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TwitterSan Diego, CA is popular among tourists for its beautiful sceneries, including beaches and state parks. This map will help you plan your trip to San Diego better with displaying beaches, some of its famous tourist attractions, and transportation routes. You will be able to interactively explore tourist attraction spots in San Diego and see what transportation you can use to get there.Layers: Tourist Attractions created by me using locations found in a Google Maps SearchSan Diego Swimming Beaches obtained from the dataset "Access points" from California State Geoportal and downloaded as a shapefile, and modified in ArcMap (Add from Web)Public Transportation dataset obtained from San Diego Open GIS Data Portal using the webservice at https://gissd.sandag.org/rdw/rest/services/Transportation/GTFS_Transit/MapServer/1 (Add from File)Pop-ups: Each layer described above has a pop-up descriptions. The Tourist Attractions layer contains a short summary of the attraction and a picture, San Diego Swimming Beaches contains name, location, and parking, restroom, lifeguard, and showers availability, and Public Transportation shows the route name and type.Bookmarks: There are three bookmarks - San Diego, Downtown San Diego, and Northern San Diego. The San Diego bookmark is the default showing the entire San Diego area. On the other hand, Downtown San Diego shows the majority of tourist attractions which are located in downtown and Northern San Diego shows Torrey Pine State Reserve, located in the northern part of the city.
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TwitterThe City of San Diego Map Gallery contains a number of web maps and applications.The CIP Project Map Viewer and San Diego Underground Utility Projects mapping applications are maintained by Quartic Solutions as subcontractor (through CGI) for the City of San Diego.
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TwitterGeospatial data about City of San Diego, California Water Pipes. Export to CAD, GIS, PDF, CSV and access via API.
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TwitterThis dataset is a collection of the current base zone designations applied to property in the City of San Diego, as per the Official Zoning Map adopted by the City Council on February 28, 2006, and all subsequent updates.
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TwitterThis dataset comprises road centerlines for all roads in San Diego County. Road centerline information is collected from recorded documents (subdivision and parcel maps) and information provided by local jurisidictions (Cities in San Diego County, County of San Diego). Road names and address ranges are as designated by the official address coordinator for each jurisidcition. Jurisdictional information is created from spatial overlays with other data layers (e.g. Jurisdiction, Census Tract).The layer contains both public and private roads. Not all roads are shown on official, recorded documents. Centerlines may be included for dedicated public roads even if they have not been constructed. Public road names are the official names as maintained by the addressing authority for the jurisdiction in which the road is located. Official road names may not match the common or local name used to identify the road (e.g. State Route 94 is the official name of certain road segments commonly referred to as Campo Road).Private roads are either named or unnamed. Named private roads are as shown on official recorded documents or as directed by the addressing authority for the jurisdiction in which the road is located. Unnamed private roads are included where requested by the local jurisidiction or by SanGIS JPA members (primarily emergency response dispatch agencies). Roads are comprised of road segments that are individually identified by a unique, and persistent, ID (ROADSEGID). Roads segments are terminated where they intersect with each other, at jurisdictional boundaries (i.e. city limits), certain census tract and law beat boundaries, at locations where road names change, and at other locations as required by SanGIS JPA members. Each road segment terminates at an intersection point that can be found in the ROADS_INTERSECTION layer.Road centerlines do not necessarily follow the centerline of dedicated rights-of-way (ROW). Centerlines are adjusted as needed to fit the actual, constructed roadway. However, many road centerline segments are created intially based on record documents prior to construction and may not have been updated to meet as-built locations. Please notify SanGIS if the actual location differs from that shown. See the SanGIS website for contact information and reporting problems (http://www.sangis.org/contact/problem.html).Note, the road speeds in this layer are based on road segment class and were published as part of an agreement between San Diego Fire-Rescue, the San Diego County Sheriff's Department, and SanGIS. The average speed is based on heavy fire vehicles and may not represent the posted speed limit.
