The seamless, county-wide parcel layer was digitized from official Assessor Parcel (AP) Maps which were originally maintained on mylar sheets and/or maintained as individual Computer Aided Design (CAD) drawing files (e.g., DWG). The CRA office continues to maintain the official AP Maps in CAD drawings and Information Systems Department/Geographic Information Systems (ISD/GIS) staff apply updates from these maps to the seamless parcel base in the County’s Enterprise GIS. This layer is a partial view of the Information Sales System (ISS) extract, a report of property characteristics taken from the County’s Megabyte Property Tax System (MPTS). This layer may be missing some attributes (e.g., Owner Name) which may not be published to the Internet due to privacy conditions under the California Public Records Act (CPRA). Please contact the Clerk-Recorder-Assessor (CRA) office at (707) 565-1888 for information on availability, associated fees, and access to other versions of Sonoma County parcels containing additional property characteristics.The seamless parcel layer is updated and published to the Internet on a monthly basis.The seamless parcel layer was developed from the source data using the general methodology outlined below. The mylar sheets were scanned and saved to standard image file format (e.g., TIFF). The individual scanned maps or CAD drawing files were imported into GIS software and geo-referenced to their corresponding real-world locations using high resolution orthophotography as control. The standard approach was to rescale and rotate the scanned drawing (or CAD file) to match the general location on the orthophotograph. Then, appropriate control points were selected to register and rectify features on the scanned map (or CAD drawing file) to the orthophotography. In the process, features in the scanned map (or CAD drawing file) were transformed to real-world coordinates, and line features were created using “heads-up digitizing” and stored in new GIS feature classes. Recommended industry best practices were followed to minimize root mean square (RMS) error in the transformation of the data, and to ensure the integrity of the overall pattern of each AP map relative to neighboring pages. Where available Coordinate Geometry (COGO) & survey data, tied to global positioning systems (GPS) coordinates, were also referenced and input to improve the fit and absolute location of each page. The vector lines were then assembled into a polygon features, with each polygon being assigned a unique identifier, the Assessor Parcel Number (APN). The APN field in the parcel table was joined to the corresponding APN field in the assessor property characteristics table extracted from the MPTS database to create the final parcel layer. The result is a seamless parcel land base, each parcel polygon coded with a unique APN, assembled from approximately 6,000 individual map page of varying scale and accuracy, but ensuring the correct topology of each feature within the whole (i.e., no gaps or overlaps). The accuracy and quality of the parcels varies depending on the source. See the fields RANK and DESCRIPTION fields below for information on the fit assessment for each source page. These data should be used only for general reference and planning purposes. It is important to note that while these data were generated from authoritative public records, and checked for quality assurance, they do not provide survey-quality spatial accuracy and should NOT be used to interpret the true location of individual property boundary lines. Please contact the Sonoma County CRA and/or a licensed land surveyor before making a business decision that involves official boundary descriptions.

This dataset was originally created to fill in gaps or other address range difficulties for the County of Sonoma dispatching system and to identify specific or special addresses that may or may not be difficult to find on the ground in the field. By no means complete, it is now the intent of this feature class to record all known addresses in Sonoma County. Most points will be directly on top of a structure. In those instances where a point is not on top of a structure it may be for one or more of the following reasons; multiple structures make positive identification of a specific address unclear, tree cover makes it difficult to identify structures, there is no structure associated with an address, or at the request of CAD 911 dispatchers for various reasons.

This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) System (MTS). The MTS represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The All Roads shapefile includes all features within the MTS Super Class "Road/Path Features" distinguished where the MAF/TIGER Feature Classification Code (MTFCC) for the feature in the MTS that begins with "S". This includes all primary, secondary, local neighborhood, and rural roads, city streets, vehicular trails (4wd), ramps, service drives, alleys, parking lot roads, private roads for service vehicles (logging, oil fields, ranches, etc.), bike paths or trails, bridle/horse paths, walkways/pedestrian trails, and stairways.

