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TwitterVector polygon map data of property parcels from Shasta County, California containing 101,781 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.
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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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TwitterThe Digital Geologic-GIS Map of the Shasta Dam Quadrangle, California is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) an ESRI file geodatabase (shdm_geology.gdb), and a 2.) Open Geospatial Consortium (OGC) geopackage. The file geodatabase format is supported with a 1.) ArcGIS Pro 3.X map file (.mapx) file (shdm_geology.mapx) and individual Pro 3.X layer (.lyrx) files (for each GIS data layer). Upon request, the GIS data is also available in ESRI shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (whis_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (whis_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (shdm_geology_metadata_faq.pdf). Please read the whis_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. QGIS software is available for free at: https://www.qgis.org/en/site/. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri.htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (shdm_geology_metadata.txt or shdm_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in ArcGIS Pro, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).
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TwitterProduction parcel layer with Situs Addresses from Assessor tables. Published weekly as an addirional parcel resource. Source parcels, maintained by Shasta County Assessor, only have the Assessor Parcel Number, this dataset includs a physical, situs, addre
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TwitterA parcel feature service for viewing land information in the City of Shasta Lake, CA. It is a representation of the taxable parcels maintained by the Shasta County Assessor Office.
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TwitterThe Digital Geologic-GIS Map of the West Shasta Copper-Zinc District, California is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) an ESRI file geodatabase (wscz_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro 3.X map file (.mapx) file (wscz_geology.mapx) and individual Pro 3.X layer (.lyrx) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (whis_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (whis_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (wscz_geology_metadata_faq.pdf). Please read the whis_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri.htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (wscz_geology_metadata.txt or wscz_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS Pro, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).
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TwitterMIT Licensehttps://opensource.org/licenses/MIT
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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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TwitterCommunities are areas within the county that are generally associated with populated locations, unincorporated towns, or incorporated cities within the Sahsta County. They are generally aligned to parcel lines, but do not have any legal definition. The
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Vector datasets of CWHR range maps are one component of California Wildlife Habitat Relationships (CWHR), a comprehensive information system and predictive model for Californias wildlife. The CWHR System was developed to support habitat conservation and management, land use planning, impact assessment, education, and research involving terrestrial vertebrates in California. CWHR contains information on life history, management status, geographic distribution, and habitat relationships for wildlife species known to occur regularly in California. Range maps represent the maximum, current geographic extent of each species within California. They were originally delineated at a scale of 1:5,000,000 by species-level experts and have gradually been revised at a scale of 1:1,000,000. For more information about CWHR, visit the CWHR webpage (https://www.wildlife.ca.gov/Data/CWHR). The webpage provides links to download CWHR data and user documents such as a look up table of available range maps including species code, species name, and range map revision history; a full set of CWHR GIS data; .pdf files of each range map or species life history accounts; and a User Guide.
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TwitterCounty Supervisorsial District boundaries and associated elected officials.
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TwitterThe Digital Geologic Map of the Bohemotash Mountain Quadrangle, California is composed of GIS data layers, two ancillary GIS tables, a Windows Help File with ancillary map text, figures and tables, GIS data layer and table FGDC metadata and ArcView 3.X legend (.AVL) files. The data were completed as a component of the Geologic Resources Evaluation (GRE) program, a National Park Service (NPS) Inventory and Monitoring (I&M) funded program that is administered by the NPS Geologic Resources Division (GRD). All GIS and ancillary tables were produced as per the NPS GIS-Geology Coverage/Shapefile Data Model (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data is available as coverage and table export (.E00) files, and as a shapefile (.SHP) and DBASEIV (.DBF) table files. The GIS data projection is NAD83, UTM Zone 10N. That data is within the area of interest of Whiskeytown-Shasta-Trinity National Recreation Area.
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TwitterThe project lead for the collection of this data was Erin Zulliger. Elk (12 adult females) were captured and equipped with GPS collars (Litetrack/Pinpoint Iridium collars, Lotek Wireless Inc., Newmarket, Ontario, Canada or Vectronic Aerospace) transmitting data from 2016-2023. The East Shasta Valley herd migrates between traditional summer and winter seasonal ranges, and migration corridors, migration stopovers, and winter ranges were modeled separately for this herd, but are not a part of this analysis. Annual home ranges were modeled using year-round data to demarcate high use areas. GPS locations were fixed at 1-13 hour intervals in the dataset. To improve the quality of the data set, the GPS data locations fixed in 2D space and visually assessed as a bad fix by the analyst were removed.The methodology used for this migration analysis allowed for the mapping of the herd’s annual range. Brownian bridge movement models (BBMMs; Sawyer et al. 2009) were constructed with GPS collar data from 12 elk, including 36 annual home range sequences, location, date, time, and average location error as inputs in Migration Mapper. BBMMs were produced at a spatial resolution of 50 m using a sequential fix interval of less than 27 hours. Home range is visualized as the 50th percentile contour (high use) and the 99th percentile contour of the year-round utilization distribution. Annual home range designations for this herd may expand with a larger sample.
