The purpose of this project was to describe each of the native and naturalized vegetation types known to occur within western San Diego County and to provide the user a means to determine each type through direct observations of species composition. The classification presented herein is the result of a detailed analysis of data collected throughout the western San Diego County study area. Under contract to the San Diego Association of Governments (SANDAG), Biologists from AECOM, Conservation Biology Institute, and the California Department of Fish and Game (CDFG) Vegetation Classification and Mapping Program (VegCAMP) collaborated on these analyses, the definition of the classifications, and preparation of this manual. This classification study was conducted in a manner consistent with the recommendations for standardized data collection and analysis by CDFG VegCAMP (https://wildlife.ca.gov/Data/VegCAMP) and the methods used in the preparation of A Manual of California Vegetation, 2nd ed. (Sawyer; Keeler-Wolf; Evens 2009), published by the California Native Plant Society (CNPS). This projects classifications is in accordance with this larger work. A Manual of California Vegetation (MCV) is intentionally consistent within the larger context of the National Vegetation Classification System (NVCS), which has been adopted by federal agencies and nongovernmental organizations such as the US Geological Survey, National Park Service, and NatureServe. Thus each of these classifications can be compared in context with the others nationwide.

WARNING: This is a pre-release dataset and its fields names and data structures are subject to change. It should be considered pre-release until the end of 2024. Expected changes:Metadata is missing or incomplete for some layers at this time and will be continuously improved.We expect to update this layer roughly in line with CDTFA at some point, but will increase the update cadence over time as we are able to automate the final pieces of the process.This dataset is continuously updated as the source data from CDTFA is updated, as often as many times a month. If you require unchanging point-in-time data, export a copy for your own use rather than using the service directly in your applications.PurposeCounty and incorporated place (city) boundaries along with third party identifiers used to join in external data. Boundaries are from the authoritative source the California Department of Tax and Fee Administration (CDTFA), altered to show the counties as one polygon. This layer displays the city polygons on top of the County polygons so the area isn"t interrupted. The GEOID attribute information is added from the US Census. GEOID is based on merged State and County FIPS codes for the Counties. Abbreviations for Counties and Cities were added from Caltrans Division of Local Assistance (DLA) data. Place Type was populated with information extracted from the Census. Names and IDs from the US Board on Geographic Names (BGN), the authoritative source of place names as published in the Geographic Name Information System (GNIS), are attached as well. Finally, the coastline is used to separate coastal buffers from the land-based portions of jurisdictions. This feature layer is for public use.Related LayersThis dataset is part of a grouping of many datasets:Cities: Only the city boundaries and attributes, without any unincorporated areasWith Coastal BuffersWithout Coastal BuffersCounties: Full county boundaries and attributes, including all cities within as a single polygonWith Coastal BuffersWithout Coastal BuffersCities and Full Counties: A merge of the other two layers, so polygons overlap within city boundaries. Some customers require this behavior, so we provide it as a separate service.With Coastal Buffers (this dataset)Without Coastal BuffersPlace AbbreviationsUnincorporated Areas (Coming Soon)Census Designated Places (Coming Soon)Cartographic CoastlinePolygonLine source (Coming Soon)Working with Coastal BuffersThe dataset you are currently viewing includes the coastal buffers for cities and counties that have them in the authoritative source data from CDTFA. In the versions where they are included, they remain as a second polygon on cities or counties that have them, with all the same identifiers, and a value in the COASTAL field indicating if it"s an ocean or a bay buffer. If you wish to have a single polygon per jurisdiction that includes the coastal buffers, you can run a Dissolve on the version that has the coastal buffers on all the fields except COASTAL, Area_SqMi, Shape_Area, and Shape_Length to get a version with the correct identifiers.Point of ContactCalifornia Department of Technology, Office of Digital Services, odsdataservices@state.ca.govField and Abbreviation DefinitionsCOPRI: county number followed by the 3-digit city primary number used in the Board of Equalization"s 6-digit tax rate area numbering systemPlace Name: CDTFA incorporated (city) or county nameCounty: CDTFA county name. For counties, this will be the name of the polygon itself. For cities, it is the name of the county the city polygon is within.Legal Place Name: Board on Geographic Names authorized nomenclature for area names published in the Geographic Name Information SystemGNIS_ID: The numeric identifier from the Board on Geographic Names that can be used to join these boundaries to other datasets utilizing