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TwitterWARNING: This is a pre-release dataset and its fields names and data structures are subject to change. It should be considered pre-release until the end of 2024. Expected changes:Metadata is missing or incomplete for some layers at this time and will be continuously improved.We expect to update this layer roughly in line with CDTFA at some point, but will increase the update cadence over time as we are able to automate the final pieces of the process.This dataset is continuously updated as the source data from CDTFA is updated, as often as many times a month. If you require unchanging point-in-time data, export a copy for your own use rather than using the service directly in your applications.PurposeCounty and incorporated place (city) boundaries along with third party identifiers used to join in external data. Boundaries are from the authoritative source the California Department of Tax and Fee Administration (CDTFA), altered to show the counties as one polygon. This layer displays the city polygons on top of the County polygons so the area isn"t interrupted. The GEOID attribute information is added from the US Census. GEOID is based on merged State and County FIPS codes for the Counties. Abbreviations for Counties and Cities were added from Caltrans Division of Local Assistance (DLA) data. Place Type was populated with information extracted from the Census. Names and IDs from the US Board on Geographic Names (BGN), the authoritative source of place names as published in the Geographic Name Information System (GNIS), are attached as well. Finally, the coastline is used to separate coastal buffers from the land-based portions of jurisdictions. This feature layer is for public use.Related LayersThis dataset is part of a grouping of many datasets:Cities: Only the city boundaries and attributes, without any unincorporated areasWith Coastal BuffersWithout Coastal BuffersCounties: Full county boundaries and attributes, including all cities within as a single polygonWith Coastal BuffersWithout Coastal BuffersCities and Full Counties: A merge of the other two layers, so polygons overlap within city boundaries. Some customers require this behavior, so we provide it as a separate service.With Coastal Buffers (this dataset)Without Coastal BuffersPlace AbbreviationsUnincorporated Areas (Coming Soon)Census Designated Places (Coming Soon)Cartographic CoastlinePolygonLine source (Coming Soon)Working with Coastal BuffersThe dataset you are currently viewing includes the coastal buffers for cities and counties that have them in the authoritative source data from CDTFA. In the versions where they are included, they remain as a second polygon on cities or counties that have them, with all the same identifiers, and a value in the COASTAL field indicating if it"s an ocean or a bay buffer. If you wish to have a single polygon per jurisdiction that includes the coastal buffers, you can run a Dissolve on the version that has the coastal buffers on all the fields except COASTAL, Area_SqMi, Shape_Area, and Shape_Length to get a version with the correct identifiers.Point of ContactCalifornia Department of Technology, Office of Digital Services, odsdataservices@state.ca.govField and Abbreviation DefinitionsCOPRI: county number followed by the 3-digit city primary number used in the Board of Equalization"s 6-digit tax rate area numbering systemPlace Name: CDTFA incorporated (city) or county nameCounty: CDTFA county name. For counties, this will be the name of the polygon itself. For cities, it is the name of the county the city polygon is within.Legal Place Name: Board on Geographic Names authorized nomenclature for area names published in the Geographic Name Information SystemGNIS_ID: The numeric identifier from the Board on Geographic Names that can be used to join these boundaries to other datasets utilizing this identifier.GEOID: numeric geographic identifiers from the US Census Bureau Place Type: Board on Geographic Names authorized nomenclature for boundary type published in the Geographic Name Information SystemPlace Abbr: CalTrans Division of Local Assistance abbreviations of incorporated area namesCNTY Abbr: CalTrans Division of Local Assistance abbreviations of county namesArea_SqMi: The area of the administrative unit (city or county) in square miles, calculated in EPSG 3310 California Teale Albers.COASTAL: Indicates if the polygon is a coastal buffer. Null for land polygons. Additional values include "ocean" and "bay".GlobalID: While all of the layers we provide in this dataset include a GlobalID field with unique values, we do not recommend you make any use of it. The GlobalID field exists to support offline sync, but is not persistent, so data keyed to it will be orphaned at our next update. Use one of the other persistent identifiers, such as GNIS_ID or GEOID instead.AccuracyCDTFA"s source data notes the following about accuracy:City boundary changes and county boundary line