This shapefile contains tax rate area (TRA) boundaries in Monterey County for the specified assessment roll year. Boundary alignment is based on the 2023 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

Geospatial data about Monterey County, California Hydrants. Export to CAD, GIS, PDF, CSV and access via API.

This digital dataset was created as part of a U.S. Geological Survey study, done in cooperation with the Monterey County Water Resource Agency, to conduct a hydrologic resource assessment and develop an integrated numerical hydrologic model of the hydrologic system of Salinas Valley, CA. As part of this larger study, the USGS developed this digital dataset of geologic data and three-dimensional hydrogeologic framework models, referred to here as the Salinas Valley Geological Framework (SVGF), that define the elevation, thickness, extent, and lithology-based texture variations of nine hydrogeologic units in Salinas Valley, CA. The digital dataset includes a geospatial database that contains two main elements as GIS feature datasets: (1) input data to the 3D framework and textural models, within a feature dataset called “ModelInput”; and (2) interpolated elevation, thicknesses, and textural variability of the hydrogeologic units stored as arrays of polygonal cells, within a feature dataset called “ModelGrids”. The model input data in this data release include stratigraphic and lithologic information from water, monitoring, and oil and gas wells, as well as data from selected published cross sections, point data derived from geologic maps and geophysical data, and data sampled from parts of previous framework models. Input surface and subsurface data have been reduced to points that define the elevation of the top of each hydrogeologic units at x,y locations; these point data, stored in a GIS feature class named “ModelInputData”, serve as digital input to the framework models. The location of wells used a sources of subsurface stratigraphic and lithologic information are stored within the GIS feature class “ModelInputData”, but are also provided as separate point feature classes in the geospatial database. Faults that offset hydrogeologic units are provided as a separate line feature class. Borehole data are also released as a set of tables, each of which may be joined or related to well location through a unique well identifier present in each table. Tables are in Excel and ascii comma-separated value (CSV) format and include separate but related tables for well location, stratigraphic information of the depths to top and base of hydrogeologic units intercepted downhole, downhole lithologic information reported at 10-foot intervals, and information on how lithologic descriptors were classed as sediment texture. Two types of geologic frameworks were constructed and released within a GIS feature dataset called “ModelGrids”: a hydrostratigraphic framework where the elevation, thickness, and spatial extent of the nine hydrogeologic units were defined based on interpolation of the input data, and (2) a textural model for each hydrogeologic unit based on interpolation of classed downhole lithologic data. Each framework is stored as an array of polygonal cells: essentially a “flattened”, two-dimensional representation of a digital 3D geologic framework. The elevation and thickness of the hydrogeologic units are contained within a single polygon feature class SVGF_3DHFM, which contains a mesh of polygons that represent model cells that have multiple attributes including XY location, elevation and thickness of each hydrogeologic unit. Textural information for each hydrogeologic unit are stored in a second array of polygonal cells called SVGF_TextureModel. The spatial data are accompanied by non-spatial tables that describe the sources of geologic information, a glossary of terms, a description of model units that describes the nine hydrogeologic units modeled in this study. A data dictionary defines the structure of the dataset, defines all fields in all spatial data attributer tables and all columns in all nonspatial tables, and duplicates the Entity and Attribute information contained in the metadata file. Spatial data are also presented as shapefiles. Downhole data from boreholes are released as a set of tables related by a unique well identifier, tables are in Excel and ascii comma-separated value (CSV) format.

This database was designed in response to the Director Memorandum - "Effective January 1, 2019 all structure greater than 120 square feet in the State Responsibility Area (SRA) damaged by wildfire will be inspected and documented in the DINS Collector App."To document structures damaged or destroyed by the 2023 Pineapple Express flooding in Monterey County open the associated Field Map app.NOTE - this feature service is configured to not allow record deletion. If a record needs to be deleted contact the program manager below.This is the schema developed and used by the CAL FIRE Office of State Fire Marshal to assess and record structure damage on flooding incidents. The schema is designed to be configured in the Esri Collector/Field Maps app for data collection during or after an incident.

