Statewide Download (FGDB) (SHP)Users can also download smaller geographic areas of this feature service in ArcGIS Pro using the Copy Features geoprocessing tool. The address service contains statewide address points and related landmark name alias table and street name alias table.The New Jersey Office of Information Technology, Office of GIS (NJOGIS), in partnership with several local GIS and public safety agencies, has built a comprehensive statewide NG9-1-1 database meeting and exceeding the requirements of the National Emergency Number Association (NENA) 2018 NG9-1-1 GIS Data Standard (NENA-STA-006.1-2018). The existing New Jersey Statewide Address Point data last published in 2016 has been transformed in the NENA data model to create this new address point data.The initial address points were processed from statewide parcel records joined with the statewide Tax Assessor's (MOD-IV) database in 2015. Address points supplied by Monmouth County, Sussex County, Morris County and Montgomery Township in Somerset County were incorporated into the statewide address points using customized Extract, Transform and Load (ETL) procedures.The previous version of the address points was loaded into New Jersey's version of the NENA NG9-1-1 data model using Extract, Transform and Load (ETL) procedures created with Esri's Data Interoperability Extension. Subsequent manual and bulk processing corrections and additions have been made, and are ongoing.***NOTE*** For users who incorporate NJOGIS services into web maps and/or web applications, please sign up for the NJ Geospatial Forum discussion listserv for early notification of service changes. Visit https://nj.gov/njgf/about/listserv/ for more information.

The new Oregon Address Geocoder is used to find the location coordinates for street addresses in the State of Oregon. This service is:Free PublicUpdated regularlyOutputs location coordinates in Oregon Lambert, feet (SRID 2992)Uses over 2 million address points and 288,000 streets for referenceIt is an ArcGIS multirole locator with two roles:Point Address - Generally more accurate results from rooftop location points. Includes a Subaddress if a unit number is located. Street Address - Less accurate results from an estimated distance along a street centerline address range if a Point Address was not found.Instructions for using the Geocoder via ArcGIS Pro, ArcGIS Online, and REST Services are below:ArcGIS ProWeb ServicesArcGIS Online

DC Atlas Pro is a mapping tool that contains hundreds of different data layers, organized by category. DC Atlas Pro is the updated version of DC Atlas Plus, both of which were created by OCTO GIS, as an easy way to view geographic information about the District of Columbia. This new and improved version of DC Atlas allows you to search for addresses, intersections, or place names; analyze and identify data; and create maps that you can share. For detailed instructions on how to use DC Atlas Pro, please visit the Get Help / How to Use This Map section of the application.

Tabular data representing library and library branch locations was downloaded from the Indiana State Library (https://www.in.gov/library/directory-of-indiana-libraries/pldirectory/). Two spreadsheets were downloaded from this site, PL-Mailing-Addresses.xls, and PL-Branch-Directory.xls. Each spreadsheet was separately geocoded by IGIO staff, and any unmatched addresses were manually placed. Both datasets were then combined using the "Merge" tool in ArcGIS Pro before publishing. Attributes include the library name, branch name (when applicable), full address (address, city, state, and ZIP code), street address, mailing address (when applicable), city, state, ZIP code, library director name, and date updated by the State Library.This layer's default symbology is the same symbol with a different size and color for libraries versus branches. Library locations are larger (12 pt size) and blue, and branches are smaller (10 pt size) and purple.

Coordinate system Update:Notably, this dataset will be provided in NAD 83 Connecticut State Plane (2011) (EPSG 2234) projection, instead of WGS 1984 Web Mercator Auxiliary Sphere (EPSG 3857) which is the coordinate system of the 2023 dataset and will remain in Connecticut State Plane moving forward.Ownership Suppression and Data Access:The updated dataset now includes parcel data for all towns across the state, with some towns featuring fully suppressed ownership information. In these instances, the owner’s name will be replaced with the label "Current Owner," the co-owner’s name will be listed as "Current Co-Owner," and the mailing address will appear as the property address itself. For towns with suppressed ownership data, users should be aware that there was no "Suppression" field in the submission to verify specific details. This measure was implemented this year to help verify compliance with Suppression.New Data Fields:The new dataset introduces the "Land Acres" field, which will display the total acreage for each parcel. This additional field allows for more detailed analysis and better supports planning, zoning, and property valuation tasks. An important new addition is the FIPS code field, which provides the Federal Information Processing Standards (FIPS) code for each parcel’s corresponding block. This allows users to easily identify which block the parcel is in.Updated Service URL:The new parcel service URL includes all the updates mentioned above, such as the improved coordinate system, new data fields, and additional geospatial information. Users are strongly encouraged to transition to the new service as soon as possible to ensure that their workflows remain uninterrupted. The URL for this service will remain persistent moving forward. Once you have transitioned to the new service, the URL will remain constant, ensuring long term stability.For a limited time, the old service will continue to be available, but it will eventually be retired. Users should plan to switch to the new service well before this cutoff to avoid any disruptions in data access.The dataset has combined the Parcels and Computer-Assisted Mass Appraisal (CAMA) data for 2024 into a single dataset. This dataset is designed to make it easier for stakeholders and the GIS community to use and access the information as a geospatial dataset. Included in this dataset are geometries for all 169 municipalities and attribution from the CAMA data for all but one municipality. Pursuant to Section 7-100l of the Connecticut General Statutes, each municipality is required to transmit a digital parcel file and an accompanying assessor’s database file (known as a CAMA report), to its respective regional council of governments (COG) by May 1 annually. These data were gathered from the CT municipalities by the COGs and then submitted to CT OPM. This dataset was created on 10/31/2024 from data collected in 2023-2024. Data was processed using Python scripts and ArcGIS Pro, ensuring standardization and integration of the data.CAMA Notes:The CAMA underwent several steps to standardize and consolidate the information. Python scripts were used to concatenate fields and create a unique identifier for each entry. The resulting dataset contains 1,353,595 entries and information on property assessments and other relevant attributes.CAMA was provided by the towns.Spatial Data Notes:Data processing involved merging the parcels from different municipalities using ArcGIS Pro and Python. The resulting dataset contains 1,290,196 parcels.No alteration has been made to the spatial geometry of the data.Fields that are associated with CAMA data were provided by towns.The data fields that have information from the CAMA were sourced from the towns’ CAMA data.If no field for the parcels was provided for linking back to the CAMA by the town a new field within the original data was selected if it had a match rate above 50%, that joined back to the CAMA.Linking fields were renamed to "Link".All linking fields had a census town code added to the beginning of the value to create a unique identifier per town.Any field that was not town name, Location, Editor, Edit Date, or a field associated back to the CAMA, was not used in the creation of this Dataset.Only the fields related to town name, location, editor, edit date, and link fields associated with the towns’ CAMA were included in the creation of this dataset. Any other field provided in the original data was deleted or not used.Field names for town (Muni, Municipality) were renamed to "Town Name".The attributes included in the data: Town Name OwnerCo-OwnerLinkEditorEdit DateCollection year – year the parcels were submittedLocationMailing AddressMailing CityMailing StateAssessed TotalAssessed LandAssessed BuildingPre-Year Assessed Total Appraised LandAppraised BuildingAppraised OutbuildingConditionModelValuationZoneState UseState Use DescriptionLand Acre Living AreaEffective AreaTotal roomsNumber of bedroomsNumber of BathsNumber of Half-BathsSale PriceSale DateQualifiedOccupancyPrior Sale PricePrior Sale DatePrior Book and PagePlanning RegionFIPS Code *Please note that not all parcels have a link to a CAMA entry.*If any discrepancies are discovered within the data, whether pertaining to geographical inaccuracies or attribute inaccuracy, please directly contact the respective municipalities to request any necessary amendmentsAdditional information about the specifics of data availability and compliance will be coming soon.If you need a WFS service for use in specific applications : Please Click Here