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TwitterThe Digital Geologic Map of the Igo Quadrangle, California is composed of GIS data layers, two ancillary GIS tables, a Windows Help File with ancillary map text, figures and tables, GIS data layer and table FGDC metadata and ArcView 3.X legend (.AVL) files. The data were completed as a component of the Geologic Resources Evaluation (GRE) program, a National Park Service (NPS) Inventory and Monitoring (I&M) funded program that is administered by the NPS Geologic Resources Division (GRD). All GIS and ancillary tables were produced as per the NPS GIS-Geology Coverage/Shapefile Data Model (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data is available as coverage and table export (.E00) files, and as a shapefile (.SHP) and DBASEIV (.DBF) table files. The GIS data projection is NAD83, UTM Zone 10N. That data is within the area of interest of Whiskeytown-Shasta-Trinity National Recreation Area.
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This shapefile contains tax rate area (TRA) boundaries in Shasta 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
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TwitterThe Digital Geologic Map of the French Gulch 15 Minute Quadrangle, California is composed of GIS data layers, two ancillary GIS tables, a Windows Help File with ancillary map text, figures and tables, GIS data layer and table FGDC metadata and ArcView 3.X legend (.AVL) files. The data were completed as a component of the Geologic Resources Evaluation (GRE) program, a National Park Service (NPS) Inventory and Monitoring (I&M) funded program that is administered by the NPS Geologic Resources Division (GRD). All GIS and ancillary tables were produced as per the NPS GIS-Geology Coverage/Shapefile Data Model (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data is available as coverage and table export (.E00) files, and as a shapefile (.SHP) and DBASEIV (.DBF) table files. The GIS data projection is NAD83, UTM Zone 10N. That data is within the area of interest of Whiskeytown-Shasta-Trinity National Recreation Area.
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TwitterA layer representing the boundaries and pertinent information related to recorded engineering drawing in the City of Shasta Lake, CA. Recorded engineering drawings that have been mapped using GIS.
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TwitterEvery published digital survey is designated as either ‘Final’, or ‘Provisional’, depending upon its status in a peer review process.Final surveys are peer reviewed with extensive quality control methods to confirm that field attributes reflect the most detailed and specific land-use classification available, following the standard DWR Land Use Legendspecific to the survey year. Data sets are considered ‘final’ following the reconciliation of peer review comments and confirmation by the originating Regional Office. During final review, individual polygons are evaluated using a combination of aerial photointerpretation, satellite image multi-spectral data and time series analysis, comparison with other sources of land use data, and general knowledge of land use patterns at the local level.Provisional data sets have been reviewed for conformance with DWR’s published data record format, and for general agreement with other sources of land use trends. Comments based on peer review findings may not be reconciled, and no significant edits or changes are made to the original survey data.The 2005 Shasta County land use survey data set was developed by DWR through its Division of Planning and Local Assistance (DPLA). DPLA was later reorganized into the Division of Statewide Integrated Water Management and the Division of Integrated Regional Water Management. 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. Land use polygons in agricultural areas were mapped in greater detail than areas of urban or native vegetation. Quality control procedures were performed jointly by staff at DWR’s DSIWM headquarters and Northern Region, under the supervision of Tito Cervantes. The finalized countywide land use vector data is in a single, polygon, shapefile format. This data was developed to aid DWR’s ongoing efforts to monitor land use for the main purpose of determining current and projected water uses. The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR Spatial Data Standards, specifically the DWR Spatial Data Standards version 2.1, dated March 9, 2016. DWR makes no warranties or guarantees - either expressed or implied - as to the completeness, accuracy, or correctness of the data. DWR neither accepts nor assumes liability arising from or for any incorrect, incomplete, or misleading subject data. Comments, problems, improvements, updates, or suggestions should be forwarded to gis@water.ca.gov. This data represents a land use survey of Shasta County conducted by DWR, Northern District Office staff(ND), currently known as Northern Region Office, under the leadership of Tito Cervantes, Senior Land and Water Use Supervisor. The field work for this survey was conducted during the summer of 2005. ND staff physically visited each delineated field, noting the crops grown at each location. Field survey boundary date was developed using: 1. Linework developed for DWR’s 1995 survey of Shasta County was used as the starting point for the digital field boundaries developed for this survey. Where needed, Northern Region staff made corrections to the field boundaries using the 1993 Digital Orthophoto Quarter Quadrangle (DOQQ) images. After field visits had been completed, 2005 National Agricultural Imagery Program (NAIP), one-meter resolution imagery from the U.S. Department of Agriculture’s Farm Services Agency was used to locate boundary changes that had occurred since the 1993 imagery was taken. Field boundaries for this survey follow the actual borders of fields, not road center lines. Line work for the Redding area was downloaded from the City of Redding website and modified to be compatible with DWR land use categories and linework. 