This service consumes Caltrans Lane Closure System CSV format for District 5: https://cwwp2.dot.ca.gov/data/d5/lcs/lcsStatusD05.csv It then queries where beginCounty or endCounty is equal to Monterey County. It uses the endLatitude and endLongitude values to plot the lane closure locations.

Waters off the coast of California are split into five distinct groundfish management areas used in the regulation and management of groundfish fisheries. All fishing areas extend from the shoreline to 200 miles offshore. The latitudinal boundaries for each fishing area are as follows: Northern Management Area: The California-Oregon border to Cape Mendocino (40°10' N. latitude) Mendocino Management Area: Cape Mendocino (40°10' N. latitude) to Point Arena (38°57.5' N. latitude) San Francisco Management Area: Point Arena (38°57.5' N. latitude) to Pigeon Point (37°11' N. latitude) Central Management Area: Pigeon Point (37°11' N. latitude) to Point Conception (34°27' N. latitude) Within the Central Groundfish Management Area, seasons and depth restrictions may differ north and south of a line extending west of 36° N. lat. (near Point Lopez, Monterey County). The areas north and south of this line are referred to as the Central Groundfish Management Area – North 36° N. lat. and the Central Groundfish Management Area – South of 36° N. lat. Southern Management Area: Point Conception (34°27' N. latitude) to the U.S.-Mexico border Attributes: Region: Northern, Mendocino, San Francisco, Central, Southern. Detail: Latitudinal boundaries of management areas.

The 1997 Monterey County land use survey data set was developed by DWR through its Division of Planning and Local Assistance (DPLA). This survey is unique in that three site visits were completed in the area. Each of the three site visits was digitized as a separate survey, the Salinas Valley in the spring, the entire county in the summer, and the Salinas Valley in the fall. The data was gathered using aerial photography and extensive field visits, the land use boundaries and attributes were digitized, and the resultant data went through standard quality control procedures before finalizing. The land uses that were gathered were detailed agricultural land uses, and lesser detailed urban and native vegetation land uses. The data was gathered and digitized by staff of DWR’s San Joaquin District. Quality control procedures were performed jointly by staff at DWR’s DPLA headquarters and San Joaquin District. The finalized data includes one countywide shapefile, two Salinas Valley shapefiles (land use vector data) and JPEG files (raster data from aerial imagery). Important Points about Using this Data Set: 1. The land use boundaries were either drawn on-screen using developed photoquads, or hand drawn directly on USGS quad maps and then digitized. They were drawn to depict observable areas of the same land use. They were not drawn to represent legal parcel (ownership) boundaries, or meant to be used as parcel boundaries. 2. For the Salinas Valley portion of Monterey County, the survey was not a "snapshot" in time, but incorporated three field visits for agricultural areas. The land use attributes of each delineated area (polygon) were based upon the surveyor’s observations in the field at those times. For the DWG and shapefiles, the attributes in the files are the observations, not the interpreted results. 3. For the area of Monterey County outside of the Salinas Valley, the survey was a "snapshot" in time (summer). The indicated land use attributes of each delineated area (polygon) were based upon what the surveyor saw in the field at that time, and, to an extent possible, whatever additional information the aerial photography might provide. For example, the surveyor might have seen a cropped field in the photograph, and the field visit showed a field of corn, so the field was given a corn attribute. In another field, the photograph might have shown a crop that was golden in color (indicating grain prior to harvest), and the field visit showed newly planted corn. This field would be given an attribute showing a double crop, grain followed by corn. The DWR land use attribute structure allows for up to three crops per delineated area (polygon). In the cases where there were crops grown before the survey took place, the surveyor may or may not have been able to detect them from the field or the photographs. For crops planted after the survey date, the surveyor could not account for these crops. Thus, although the data is very accurate for that point in time, it may not be an accurate determination of what was grown in the fields for the whole year. If the area being surveyed does have double or multicropping systems, it is likely that there are more crops grown than could be surveyed with a "snapshot". 3. If the data is to be brought into a GIS for analysis of cropped (or planted) acreage, two things must be understood: a. The acreage of each field delineated is the gross area of the field. The amount of actual planted and irrigated acreage will always be less than the gross acreage, because of ditches, farm roads, other roads, farmsteads, etc. Thus, a delineated corn field may have a GIS calculated acreage of 40 acres but will have a smaller cropped (or net) acreage, maybe 38 acres. b. Double and multicropping must be taken into account. A delineated field of 40 acres might have been cropped first with grain, then with corn, and coded as such. To estimate actual cropped acres, the two crops are added together (38 acres of grain and 38 acres of corn) which results in a total of 76 acres of net crop (or planted) acres. 4. Water source and irrigation method information were not collected for this survey. 5. Not all land use codes will be represented in the survey.