adjustments filed with the Board of Equalization per Government Code 54900. This GIS layer contains the boundaries of the unincorporated county and incorporated cities within the state of California. The initial dataset was created in March of 2015 and was based on the State Board of Equalization tax rate area boundaries. As of April 1, 2024, the maintenance of this dataset is provided by the California Department of Tax and Fee Administration for the purpose of determining sales and use tax rates. The boundaries are continuously being revised to align with aerial imagery when areas of conflict are discovered between the original boundary provided by the California State Board of Equalization and the boundary made publicly available by local, state, and federal government. Some differences may occur between actual recorded boundaries and the boundaries used for sales and use tax purposes. The boundaries in this map are representations of taxing jurisdictions for the purpose of determining sales and use tax rates and should not be used to determine precise city or county boundary line locations. COUNTY = county name; CITY = city name or unincorporated territory; COPRI = county number followed by the 3-digit city primary number used in the California State Board of Equalization"s 6-digit tax rate area numbering system (for the purpose of this map, unincorporated areas are assigned 000 to indicate that the area is not within a city).Boundary ProcessingThese data make a structural change from the source data. While the full boundaries provided by CDTFA include coastal buffers of varying sizes, many users need boundaries to end at the shoreline of the ocean or a bay. As a result, after examining existing city and county boundary layers, these datasets provide a coastline cut generally along the ocean facing coastline. For county boundaries in northern California, the cut runs near the Golden Gate Bridge, while for cities, we cut along the bay shoreline and into the edge of the Delta at the boundaries of Solano, Contra Costa, and Sacramento counties.In the services linked above, the versions that include the coastal buffers contain them as a second (or third) polygon for the city or county, with the value in the COASTAL field set to whether it"s a bay or ocean polygon. These can be processed back into a single polygon by dissolving on all the fields you wish to keep, since the attributes, other than the COASTAL field and geometry attributes (like areas) remain the same between the polygons for this purpose.SliversIn cases where a city or county"s boundary ends near a coastline, our coastline data may cross back and forth many times while roughly paralleling the jurisdiction"s boundary, resulting in many polygon slivers. We post-process the data to remove these slivers using a city/county boundary priority algorithm. That is, when the data run parallel to each other, we discard the coastline cut and keep the CDTFA-provided boundary, even if it extends into the ocean a small amount. This processing supports consistent boundaries for Fort Bragg, Point Arena, San Francisco, Pacifica, Half Moon Bay, and Capitola, in addition to others. More information on this algorithm will be provided soon.Coastline CaveatsSome cities have buffers extending into water bodies that we do not cut at the shoreline. These include South Lake Tahoe and Folsom, which extend into neighboring lakes, and San Diego and surrounding cities that extend into San Diego Bay, which our shoreline encloses. If you have feedback on the exclusion of these items, or others, from the shoreline cuts, please reach out using the contact information above.Offline UseThis service is fully enabled for sync and export using Esri Field Maps or other similar tools. Importantly, the GlobalID field exists only to support that use case and should not be used for any other purpose (see note in field descriptions).Updates and Date of ProcessingConcurrent with CDTFA updates, approximately every two weeks, Last Processed: 12/17/2024 by Nick Santos using code path at https://github.com/CDT-ODS-DevSecOps/cdt-ods-gis-city-county/ at commit 0bf269d24464c14c9cf4f7dea876aa562984db63. It incorporates updates from CDTFA as of 12/12/2024. Future updates will include improvements to metadata and update frequency.
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TwitterCC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
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This EnviroAtlas dataset presents environmental benefits of the urban forest in 1735 block groups in San Diego, California. Carbon attributes, temperature reduction, pollution removal and value, and runoff effects are calculated for each block group using i-Tree models (www.itreetools.org), local weather data, pollution data, EPA provided city boundary and land cover data, and U.S. Census derived block group boundary data. This dataset was produced by the US Forest Service to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).