2. For field data collection, digital images and land use boundaries were copied onto laptop computers. The staff took these laptops into the field and virtually all agricultural fields were visited to positively identify agricultural land uses. Site visits occurred from July through September 2005. Using a standardized process, land use codes were digitized directly into the laptop computers using ArcMap. For most areas of urban land use, attributes were based upon aerial photo interpretation rather than fieldwork. 3. The digital land use map was reviewed using the 2005 NAIP four-band imagery and 2005 Landsat 5 images to identify fields that may have been misidentified. The survey data was also reviewed by summarizing land use categories and checking the results for unusual attributes or acreages. 4. After quality control procedures were completed, the data was finalized by staff in both ND and Sacramento's DPLA. Important Points about Using this Data Set: 1. The land use boundaries were drawn on-screen using orthorectified 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 a "snapshot" in time. The indicated land use attributes of each delineated area (polygon) were based upon what the surveyor saw in the field at that time, and whatever additional information the aerial photography might provide. 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. Double cropping and mixed land use must be taken into account when calculating the acreage of each crop or other land use mapped in this survey. A delineated field of 40 acres might have been cropped first with grain, then with corn, and coded as such. For double cropped fields, a “D” will be entered in the “MULTIUSE” field of the DBF file of the shapefile. To calculate the crop acreage for that field, 40 acres should be allocated to the grain category and then 40 acres should also be allocated to corn. For polygons mapped as “mixed land use”, an “M” will be entered in the “MULTIUSE” field. To calculate the appropriate acreages for each land use within this polygon, multiply the percent (as a decimal fraction) associated with each land use by the acres represented by the polygon. 4. All Land Use Codes are respresentative of the current 2016 Legend unless otherwise noted. Not all land use codes will be represented in the survey. The primary focus of this land use survey is mapping agricultural fields. Urban residences and other urban areas were delineated using aerial photo interpretation. Some urban areas may have been missed, especially in forested areas. Before final processing, standard quality control procedures were performed jointly by staff at DWR's Northern District, and at DPLA headquarters under the leadership of Jean Woods, Senior Land and Water Use Supervisor. After quality control procedures were completed, the data was finalized. The positional accuracy of the digital line work, which is based upon the 9' x 9' color photos, is approximately 23 meters. The land use attribute accuracy for agricultural fields is high, because almost every delineated field was visited by a surveyor. The accuracy is 95 percent because some errors may have occurred. Possible sources of attribute errors are: a) Human error in the identification of crop types, b) Data entry errors.
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The project leads for the collection of this data were Erin Nigon and Michael Hunnicutt. The East Shasta Valley sub-herd of Rocky Mountain elk (Cervus canadensis nelsoni) range as far east as the eastern foothills of Shasta Valley, as far north as the Klamath River, and as far south and east as Deer Mountain. In the winter, these elk spend most of their time on private ranchlands in Shasta Valley. This area offers patches of oak woodlands and grasslands on gentle slopes. In the spring, elk migrate to their summer range around Grass Lake, Bull Meadows, and Deer Mountain where the habitat is primarily characterized by mixed conifer timber stands of Ponderosa pine (Pinus ponderosa), lodgepole pine (Pinus contorta) and Douglas fir (Pseudotsuga menziesii). The meadows around Grass Lake seem especially important to this sub-herd, as neonatal calves have been documented in this area since at least 1984 (Fischer 1987). Some animals from this sub-herd have moved into Oregon periodically, while others have moved long distances eastward to other sub-herds, but Highway 97 presents a significant barrier to this movement. Most elk mortality due to vehicle collisions on Highway 97 has been documented to occur between Horsethief Creek, and Grass Lake Summit (California Department of Transportation, unpublished data). Because of this, a wildlife crossing is proposed for this area to promote habitat connectivity and wildlife movement. Elk (5 adult females, 5 juvenile [less than 1 year of age] males, and 8 juvenile females) were captured from 2016 to 2020 and equipped with Lotek satellite GPS collars. Additional GPS data was collected from elk (7 females and 1 male) in 1999-2001 and included in the analysis to supplement the small sample size of the 2016-2020 dataset. GPS locations were fixed at 4-hour intervals in the 2016-2020 dataset and 3 to 8-hour intervals in the 1999-2001 dataset.
