Shapefile contains county boundaries for the five counties that are included in the Bay Area Regional Climate Action Planning Initiative Frontline Communities Map.

The original shapefile was downloaded from the California Air Resources Board, Geographical Information System (GIS) Library. The “Select Layer By Attribute” tool in ArcMap was used to select only those five counties that are part of the Bay Area Regional Climate Action Planning Initiative. No display filters were used to visualize the features in the final map. To learn more about the methodology behind the original dataset, please visit: https://ww2.arb.ca.gov/geographical-information-system-gis-library

The Frontline Communities Map is meant to help identify communities that are considered frontline communities for the purpose of the USEPA’s Climate Pollution Reduction Grant (CPRG) program’s planning effort, which is a five-county climate action planning process led by the Air District. USEPA refers to these communities as low-income and disadvantaged communities (LIDACs).

Summary Geographic boundaries for the bay area counties

WARNING: 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.

County boundaries for the San Francisco Bay Region, clipped to remove major coastal and bay water areas. Features were extracted from, and clipped using, California 2020 TIGER/Line shapefiles by the Metropolitan Transportation Commission. The 2020 TIGER/Line Shapefiles reflect available governmental unit boundaries of the counties and equivalent entities as of May 28, 2021.Counties and equivalent entities are primary legal divisions of states. In most states, these entities are termed “counties.” Each county or statistically equivalent entity is assigned a 3-character FIPS code that is unique within a state.

Shapefile contains census tracts identified as disadvantaged in the Climate and Economic Justice Screening Tool (CEJST) for the five counties that are included in the Bay Area Regional Climate Action Planning Initiative Frontline Communities Map.

The original shapefile was downloaded from the The White House Council on Environmental Quality, Climate and Economic Justice Screening Tool (CEJST), Methodology & Data webpage.. The “Clip” tool in ArcMap was used to select only those features which are located within the boundaries of the five Bay Area counties included in the Frontline Communities Map. Only those census tracts where SN_C column is equal to 1 are displayed. Where, SN_C is defined as "Identified as disadvantaged" in the original codebook and 1 is equivalent to a true statement. To learn more about the methodology behind the original dataset, please visit: https://screeningtool.geoplatform.gov/en/methodology#3/33.47/-97.5

The Frontline Communities Map is meant to help identify communities that are considered frontline communities for the purpose of the USEPA’s Climate Pollution Reduction Grant (CPRG) program’s planning effort, which is a five-county climate action planning process led by the Air District. USEPA refers to these communities as low-income and disadvantaged communities (LIDACs).

As outlined in Executive Order 14008 on Tackling the Climate Crisis at Home and Abroad, the Climate and Economic Justice Screening Tool (CEJST) is a geospatial mapping tool designed to identify disadvantaged communities that are marginalized and overburdened by pollution and underinvestment, for the purposes of Justice40 Initiative.

Shapefile contains census tracts identified as Equity Priority Communities by MTC as part of the Plan Bay Area 2050 process for the five counties that are included in the Bay Area Regional Climate Action Planning Initiative Frontline Communities Map.

The original shapefile was downloaded from the Metropolitan Transportation Commission (MTC), Equity Priority Communities webpage. The “Clip” tool in ArcMap was used to select only those features which are located within the boundaries of the five Bay Area counties included in the Frontline Communities Map. Only those census tracts where epc_2050 column is equal to 1 are displayed. Where, epc_2050 is defined as "Equity Priority Community PBA 2050" in the original codebook and 1 is equivalent to a true statement. To learn more about the methodology behind the original dataset, please visit: https://opendata.mtc.ca.gov/datasets/MTC::equity-priority-communities-plan-bay-area-2050/about

The Frontline Communities Map is meant to help identify communities that are considered frontline communities for the purpose of the USEPA’s Climate Pollution Reduction Grant (CPRG) program’s planning effort, which is a five-county climate action planning process led by the Air District. USEPA refers to these communities as low-income and disadvantaged communities (LIDACs).

