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TwitterRiverside County's GIS web viewer that supplies various datasets containing parcel, transportation, environmental, and boundary layers and more.
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TwitterVector polygon map data of property parcels from Riverside County, California containing 846, 890 features.
Property parcel GIS map data consists of detailed information about individual land parcels, including their boundaries, ownership details, and geographic coordinates.
Property parcel data can be used to analyze and visualize land-related information for purposes such as real estate assessment, urban planning, or environmental management.
Available for viewing and sharing as a map in a Koordinates map viewer. This data is also available for export to DWG for CAD, PDF, KML, CSV, and GIS data formats, including Shapefile, MapInfo, and Geodatabase.
APN refers to Assessor's Parcel Number FLAG refers to a special designation for the parcel
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The California Department of Fish and Game (CDFG) contracted with the California Native Plant Society (CNPS) and Aerial Information Systems (AIS) to produce an alliance-level, vegetation classification and map of Western Riverside County, California. The resulting classification and map products will be used to help establish a monitoring basis for the vegetation and habitats of the Western Riverside County Multi-Species Habitat Conservation Plan (MSHCP). The plan aims to conserve over 500,000 acres of land out of the 1.26 million acre total. This area is the largest MSHCP ever attempted and is an integral piece of the network of Southern California Habitat Conservation Plans and Natural Community Conservation Planning (Dudek 2001, Dudek 2003). Riverside County is one of the fastest growing counties in California, as well as one of the most biodiverse counties in the United States. A wide array of habitats are found within the non-developed lands in Western Riverside County, including coastal sage scrub, vernal pools, montane coniferous forest, chaparral, foothill woodland, annual grassland, and desert. In the CNPS contract, vegetation resources were assessed quantitatively through field surveys, data analysis, and final vegetation classification. Field survey data were analyzed statistically to come up with a floristically-based classification. Each vegetation type sampled was classified according to the National Vegetation Classification System to the alliance level (and association level if possible). The vegetation alliances were described floristically and environmentally in standard descriptions, and a final key was produced to differentiate among 101 alliances, 169 associations, and 3 unique stands (for final report, see https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=18245). In a parallel but separate effort by AIS (as reported in this dataset), vegetation mapping was undertaken through interpretation of ortho-rectified, aerial photographs for vegetation signatures in color infrared (CIR) and in natural color (imagery flown in winter or summer). A detailed map has been produced through the following process: 1) hand-delineation of polygons on base CIR imagery, 2) digitization of polygons, and 3) attribution of the vegetation types and overstory cover values. The map was created in a Geographic Information System (GIS) digital format, as was the database of field surveys. The dataset was produced through an on-screen photo interpretation procedure using three sets of geo-referenced imagery. The data is classified to a floristic classification derived through clustering analysis procedures based on species dominance and significance. The classification is based on the MCV (Manual of California Vegetation) in which 103 alliances and 169 floristic associations have been defined for the study area. Over 3300 full plot and reconnaissance points have been used in helping classify the mapped polygons. Mapped polygons are classified to either an association, alliance or mapping unit which may be an aggregation of associations or alliances. The dataset encompasses the western portions of Riverside County from the county boundary on the west eastward to the summit of the San Jacinto Mountains and Anza valley.
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TwitterThis Digital Raster Graphic (DRG) was created using scanned U.S. Geological Survey 7.5-minute 1 to 24,000 scale maps georeferenced in Universal Transverse Mercator (UTM) grid. DRGs can be acquired with or without collar information for use in Geographic Information System (GIS) environment. Collarless DRGs can be edge matched creating a continuous collection of topographic maps.
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TwitterThis polygon feature class represents the Riverside County Assessor Map Book-page Boundaries. It is created by extracting information from the Assessor's AOI feature class.AttributesAOI - Assessor book and page numbers combinedBOOK - Book numberPAGE - Page number
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TwitterPoint feature class to indicate all addresses contained within a parcel within the City of Temecula. This data is a supplement to the Riverside County Assessor data.Locations of every address in the City in light of the fact the assessor parcel data includes only one address per parcel, it is necessary to supplement this information by including all addresses that may be located within a parcel. The most effective way to accomplish this is by indicating multiple addresses on one parcel with a point feature.This data layer is updated at the time that new addresses are assigned or addresses are changed or modified.
