A collection of maps of San Diego County MPAs to target various audiences for improving understanding of the location, purpose and management of California’s marine protected areas.

This 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.

The Vegetation Map of Cañada de San Vicente (CSV), San Diego County, was created by the California Department of Fish and Game (DFG) Vegetation and Mapping Program (VegCAMP). CSV, formerly known as Monte Vista Ranch, was acquired in April 2009 by DFG and is currently not open to the public as the management plan is not complete. The map study area boundary is based on the DFG Lands layer that was published in April, 2011 and includes 4888 acres of land. This includes 115 acres of private land located in the northeast corner of the map that was considered an area of interest (AOI) before purchase by DFG. The map is based on field data from 38 vegetation Rapid Assessment surveys (RAs), 111 reconnaissance points, and 118 verification points that were conducted between April 2009 and January 2012. The rapid assessment surveys were collected as part of a comprehensive effort to create the Vegetation Classification Manual for Western San Diego County (Sproul et al., 2011). A total of 1265 RAs and 18 relevés were conducted for this larger project, all of which were analyzed together using cluster analysis to develop the final vegetation classification. The CSV area was delineated by vegetation type and each polygon contains attributes for hardwood tree, shrub and herb cover, roadedness, development, clearing, and heterogeneity. Of 545 woodland and shrubland polygons that were delineated, 516 were mapped to the association level and 29 to the alliance level (due to uncertainty in the association). Of 46 herbaceous polygons that were delineated, 36 were mapped to the group or macrogroup level and 8 were mapped to association. Four polygons were mapped as urban or agriculture. The classification and map follow the National Vegetation Classification Standard (NVCS) and Federal Geographic Data Committee (FGDC) standard and State of California Vegetation and Mapping Standards. The minimum mapping area unit (MMU) is one acre, though occasionally, vegetation is mapped below MMU for special types including wetland, riparian, and native herbaceous and when it was possible to delineate smaller stands with a high degree of certainty (e.g., with available field data). In total, about 45 percent of the polygons were supported by field data points and 55 percent were based on photointerpretation.

Map showing the locations and status of all cool zones in San Diego County. This map also includes demographic data from the American Community Survey which shows the percentage of senior citizens by census tract.

Tax rate area boundaries and related data based on changes filed with the Board of Equalization per Government Code 54900 for the specified assessment roll year. The data included in this map is maintained by the California State Board of Equalization and may differ slightly from the data published by other agencies. BOE_TRA layer = tax rate area boundaries and the assigned TRA number for the specified assessment roll year; BOE_Changes layer = boundary changes filed with the Board of Equalization for the specified assessment roll year; Data Table (C##_YYYY) = tax rate area numbers and related districts for the specified assessment roll year

This data set maps the soil-slip susceptibility for several areas in southwestern California. Created using Environmental Systems Research Institute's ARC/INFO software, the data base consists of raster maps containing grid cells coded with soil- slip susceptibility values. In addition, the data set includes the following graphic and text products: (1) postscript graphic plot files containing the soil-slip susceptibility map, topography, cultural data, and a key of the colored map units, and (2) PDF and text files of the Readme (including the metadata file as an appendix) and accompanying text, and a PDF file of the plot files. Intense winter rains commonly generated debris flows in upland areas of southwestern California. These debris flows initiate as small landslides referred to as soil slips. Most of the soil slips mobilize into debris flows that travel down slope at varying speeds and distances. The debris flows can be a serious hazard to people and structures in their paths. The soil-slip susceptibility maps identify those natural slopes most likely to be the sites of soil slips during periods of intense winter rainfall. The maps were largely derived by extrapolation of debris-flow inventory data collected from selected areas of southwestern California. Based on spatial analyses of soil slips, three factors in addition to rainfall, were found to be most important in the origin of soil slips. These factors are geology, slope, and aspect. Geology, by far the most important factor, was derived from existing geologic maps. Slope and aspect data were obtained from 10-meter digital elevation models (DEM). Soil-slip susceptibility maps at a scale of 1:24,000 were derived from combining numerical values for geology, slope, and aspect on a 10-meter cell size for 128 7.5' quadrangles and assembled on 1:100,000-scale topographic maps. The resultant maps of relative soil-slip susceptibility represent the best estimate generated from available debris-flow inventory maps and DEM data.