Formerly called “Communities of Concern,” Equity Priority Communities are census tracts that have a significant concentration of underserved populations. The Equity Priority Communities framework helps MTC make decisions on investments that meaningfully reverse the disparities in access to transportation, housing and other community services.

The Equity Priority Communities (tract geography) dataset is based upon eight demographic variables: • People of Color (70% threshold) • Low-Income (28% threshold) • Limited English Proficiency (12% threshold) • Seniors 75 Years and Over (8% threshold) • Zero-Vehicle Households (15% threshold) • Single Parent Families (18% threshold) • People with a Disability (12% threshold) • Rent-Burdened Households (14% threshold)

A tract is considered an Equity Priority Community: 1. If a tract exceeds both threshold values for BOTH Low-Income AND People of Color, or 2. If a tract exceeds the threshold value for Low-Income AND exceeds the threshold values for three or more of the six remaining variables

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

WARNING: 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 March 2025. 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 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 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 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 layer removes the coastal buffer 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 BuffersWithout Coastal Buffers (this dataset)Cities 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)Working with Coastal BuffersThe dataset you are currently viewing excludes 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, odsdataservices@state.ca.govField 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

This digital map database provides an areally continuous representation of the Quaternary surficial deposits of the San Francisco Bay region merged from the database files from Knudsen and others (2000) and Witter and others (2006). The more detailed mapping by Witter and others (2006) of the inner part of the region (compiled at a scale of 1:24,000), is given precedence over the less detailed mapping by Knudsen and others (2000) of the outer part of the area (compiled at a scale of 1:100,000). The Quaternary map database is accompanied by a list of the map-unit names represented by polygon identities, a digital map index of the 1:24,000-scale topographic quadrangles of the region, and a figure illustrating the contents of the database. The Quaternary map database includes line work and the identity of the Quaternary map units, but no further description of the map units or how they were mapped. Use of the database should thus be accompanied by consultation with the original reports, which describe the map units and mapping procedures: citation of this database should be accompanied by citation of those original reports. As with all such digital maps, use of this database should attend to the compilation scales involved and not try to extract spatial detail or accuracy beyond those limits. Database layers: SFBQuat-lns: Quaternary map database: unit boundaries and their attributes SFBQuat-pys: Quaternary map database: polygons and their attributes SFBIndex-lns: Boundaries of 7.5-minute quadrangles for the map area, distinguishing those that form boundaries of 15-minute and 30x60-minute quadrangles SFBIndex-pys: 7.5-minute quadrangles, and for those within map area, their names and the names of the 30x60-minute quadrangles that contain them. The liquefaction ratings presented in the original reports for the various Quaternary map units remain valid and can be assigned to the units in this database if desired, with ratings of Witter and others (2006) given precedence. Assembly of the Quaternary map database involved stripping out all the information from the source maps that dealt with liquefaction, a major component of the original reports, and adjusting line work at the common boundary between the two source maps to produce a nearly seamless spatial database. The common boundary between the two sources is retained. Mismatches remaining at that common boundary are of two types: (1) contrasts in the degree of subdivision of the deposits resulting from the different compilation scales, and (2) terminations of narrow bands of water and artificial fill and levees at quadrangle boundaries that resulted from differences in details shown on the 1:24,000-scale topographic maps used as a source of mapping information in the original reports. The illustrative figure accompanying the database shows the content of the database plotted at a scale of 1:275,000, with the different map units distinguished by color and the different types of lines distinguished by symbol and color. An index map in that figure shows the 165 7½-minute quadrangles covering the region and the areas of the two source maps. Knudsen, K.L., Sowers, J.M., Witter, R.C., Wentworth, C.M., Helley, E.J., Nicholson, R.S., Wright, H.M., and Brown, K.M., 2000, Preliminary maps of Quaternary deposits and liquefaction susceptibility, nine-county San Francisco Bay region, California: a digital database: U.S. Geological Survey Open File Report 00-444. http://pubs.usgs.gov/of/2000/of00-444/ Witter, R.C., Knudsen, K.L, Sowers, J.M., Wentworth, C.M., Koehler, R.D., Randolph, C. E., Brooks, S.K., and Gans, K.D., 2006, Maps of Quaternary Deposits and Liquefaction Susceptibility in the Central San Francisco Bay Region, California: U.S. Geological Survey Open-File Report 06-1037 (http://pubs.usgs.gov/of/2006/1037)