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Aerial Information Systems, Inc. (AIS) was contracted by the Western Riverside County Regional Conservation Authority to perform an update to their original 2005 Western Riverside Vegetation Map. The project was funded through a Local Assistance Grant from the California Department of Fish and Wildlife (CDFW). The original vegetation layer was created in 2005 using a baseline image dataset created from 2000/01 Emerge imagery flown in early spring. The original map has been used to monitor and evaluate the habitat in the Western Riverside County Multi-species Habitat Conservation Plan (MSHCP).
An update to the original map was needed to address changes in vegetation makeup that have occurred in the intervening years due to widespread and multiple burns in the mapping area, urban expansion, and broadly occurring vegetation succession.
The update conforms to the standards set by the National Vegetation Classification System (NVCS) published in 2008 by the Federal Geographic Data Committee. (FGDC-STD-005-2008, Vegetation Subcommittee, Federal Geographic Data Committee, February 2008) The update also adheres to the vegetation types as represented in the 2008-second edition of the Manual of California Vegetation (MCV2). Extensive ground based field data both within and nearby the western Riverside County mapping area has been acquired since the completion of the project in 2005. This additional data has resulted in the reclassification of several vegetation types that are addressed in the updated vegetation map.
The mapping area covers 1,017,364 acres of the original 1.2 million acres mapped in the 2005 study. The new study covers portions of the Upper Santa Ana River Valley, Perris Plain, and the foothills of the San Jacinto and Santa Ana Mountains but excludes US Forest Service land. The final geodatabase includes an updated 2012 vegetation map. Vegetative and cartographic comparisons between the newly created 2012 image-based map and the original vegetation map produced in 2005 are described in this report.
The Update mapping was performed using baseline digital imagery created in 2012 by the US Department of Agriculture – Farm Service Agency’s National Agricultural Imagery Program (NAIP). Vegetation units were mapped using the National Vegetation Classification System (NVCS) to the Alliance and Association level as depicted in the MCV2. Approximately 55 percent of the study area is classified to vegetated or naturally occurring sparsely vegetated types; the remaining 45 percent is unvegetated, with over a third (36 percent) in urban development and an additional 9 percent in agriculture.
The major tasks for the Update project consisted of updating the original mapping classification to conform to the changes and refinements to the MCV2 classification, updating the existing vegetation map to 2012 conditions, retroactively correcting the 2005 vegetation interpretations, creating the final report and project metadata, and producing the final vegetation geodatabase.
After completion of the original 2005 vegetation map, CDFW crosswalked the original mapping units to the NVCS hierarchical names as defined in the Manual of California Vegetation (MCV).The original crosswalk was revised during the Update effort to reflect changes in the original MCV classification as depicted in the second edition (MCV2). Changes were minor and did not result in a significant effort in the updating process.
The updating process in many steps is similar to the creation of the original vegetation map. First, photo interpreters review the study area for terrain, environmental features, and probable vegetation types present. Questionable photo signatures on the new baseline imagery (2012 NAIP) were compared to the original 2000/01 Emerge imagery. Photo signatures for a given vegetation polygon were correlated between the two image datasets.
Production level updates to the linework and labeling commenced following the correlation of the two baseline image datasets and the subsequent refinement of photo interpretation criteria and biogeographical descriptions of the types. Existing datasets depicting topography, fire history, climate and past vegetation gathering efforts aided photo interpreters in their delineations and floristic assignments during the updating effort. The production updating effort took approximately 11 months.
