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, coastal buffers are removed, leaving 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 BuffersWithout Coastal Buffers (this dataset)Place 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.

Reason for SelectionProtected natural areas in urban environments provide urban residents a nearby place to connect with nature and offer refugia for some species. They help foster a conservation ethic by providing opportunities for people to connect with nature, and also support ecosystem services like offsetting heat island effects (Greene and Millward 2017, Simpson 1998), water filtration, stormwater retention, and more (Hoover and Hopton 2019). In addition, parks, greenspace, and greenways can help improve physical and psychological health in communities (Gies 2006). Urban park size complements the equitable access to potential parks indicator by capturing the value of existing parks.Input DataSoutheast Blueprint 2024 extentFWS National Realty Tracts, accessed 12-13-2023Protected Areas Database of the United States(PAD-US):PAD-US 3.0national geodatabase -Combined Proclamation Marine Fee Designation Easement, accessed 12-6-20232020 Census Urban Areas from the Census Bureau’s urban-rural classification; download the data, read more about how urban areas were redefined following the 2020 censusOpenStreetMap data “multipolygons” layer, accessed 12-5-2023A polygon from this dataset is considered a beach if the value in the “natural” tag attribute is “beach”. Data for coastal states (VA, NC, SC, GA, FL, AL, MS, LA, TX) were downloaded in .pbf format and translated to an ESRI shapefile using R code. OpenStreetMap® is open data, licensed under theOpen Data Commons Open Database License (ODbL) by theOpenStreetMap Foundation (OSMF). Additional credit to OSM contributors. Read more onthe OSM copyright page.2021 National Land Cover Database (NLCD): Percentdevelopedimperviousness2023NOAA coastal relief model: volumes 2 (Southeast Atlantic), 3 (Florida and East Gulf of America), 4 (Central Gulf of America), and 5 (Western Gulf of America), accessed 3-27-2024Mapping StepsCreate a seamless vector layer to constrain the extent of the urban park size indicator to inland and nearshore marine areas <10 m in depth. The deep offshore areas of marine parks do not meet the intent of this indicator to capture nearby opportunities for urban residents to connect with nature. Shallow areas are more accessible for recreational activities like snorkeling, which typically has a maximum recommended depth of 12-15 meters. This step mirrors the approach taken in the Caribbean version of this indicator.Merge all coastal relief model rasters (.nc format) together using QGIS “create virtual raster”.Save merged raster to .tif and import into ArcPro.Reclassify the NOAA coastal relief model data to assign areas with an elevation of land to -10 m a value of 1. Assign all other areas (deep marine) a value of 0.Convert the raster produced above to vector using the “RasterToPolygon” tool.Clip to 2024 subregions using “Pairwise Clip” tool.Break apart multipart polygons using “Multipart to single parts” tool.Hand-edit to remove deep marine polygon.Dissolve the resulting data layer.This produces a seamless polygon defining land and shallow marine areas.Clip the Census urban area layer to the bounding box of NoData surrounding the extent of Southeast Blueprint 2024.Clip PAD-US 3.0 to the bounding box of NoData surrounding the extent of Southeast Blueprint 2024.Remove the following areas from PAD-US 3.0, which are outside the scope of this indicator to represent parks:All School Trust Lands in Oklahoma and Mississippi (Loc Des = “School Lands” or “School Trust Lands”). These extensive lands are leased out and are not open to the public.All tribal and military lands (“Des_Tp” = "TRIBL" or “Des_Tp” = "MIL"). Generally, these lands are not intended for public recreational use.All BOEM marine lease blocks (“Own_Name” = "BOEM"). These Outer Continental Shelf lease blocks do not represent actively protected marine parks, but serve as the “legal definition for BOEM offshore boundary coordinates...for leasing and administrative purposes” (BOEM).All lands designated as “proclamation” (“Des_Tp” = "PROC"). These typically represent the