Migration lines as symbolized connect GPS data points per elk per seasonal migration. GPS points were extracted only during migrations using net-squared displacement graphs. Fifty-one migration sequences from 10 elk, with an average migration time of 4.87 days and an average migration distance of 22.14 km, were used from the 2016-2020 dataset. Fourteen migration sequences from 8 elk, with an average migration time of 7.43 days and an average migration distance of 30.08 km, were used from the 1999-2001 dataset. Average migration distance and time were higher in 1999-2001 dataset due to a single male elk outlier; removing this outlier led to a mean migration distance of 20.36 km and a mean migration time of 5.75 days for the 1999-2001 dataset.
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TwitterThe datasets used in the creation of the predicted Habitat Suitability models includes the CWHR range maps of Californias regularly-occurring vertebrates which were digitized as GIS layers to support the predictions of the CWHR System software. These vector datasets of CWHR range maps are one component of California Wildlife Habitat Relationships (CWHR), a comprehensive information system and predictive model for Californias wildlife. The CWHR System was developed to support habitat conservation and management, land use planning, impact assessment, education, and research involving terrestrial vertebrates in California. CWHR contains information on life history, management status, geographic distribution, and habitat relationships for wildlife species known to occur regularly in California. Range maps represent the maximum, current geographic extent of each species within California. They were originally delineated at a scale of 1:5,000,000 by species-level experts and have gradually been revised at a scale of 1:1,000,000. For more information about CWHR, visit the CWHR webpage (https://www.wildlife.ca.gov/Data/CWHR). The webpage provides links to download CWHR data and user documents such as a look up table of available range maps including species code, species name, and range map revision history; a full set of CWHR GIS data; .pdf files of each range map or species life history accounts; and a User Guide.The models also used the CALFIRE-FRAP compiled "best available" land cover data known as Fveg. This compilation dataset was created as a single data layer, to support the various analyses required for the Forest and Rangeland Assessment, a legislatively mandated function. These data are being updated to support on-going analyses and to prepare for the next FRAP assessment in 2015. An accurate depiction of the spatial distribution of habitat types within California is required for a variety of legislatively-mandated government functions. The California Department of Forestry and Fire Protections CALFIRE Fire and Resource Assessment Program (FRAP), in cooperation with California Department of Fish and Wildlife VegCamp program and extensive use of USDA Forest Service Region 5 Remote Sensing Laboratory (RSL) data, has compiled the "best available" land cover data available for California into a single comprehensive statewide data set. The data span a period from approximately 1990 to 2014. Typically the most current, detailed and consistent data were collected for various regions of the state. Decision rules were developed that controlled which layers were given priority in areas of overlap. Cross-walks were used to compile the various sources into the common classification scheme, the California Wildlife Habitat Relationships (CWHR) system.CWHR range data was used together with the FVEG vegetation maps and CWHR habitat suitability ranks to create Predicted Habitat Suitability maps for species. The Predicted Habitat Suitability maps show the mean habitat suitability score for the species, as defined in CWHR. CWHR defines habitat suitability as NO SUITABILITY (0), LOW (0.33), MEDIUM (0.66), or HIGH (1) for reproduction, cover, and feeding for each species in each habitat stage (habitat type, size, and density combination). The mean is the average of the reproduction, cover, and feeding scores, and can be interpreted as LOW (less than 0.34), MEDIUM (0.34-0.66), and HIGH (greater than 0.66) suitability. Note that habitat suitability ranks were developed based on habitat patch sizes >40 acres in size, and are best interpreted for habitat patches >200 acres in size. The CWHR Predicted Habitat Suitability rasters are named according to the 4 digit alpha-numeric species CWHR ID code. The CWHR Species Lookup Table contains a record for each species including its CWHR ID, scientific name, common name, and range map revision history (available for download at https://www.wildlife.ca.gov/Data/CWHR).
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TwitterVector polygon map data of property parcels from Shasta County, California containing 101,781 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.