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Tax rate area boundaries and related data based on changes filed with the Board of Equalization per Government Code 54900 for the specified assessment roll year. The data included in this map is maintained by the California State Board of Equalization and may differ slightly from the data published by other agencies. BOE_TRA layer = tax rate area boundaries and the assigned TRA number for the specified assessment roll year; BOE_Changes layer = boundary changes filed with the Board of Equalization for the specified assessment roll year; Data Table (C##_YYYY) = tax rate area numbers and related districts for the specified assessment roll year
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TwitterData was spatially adjusted in 2020. CSA_NUMBER: The CSA numberNAME: Name of CSASUBZONE: Wine Country referenceST_LIGHTING: "Y" or "N" to denote if CSA funds activity. Blank is an assumed "N"ST_SWEEPING: "Y" or "N" to denote if CSA funds activity. Blank is an assumed "N"PARK_REC: "Y" or "N" to denote if CSA funds activity. Blank is an assumed "N"FIRE_PROTECT: "Y" or "N" to denote if CSA funds activity. Blank is an assumed "N"SEWER: "Y" or "N" to denote if CSA funds activity. Blank is an assumed "N"WATER: "Y" or "N" to denote if CSA funds activity. Blank is an assumed "N"TRASH: "Y" or "N" to denote if CSA funds activity. Blank is an assumed "N"ROAD_MAINT: "Y" or "N" to denote if CSA funds activity. Blank is an assumed "N"FLOOD_CTRL: "Y" or "N" to denote if CSA funds activity. Blank is an assumed "N"POLICE: "Y" or "N" to denote if CSA funds activity. Blank is an assumed "N"DRAINAGE_CTRL: "Y" or "N" to denote if CSA funds activity. Blank is an assumed "N"LIBRARY: "Y" or "N" to denote if CSA funds activity. Blank is an assumed "N"LANDSCAPING: "Y" or "N" to denote if CSA funds activity. Blank is an assumed "N"SPHERE_NUMBER: Not used
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TwitterCDFW BIOS GIS Dataset, Contact: Karyn L Drennen, Description: The Biological Monitoring Program is a part of the Western Riverside County Multi-Species Habitat Conservation Plan (MSHCP), which was permitted in June, 2004. The Monitoring Program monitors the status of 146 Covered Species within a designated Conservation Area to provide information to permittees, land managers, the public, and wildlife agencies (i.e., the California Department of Fish and Wildlife and the U.S. Fish and Wildlife Service).
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This ownership dataset utilizes a methodology that results in a federal ownership extent that matches the Federal Responsibility Areas (FRA) footprint from CAL FIRE's State Responsibility Areas for Fire Protection (SRA) data. FRA lands are snapped to county parcel data, thus federal ownership areas will also be snapped. Since SRA Fees were first implemented in 2011, CAL FIRE has devoted significant resources to improve the quality of SRA data. This includes comparing SRA data to data from other federal, state, and local agencies, an annual comparison to county assessor roll files, and a formal SRA review process that includes input from CAL FIRE Units. As a result, FRA lands provide a solid basis as the footprint for federal lands in California (except in the southeastern desert area). The methodology for federal lands involves:
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City of Riverside Open Data for use in the city.
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TwitterThe Geologic Map of the Perris 7.5? Quadrangle, Riverside County, California contains a digital geologic map database of the Perris 7.5? quadrangle, Riverside County, California that includes: 1. ARC/INFO (Environmental Systems Research Institute, "http://www.esri.com") version 7.2.1 coverages of the various elements of the geologic map.
The Correlation of Map Units and Description of Map Units is in the editorial format of USGS Geologic Investigations Series (I-series) maps but has not been edited to comply with I-map standards. Within the geologic map data package, map units are identified by standard geologic map criteria such as formationname, age, and lithology. Where known, grain size is indicated on the map by a subscripted letter or letters following the unit symbols as follows: lg, large boulders; b, boulder; g, gravel; a, arenaceous; s, silt; c, clay; e.g. Qyfa is a predominantly young alluvial fan deposit that is arenaceous. Multiple letters are used for more specific identification or for mixed units, e.g., Qfysa is a silty sand. In some cases, mixed units are indicated by a compound symbol; e.g., Qyf2sc.
[Summary provided by the USGS.]
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This shapefile contains tax rate area (TRA) boundaries in Riverside County for the specified assessment roll year. Boundary alignment is based on the 2017 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
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TwitterGeologic Map of the Elsinore 7.5? Quadrangle, Riverside County, California ontains a digital geologic map database of the Elsinore 7.5 - quadrangle, Riverside County, California that includes:
ARC/INFO (Environmental Systems Research Institute, http://www.esri.com) version 7.2.1 coverages of the various elements of the geologic map.
A Postscript file to plot the geologic map on a topographic base, and containing a Correlation of Map Units diagram (CMU), a Description of Map Units (DMU), and an index map.