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TwitterA historical district means a significant concentration, linkage, or continuity of sites, buildings, structures, or objects that are united historically, geographically, or aesthetically by plan or physical development and that have a special character, historical interest, cultural or aesthetic value, or that represent one or more architectural periods or styles in the history and development of the City." (San Diego Land Development Code Section 113.0103)Please note that this data has been modified since its original publication for use in the San Diego Ocean Planning Partnership. In particular, a field linking to the City of San Diego's website has been added for further context on historic districts.Please also note that this dataset contains both existing (adopted) districts as well as proposed districts identified by the "TYPE" field.
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TwitterGeospatial data about City of San Diego, California Storm Drain. Export to CAD, GIS, PDF, CSV and access via API.
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TwitterThese data provide an accurate high-resolution shoreline compiled from imagery of PORT OF SAN DIEGO, CA . This vector shoreline data is based on an office interpretation of imagery that may be suitable as a geographic information system (GIS) data layer. This metadata describes information for both the line and point shapefiles. The NGS attribution scheme 'Coastal Cartographic Object Attribut...
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TwitterThis dataset contains the geographic data used to create maps for the San Diego County Regional Equity Indicators Report led by the Office of Equity and Racial Justice (OERJ). The full report can be found here: https://data.sandiegocounty.gov/stories/s/7its-kgpt
Demographic data from the report can be found here: https://data.sandiegocounty.gov/dataset/Equity-Report-Data-Demographics/q9ix-kfws
Filter by the Indicator column to select data for a particular indicator map.
Export notes: Dataset may not automatically open correctly in Excel due to geospatial data. To export the data for geospatial analysis, select Shapefile or GEOJSON as the file type. To view the data in Excel, export as a CSV but do not open the file. Then, open a blank Excel workbook, go to the Data tab, select “From Text/CSV,” and follow the prompts to import the CSV file into Excel. Alternatively, use the exploration options in "View Data" to hide the geographic column prior to exporting the data.
USER NOTES: 4/7/2025 - The maps and data have been removed for the Health Professional Shortage Areas indicator due to inconsistencies with the data source leading to some missing health professional shortage areas. We are working to fix this issue, including exploring possible alternative data sources.
5/21/2025 - The following changes were made to the 2023 report data (Equity Report Year = 2023). Self-Sufficiency Wage - a typo in the indicator name was fixed (changed sufficienct to sufficient) and the percent for one PUMA corrected from 56.9 to 59.9 (PUMA = San Diego County (Northwest)--Oceanside City & Camp Pendleton). Notes were made consistent for all rows where geography = ZCTA. A note was added to all rows where geography = PUMA. Voter registration - label "92054, 92051" was renamed to be in numerical order and is now "92051, 92054". Removed data from the percentile column because the categories are not true percentiles. Employment - Data was corrected to show the percent of the labor force that are employed (ages 16 and older). Previously, the data was the percent of the population 16 years and older that are in the labor force. 3- and 4-Year-Olds Enrolled in School - percents are now rounded to one decimal place. Poverty - the last two categories/percentiles changed because the 80th percentile cutoff was corrected by 0.01 and one ZCTA was reassigned to a different percentile as a result. Low Birthweight - the 33th percentile label was corrected to be written as the 33rd percentile. Life Expectancy - Corrected the category and percentile assignment for SRA CENTRAL SAN DIEGO. Parks and Community Spaces - corrected the category assignment for six SRAs.
5/21/2025 - Data was uploaded for Equity Report Year 2025. The following changes were made relative to the 2023 report year. Adverse Childhood Experiences - added geographic data for 2025 report. No calculation of bins nor corresponding percentiles due to small number of geographic areas. Low Birthweight - no calculation of bins nor corresponding percentiles due to small number of geographic areas.
