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COVIDcast displays signals related to COVID-19 activity levels across the United States, derived from a variety of anonymized, aggregated data sources made available by multiple partners.
One of COVIDcast streams displays results for a CMU-run symptom survey, advertised through Facebook.
This dataset is gathered using the delphi-epidata API and contains covidcast_meta and covidcast datasources.
Presently the dataset contains fb-survey data signal which is based on CMU-run symptom surveys, advertised through Facebook. Using this survey data, CMU estimate the percentage of people in a given location, on a given day that have CLI (covid-like illness = fever, along with cough, or shortness of breath, or difficulty breathing), and separately, that have ILI (influenza-like illness = fever, along with cough or sore throat).
Files are organized in folders based on the spatial resolution of fb-survey data (state, county, hrr, msa).
Each file contains the percentage of people in a given location, on a given day that have CLI or ILI. Data consists of raw and smoothed estimates and is gathered for all time values available at delphi-epidata.
Each file contains the following columns: - geo_value - location code - time_value - time unit (e.g. date) over which underlying events happened - direction - trend classifier (+1 -> increasing, 0 steady or not determined, -1 -> decreasing) - value - value (statistic) derived from the underlying data source - stderr - standard error of the statistic with respect to its sampling distribution, null when not applicable - sample_size - number of "data points" used in computing the statistic, null when not applicable
Additionally, the dataset contains the most recent covidcast_meta where you can find the summary statistics for fb-survey data.
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Twittero Neighborhood Mixed Use (NMU)Economic development potential estimated to be, but not limited to:• Up to 100,000 ft2 of retail• 1 to 2-mile trade areao Employment Mixed Use (EMU)Economic development potential estimated to be, but not limited to:• Office, warehousing, tech/flex• Some retailo Community Mixed Use (CMU)Economic development potential estimated to be, but not limited to:• Up to 350,000 ft2 of retail• 4 to 6-mile trade areao Regional Mixed Use (RMU)Economic development potential estimated to be, but not limited to:• Over 500,000 ft2 of retail• >10-mile trade area
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TwitterThe data set for the Butler Peak 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, as part of an ongoing effort to utilize a Geographical Information System (GIS) format to create a regional digital geologic database for southern California. This regional database is being developed as a contribution to the National Geologic Map Data Base of the National Cooperative Geologic Mapping Program of the USGS. Development of the data set for the Butler Peak quadrangle has also been supported by the U.S. Forest Service, San Bernardino National Forest.
The digital geologic map database for the Butler Peak quadrangle has been created as a general-purpose data set that is applicable to other land-related investigations in the earth and biological sciences. For example, the U.S. Forest Service, San Bernardino National Forest, is using the database as part of a study of an endangered plant species that shows preference for particular rock type environments. The Butler Peak database is not suitable for site-specific geologic evaluations at scales greater than 1:24,000 (1 in = 2,000 ft).
This data set maps and describes the geology of the Butler Peak 7.5' quadrangle, San Bernardino County, California. Created using Environmental Systems Research Institute's ARC/INFO software, the data base consists of the following items: (1) a map coverage showing geologic contacts and units,(2) a scanned topographic base at a scale of 1:24,000, and (3) 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 on a 1:24,000 topographic base accompanied by a Description of Map Units (DMU), a Correlation of Map Units (CMU), and a key to point and line symbols; (2) PDF files of the DMU and CMU, and of this Readme, and (3) this metadata file.
The geologic map data base contains original U.S. Geological Survey data generated by detailed field observation and by interpretation of aerial photographs. The map was created by transferring lines from the aerial photographs to a 1:24,000 mylar orthophoto-quadrangle and then to a base-stable topographic map. This map was then scribed, and a .007 mil, right-reading, black line clear film made by contact photographic processes.The black line was scanned and auto-vectorized by Optronics Specialty Company, Northridge, CA. The non-attributed scan was imported into ARC/INFO, where the database was built. Within the database, geologic contacts are represented as lines (arcs), geologic units as polygons, 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.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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The General Plan guides future growth for the city, and is redone every 15-20 years. Localized changes occur in between major general plan updates. The General Plan divides the city and its sphere of influence into distinct land use categories, outlined below: The current General Plan was adopted February 2024. The new plan is expected to be in effect until 2043. For more information, visit the Manteca General Plan Update website.General Plan Codes:AG - AgricultureAI - Agricultural IndustrialC - CommercialCMU - Commercial Mixed UseDW - DowntownVLDR - Very Low Density Residential 0.5 to 2 dwelling units/acre (du/ac)LDR - Low Density Residential 2.1 to 8 du/acMDR - Medium Density Residential 8.1 to 20 du/acHDR - High Density Residential 20.1 to 30 du/acBIP - Business Industrial ParkBP - Business ProfessionalI - IndustrialOS - Open SpaceP - ParkPQP - Public/Quasi-PublicUR - Urban ReserveUR-AG - Urban Reserve AgricultureUR-CMU - Urban Reserve Commercial Mixed UseUR-C - Urban Reserve CommercialUR-VLDR - Urban Reserve Very Low Density ResidentialUR-LDR - Urban Reserve Low Density ResidentialUR-MDR - Urban Reserve Medium Density ResidentialUR-BIP - Urban Reserve Business Industrial ParkUR-I - Urban Reserve IndustrialUR-P - Urban Reserve ParkUR-PQP - Urban Reserve Public/Quasi-Public
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o Neighborhood Mixed Use (NMU)Economic development potential estimated to be, but not limited to:• Up to 100,000 ft2 of retail• 1 to 2-mile trade areao Employment Mixed Use (EMU)Economic development potential estimated to be, but not limited to:• Office, warehousing, tech/flex• Some retailo Recreational Mixed Use (XMU)Economic development anchored by a recreational amenity:• Size of businesses and services dependnet upon amenity size• Pedestrian and bicycle mobility preservedo Community Mixed Use (CMU)Economic development potential estimated to be, but not limited to:• Up to 350,000 ft2 of retail• 4 to 6-mile trade areao Regional Mixed Use (RMU)Economic development potential estimated to be, but not limited to:• Over 350,000 ft2 of retail• >10-mile trade area
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
COVIDcast displays signals related to COVID-19 activity levels across the United States, derived from a variety of anonymized, aggregated data sources made available by multiple partners.
One of COVIDcast streams displays results for a CMU-run symptom survey, advertised through Facebook.
This dataset is gathered using the delphi-epidata API and contains covidcast_meta and covidcast datasources.
Presently the dataset contains fb-survey data signal which is based on CMU-run symptom surveys, advertised through Facebook. Using this survey data, CMU estimate the percentage of people in a given location, on a given day that have CLI (covid-like illness = fever, along with cough, or shortness of breath, or difficulty breathing), and separately, that have ILI (influenza-like illness = fever, along with cough or sore throat).
Files are organized in folders based on the spatial resolution of fb-survey data (state, county, hrr, msa).
Each file contains the percentage of people in a given location, on a given day that have CLI or ILI. Data consists of raw and smoothed estimates and is gathered for all time values available at delphi-epidata.
Each file contains the following columns: - geo_value - location code - time_value - time unit (e.g. date) over which underlying events happened - direction - trend classifier (+1 -> increasing, 0 steady or not determined, -1 -> decreasing) - value - value (statistic) derived from the underlying data source - stderr - standard error of the statistic with respect to its sampling distribution, null when not applicable - sample_size - number of "data points" used in computing the statistic, null when not applicable
Additionally, the dataset contains the most recent covidcast_meta where you can find the summary statistics for fb-survey data.