Portable Document Format (.pdf) files of:
a. This Readme; includes in Appendix I, data contained in els_met.txt
b. The same graphic as plotted in 2 above. Test plots have not produced precise 1:24,000-scale map sheets. Adobe Acrobat page size setting influences map scale.
The Correlation of Map Units and Description of Map Units is in the editorial format of USGS Geologic Investigations Series (I-series) maps but has not been edited to comply with I-map standards. Within the geologic map data package, map units are identified by standard geologic map criteria such as formation-name, age, and lithology. Where known, grain size is indicated on the map by a subscripted letter or letters following the unit symbols as follows: lg, large boulders; b, boulder; g, gravel; a, arenaceous; s, silt; c, clay; e.g. Qyfa is a predominantly young alluvial fan deposit that is arenaceous. Multiple letters are used for more specific identification or for mixed units, e.g., Qfysa is a silty sand. In some cases, mixed units are indicated by a compound symbol; e.g., Qyf2sc. Even though this is an Open-File Report and includes the standard USGS Open-File disclaimer, the report closely adheres to the stratigraphic nomenclature of the U.S. Geological Survey. Descriptions of units can be obtained by viewing or plotting the .pdf file (3b above) or plotting the postscript file (2 above).
[Summary provided by the USGS.]
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This is SCAG 2019 Regional Land Use dataset developed for the final 2024 Connect SoCal, the 2024-2050 Regional Transportation Plan/Sustainable Communities Strategy (RTP/SCS), including general plan land use, specific plan land use, zoning code, and existing land use at parcel-level (approximately five million parcels) for 197 local jurisdictions in the SCAG region.The regional land use dataset is developed (1) to aid in SCAG’s regional transportation planning, scenario planning and growth forecasting, (2) facilitate policy discussion on various planning issues, and (3) enhance information database to better serve SCAG member jurisdictions, research institutes, universities, developers, general public, etc. It is the most frequently and widely utilized SCAG geospatial data. From late 2019 to early 2020, SCAG staff obtained the 2019 parcel boundary GIS file and tax roll property information from county assessor’s offices. After months of data standardization and clean-up process, SCAG staff released the 2019 parcel boundary GIS files along with the 2019 Annual Land Use dataset in February 2021. In December 2021, SCAG staff successfully developed the preliminary dataset of the 2019 regional land use data and released the draft SCAG Data/Map Book in May 2022. The preliminary land use data was reviewed by local jurisdictions during the Local Data Exchange (LDX) process for Connect SoCal 2024. As a part of the final 2019 regional land use data development process, SCAG staff made every effort to review the local jurisdictions’ inputs and comments and incorporated any updates to the regional land use datasets. The products of this project has been used as one of the key elements for Connect SoCal 2024 plan development, growth forecasting, scenario planning, and SCAG’s policy discussion on various planning issues, as well as Connect SoCal key growth strategy analysis.Note: This dataset is intended for planning purposes only, and SCAG shall incur no responsibility or liability as to the completeness, currentness, or accuracy of this information. SCAG assumes no responsibility arising from use of this information by individuals, businesses, or other public entities. The information is provided with no warranty of any kind, expressed or implied, including but not limited to the implied warranties of merchantability and fitness for a particular purpose. Users should consult with each local jurisdiction directly to obtain the official land use information.2019 SCAG Land Use Codes: LegendLand Use Description Single Family Residential1110 Single Family Residential 1111 High Density Single Family Residential (9 or more DUs/ac) 1112 Medium Density Single Family Residential (3-8 DUs/ac) 1113 Low Density Single Family Residential (2 or less DUs/ac)Multi-Family Residential1120 Multi-Family Residential 1121 Mixed Multi-Family Residential1122 Duplexes, Triplexes and 2- or 3-Unit Condominiums and Townhouses1123 Low-Rise Apartments, Condominiums, and Townhouses1124 Medium-Rise Apartments and Condominiums1125 High-Rise Apartments and CondominiumsMobile Homes and Trailer Parks1130 Mobile Homes and Trailer Parks1131 Trailer Parks and Mobile Home Courts, High-Density1132 Mobile Home Courts and Subdivisions, Low-DensityMixed Residential1140 Mixed Residential1100 