Prepared by: Office of Evaluation, Performance, and Analytics and the Office of Equity and Racial Justice, County of San Diego, in collaboration with the San Diego Regional Policy & Innovation Center (https://www.sdrpic.org).
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TwitterHistorical districts contain multiple properties and/or objects that share historical significance. The City’s Historical Resources Board can establish a district if the contributing resources meet one of six criteria. For more information, read the nomination guidelines.
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TwitterShapefile of the City’s street network. This shapefile contains the street segments identified in our streets repair projects and Overall Condition Index datasets. This data is displayed on streets.sandiego.gov.
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Twitter2005 Lidar coverage over cities of San Diego, Poway, and Chula Vista. These lidar data are part of a larger project that collected lidar for a number of coastal cities in San Diego County. Data from the same 2005 lidar project may be available for other cities beyond San Diego, Poway, and Chula Vista but those cities should be contacted individually. Lidar data were collected in conjunction with a three-inch resolution imagery collection for San Diego, Poway, and Chula Vista. Lidar products include LAS files and ASCII canopy data at a minimum; Poway adds two foot contours. Point spacing of LAS data is approximately one meter. Data have also been resampled to a one-ninth arc second grid (three meter spacing) and placed within the National Elevation Dataset.
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TwitterApprovals for permits, maps, agreements, and other applications processed by Development Services Department’s current cloud-based permitting system. Approval types began migrating to the current system in 2018. Data from the legacy system can be found in this dataset. A permit is required for projects such as new construction, additions, remodeling, or repairs to electrical, mechanical, and plumbing systems. A full list of the available record types is available within the metadata.
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TwitterVector polygon map data of property parcels from the City of San Antonio, Texas containing 629,531 features.
Parcel map data consists of detailed information about individual land parcels, including their boundaries, ownership details, and geographic coordinates.
Parcel data can be used to analyze and visualize land-related information for purposes such as real estate assessment, urban planning, or environmental management.
Attributes for this data layer include: Shape_area, GlobalID, Shape_len, Shape, ModifiedDate, ParcelKey, and ModifiedUID.
Available for viewing and sharing in a Koordinates map viewer. This data is also available for export to DWG for CAD, PDF, KML, CSV, and GIS data formats, including Shapefile, MapInfo, and Geodatabase.
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TwitterThis web map utilizes the layers listed below. Most layers are created and maintained by national organizations specializing in the topical area for which they represent. This map is to consolidate information on an SVI of San Diego County, and bring together hazard information such as earthquake, drought, and wildfire information.
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TwitterVegetation mapping has been conducted at various City of San Diego Park and Recreation Open Space lands in support of natural resource management objectives and the City's MSCP. In 2004, vegetation mapping and sensitive species surveys were conducted at the Tecolote Canyon Natural Park by HELIX Environmental Planning, Inc. (HELIX) to establish baseline data for the park's Natural Resource Management Plan. RECON Environmental conducted vegetation mapping at Mission Trails Regional Park (MTRP) in 2008 in support of the MSCP. This dataset was compiled as part of the Southern California Data Integration Project. Vegetation mapping (including mapping of exotic species) of Tecolote Canyon was conducted in the spring of 2004 on georeferenced aerial photos (flown January 2003; scale 1"=200'; Andrea Bitterling, pers. comm.). Vernal pools and rare plants were mapped with a GPS, with accuracy of approximately 1 meter. RECON biologists mapped the vegetation in MTRP between March 18 and April 24, 2008. A three-fold approach to vegetation mapping at MTRP was taken: reviewing historical biological information, mapping potential vegetation communities using aerial photographs, and conducting field mapping. Prior to conducting the field work, existing GIS data from the California Natural Diversity Database (CNDDB), vegetation data from SanGIS, and vernal pool data from the City of San Diego were all