The San Francisco Bay Region Jurisdictions feature set was developed by the Metropolitan Transportation Commission so tables containing values for both incorporated and unincorporated areas could be joined to a spatial feature set for mapping and analysis. County-level, 2020 TIGER/Line shapefiles, current as of May 28, 2021, were used to develop this feature set. Incorporated places (cities and towns) were erased from the county shapefile for the region. The remaining county areas (unincorporated lands) were then added to the incorporated places to produce a full, incorporated-unincorporated feature set for the region. For the final processing step, major water features were clipped from the jurisdiction feature set so only land areas remained.

This digital map database, compiled from previously published and unpublished data, and new mapping by the authors, represents the general distribution of bedrock and surficial deposits in the mapped area. Together with the accompanying text file (nesfmf.ps, nesfmf.pdf, nesfmf.txt), it provides current information on the geologic structure and stratigraphy of the area covered. The database delineates map units that are identified by general age and lithology following the stratigraphic nomenclature of the U.S. Geological Survey. The scale of the source maps limits the spatial resolution (scale) of the database to 1:62,500 or smaller.

In 1984, the General Assembly enacted the Chesapeake Bay Critical Area Act to regulate development, manage land use and conserve natural resources on land in those areas designated as Critical Area. For this document, the Critical Area is all land and water areas within 1,000 feet of the tidal waters' edge or from the landward edge of adjacent tidal wetlands and the lands under them. Georeferenced digital data files of the critical Area have been produced for Baltimore City and the 16 Maryland counties with land located within the Critical Area. The digital maps produced for each jurisdiction are polygons depicting the Critical Area and the land use classifications recognized by the Chesapeake Bay Critical Area Commission (CBCAC). Each jurisdiction is a separate file. The data were produced from hard copy parcel maps originally submitted by the counties as part of the requirements for developing their Critical Area Program. For the purpose of the Mdimap web service the Critical Area Data is displayed by two data layers, one general layer and one layer showing the available critical area data for local towns.This data set represents the Department of Natural Resources interpretation of the location and extent of the Critical Area; however, the digital maps are not recognized as the "official" maps. In accordance with Subsection 8-1807(a) of the Critical Area Act, the Critical Area consists of (1) All waters and lands under the Chesapeake Bay and its tributaries to the head of tide as indicated on the State wetland maps, and all State and private wetlands designated under Environment Article, Title 16, annotated Code of Maryland; (2) All land and water areas within 1,000 feet beyond the landward boundaries of State or private wetlands and the of tides designated under Environment Article, Article 16, Annotated Code of Maryland; and (3) Modification to these areas through inclusions or exclusions proposed by local jurisdictions and approved by Commission as specified in Natural Resources Article, Subsection 8-1807, annotated Code of Maryland. These maps are hard copy maps that cannot be exactly replicated in a digital format; therefore, some interpretation was necessary to create the digital line. Hard copy maps depicting the official Critical Area boundary line are available for review at the Chesapeake Bay Critical Area Commission, and at most local planning and zoning departments. The Department of Natural Resources makes no warranty, expressed or implied, as to the use or appropriateness of Spatial Data, and there are no warranties of merchantability or fitness for a particular purpose or use. The intended use is for general information and planning purposes. It is not intended to be used to determine the exact location of the Critical Area boundary on a specific parcel or to determine the acreage within the Critical Area on a specific site. The information contained in Spatial Data is from publicly available sources, but no representation is made as to the accuracy or completeness of Spatial Data. The Department of Natural Resources shall not be subject to liability for human error, error due to software conversion, defect, or failure of machines, or any material used in the connection with the machines, including tapes, disks, CD-ROMs or DVD-ROMs and energy. The Department of Natural Resources shall not be liable for any lost profits, consequential damages, or claims against the Department of Natural Resources by third parties. The liability of the Department of Natural Resources for damage regardless of the form of the action shall not exceed any distribution fees that may have been paid in obtaining Spatial Data.There were many parties involved in producing Maryland's Critical Area data and the key parties will be listed. Each county and city (listed below) produced a hard copy map and submitted the map to the Chesapeake Bay Critical Area Commission (CBCAC) for approval. Through Coastal Zone Management grants, CBCAC digit

This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data.