Florida COVID-19 Cases by Zip Code exported from the Florida Department of Health GIS Layer on date seen in file name. Archived by the University of South Florida Libraries, Digital Heritage and Humanities Collections. Contact: LibraryGIS@usf.edu.Please Cite Our GIS HUB. If you are a researcher or other utilizing our Florida COVID-19 HUB as a tool or accessing and utilizing the data provided herein, please provide an acknowledgement of such in any publication or re-publication. The following citation is suggested: University of South Florida Libraries, Digital Heritage and Humanities Collections. 2020. Florida COVID-19 Hub. Available at https://covid19-usflibrary.hub.arcgis.com/.https://doi.org/10.5038/USF-COVID-19-GISLive FDOH Data Source: https://services1.arcgis.com/CY1LXxl9zlJeBuRZ/arcgis/rest/services/Florida_Cases_Zips_COVID19/FeatureServerFor data 5/10/2020 or after: Archived data was exported directly from the live FDOH layer into the archive. For data prior to 5/10/2020: Data was exported by the University of South Florida - Digital Heritage and Humanities Collection using ArcGIS Pro Software. Data was then converted to shapefile and csv and uploaded into ArcGIS Online archive. For data definitions please visit the following box folder: https://usf.box.com/s/vfjwbczkj73ucj19yvwz53at6v6w614hData definition files names include the relative date they were published. The below information was taken from ancillary documents associated with the original layer from FDOH.Q. How is the zip code assigned to a person or case? Cases are counted in a zip code based on residential or mailing address, or by healthcare provider or lab address if other addresses are missing.Q. Why is the city data and the zip code data different? The zip code data is supplied to a healthcare worker, case manager, or lab technician by each individual during intake when a test is first recorded. When entering a zip code, the system we use automatically produces a list of cities within that zip code for the individual to further specify where they live. Sometimes the individual uses the postal city, which may be Miami, when in reality that person lives outside the City of Miami boundaries in the jurisdiction of Coral Gables. Many zip codes contain multiple city/town jurisdictions, and about 20% of zip codes overlap more than one county. Q: How is the Zip Code data calculated and/or shown? If a COUNTY has five or more cases (total): • In zip codes with fewer than 5 cases, the total number of cases is shown as “<5”. • Zip codes with 0 cases in these counties are “0" or "No cases.” • All values of 5 or greater are shown by the actual number of cases in that zip code. If a COUNTY has fewer than five total cases across all of its zip codes, then ALL of the zip codes within that county show the total number of cases as "Suppressed." Q: My zip code says "SUPPRESSED" under cases. What does that mean? IF Suppressed: This county currently has fewer than five cases across all zip codes in the county. In an effort to protect the privacy of our COVID-19-Positive residents, zip code data is only available in counties where five or more cases have been reported. Q: What about PO Box zip codes, or zip codes with letters, like 334MH? PO Box zip codes are not shown in the map. “Filler” zip codes with letters, like 334MH, are typically areas where no or very few people live – like the Florida Everglades, and are shown on the map like any other zip code. Key Data about Cases by Zip Code: ZIP = The zip code COUNTYNAME = The county for the zip code (multi-part counties have been split) ZIPX = The unique county-zip identifier used to pair the data during updates POName = The postal address name assigned to the zip code place_labels = A list of the municipalities intersecting the zip code boundary c_places = The list of cities cases self-reported as being residents of Cases_1 = The number of cases in each zip code, with conditions*LabelY = A calculated field for map display only. All questions regarding this dataset should be directed to the Florida Department of Health.

Pursuant to Section 7-100l of the Connecticut General Statutes, each municipality is required to transmit a digital parcel file and an accompanying assessor’s database file (known as a CAMA report), to its respective regional council of governments (COG) by May 1 annually. The dataset has combined the Parcels and Computer-Assisted Mass Appraisal (CAMA) data for 2025 into a single dataset. This dataset is designed to make it easier for stakeholders and the GIS community to use and access the information as a geospatial dataset. Included in this dataset are geometries for all 169 municipalities and attribution from the CAMA data for all but one municipality. These data were gathered from the CT municipalities by the COGs and then submitted to CT OPM. This dataset was created on September 2025 from data collected in 2024-2025. Data was processed using Python scripts and ArcGIS Pro for standardization and integration of the data. To learn more about Parcel and CAMA in CT visit our Parcels Page in the Geodata Portal.Coordinate system: This dataset is provided in NAD 83 Connecticut State Plane (2011) (EPSG 2234) projection as it was for 2024. Prior versions were provided at WGS 1984 Web Mercator Auxiliary Sphere (EPSG 3857). Ownership Suppression: The updated dataset includes parcel data for all towns across the state, with some towns featuring fully suppressed ownership information. In these instances, the owner’s name was replaced with the label "Current Owner," the co-owner’s name will be listed as "Current Co-Owner," and the mailing address will appear as the property address itself. For towns with fully suppressed ownership data, please note that no "Suppression" field was included in the submission to confirm these details and this labeling approach was implemented as the solution.New Data Fields:The new dataset introduces the “Property Zip” and “Mailing Zip” fields, which will display the zip codes for the owner and property.Service URL:In 2024, we implemented a stable URL to maintain public access to the most up-to-date data layer. Users are strongly encouraged to transition to the new service as soon as possible to ensure uninterrupted workflows. This URL will remain persistent, providing long-term stability for your applications and integrations. Once you’ve transitioned to the new service, no further URL changes will be necessary.CAMA Notes:The CAMA underwent several steps to standardize and consolidate the information. Python scripts were used to concatenate fields and create a unique identifier for each entry. The resulting dataset contains 1,354,720 entries and information on property assessments and other relevant attributes.CAMA was provided by the towns.Spatial Data Notes:Data processing involved merging the parcels from different municipalities using ArcGIS Pro and Python. The resulting dataset contains 1,282,833 parcels.No alteration has been made to the spatial geometry of the data.Fields that are associated with CAMA data were provided by towns.The data fields that have information from the CAMA were sourced from the towns’ CAMA data.If no field for the parcels was provided for linking back to the CAMA by the town a new field within the original data was selected if it had a match rate above 50%, that joined back to the CAMA.Linking fields were renamed to "Link".All linking fields had a census town code added to the beginning of the value to create a unique identifier per town.Any field that was not town name, Location, Editor, Edit Date, or a field associated back to the CAMA, was not used in the creation of this Dataset.Only the fields related to town name, location, editor, edit date, and link fields associated with the towns’ CAMA were included in the creation of this dataset. Any other field provided in the original data was deleted or not used.Field names for town (Muni, Municipality) were renamed to "Town Name".Attributes included in the data: Town Name OwnerCo-OwnerLinkEditorEdit DateCollection year – year the parcels were submittedLocationProperty ZipMailing AddressMailing CityMailing StateMailing ZipAssessed TotalAssessed LandAssessed BuildingPre-Year Assessed Total Appraised LandAppraised BuildingAppraised OutbuildingConditionModelValuationZoneState UseState Use DescriptionLand Acre Living AreaEffective AreaTotal roomsNumber of bedroomsNumber of BathsNumber of Half-BathsSale PriceSale DateQualifiedOccupancyPrior Sale PricePrior Sale DatePrior Book and PagePlanning RegionFIPS Code *Please note that not all parcels have a link to a CAMA entry.*If any discrepancies are discovered within the data, whether pertaining to geographical inaccuracies or attribute inaccuracy, please directly contact the respective municipalities to request any necessary amendmentsAdditional information about the specifics of data availability and compliance will be coming soon.If you need a WFS service for use in specific applications : Please Click HereContact: opm.giso@ct.gov