examined. In addition, aerial photographs from 2000, 2002, 2003, and 2007 were reviewed to assist with vegetation identification. Digital orthorectified aerial images with 1-foot resolution, taken in 2007, were carefully reviewed on a computer monitor and on printed maps prior to field surveys to identify unique color and shape patterns of exotic species and to distinguish stands (polygons) to be mapped in the field. These photographs, with preliminary stand overlays, were used to create field maps for MTRP. The field maps were used to confirm and map vegetation communities identified in the field. Field mapping consisted of driving or hiking to all areas in the MTRP. Areas identified as a homogeneous vegetation community stand in the field were mapped as individual polygons (CNPS 2004). Homogenous stands ranged in size from 0.25 acre to hundreds of acres. Most of the homogeneous stands were large, making it difficult to summarize the species composition, cover, and structure of an entire stand. Sampling of representative portions of large stands was performed using the California Native Plant Society (CNPS) Rapid Assessment Method to determine the species composition and cover class for characteristic plant species within each stand. Sampling consisted of selecting a representative area, walking through the area, and identifying characteristic species present, qualitatively estimating cover for each characteristic species and using binoculars to scan the entire stand to confirm that it was homogenous. Occasionally, stands were inaccessible, precluding direct observations. In these cases, estimations were made using aerial photographs, binoculars, and best judgment of the biologists. Following field mapping, all collected data was reviewed in the office to determine a vegetation series classification, vegetation alliance and where applicable, an association (Sawyer and Keeler-Wolf classification). The series, alliance, and association were used to name all vegetation communities mapped at MTRP. Several factors limited data collection at MTRP. Primarily these included species phenology and some areas with difficult access. Native or invasive plant species apparent at the time of the surveys were noted and classified. Due to differences in phenology of many species, plants apparent or obvious outside of the early spring survey period may not have been identified. References Andrea Bitterling, HELIX. 2009. Personal Communication, 2009. RECON. 2009. Report for Phase I of the Resource Management Plan for Mission Trails Regional Park, City of San Diego. Prepared for City of San Diego Parks & Recreation Department, January 7, 2009.
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TwitterExplore active listings and real-time home values for houses, condominiums, and townhomes in San Diego Mid-City:Kensington-Talmadge CA See prices, sizes, and property types on an interactive map.
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TwitterMIT Licensehttps://opensource.org/licenses/MIT
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Note: The schema changed in February 2025 - please see below. We will post a roadmap of upcoming changes, but service URLs and schema are now stable. For deployment status of new services beginning in February 2025, see https://gis.data.ca.gov/pages/city-and-county-boundary-data-status. Additional roadmap and status links at the bottom of this metadata.This dataset is regularly updated as the source data from CDTFA is updated, as often as many times a month. If you require unchanging point-in-time data, export a copy for your own use rather than using the service directly in your applications. PurposeCounty boundaries along with third party identifiers used to join in external data. Boundaries are from the California Department of Tax and Fee Administration (CDTFA). These boundaries are the best available statewide data source in that CDTFA receives changes in incorporation and boundary lines from the Board of Equalization, who receives them from local jurisdictions for tax purposes. Boundary accuracy is not guaranteed, and though CDTFA works to align boundaries based on historical records and local changes, errors will exist. If you require a legal assessment of boundary location, contact a licensed surveyor.This dataset joins in multiple attributes and identifiers from the US Census Bureau and Board on Geographic Names to facilitate adding additional third party data sources. In addition, we attach attributes of our own to ease and reduce common processing needs and questions. Finally, coastal buffers are separated into separate polygons, leaving the land-based portions of jurisdictions and coastal buffers in adjacent polygons. This feature layer is for public use. Related LayersThis dataset is part of a grouping of many datasets:Cities: Only the city boundaries and