This shapefile contains tax rate area (TRA) boundaries in Santa Clara County for the specified assessment roll year. Boundary alignment is based on the 2012 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

Western Foundation of Vertebrate Zoology contracted Stillwater Sciences in 2018 to create a fine-scale vegetation map of portions of the Santa Clara River. The mapping study area, consists of approximately 16,370 acres of Ventura County. Work was performed on the project during the summer and fall of 2018. The projects main goal was to address the need for detailed up-to-date vegetation information in support of identifying and modeling habitat for southwestern willow flycatcher, yellow-billed cuckoo, and least Bell's vireo. Funding for the project was provided by an Endangered Species Act Section 6 grant from the United States Fish and Wildlife Service to the California Department of Fish and Wildlife. This project builds off a prior mapping project that was conducted by Stillwater Sciences and URS, which was funded by the California State Coastal Conservancy and the Santa Clara River Trustee Council, in 2007. Species composition data collected in the field was compiled and reviewed in the office to assign the appropriate MCV alliance to each sampled location. In cases where the species present were best described by an MCV association (a sub-category of the broader MCV alliance), one was assigned. For field sampled locations with unique species composition not currently represented by an existing MCV alliance or association, a provisional alliance or association was created. In addition, some areas were classified into broader land cover types (e.g., agriculture, developed, riverwash). The vegetation map was produced applying digital aerial imagery (natural color, 2-foot resolution) from the National Agricultural Imagery Program (NAIP) (USDA-FSA 2016) flown in May, June, and July 2016. The minimum mapping unit (MMU) is 0.5 acres for most types and 0.1 for more unusual types that were discernable from areal photography and/or documented in the field. Once the map was made photointerpretation of the NAIP imagery took place in order to identify vegetation types. Field mapping took place after to refine the vegetation type definitions, CNPS vegetation reconnaissance field forms were used in the field. There was a total of 91 mapping classes. There was no accuracy assessment was done for this project. More information can be found in the project report, which is bundled with the vegetation map published for BIOs here: https://filelib.wildlife.ca.gov/Public/BDB/GIS/BIOS/Public_Datasets/2900_2999/ds2961.zip

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 2019Contra 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 2019City and County of San Francisco - does not have a sphere of influenceSan Mateo County - 'Sphere of Influence' feature service data downloaded from San Mateo County GIS open data on 15 August 2019Santa Clara County - 'City Spheres of Influence' feature service data downloaded from Santa Clara County Planning Office GIS Data on 15 August 2019Solano County - SphereOfInfluence feature service data downloaded from Solano GeoHub on 15 August 2019Sonoma County - 'SoCo PRMD GIS Spheres Influence.zip' downloaded from County of Sonoma on 15 August 2019