Santa Rosa Plain Programmatic Biological Opinion Parcels - Data "CDR_PARCELS" obtained from County of Sonoma GIS Central.

A distinction should be made with respect to this layer which includes GIS parcels and the official Assessor Parcels residing in the Assessor Map books at the Sonoma County Assessor Office. For official parcel records please contact the Sonoma County Assessor (707)565-1888. These parcels should NOT be represented as survey data, and the official record of survey takes precedence where there are discrepancies. It is the end user's responsibility to check the accuracy of the GIS data by comparing it with the published data from the Sonoma County Assessor / Recorder office. The Sonoma County parcel base was originally compiled from Assessor Parcel maps at a scale of 1:6000. The individual Assessor Parcel maps were enlarged or reduced in size using an electrostatic process to produce the maps at the 1:6000 scale, the maps were then fit together by hand and transcribed on to mylar. The mylar base consisted of 1:6000 USGS base map information typically found on the 7.5 USGS quad series. This base information consisted of Topography, Roads, Section, and Rancho lines to name some. Using this information, the Assessor Parcel maps were fit to the individual 1:6000 scale maps. Each 1:6000 scale map represents 1/6 (quad sixths) of a 7.5 minute USGS Quadrangle series map. In 1998 the State Board of Equalization provided the impetus to produce the Russian River Project for all of Planning Area 4. One aspect required for this project was a digital parcel base for Planning Area 4. This involved the conversion of the 1:6000 mylars with the transcribed parcels on them into a digital version of the parcels. The mylars where scanned and geo-referenced using the base map information originally included with the 1:6000 mylar base. The maps were geo-referenced to a digital version of the USGS 7.5 minute Quadrangle series available from the Teale Data Center. The original projection was California State Plane Zone 2 NAD 1927. County Staff then used AutoCAD software to heads up digitize each 1:6000 scale map in Planning Area 4. A custom application was created and used by GIS staff involving the use of Avenue and ArcView 3.2 to create a point for all the parcels in Planning Area 4, attributes included Assessor Parcel Number. The DWGs were then converted to shapefiles and then converted to ArcINFO coverages, the parcel tags were converted from shapefiles to ArcINFO coverages and the point coverage was merged with the polygon coverage with the IDENTITY command. An exhaustive process was involved to eliminate errors once the DWGs were converted to ArcINFO coverages so polygons could be generated. The coverages were then aggregated using the MAPJOIN command, the original boundary of the 1:6000 scale maps was removed using the REGIONDISSOLVE command to merge adjacent polygons with the same AP number. In 1999 the remainder of the planning areas were converted to digital form following the Russian River Project and the seamless base was completed in 2001. The seamless parcel base was maintained in ArcINFO until the release of ArcGIS 8.3, which included topology tools necessary for its maintenance. The seamless base prior to late 2002 was suitable for 1:100000 scale while the control points (the corners for the 1:6000 scale maps) were suitable for 1:24000 scale. Prior to rectification to the Merrick 2000 orthophotography, the parcel data were derived from 1:6000 scale maps (enlarged from USGS 7.5 minute quadrangle 1:24,000 series) and digitized in California State Plane, Zone II, NAD 27 coordinates (survey feet), but were converted to California State Plane, Zone II, NAD 83 coordinates (survey feet) as part of a rectification process now underway. The parcels used to use the USGS 7.5 minute quadrangle (1:24,000) series for coordinate control, but no guarantee is made for their spatial accuracy. The data were re-projected to NAD 83 coordinates to overlay the orthophotography, but the parcel boundaries will not correspond precisely with features in the images. The parcels were rectified to orthophotography flown in April - May 2000 using geo-referencing tools available in ArcGIS 8.3. This project was completed in July 2005. In general, the parcels meet National Accuracy Standards for 1:24,000 scale maps, and likely exceed that accuracy in urban areas. A complete description of the process is detailed in a series of documents located on a local file server: S:\COMMON\GIS\Documentation\Parcel Rectification & Update Process\Procedure - *. doc. A brief summary is as follows. Individual Assessor Parcel pages or CAD drawings are rectified to the orthophoto. COGO & survey data are used when available and in sufficient quantities to enable the bulk of an Assessor Parcel page to be digitized using said information. Polygons are generated directly from the COGO data, CAD dwg are exported to feature classes, where polygons are then generated, rectified Assessor Parcel pages are vectorized using ArcScan and subsequently polygons are generated. A spatial join is used to assign attributes to the newly generated polygons. Polygons are then assigned an accuracy rank based on source, quality of the fit to the orthophoto, and RMS error encountered during rectification (only the scanned Assessor maps will have and RMS error associated with them). See the fields RANK and DESCRIPTION for information on fit assessment. Areas that have been successfully updated as such have a reasonable expectation of accuracy of +/- 10 and possibly better, areas that have not been updated or are flagged in SCAMP under the GIS group Projects as Needs Survey Data, the original accuracy assessment of 1:100000 applies.

