dataset]. https://catalog.data.gov/dataset/monthly-check-register-69e28
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    Dataset updated
    Apr 5, 2025
    Dataset provided by
    Lake County Illinois GIS
    Description

    {{description}}

  18. Medical Service Study Areas

    • healthdata.gov
    • data.ca.gov
    • +3more
    application/rdfxml +5
    Updated Apr 8, 2025
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    chhs.data.ca.gov (2025). Medical Service Study Areas [Dataset]. https://healthdata.gov/State/Medical-Service-Study-Areas/nvx2-hzzm
    Explore at:
    csv, application/rdfxml, application/rssxml, xml, json, tsvAvailable download formats
    Dataset updated
    Apr 8, 2025
    Dataset provided by
    chhs.data.ca.gov
    Description
    This is the current Medical Service Study Area. California Medical Service Study Areas are created by the California Department of Health Care Access and Information (HCAI).

    Check the Data Dictionary for field descriptions.


    Checkout the California Healthcare Atlas for more Medical Service Study Area information.

    This is an update to the MSSA geometries and demographics to reflect the new 2020 Census tract data. The Medical Service Study Area (MSSA) polygon layer represents the best fit mapping of all new 2020 California census tract boundaries to the original 2010 census tract boundaries used in the construction of the original 2010 MSSA file. Each of the state's new 9,129 census tracts was assigned to one of the previously established medical service study areas (excluding tracts with no land area), as identified in this data layer. The MSSA Census tract data is aggregated by HCAI, to create this MSSA data layer. This represents the final re-mapping of 2020 Census tracts to the original 2010 MSSA geometries. The 2010 MSSA were based on U.S. Census 2010 data and public meetings held throughout California.


    <a href="https://hcai.ca.gov/">https://hcai.ca.gov/</a>

    Source of update: American Community Survey 5-year 2006-2010 data for poverty. For source tables refer to InfoUSA update procedural documentation. The 2010 MSSA Detail layer was developed to update fields affected by population change. The American Community Survey 5-year 2006-2010 population data pertaining to total, in households, race, ethnicity, age, and poverty was used in the update. The 2010 MSSA Census Tract Detail map layer was developed to support geographic information systems (GIS) applications, representing 2010 census tract geography that is the foundation of 2010 medical service study area (MSSA) boundaries. ***This version is the finalized MSSA reconfiguration boundaries based on the US Census Bureau 2010 Census. In 1976 Garamendi Rural Health Services Act, required the development of a geographic framework for determining which parts of the state were rural and which were urban, and for determining which parts of counties and cities had adequate health care resources and which were "medically underserved". Thus, sub-city and sub-county geographic units called "medical service study areas [MSSAs]" were developed, using combinations of census-defined geographic units, established following General Rules promulgated by a statutory commission. After each subsequent census the MSSAs were revised. In the scheduled revisions that followed the 1990 census, community meetings of stakeholders (including county officials, and representatives of hospitals and community health centers) were held in larger metropolitan areas. The meetings were designed to develop consensus as how to draw the sub-city units so as to best display health care disparities. The importance of involving stakeholders was heightened in 1992 when the United States Department of Health and Human Services' Health and Resources Administration entered a formal agreement to recognize the state-determined MSSAs as "rational service areas" for federal recognition of "health professional shortage areas" and "medically underserved areas". After the 2000 census, two innovations transformed the process, and set the stage for GIS to emerge as a major factor in health care resource planning in California. First, the Office of Statewide Health Planning and Development [OSHPD], which organizes the community stakeholder meetings and provides the staff to administer the MSSAs, entered into an Enterprise GIS contract. Second, OSHPD authorized at least one community meeting to be held in each of the 58 counties, a significant number of which were wholly rural or frontier counties. For populous Los Angeles County, 11 community meetings were held. As a result, health resource data in California are collected and organized by 541 geographic units. The boundaries of these units were established by community healthcare experts, with the objective of maximizing their usefulness for needs assessment purposes. The most dramatic consequence was introducing a data simultaneously displayed in a GIS format. A two-person team, incorporating healthcare policy and GIS expertise, conducted the series of meetings, and supervised the development of the 2000-census configuration of the MSSAs.

