Polygonal data representing the fire protection districts within Monterey County, CA, per LAFCO of Monterey County. Last updated August 2020.

This point shapefile represents parks within Monterey County, California. This layer is part of a collection of GIS data for Monterey County in California.

1,3-D application map layers include a layer which depicts the total number of 1,3-D applications in each section in Monterey County summed for the years 2018-2023 and seperate map layers which depict the total number of 1,3-D applications for each section in Monterey County for each of the individual years. 1,3-D application layers are slightly transparent to facilitate visiallization of underlying field/ranch boundaires which cross section lines. CSCD school sites located in Monterey County are grouped and symbolized seperately from those in other parts of California and the two groups can be toggled on and off independently so that schools near the Monterey county boundary can be clearly distinguished.

This shapefile contains tax rate area (TRA) boundaries in Monterey County for the specified assessment roll year. Boundary alignment is based on the 2009 county parcel map. A tax rate area (TRA) is a geographic area within the jurisdiction of a unique combination of cities, schools, and revenue districts that utilize the regular city or county assessment roll, per Government Code 54900. Each TRA is assigned a six-digit numeric identifier, referred to as a TRA number. TRA = tax rate area number

This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data.

Summarizes data submitted to State of California for agricultural considerations.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands†from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Pigeon Point to South Monterey Bay Region includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both vid... Visit https://dataone.org/datasets/624b6171-c94b-4c32-ad93-58a0165230e7 for complete metadata about this dataset.

This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data.

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.

CDFW BIOS GIS Dataset, Contact: Robert Holland, Description: Vernal pools in five counties along the California central coast (Monterey, San Benito, Santa Barbara, San Luis Obispo, and Ventura counties) were mapped from one-meter resolution digital orthophoto quadrangles from USGS.

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.

Summarizes data submitted to State of California for agricultural considerations.

This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data.

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.

This point shapefile represents hospitals in Monterey County, California. This layer is part of a collection of GIS data for Monterey County in California.

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 Wildlife's Biogeographic Information and Observation System by staff from the Vegetation Classification and Mapping Program.

This point shapefile represents public libraries in Monterey County, California. This layer is part of a collection of GIS data for Monterey County in California.

This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data.

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.

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.