Contra Costa County is located at the northern end of the Diablo Range of Central California. It is bounded on the north by Carquinez Strait, through which flows 27 percent of California's surface water runoff. San Francisco Bay forms the western boundary, the San Joaquin Valley borders it on the east and the Livermore Valley forms the southern boundary. Contra Costa is one of the nine Bay Area counties with streams that are tributaries to San Francisco Bay. Most of the county is mountainous with steep rugged topography. Mount Diablo, in the center of the county, is one of the highest peaks in the Bay Area, reaching an elevation of 1173 meters (3,849 ft). Contra Costa County is covered by twenty-five 7.5' topographic Quadrangles shown on the index map (ccq_quad or Sheet 2). However, two of the quadrangles (Hayward and Petaluma Point) contain no Quaternary deposits in Contra Costa County, and so are not discussed herein. The Quaternary deposits in Contra Costa County comprise two distinct depositional environments. One, forming a transgressive sequence of alluvial fan and fan-delta deposits, is mapped in the western four-fifths of the county. The second, forming a combination of eolian dune and river delta deposits, is mapped in the San Joaquin Valley in the eastern part of the county.

This raster dataset depicts a final version of the Coarse Filter Vegetation Map as a 30 meter grid with 61 cover types, 51 of which are natural or semi-natural land cover, for the nine county San Francisco Bay Area Region, California. See Resource Details for detailed data compilation description. This data was compiled from data sourced from the United States Department of Agriculture Forest Service, The Nature Conservancy and the California Department of Forestry and Fire.

This layer includes 9 annotation features for the county labels for the San Francisco Bay Water Quality Improvment Fund (SFBWQIF) area of interest These features are incorporated in the San Francisco Bay Water Quality Improvement Fund Story Map, an interactive series of maps and QlikSense graphics highlighting the competitive grant program which supports projects to protect and restore San Francisco Bay. The application can be found on the EPA GeoPlatform at: "https://epa.maps.arcgis.com/apps/MapSeries/index.html?appid=db223d22741140b9b10baf7e91815271" "https://epa.maps.arcgis.com/apps/MapSeries/index.html?appid=db223d22741140b9b10baf7e91815271" The story map is also embedded in the following EPA web page: "https://www2.epa.gov/sfbay-delta/sf-bay-water-quality-improvement-fund-interactive-project-map" https://www2.epa.gov/sfbay-delta/sf-bay-water-quality-improvement-fund-interactive-project-map

Summary

Geojson files used to visualize geospatial layers relevant to identifying and assessing trucking fleet decarbonization opportunities with the MIT Climate & Sustainability Consortium's Geospatial Trucking Industry Decarbonization Explorer (Geo-TIDE) tool.

Relevant Links

Link to the online version of the tool (requires creation of a free user account).

Link to GitHub repo with source code to produce this dataset and deploy the Geo-TIDE tool locally.

Funding

This dataset was produced with support from the MIT Climate & Sustainability Consortium.

Original Data Sources

These geojson files draw from and synthesize a number of different datasets and tools. The original data sources and tools are described below:

Filename(s) Description of Original Data Source(s) Link(s) to Download Original Data License and Attribution for Original Data Source(s)

faf5_freight_flows/*.geojson

trucking_energy_demand.geojson

highway_assignment_links_*.geojson

infrastructure_pooling_thought_experiment/*.geojson

Regional and highway-level freight flow data obtained from the Freight Analysis Framework Version 5. Shapefiles for FAF5 region boundaries and highway links are obtained from the National Transportation Atlas Database. Emissions attributes are evaluated by incorporating data from the 2002 Vehicle Inventory and Use Survey and the GREET lifecycle emissions tool maintained by Argonne National Lab.