approved boundary of public lands, within which land protection is authorized to occur, but not all lands within the proclamation boundary are necessarily currently in a conserved status.Retain only selected attribute fields from PAD-US to get rid of irrelevant attributes.Merged the filtered PAD-US layer produced above with the OSM beaches and FWS National Realty Tracts to produce a combined protected areas dataset.The resulting merged data layer contains overlapping polygons. To remove overlapping polygons, use the Dissolve function.Clip the resulting data layer to the inland and nearshore extent.Process all multipart polygons (e.g., separate parcels within a National Wildlife Refuge) to single parts (referred to in Arc software as an “explode”).Select all polygons that intersect the Census urban extent within 0.5 miles. We chose 0.5 miles to represent a reasonable walking distance based on input and feedback from park access experts. Assuming a moderate intensity walking pace of 3 miles per hour, as defined by the U.S. Department of Health and Human Service’s physical activity guidelines, the 0.5 mi distance also corresponds to the 10-minute walk threshold used in the equitable access to potential parks indicator.Dissolve all the park polygons that were selected in the previous step.Process all multipart polygons to single parts (“explode”) again.Add a unique ID to the selected parks. This value will be used in a later step to join the parks to their buffers.Create a 0.5 mi (805 m) buffer ring around each park using the multiring plugin in QGIS. Ensure that “dissolve buffers” is disabled so that a single 0.5 mi buffer is created for each park.Assess the amount of overlap between the buffered park and the Census urban area using “overlap analysis”. This step is necessary to identify parks that do not intersect the urban area, but which lie within an urban matrix (e.g., Umstead Park in Raleigh, NC and Davidson-Arabia Mountain Nature Preserve in Atlanta, GA). This step creates a table that is joined back to the park polygons using the UniqueID.Remove parks that had ≤10% overlap with the urban areas when buffered. This excludes mostly non-urban parks that do not meet the intent of this indicator to capture parks that provide nearby access for urban residents. Note: The 10% threshold is a judgement call based on testing which known urban parks and urban National Wildlife Refuges are captured at different overlap cutoffs and is intended to be as inclusive as possible.Calculate the GIS acres of each remaining park unit using the Add Geometry Attributes function.Buffer the selected parks by 15 m. Buffering prevents very small and narrow parks from being left out of the indicator when the polygons are converted to raster.Reclassify the parks based on their area into the 7 classes seen in the final indicator values below. These thresholds were informed by park classification guidelines from the National Recreation and Park Association, which classify neighborhood parks as 5-10 acres, community parks as 30-50 acres, and large urban parks as optimally 75+ acres (Mertes and Hall 1995).Assess the impervious surface composition of each park using the NLCD 2021 impervious layer and the Zonal Statistics “MEAN” function. Retain only the mean percent impervious value for each park.Extract only parks with a mean impervious pixel value <80%. This step excludes parks that do not meet the intent of the indicator to capture opportunities to connect with nature and offer refugia for species (e.g., the Superdome in New Orleans, LA, the Astrodome in Houston, TX, and City Plaza in Raleigh, NC).Extract again to the inland and nearshore extent.Export the final vector file to a shapefile and import to ArcGIS Pro.Convert the resulting polygons to raster using the ArcPy Feature to Raster function and the area class field.Assign a value of 0 to all other pixels in the Southeast Blueprint 2024 extent not already identified as an urban park in the mapping steps above. Zero values are intended to help users better understand the extent of this indicator and make it perform better in online tools.Use the land and shallow marine layer and “extract by mask” tool to save the final version of this indicator.Add color and legend to raster attribute table.As a final step, clip