ResidentialRural Residential 1150 Rural ResidentialGeneral Office1210 General Office Use 1211 Low- and Medium-Rise Major Office Use 1212 High-Rise Major Office Use 1213 SkyscrapersCommercial and Services1200 Commercial and Services1220 Retail Stores and Commercial Services 1221 Regional Shopping Center 1222 Retail Centers (Non-Strip With Contiguous Interconnected Off-Street Parking) 1223 Retail Strip Development1230 Other Commercial 1231 Commercial Storage 1232 Commercial Recreation 1233 Hotels and MotelsFacilities1240 Public Facilities1241 Government Offices1242 Police and Sheriff Stations1243 Fire Stations1244 Major Medical Health Care Facilities1245 Religious Facilities1246 Other Public Facilities1247 Public Parking Facilities1250 Special Use Facilities1251 Correctional Facilities1252 Special Care Facilities1253 Other Special Use FacilitiesEducation1260 Educational Institutions1261 Pre-Schools/Day Care Centers1262 Elementary Schools1263 Junior or Intermediate High Schools1264 Senior High Schools1265 Colleges and Universities1266 Trade Schools and Professional Training FacilitiesMilitary Installations1270 Military Installations1271 Base (Built-up Area)1272 Vacant Area1273 Air Field1274 Former Base (Built-up Area)1275 Former Base Vacant Area1276 Former Base Air FieldIndustrial1300 Industrial 1310 Light Industrial1311 Manufacturing, Assembly, and Industrial Services1312 Motion Picture and Television Studio Lots1313 Packing Houses and Grain Elevators1314 Research and Development1320 Heavy Industrial1321 Manufacturing1322 Petroleum Refining and Processing1323 Open Storage1324 Major Metal Processing1325 Chemical Processing1330 Extraction1331 Mineral Extraction - Other Than Oil and Gas1332 Mineral Extraction - Oil and Gas1340 Wholesaling and WarehousingTransportation, Communications, and Utilities1400 Transportation, Communications, and Utilities 1410 Transportation1411 Airports1412 Railroads1413 Freeways and Major Roads1414 Park-and-Ride Lots1415 Bus Terminals and Yards1416 Truck Terminals1417 Harbor Facilities1418 Navigation Aids1420 Communication Facilities1430 Utility Facilities1431 Electrical Power Facilities1432 Solid Waste Disposal Facilities1433 Liquid Waste Disposal Facilities1434 Water Storage Facilities1435 Natural Gas and Petroleum Facilities1436 Water Transfer Facilities 1437 Improved Flood Waterways and Structures1438 Mixed Utilities1440 Maintenance Yards1441 Bus Yards1442 Rail Yards1450 Mixed Transportation1460 Mixed Transportation and UtilityMixed Commercial and Industrial1500 Mixed Commercial and IndustrialMixed Residential and Commercial1600 Mixed Residential and Commercial 1610 Residential-Oriented Residential/Commercial Mixed Use 1620 Commercial-Oriented Residential/Commercial Mixed UseOpen Space and Recreation1800 Open Space and Recreation 1810 Golf Courses 1820 Local Parks and Recreation 1830 Regional Parks and Recreation 1840 Cemeteries 1850 Wildlife Preserves and Sanctuaries 1860 Specimen Gardens and Arboreta 1870 Beach Parks 1880 Other Open Space and Recreation 1890 Off-Street TrailsAgriculture2000 Agriculture2100 Cropland and Improved Pasture Land2110 Irrigated Cropland and Improved Pasture Land2120 Non-Irrigated Cropland and Improved Pasture Land2200 Orchards and Vineyards2300 Nurseries2400 Dairy, Intensive Livestock, and Associated Facilities2500 Poultry Operations2600 Other Agriculture2700 Horse RanchesVacant3000 Vacant3100 Vacant Undifferentiated3200 Abandoned Orchards and Vineyards3300 Vacant With Limited Improvements3400 Beaches (Vacant)1900 Urban VacantWater4000 Water4100 Water, Undifferentiated4200 Harbor Water Facilities4300 Marina Water Facilities4400 Water Within a Military Installation4500 Area of Inundation (High Water)Specific Plan7777 Specific PlanUnder Construction1700 Under ConstructionUndevelopable or Protected Land8888 Undevelopable or Protected LandUnknown9999 Unknown
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TwitterThe data set for the Porcupine Wash quadrangle has been prepared by the Southern California Areal Mapping Project (SCAMP), a cooperative project sponsored jointly by the U.S. Geological Survey and the California Division of Mines and Geology. The Porcupine Wash data set represents part of an ongoing effort to create a regional GIS geologic database for southern California. This regional digital database, in turn, is being developed as a contribution to the National Geologic Map Database of the National Cooperative Geologic Mapping Program of the USGS. The Porcupine Wash database has been prepared in cooperation with the National Park Service as part of an ongoing project to provide Joshua Tree National Park with a geologic map base for use in managing Park resources and developing interpretive materials.