Shapefile for FAF5 Regions

Shapefile for FAF5 Highway Network Links

FAF5 2022 Origin-Destination Freight Flow database

FAF5 2022 Highway Assignment Results

Attribution for Shapefiles: United States Department of Transportation Bureau of Transportation Statistics National Transportation Atlas Database (NTAD). Available at: https://geodata.bts.gov/search?collection=Dataset.

License for Shapefiles: This NTAD dataset is a work of the United States government as defined in 17 U.S.C. § 101 and as such are not protected by any U.S. copyrights. This work is available for unrestricted public use.

Attribution for Origin-Destination Freight Flow database: National Transportation Research Center in the Oak Ridge National Laboratory with funding from the Bureau of Transportation Statistics and the Federal Highway Administration. Freight Analysis Framework Version 5: Origin-Destination Data. Available from: https://faf.ornl.gov/faf5/Default.aspx. Obtained on Aug 5, 2024. In the public domain.

Attribution for the 2022 Vehicle Inventory and Use Survey Data: United States Department of Transportation Bureau of Transportation Statistics. Vehicle Inventory and Use Survey (VIUS) 2002 [supporting datasets]. 2024. https://doi.org/10.21949/1506070

Attribution for the GREET tool (original publication): Argonne National Laboratory Energy Systems Division Center for Transportation Research. GREET Life-cycle Model. 2014. Available from this link.

Attribution for the GREET tool (2022 updates): Wang, Michael, et al. Summary of Expansions and Updates in GREET® 2022. United States. https://doi.org/10.2172/1891644

grid_emission_intensity/*.geojson

Emission intensity data is obtained from the eGRID database maintained by the United States Environmental Protection Agency.

eGRID subregion boundaries are obtained as a shapefile from the eGRID Mapping Files database.

eGRID database

Shapefile with eGRID subregion boundaries

Attribution for eGRID data: United States Environmental Protection Agency: eGRID with 2022 data. Available from https://www.epa.gov/egrid/download-data. In the public domain.

Attribution for shapefile: United States Environmental Protection Agency: eGRID Mapping Files. Available from https://www.epa.gov/egrid/egrid-mapping-files. In the public domain.

US_elec.geojson

US_hy.geojson

US_lng.geojson

US_cng.geojson

US_lpg.geojson

Locations of direct current fast chargers and refueling stations for alternative fuels along U.S. highways. Obtained directly from the Station Data for Alternative Fuel Corridors in the Alternative Fuels Data Center maintained by the United States Department of Energy Office of Energy Efficiency and Renewable Energy.

US_elec.geojson

US_hy.geojson

US_lng.geojson

US_cng.geojson

US_lpg.geojson

Attribution: U.S. Department of Energy, Energy Efficiency and Renewable Energy. Alternative Fueling Station Corridors. 2024. Available from: https://afdc.energy.gov/corridors. In the public domain.

These data and software code ("Data") are provided by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy, LLC ("Alliance"), for the U.S. Department of Energy ("DOE"), and may be used for any purpose whatsoever.

daily_grid_emission_profiles/*.geojson

Hourly emission intensity data obtained from ElectricityMaps.

Original data can be downloaded as csv files from the ElectricityMaps United States of America database

Shapefile with region boundaries used by ElectricityMaps

License: Open Database License (ODbL). Details here: https://www.electricitymaps.com/data-portal

Attribution for csv files: Electricity Maps (2024). United States of America 2022-23 Hourly Carbon Intensity Data (Version January 17, 2024). Electricity Maps Data Portal. https://www.electricitymaps.com/data-portal.

Attribution for shapefile with region boundaries: ElectricityMaps contributors (2024). electricitymaps-contrib (Version v1.155.0) [Computer software]. https://github.com/electricitymaps/electricitymaps-contrib.

gen_cap_2022_state_merged.geojson

trucking_energy_demand.geojson

Grid electricity generation and net summer power capacity data is obtained from the state-level electricity database maintained by the United States Energy Information Administration.