The Bicycle Plan is the countywide planning document for bicycle facilities. The GIS data component of the Bicycle Plan consists of an inventory of existing and proposed bikeways with a class I through IV designation. Bikeway data was captured using road centerlines captured from the aerial photography as the apparent centerline and heads up digitizing directly from the orthophotography by GIS staff. Attributes were compiled via a conflation process from the original bikeway data to the new coverage captured from the aerial photography. Subsequently a QC process followed to correct errors in the conflation and digitizing process. Bikeways captured from the Merrick Street centerlines do not represent the actual location of the bikeway feature. Heads up digitized features do represent the apparent centerline of the bikeway feature.

The Permit Sonoma GIS Parcel dataset represents unincorporated lands & incorporated (city) lands within Sonoma County.

This .tif file represents the intensity values of the NIR Lidar laser returns from the Sonoma Creek Topo bathymetric dataset. The horizontal datum for this dataset is NAD83 (2011), the vertical datum is NAVD88, Geoid 18, and the data is projected in California State Plane, Zone 2. Units are in US Survey Feet. NV5 Geospatial collected the Sonoma Creek Topo bathymetric Lidar data for Sonoma Water between 02/04/2021 and 02/06/2021.

You are free to: Share - copy and redistribute the data in any medium or format. Adapt - You may make derivative works, transform, and build upon the data for any purpose, even commercial. The licensor cannot revoke these freedoms as long as you follow the license terms.License terms: Attribution - You must give appropriate credit (if supplied, you must provide the name of the creator and attribution parties, a copyright notice, a license notice, a disclaimer notice and a link to the material) and indicate if any changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you, your organization, or your use of the data. ShareAlike - if you modify, transform, or build on the data, you must distribute your contributions under the same license as the original.No additional Restrictions - You may not apply legal terms or technological measures that legally restrict others form doing anything the license permits.Notices: You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation. No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the data.EXCEPT TO THE EXTENT REQUIRED BY APPLICABLE LAW, IN NO EVENT WILL LICENSOR BE LIABLE TO YOU ON ANY LEGAL THEORY FOR ANY SPECIAL, INCIDENTAL, CONSEQUENTIAL, PUNITIVE OR EXEMPLARY DAMAGES ARISING OUT OF THIS LICENSE OR THE USE OF THE DATA, EVEN IF LICENSOR HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.The above is an easily understandable summary of and not a substitute for the license and disclaimer for the Attribution-ShareAlike 3.0 United States (CC BY-SA 3.0 US) the full text is available at creativecommons.org.https://creativecommons.org/licenses/by-sa/3.0/us/legalcode

This layer intends to document all parks in each regional park. A parks inclusion in this layer may not constitute offical park access or regional parks authorization to use this park as some of these park are classified as 'volunteer'. In addition to the alinment of the park other attributes record the condition and intended use of the park.