The digital geologic map database for the Porcupine Wash quadrangle has been created as a general-purpose data set that is applicable to land-related investigations in the earth and biological sciences. Along with geologic map databases in preparation for adjoining quadrangles, the Porcupine Wash database has been generated to further our understanding of bedrock and surficial processes at work in the region and to document evidence for seismotectonic activity in the eastern Transverse Ranges. The database is designed to serve as a base layer suitable for ecosystem and mineral resource assessment and for building a hydrogeologic framework for Pinto Basin.
This data set maps and describes the geology of the Porcupine Wash 7.5 minute quadrangle, Riverside County, southern California. The quadrangle, situated in Joshua Tree National Park in the eastern Transverse Ranges physiographic and structural province, encompasses parts of the Hexie Mountains, Cottonwood Mountains, northern Eagle Mountains, and south flank of Pinto Basin. It is underlain by a basement terrane comprising Proterozoic metamorphic rocks, Mesozoic plutonic rocks, and Mesozoic and Mesozoic or Cenozoic hypabyssal dikes. The basement terrane is capped by a widespread Tertiary erosion surface preserved in remnants in the Eagle and Cottonwood Mountains and buried beneath Cenozoic deposits in Pinto Basin. Locally, Miocene basalt overlies the erosion surface. A sequence of at least three Quaternary pediments is planed into the north piedmont of the Eagle and Hexie Mountains, each in turn overlain by successively younger residual and alluvial deposits.
The Tertiary erosion surface is deformed and broken by north-northwest-trending, high-angle, dip-slip faults and an east-west trending system of high-angle dip- and left-slip faults. East-west trending faults are younger than and perhaps in part coeval with faults of the northwest-trending set.
The Porcupine Wash database was created using ARCVIEW and ARC/INFO, which are geographical information system (GIS) software products of Environmental Systems Research Institute (ESRI). The database consists of the following items: (1) a map coverage showing faults and geologic contacts and units, (2) a separate coverage showing dikes, (3) a coverage showing structural data, (4) a scanned topographic base at a scale of 1:24,000, and (5) attribute tables for geologic units (polygons and regions), contacts (arcs), and site-specific data (points). The database, accompanied by a pamphlet file and this metadata file, also includes the following graphic and text products: (1) A portable document file (.pdf) containing a navigable graphic of the geologic map on a 1:24,000 topographic base. The map is accompanied by a marginal explanation consisting of a Description of Map and Database Units (DMU), a Correlation of Map and Database Units (CMU), and a key to point-and line-symbols. (2) Separate .pdf files of the DMU and CMU, individually. (3) A PostScript graphic-file containing the geologic map on a 1:24,000 topographic base accompanied by the marginal explanation. (4) A pamphlet that describes the database and how to access it. Within the database, geologic contacts , faults, and dikes are represented as lines (arcs), geologic units as polygons and regions, and site-specific data as points. Polygon, arc, and point attribute tables (.pat, .aat, and .pat, respectively) uniquely identify each geologic datum and link it to other tables (.rel) that provide more detailed geologic information.
Map nomenclature and symbols
Within the geologic map database, map units are identified by standard geologic map criteria such as formation-name, age, and lithology. The authors have attempted to adhere to the stratigraphic nomenclature of the U.S. Geological Survey and the North American Stratigraphic Code, but the database has not received a formal editorial review of geologic names.
Special symbols are associated with some map units. Question marks have been added to the unit symbol (e.g., QTs?, Prpgd?) and unit name where unit assignment based on interpretation of aerial photographs is uncertain. Question marks are plotted as part of the map unit symbol for those polygons to which they apply, but they are not shown in the CMU or DMU unless all polygons of a given unit are queried. To locate queried map-unit polygons in a search of database, the question mark must be included as part of the unit symbol.
