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.

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

Public view of the parcel layer. This view is limited to only the attributes that can be seen by the general public.The data table includes the following fields: Shape Type (Shape), Shape.STArea() (Shape_Area), Shape.STLength() (Shape_Area), Name (APN), Created By Record (CreatedbyR), Retired By Record (RetiredbyR), Stated Area, Stated Area Unit (StatedAr_1), Calculated Area (Calculated), Misclose Ratio (MiscloseRa), Misclose Distance (MiscloseDi), Is Seed (IsSeed), Created By (created_us), Created Date (created_da), Modified By (last_edite), Modified Date (last_edi_1), Validation Status (VALIDATION), APN Dashed (APN_Dashed), Map Page (Map_Page), Municipality (Municipali), FloorOrder, HideThere are approximately 51,300 real property parcels in Napa County. Parcels delineate the approximate boundaries of property ownership as described in Napa County deeds, filed maps, and other source documents. GIS parcel boundaries are maintained by the Information Technology Services GIS team. Assessor Parcel Maps are created and maintained by the Assessor Division Mapping Section. Each parcel has an Assessor Parcel Number (APN) that is its unique identifier. The APN is the link to various Napa County databases containing information such as owner name, situs address, property value, land use, zoning, flood data, and other related information. Data for this map service is sourced from the Napa County Parcels dataset which is updated nightly with any recent changes made by the mapping team. There may at times be a delay between when a document is recorded and when the new parcel boundary configuration and corresponding information is available in the online GIS parcel viewer.From 1850 to early 1900s assessor staff wrote the name of the property owner and the property value on map pages. They began using larger maps, called “tank maps” because of the large steel cabinet they were kept in, organized by school district (before unification) on which names and values were written. In the 1920s, the assessor kept large books of maps by road district on which names were written. In the 1950s, most county assessors contracted with the State Board of Equalization for board staff to draw standardized 11x17 inch maps following the provisions of Assessor Handbook 215. Maps were originally drawn on linen. By the 1980’s Assessor maps were being drawn on mylar rather than linen. In the early 1990s Napa County transitioned from drawing on mylar to creating maps in AutoCAD. When GIS arrived in Napa County in the mid-1990s, the AutoCAD images were copied over into the GIS parcel layer. Sidwell, an independent consultant, was then contracted by the Assessor’s Office to convert these APN files into the current seamless ArcGIS parcel fabric for the entire County. Beginning with the 2024-2025 assessment roll, the maps are being drawn directly in the parcel fabric layer.Parcels in the GIS parcel fabric are drawn according to the legal description using coordinate geometry (COGO) drawing tools and various reference data such as Public Lands Survey section boundaries and road centerlines. The legal descriptions are not defined by the GIS parcel fabric. Any changes made in the GIS parcel fabric via official records, filed maps, and other source documents are uploaded overnight. There is always at least a 6-month delay between when a document is recorded and when the new parcel configuration and corresponding information is available in the online parcel viewer for search or download.Parcel boundary accuracy can vary significantly, with errors ranging from a few feet to several hundred feet. These distortions are caused by several factors such as: the map projection - the error derived when a spherical coordinate system model is projected into a planar coordinate system using the local projected coordinate system; and the ground to grid conversion - the distortion between ground survey measurements and the virtual grid measurements. The aim of the parcel fabric is to construct a visual interpretation that is adequate for basic geographic understanding. This digital data is intended for illustration and demonstration purposes only and is not considered a legal resource, nor legally authoritative.

These data were acquired by the National Center for Airborne Laser Mapping (NCALM) in 2003. They have kindly agreed to make these data available to the research community through OpenTopography.Note: This is a classified last return dataset (i.e. there is not first return / canopy top data included). A bare earth model can be created from these data, but a model generated from the full point cloud produces something that approximates a low vegetation surface - not ground, but also not canopy top.UPDATE: Full unfiltered 2003 point cloud ASCII files. Bulk download of the original unfiltered ASCII files (64 GB) from the 2003 Napa Watershed collection by the National Center for Airbone Laser Mapping (NCALM). The original ASCII data has been made available in response to the August 26, 2014 Mw 6.0 South Napa Earthquake.