Florida COVID-19 Cases by Zip Code exported from the Florida Department of Health GIS Layer on date seen in file name. Archived by the University of South Florida Libraries, Digital Heritage and Humanities Collections. Contact: LibraryGIS@usf.edu.Please Cite Our GIS HUB. If you are a researcher or other utilizing our Florida COVID-19 HUB as a tool or accessing and utilizing the data provided herein, please provide an acknowledgement of such in any publication or re-publication. The following citation is suggested: University of South Florida Libraries, Digital Heritage and Humanities Collections. 2020. Florida COVID-19 Hub. Available at https://covid19-usflibrary.hub.arcgis.com/.https://doi.org/10.5038/USF-COVID-19-GISLive FDOH Data Source: https://services1.arcgis.com/CY1LXxl9zlJeBuRZ/arcgis/rest/services/Florida_Cases_Zips_COVID19/FeatureServerFor data 5/10/2020 or after: Archived data was exported directly from the live FDOH layer into the archive. For data prior to 5/10/2020: Data was exported by the University of South Florida - Digital Heritage and Humanities Collection using ArcGIS Pro Software. Data was then converted to shapefile and csv and uploaded into ArcGIS Online archive. For data definitions please visit the following box folder: https://usf.box.com/s/vfjwbczkj73ucj19yvwz53at6v6w614hData definition files names include the relative date they were published. The below information was taken from ancillary documents associated with the original layer from FDOH.Q. How is the zip code assigned to a person or case? Cases are counted in a zip code based on residential or mailing address, or by healthcare provider or lab address if other addresses are missing.Q. Why is the city data and the zip code data different? The zip code data is supplied to a healthcare worker, case manager, or lab technician by each individual during intake when a test is first recorded. When entering a zip code, the system we use automatically produces a list of cities within that zip code for the individual to further specify where they live. Sometimes the individual uses the postal city, which may be Miami, when in reality that person lives outside the City of Miami boundaries in the jurisdiction of Coral Gables. Many zip codes contain multiple city/town jurisdictions, and about 20% of zip codes overlap more than one county. Q: How is the Zip Code data calculated and/or shown? If a COUNTY has five or more cases (total): • In zip codes with fewer than 5 cases, the total number of cases is shown as “<5”. • Zip codes with 0 cases in these counties are “0" or "No cases.” • All values of 5 or greater are shown by the actual number of cases in that zip code. If a COUNTY has fewer than five total cases across all of its zip codes, then ALL of the zip codes within that county show the total number of cases as "Suppressed." Q: My zip code says "SUPPRESSED" under cases. What does that mean? IF Suppressed: This county currently has fewer than five cases across all zip codes in the county. In an effort to protect the privacy of our COVID-19-Positive residents, zip code data is only available in counties where five or more cases have been reported. Q: What about PO Box zip codes, or zip codes with letters, like 334MH? PO Box zip codes are not shown in the map. “Filler” zip codes with letters, like 334MH, are typically areas where no or very few people live – like the Florida Everglades, and are shown on the map like any other zip code. Key Data about Cases by Zip Code: ZIP = The zip code COUNTYNAME = The county for the zip code (multi-part counties have been split) ZIPX = The unique county-zip identifier used to pair the data during updates POName = The postal address name assigned to the zip code place_labels = A list of the municipalities intersecting the zip code boundary c_places = The list of cities cases self-reported as being residents of Cases_1 = The number of cases in each zip code, with conditions*LabelY = A calculated field for map display only. All questions regarding this dataset should be directed to the Florida Department of Health.

Florida COVID-19 Cases by Zip Code exported from the Florida Department of Health GIS Layer on date seen in file name. Archived by the University of South Florida Libraries, Digital Heritage and Humanities Collections. Contact: LibraryGIS@usf.edu.Please Cite Our GIS HUB. If you are a researcher or other utilizing our Florida COVID-19 HUB as a tool or accessing and utilizing the data provided herein, please provide an acknowledgement of such in any publication or re-publication. The following citation is suggested: University of South Florida Libraries, Digital Heritage and Humanities Collections. 2020. Florida COVID-19 Hub. Available at https://covid19-usflibrary.hub.arcgis.com/.https://doi.org/10.5038/USF-COVID-19-GISLive FDOH Data Source: https://services1.arcgis.com/CY1LXxl9zlJeBuRZ/arcgis/rest/services/Florida_Cases_Zips_COVID19/FeatureServerFor data 5/10/2020 or after: Archived data was exported directly from the live FDOH layer into the archive. For data prior to 5/10/2020: Data was exported by the University of South Florida - Digital Heritage and Humanities Collection using ArcGIS Pro Software. Data was then converted to shapefile and csv and uploaded into ArcGIS Online archive. For data definitions please visit the following box folder: https://usf.box.com/s/vfjwbczkj73ucj19yvwz53at6v6w614hData definition files names include the relative date they were published. The below information was taken from ancillary documents associated with the original layer from FDOH.Q. How is the zip code assigned to a person or case? Cases are counted in a zip code based on residential or mailing address, or by healthcare provider or lab address if other addresses are missing.Q. Why is the city data and the zip code data different? The zip code data is supplied to a healthcare worker, case manager, or lab technician by each individual during intake when a test is first recorded. When entering a zip code, the system we use automatically produces a list of cities within that zip code for the individual to further specify where they live. Sometimes the individual uses the postal city, which may be Miami, when in reality that person lives outside the City of Miami boundaries in the jurisdiction of Coral Gables. Many zip codes contain multiple city/town jurisdictions, and about 20% of zip codes overlap more than one county. Q: How is the Zip Code data calculated and/or shown? If a COUNTY has five or more cases (total): • In zip codes with fewer than 5 cases, the total number of cases is shown as “<5”. • Zip codes with 0 cases in these counties are “0" or "No cases.” • All values of 5 or greater are shown by the actual number of cases in that zip code. If a COUNTY has fewer than five total cases across all of its zip codes, then ALL of the zip codes within that county show the total number of cases as "Suppressed." Q: My zip code says "SUPPRESSED" under cases. What does that mean? IF Suppressed: This county currently has fewer than five cases across all zip codes in the county. In an effort to protect the privacy of our COVID-19-Positive residents, zip code data is only available in counties where five or more cases have been reported. Q: What about PO Box zip codes, or zip codes with letters, like 334MH? PO Box zip codes are not shown in the map. “Filler” zip codes with letters, like 334MH, are typically areas where no or very few people live – like the Florida Everglades, and are shown on the map like any other zip code. Key Data about Cases by Zip Code: ZIP = The zip code COUNTYNAME = The county for the zip code (multi-part counties have been split) ZIPX = The unique county-zip identifier used to pair the data during updates POName = The postal address name assigned to the zip code place_labels = A list of the municipalities intersecting the zip code boundary c_places = The list of cities cases self-reported as being residents of Cases_1 = The number of cases in each zip code, with conditions*LabelY = A calculated field for map display only. All questions regarding this dataset should be directed to the Florida Department of Health.

