United States of America GIS data

The dataset contains locations and attributes for above ground permits applied for and approved by the District Department of Transportation. They are existing occupied constructions and events. Examples include: moving trucks, roll off debris container, moving storage container, construction staging area, mobile crane work zone, other reserved parking. The public space permit process is described on the DDOT website https://ddot.dc.gov. These data are shared via an automated process where addresses are batch matched (geocoded) to the District's Master Address Repository. Users may find that some data points will contain 0,0 for X,Y coordinates resulting in inconsistent spatial locations. Addresses for these data points could not be automatically geocoded and will need to be manually geocoded to 'best fit' locations in DC. Use the MAR Geocoder to help complete this.

The urban areas created by the US Census Bureau "represent densely developed territory, and encompass residential, commercial, and other nonresidential urban land uses. Each urban area must encompass at least 2,000 housing units or at least 5,000 people." They were created by the Bureau following the 2020 census based on the population and housing unit density of individual blocks. The 2020 Census increased the urban population and housing unit count requirements for the first time since 1910, resulting in differences between the 2010 and 2020 boundaries beyond those resulting from population change. In addition, they also stopped distinguishing between "urbanized areas" and "urban clusters" and renamed areas as needed to reflect the updated boundaries. Please see the US Census Bureau website for more information.

Race Routes for Special Events: Five-Kilometer Ocean-City Route.

Locations and businesses permitted to offer valet parking and their permit status.

City-owned and leased facilities maintained in the City's Facility System of Record (FSR). Does not include the following agencies which are not part of the City and County of San Francisco: SFHA, OCII and City College. This dataset was developed through a process involving some of the primary stewards for the facility data and their stakeholders. It is meant to be a living reference and will be maintained and updated through established workflows and processes over time. You can access the attached User Guide for more detail by clicking the red About button and scrolling to attachments. Data pushed to ArcGIS Online on October 19, 2026 at 3:15 AM by SFGIS. Data from: https://data.sfgov.org/d/nc68-ngbr Description of dataset columns: facility_id System generated unique facility identifier common_name Commonly known/used facility name address Address or location description of facility city City where facility is located. zip_code ZIP Code where facility is located. block_lot The block and lot number, also known as the Assessor Parcel Number or APN. For facilities with multiple APNs associated, the lowest numbered APN is used. This will blank if in the facility is the right-of-way or outside of San Francisco county. owned_leased Indicates if the facility is owned or leased by the City. dept_id_for_jurisdiction Department ID of the City department with jurisdiction over the facility. jurisdiction Jurisdiction: department name of the City department with jurisdiction over the facility. gross_sq_ft Gross square footage of facility (original source: FRRM). Note: Incomplete data, updating as values are determined. longitude The longitude of the facility's location. latitude The latitude of the facility's location. supervisor_district Board of Supervisors District in which the facility is located, if applicable. Note: there are city facilities that are outside the boundaries of the City and County of San Francisco. city_tenants City departments that are tenants of the facility, separated by a semi-colon. land_id Foreign key to City Lands table. geom The geometry/location column which allows the facility to be mapped in Socrata. data_last_updated Timestamp when the record (row) was last updated in the source system data_as_of Timestamp when the record (row) was last refreshed in the source system data_loaded_at Timestamp when the record (row) was was last updated here (in the data portal) Analysis Neighborhoods DELETE - Neighborhoods_from_fyvs_ahh9 DELETE - Supervisor Districts DELETE - Current Police Districts DELETE - Fire Prevention Districts DELETE - Zip Codes Neighborhoods SF Find Neighborhoods Current Police Districts Current Supervisor Districts Note: If no description was provided by DataSF, the cell is left blank. See the source data for more information.

Intended for searching and web map display in Portal web maps and web applications or in ArcGIS Pro. Source of feature class that published this web service is from TERRA enterprise geodatabase in the YCSO_Flex_Boundaries Feature Dataset. Key words are standardized for ArcGIS Pro users to be able to search through the County's Geo Portal web services without being logged in. A common label expression was created for each layer.

Polygon features representing zoning districts for the City of Flagler Beach, with each feature carrying a zoning code and zoning description such as single family residential, tourist commercial, or recreation/PUD. Attributes also include ordinance numbers, book and page references, and notes. Published by GISAdmin_FCMAPS.