this identifier.GEOID: numeric geographic identifiers from the US Census Bureau Place Type: Board on Geographic Names authorized nomenclature for boundary type published in the Geographic Name Information SystemPlace Abbr: CalTrans Division of Local Assistance abbreviations of incorporated area namesCNTY Abbr: CalTrans Division of Local Assistance abbreviations of county namesArea_SqMi: The area of the administrative unit (city or county) in square miles, calculated in EPSG 3310 California Teale Albers.COASTAL: Indicates if the polygon is a coastal buffer. Null for land polygons. Additional values include "ocean" and "bay".GlobalID: While all of the layers we provide in this dataset include a GlobalID field with unique values, we do not recommend you make any use of it. The GlobalID field exists to support offline sync, but is not persistent, so data keyed to it will be orphaned at our next update. Use one of the other persistent identifiers, such as GNIS_ID or GEOID instead.AccuracyCDTFA"s source data notes the following about accuracy:City boundary changes and county boundary line adjustments filed with the Board of Equalization per Government Code 54900. This GIS layer contains the boundaries of the unincorporated county and incorporated cities within the state of California. The initial dataset was created in March of 2015 and was based on the State Board of Equalization tax rate area boundaries. As of April 1, 2024, the maintenance of this dataset is provided by the California Department of Tax and Fee Administration for the purpose of determining sales and use tax rates. The boundaries are continuously being revised to align with aerial imagery when areas of conflict are discovered between the original boundary provided by the California State Board of Equalization and the boundary made publicly available by local, state, and federal government. Some differences may occur between actual recorded boundaries and the boundaries used for sales and use tax purposes. The boundaries in this map are representations of taxing jurisdictions for the purpose of determining sales and use tax rates and should not be used to determine precise city or county boundary line locations. COUNTY = county name; CITY = city name or unincorporated territory; COPRI = county number followed by the 3-digit city primary number used in the California State Board of Equalization"s 6-digit tax rate area numbering system (for the purpose of this map, unincorporated areas are assigned 000 to indicate that the area is not within a city).Boundary ProcessingThese data make a structural change from the source data. While the full boundaries provided by CDTFA include coastal buffers of varying sizes, many users need boundaries to end at the shoreline of the ocean or a bay. As a result, after examining existing city and county boundary layers, these datasets provide a coastline cut generally along the ocean facing coastline. For county boundaries in northern California, the cut runs near the Golden Gate Bridge, while for cities, we cut along the bay shoreline and into the edge of the Delta at the boundaries of Solano, Contra Costa, and Sacramento counties.In the services linked above, the versions that include the coastal buffers contain them as a second (or third) polygon for the city or county, with the value in the COASTAL field set to whether it"s a bay or ocean polygon. These can be processed back into a single polygon by dissolving on all the fields you wish to keep, since the attributes, other than the COASTAL field and geometry attributes (like areas) remain the same between the polygons for this purpose.SliversIn cases where a city or county"s boundary ends near a coastline, our coastline data may cross back and forth many times while roughly paralleling the jurisdiction"s boundary, resulting in many polygon slivers. We post-process the data to remove these slivers using a city/county boundary priority algorithm. That is, when the data run parallel to each other, we discard the coastline cut and keep the CDTFA-provided boundary, even if it extends into the ocean a small amount. This processing supports consistent boundaries for Fort Bragg, Point Arena, San Francisco, Pacifica, Half Moon Bay, and Capitola, in addition to others. More information on this algorithm will be provided soon.Coastline CaveatsSome cities have buffers extending into water bodies that we do not cut at the shoreline. These include South Lake Tahoe and Folsom, which extend into neighboring lakes, and San Diego and surrounding cities that extend into San Diego Bay, which our shoreline encloses. If you have feedback on the exclusion of these items, or others, from the shoreline cuts, please reach out using the contact information above.Offline UseThis service is fully enabled for sync and export using Esri Field Maps or other similar tools. Importantly, the GlobalID field exists only to support that use case and should not be used for any other purpose (see note in field descriptions).Updates and Date of ProcessingConcurrent with CDTFA updates, approximately every two weeks, Last Processed: 12/17/2024 by Nick Santos using code path at https://github.com/CDT-ODS-DevSecOps/cdt-ods-gis-city-county/ at commit 0bf269d24464c14c9cf4f7dea876aa562984db63. It incorporates updates from CDTFA as of 12/12/2024. Future updates will include improvements to metadata and update frequency.