Florida COVID-19 Cases by Zip Code exported from the Florida Department of Health GIS Layer on date seen in file name. Archived by the University of South Florida Libraries, Digital Heritage and Humanities Collections. Contact: LibraryGIS@usf.edu.Please Cite Our GIS HUB. If you are a researcher or other utilizing our Florida COVID-19 HUB as a tool or accessing and utilizing the data provided herein, please provide an acknowledgement of such in any publication or re-publication. The following citation is suggested: University of South Florida Libraries, Digital Heritage and Humanities Collections. 2020. Florida COVID-19 Hub. Available at https://covid19-usflibrary.hub.arcgis.com/.https://doi.org/10.5038/USF-COVID-19-GISLive FDOH Data Source: https://services1.arcgis.com/CY1LXxl9zlJeBuRZ/arcgis/rest/services/Florida_Cases_Zips_COVID19/FeatureServerFor data 5/10/2020 or after: Archived data was exported directly from the live FDOH layer into the archive. For data prior to 5/10/2020: Data was exported by the University of South Florida - Digital Heritage and Humanities Collection using ArcGIS Pro Software. Data was then converted to shapefile and csv and uploaded into ArcGIS Online archive. For data definitions please visit the following box folder: https://usf.box.com/s/vfjwbczkj73ucj19yvwz53at6v6w614hData definition files names include the relative date they were published. The below information was taken from ancillary documents associated with the original layer from FDOH.Q. How is the zip code assigned to a person or case? Cases are counted in a zip code based on residential or mailing address, or by healthcare provider or lab address if other addresses are missing.Q. Why is the city data and the zip code data different? The zip code data is supplied to a healthcare worker, case manager, or lab technician by each individual during intake when a test is first recorded. When entering a zip code, the system we use automatically produces a list of cities within that zip code for the individual to further specify where they live. Sometimes the individual uses the postal city, which may be Miami, when in reality that person lives outside the City of Miami boundaries in the jurisdiction of Coral Gables. Many zip codes contain multiple city/town jurisdictions, and about 20% of zip codes overlap more than one county. Q: How is the Zip Code data calculated and/or shown? If a COUNTY has five or more cases (total): • In zip codes with fewer than 5 cases, the total number of cases is shown as “<5”. • Zip codes with 0 cases in these counties are “0" or "No cases.” • All values of 5 or greater are shown by the actual number of cases in that zip code. If a COUNTY has fewer than five total cases across all of its zip codes, then ALL of the zip codes within that county show the total number of cases as "Suppressed." Q: My zip code says "SUPPRESSED" under cases. What does that mean? IF Suppressed: This county currently has fewer than five cases across all zip codes in the county. In an effort to protect the privacy of our COVID-19-Positive residents, zip code data is only available in counties where five or more cases have been reported. Q: What about PO Box zip codes, or zip codes with letters, like 334MH? PO Box zip codes are not shown in the map. “Filler” zip codes with letters, like 334MH, are typically areas where no or very few people live – like the Florida Everglades, and are shown on the map like any other zip code. Key Data about Cases by Zip Code: ZIP = The zip code COUNTYNAME = The county for the zip code (multi-part counties have been split) ZIPX = The unique county-zip identifier used to pair the data during updates POName = The postal address name assigned to the zip code place_labels = A list of the municipalities intersecting the zip code boundary c_places = The list of cities cases self-reported as being residents of Cases_1 = The number of cases in each zip code, with conditions*LabelY = A calculated field for map display only. All questions regarding this dataset should be directed to the Florida Department of Health.

This data set represents the location of sites within New Jersey that are regulated by the New Jersey Solid Waste Management Act at N.J.S.A. 13:1E-1 et seq., appropriate parts of the federal Resource Conservation and Recovery Act (RCRA) codified at 40 C.F.R., the New Jersey Comprehensive Regulated Medical Waste Management Act at N.J.S.A. 13:1E-48.1 et seq, and the New Jersey Statewide Mandatory Source Separation and Recycling Act at N.J.S.A. 13:1E-99.11 et seq. The Division of Sustainable Waste Management regulates safe management of solid waste, RCRA hazardous waste, regulated medical waste (RMW), and recycling of source separated recyclable materials through guidance, technical assistance, regulations, permits, approvals, environmental monitoring, compliance evaluation and enforcement. Waste types handled at these facilities include solid waste types specified at N.J.A.C 7:26-2.13(g), hazardous waste types specified at 40 C.F.R. part 261 subparts A through D, and RMW types (classes) specified at N.J.A.C. 7:26-3A.6(a). NJDEP is authorized by EPA to administer the federal RCRA hazardous waste program. The dataset shows operating Hazardous Waste Treatment, Storage, and Disposal (TSD) Facilities, Regulated Medical Waste Facilities and Solid Waste Facilities including Landfills, Transfer Stations / Materials Recovery Facilities, and Recycling Centers classified as Class B, C, and D, Multi-class Recycling facilities accepting both Class B and C recyclable materials. Since the dataset is prepared for Environmental Justice Stressor Tool, the Recycling Centers (Class B, C, B&C, and D) has been filtered to include facilities that accept 100 tons or more per day of approved source separated recyclable materials. The dataset is generated in ArcGIS Pro based on facility address as well as Block and Lot information given. Data has been updated in 2022 using ArcGIS Pro.

Florida COVID-19 Cases by Zip Code exported from the Florida Department of Health GIS Layer on date seen in file name. Archived by the University of South Florida Libraries, Digital Heritage and Humanities Collections. Contact: LibraryGIS@usf.edu.Please Cite Our GIS HUB. If you are a researcher or other utilizing our Florida COVID-19 HUB as a tool or accessing and utilizing the data provided herein, please provide an acknowledgement of such in any publication or re-publication. The following citation is suggested: University of South Florida Libraries, Digital Heritage and Humanities Collections. 2020. Florida COVID-19 Hub. Available at https://covid19-usflibrary.hub.arcgis.com/.https://doi.org/10.5038/USF-COVID-19-GISLive FDOH Data Source: https://services1.arcgis.com/CY1LXxl9zlJeBuRZ/arcgis/rest/services/Florida_Cases_Zips_COVID19/FeatureServerFor data 5/10/2020 or after: Archived data was exported directly from the live FDOH layer into the archive. For data prior to 5/10/2020: Data was exported by the University of South Florida - Digital Heritage and Humanities Collection using ArcGIS Pro Software. Data was then converted to shapefile and csv and uploaded into ArcGIS Online archive. For data definitions please visit the following box folder: https://usf.box.com/s/vfjwbczkj73ucj19yvwz53at6v6w614hData definition files names include the relative date they were published. The below information was taken from ancillary documents associated with the original layer from FDOH.Q. How is the zip code assigned to a person or case? Cases are counted in a zip code based on residential or mailing address, or by healthcare provider or lab address if other addresses are missing.Q. Why is the city data and the zip code data different? The zip code data is supplied to a healthcare worker, case manager, or lab technician by each individual during intake when a test is first recorded. When entering a zip code, the system we use automatically produces a list of cities within that zip code for the individual to further specify where they live. Sometimes the individual uses the postal city, which may be Miami, when in reality that person lives outside the City of Miami boundaries in the jurisdiction of Coral Gables. Many zip codes contain multiple city/town jurisdictions, and about 20% of zip codes overlap more than one county. Q: How is the Zip Code data calculated and/or shown? If a COUNTY has five or more cases (total): • In zip codes with fewer than 5 cases, the total number of cases is shown as “<5”. • Zip codes with 0 cases in these counties are “0" or "No cases.” • All values of 5 or greater are shown by the actual number of cases in that zip code. If a COUNTY has fewer than five total cases across all of its zip codes, then ALL of the zip codes within that county show the total number of cases as "Suppressed." Q: My zip code says "SUPPRESSED" under cases. What does that mean? IF Suppressed: This county currently has fewer than five cases across all zip codes in the county. In an effort to protect the privacy of our COVID-19-Positive residents, zip code data is only available in counties where five or more cases have been reported. Q: What about PO Box zip codes, or zip codes with letters, like 334MH? PO Box zip codes are not shown in the map. “Filler” zip codes with letters, like 334MH, are typically areas where no or very few people live – like the Florida Everglades, and are shown on the map like any other zip code. Key Data about Cases by Zip Code: ZIP = The zip code COUNTYNAME = The county for the zip code (multi-part counties have been split) ZIPX = The unique county-zip identifier used to pair the data during updates POName = The postal address name assigned to the zip code place_labels = A list of the municipalities intersecting the zip code boundary c_places = The list of cities cases self-reported as being residents of Cases_1 = The number of cases in each zip code, with conditions*LabelY = A calculated field for map display only. All questions regarding this dataset should be directed to the Florida Department of Health.