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 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. The 2004 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 updated version uses a 2016 edition of 1 meter color aerial imagery taken by the National Agriculture Imagery Program (NAIP; https://www.fsa.usda.gov/programs-and-services/aerial-photography/imagery-programs/naip-imagery/index) as the base imagery. It therefore permits an assessment of the change in the patterns of vegetation over 23 years in the county.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 were used in a concurrent project that mapped Sonoma County including the use of LiDAR and Ecognition''s segmentation of imagery to delineate stands. However, the use of such technologies would have made it more difficult to track land cover change in Napa county, because differences in publication dates would not be definitively attributable to actual land cover change or changes 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 polygons to determine if change had occurred. If so, the boundaries and attributes were modified in the new edition of the map. We also used the time series of imagery available on Google Earth, and the high resolution imagery available through ArcMap to further inspect many edited polygons. We conducted 3 rounds of quality assessment/quality control exercises. Funding was not available to do field assessments, but we incorporated field expertise for the Angwin Experimental Forest, reviewed vegetation types identified in the Knoxville Wildlife Area from a 2014 map incorporating 29 of them, and used overlap with the Sonoma Vegetation Map to assess some polygons thought to contain redwood trees (Sequoia sempervirens) along the western side of Napa County.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.

Data Source: Napa County HHSA, Public Health Division

This data biography shares the how, who, what, where, when, and why about this dataset. We, the epidemiology team at Napa County Health and Human Services Agency, Public Health Division, created it to help you understand where the data we analyze and share comes from. If you have any further questions, we can be reached at epidemiology@countyofnapa.org.

How was the data collected? The Napa County Health and Human Services Agency Public Health Division partnered with UpValley Family Centers, the Calistoga Joint Unified School District, and the City of Calistoga to host a Community Conversation on November 16, 2022. Participants worked in small groups to list community resources they know and use. This dataset includes results from three asset categories: Institutions, Physical Places & Spaces, and Local Economy.

Who was included and excluded from the data? The Community Conversation was open to anyone and sought participation from people who live and/or work in Calistoga. Only community members able to attend the event contributed to this dataset. The event was bilingual in Spanish and English.

Where was the data collected? The Community Conversation was held at the Calistoga Junior-Senior High School.

When was the data collected? The Community Conversation was held on November 16, 2022.

Where can I learn more about this data? https://www.livehealthynapacounty.org/uploads/5/1/4/4/51449431/calistoga_community_conversation_2022_report_final.pdf

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

The August 24, 2014, South Napa earthquake (M6.0) produced significant damage resulting from shaking, fault rupture, fault afterslip, and ground deformation. Lidar data were collected to aid specialized work on the South Napa earthquake including: (1) fault afterslip, especially in the Browns Valley residential neighborhood; (2) shaking and correlation to damage such as red- and yellow-tagged structures, especially in the downtown Napa area; (3) seismic hazards of the West Napa Fault System, especially in residential areas; and (4) geospatial analysis and imagery support (such as post-processing of lidar and other imagery that has already been acquired).

Airborne lidar data and imagery were collected on September 9, 2014 as part of multi-agency/institutional response to the August 24, 2014 South Napa Earthquake. Details of the scientific response to this earthquake including the lidar acquisition can be found in Hudnut et al., 2014: USGS Special Open-File Report 2014-1249. Data were collected and initially processed by Towill and are available both as raw files and products as initially delivered by the vendor, as well as the USGS re-processed version of re-classified point clouds and 0.25 meter DEM's from the USGS HDDS Explorer. Point clouds available from USGS and OpenTopography were reclassified (metadata) by the US Geological Survey; this re-processing was funded by FEMA. Orthoimagery were collected by Towill on September 9, 2014, and by Google on August 24, 2014.

Geologic Map of Napa Quadrangle, California. Scale: 1:100,000. Online PDF map.

A map with various base layers to be used as a template for creating thematic maps for the Napa County CWPP online maps. Most layers are from Napa County's online gis data catalog but some layers were derived from public data sources such as Wikipedia and others.

This record is maintained in the National Geologic Map Database (NGMDB). The NGMDB is a Congressionally mandated national archive of geoscience maps, reports, and stratigraphic information, developed according to standards defined by the cooperators, i.e., the USGS and the Association of American State Geologists (AASG). Included in this system is a comprehensive set of publication citations, stratigraphic nomenclature, downloadable content, unpublished source information, and guidance on standards development. The NGMDB contains information on more than 90,000 maps and related geoscience reports published from the early 1800s to the present day, by more than 630 agencies, universities, associations, and private companies. For more information, please see http://ngmdb.usgs.gov/.