This dataset includes one file for each of the 51 counties that were collected, as well as a CA_Merged file with the parcels merged into a single file.Note – this data does not include attributes beyond the parcel ID number (PARNO) – that will be provided when available, most likely by the state of California.DownloadA 1.6 GB zipped file geodatabase is available for download - click here.DescriptionA geodatabase with parcel boundaries for 51 (out of 58) counties in the State of California. The original target was to collect data for the close of the 2013 fiscal year. As the collection progressed, it became clear that holding to that time standard was not practical. Out of expediency, the date requirement was relaxed, and the currently available dataset was collected for a majority of the counties. Most of these were distributed with minimal metadata.The table “ParcelInfo” includes the data that the data came into our possession, and our best estimate of the last time the parcel dataset was updated by the original source. Data sets listed as “Downloaded from” were downloaded from a publicly accessible web or FTP site from the county. Other data sets were provided directly to us by the county, though many of them may also be available for direct download. Â These data have been reprojected to California Albers NAD84, but have not been checked for topology, or aligned to county boundaries in any way. Tulare County’s dataset arrived with an undefined projection and was identified as being California State Plane NAD83 (US Feet) and was assigned by ICE as that projection prior to reprojection. Kings County’s dataset was delivered as individual shapefiles for each of the 50 assessor’s books maintained at the county. These were merged to a single feature class prior to importing to the database.The attribute tables were standardized and truncated to include only a PARNO (APN). The format of these fields has been left identical to the original dataset. The Data Interoperablity Extension ETL tool used in this process is included in the zip file. Where provided by the original data sources, metadata for the original data has been maintained. Please note that the attribute table structure changes were made at ICE, UC Davis, not at the original data sources.Parcel Source InformationCountyDateCollecDateCurrenNotesAlameda4/8/20142/13/2014Download from Alamenda CountyAlpine4/22/20141/26/2012Alpine County PlanningAmador5/21/20145/14/2014Amador County Transportation CommissionButte2/24/20141/6/2014Butte County Association of GovernmentsCalaveras5/13/2014Download from Calaveras County, exact date unknown, labelled 2013Contra Costa4/4/20144/4/2014Contra Costa Assessor’s OfficeDel Norte5/13/20145/8/2014Download from Del Norte CountyEl Dorado4/4/20144/3/2014El Dorado County AssessorFresno4/4/20144/4/2014Fresno County AssessorGlenn4/4/201410/13/2013Glenn County Public WorksHumboldt6/3/20144/25/2014Humbodt County AssessorImperial8/4/20147/18/2014Imperial County AssessorKern3/26/20143/16/2014Kern County AssessorKings4/21/20144/14/2014Kings CountyLake7/15/20147/19/2013Lake CountyLassen7/24/20147/24/2014Lassen CountyLos Angeles10/22/201410/9/2014Los Angeles CountyMadera7/28/2014Madera County, Date Current unclear likely 7/2014Marin5/13/20145/1/2014Marin County AssessorMendocino4/21/20143/27/2014Mendocino CountyMerced7/15/20141/16/2014Merced CountyMono4/7/20144/7/2014Mono CountyMonterey5/13/201410/31/2013Download from Monterey CountyNapa4/22/20144/22/2014Napa CountyNevada10/29/201410/26/2014Download from Nevada CountyOrange3/18/20143/18/2014Download from Orange CountyPlacer7/2/20147/2/2014Placer CountyRiverside3/17/20141/6/2014Download from Riverside CountySacramento4/2/20143/12/2014Sacramento CountySan Benito5/12/20144/30/2014San Benito CountySan Bernardino2/12/20142/12/2014Download from San Bernardino CountySan Diego4/18/20144/18/2014San Diego CountySan Francisco5/23/20145/23/2014Download from San Francisco CountySan Joaquin10/13/20147/1/2013San Joaquin County Fiscal year close dataSan Mateo2/12/20142/12/2014San Mateo CountySanta Barbara4/22/20149/17/2013Santa Barbara CountySanta Clara9/5/20143/24/2014Santa Clara County, Required a PRA requestSanta Cruz2/13/201411/13/2014Download from Santa Cruz CountyShasta4/23/20141/6/2014Download from Shasta CountySierra7/15/20141/20/2014Sierra CountySolano4/24/2014Download from Solano Couty, Boundaries appear to be from 2013Sonoma5/19/20144/3/2014Download from Sonoma CountyStanislaus4/23/20141/22/2014Download from Stanislaus CountySutter11/5/201410/14/2014Download from Sutter CountyTehama1/16/201512/9/2014Tehama CountyTrinity12/8/20141/20/2010Download from Trinity County, Note age of data 2010Tulare7/1/20146/24/2014Tulare CountyTuolumne5/13/201410/9/2013Download from Tuolumne CountyVentura11/4/20146/18/2014Download from Ventura CountyYolo11/4/20149/10/2014Download from Yolo CountyYuba11/12/201412/17/2013Download from Yuba County