Florida COVID-19 Cases by Zip Code exported from the Florida Department of Health GIS Layer on date seen in file name. Archived by the University of South Florida Libraries, Digital Heritage and Humanities Collections. Contact: LibraryGIS@usf.edu.Please Cite Our GIS HUB. If you are a researcher or other utilizing our Florida COVID-19 HUB as a tool or accessing and utilizing the data provided herein, please provide an acknowledgement of such in any publication or re-publication. The following citation is suggested: University of South Florida Libraries, Digital Heritage and Humanities Collections. 2020. Florida COVID-19 Hub. Available at https://covid19-usflibrary.hub.arcgis.com/.https://doi.org/10.5038/USF-COVID-19-GISLive FDOH Data Source: https://services1.arcgis.com/CY1LXxl9zlJeBuRZ/arcgis/rest/services/Florida_Cases_Zips_COVID19/FeatureServerFor data 5/10/2020 or after: Archived data was exported directly from the live FDOH layer into the archive. For data prior to 5/10/2020: Data was exported by the University of South Florida - Digital Heritage and Humanities Collection using ArcGIS Pro Software. Data was then converted to shapefile and csv and uploaded into ArcGIS Online archive. For data definitions please visit the following box folder: https://usf.box.com/s/vfjwbczkj73ucj19yvwz53at6v6w614hData definition files names include the relative date they were published. The below information was taken from ancillary documents associated with the original layer from FDOH.Q. How is the zip code assigned to a person or case? Cases are counted in a zip code based on residential or mailing address, or by healthcare provider or lab address if other addresses are missing.Q. Why is the city data and the zip code data different? The zip code data is supplied to a healthcare worker, case manager, or lab technician by each individual during intake when a test is first recorded. When entering a zip code, the system we use automatically produces a list of cities within that zip code for the individual to further specify where they live. Sometimes the individual uses the postal city, which may be Miami, when in reality that person lives outside the City of Miami boundaries in the jurisdiction of Coral Gables. Many zip codes contain multiple city/town jurisdictions, and about 20% of zip codes overlap more than one county. Q: How is the Zip Code data calculated and/or shown? If a COUNTY has five or more cases (total): • In zip codes with fewer than 5 cases, the total number of cases is shown as “<5”. • Zip codes with 0 cases in these counties are “0" or "No cases.” • All values of 5 or greater are shown by the actual number of cases in that zip code. If a COUNTY has fewer than five total cases across all of its zip codes, then ALL of the zip codes within that county show the total number of cases as "Suppressed." Q: My zip code says "SUPPRESSED" under cases. What does that mean? IF Suppressed: This county currently has fewer than five cases across all zip codes in the county. In an effort to protect the privacy of our COVID-19-Positive residents, zip code data is only available in counties where five or more cases have been reported. Q: What about PO Box zip codes, or zip codes with letters, like 334MH? PO Box zip codes are not shown in the map. “Filler” zip codes with letters, like 334MH, are typically areas where no or very few people live – like the Florida Everglades, and are shown on the map like any other zip code. Key Data about Cases by Zip Code: ZIP = The zip code COUNTYNAME = The county for the zip code (multi-part counties have been split) ZIPX = The unique county-zip identifier used to pair the data during updates POName = The postal address name assigned to the zip code place_labels = A list of the municipalities intersecting the zip code boundary c_places = The list of cities cases self-reported as being residents of Cases_1 = The number of cases in each zip code, with conditions*LabelY = A calculated field for map display only. All questions regarding this dataset should be directed to the Florida Department of Health.