Elevation contours covering Napa County at a 2-foot interval. Contour extents were clipped such that they extend 100-ft. beyond the county boundary.Elevation data was derived from bare-earth surface digital elevation models (DEMs) created from LiDAR data flown in 2018 in response to the widespread 2017 fires in Northern California as part of ongoing nationwide 3DEP (U.S. Geological Survey 3D Elevation Program) efforts.In limited areas, located along the western edge of the county boundary, supplemental DEMs were acquired from other sources to fill in gaps in the 3DEP data. Use of this supplemental data was negligible, totaling 24 acres out of 507,475 acres countywide (0.005% of total land area).All DEM tiles (n=41) were merged into a single mosaic. Due to computing limitations, the mosaic was cut into three sections (north, central, and south) of roughly equal size for processing purposes. Two-foot contour lines were generated for each section, then further divided into 1-mile x 1-mile tiles, for a total or 886 tiles.IMPORTANT: refer to the "Tile sources.xlsx" file included in the ZIP for this tile to see what DEMs were used in generating the tile's contours. See "Lineage" section of this metadata for a detailed list of DEM tiles used to generate topo countywide.This topo was prepared under the direction of Patrick Ryan, PE (#85618).The data herein utilizes the NAD_1983_StatePlane_California_II_FIPS_0402_Feet (EPSG:2226) coordinate system (Lambert_Conformal_Conic Projection).Original datums used in the 3DEP DEMs:Horiontal: North American Datum of 1983 (NAD83) Vertical: North American Vertical Datum of 1988 (NAVD88)KNOWN ISSUES / LIMITATIONS:The data herein was generated from DEMs, not the original LiDAR data. This posed certain challenges to the team during processing, namely the inability to utilize point classifications to include/exclude specific types of LiDAR returns. For this reason, in some cases water bodies may show contour lines passing through them. Other issues are mentioned in the Lineage --> Processing Step section of this metadata.

description: This Open-File report consists of a digital geologic map database and associated digital plot files and text files, revised from a hard copy by Sowers and others (1995). This digital map database provides current information on Quaternary geology and liquefaction susceptibility of the Napa, California, 1:100,000 quadrangle. The database delineates map units that are identified by general age and lithology following the stratigraphic nomenclature of the U.S. Geological Survey.; abstract: This Open-File report consists of a digital geologic map database and associated digital plot files and text files, revised from a hard copy by Sowers and others (1995). This digital map database provides current information on Quaternary geology and liquefaction susceptibility of the Napa, California, 1:100,000 quadrangle. The database delineates map units that are identified by general age and lithology following the stratigraphic nomenclature of the U.S. Geological Survey.

Countywide vegetation classes based on definitions found in the Napa County Water Quality & Tree Protection Ordinance (WQTPO).More information related to the WQTPO and these classes can be found in the following documents:Final Ordinance, approved 4/9/2019 Implementation Guide to the WQTPOThis layer is a view of the original Vegetation layer. The description from the source layer follows: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.

A group of layers from the National Flood Hazard Layer from FEMA:Flood Control StructuresProfile BaselineCross-sectionsBase Flood ElevationsFIRM Map PanelsLOMRFlood Hazard AreasThis layer is updated every 6 months by Napa Co. PBES Dept.

This geologic map database is comprised of new geologic mapping, at a 1:24,000 scale, along the southern Bartlett Springs fault in the northern California Coast Ranges. The map covers an area of 258 square miles in Lake, Napa, Colusa, and Yolo counties, work was undertaken between 2016 and 2021, and supported by the USGS National Cooperative Geologic Map Program. This geodatabase contains the most up-to-date and highest resolution mapping in the region. Results and observations reported here help elucidate the geologic deformational history, as well as relationships between active older and active structures. Please consult the map pamphlet and description of map units for a detailed presentation and interpretation of data and discussion of results. The report and geodatabase contain two plates including the geologic map as well as a correlation of map units, four geologic cross sections, six microseismic cross sections, and a microseismicity fault map.

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

Linework representing fault rupture and ground deformation features interpreted from airborne imagery, lidar, and InSAR interferograms, are combined with digitized field mapping into a single KMZ file.

A map highlighting the drainage basins defined by Napa County in their modeling efforts. The Napa County Watersheds were generated from two elevation datasets. The Napa River Watershed was generated from LIDAR data processed by NCALM at UC Berkeley (https://calm.geo.berkeley.edu/ncalm/index.html). The eastern side of the county was delineated from DTM data which was generated from aerial photography (2002). The watersheds are intended to be used for hydrologic modeling and planning.Ridgelines are also from Napa County and depict major and minor ridgelines.Other topographic features important to wildfire planning may in added in the future.