NO LONGER UPDATED. Data source: County of San Diego, Health and Human Services Agency, Public Health Services, Epidemiology and Immunization Services Branch

This digital map database represents the general distribution of bedrock and surficial geologic units, and related data in the Fonts Point and Seventeen Palms 7.5’ quadrangles, California. The database delineates map units that are identified by general age and lithology following the stratigraphic nomenclature of the U.S. Geological Survey. This investigation delineates the geologic framework of an area of 75 square kilometers (km2) located west of the Salton Sea in southern California. The study area encompasses the south flank of the Santa Rosa Mountains and the eastern part of the Borrego Badlands. In this study area, regionally important stratigraphic and structural elements collectively inform the late Cenozoic geologic evolution of the Anza-Borrego sector of the Salton Trough province. This geodatabase contains all of the map information used to publish the Preliminary Geologic Map of the Southern Santa Rosa Mountains and Borrego Badlands, San Diego County, Southern California Pettinga, J.R., Dudash, S.L., and Cossette, P.M., 2023, Preliminary Geologic Map of the Southern Santa Rosa Mountains and Borrego Badlands, San Diego County, Southern California: U.S. Geological Survey Open-File Report 2023–1076, scale 1:12,000, https://doi.org/10.3133/ofr20231076.

Recreation Sites, Trails, Watersheds, National Visitor Use Monitoring Data, and San Diego County Population Data for the San Diego River Gorge Visitor Use Management Plan Story Map Project - Cleveland National Forest, 2022

CDFW BIOS GIS Dataset, Contact: Eric Zahn, Description: This dataset represents a summary of SDTT data collected from 1996-2006. Any track or sign identified from 15 target animals was recorded. Surveys consisted of transects of approximately one mile in length and 30 feet in width along designated dirt trails and roads throughout open space lands in San Diego County.

Tax rate area boundaries and related data based on changes filed with the Board of Equalization per Government Code 54900 for the specified assessment roll year. The data included in this map is maintained by the California State Board of Equalization and may differ slightly from the data published by other agencies. BOE_TRA layer = tax rate area boundaries and the assigned TRA number for the specified assessment roll year; BOE_Changes layer = boundary changes filed with the Board of Equalization for the specified assessment roll year; Data Table (C##_YYYY) = tax rate area numbers and related districts for the specified assessment roll year

This 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.

This dataset contains data included in 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.

Geographic data used to create maps in the report can be found here: https://data.sandiegocounty.gov/dataset/Equity-Report-Data-Geography/p6uw-qxpv

Filter by the Indicator column to select data for a particular indicator.

User notes: 10/9/25 - for the report year 2025, data for the following indicators were uploaded with changes relative to report year 2023: Crime Rate: As of January 1, 2021, the FBI replaced the Summary Reporting System (SRS) with the National Incident Based Reporting System (NIBRS), which expands how crimes were recorded and classified. This report uses California’s version of NIBRS, the California Incident Based Reporting System (CIBRS), obtained from the SANDAG Open Data Portal. Crime rates are not disaggregated by jurisdiction, as in the previous Equity Indicator Report. Internet access: The age group variable was incorporated to account for notable disparities in internet access by age. Police Stops and Searches: refined methods. Agency data was aggregated to San Diego County because data was available for all agencies; previously data was available for three agencies. Analysis of RIPA data was updated to exclude stops where the stop was made in response to a call for service, combine transgender women and transgender men into a transgender category, and limit to contraband found during search. Used term “discovery rate” instead of “hit rate.” Removed comparison to traffic collision data and instead compared to population estimates from the American Community Survey. Jail Incarceration: new data sources. The numerator data for the average daily population data in jail was obtained from the San Diego County Sheriff's Office. Population data to calculate the rates was obtained from the San Diego Association of Governments (SANDAG). The terms for conviction status were corrected to "locally sentenced" and "unsentenced" for sentencing status. For jail population data, East African was reclassified as Black and Middle Eastern as White to allow for calculation of rates using SANDAG population estimates.

8/1/25 - for the report year 2025, the following change were made: Business Ownership: the minority and nonminority labels were switched for the population estimates and some of the race/ethnicity data for nonemployer businesses were corrected. Homelessness: added asterisks to category name for unincorporated regions to allow for a footnote in the figure in the story page.

7/11/25 - for the report year 2025, the following changes were made: Beach Water Quality: the number of days with advisories was corrected for Imperial Beach municipal beach, San Diego Bay, and Ocean Beach.

5/22/25 - for the report year 2023, the following changes were made: Youth poverty/Poverty: IPUMS identified an error in the POVERTY variable for multi-year ACS samples. In July 2024, they released a revised version of all multi-year ACS samples to IPUMS USA, which included corrected POVERTY values. The corrected POVERTY values were downloaded, and the analysis was rerun for this indicator using the 2021 ACS 5-year Estimates. Youth Poverty: data source label corrected to be 2021 for all years. Employment, Homeownership, and Cost-Burdened Households - Notes were made consistent for rows where category = Race/Ethnicity.