The California Department of Fish and Wildlife Vegetation Classification and Mapping Program (VegCAMP) created a fine-scale vegetation classification and map of the Department's Oak Grove property, San Diego County, California following FGDC and National Vegetation Classification Standards. The vegetation classification was derived from floristic field survey data collected in the field in May 2010 and was based on previously described Alliances and Associations. The map was produced using true-color 2009 1-meter National Agricultural Imagery Program (NAIP) imagery as the base. Supplemental imagery including 2005 1-meter California Color Infrared (CIR) and true-color 1-foot aerial imagery available through GlobeXplorer ImageConnect were also used. The minimum mapping unit (MMU) is one acre, with the exception of wetland types, which were sometimes mapped to ½ acre. Field verification of 45 percent of the mapped polygons was conducted in June 2011; in combination with the 2010 sampling effort, 83 percent of the polygons were verified in the field.

This map page grid was designed and implemented by the Los Angeles County Fire Department, Information Management Division, and Geographic Information Systems Section. Wholly based on the United States National Grid (USNG), it aims to be the Los Angeles County regional grid because of its ease of use and extensive coverage.

Each block measures 2,000 meters by 2,000 meters and are comprised of four 1,000 meter/1 kilometer USNG blocks. i.e. 11SLT4771, 11SLT4871, 11SLT4770 and 11SLT4870; left to right and up to down. For ease of use each 2,000 meter block is designated by a page number from 1 to 9,750, and it is inferred that the 1,000 meter divisions of each page are designated A, B, C or D; left to right and up to down. Therefore, each 1,000 meter block within this regional grid has a unique descriptor of 4 numerals and 1 letter.

The region covered by the grid includes Los Angeles County completely and 2 of the islands in the Channel Islands archipelago that fall into the Los Angeles County jurisdiction. It also covers close to 100% of Orange County, 50% of Ventura County, and the Los Angeles County adjacent portions of Kern County, San Bernardino County and Riverside County, and a portion of Marine Corps Base Camp Pendleton in Northwest San Diego County.

PAGE = Grid Number

Reference Date: 2016

Contact Information:

Los Angeles County Fire Department Geographic Information Systems Section LACoFDGIS@fire.lacounty.gov

This dataset consists of polygons representing Indian Reservations in the County of San Diego as documented by the County of San Diego Assessor's Office, Mapping Division. An Indian Reservation is an area of land managed by a native American tribe under the United States Department of the Interior's Bureau of Indian Affairs. The polygons are intended to represent those lands recognized as part of the Indian Nation by the Bureau of Indian Affairs (BIA). The data does not include parcels that may be owned by a Tribe but which are not officially recognized as reservation lands by BIA. Because tribes possess tribal sovereignty, even though it is limited, laws on tribal lands vary from the surrounding area. These laws can permit legal casinos on reservations for example. The tribal council, not the local or federal government, generally has jurisdiction over reservations. Most Indian reservations were established by the federal government. The name "reservation" comes from the conception of the Indian tribes as independent sovereigns at the time of the U.S. Constitution was ratified.

City, Town, and Village boundary file, digitized from the Oswego County, NY tax maps as originally drawn by Stewart Mapping Services, Inc of San Antonio Texas, but with topology corrected by Oswego County Department of Real Property Tax Services.