    MSSA Configuration Guidelines (General Rules):- Each MSSA is composed of one or more complete census tracts.- As a general rule, MSSAs are deemed to be "rational service areas [RSAs]" for purposes of designating health professional shortage areas [HPSAs], medically underserved areas [MUAs] or medically underserved populations [MUPs].- MSSAs will not cross county lines.- To the extent practicable, all census-defined places within the MSSA are within 30 minutes travel time to the largest population center within the MSSA, except in those circumstances where meeting this criterion would require splitting a census tract.- To the extent practicable, areas that, standing alone, would meet both the definition of an MSSA and a Rural MSSA, should not be a part of an Urban MSSA.- Any Urban MSSA whose population exceeds 200,000 shall be divided into two or more Urban MSSA Subdivisions.- Urban MSSA Subdivisions should be within a population range of 75,000 to 125,000, but may not be smaller than five square miles in area. If removing any census tract on the perimeter of the Urban MSSA Subdivision would cause the area to fall below five square miles in area, then the population of the Urban MSSA may exceed 125,000. - To the extent practicable, Urban MSSA Subdivisions should reflect recognized community and neighborhood boundaries and take into account such demographic information as income level and ethnicity. Rural Definitions: A rural MSSA is an MSSA adopted by the Commission, which has a population density of less than 250 persons per square mile, and which has no census defined place within the area with a population in excess of 50,000. Only the population that is located within the MSSA is counted in determining the population of the census defined place. A frontier MSSA is a rural MSSA adopted by the Commission which has a population density of less than 11 persons per square mile. Any MSSA which is not a rural or frontier MSSA is an urban MSSA. Last updated December 6th 2024.
  19. s

    Property Lookup

    • data.stlouisco.com
    • hamhanding-dcdev.opendata.arcgis.com
    Updated Mar 31, 2017
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    Saint Louis County GIS Service Center (2017). Property Lookup [Dataset]. https://data.stlouisco.com/app/property-lookup
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    Dataset updated
    Mar 31, 2017
    Dataset authored and provided by
    Saint Louis County GIS Service Center
    Description

    Web App. Use the tabs provided to discover information about map features and capabilities. Link to Metadata. A variety of searches can be performed to find the parcel of interest. Use the Query Tool to build searches. Click Apply button at the bottom of the tool.Query by Name (Last First) (e.g. Bond James)Query by Address (e.g. 41 S Central)Query by Locator number (e.g. 21J411046)Search results will be listed under the Results tab. Click on a parcel in the list to zoom to that parcel. Click on the parcel in the map and scroll through the pop-up to see more information about the parcel. Click the ellipse in the Results tab or in the pop-up to view information in a table. Attribute information can be exported to CSV file. Build a custom Filter to select and map properties by opening the Parcels attribute table:1. Click the arrow tab at the bottom middle of the map to expand the attribute table window2. Click on the Parcels tab3. Check off Filter by map extent4. Open Options>Filter5. Build expressions as needed to filter by owner name or other variables6. Select the needed records from the returned list7. Click Zoom to which will zoom to the selected recordsPlease note that as the map zooms out detailed layers, such as the parcel boundaries will not display.In addition to Search capabilities, the following tools are provided:MeasureThe measure tool provides the capabilities to draw a point, line, or polygon on the map and specify the unit of measurement.DrawThe draw tool provides the capabilities to draw a point, line, or polygon on the map as graphics. PrintThe print tool exports the map to either a PDF or image file. Click Settings button to configure map or remove legend.Map navigation using mouse and keyboard:Drag to panSHIFT + CTRL + Drag to zoom outMouse Scroll Forward to zoom inMouse Scroll Backward to zoom outUse Arrow keys to pan+ key to zoom in a level- key to zoom out a levelDouble Click to Zoom inFAQsHow to select a parcel: Click on a parcel in the map, or use Query Tool to search for parcel by owner, address or parcel id.How to select more than one parcel: Go to Select Tool and choose options on Select button.How to clear selected parcel(s): Go to Select Tool and click Clear.