Description for i03_DAU_county_cnty2018 is as follows:Detailed Analysis Unit-(DAU) Convergence via County Boundary cnty18_1 for Cal-Fire, (See metadata for CAL-FIRE cnty18_1), State of California.The existing DAU boundaries were aligned with cnty18_1 feature class.Originally a collaboration by Department of Water Resources, Region Office personnel, Michael L. Serna, NRO, Jason Harbaugh - NCRO, Cynthia Moffett - SCRO and Robert Fastenau - SRO with the final merge of all data into a cohesive feature class to create i03_DAU_COUNTY_cnty24k09 alignment which has been updated to create i03_DAU_COUNTY_cnty18_1.This version was derived from a preexisting “dau_v2_105, 27, i03_DAU_COUNTY_cnty24k09” Detailed Analysis Unit feature class's and aligned with Cal-Fire's 2018 boundary.Manmade structures such as piers and breakers, small islands and coastal rocks have been removed from this version. Inlets waters are listed on the coast only.These features are reachable by County\DAU. This allows the county boundaries, the DAU boundaries and the State of California Boundary to match Cal-Fire cnty18_1.DAU BackgroundThe first investigation of California's water resources began in 1873 when President Ulysses S. Grant commissioned an investigation by Colonel B. S. Alexander of the U.S. Army Corps of Engineers. The state followed with its own study in 1878 when the State Engineer's office was created and filled by William Hammond Hall. The concept of a statewide water development project was first raised in 1919 by Lt. Robert B. Marshall of the U.S. Geological Survey.In 1931, State Engineer Edward Hyatt introduced a report identifying the facilities required and the economic means to accomplish a north-to-south water transfer. Called the "State Water Plan", the report took nine years to prepare. To implement the plan, the Legislature passed the Central Valley Act of 1933, which authorized the project. Due to lack of funds, the federal government took over the CVP as a public works project to provide jobs and its construction began in 1935.In 1945, the California Legislature authorized an investigation of statewide water resources and in 1947, the California Legislature requested that an investigation be conducted of the water resources as well as present and future water needs for all hydrologic regions in the State. Accordingly, DWR and its predecessor agencies began to collect the urban and agricultural land use and water use data that serve as the basis for the computations of current and projected water uses.The work, conducted by the Division of Water Resources (DWR’s predecessor) under the Department of Public Works, led to the publication of three important bulletins: Bulletin 1 (1951), "Water Resources of California," a collection of data on precipitation, unimpaired stream flows, flood flows and frequency, and water quality statewide; Bulletin 2 (1955), "Water Utilization and Requirements of California," estimates of water uses and forecasts of "ultimate" water needs; and Bulletin 3 (1957), "The California Water Plan," plans for full practical development of California’s water resources, both by local projects and a major State project to meet the State's ultimate needs. (See brief addendum below* “The Development of Boundaries for Hydrologic Studies for the Sacramento Valley Region”)DWR subdivided California into study areas for planning purposes. The largest study areas are the ten hydrologic regions (HR), corresponding to the State’s major drainage basins. The next levels of delineation are the Planning Areas (PA), which in turn are composed of multiple detailed analysis units (DAU). The DAUs are often split by county boundaries, so are the smallest study areas used by DWR.The DAU/counties are used for estimating water demand by agricultural crops and other surfaces for water resources planning. Under current guidelines, each DAU/County has multiple crop and land-use categories. Many planning studies begin at the DAU or PA level, and the results are aggregated into hydrologic regions for presentation.Since 1950 DWR has conducted over 250 land use surveys of all or parts of California's 58 counties. Early land use surveys were recorded on paper maps of USGS 7.5' quadrangles. In 1986, DWR began to develop georeferenced digital maps of land use survey data, which are available for download. Long term goals for this program is to survey land use more frequently and efficiently using satellite imagery, high elevation digital imagery, local sources of data, and remote sensing in conjunction with field surveys.There are currently 58 counties and 278 DAUs in California.Due to some DAUs being split by county lines, the total number of DAU’s identifiable via DAU by County is 782.**ADDENDUM**The Development of Boundaries for Hydrologic Studies for the Sacramento Valley Region[Detailed Analysis Units made up of a grouping of the Depletion Study Drainage Areas (DSA) boundaries occurred on the Eastern Foothills and Mountains within the Sacramento Region. Other DSA’s were divided into two or more DAU’s; for example, DSA 58 (Redding Basin) was divided into 3 DAU’s; 143,141, and 145. Mountain areas on both the east and west side of the Sacramento River below Shasta Dam went from ridge top to ridge top, or topographic highs. If available, boundaries were set adjacent to stream gages located at the low point of rivers and major creek drainages.Later, as the DAU’s were developed, some of the smaller watershed DSA boundaries in the foothill and mountain areas were grouped. The Pit River DSA was split so water use in the larger valleys (Alturas area, Big Valley, Fall River Valley, Hat Creek) could be analyzed. A change in the boundary of the Sacramento Region mountain area occurred at this time when Goose Lake near the Oregon State Line was included as part of the Sacramento Region.The Sacramento Valley Floor hydrologic boundary was at the edge of the alluvial soils and slightly modified to follow the water bearing sediments to a depth of 200 feet or more. Stream gages were located on incoming streams and used as an exception to the alluvial soil boundary. Another exception to the alluvial boundary was the inclusion of the foothills between Red Bluff and the Redding Basin. Modifications of the valley floor exterior boundary were made to facilitate analysis; some areas at the northern end of the valley followed section lines or other established boundaries.Valley floor boundaries, as originally shown in Bulletin 2, Water Utilization and Requirements of California, 1955 were based on physical topographic features such as ridges even if they only rise a few feet between basins and/or drainage areas. A few boundaries were based on drainage canals. The Joint DWR-USBR Depletion Study Drainage Areas (DSA) used drainage areas where topographic highs drained into one drainage basin. Some areas were difficult to study, particularly in areas transected by major rivers. Depletion Study Drainage Areas containing large rivers were separated into two DAU’s; one on each side of the river. This made it easier to analyze water source, water supply, and water use and drainage outflow from the DAU.Many of the DAUs that consist of natural drainage basins have stream gages located at outfall gates, which provided an accurate estimate of water leaving the unit. Detailed Analysis Units based on political boundaries or other criteria are much more difficult to analyze than those units that follow natural drainage basins.]**END ADDENDUM**.............................................................................................................................................cnty18_1 metadata Summary:(*See metadata for CAL-FIRE cnty18_1). CAL-FIRE cnty18_1 boundary feature class is used for cartographic purposes, for generating statistical data, and for clipping data. Ideally, state and federal agencies should be using the same framework data for common themes such as county boundaries. This layer provides an initial offering as "best available" at 1:24,000 scale.cnty18_1 metadata Description:(*See metadata for CAL-FIRE cnty18_1).cnty18_1 metadata Credits:CAL-FIRE cnty18_1 metadata comment:This specific dataset represents the full detailed county dataset with all coding (islands, inlets, constructed features, etc.). The user has the freedom to use this coding to create definition queries, symbolize, or dissolve to create a more generalized dataset as needed.In November 2015, the dataset was adjusted to include a change in the Yuba-Placer county boundary from 2010 that was not yet included in the 14_1 version of the dataset (ord. No. 5546-B). This change constitutes the difference between the 15_1 and 14_1 versions of this dataset.In March 2018, the dataset was adjusted to include a legal boundary change between Santa Clara and Santa Cruz Counties (December 11, 1998) as stated in Resolution No. 98-11 (Santa Clara) and Resolution No. 432-98 (Santa Cruz). This change constitutes the difference between the 18_1 and 15_1 versions of this dataset.(*See metadata for CAL-FIRE cnty18_1). - U.S. Bureau of Reclamation, California Department of Conservation, California Department of Fish and Game, California Department of Forestry and Fire protection