The California Association Local Agency Formation Commissions defines a sphere of influence (SOI) as "a planning boundary outside of an agency’s legal boundary (such as the city limit line) that designates the agency’s probable future boundary and service area." This feature set represents the SOIs of the incorporated jurisdictions for the San Francisco Bay Region. The Metropolitan Transportation Commission (MTC) updated the feature set in late 2019 as part of the jurisdiction review process for the BASIS data gathering project. Changes were made to the growth boundaries of the following jurisdictions based on BASIS feedback and associated work: Antioch, Brentwood, Campbell, Daly City, Dublin, Fremont, Hayward, Los Gatos, Monte Sereno, Newark, Oakland, Oakley, Pacifica, Petaluma, Pittsburg, Pleasanton, San Bruno, San Francisco (added to reflect other jurisdictions whose SOI is the same as their jurisdiction boundary), San Jose, San Leandro, Santa Clara, Saratoga, and Sunnyvale. Notes: With the exception of San Mateo and Solano Counties, counties included jurisdiction (city/town) areas as part of their SOI boundary data. San Mateo County and Solano County only provided polygons representing the SOI areas outside the jurisdiction areas. To create a consistent, regional feature set, the Metropolitan Transportation Commission (MTC) added the jurisdiction areas to the original, SOI-only features and dissolved the features by name.Because of differences in base data used by the counties and the MTC, edits were made to the San Mateo County and Solano County SOI features that should have been adjacent to their jurisdiction boundary so the dissolve function would create a minimum number of features. Original sphere of influence boundary acquisitions:Alameda County - CityLimits_SOI.shp received as e-mail attachment from Alameda County Community Development Agency on 30 August 2019 Contra Costa County - BND_LAFCO_Cities_SOI.zip downloaded from https://gis.cccounty.us/Downloads/Planning/ on 15 August 2019Marin County - 'Sphere of Influence - City' feature service data downloaded from Marin GeoHub on 15 August 2019Napa County - city_soi.zip downloaded from their GIS Data Catalog on 15 August 2019 City and County of San Francisco - does not have a sphere of influence San Mateo County - 'Sphere of Influence' feature service data downloaded from San Mateo County GIS open data on 15 August 2019 Santa Clara County - 'City Spheres of Influence' feature service data downloaded from Santa Clara County Planning Office GIS Data on 15 August 2019 Solano County - SphereOfInfluence feature service data downloaded from Solano GeoHub on 15 August 2019 Sonoma County - 'SoCo PRMD GIS Spheres Influence.zip' downloaded from County of Sonoma on 15 August 2019

Additional attributes published by Sonoma Co. GIS

County of Sonoma Environmental Health LNU Lightning Complex Fire Phase 2 CleanupPhase 2 is the removal of the remaining structural ash and debris as well as soil testing to ensure the site is clean, safe for rebuilding, and free of potentially leached toxins. Phase 2 cleanup can only initiate after the Phase 1 HHW Sweep is complete and the property owner has been given proper authorization to begin debris removal.There are two options for Phase 2. Property owners may choose to enter into the public Right of Entry (ROE) program in which contractors working with the state do the debris removal on your property. The second option is the private debris removal option in which property owners clean up their property with the use of contractors and appropriately certified personnel to meet the Debris Removal Requirements.

County-maintained streets in Sonoma County, California. Authored by the Department of Transportation & Public Works, County of Sonoma.

This shapefile contains tax rate area (TRA) boundaries in Sonoma County for the specified assessment roll year. Boundary alignment is based on the 2018 county parcel map. A tax rate area (TRA) is a geographic area within the jurisdiction of a unique combination of cities, schools, and revenue districts that utilize the regular city or county assessment roll, per Government Code 54900. Each TRA is assigned a six-digit numeric identifier, referred to as a TRA number. TRA = tax rate area number

Road centerlines are captured from the aerial photography as the apparent centerline. Attributes originally compiled via a conflation process from the original street centerline data to the new centerline coverage captured from the aerial photography. Subsequently an extensive QC process followed to correct errors in the conflation process. These areas where identified by staff in phase one of the QC process.