Geologic map unit labels entered in database items LABL and PLABL contain substitute characters for conventional stratigraphic age symbols: Proterozoic appears as 'Pr' in LABL and as '<' in PLABL, Triassic appears as 'Tr' in LABL and as '^' in PLABL. The substitute characters in PLABL invoke their corresponding symbols from the GeoAge font group to generate map unit labels with conventional stratigraphic symbols.
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TwitterThis data set maps the soil-slip susceptibility for several areas in southwestern California. Created using Environmental Systems Research Institute's ARC/INFO software, the data base consists of raster maps containing grid cells coded with soil- slip susceptibility values. In addition, the data set includes the following graphic and text products: (1) postscript graphic plot files containing the soil-slip susceptibility map, topography, cultural data, and a key of the colored map units, and (2) PDF and text files of the Readme (including the metadata file as an appendix) and accompanying text, and a PDF file of the plot files. Intense winter rains commonly generated debris flows in upland areas of southwestern California. These debris flows initiate as small landslides referred to as soil slips. Most of the soil slips mobilize into debris flows that travel down slope at varying speeds and distances. The debris flows can be a serious hazard to people and structures in their paths. The soil-slip susceptibility maps identify those natural slopes most likely to be the sites of soil slips during periods of intense winter rainfall. The maps were largely derived by extrapolation of debris-flow inventory data collected from selected areas of southwestern California. Based on spatial analyses of soil slips, three factors in addition to rainfall, were found to be most important in the origin of soil slips. These factors are geology, slope, and aspect. Geology, by far the most important factor, was derived from existing geologic maps. Slope and aspect data were obtained from 10-meter digital elevation models (DEM). Soil-slip susceptibility maps at a scale of 1:24,000 were derived from combining numerical values for geology, slope, and aspect on a 10-meter cell size for 128 7.5' quadrangles and assembled on 1:100,000-scale topographic maps. The resultant maps of relative soil-slip susceptibility represent the best estimate generated from available debris-flow inventory maps and DEM data.
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TwitterAerial Information Systems, Inc. (AIS) was contracted by the Coachella Valley Conservation Commission (CVCC) through a Local Assistance Grant originating from the California Department of Fish and Wildlife (CDFW) to map and describe the essential habitats for bighorn sheep monitoring within the San Jacinto-Santa Rosa Mountains Conservation Area. This effort was completed in support of the Coachella Valley Multiple Species Habitat Conservation Plan (CVMSHCP). The completed vegetation map is consistent with the California Department of Fish and Wildlife classification methodology and mapping standards. The mapping area covers 187,465 acres of existing and potential habitat on the northern slopes of the San Jacinto and Santa Rosa Mountains ranging from near sea level to over 6000 feet in elevation. The map was prepared over a baseline digital image created in 2014 by the US Department of Agriculture – Farm Service Agency’s National Agricultural Imagery Program (NAIP). Vegetation units were mapped using the National Vegetation Classification System (NVCS) to the Alliance (and in several incidences to the Association) level (See Appendix A for more detail) as described in the second edition of the Manual of California Vegetation Second Edition (Sawyer et al, 2009). The mapping effort was supported by extensive ground-based field gathering methods using CNPS rapid assessment protocol in the adjacent areas as part of the Desert Renewable Energy Conservation Plan (DRECP) to the north and east; and by the 2012 Riverside County Multiple Species Habitat Conservation Plan vegetation map in the western portion of Riverside County adjacent to the west. These ground-based data have been classified and described for the abovementioned adjacent regions and resultant keys and descriptions for those efforts have been used in part for this project.For detailed information please refer to the following report: Menke, J. and D. Johnson. 2015. Vegetation Mapping – Peninsular Bighorn Sheep Habitat. Final Vegetation Mapping Report. Prepared for the Coachella Valley Conservation Commission. Aerial Information Systems, Inc., Redlands, CA.
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TwitterThe data set for the Corona North 7.5' quadrangle was prepared under the U.S. Geological Survey Southern California Areal Mapping Project (SCAMP) as part of an ongoing effort to develop a regional geologic framework of southern California, and to utilize a Geographic Information System (GIS) format to create regional digital geologic databases. These regional databases are being developed as contributions to the National Geologic Map Database of the National Cooperative Geologic Mapping Program of the USGS.