to the spatial extent of Southeast Blueprint 2024.Note: For more details on the mapping steps, code used to create this layer is available in theSoutheast Blueprint Data Downloadunder > 6_Code.Final indicator valuesIndicator values are assigned as follows:6= 75+ acre urban park5= 50 to <75 acre urban park4= 30 to <50 acre urban park3= 10 to <30 acre urban park2=5 to <10acreurbanpark1 = <5 acre urban park0 = Not identified as an urban parkKnown IssuesThis indicator does not include park amenities that influence how well the park serves people and should not be the only tool used for parks and recreation planning. Park standards should be determined at a local level to account for various community issues, values, needs, and available resources.This indicator includes some protected areas that are not open to the public and not typically thought of as “parks”, like mitigation lands, private easements, and private golf courses. While we experimented with excluding them using the public access attribute in PAD, due to numerous inaccuracies, this inadvertently removed protected lands that are known to be publicly accessible. As a result, we erred on the side of including the non-publicly accessible lands.The NLCD percent impervious layer contains classification inaccuracies. As a result, this indicator may exclude parks that are mostly natural because they are misclassified as mostly impervious. Conversely, this indicator may include parks that are mostly impervious because they are misclassified as mostly

Unincorporated Urban Growth Areas (UGA) as defined by the Growth Management Act (GMA). The annual update is conducted by collecting UGA polygons directly from each of Washington's 39 counties. As of 2025, there are 27 counties with UGAs.All UGA polygons are normalized against the Department of Revenue's (DOR) "City Boundaries" layer (shared to the Washington Geoportal a.k.a. the GIS Open Data site: geo.wa.gov). The City Boundaries layer was processed into this UGA layer such that any overlapping area of UGA polygons (from authoritative individual counties) was erased. Since DOR polygons and county-sourced UGA polygons do not have perfect topology, many slivers resulted after the erase operation. These are attempted to be irradicated by these processing steps. "Multipart To Singlepart" Esri tool; exploded all polygons to be individualSlivers were mathematically identified using a 4 acre area threshold and a 0.3 "thinness ratio" threshold as described by Esri's "Polygon Sliver" tool. These slivers are merged into the neighboring features using Esri's "Eliminate" tool.Polygons that are less than 5,000 sq. ft. and not part of a DOR city (CITY_NM = Null) were also merged via the "Eliminate" tool. (many very small slivers were manually found yet mathematically did not meet the thinness ratio threshold)The final 8 polygons less than 25 sq. ft. were manually deleted (also slivers but were not lined up against another feature and missed by the "Eliminate" tool runs)Dissolved all features back to multipart using all fieldsAll UGAs polygons remaining are unincorporated areas beyond the city limits. Any polygon with CITY_NM populated originated from the DOR "City Boundaries" layer. The DOR's City Boundaries are updated quarterly by DOR. For the purposes of this UGA layer, the city boundaries was downloaded one time (4/24/2025) and will not be updated quarterly. Therefore, if precise city limits are required by any user of UGA boundaries, please refer to the city boundaries layer and conduct any geoprocessing needed. The DOR's "City Boundaries" layer is available here:https://www.arcgis.com/home/item.html?id=69fcb668dc8d49ea8010b6e33e42a13aData is updated in conjunction with the annual statewide parcel layer update. Latest update completed April 2025.

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.