Every 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 2014 Santa Clara 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 were 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 Santa Clara County conducted by the California Department of Water Resources, North Central Regional Office staff. Land use field boundaries were digitized with ArcGIS 10.3 using 2012 U.S.D.A National Agriculture Imagery Program (NAIP) one-meter imagery as the base. Agricultural fields were delineated by following actual field boundaries instead of using the centerlines of roads to represent the field borders. Field boundaries were reviewed and updated using 2014 Landsat 8 imagery and 2014 U.S.D.A National Agriculture Imagery Program (NAIP) one-meter imagery after it became available in late 2014. The county boundary is based on the CalFire updated State and County boundary layer dated 2009. Field boundaries were not drawn to represent legal parcel (ownership) boundaries, and are not meant to be used as parcel boundaries. The field work for this survey was conducted from June 16, 2014 through July 24, 2014. Images, land use boundaries and ESRI ArcMap software were loaded onto laptop computers that were used as the field data collection tools. Staff took these laptops into the field and virtually all agricultural fields were visited to identify the land use. Global positioning System (GPS) units connected to the laptops were used to confirm the surveyor's location with respect to the fields. Land use codes were digitized in the field using dropdown selections from defined domains. Upon completion of the survey, a Python script was used to convert the data table into the standard land use format. ArcGIS geoprocessing tools and topology rules were used to locate errors for quality control. The primary focus of this land use survey is mapping agricultural fields. Urban residences and other urban areas were delineated using aerial photo interpretation. Some urban areas may have been missed. Rural residential land use was delineated by drawing polygons to surround houses and other buildings along with some of the surrounding land. These footprint areas do not represent the entire footprint of urban land. Sources of irrigation water were not identified for most areas. The exception is the area of the Corde Valle Golf Course near San Martin and a few nearby fields where recycled water is used as a water source in addition to groundwater. 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.