description: The Digital Geologic Map of San Antonio Missions National Historical Park and vicinity, Texas is composed of GIS data layers complete with ArcMap 9.3 layer (.LYR) files, two ancillary GIS tables, a Map PDF document with ancillary map text, figures and tables, a FGDC metadata record and a 9.3 ArcMap (.MXD) Document that displays the digital map in 9.3 ArcGIS. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) funded program that is administered by the NPS Geologic Resources Division (GRD). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Texas Water Development Board and University of Texas at Austin, Bureau of Economic Geology. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation sections(s) of this metadata record (saan_metadata.txt; available at http://nrdata.nps.gov/saan/nrdata/geology/gis/saan_metadata.xml). All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.1. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data is available as a 9.3 personal geodatabase (saan_geology.mdb), and as shapefile (.SHP) and DBASEIV (.DBF) table files. The GIS data projection is NAD83, UTM Zone 14N. The data is within the area of interest of San Antonio Missions National Historical Park.; abstract: The Digital Geologic Map of San Antonio Missions National Historical Park and vicinity, Texas is composed of GIS data layers complete with ArcMap 9.3 layer (.LYR) files, two ancillary GIS tables, a Map PDF document with ancillary map text, figures and tables, a FGDC metadata record and a 9.3 ArcMap (.MXD) Document that displays the digital map in 9.3 ArcGIS. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) funded program that is administered by the NPS Geologic Resources Division (GRD). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Texas Water Development Board and University of Texas at Austin, Bureau of Economic Geology. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation sections(s) of this metadata record (saan_metadata.txt; available at http://nrdata.nps.gov/saan/nrdata/geology/gis/saan_metadata.xml). All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.1. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data is available as a 9.3 personal geodatabase (saan_geology.mdb), and as shapefile (.SHP) and DBASEIV (.DBF) table files. The GIS data projection is NAD83, UTM Zone 14N. The data is within the area of interest of San Antonio Missions National Historical Park.

Introduction

This group of maps shows relative susceptibility of hill slopes to the initiation sites of rainfall-triggered soil slip-debris flows in southwestern California. As such, the maps offer a partial answer to one part of the three parts necessary to predict the soil-slip/debris-flow process. A complete prediction of the process would include assessments of "where", "when", and "how big". These maps empirically show part of the "where" of prediction (i.e., relative susceptibility to sites of initiation of the soil slips) but do not attempt to show the extent of run out of the resultant debris flows. Some information pertinent to "when" the process might begin is developed. "When" is determined mostly by dynamic factors such as rainfall rate and duration, for which local variations are not amenable to long-term prediction. "When" information is not provided on the maps but is described later in this narrative. The prediction of "how big" is addressed indirectly by restricting the maps to a single type of landslide process soil slip-debris flows.

The susceptibility maps were created through an iterative process from two kinds of information. First, locations of sites of past soil slips were obtained from inventory maps of past events. Aerial photographs, taken during six rainy seasons that produced abundant soil slips, were used as the basis for soil slip-debris flow inventory. Second, digital elevation models (DEM) of the areas that were inventoried were used to analyze the spatial characteristics of soil slip locations. These data were supplemented by observations made on the ground. Certain physical attributes of the locations of the soil-slip debris flows were found to be important and others were not. The most important attribute was the mapped bedrock formation at the site of initiation of the soil slip. However, because the soil slips occur in surficial materials overlying the bedrocks units, the bedrock formation can only serve as a surrogate for the susceptibility of the overlying surficial materials.

The maps of susceptibility were created from those physical attributes learned to be important from the inventories. The multiple inventories allow a model to be created from one set of inventory data and evaluated with others. The resultant maps of relative susceptibility represent the best estimate generated from available inventory and DEM data.

Slope and aspect values used in the susceptibility analysis were 10-meter DEM cells at a scale of 1:24,000. For most of the area 10-meter DEMs were available; for those quadrangles that have only 30-meter DEMs, the 30-meter DEMS were resampled to 10-meters to maintain resolution of 10-meter cells. Geologic unit values used in the susceptibility analysis were five-meter cells. For convenience, the soil slip susceptibility values are assembled on 1:100,000-scale bases. Any area of the 1:100,000-scale maps can be transferred to 1:24,000-scale base without any loss of accuracy. Figure 32 is an example of part of a 1:100,000-scale susceptibility map transferred back to a 1:24,000-scale quadrangle.

The Digital Environmental Geologic Map of San Antonio Missions National Historical Park and vicinity, Texas is composed of GIS data layers complete with ArcMap 9.3 layer (.LYR) files, two ancillary GIS tables, a Map PDF document with ancillary map text, figures and tables, a FGDC metadata record and a 9.3 ArcMap (.MXD) Document that displays the digital map in 9.3 ArcGIS. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) funded program that is administered by the NPS Geologic Resources Division (GRD). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Not Published. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation sections(s) of this metadata record (saeg_metadata.txt; available at http://nrdata.nps.gov/saan/nrdata/geology/gis/saeg_metadata.xml). All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.1. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data is available as a 9.3 personal geodatabase (saeg_geology.mdb), and as shapefile (.SHP) and DBASEIV (.DBF) table files. The GIS data projection is NAD83, UTM Zone 14N. The data is within the area of interest of San Antonio Missions National Historical Park.

