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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. 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 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
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
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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The Mendocino Pygmy Forest is one of the best-known examples of a rare natural community in California. The unique soil and climatic attributes and the resulting vegetation of the Mendocino coastal terraces described by Jenny et al (1969), Westman (1975), Westman and Whittaker (1975), Sholars (1979), Sholars (1982), Sholars (1984) and others are well- known in the scientific and conservation literature.
The mapping and classification process assumed that the unique and biologically significant elements of the pygmy forest ecosystem were definable without a complete inventory of the surrounding regional vegetation and land-use patterns. The boundary of the mapped areas was created using existing geographic information on soils, topography, land use, along with fieldwork from previous efforts. Within that area, an array of vegetation samples were collected and classified representing the full array of vegetation patterns within it. The boundary was refined as part of the mapping process. It was later expanded to include property owned by the Mendocino Coast Park and Recreation District after receiving permission to conduct surveys as part of this project. (Polygons that would not have been mapped for the original project but are within the MCPRD property are marked “MCPRD Additional” in the Notes field.)
The map was produced using a classification based on an analysis of surveys taken throughout the range of the oligotrophic areas supporting Pygmy Forest vegetation. This classification has been incorporated into the Manual of California Vegetation Online Database. The map classification is mostly at the Association Level of the NVCS hierarchy (12 types), with some at the Alliance Level (5 types) and Group Level (3 types), and 4 land use and water classes. It was hand-digitized using photointerpretation based on the 2014 NAIP Imagery, with other ancillary data used to help with the identification of vegetation types. The minimum mapping unit was 1 acre for vegetation types, and 0.25 acres for water, developed and agricultural type. The total area mapped was 9782 acres.
An accuracy assessment performed on the map. The overall accuracy of each of the 5 most reliably sampled types was between 82 and 92 % accuracy, meeting minimum accuracy standards.
For more information, see the supplemental information below and the report for the map cited in the references.
References
California Department of Fish and Wildlife, Vegetation Classification and Mapping Program. Classification and Mapping of Pygmy Forest and Related Mendocino Cypress (Hesperocyparis pygmaea) Vegetation, Mendocino and Sonoma Counties, California. CDFW; 11/2018. https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=161736
A Manual of California Vegetation, Online Edition. http://www.cnps.org/cnps/vegetation/. California Native Plant Society, Sacramento, CA.
USNVC [United States National Vegetation Classification]. http://usnvc.org/. 2017. United States National Vegetation Classification Database, V2.01. Federal Geographic Data Committee, Vegetation Subcommittee, Washington DC
Jenny, H. R.J. Arkley, and A.M. Schultz. 1969. The pygmy forest-podsol ecosystem and its dune associates of the Mendocino coast. Madroño20:60-74.
Westman, W.E. 1975. Edaphic climax pattern of the pygmy forest region of California. Ecological Monographs30:279-338.
Westman, W.E. and R.H. Whittaker. 1975. The pygmy forest region of northern California: studies on biomass and primary productivity. Journal of Ecology63:493-520.
Sholars, R.E. 1979. Water relations in the pygmy forest of Mendocino County. Ph.D. diss. University of California, Davis.
Sholars, R.E. 1982. The pygmy forest and associated plant communities of coastal Mendocino County, California; genesis, soils, vegetation. Black Bear Press, Mendocino, CA.
Sholars, R.E. 1984. The pygmy forest of Mendocino. Fremontia12(3): 3-8.
Bowles, C.J. and E. Cowgill. 2012. Discovering marine terraces using airborne LiDAR along the Mendocino-Sonoma coast, northern California. Geosphere8(2):386–402.
Soil Survey Staff, Natural Resources Conservation Service (NRCS), United States Department of Agriculture. Web Soil Survey. Available online at https://websoilsurvey.nrcs.usda.gov/. Accessed [October 13, 2014].
