This tiled imagery service represents a snapshot of the land surface within Napa County and is made available for public use. The tile cache scheme follows the ArcGIS Online Model and can viewed down to ~1:283 scale. A hard copy of this data is also available directly from the GIS Team. For more information, contact gisstaff@countyofnapa.org.Extent and Resolution:Ortho-imagery and Oblique imagery within Napa County, California. Projection:State Plane Coordinate System1983 California Zone 2North American Datum 1983 (2011) NAVD88 US Survey Feet Capture Window:Imagery was obtained between the dates of June 5 and June18th. Bands:3 (RGB)Sensor:Accuracy of Orthophotography:For questions regarding use and access, please contact gisstaff@countyofnapa.org.

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.

This tiled imagery service represents a snapshot of the land surface within Napa County and is made available for public use. The tile cache scheme follows the ArcGIS Online Model and can viewed down to ~1:283 scale. A hard copy of this data is also available directly from the GIS Team. For more information, contact gisstaff@countyofnapa.org.Extent and Resolution:Orthoimagery and Oblique imagery within Napa County, California. Projection:State Plane Coordinate System1983 California Zone 2North American Datum 1983 (2011) NAVD88 US Survey Feet Capture Window:Imagery was obtained between the dates of March 16 - March 21. Bands:3 (RGB)4th band IR is available in the raw imagery mosaic.Sensor:Accuracy of Orthophotography:For questions regarding use and access, please contact gisstaff@countyofnapa.org.

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.

Analysis of ‘Vegetation - Napa County Update 2016 [ds2899]’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/097f8cf3-c14b-4608-a537-d1405389075d on 28 January 2022.

--- Dataset description provided by original source is as follows ---

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.

--- Original source retains full ownership of the source dataset ---

Internal view of the parcel layer. This view contains all the attributes that can be seen by County employees.There 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.SFAP & CFAP DISCLAIMER: Per the California Code, RTC 606. some legal parcels may have been combined for assessment purposes (CFAP) or separated for assessment purposes (SFAP) into multiple parcels for a variety of tax assessment reasons. SFAP and CFAP parcels are assigned their own APN number and primarily result from a parcel being split by a tax rate area boundary, due to a recorded land use lease, or by request of the property owner. Assessor parcel (APN) maps reflect when parcels have been separated or combined for assessment purposes, and are one legal entity. The goal of the GIS parcel fabric data is to distinguish the SFAP and CFAP parcel configurations from the legal configurations, to convey the legal parcel configurations. This workflow is in progress. Please be advised that while we endeavor to restore SFAP and CFAP parcels back to their legal configurations in the primary parcel fabric layer, SFAP and CFAP parcels may be distributed throughout the dataset. Parcels that have been restored to their legal configurations, do not reflect the SFAP or CFAP parcel configurations that correspond to the current property tax delineations. We intend for parcel reports and parcel data to capture when a parcel has been separated or combined for assessment purposes, however in some cases, information may not be available in GIS for the SFAP/CFAP status of a parcel configuration shown. For help or questions regarding a parcel’s SFAP/CFAP status, or property survey data, please visit Napa County’s Surveying Services or Property Mapping Information. For more information you can visit our website: When a Parcel is Not a Parcel | Napa County, CA

Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

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.

DO NOT DELETE OR MODIFY THIS ITEM. This item is managed by the ArcGIS Hub application. To make changes to this site, please visit https://hub.arcgis.com/admin/

All current structural footprints.The shape and orientation of the ground floor of all structures in a local government. This information is typically compiled from orthoimagery or other aerial photography sources. This representation of the building footprints support the local government basemaps. It also serves as a source for public works, public safety, planning and other agencies that are responsible for the active management of site addresses, facilities, and land use information.

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.

In 1995, the Manual of California Vegetation (MCV) introduced a quantitatively based method for classifying and mapping vegetation in California. In 2002 Department of Fish and Wildlife, Information Center for the Environment, and Aerial Information Systems used this method to develop a classification of vegetation types for Napa County, and to attribute the polygons of a new vegetation map. The complete report for this study can be viewed at: http://www.nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=14660.

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 (http://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.

Data last synced 07-07-2025 06:04. Data synced on a Monthly interval.

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.

For 21 vegetation types (PIs), random polygons of each of the 5 density classes were selected to estimate tree crown density in each polygon. The polygons in each unique PI and Density class combination were then averaged and those averages are recorded in this table. Tree crown density was estimated for PIs with oak as a dominant tree type, as well as some PIs not dominated by oaks. For each PI, 5 polygons were selected per density class; or for PIs which did not have at least 5 polygons per density class, all polygons in the density class were used. In each polygon, we counted the number of tree crowns, or if the polygon was very large, we counted crowns in a small sample of the polygon and used the sample to estimate tree crowns in the entire polygon. Note that because it is sometimes difficult to distinguish between oaks and other trees, we estimated total tree crowns—not necessarily just oak crowns. Once the number of tree crowns in each polygon was estimated, we divided the number of trees by polygon area to obtain an estimate of tree density (in trees/acre). Tree density was estimated for the following PIs:• 1000 series (1101, 1122, 1123, 1124, 1126, 1201, 1202, 1221, 1222, 1223)• 2000 series (2104, 2121, 2123, 2126, 2222, 2230)• 3000 series (3101, 3102, 3121, 3122, 3123, 3124, 3125)

This map application is intended to show information related to fires and evacuations within Napa County.Data updates are performed regularly at the direction of the Napa County EOC's Incident Command, Operations and the Public Information Officer. Map source for application https://napacounty.maps.arcgis.com/home/item.html?id=cdec2f2115ef42e7874606f39d72ea12

This shapefile contains tax rate area (TRA) boundaries in Napa County for the specified assessment roll year. Boundary alignment is based on the 2019 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

10 foot interval, elevation contours of the Napa River non-watershed area. The area covered by this data is referred to as the non-watershed Area because it lies outside the Napa River Watershed. The contours were mapped at a scale of 1"=400ft and meet National Map Accuracy standards at this scale. The vertical datum for the contours is NAVD88. Produced during the 2002/2003 Orthophotography Project.

This layer contains polygons for both pending and approved agricultural Erosion Control Plans. It does not include structural or grading ECPs that are not ag related.