As described in the Executive Summary below from the Draft 2021-2029 Housing Element, these are the parcels from the 'Rezoning Program' as of 7/26/21. For more information about the Draft Housing Element, please click here.EXECUTIVE SUMMARY (from Draft Housing Element):The County is required to ensure the availability of residential sites, at adequate densities and appropriate development standards, in the unincorporated areas to accommodate its share of the regional housing need--also known as the Regional Housing Needs Allocation (RHNA). The unincorporated areas have been assigned a RHNA of 90,052 units for the 2021-2029 Housing Element planning period, which is subdivided by level of affordability as follows:Very Low Income – 25,648Lower Income – 13,691Moderate Income – 14,180Above Moderate Income – 36,533The Sites Inventory (Appendix A) is comprised of vacant and underutilized sites that are zoned at appropriate densities and development standards to facilitate housing development. Other strategies to accommodate the RHNA include projected number of ADUs, specific plan capacity, selected entitled projects, and capacity or planned development on County-owned sites within cities. The remainder of the RHNA is accommodated by sites to be rezoned to accommodate higher density housing development.MORE DETAILED INFO ON METHODOLOGY: ((PLACEHOLDER for Appendix G from BOS Consent posting))UPDATE HISTORY:1/5/21 - Coded Supervisorial District for each parcel2/4/21 - Added four fields that show the proposed / existing Land Use Policy / Zoning that display the category + brief description + density range - done mainly for the Story Map. Also, renamed the GIS layer (removed 'Adequate_Sites_Inventory' from the name).3/16/21 - Added 'Status Update (2021)' field to flag those parcels for removal following findings from Housing Section and EIR consultant.3/31/21 - Began making edits based on QC done by Housing Section in March, 2021 and exported this layer to an ARCHIVE version so we have the original data if needed. Made the following updates in AltadenaCoded all 'GC' categories as 'N/A' for RHNA Eligible and removed proposed LUP / Zoning category - THESE CAN NO LONGER BE COUNTED IN REZONE.Downgraded Proposed MU to Proposed CG for all current 'MU / Commercial Zones', and updated min/max density. Nulled out proposed zoning categories. Need to re-do unit calculations!4/1/21 - Continuing with Altadena QC, updating Status Update (2021) field:Downgraded Proposed MU to Proposed CG for all current 'MU / Non-Commercial Zones', and updated min/max density. Need Proposed Zoning from HE Section for consistency with CG category. Need to re-do unit calculations!Coded the ones marked 'Zoe to review'4/4/21 - Coded additional parcels that were condos (missed from before). Updated '2021 Update notes' and condo-related fields (including units). In Altadena, re-calculated units for all that are downgraded from Prop LU MU > CG. Identified those not meeting 16 unit minimum, and of those that were RHNA eligible, were coded as 'No'. Noted in the '2021 Update notes'.4/5/21 - Made the following edits per QC results from Housing Section:Lennox / W. Athens - coded '65 dB' parcels as "N/A" (removing from Rezoning list).Altadena - verified that no additional RHNA eligible parcels removed due to the criteria: “Existing residential buildings 50 or more years old, where the number of units allowed under the new LU is at least 2 - 3 times what's on the ground”All areas - coded Density Bonus of 27.5% as identified from the Housing Section as blank4/6/21 - Continued making edits per the QC results from Housing Section from the Rezoning list.4/7/21 - Continued making edits per the QC results from the Housing Section for Altadena.4/10/21 - Double-checked all Rezone edits. Re-calculated all units for all those that were updated (Status Update 2021 IS NOT NULL) and are on Rezoning list (RHNA Eligible? <> 'N/A'). Exported RHNA eligible to spreadsheet and double-checked unit maths.4/12/21 - Updated last proposed zoning categories in Altadena (confirmed by Housing Section). Updated current / proposed zoning descriptions (removed zoning suffices).4/13/21 - Made additional QC updates to some statuses regarding parcels that overlap with ASI.4/14/21 - Updated current zoning for the recently adopted By-Right Housing Ordinance Zone Change (all of these cases have the status of "N/A" - or, not considered for rezoning)4/15/21 - Researched 11 parcels that were coded as 'Yes - Rezoning Program' for RHNA Eligibility AND were flagged as not RHNA eligible for the model runs done previously 'Filter 2b'. Confirmed they should all remain RHNA eligible with the exception of 2.4/27/21 - Updated status for additional sites during week of 