National Agriculture Imagery Program (NAIP), United States Department of Agriculture. https://www.fsa.usda.gov/programs-and-services/aerial-photography/imagery-programs/naip-imagery/index
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
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
This map is designated as Final.Land-Use Data Quality ControlEvery published digital survey is designated as either ‘Final’, or ‘Provisional’, depending upon its status in a peer review process. Final surveys are peer reviewed with extensive quality control methods to confirm that field attributes reflect the most detailed and specific land-use classification available, following the standard DWR Land Use Legendspecific to the survey year. Data sets are considered ‘final’ following the reconciliation of peer review comments and confirmation by the originating Regional Office. During final review, individual polygons are evaluated using a combination of aerial photointerpretation, satellite image multi-spectral data and time series analysis, comparison with other sources of land use data, and general knowledge of land use patterns at the local level.Provisional data sets have been reviewed for conformance with DWR’s published data record format, and for general agreement with other sources of land use trends. Comments based on peer review findings may not be reconciled, and no significant edits or changes are made to the original survey data.The 2012 Sonoma County land use survey data was developed by the State of California, Department of Water Resources (DWR) through its Division of Integrated Regional Water Management (DIRWM) and Division of Statewide Integrated Water Management (DSIWM). Land use boundaries were digitized and land use data was gathered by staff of DWR’s North Central Region using extensive field visits and aerial photography. Land use polygons in agricultural areas were mapped in greater detail than areas of urban or native vegetation. Quality control procedures were performed jointly by staff at DWR’s DSIWM headquarters, under the leadership of Jean Woods, and North Central Region, under the supervision of Kim Rosmaier. This data was developed to aid DWR’s ongoing efforts to monitor land use for the main purpose of determining current and projected water uses. The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR Spatial Data Standards, specifically the DWR Spatial Data Standards version 2.1, dated March 9, 2016. DWR makes no warranties or guarantees - either expressed or implied - as to the completeness, accuracy, or correctness of the data. DWR neither accepts nor assumes liability arising from or for any incorrect, incomplete, or misleading subject data. Comments, problems, improvements, updates, or suggestions should be forwarded to gis@water.ca.gov. This data represents a land use survey of Sonoma County conducted by the California Department of Water Resources, North Central Regional Office staff. The field work for this survey was conducted during July - September 2012 by staff visiting each field and noting what was grown. The county was divided into five survey areas using major road as centerlines and other geographic features for boundaries. The county was surveyed with two teams. The linework was heads up digitized in ArcGIS 10.0 with 2010 National Agriculture Imagery Program (NAIP) one-meter imagery as the base. Field Boundaries were reviewed with ArcGIS 10.2 and NAIP 2012 imagery when it became available. The data was recombined after it was finished. The Virtual Basic Landuse Attributor was used for the survey and to start the post survey process; after converting to ArcGIS 10.2, the domain file geodatabase structure was used to attribute and help finish facilitating the post survey process. Tables were run through a Python script to put the data in the standard landuse format. ArcGIS geoprocessing tools and topology rules were used to locate errors and for quality control and assurance. Horse pastures were designated either S2 or S6. The special condition 'G' was used to denote vineyards that had sprinklers for frost protection rather than representing a cover crop as stated in the February 2009 Standard Land Use Legend used for this survey. Field Boundaries were not drawn to represent legal parcel (ownership) boundaries, or meant to be used as parcel boundaries. Images and land use boundaries were loaded onto laptop computers that were used as the field data collection tools. GPS units connected to the laptops were used to confirm surveyor's location with respect to the fields. Staff took these laptops into the field and virtually all the areas were visited to positively identify the land use. Land use codes were digitized in the field on laptop computers using ESRI ArcMAP software, version 10.0. Before final processing, standard quality control procedures were performed jointly by staff at DWR’s North Central Region, and at DSIWM headquarters under the leadership of Jean Woods. Senior Land and Water Use Supervisor. After quality control procedures were completed, the data was finalized. The positional accuracy of the digital line work, which is based upon the orthorectified NAIP imagery, is approximately 6 meters. The land use attribute accuracy for agricultural fields is high, because almost every delineated field was visited by a surveyor. The accuracy is 95 percent because some errors may have occurred. Possible sources of attribute errors are: a) Human error in the identification of crop types, b) Data entry errors.
Parcels that have changed ownership/title since the October 2017 Tubbs Fire. Based upon .csv data received from Sonoma County Recorder's office on a monthly basis.
Attribution-NoDerivs 3.0 (CC BY-ND 3.0)https://creativecommons.org/licenses/by-nd/3.0/
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This map identifies the principal areas in the San Francisco Bay region that are likely to produce debris flows, which are also called "mudslides." Debris flows that occur in the bay region are fast-moving downslope flows of mud that may include rocks, vegetation, and other debris. These flows begin during intense rainfall as shallow landslides on steep slopes. The rapid movement and sudden arrival of debris flows pose a hazard to life and property during and immediately following the triggering rainfall. Debris flows in a given storm originate from a number of sources scattered throughout steep parts of the landscape, as shown in figure 1 (on map sheet; files sfbrdf.ps, al-df.ps, etc.). During subsequent storms, new debris flows originate from different sources. These various sources, however, are similar in topographic form because debris-flow initiation requires steep slopes and prefers concave parts of hillsides. These topographic characteristics are used to predict the likely future source areas shown on this map.
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Attribution-NoDerivs 3.0 (CC BY-ND 3.0)https://creativecommons.org/licenses/by-nd/3.0/
License information was derived automatically
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. 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.