The dataset consists of tiled orthogonal imagery produced from nadir images captured by Pictometry International. Automatic aerial triangulation (AAT) was performed. The triangulated frames were rectified to a LiDAR derived DEM. Mosaicking was performed using an automatic seaming algorithm and manually edited to eliminate seams through elevated features where possible.

The City Limit dataset represents the nine city, urban (incorporated) municipality boundaries within the County of Sonoma. The dataset includes ALL RECORDED ANNEXATIONS to date.Related Resource:Permit Sonoma GIS HomepageSonoma Local Agency Formation Commission(LAFCO)Annexation Report(The annexation report represents unincorporated lands annexed into city jurisdictions.)Refer to Map series per jurisdiction -City of CloverdaleCity of CotatiCity of HealdsburgCity of PetalumaCity of Rohnert ParkCity of Santa RosaCity of SebastopolCity of SonomaTown of Windsor

This is a vector tile service of the fine scale vegetation and habitat map, to be used in web maps and GIS software packages. It is mean to be used in conjunction with the vector tile service that provides labels for each polygon. There is an additional vector tile service that provides solid colored polygons for the vegetation map if hollow outlines are not desired. The Sonoma County fine scale vegetation and habitat map is an 82-class vegetation map of Sonoma County with 212,391 polygons. The fine scale vegetation and habitat map represents the state of the landscape in 2013 and adheres to the National Vegetation Classification System (NVC). The map was designed to be used at scales of 1:5,000 and smaller. The full datasheet for this product is available here: https://sonomaopenspace.egnyte.com/dl/qOm3JEb3tD Class definitions, as well as a dichotomous key for the map classes, can be found in the Sonoma Vegetation and Habitat Map Key (https://sonomaopenspace.egnyte.com/dl/xObbaG6lF8). The fine scale vegetation and habitat map was created using semi-automated methods that include field work, computer-based machine learning, and manual aerial photo interpretation. The vegetation and habitat map was developed by first creating a lifeform map, an 18-class map that served as a foundation for the fine-scale map. The lifeform map was created using “expert systems” rulesets in Trimble Ecognition. These rulesets combine automated image segmentation (stand delineation) with object based image classification techniques. In contrast with machine learning approaches, expert systems rulesets are developed heuristically based on the knowledge of experienced image analysts. Key data sets used in the expert systems rulesets for lifeform included: orthophotography (’11 and ’13), the LiDAR derived Canopy Height Model (CHM), and other LiDAR derived landscape metrics. After it was produced using Ecognition, the preliminary lifeform map product was manually edited by photo interpreters. Manual editing corrected errors where the automated methods produced incorrect results. Edits were made to correct two types of errors: 1) unsatisfactory polygon (stand) delineations and 2) incorrect polygon labels. The mapping team used the lifeform map as the foundation for the finer scale and more floristically detailed Fine Scale Vegetation and Habitat map. For example, a single polygon mapped in the lifeform map as forest might be divided into four polygons in the in the fine scale map including redwood forest, Douglas-fir forest, Oregon white oak forest, and bay forest. The fine scale vegetation and habitat map was developed using a semi-automated approach. The approach combines Ecognition segmentation, extensive field data collection, machine learning, manual editing, and expert review. Ecognition segmentation results in a refinement of the lifeform polygons. Field data collection results in a large number of training polygons labeled with their field-validated map class. Machine learning relies on the field collected data as training data and a stack of GIS datasets as predictor variables. The resulting model is used to create automated fine-scale labels countywide. Machine learning algorithms for this project included both Random Forests and Support Vector Machines (SVMs). Machine learning is followed by extensive manual editing, which is used to 1) edit segment (polygon) labels when they are incorrect and 2) edit segment (polygon) shape when necessary. The map classes in the fine scale vegetation and habitat map generally correspond to the alliance level of the National Vegetation Classification, but some map classes - especially riparian vegetation and herbaceous types - correspond to higher levels of the hierarchy (such as group or macrogroup).