Contour2006 is a Polyline Shapefile of contours generated from LiDAR data for the San Jose Phase 3 project of Santa Clara County, Ca. The purpose of the bare-earth LiDAR Point and Breakline data is to provide ground surface data and one-foot (Valley Area) and five-foot (Mountain Areas) contour generation, and the delineation of watercourse ( Top of Bank ). LAS format files, raw LiDAR data in its native format, classified bare-earth LiDAR DEM and photogrammetrically derived breaklines generated from LiDAR Intensity stereo-pairs. Breakline, Top of Bank, and contour files in ESRI personal geodatabase format, Microstation V8 .dgn format, and AutoCAD 2004 formats for the San Jose Phase 3 project of Santa Clara County, Ca. It is primarily used to model elevation and as a reference layer. Contour2006 has the following fields:

OBJECTID_1: Unique identifier automatically generated by Esri type: OID, length: 4, domain: none

TYPE: The type of contour line type: String, length: 25, domain: none

ELEVATION: The elevation of the contour line - in feet type: Double, length: 8, domain: none

Shape_Leng: The length of the shape - in feet type: Double, length: 8, domain: none

TILE_ID: The unique ID associated with the tile type: String, length: 9, domain: none

ObjectID: Unique identifier automatically generated by Esri type: Integer, length: 4, domain: none

Shape: Field that stores geographic coordinates associated with feature type: Geometry, length: 4, domain: none

Shape_Length: The length of the shape - in feet type: Double, length: 0, domain: none