U.S. state boundaries obtained from this United States Department of the Interior U.S. Geological Survey ScienceBase-Catalog.

Annual electricity generation by state

Net summer capacity by state

Shapefile with U.S. state boundaries

Attribution for electricity generation and capacity data: U.S. Energy Information Administration (Aug 2024). Available from: https://www.eia.gov/electricity/data/state/. In the public domain.

electricity_rates_by_state_merged.geojson

Commercial electricity prices are obtained from the Electricity database maintained by the United States Energy Information Administration.

Electricity rate by state

Attribution: U.S. Energy Information Administration (Aug 2024). Available from: https://www.eia.gov/electricity/data.php. In the public domain.

demand_charges_merged.geojson

demand_charges_by_state.geojson

Maximum historical demand charges for each state and zip code are derived from a dataset compiled by the National Renewable Energy Laboratory in this this Data Catalog.

Historical demand charge dataset

The original dataset is compiled by the National Renewable Energy Laboratory (NREL), the U.S. Department of Energy (DOE), and the Alliance for Sustainable Energy, LLC ('Alliance').

Attribution: McLaren, Joyce, Pieter Gagnon, Daniel Zimny-Schmitt, Michael DeMinco, and Eric Wilson. 2017. 'Maximum demand charge rates for commercial and industrial electricity tariffs in the United States.' NREL Data Catalog. Golden, CO: National Renewable Energy Laboratory. Last updated: July 24, 2024. DOI: 10.7799/1392982.

eastcoast.geojson

midwest.geojson

la_i710.geojson

h2la.geojson

bayarea.geojson

saltlake.geojson

northeast.geojson

Highway corridors and regions targeted for heavy duty vehicle infrastructure projects are derived from a public announcement on February 15, 2023 by the United States Department of Energy.

The shapefile with Bay area boundaries is obtained from this Berkeley Library dataset.

The shapefile with Utah county boundaries is obtained from this dataset from the Utah Geospatial Resource Center.

Shapefile for Bay Area country boundaries

Shapefile for counties in Utah

Attribution for public announcement: United States Department of Energy. Biden-Harris Administration Announces Funding for Zero-Emission Medium- and Heavy-Duty Vehicle Corridors, Expansion of EV Charging in Underserved Communities (2023). Available from https://www.energy.gov/articles/biden-harris-administration-announces-funding-zero-emission-medium-and-heavy-duty-vehicle.

Attribution for Bay area boundaries: San Francisco (Calif.). Department Of Telecommunications and Information Services. Bay Area Counties. 2006. In the public domain.

Attribution for Utah boundaries: Utah Geospatial Resource Center & Lieutenant Governor's Office. Utah County Boundaries (2023). Available from https://gis.utah.gov/products/sgid/boundaries/county/.

License for Utah boundaries: Creative Commons 4.0 International License.

incentives_and_regulations/*.geojson

State-level incentives and regulations targeting heavy duty vehicles are collected from the State Laws and Incentives database maintained by the United States Department of Energy's Alternative Fuels Data Center.

Data was collected manually from the State Laws and Incentives database.

Attribution: U.S. Department of Energy, Energy Efficiency and Renewable Energy, Alternative Fuels Data Center. State Laws and Incentives. Accessed on Aug 5, 2024 from: https://afdc.energy.gov/laws/state. In the public domain.

These data and software code ("Data") are provided by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy, LLC ("Alliance"), for the U.S. Department of Energy ("DOE"), and may be used for any purpose whatsoever.

costs_and_emissions/*.geojson

diesel_price_by_state.geojson

trucking_energy_demand.geojson

Lifecycle costs and emissions of electric and diesel trucking are evaluated by adapting the model developed by Moreno Sader et al., and calibrated to the Run on Less dataset for the Tesla Semi collected from the 2023 PepsiCo Semi pilot by the North American Council for Freight Efficiency.