This dataset is a subset of the authoritative 2018 FMMP shapefiles sourced from California's Department of Conservation Farmland Mapping & Monitoring Program website at https://www.conservation.ca.gov/dlrp/fmmp. This dataset only displays Important Farmlands within Monterey County limits.Established in 1982, Government Code Section 65570 mandates FMMP to biennially report on the conversion of farmland and grazing land, and to provide maps and data to local government and the public.The Farmland Mapping and Monitoring Program (FMMP) provides data to decision makers for use in planning for the present and future use of California's agricultural land resources. The data is a current inventory of agricultural resources. This data is for general planning purposes and has a minimum mapping unit of ten acres.

CDFW BIOS GIS Dataset, Contact: U.S. Fish & Wildlife Service USFWS, Description: These data identify the areas (in general) where final critical habitat for the purple amole (Chloragalum purpureum var. purpureum) occurs. Critical habitat for the species lies immediately adjacent to Fort Hunter Liggett in Monterey County, California.

PRC 4201 - 4204 and Govt. Code 51175-89 direct the California Department of Forestry and Fire Protection (CAL FIRE) to map areas of significant fire hazards based on fuels, terrain, weather, and other relevant factors. These zones, referred to as Fire Hazard Severity Zones (FHSZ), define the application of various mitigation strategies to reduce risk associated with wildland fires.

CAL FIRE is remapping Fire Hazard Severity Zones (FHSZ) for State Responsibility Areas (SRA) and Very High Fire Hazard Severity Zones (VHFHSZ) recommendations in Local Responsibility Areas (LRA) to provide updated map zones, based on new data, science, and technology.

This specific dataset provides FHSZs within SRA lands only, and represents the proposed zones, subject to changes based on local hearings. A subsequent dataset release will provide the actual adopted zones.

Maps of the proposed zones in SRA are available at: http://frap.cdf.ca.gov/projects/hazard/fhz.html More information about the project can be found at: http://frap.cdf.ca.gov/projects/hazard/hazard.html

This web map displays roads within unincorporated Monterey County, CA that are closed or are under traffic advisory, according to Monterey County PWFP-Public Works. This map is regularly maintained by Monterey County PWFP and is subject to change depending on conditions. For additional information, contact Monterey County Public Works at (831)755-4925. This map does not display closed roads within City Limits or highways and roads maintained by Caltrans.

LAFCO is responsible for regulating the boundaries of cities and special districts, establishing Spheres of Influence, and conducting studies of local government services. The Commission coordinates logical and timely changes to local government boundaries including annexations and detachments of territory, incorporation of cities, formation of special districts, and consolidation, merger, and dissolution of special districts. LAFCO is also charged with reviewing and approving ways to reorganize, simplify, and streamline governmental organizations.For more information about Monterey County's County Service Areas, visit LAFCO's website at https://www.co.monterey.ca.us/government/government-links/lafco.