4/19, and on 4/27. Updated 107 parcels to the RHNA Eligibility Status of "Yes - Moderate Income"4/28/21 - Updated 310 parcels to the RHNA Eligibility Status of "Yes - Above Moderate Income"5/4/21 - Updated RHNA Eligibility Status to "No" since it overlapped with ASI.5/5/21 - Updated RHNA Eligibility Status to "Yes - Moderate" and "Yes - Above Moderate", and also removed two parcels that were also Historical Sites, per QC requests from Housing Section. SUMMARIZED THIS DATA AS A TABLE TO RESPOND TO SUPERVISORIAL DISTRICT 1.5/11/21 - Updated schema:RHNA Eligible now just 'Yes' or 'No' (Rather than 'Yes + Inc level')Added fields for various income levels - to match what is in ASI layerKept 'Realistic Capacity' for the 'Non RHNA-Eligible' sites (these aren't broken down by Income level)Calculated 'Very Low' and 'Low' income levels to be 50/50 of the 'Realistic Capacity' (rounded up for VL, rounded down for L)5/12/21 - PREP FOR HCD TEMPLATE - Added field for Vacant / Non Vacant uses per the Assessor Use Code (ends in 'V' or 'X')6/2/21 - Updated one parcel that had 'Prop min density' blank. Trimmed Site Address field of trailing spaces.6/10/21 - ARCHIVED - exported to an archived layer as this is a snapshot in time from when it was sent to HCD on 6/7/21.6/28/21 - Exported the features (essentially copied the layer) as there was some strange behavior of attributes not selecting and joins not fully working - suspected that the data was slightly corrupted somehow, however a simple copy seemed to fix the issue. Modified several parcels per QC done by Housing Section in June, added some parcels as well.6/29/21 - Added sites per June QC and updated relevant fields - flagged those that need to have units recalculated in a temporary field.6/30/21 - Updated units for added sites. Flagged several parcels in FF and WALP for removal. RENAMED 'RHNA STATUS' CATEGORIES FROM "N/A" TO "REMOVE" (to be consistent with the ASI)7/1/21 - Removed or otherwise modified several parcels due to overlapping with new bldg permits / entitlements.7/6/21 - Updated based on refinements identified by the Housing Section on 7/1/21: Adding back Central Ave in Florence-Firestone and adding/removing sites in La Crescenta-Montrose, and updating some minor things (not related to units).7/7/21 - Checked math on all unit calculations using formulas in Excel - a small number of them were off by 1 unit (probably due to not rounding), and they were fixed. Added 'Planning Areas' field.7/20/21 - Incorporated changes following additional QC and zoning Inconsistencies identified in South and West Whittier following significant shortfall with the removal of Northlake Specific Plan:Added Income Category field and calculated valuesRemoved one parcel that overlapped with an existing Mobile Home ParkRemoved 1,122 polygons flagged as "REMOVED" that overlapped with the South and West Whittier changes (select by location against "Zoning_Inconsistancy_Parcels_SDs_345" layer.Added parcels for Above Moderate RHNA units from "Zoning_Inconsistancy_Parcels_SDs_345" layer and filled in fields as necessary.Added Adj Cluster IDs for 8 of the newly added parcels (adding to the next highest available ID in the whole dataset)7/24/21 - Coded all empty Site Addresses with nearest Street Intersection. See analysis fields starting with "Street_Intersection" in 'Housing_Element_2021_2029' File GDB.7/25/21 - Added ZIP Codes for those that were blank.7/26/21 - re-worded the metadata description (above UPDATE HISTORY)7/30/21 - 7/31/21 - Added Proposed Florence-Firestone TOD parcels.9/13/21 - Slight update to calculate the 'Income Category' field for those with RHNA Eligible = NO - to make those NULL.11/16/21 - Removed Density Bonus from the bottom 15% of sites (71 sites out of the 468) per HCD's comment. For the sites that fell below the 16 units, they were moved to the Above Moderate income category to receive RHNA credit.12/30/21 - Added updated Supervisorial District ID from 2021 update.2/17/22 - Cleared out Realistic Capacity and all income level units for "RHNA Eligible = NO". This is a clean-up measure. Kept all unit calculations for these up until the 'Realistic Capacity' field.3/15/22 & 3/16/22 - Re-allocation of income-level units per recommendation by HCD. New fields were added to indicate the original