Intended as a repository for all publicly owned land in Sonoma County, this would include but is not limited to county, state, local, and federal property which may or may not include parks, landfills, corporate yards, business and services, hospital property. This layer is not intended to make any determination regarding public access. This layer was compiled from two primary sources; the County seamless parcel base and the Merrick 2000 orthophotography. This layer was originally created to support the 1989 version of the Open Space Element of the General Plan.

Napa County has used a 2004 edition vegetation map produced using the Manual of California Vegetation classification system (Thorne et al. 2004) as one of the input layers for land use decision and policy. The county decided to update the map because of its utility. A University of California, Davis (UCD) group was engaged to produce the map. The earlier map used black and white digital orthophoto quadrangles from 1993, with a pixel resolution of 3 meters. This image was delineated using a heads up digitization technique produced by ASI (Aerial Services Incorporated). The resulting polygons were the provided vegetation and landcover attributes following the classification system used by California State Department of Fish and Wildlife mappers in the Manual of California Vegetation. That effort included a brief field campaign in which surveyors drove accessible roads and verified or corrected the dominant vegetation of polygons adjacent to roadways or visible using binoculars. There were no field relevé or rapid assessment plots conducted. This update version uses a 2016 edition of 1 meter color aerial imagery taken by the National Agriculture Imagery Program (NAIP) as the base imagery. In consultation with the county we decided to use similar methods to the previous mapping effort, in order to preserve the capacity to assess change in the county over time. This meant forgoing recent data and innovations in remote sensing such as the use LiDAR and Ecognition’s segmentation of imagery to delineate stands, which have been recently used in a concurrent project mapping of Sonoma County. The use of such technologies would have made it more difficult to track changes in landcover, because differences between publication dates would not be definitively attributable to either actual land cover change or to change in methodology. The overall cost of updating the map in the way was approximately 20% of the cost of the Sonoma vegetation mapping program.Therefore, we started with the original map, and on-screen inspections of the 2004 polygons to determine if change had occurred. If so, the boundaries and attributes were modified in this new edition of the map. We also used the time series of imagery available on Google Earth, to further inspect many edited polygons. While funding was not available to do field assessments, we incorporated field expertise and other map data from four projects that overlap with parts of Napa Count: the Angwin Experimental Forest; a 2014 vegetation map of the Knoxville area; agricultural rock piles were identified by Amber Manfree; and parts of a Sonoma Vegetation Map that used 2013 imagery.The Angwin Experimental Forest was mapped by Peter Lecourt from Pacific Union College. He identified several polygons of redwoods in what are potentially the eastern-most extent of that species. We reviewed those polygons with him and incorporated some of the data from his area into this map.The 2014 Knoxville Vegetation map was developed by California Department of Fish and Wildlife. It was made public in February of 2019, close to the end of this project. We reviewed the map, which covers part of the northeast portion of Napa County. We incorporated polygons and vegetation types for 18 vegetation types including the rare ones, we reviewed and incorporated some data for another 6 types, and we noted in comments the presence of another 5 types. There is a separate report specifically addressing the incorporation of this map to our map.Dr Amber Manfree has been conducting research on fire return intervals for parts of Napa County. In her research she identified that large piles of rocks are created when vineyards are put in. These are mapable features. She shared the locations of rock piles she identified, which we incorporated into the map. The Sonoma Vegetation Map mapped some distance into the western side of Napa County. We reviewed that map’s polygons for coast redwood. We then examined our imagery and the Google imagery to see if we could discern the whorled pattern of tree branches. Where we could, we amended or expanded redwood polygons in our map.The Vegetation classification systems used here follows California’s Manual of California Vegetation and the National Vegetation Classification System (MCV and NVCS). We started with the vegetation types listed in the 2004 map. We predominantly use the same set of species names, with modifications/additions particularly from the Knoxville map. The NVCS uses Alliance and Association as the two most taxonomically detailed levels. This map uses those levels. It also refers to vegetation types that have not been sampled in the field and that has 3-6 species and a site descriptor as Groups, which is the next more general level in the NVCS classification. We conducted 3 rounds of quality assessment/quality control exercises.