BAARI (Bay Area Aquatic Resource Inventory) was established to meet regional needs for wetlands and stream monitoring. One primary objective was to apply standardized monitoring tools to ensure data comparability and consistent, documented quality. These data help agencies and organizations assess the extent and condition of wetlands in local watersheds and identify and prioritize opportunities for ecological restoration and enhancement in a watershed context.BackgroundBAARI data is part of the Wetland and Riparian Area Monitoring Plan (WRAMP), which consists of a 1-2-3 level monitoring framework. This allows assessment of wetlands at two scales: landscape and highly localized. BAARI is Level 1 of this framework, developed for landscape level analyses of wetland extent, distribution and abundance. Geographic information systems (GIS) and remote sensing are used to map and create inventories of existing wetlands (both modern and historical). These inventories quantify the extent of wetland habitats and projects, and are used for landscape profiles of wetlands at the state, regional, watershed, and local scales. Level 2 entails rapid field assessment of wetland health or ecological condition. In California the California Rapid Assessment Method (CRAM) is a diagnostic tool that two or more trained practitioners can use to assess the condition of a wetland or riparian site in one half day or less using visual indicators in the field. Level 3 monitoring entails intensive sampling of ecological function or specific aspects of wetland condition. These assessments are intensive quantitative measurements of condition, stress, or cause-and-effect relationships. A Level 3 assessment is an in-depth study of a particular attribute of wetland health such as water quality, fish habitat, bird populations, vegetative cover and diversity, or physical processes. Level 3 monitoring can describe the performance of specific ecological functions at the site scale. Information on the WRAMP is available at http://www.mywaterquality.ca.gov/eco_health/wetlands/condition/wramp_toolkit.shtmlMore information on BAARI can be found online at: http://www.sfei.org/BAARI. Description of Updates in Version 2.1Added channels in Santa Clara County based on the Santa Clara Valley Water District's 2004 stream layer, available at http://data-valleywater.opendata.arcgis.com/datasets/e74548aaba0e46918523d62645e283fd_9 . Presence of these channels was confirmed in recent aerial imagery. Streams added include teh Permanente Diversion Channel, Upper Sunnyvale West Channel (The upper portion is also referred to as Moffett Channel, sections of teh Vasona Canal. Page Channel also reclassified from a 'Ditch' (FD) to an 'Engineered Channel (FEC)In the Petaluma River Watershed, another SFEI study mapped a few channels in great detail using a Lidar derived DEM. These channels were incorporated into BAARI. Also, a depressional wetland was reclassified as Unnatural (DOWU)Ran topology on the streams layer and corrected small errors. This included removing small segments >50m long, and correcting some overlaps and self-intersections.Description of Updates in Version 2Local experts provided advice on and reviewed BAARI’s stream, wetland and riparian GIS layers in specific locations to help update the data as conditions in the field changed and/or to increase its accuracy and detail. Improving the accuracy and detail of BAARI improves the base maps for all monitoring and assessment efforts to understand the distribution, amount and ecological condition of Bay Area aquatic resources. The following updates were made to BAARI under this project:The Santa Clara Valley Water District (SCVWD) provided their GIS based stream data for the Guadalupe River Watershed. SFEI’s GIS team incorporated parts of the SCVWD dataset into BAARI to improve the accuracy and detail of the BAARI stream layer with the Guadalupe River watershed. Updates included features such as underground connectors between the upper and lower watershed reaches, and enhanced details of portions of the upper watershed. Watershed Sciences developed six hand-drawn maps showing field verified ditch locations circa 2006. Those data were used in developing the sediment TMDL for the watershed. Watershed sciences provided those maps to SFEI’s GIS team and worked with them to compare the remotely sensed stream and ditch locations in the BAARI data set (based on 2009 NAIP imagery) to her maps and other data (including Google Earth using multiple image dates). Based on this careful comparative process, about 500 linear updates were made to the BAARI stream layer for the Sonoma Creek watershed with the data source attributed to Laurel Collins’ maps. SFEI staff added stream names for the whole BAARI dataset (Bay Area 9 counties, ocean shoreline, and Tomales Bay - 530 different names applied to more than 24000 stream segments).Additional corrections to wetland and stream presence, extent, and classification were appended to the dataset by SFEI staff where inaccuracies were identified based on local expertise of wetlands in the Bay Area.All BAARI updates were reviewed by a second GIS staff member to ensure that they were acceptable and followed BAARI mapping protocols. Description of Attribute Fields in BAARIBaylandsRestProj: restoration project associated with this wetland. This field has not been updated in version 2. Refer to http://www.EcoAtlas.org for current listings of ecological restoration projects. Source_Dat: source(s) from which the wetland polygon was digitized, or otherwise incorporated into BAARIWetlandTyp: Coded classification of the wetland type. Codes are defined on p5-6 of "BAARI Mapping Standards" Organization: organization that digitized the wetland polygonClickCode: simplification of the 'WetlandTyp' attribute used for map database queries in web mapping applications such as http://www.EcoAtlas.org. Refers to the standardized wetland classification system employed by the California Aquatic Resources Inventory (CARI). More information about CARI is available at http://www.sfei.org/it/gis/cari ClickLabel: verbal description of the ClickCode codeLegCode: further simplification of the 'WetlandTyp' attribute used in the legends of web mapping applications such as http://www.EcoAtlas.orgLegLabel: verbal description of the LegCode codeORIG_FID: unusedOpenWater: Open Water (1) or a wetland (0)TidRip: unusedGlobalID: Unique identifier, if one exists StreamsWetlandTyp: Coded classification of the stream type. Codes are defined on p9-10 of "BAARI Mapping Standards" Bayland: Identifies whether the feature falls within the historical extent of the Baylands (1) or not (0)Strahler: Strahler stream order of the stream segment.ClickCode: simplification of the 'WetlandTyp' attribute used for map database queries in web mapping applications such as http://www.EcoAtlas.orgClickLabel: verbal description of the ClickCode codeLegCode: further simplification of the 'WetlandTyp' attribute used in the legends of web mapping applications such as http://www.EcoAtlas.orgLegLabel: verbal description of the LegCode codeGlobalID: Unique identifier, if one exists (e.g. ReachCode attribute in NHD)IDNum: Numerical version of GlobalIDStreamName: the recognized Geographic Names Information System (GNIS) name of the streamSource_Dat: source(s) from which the segment was digitized, or otherwise incorporated into BAARI.Name_Source: source from which 'StreamName' was identifiedFNode: "From Node" used to determine stream flow directionTNode: "To Node" used to determine stream flow directionLegHeader: legend header used in the legends of web mapping applications such as http://www.EcoAtlas.orgTMDL_DATA: "Yes" value indicates TMDL data is available for this stream segment. Contact SFEI for information about integrating TMDL data with BAARIWetlands (Non-tidal)WetlandTyp: Coded classification of the wetland type. Codes are defined on p6-9 of "BAARI Mapping Standards" SourceData: source(s) from which the wetland polygon was digitized, or otherwise incorporated into BAARIOrganization: organization that digitized the wetland polygonClickCode: simplification of the 'WetlandTyp' attribute used for map database queries in web mapping applications such as http://www.EcoAtlas.orgClickLabel: verbal description of the ClickCode codeLegCode: further simplification of the 'WetlandTyp' attribute used in the legends of web mapping applications such as http://www.EcoAtlas.orgLegLabel: verbal description of the LegCode codeGlobalID: Unique identifier, if one exists