In

The East Bay Regional Park District (EBRPD) initiated this project to map the topography, physical and biotic features, and diverse plant communities of the east bay region. This project was funded by the California Department of Forestry and Fire Protection (CAL FIRE), the California State Coastal Conservancy (SCC), and California Department of Fish and Wildlife (CDFW) grants. The mapping study area, consists of approximately 987,000 acres of Alameda and Contra Costa counties. This 115-class fine scale vegetation map was completed in May 2025 and contains 140,442 polygons. The map is based on summer 2020 National Aerial Imagery Program (NAIP) imagery. The map additionally contains lidar-derived information about stand height, canopy cover, and percentage of impervious cover as well as canopy mortality data for each polygon. The minimum mapping unit (MMU) for this project ranges from 1/5 to 1 acre depending on feature type, and is described in detail in the mapping report (Tukman Geospatial, 2025). Development of the Alameda and Contra Costa fine scale vegetation map was managed by EBRPD and staffed by personnel from Tukman Geospatial. Field surveys were completed by trained botanists from the California Native Plant Society (CNPS), who were assisted by botanists from Nomad Ecology Consulting. Data from these surveys, combined with older surveys from previous efforts, were analyzed by the CNPS Vegetation Program, with support from the CDFW Vegetation Classification and Mapping Program (VegCAMP) to develop a county-specific vegetation classification. The floristic classification follows protocols compliant with the Federal Geographic Data Committee (FGDC) and National Vegetation Classification Standards (NVCS). For more information on the field sampling and vegetation classification work, refer to the final report issued by CNPS and corresponding floristic descriptions (Sikes et al., 2025), which are bundled with the vegetation map published for BIOS here: https://filelib.wildlife.ca.gov/Public/BDB/GIS/BIOS/Public_Datasets/3200_3299/ds3206.zipThe foundation for this vegetation map is an enhanced lifeform map produced in 2023 with funding from CAL FIRE. This lifeform map was developed using fine scale segmentation in Trimble® Ecognition® with machine learning and further manual image interpretation. In 2023-2025, Tukman Geospatial and Nomad Ecology staff conducted countywide reconnaissance field work. Field-collected data was used to train automated machine learning algorithms, which produced a semi-automated countywide fine scale vegetation and habitat map. Throughout 2024 and 2025, Tukman Geospatial manually edited the fine scale maps, and Tukman Geospatial and Nomad Ecology went to the field for validation trips to inform and improve the manual editing process. In 2025, input from Alameda and Contra Costa counties’ community of land managers and by the funders of the project was used to further refine the map.Accuracy assessment plot data were collected in 2025. Accuracy assessment results were compiled and analyzed May of 2025. The overall accuracy of the vegetation map by lifeform is 97%. The overall accuracy of the vegetation map by fine scale vegetation map class is 80.8%, with an overall ‘fuzzy’ accuracy of 93.1%.For a complete datasheet of the product, click here. Map class definitions, as well as a dichotomous key for the map classes, can be found in the Alameda and Contra Costa Fine Scale Vegetation Map Key (https://vegmap.press/alcc_mapping_key). A key to map class abbreviations is also available (https://vegmap.press/alcc_vegmap_abbrevs).

This polygon shapefile displays Census tracts for the San Francisco Bay Area in California based on entity boundaries established on January 1, 1990. Census tracts are small, relatively permanent statistical subdivisions of a county (or statistical equivalent of a county), and are defined by local participants as part of the U.S. Census Bureau's Participant Statistical Areas Program. The U.S. Census Bureau delineated the census tracts in situations where no local participant existed or where local or tribal governments declined to participate. This layer is part of the Bay Area Metropolitan Transportation Commission (MTC) GIS Maps and Data collection.