This feature layer, utilizing National Geospatial Data Asset (NGDA) data from the U.S. Geological Survey, displays hospitals, medical centers, ambulance services, fire stations and EMS stations in the U.S. Per the USGS, “Structures data are designed to be used in general mapping and in the analysis of structure related activities using geographic information system technology. The National Map structures data is commonly combined with other data themes, such as boundaries, elevation, hydrography, and transportation, to produce general reference base maps. The types of structures collected are largely determined by the needs of disaster planning and emergency response, and homeland security organizations.” Data Source Location: Medical Emergency Response Structures - Overview

Congressional Districts, Voting Districts, State Legislative Districts - Upper, State Legislative Districts - Lower; January 1, 2015 vintage; Generalized

ACS 2022 Legal and Statistical Entities Web Map Service; January 1, 2022 vintage

Legal and Statistical Entities Web Map Service; January 1, 2020 vintage

Legal and Statistical Entities Web Map Service; January 1, 2020 vintage

Legal and Statistical Entities Web Map Service; January 1, 2010 vintage

ACS 2017 Legal and Statistical Entities Web Map Service; January 1, 2017 vintage

ACS 2019 Legal and Statistical Entities Web Map Service; January 1, 2019 vintage

Census Regions, Census Divisions; January 1, 2015 vintage; Generalized

County Subdivisions, Subbarrios, Consolidated Cities, Incorporated Places, and Census Designated Places; January 1, 2015 vintage; Generalized

Legal and Statistical Entities Web Map Service; January 1, 2000 vintage

Census Regions, Census Divisions; January 1, 2015 vintage; Generalized

Census Current (2026) WMS Legal and Statistical Entities Web Map Service; January 1, 2026 vintage

Legal and Statistical Entities Web Map Service; January 1, 2000 vintage

Census Regions, Census Divisions; January 1, 2015 vintage; Generalized

ACS 2025 Legal and Statistical Entities Web Map Service; January 1, 2025 vintage

ACS 2012 Legal and Statistical Entities Web Map Service; January 1, 2012 vintage

ACS 2013 Legal and Statistical Entities Web Map Service; January 1, 2013 vintage

ACS 2013 Legal and Statistical Entities Web Map Service; January 1, 2013 vintage

ACS 2013 Legal and Statistical Entities Web Map Service; January 1, 2013 vintage

NOTE: Due to the higher resolution of this data, it may be slow to load or require the user to zoom to a smaller area of interest. Date of Images: Post-Event: 7/11/2026, 7/12/2026 Pre-Event: Date of Next Image: Unknown Summary: Skysat is a high-resolution satellite constellation operated by Planet and allows for multiple viewing opportunities of any location on Earth daily. Skysat collects 4-band imagery which allows for multiple derived products to be produced. The True Color RGB composite provides a product of how the surface would look to the naked eye from space. The RGB is created using the red, green, and blue channels of the respective instrument. The Color Infrared composite is created using the near-infrared, red, and green channels. The near-infrared gives the ability to see through thin clouds. Healthy vegetation is shown as red, water is in blue. Normalized Differential Vegetation Index (NDVI) maps are produced by converting pixel values to NDVI = (Red – NIR)/(Red + NIR), NIR indicates the near infrared band. The dynamically generated Normalized Difference Vegetation Index (NDVI) layer is an index for quantifying green vegetation. It reflects the state of vegetation health based on how vegetation reflects light at certain wavelengths. Suggested Use: The True Color RGB provides a product of how the surface would look to the naked eye from space and may show damage caused by severe weather. The True Color RGB is produced using the 3 visible wavelength bands (red, green, and blue) from the respective sensor. Some minor atmospheric corrections have occurred. A Color Infrared composite depicts healthy vegetation as red, water as blue. Some minor atmospheric corrections have occurred. For NDVI, dark green colors are areas with a lot of green leaf growth which indicates the presence of chlorophyll. Chlorophyll reflects more infrared light and less visible light. Areas with some green leaf growth are in light greens, and areas with little to no vegetation growth are even lighter greens. Resolution: ~1 meter Esri REST Endpoint: See URL section on right side of page of individual layers below.

ACS 2013 Legal and Statistical Entities Web Map Service; January 1, 2013 vintage

Legal and Statistical Entities Web Map Service; January 1, 2000 vintage

ACS 2013 Legal and Statistical Entities Web Map Service; January 1, 2013 vintage

ACS 2013 Legal and Statistical Entities Web Map Service; January 1, 2013 vintage

ACS 2013 Legal and Statistical Entities Web Map Service; January 1, 2013 vintage

ACS 2013 Legal and Statistical Entities Web Map Service; January 1, 2013 vintage

ACS 2018 Legal and Statistical Entities Web Map Service; January 1, 2018 vintage

ACS 2013 Legal and Statistical Entities Web Map Service; January 1, 2013 vintage