Measure and Map Access to Grocery StoresFrom the perspective of the people living in each neighborhood How do people in your city get to the grocery store? The answer to that question depends on the person and where they live. This collection of layers, maps and apps help answer the question.Some live in cities and stop by a grocery store within a short walk or bike ride of home or work. Others live in areas where car ownership is more prevalent, and so they drive to a store. Some do not own a vehicle, and rely on a friend or public transit. Others rely on grocery delivery for their needs. And, many live in rural areas far from town, so a trip to a grocery store is an infrequent event involving a long drive.This map from Esri shows which areas are within a ten minute walk (in green) or ten minute drive (in blue) of a grocery store in the United States and Puerto Rico. Darker color indicates access to more stores. Summarizing this data shows that 20% of U.S. population live within a 10 minute walk of a grocery store, and 90% of the population live within a 10 minute drive of a grocery store. Click on the map to see a summary for each state.Every census block is scored with a count of walkable and drivable stores nearby, making this a map suitable for a dashboard for any city, or any of the 50 states, DC and Puerto Rico. Two colorful layers visualize this definition of access, one for walkable access (suitable for looking at a city neighborhood by neighborhood) and one for drivable access (suitable for looking across a city, county, region or state).On the walkable layer, shades of green define areas within a ten minute walk of one or more grocery stores. The colors become more intense and trend to a blue-green color for the busiest neighborhoods, such as downtown San Francisco. As you zoom in, a layer of Census block points visualizes the local population with or without walkable access. As you zoom out to see the entire city, the map adds a light blue - to dark blue layer, showing which parts of the region fall within ten minutes' drive of one or more grocery stores. As a result, the map is useful at all scales, from national to regional, state and local levels. It becomes easier to spot grocery stores that sit within a highly populated area, and grocery stores that sit in a shopping center far away from populated areas. This view of a city begins to hint at the question: how many people have each type of access to grocery stores? And, what if they are unable to walk a mile regularly, or don't own a car? How to Use This MapUse this map to introduce the concepts of access to grocery stores in your city or town. This is the kind of map where people will want to look up their home or work address to validate what the map is saying against their own experiences. The map was built with that use in mind. Many maps of access use straight-line, as-the-crow-flies distance, which ignores real-world barriers to walkability like rivers, lakes, interstates and other characteristics of the built environment. Block analysis using a network data set and Origin-Destination analysis factors these barriers in, resulting in a more realistic depiction of access. There is data behind the map, which can be summarized to show how many people have walkable access to local grocery stores. The map includes a feature layer of population in Census block points, which are visible when you zoom in far enough. This feature layer of Census block centroids can be plugged into an app like this one that summarizes the population with/without walkable or drivable access. Lastly, this map can serve as backdrop to other community resources, like food banks, farmers markets (example), and transit (example). Add a transit layer to immediately gauge its impact on the population's grocery access. You can also use this map to see how it relates to communities of concern. Add a layer of any block group or tract demographics, such as Percent Senior Population (examples), or Percent of Households with Access to 0 Vehicles (examples). The map is a useful visual and analytic resource for helping community leaders, business and government leaders see their town from the perspective of its residents, and begin asking questions about how their community could be improved. Data sourcesPopulation data is from the 2020 U.S. Census blocks. Each census block has a count of stores within a 10 minute walk, and a count of stores within a ten minute drive. Census blocks known to be unpopulated are given a score of 0. The layer is available as a hosted feature layer. Grocery store locations are from SafeGraph, reflecting what was in the data as of September 2024. For this project, ArcGIS StreetMap Premium was used for the street network in the origin-destination analysis work, because it has the necessary attributes on each street segment to identify which streets are considered walkable, and supports a wide variety of driving parameters. The walkable access layer and drivable access layers are rasters, whose colors were chosen to allow the drivable access layer to serve as backdrop to the walkable access layer. Data PreparationArcGIS Network Analyst was used to set up a network street layer for analysis. ArcGIS StreetMap Premium was installed to a local hard drive and selected in the Origin-Destination workflow as the network data source. This allows the origins (Census block centroids) and destinations (SafeGraph grocery stores) to be connected to that network, to allow origin-destination analysis. The Census blocks layer contains the centroid of each Census block. The data allows a simple popup to be created. This layer's block figures can be summarized further, to tract, county and state levels. The SafeGraph grocery store locations were provided by SafeGraph. The source data included NAICS code 445110 and 452311 as an initial screening. The CSV file was imported using the Data Interoperability geoprocessing tools in ArcGIS Pro, where a definition query was applied to the layer to exclude any records that were not grocery stores. The final layer used in the analysis had approximately 63,000 records. In this map, this layer is included as a vector tile layer. MethodologyEvery census block in the U.S. was assigned two access scores, whose numbers are simply how many grocery stores are within a 10 minute walk and a 10 minute drive of that census block. Every census block has a score of 0 (no stores), 1, 2 or more stores. The count of accessible stores was determined using Origin-Destination Analysis in ArcGIS Network Analyst, in ArcGIS Pro. A set of Tools in this ArcGIS Pro package allow a similar analysis to be conducted for any city or other area. The Tools step through the data prep and analysis steps. Download the Pro package, open it and substitute your own layers for Origins and Destinations. Parcel centroids are a suggested option for Origins, for example. Origin-Destination analysis was configured, using ArcGIS StreetMap Premium as the network data source. Census block centroids with population greater than zero were used as the Origins, and grocery store locations were used as the Destinations. A cutoff of 10 minutes was used with the Walk Time option. Only one restriction was applied to the street network: Walkable, which means Interstates and other non-walkable street segments were treated appropriately. You see the results in the map: wherever freeway overpasses and underpasses are present near a grocery store, the walkable area extends across/through that pass, but not along the freeway. A cutoff of 10 minutes was used with the Drive Time option. The default restrictions were applied to the street network, which means a typical vehicle's access to all types of roads was factored in. The results for each analysis were captured in a Lines layer, which shows which origins are within the 10 minute cutoff of each destination over the street network, given the assumptions about that network (walking, or driving a vehicle). The Lines layer is not published but is used to count how many stores each origin has access to over the road network. The Lines layer was then summarized by census block ID to capture the Maximum value of the Destination_Rank field. A census block within 10 minutes of 3 stores would have 3 records in the Lines layer, but only one value in the summarized table, with a MAX_Destination_Rank field value of 3. This is the number of stores accessible to that census block in the 10 minutes measured, for walking and driving. These data were joined to the block centroids layer and given unique names. At this point, all blocks with zero population or null values in the MAX_Destination_Rank fields were given a store count of 0, to help the next step. Walkable and Drivable areas are calculated into a raster layer, using Nearest Neighbor geoprocessing tool on the count of stores within a 10 minute walk, and a count of stores within a ten minute drive, respectively. This tool used a 100 meter grid and interpolates the values between each census block. A census tracts layer containing all water polygons "erased" from the census tract boundaries was used as an environment setting, to help constrain interpolation into/across bodies of water. The same layer use used to "shoreline" the Nearest Neighbor results, to eliminate any interpolation into the ocean or Great Lakes. This helped but was not perfect. Notes and LimitationsThe map provides a baseline for discussing access to grocery stores in a city. It does not presume local population has the desire or means to walk or drive to obtain groceries. It does not take elevation gain or loss into account. It does not factor time of day nor weather, seasons, or other variables that affect a person's commute choices. Walking and driving are just two ways people get to a grocery store. Some people ride a bike, others take public transit, have groceries delivered, or rely on a friend with a vehicle.

Florida COVID-19 Cases by Zip Code exported from the Florida Department of Health GIS Layer on date seen in file name. Archived by the University of South Florida Libraries, Digital Heritage and Humanities Collections. Contact: LibraryGIS@usf.edu.Please Cite Our GIS HUB. If you are a researcher or other utilizing our Florida COVID-19 HUB as a tool or accessing and utilizing the data provided herein, please provide an acknowledgement of such in any publication or re-publication. The following citation is suggested: University of South Florida Libraries, Digital Heritage and Humanities Collections. 2020. Florida COVID-19 Hub. Available at https://covid19-usflibrary.hub.arcgis.com/.https://doi.org/10.5038/USF-COVID-19-GISLive FDOH Data Source: https://services1.arcgis.com/CY1LXxl9zlJeBuRZ/arcgis/rest/services/Florida_Cases_Zips_COVID19/FeatureServerFor data 5/10/2020 or after: Archived data was exported directly from the live FDOH layer into the archive. For data prior to 5/10/2020: Data was exported by the University of South Florida - Digital Heritage and Humanities Collection using ArcGIS Pro Software. Data was then converted to shapefile and csv and uploaded into ArcGIS Online archive. For data definitions please visit the following box folder: https://usf.box.com/s/vfjwbczkj73ucj19yvwz53at6v6w614hData definition files names include the relative date they were published. The below information was taken from ancillary documents associated with the original layer from FDOH.Q. How is the zip code assigned to a person or case? Cases are counted in a zip code based on residential or mailing address, or by healthcare provider or lab address if other addresses are missing.Q. Why is the city data and the zip code data different? The zip code data is supplied to a healthcare worker, case manager, or lab technician by each individual during intake when a test is first recorded. When entering a zip code, the system we use automatically produces a list of cities within that zip code for the individual to further specify where they live. Sometimes the individual uses the postal city, which may be Miami, when in reality that person lives outside the City of Miami boundaries in the jurisdiction of Coral Gables. Many zip codes contain multiple city/town jurisdictions, and about 20% of zip codes overlap more than one county. Q: How is the Zip Code data calculated and/or shown? If a COUNTY has five or more cases (total): • In zip codes with fewer than 5 cases, the total number of cases is shown as “<5”. • Zip codes with 0 cases in these counties are “0" or "No cases.” • All values of 5 or greater are shown by the actual number of cases in that zip code. If a COUNTY has fewer than five total cases across all of its zip codes, then ALL of the zip codes within that county show the total number of cases as "Suppressed." Q: My zip code says "SUPPRESSED" under cases. What does that mean? IF Suppressed: This county currently has fewer than five cases across all zip codes in the county. In an effort to protect the privacy of our COVID-19-Positive residents, zip code data is only available in counties where five or more cases have been reported. Q: What about PO Box zip codes, or zip codes with letters, like 334MH? PO Box zip codes are not shown in the map. “Filler” zip codes with letters, like 334MH, are typically areas where no or very few people live – like the Florida Everglades, and are shown on the map like any other zip code. Key Data about Cases by Zip Code: ZIP = The zip code COUNTYNAME = The county for the zip code (multi-part counties have been split) ZIPX = The unique county-zip identifier used to pair the data during updates POName = The postal address name assigned to the zip code place_labels = A list of the municipalities intersecting the zip code boundary c_places = The list of cities cases self-reported as being residents of Cases_1 = The number of cases in each zip code, with conditions*LabelY = A calculated field for map display only. All questions regarding this dataset should be directed to the Florida Department of Health.