  20. r

    Place Vulnerability Analysis Solution for ArcGIS Pro (BETA)

    • opendata.rcmrd.org
    • visionzero.geohub.lacity.org
    • +1more
    Updated Feb 12, 2019
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    NAPSG Foundation (2019). Place Vulnerability Analysis Solution for ArcGIS Pro (BETA) [Dataset]. https://opendata.rcmrd.org/content/ee44dd7cd11c4017a67d43fcbb1cb467
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    Dataset updated
    Feb 12, 2019
    Dataset authored and provided by
    NAPSG Foundation
    License

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

    Area covered
    Description

    Purpose: This is an ArcGIS Pro template that GIS Specialists can use to identify vulnerable populations and special needs infrastructure most at risk to flooding events.How does it work?Determine and understand the Place Vulnerability (based on Cutter et al. 1997) and the Special Needs Infrastructure for an area of interest based on Special Flood Hazard Zones, Social Vulnerability Index, and the distribution of its Population and Housing units. The final product will be charts of the data distribution and a Hosted Feature Layer. See this Story Map example for a more detailed explanation.This uses the FEMA National Flood Hazard Layer as an input (although you can substitute your own flood hazard data), check availability for your County before beginning the Task: FEMA NFHL ViewerThe solution consists of several tasks that allow you to:Select an area of interest for your Place Vulnerability Analysis. Select a Hazard that may occur within your area of interest.Select the Social Vulnerability Index (SVI) features contained within your area of interest using the CDC’s Social Vulnerability Index (SVI) – 2016 overall SVI layer at the census tract level in the map.Determine and understand the Social Vulnerability Index for the hazard zones identified within you area of interest.Identify the Special Needs Infrastructure features located within the hazard zones identified within you area of interest.Share your data to ArcGIS Online as a Hosted Feature Layer.FIRST STEPS:Create a folder C:\GIS\ if you do not already have this folder created. (This is a suggested step as the ArcGIS Pro Tasks does not appear to keep relative paths)Download the ZIP file.Extract the ZIP file and save it to the C:\GIS\ location on your computer. Open the PlaceVulnerabilityAnalysis.aprx file.Once the Project file (.aprx) opens, we suggest the following setup to easily view the Tasks instructions, the Map and its Contents, and the Databases (.gdb) from the Catalog pane.The following public web map is included as a Template in the ArcGIS Pro solution file: Place Vulnerability Template Web MapNote 1:As this is a beta version, please take note of some pain points:Data input and output locations may need to be manually populated from the related workspaces (.gdb) or the tools may fail to run. Make sure to unzip/extract the file to the C:\GIS\ location on your computer to avoid issues.Switching from one step to the next may not be totally seamless yet.If you are experiencing any issues with the Flood Hazard Zones service provided, or if the data is not available for your area of interest, you can also download your Flood Hazard Zones data from the FEMA Flood Map Service Center. In the search, use the FEMA ID. Once downloaded, save the data in your project folder and use it as an input.Note 2:In this task, the default hazard being used are the National Flood Hazard Zones. If you would like to use a different hazard, you will need to add the new hazard layer to the map and update all query expressions accordingly.For questions, bug reports, or new requirements contact pdoherty@publicsafetygis.org

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Education and Research (2022). Check List for GIS Ambassadors [Dataset]. https://edu.hub.arcgis.com/documents/9510e8c9d06c44b487aaa39efccd5131

Check List for GIS Ambassadors

Explore at:
Dataset updated
Sep 20, 2022
Dataset authored and provided by
Education and Research
Description

A check list of items to discuss with the teacher to make sure you have all the information required before your GIS Ambassador support session.

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