This data set maps and describes the geology of the Corona North 7.5' quadrangle, Riverside and San Bernardino Counties, California. Created using Environmental Systems Research Institute's ARC/INFO software, the data base consists of the following items: (1) a map coverage containing geologic contacts and units, (2) a coverage containing structural data, (3) a coverage containing geologic unit annotation and leaders, and (4) attribute tables for geologic units (polygons), contacts (arcs), and site-specific data (points). In addition, the data set includes the following graphic and text products: (1) a postscript graphic plot-file containing the geologic map, topography, cultural data, a Correlation of Map Units (CMU) diagram, a Description of Map Units (DMU), and a key for point and line symbols, and (2) PDF files of the Readme (including the metadata file as an appendix), and the graphic produced by the Postscript plot file.
The Corona North quadrangle is located near the northern end of the Peninsular Ranges Province. All but the southeastern tip of the quadrangle is within the Perris block, a relatively stable, rectangular in plan area located between the Elsinore and San Jacinto fault zones. The southeastern tip of the quadrangle is barely within the Elsinore fault zone.
The quadrangle is underlain by Cretaceous plutonic rocks that are part of the composite Peninsular Ranges batholith. These rocks are exposed in a triangular-shaped area bounded on the north by the Santa Ana River and on the south by Temescal Wash, a major tributary of the Santa Ana River. A variety of mostly silicic granitic rocks occur in the quadrangle, and are mainly of monzogranite and granodioritic composition, but range in composition from micropegmatitic granite to gabbro. Most rock units are massive and contain varying amounts of meso- and melanocratic equant-shaped inclusions. The most widespread granitic rock is monzogranite of the Cajalco pluton, a large pluton that extends some distance south of the quadrangle. North of Corona is a body of micropegmatite that appears to be unique in the batholith rocks.
Diagonally bisecting the quadrangle is the Santa Ana River. North of the Santa Ana River alluvial deposits are dominated by the distal parts of alluvial fans emanating from the San Gabriel Mountains north of the quadrangle. Widespread areas of the fan deposits are covered by a thin layer of wind blown sand.
Alluvial deposits in the triangular-shaped area between the Santa Ana River and Temescal Wash are quite varied, but consist principally of locally derived older alluvial fan deposits. These deposits rest on remnants of older, early Quaternary or late Tertiary age, nonmarine sedimentary deposits that were derived from both local sources and sources as far away as the San Bernardino Mountains. These deposits in part were deposited by an ancestral Santa Ana River. Older are a few scattered remnants of late Tertiary (Pliocene) marine sandstone that include some conglomerate lenses. Clasts in the conglomerate include siliceous volcanic rocks exotic to this part of southern California. This sandstone was deposited as the southeastern-most part of the Los Angeles sedimentary marine basin and was deposited along a rocky shoreline developed in the granitic rocks, much like the present day shoreline at Monterey, California. Most of the sandstone and granitic paleoshoreline features have been removed by quarrying and grading in the area of Porphyry north to Highway 91. Excellent exposures in highway road cuts still remain on the north side of Highway 91 just east of the 91-15 interchange and on the east side of U.S. 15 just north of the interchange.
South of Temescal Wash is a series of both younger and older alluvial fan deposits emanating from the Santa Ana Mountains to the southeast. In the immediate southwest corner of the quadrangle is a small exposure of sandstone and pebble conglomerate of the Sycamore Canyon member of the Puente Formation of early Pliocene and Miocene age and sandstone and conglomerate of undivided Sespe and Vaqueros Formations of early Miocene, Oligocene, and late Eocene age.
The geologic map data base contains original U.S. Geological Survey data generated by detailed field observation recorded on 1:24,000 scale aerial photographs. The map was created by transferring lines from the aerial photographs to a 1:24,000 scale topographic base. The map was digitized and lines, points, and polygons were subsequently edited using standard ARC/INFO commands. Digitizing and editing artifacts significant enough to display at a scale of 1:24,000 were corrected. Within the database, geologic contacts are represented as lines (arcs), geologic units are polygons, and site-specific data as points. Polygon, arc, and point attribute tables (.pat, .aat, and .pat, respectively) uniquely identify each geologic datum.
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