5/9/25 - Excluding data for the crime section indicators, data were appended on May 9, 2025 and the report will be updated to reflect the new data in August 2025. The following changes in methods were made: For indicators based on American Community Survey (ACS) data, the foreign-born category name was changed to Nativity Status. Internet access: Group quarters is a category included in the survey sample, but it is not part of the universe for the analysis. For the 2025 Equity Report year, respondents in group quarters were excluded from the analysis, whereas for the 2023 Equity Report year, these respondents were included. Adverse childhood experiences - new data source.

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).

Tax rate area boundaries and related data based on changes filed with the Board of Equalization per Government Code 54900 for the specified assessment roll year. The data included in this map is maintained by the California State Board of Equalization and may differ slightly from the data published by other agencies. BOE_TRA layer = tax rate area boundaries and the assigned TRA number for the specified assessment roll year; BOE_Changes layer = boundary changes filed with the Board of Equalization for the specified assessment roll year; Data Table (C##_YYYY) = tax rate area numbers and related districts for the specified assessment roll year

This map shows meth purchasing patterns across San Diego County in 2023.

San Diego County, CA has a B wealth grade. Median household income: $102,322. Unemployment rate: 5.9%. Income grows 6.2% yearly.

Tax rate area boundaries and related data based on changes filed with the Board of Equalization per Government Code 54900 for the specified assessment roll year. The data included in this map is maintained by the California State Board of Equalization and may differ slightly from the data published by other agencies. BOE_TRA layer = tax rate area boundaries and the assigned TRA number for the specified assessment roll year; BOE_Changes layer = boundary changes filed with the Board of Equalization for the specified assessment roll year; Data Table (C##_YYYY) = tax rate area numbers and related districts for the specified assessment roll year

Geologic map of the Bonsall 7.5-minute quadrangle, San Diego County, California. Online geologic map PDF. scale 1:24000

The San Diego Coast District, Department of Natural Resources, and California State Parks created a fine-scale vegetation map of portions of the Los Penasquitos Lagoon. San Diego Coast District, Department of Natural Resources, and California State Parks conducted field reconnaissance assistance for this project, as well as accuracy assessment (AA) field data collection. CDFW’s Vegetation Classification and Mapping Program (VegCAMP) provided in-kind service to allocate and score the AA. The mapping study area consists of approximately 1204.82 acres of San Diego county. Prior to performing field work, preliminary polygons were delineated on a 2013 true color aerial image with 6 inch pixel resolution. The majority of polygons were later surveyed in the field and redrawn as needed to accurately reflect the boundaries of each vegetation type. Field data was collected from mid 2013 to early 2015. The primary purpose of the project was to further CDFW’s goal of developing fine-scale digital vegetation maps as part of the California Biodiversity Initiative Roadmap of 2018. Mapped vegetation was classified according to the Vegetation Manual for Western San Diego County (AECOM 2011) codes. Holland (sensu Oberbauer 2008) classes were derived via the crosswalk recommended in the Vegetation Manual for Western San Diego County (AECOM 2011). CNPS under separate contract and in collaboration with CDFW VegCAMP developed the floristic vegetation classification used for the project. The floristic classification follows protocols compliant with the Federal Geographic Data Committee (FGDC) and National Vegetation Classification Standards (NVCS). The vegetation map was produced applying heads-up digitizing techniques using LIDAR vegetation elevation data, false color infrared, and other aerial imagery. Map polygons are assessed for Vegetation Type, Percent Cover, Exotics, Development Disturbance, and other attributes. The minimum mapping unit (MMU) is 0.1 hectares. Mappers retained salt panne, mudflat, and water polygons that were below the MMU due to the importance of these habitats. In addition, polygons that were enclosed by these habitat types (such as islands of Salicornia pacifica surrounded by water) were allowed as exceptions to the MMU rule, as were polygons on the perimeter of the mapped area. Polygons initially mapped as salt panne, mudflat, or water that were later changed to a different category based on examination in the field were also allowed as exceptions to the MMU rule. Field reconnaissance and accuracy assessment enhanced map quality. The accuracy assessment was performed in the autumn of 2016. A total of 61 plots from 20 categories were evaluated. The final map accuracy was 56% using a traditional error matrix. There was a total of 42 mapping classes. The overall Fuzzy Accuracy Assessment rating for the final vegetation map, at the association levels, is 89% percent.