This part of DS 781 presents data for faults for the geologic and geomorphic map of the Offshore of Half Moon Bay map area, California. The vector data file is included in "Faults_OffshoreHalfMoonBay.zip," which is accessible from http://pubs.usgs.gov/ds/781/OffshoreHalfMoonBay/data_catalog_OffshoreHalfMoonBay.html. The Offshore of Half Moon Bay map area lies about 12 km southwest of the San Andreas Fault, the dominant structure in the distributed, right-lateral, transform boundary between the North American and Pacific plates. The map area straddles the right-lateral San Gregorio Fault, the most important structure west of the San Andreas Fault in this broad zone. The San Gregorio is part of fault system that occurs predominantly in the offshore, extending about 400 km from Point Conception on the south to Bolinas and Point Reyes on the north (Dickinson and others, 2005), intersecting land at a few coastal promontories. In the Offshore of Half Moon Bay map area, the San Gregorio Fault forms a distributed shear zone about 2 to 4.5 km wide that includes two primary diverging fault strands. The eastern strand (also known as the Seal Cove Fault or Coastways Fault) roughly parallels the shoreline, lies onshore for about 3 km at Pillar Point, and locally forms the boundary between outcrops of Cretaceous grantic rocks to the east and Purisima Formation to the west. The western strand (also known as the Frijoles Fault) lies entirely offshore and forms a boundary between the Purisima Formation on the east and undifferentiated Cretaceous and (or) Tertiary rocks (Pigeon Point Formation?) of the Pigeon Point structural block (McCulloch, 1987) on the west. The Pigeon Point block forms a northwest-trending bedrock ridge that extends offshore for about 30 km from Pescadero Point and forms the northwest boundary of the outer Santa Cruz Basin (McCulloch, 1987). Cumulative lateral slip on the San Gregorio Fault zone is thought to range from 4 to 10 mm/yr in this region (U.S. Geological Survey, 2010). Bathymetric (Bathymetry--Offshore Half Moon Bay, California, DS 781) and seismic-reflection data (see field activity S-15-10-NC) reveal that the offshore outcrops of the Purisima Formation between the eastern and western strands of the San Gregorio Fault Zone are spectacularly folded, faulted and rotated by the strike-slip motion and drag along the faults. The entire map area lies along strike with the young, high topography of the Santa Cruz Mountains and Coast Ranges. This regional uplift has been linked to a northwest transpressive bend in the San Andreas Fault (for example, Zoback and others, 1999). Uplift of nearby marine terraces at rates up to 0.44 mm/yr confirms that this uplift includes the coastal zone (Weber and others, 1995). Faults were primarily mapped by interpretation of seismic reflection profile data (see field activity S-15-10-NC). The seismic reflection profiles were collected between 2007 and 2010. References Cited Dickinson, W.R., Ducea, M., Rosenberg, L.I., Greene, H.G., Graham, S.A., Clark, J.C., Weber, G.E., Kidder, S., Ernst, W.G., and Brabb, E.E., 2005, Net dextral slip, Neogene San Gregorio-Hosgri fault zone, coastal California: Geologic evidence and tectonic implications: Geological Society of America Special Paper 391, 43 p. McCulloch, D.S., 1987, Regional geology and hydrocarbon potential of offshore Central California, in Scholl, D.W., Grantz, A., and Vedder, J.G., eds., Geology and resource potential of the continental margin of Western North America and adjacent ocean basins - Beaufort Sea to Baja California: Circum-Pacific Council for Energy and Mineral Resources Earth Science Series, v. 6, p. 353-401. U.S. Geological Survey and California Geological Survey, 2010, Quaternary fault and fold database for the United States, accessed April 5, 2012, from USGS website: http://earthquake.usgs.gov/hazards/qfaults/. Weber, G.E., Nolan, J.M., and Zinn, E.N., 1995, Determination of late Pleistocene-Holocene slip rates along the San Gregorio fault zone, San Mateo and Santa Cruz counties, California: Final Technical Report, National Earthquake Hazard Reduction Program, Contract No. 1434-93-G-2336, 70 p., 4 map sheets. Zoback, M.L., Jachens, R.C., and Olson, J.A., 1999, Abrupt along-strike change in tectonic style: San Andreas fault zone, San Francisco Peninsula: Journal of Geophysical Research, v. 104 (B5), p. 10,719-10,742.