income level unit numbers (as submitted to the state following the Board Hearing), and an HCD Comments field was added to flag these parcels that changed, and the transfer of units between the income categories.SLA - move units from VL/L to Mod. Added 2,238 to Mod and subtracted 1,144 from VL, and 1,094 Low Income (lots with sf < 5,950). Checked if there were any project-specific allocations to income levels and there were none.SLA - move units from L to AM. Remaining Low Income after Step 1 is 5,819, so take approximately half of that. Selecting from pool outside of those selected in STEP 1, and lot size < 10,000sf, moved 2,566 from Low Income to Above Moderate. Checked if there were any project-specific allocations to income levels and there were none. OTHER SUBMARKET - move units from L to AM. Moved 10,031 units from L to AM (lots < 90,000 sf). NOTE, that this was most of

Initial Data Capture: Building were originally digitized using ESRI construction tools such as rectangle and polygon. Textron Feature Analyst was then used to digitize buildings using a semi-automated polygon capture tool as well as a fully automated supervised learning method. The method that proved to be most effective was the semi-automated polygon capture tool as the fully automated process produced polygons that required extensive cleanup. This tool increased the speed and accuracy of digitizing by 40%.Purpose of Data Created: To supplement our GIS viewers with a searchable feature class of structures within Ventura County that can aid in analysis for multiple agencies and the public at large.Types of Data Used: Aerial Imagery (Pictometry 2015, 9inch ortho/oblique, Pictometry 2018, 6inch ortho/oblique) Simi Valley Lidar Data (Q2 Harris Corp Lidar) Coverage of Data:Buildings have been collected from the aerial imageries extent. The 2015 imagery coverage the south county from the north in Ojai to the south in thousand oaks, to the east in Simi Valley, and to the West in the county line with Santa Barbara. Lockwood Valley was also captured in the 2015 imagery. To collect buildings for the wilderness areas we needed to use the imagery from 2007 when we last flew aerial imagery for the entire county. 2018 Imagery was used to capture buildings that were built after 2015.Schema: Fields: APN, Image Date, Image Source, Building Type, Building Description, Address, City, Zip, Data Source, Parcel Data (Year Built, Basement yes/no, Number of Floors) Zoning Data (Main Building, Out Building, Garage), First Floor Elevation, Rough Building Height, X/Y Coordinates, Dimensions. Confidence Levels/Methods:Address data: 90% All Buildings should have an address if they appear to be a building that would normally need an address (Main Residence). To create an address, we do a spatial join on the parcels from the centroid of a building polygon and extract the address data and APN. To collect the missing addresses, we can do a spatial join between the master address and the parcels and then the parcels back to the building polygons. Using a summarize to the APN field we will be able to identify the parcels that have multiple buildings and delete the address information for the buildings that are not a main residence.Building Type Data: 99% All buildings should have a building type according to the site use category code provided from the parcel table information. To further classify multiple buildings on parcels in residential areas, the shape area field was used to identify building polygons greater than 600 square feet as an occupied residence and all other buildings less than that size as outbuildings. All parcels, inparticular parcels with multiple buildings, are subject to classification error. Further defining could be possible with extensive quality control APN Data: 98% All buildings have received APN data from their associated parcel after a spatial join was performed. Building overlapping parcel lines had their centroid derived which allowed for an accurate spatial join.Troubleshooting Required: Buildings would sometimes overlap parcel lines making spatial joining inaccurate. To fix this you create a point from the centroid of the building polygon, join the parcel information to the point, then join the point with the parcel information back to the building polygon.