School district boundaries created from fund numbers which are provided by the San Diego County Auditor/Controller's Property Tax Services Division (from SanGIS)

The California Interagency Watershed Map of 1999 (Calwater 2.2, updated May 2004, "calw221") is the State of California's working definition of watershed boundaries. Previous Calwater versions (1.2 and 2.2) described California watersheds, beginning with the division of the State's 101 million acres into ten Hydrologic Regions (HR). Each HR is progressively subdivided into six smaller, nested levels: the Hydrologic Unit (HU, major rivers), Hydrologic Area (HA, major tributaries), Hydrologic Sub-Area (HSA), Super Planning Watershed (SPWS), and Planning Watershed (PWS). At the Planning Watershed (the most detailed level), where implemented, polygons range in size from approximately 3,000 to 10,000 acres. At all levels, a total of 7035 polygons represent the State's watersheds. The present version, Calwater 2.2.1, refines the watershed coding structure and documentation (database fields were added and some were renamed). There are significant watershed boundary, code, and name differences between Calwater versions 1.2 (1995), 2.0 (1998), and 2.2 (1999). The differences between versions 2.2 (1999) and 2.2.1 (2004) are attribute field names and some inserted lines that identify differences between State and federal watersheds. Calwater 2.2.1 most accurately delineates true watersheds in mountainous terrain. However, neither Calwater 2.2.1 nor any of its predecessors is a "pure" watershed map because administrative boundaries such as the State border were used to delineate watershed areas. Some of the boundaries, particularly in developed valley areas, also have legal and administrative purposes other than the representation of actual drainage divides. Examples include the so-called "Legal Delta" (California Water Code, Chapter 2, the Delta, Sec. 12220) and other district boundaries. Neither is Calwater a legal map document, as it does not represent State of California Regional Water Quality Control Board (RWQCB) jurisdictions, officiated by the State Water Resources Control Board (SWRCB) under California Water Code Section 13200. Calwater is a hybrid, a spatial cross-reference for use in local, State, and federal information communities. The California Resources Agency (CRA) Department of Forestry and Fire Protection (CDF) contracted with Tierra Data Systems for the original digital production in 1993, based on Hydrologic Basin Planning Maps published in hardcopy (SWRCB, 1986). The State of California Stephen P. Teale Data Center GIS Solutions Group (Teale) under the direction of the California Department of Water Resrouces (DWR) and CDF, finalized the current version in ESRI ArcInfo coverage format in 1999 with USDA Forest Service and RWQCB/SWRCB inputs. The CRA California Spatial Information Library (CaSIL) is the current distributor of the coverage in the Teale Albers Conical Equal-Area projection, North American Datum of 1983. The California Department of Fish and Game (DFG) authored Calwater attribution design and documentation culminating in May 2004 with this Federal Geographic Data Committee (FGDC-STD-001-1998) standard metadata.This dataset comprises a portion of the full California dataset to cover hydrological basins that intersect San Diego County, Imperial County, Riverside County and Orange County.

A geographic representation of the district boundaries created from fund numbers which are provided by the County Auditor/Controller's Property Tax Services (PTS) Division.

The 1998 San Diego County land use survey data set was developed by DWR through its Division of Planning and Local Assistance (DPLA). 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 Southern District. Quality control procedures were performed jointly by staff at DWR’s DPLA headquarters and Southern District. The finalized land use vector data is a single, polygon, shapefile format. Important points about using this dataset: 1. The land use boundaries were either hand drawn directly on USGS quad maps and then digitized, or digitized on-screen using corrected imagery. 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. This survey was not a "snapshot" in time, but incorporated two field visits for agricultural areas. The original land use attributes of each delineated area (polygon) were based upon the surveyor’s observations in the field at those times, and are reflected in the quad DWG and shapefiles. For the survey-wide shapefile 98SD.shp, the attributes are the interpreted results. 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.