attributes, without any unincorporated areasWith Coastal BuffersWithout Coastal BuffersCounties: Full county boundaries and attributes, including all cities within as a single polygonWith Coastal Buffers (this dataset)Without Coastal BuffersCities and Full Counties: A merge of the other two layers, so polygons overlap within city boundaries. Some customers require this behavior, so we provide it as a separate service.With Coastal BuffersWithout Coastal BuffersCity and County AbbreviationsUnincorporated Areas (Coming Soon)Census Designated PlacesCartographic CoastlinePolygonLine source (Coming Soon)State BoundaryWith Bay CutsWithout Bay Cuts Working with Coastal Buffers The dataset you are currently viewing includes the coastal buffers for cities and counties that have them in the source data from CDTFA. In the versions where they are included, they remain as a second polygon on cities or counties that have them, with all the same identifiers, and a value in the COASTAL field indicating if it"s an ocean or a bay buffer. If you wish to have a single polygon per jurisdiction that includes the coastal buffers, you can run a Dissolve on the version that has the coastal buffers on all the fields except OFFSHORE and AREA_SQMI to get a version with the correct identifiers. Point of ContactCalifornia Department of Technology, Office of Digital Services, gis@state.ca.gov Field and Abbreviation DefinitionsCDTFA_COUNTY: CDTFA county name. For counties, this will be the name of the polygon itself. For cities, it is the name of the county the city polygon is within.CDTFA_COPRI: county number followed by the 3-digit city primary number used in the Board of Equalization"s 6-digit tax rate area numbering system. The boundary data originate with CDTFA's teams managing tax rate information, so this field is preserved and flows into this dataset.CENSUS_GEOID: numeric geographic identifiers from the US Census BureauCENSUS_PLACE_TYPE: City, County, or Town, stripped off the census name for identification purpose.GNIS_PLACE_NAME: Board on Geographic Names authorized nomenclature for area names published in the Geographic Name Information SystemGNIS_ID: The numeric identifier from the Board on Geographic Names that can be used to join these boundaries to other datasets utilizing this identifier.CDT_COUNTY_ABBR: Abbreviations of county names - originally derived from CalTrans Division of Local Assistance and now managed by CDT. Abbreviations are 3 characters.CDT_NAME_SHORT: The name of the jurisdiction (city or county) with the word "City" or "County" stripped off the end. Some changes may come to how we process this value to make it more consistent.AREA_SQMI: The area of the administrative unit (city or county) in square miles, calculated in EPSG 3310 California Teale Albers.OFFSHORE: Indicates if the polygon is a coastal buffer. Null for land polygons. Additional values include "ocean" and "bay".PRIMARY_DOMAIN: Currently empty/null for all records. Placeholder field for official URL of the city or countyCENSUS_POPULATION: Currently null for all records. In the future, it will include the most recent US Census population estimate for the jurisdiction.GlobalID: While all of the layers we provide in this dataset include a GlobalID field with unique values, we do not recommend you make any use of it. The GlobalID field exists to support offline sync, but is not persistent, so data keyed to it will be orphaned at our next update. Use one of the other persistent identifiers, such as GNIS_ID or GEOID instead. Boundary AccuracyCounty boundaries were originally derived from a 1:24,000 accuracy dataset, with improvements made in some places to boundary alignments based on research into historical records and boundary changes as CDTFA learns of them. City boundary data are derived from pre-GIS tax maps, digitized at BOE and CDTFA, with adjustments made directly in GIS for new annexations, detachments, and corrections.Boundary accuracy within the dataset varies. While CDTFA strives to correctly include or exclude parcels from jurisdictions for accurate tax assessment, this dataset does not guarantee that a parcel is placed in the correct jurisdiction. When a parcel is in the correct jurisdiction, this dataset cannot guarantee accurate placement of boundary lines within or between parcels or rights of way. This dataset also provides no information on parcel boundaries. For exact jurisdictional or parcel boundary locations, please consult the county assessor's office and a licensed surveyor. CDTFA's data is used as the best available source because BOE and CDTFA receive information about changes in jurisdictions which otherwise need to be collected independently by an agency or company to compile into usable map boundaries. CDTFA maintains the best available statewide boundary information. CDTFA's source data notes the following about