Florida COVID-19 Cases by Zip Code exported from the Florida Department of Health GIS Layer on date seen in file name. Archived by the University of South Florida Libraries, Digital Heritage and Humanities Collections. Contact: LibraryGIS@usf.edu.Please Cite Our GIS HUB. If you are a researcher or other utilizing our Florida COVID-19 HUB as a tool or accessing and utilizing the data provided herein, please provide an acknowledgement of such in any publication or re-publication. The following citation is suggested: University of South Florida Libraries, Digital Heritage and Humanities Collections. 2020. Florida COVID-19 Hub. Available at https://covid19-usflibrary.hub.arcgis.com/.https://doi.org/10.5038/USF-COVID-19-GISLive FDOH Data Source: https://services1.arcgis.com/CY1LXxl9zlJeBuRZ/arcgis/rest/services/Florida_Cases_Zips_COVID19/FeatureServerFor data 5/10/2020 or after: Archived data was exported directly from the live FDOH layer into the archive. For data prior to 5/10/2020: Data was exported by the University of South Florida - Digital Heritage and Humanities Collection using ArcGIS Pro Software. Data was then converted to shapefile and csv and uploaded into ArcGIS Online archive. For data definitions please visit the following box folder: https://usf.box.com/s/vfjwbczkj73ucj19yvwz53at6v6w614hData definition files names include the relative date they were published. The below information was taken from ancillary documents associated with the original layer from FDOH.Q. How is the zip code assigned to a person or case? Cases are counted in a zip code based on residential or mailing address, or by healthcare provider or lab address if other addresses are missing.Q. Why is the city data and the zip code data different? The zip code data is supplied to a healthcare worker, case manager, or lab technician by each individual during intake when a test is first recorded. When entering a zip code, the system we use automatically produces a list of cities within that zip code for the individual to further specify where they live. Sometimes the individual uses the postal city, which may be Miami, when in reality that person lives outside the City of Miami boundaries in the jurisdiction of Coral Gables. Many zip codes contain multiple city/town jurisdictions, and about 20% of zip codes overlap more than one county. Q: How is the Zip Code data calculated and/or shown? If a COUNTY has five or more cases (total): • In zip codes with fewer than 5 cases, the total number of cases is shown as “<5”. • Zip codes with 0 cases in these counties are “0" or "No cases.” • All values of 5 or greater are shown by the actual number of cases in that zip code. If a COUNTY has fewer than five total cases across all of its zip codes, then ALL of the zip codes within that county show the total number of cases as "Suppressed." Q: My zip code says "SUPPRESSED" under cases. What does that mean? IF Suppressed: This county currently has fewer than five cases across all zip codes in the county. In an effort to protect the privacy of our COVID-19-Positive residents, zip code data is only available in counties where five or more cases have been reported. Q: What about PO Box zip codes, or zip codes with letters, like 334MH? PO Box zip codes are not shown in the map. “Filler” zip codes with letters, like 334MH, are typically areas where no or very few people live – like the Florida Everglades, and are shown on the map like any other zip code. Key Data about Cases by Zip Code: ZIP = The zip code COUNTYNAME = The county for the zip code (multi-part counties have been split) ZIPX = The unique county-zip identifier used to pair the data during updates POName = The postal address name assigned to the zip code place_labels = A list of the municipalities intersecting the zip code boundary c_places = The list of cities cases self-reported as being residents of Cases_1 = The number of cases in each zip code, with conditions*LabelY = A calculated field for map display only. All questions regarding this dataset should be directed to the Florida Department of Health.

Florida COVID-19 Cases by Zip Code exported from the Florida Department of Health GIS Layer on date seen in file name. Archived by the University of South Florida Libraries, Digital Heritage and Humanities Collections. Contact: LibraryGIS@usf.edu.Please Cite Our GIS HUB. If you are a researcher or other utilizing our Florida COVID-19 HUB as a tool or accessing and utilizing the data provided herein, please provide an acknowledgement of such in any publication or re-publication. The following citation is suggested: University of South Florida Libraries, Digital Heritage and Humanities Collections. 2020. Florida COVID-19 Hub. Available at https://covid19-usflibrary.hub.arcgis.com/.https://doi.org/10.5038/USF-COVID-19-GISLive FDOH Data Source: https://services1.arcgis.com/CY1LXxl9zlJeBuRZ/arcgis/rest/services/Florida_Cases_Zips_COVID19/FeatureServerFor data 5/10/2020 or after: Archived data was exported directly from the live FDOH layer into the archive. For data prior to 5/10/2020: Data was exported by the University of South Florida - Digital Heritage and Humanities Collection using ArcGIS Pro Software. Data was then converted to shapefile and csv and uploaded into ArcGIS Online archive. For data definitions please visit the following box folder: https://usf.box.com/s/vfjwbczkj73ucj19yvwz53at6v6w614hData definition files names include the relative date they were published. The below information was taken from ancillary documents associated with the original layer from FDOH.Q. How is the zip code assigned to a person or case? Cases are counted in a zip code based on residential or mailing address, or by healthcare provider or lab address if other addresses are missing.Q. Why is the city data and the zip code data different? The zip code data is supplied to a healthcare worker, case manager, or lab technician by each individual during intake when a test is first recorded. When entering a zip code, the system we use automatically produces a list of cities within that zip code for the individual to further specify where they live. Sometimes the individual uses the postal city, which may be Miami, when in reality that person lives outside the City of Miami boundaries in the jurisdiction of Coral Gables. Many zip codes contain multiple city/town jurisdictions, and about 20% of zip codes overlap more than one county. Q: How is the Zip Code data calculated and/or shown? If a COUNTY has five or more cases (total): • In zip codes with fewer than 5 cases, the total number of cases is shown as “<5”. • Zip codes with 0 cases in these counties are “0" or "No cases.” • All values of 5 or greater are shown by the actual number of cases in that zip code. If a COUNTY has fewer than five total cases across all of its zip codes, then ALL of the zip codes within that county show the total number of cases as "Suppressed." Q: My zip code says "SUPPRESSED" under cases. What does that mean? IF Suppressed: This county currently has fewer than five cases across all zip codes in the county. In an effort to protect the privacy of our COVID-19-Positive residents, zip code data is only available in counties where five or more cases have been reported. Q: What about PO Box zip codes, or zip codes with letters, like 334MH? PO Box zip codes are not shown in the map. “Filler” zip codes with letters, like 334MH, are typically areas where no or very few people live – like the Florida Everglades, and are shown on the map like any other zip code. Key Data about Cases by Zip Code: ZIP = The zip code COUNTYNAME = The county for the zip code (multi-part counties have been split) ZIPX = The unique county-zip identifier used to pair the data during updates POName = The postal address name assigned to the zip code place_labels = A list of the municipalities intersecting the zip code boundary c_places = The list of cities cases self-reported as being residents of Cases_1 = The number of cases in each zip code, with conditions*LabelY = A calculated field for map display only. All questions regarding this dataset should be directed to the Florida Department of Health.