Hydrographic areas (HA) or hydrographic basins in Nevada were delineated by the U.S. Geological Survey (USGS) and Nevada Division of Water Resources in the late 1960s (Cardinalli and others, 1968; Rush, 1968) for scientific and administrative purposes. In 1988, the USGS published Hydrologic Atlas 694-C where the hydrographic areas of Nevada delineated in the 1960's (and hydrographic areas from surrounding states) were used to define the groundwater flow systems of the Great Basin (Harrill and others, 1988). These data were digitized and released in GIS format by the USGS in 2009 (Buto and Reichelt, 2009). As part of the Nevada Water Initiative project, NDWR has updated the 2009 USGS dataset to include flow systems occurring within the State of Nevada that were previously excluded because they were outside of the Great Basin region. Additionally, NDWR has updated existing HAs overlapping the state boundary with adjacent states HUC boundaries to form more hydrologically based units. Within the State of Nevada, the 1:1,000,000-scale HAs digitized by the USGS were spatially joined to the 1:750,000-scale hydrographic areas used by NDWR for administering water rights in the State and the groundwater flow system attributes were transferred from the USGS dataset to the NDWR HAs. Outside of the State, the 1,000,000-scale HAs were spatially joined to the corresponding USGS 10-Digit Hydrologic Units (HUC10) which overlapped with each HA. Along the State boundary, the 1:750,000-scale NDWR HAs were merged with the rest of the hydrologically continuous basin (as a HUC10 boundary) that exist adjacent to the State. In the NDWR HAs where there was no corresponding groundwater flow system delineated by the USGS, each HA was assigned a flow system based on the following: Within the Truckee, Carson, Walker, and Colorado River systems, several NDWR HAs adjacent to the Nevada State boundary were excluded from the original dataset. Based on the known watersheds of these surface water systems, previously delineated NDWR HAs were assigned to the groundwater flow system based on the watershed boundary.Along the northern border of Nevada with Idaho and Oregon, NDWR HAs belonging to tributary watersheds of the Snake River basin were assigned groundwater flow systems based on watershed area. These systems include those belonging to the Owyhee River, Bruneau River, Salmon Falls Creek, and Goose Creek. Along the northwestern border of Nevada with Oregon and California, small portions of several endorheic basins within the adjacent states extend into Nevada. Due to the potentially complex nature of these groundwater flow systems, the NDWR HAs associated with these endorheic basins were assigned an 'Undetermined' groundwater flow system and may be revisited as part of the Nevada Water Initiative in the future.To document the delineation source and status of each groundwater flow system boundary, a line dataset was produced categorizing each boundary into one of five types: 1. Delineated by NDWR, 2. Delineated by NDWR, Extends Beyond Area Shown, 3. Delineated by USGS, 4. Delineated by USGS, Modified by NDWR, and 5. Undetermined. The Nevada State boundary was also included with these data to better show where the HA data source was merged from the NDWR HAs to the USGS HUC10 boundaries. A polygon dataset of all groundwater flow systems was also created by merging all the HAs and HUC10 boundaries associated with each flow system into a single polygon. Each dataset includes the following attributes:Hydrographic Basin-scale polygons: NDWR Basin Number (ID), NDWR Basin Name, NDWR Basin Sub-Area Name, Groundwater Flow System ID, Groundwater Flow System Name, Groundwater Flow System Source, and Polygon Data Source (NDWR HA or USGS HUC10) Boundary lines: boundary typeFlow system scale polygons: Groundwater Flow System Number (ID), Groundwater Flow System Name, and Groundwater Flow System Source Known issues associated with these data include the following:The boundaries of the NDWR HA and the USGS HUC10 datasets do not necessarily align where they were merged along the Nevada State border. This results in apparent jogs in the boundaries along the State border where the data source switches.Along the border with Oregon, the three NDWR HAs of Macy Flat, Guano Valley, and Sage Hen Valley (HAs 010, 006, and 005 respectively) align with two HUC10 boundaries in Oregon and could not be merged with the associated HUC10s without removing one of the NDWR HAs.The extents of the bordering endorheic basin flow systems have not been determined.The southern extent of the Owens River system is known to extend beyond the delineated boundary.References Cited:Buto, S.G. and Reichelt, J.C., 2009, 1:1,000,000-scale Hydrographic Areas of the Great Basin: U.S. Geological Survey data release, https://doi.org/10.5066/P9VCBUAUCardinalli, J.L., Roach, L.M., Rush, F.E., and Vasey, B.J., 1968, State of Nevada hydrographic areas, scale 1:500,000, in Rush, F.E., ed., Index of hydrographic areas: Nevada Division of Water Resources Information Report 6, 38 p, https://images.water.nv.gov/images/publications/Information%20series/6.pdfHarrill, J.R., Gates, J.S., and Thomas, J.M., 1988, Major ground-water flow systems in the Great Basin region of Nevada, Utah, and adjacent states: U.S. Geological Survey Hydrologic Investigations Atlas HA-694-C, scale 1:1,000,000, 2 sheets, https://doi.org/10.3133/ha694CAuthors: Vergin, T.N., and Allander, K.K.Initial Release: November 4, 2024