accuracy: City boundary changes and county boundary line adjustments filed with the Board of Equalization per Government Code 54900. This GIS layer contains the boundaries of the unincorporated county and incorporated cities within the state of California. The initial dataset was created in March of 2015 and was based on the State Board of Equalization tax rate area boundaries. As of April 1, 2024, the maintenance of this dataset is provided by the California Department of Tax and Fee Administration for the purpose of determining sales and use tax rates. The boundaries are continuously being revised to align with aerial imagery when areas of conflict are discovered between the original boundary provided by the California State Board of Equalization and the boundary made publicly available by local, state, and federal government. Some differences may occur between actual recorded boundaries and the boundaries used for sales and use tax purposes. The boundaries in this map are representations of taxing jurisdictions for the purpose of determining sales and use tax rates and should not be used to determine precise city or county boundary line locations. Boundary ProcessingThese data make a structural change from the source data. While the full boundaries provided by CDTFA include coastal buffers of varying sizes, many users need boundaries to end at the shoreline of the ocean or a bay. As a result, after examining existing city and county boundary layers, these datasets provide a coastline cut generally along the ocean facing coastline. For county boundaries in northern California, the cut runs near the Golden Gate Bridge, while for cities, we cut along the bay shoreline and into the edge of the Delta at the boundaries of Solano, Contra Costa, and Sacramento counties. In the services linked above, the versions that include the coastal buffers contain them as a second (or third) polygon for the city or county, with the value in the COASTAL field set to whether it"s a bay or ocean polygon. These can be processed back into a single polygon by dissolving on all the fields you wish to keep, since the attributes, other than the COASTAL field and geometry attributes (like areas) remain the same between the polygons for this purpose. SliversIn cases where a city or county"s boundary ends near a coastline, our coastline data may cross back and forth many times while roughly paralleling the jurisdiction"s boundary, resulting in many polygon slivers. We post-process the data to remove these slivers using a city/county boundary priority algorithm. That is, when the data run parallel to each other, we discard the coastline cut and keep the CDTFA-provided boundary, even if it extends into the ocean a small amount. This processing supports consistent boundaries for Fort Bragg, Point Arena, San Francisco, Pacifica, Half Moon Bay, and Capitola, in addition to others. More information on this algorithm will be provided soon. Coastline CaveatsSome cities have buffers extending into water bodies that we do not cut at the shoreline. These include South Lake Tahoe and Folsom, which extend into neighboring lakes, and San Diego and surrounding cities that extend into San Diego Bay, which our shoreline encloses. If you have feedback on the exclusion of these
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TwitterSan Diego, CA is popular among tourists for its beautiful sceneries, including beaches and state parks. This map will help you plan your trip to San Diego better with displaying beaches, some of its famous tourist attractions, and transportation routes. You will be able to interactively explore tourist attraction spots in San Diego and see what transportation you can use to get there.Layers: Tourist Attractions created by me using locations found in a Google Maps SearchSan Diego Swimming Beaches obtained from the dataset "Access points" from California State Geoportal and downloaded as a shapefile, and modified in ArcMap (Add from Web)Public Transportation dataset obtained from San Diego Open GIS Data Portal using the webservice at https://gissd.sandag.org/rdw/rest/services/Transportation/GTFS_Transit/MapServer/1 (Add from File)Pop-ups: Each layer described above has a pop-up descriptions. The Tourist Attractions layer contains a short summary of the attraction and a picture, San Diego Swimming Beaches contains name, location, and parking, restroom, lifeguard, and showers availability, and Public Transportation shows the route name and type.Bookmarks: There are three bookmarks - San Diego, Downtown San Diego, and Northern San Diego. The San Diego bookmark is the default showing the entire San Diego area. On the other hand, Downtown San Diego shows the majority of tourist attractions which are located in downtown and Northern San Diego shows Torrey Pine State Reserve, located in the northern part of the city.