Florida COVID-19 Cases by Zip Code exported from the Florida Department of Health GIS Layer on date seen in file name. Archived by the University of South Florida Libraries, Digital Heritage and Humanities Collections. Contact: LibraryGIS@usf.edu.Please Cite Our GIS HUB. If you are a researcher or other utilizing our Florida COVID-19 HUB as a tool or accessing and utilizing the data provided herein, please provide an acknowledgement of such in any publication or re-publication. The following citation is suggested: University of South Florida Libraries, Digital Heritage and Humanities Collections. 2020. Florida COVID-19 Hub. Available at https://covid19-usflibrary.hub.arcgis.com/.https://doi.org/10.5038/USF-COVID-19-GISLive FDOH Data Source: https://services1.arcgis.com/CY1LXxl9zlJeBuRZ/arcgis/rest/services/Florida_Cases_Zips_COVID19/FeatureServerFor data 5/10/2020 or after: Archived data was exported directly from the live FDOH layer into the archive. For data prior to 5/10/2020: Data was exported by the University of South Florida - Digital Heritage and Humanities Collection using ArcGIS Pro Software. Data was then converted to shapefile and csv and uploaded into ArcGIS Online archive. For data definitions please visit the following box folder: https://usf.box.com/s/vfjwbczkj73ucj19yvwz53at6v6w614hData definition files names include the relative date they were published. The below information was taken from ancillary documents associated with the original layer from FDOH.Q. How is the zip code assigned to a person or case? Cases are counted in a zip code based on residential or mailing address, or by healthcare provider or lab address if other addresses are missing.Q. Why is the city data and the zip code data different? The zip code data is supplied to a healthcare worker, case manager, or lab technician by each individual during intake when a test is first recorded. When entering a zip code, the system we use automatically produces a list of cities within that zip code for the individual to further specify where they live. Sometimes the individual uses the postal city, which may be Miami, when in reality that person lives outside the City of Miami boundaries in the jurisdiction of Coral Gables. Many zip codes contain multiple city/town jurisdictions, and about 20% of zip codes overlap more than one county. Q: How is the Zip Code data calculated and/or shown? If a COUNTY has five or more cases (total): • In zip codes with fewer than 5 cases, the total number of cases is shown as “<5”. • Zip codes with 0 cases in these counties are “0" or "No cases.” • All values of 5 or greater are shown by the actual number of cases in that zip code. If a COUNTY has fewer than five total cases across all of its zip codes, then ALL of the zip codes within that county show the total number of cases as "Suppressed." Q: My zip code says "SUPPRESSED" under cases. What does that mean? IF Suppressed: This county currently has fewer than five cases across all zip codes in the county. In an effort to protect the privacy of our COVID-19-Positive residents, zip code data is only available in counties where five or more cases have been reported. Q: What about PO Box zip codes, or zip codes with letters, like 334MH? PO Box zip codes are not shown in the map. “Filler” zip codes with letters, like 334MH, are typically areas where no or very few people live – like the Florida Everglades, and are shown on the map like any other zip code. Key Data about Cases by Zip Code: ZIP = The zip code COUNTYNAME = The county for the zip code (multi-part counties have been split) ZIPX = The unique county-zip identifier used to pair the data during updates POName = The postal address name assigned to the zip code place_labels = A list of the municipalities intersecting the zip code boundary c_places = The list of cities cases self-reported as being residents of Cases_1 = The number of cases in each zip code, with conditions*LabelY = A calculated field for map display only. All questions regarding this dataset should be directed to the Florida Department of Health.

Florida COVID-19 Cases by Zip Code exported from the Florida Department of Health GIS Layer on date seen in file name. Archived by the University of South Florida Libraries, Digital Heritage and Humanities Collections. Contact: LibraryGIS@usf.edu.Please Cite Our GIS HUB. If you are a researcher or other utilizing our Florida COVID-19 HUB as a tool or accessing and utilizing the data provided herein, please provide an acknowledgement of such in any publication or re-publication. The following citation is suggested: University of South Florida Libraries, Digital Heritage and Humanities Collections. 2020. Florida COVID-19 Hub. Available at https://covid19-usflibrary.hub.arcgis.com/.https://doi.org/10.5038/USF-COVID-19-GISLive FDOH Data Source: https://services1.arcgis.com/CY1LXxl9zlJeBuRZ/arcgis/rest/services/Florida_Cases_Zips_COVID19/FeatureServerFor data 5/10/2020 or after: Archived data was exported directly from the live FDOH layer into the archive. For data prior to 5/10/2020: Data was exported by the University of South Florida - Digital Heritage and Humanities Collection using ArcGIS Pro Software. Data was then converted to shapefile and csv and uploaded into ArcGIS Online archive. For data definitions please visit the following box folder: https://usf.box.com/s/vfjwbczkj73ucj19yvwz53at6v6w614hData definition files names include the relative date they were published. The below information was taken from ancillary documents associated with the original layer from FDOH.Q. How is the zip code assigned to a person or case? Cases are counted in a zip code based on residential or mailing address, or by healthcare provider or lab address if other addresses are missing.Q. Why is the city data and the zip code data different? The zip code data is supplied to a healthcare worker, case manager, or lab technician by each individual during intake when a test is first recorded. When entering a zip code, the system we use automatically produces a list of cities within that zip code for the individual to further specify where they live. Sometimes the individual uses the postal city, which may be Miami, when in reality that person lives outside the City of Miami boundaries in the jurisdiction of Coral Gables. Many zip codes contain multiple city/town jurisdictions, and about 20% of zip codes overlap more than one county. Q: How is the Zip Code data calculated and/or shown? If a COUNTY has five or more cases (total): • In zip codes with fewer than 5 cases, the total number of cases is shown as “<5”. • Zip codes with 0 cases in these counties are “0" or "No cases.” • All values of 5 or greater are shown by the actual number of cases in that zip code. If a COUNTY has fewer than five total cases across all of its zip codes, then ALL of the zip codes within that county show the total number of cases as "Suppressed." Q: My zip code says "SUPPRESSED" under cases. What does that mean? IF Suppressed: This county currently has fewer than five cases across all zip codes in the county. In an effort to protect the privacy of our COVID-19-Positive residents, zip code data is only available in counties where five or more cases have been reported. Q: What about PO Box zip codes, or zip codes with letters, like 334MH? PO Box zip codes are not shown in the map. “Filler” zip codes with letters, like 334MH, are typically areas where no or very few people live – like the Florida Everglades, and are shown on the map like any other zip code. Key Data about Cases by Zip Code: ZIP = The zip code COUNTYNAME = The county for the zip code (multi-part counties have been split) ZIPX = The unique county-zip identifier used to pair the data during updates POName = The postal address name assigned to the zip code place_labels = A list of the municipalities intersecting the zip code boundary c_places = The list of cities cases self-reported as being residents of Cases_1 = The number of cases in each zip code, with conditions*LabelY = A calculated field for map display only. All questions regarding this dataset should be directed to the Florida Department of Health.