The study area for this project was Garrapata State Park in northwestern Monterey County, California. Development of Garrapata State Park land by Spanish missionaries began in the late 1700s (Costanoan Rumsen Carmel Tribe 2001). Cattle ranching on the land began in the 1830s with land grants to ranchers, beginning a long stint of grazing on most of the land south of the Carmel River. In 1980, the state of California began purchasing parcels of land and the area was officially classified as a state park in 1985 (Garrapata State Park Monterey Sector 2003).Garrapata State Park encompasses 2,866 acres along the pacific coast, immediately south of Carmel Highlands. The area is largely dominated by steep foothills of the coastal Santa Lucia Range and is dissected by several steep creeks: Wildcat Creek, Malpaso Creek, Soberanes Creek, Doud Creek and Granite Creek. Elevation ranges from sea level to 2,011 ft atop Rocky Ridge. The park also contains an approximately 4.1-mile stretch of coastal bluff, rocky intertidal zone, and beach west of Highway. The park''s Mediterranean climate is characterized by dry summers and cool wet winters and receives approximately 28 inches of mean annual precipitation (PRISM 2012). Wildfire is a prominent disturbance in this landscape; the Soberanes Fire which began in Garrapata State Park in 2016 was one of the largest fires recorded in California history, burning 132,127 acres (CAL Fire 2016).The National Vegetation Classification System allows vegetation to be mapped at three broad levels— physiognomy, biogeography, and floristics—each of which can be broken down into multiple sublevels (USNVC 2020). Floristic-level mapping provides the finest resolution and is the only level to reflect local environmental conditions. Such fine-scale data resolution helps establish a more precise inventory of native and non-native vegetation communities, which benefits land managers interested in protecting valued natural resources, monitoring fuel loads for fire management, and understanding habitat requirements of wildlife. We attempted to map vegetation communities to the alliance sublevel, which is the broadest sublevel at the floristic level of mapping. We did not attempt to map associations, which occur at the level below alliances.Vegetation community mapping comprised preliminary delineation of somewhat homogeneous vegetation stands, field-based classification of alliances and other mapping units, and quality assurance. We first estimated the boundaries of stands using aerial and satellite-derived orthoimagery which were later classified through field observations. Most of the stands we mapped were conformant with previously defined alliances. Non-conformant stands were classified within novel mapping units, defined in Appendix B. We also used novel mapping units for two situations where the exact alliance could not be readily determined in fall; these classes were “Willows” and “Unidentified annual grasses”.We examined aerial and satellite imagery to initially digitize polygons around areas where vegetation looked homogenous and distinct from surrounding areas. We used a mosaic of natural color (red, green, blue [RGB] band) and color infrared (CIR) National Agriculture Imagery Program (NAIP) orthophotos to conduct initial digitizing of vegetation alliance polygons. Polygons were delineated based on areas of visible homogeneity within the landscape; breaks or abrupt changes in color, structure, or relative height of vegetation usually indicated the need to create separate vegetation community polygons. We established minimum mapping units (MMUs) of 0.25 acres for common mapping units and 0.1 acres for uncommon classes, to maximize the level of detail conveyed in vegetation maps given time constraints and clarity of aerial and satellite imagery. The status of each vegetation community polygon was indicated as “unconfirmed” until field crews verified whether initial delineations were correct.Polygons were classified based on the dominant species composition of each polygon. Classification rules were based on rules provided by CNPS, and where rules contradicted each other, we adopted a rule based on either the most recent or the most locally relevant CNPS-listed rule. Most rules were based on the percent cover of the tallest stratum of vegetation. Rules for novel mapping units were that the nominate dominant species should have 50% relative cover.The vegetation map was prepared for publication in California Department of Fish and Wildlifes Biogeographic Information and Observation System by staff from the Vegetation Classification and Mapping Program.

LAFCO is responsible for regulating the boundaries of cities and special districts, establishing Spheres of Influence, and conducting studies of local government services. The Commission coordinates logical and timely changes to local government boundaries including annexations and detachments of territory, incorporation of cities, formation of special districts, and consolidation, merger, and dissolution of special districts. LAFCO is also charged with reviewing and approving ways to reorganize, simplify, and streamline governmental organizations.For more information about Monterey County's Community Service Districts, visit LAFCO's website at https://www.co.monterey.ca.us/government/government-links/lafco.

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