100+ datasets found
  1. 🌎 Location Intelligence Data | From Google Map

    • kaggle.com
    zip
    Updated Apr 21, 2024
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    Azhar Saleem (2024). 🌎 Location Intelligence Data | From Google Map [Dataset]. https://www.kaggle.com/datasets/azharsaleem/location-intelligence-data-from-google-map
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    zip(1911275 bytes)Available download formats
    Dataset updated
    Apr 21, 2024
    Authors
    Azhar Saleem
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    👨‍💻 Author: Azhar Saleem

    "https://github.com/azharsaleem18" target="_blank"> https://img.shields.io/badge/GitHub-Profile-blue?style=for-the-badge&logo=github" alt="GitHub Profile"> "https://www.kaggle.com/azharsaleem" target="_blank"> https://img.shields.io/badge/Kaggle-Profile-blue?style=for-the-badge&logo=kaggle" alt="Kaggle Profile"> "https://www.linkedin.com/in/azhar-saleem/" target="_blank"> https://img.shields.io/badge/LinkedIn-Profile-blue?style=for-the-badge&logo=linkedin" alt="LinkedIn Profile">
    "https://www.youtube.com/@AzharSaleem19" target="_blank"> https://img.shields.io/badge/YouTube-Profile-red?style=for-the-badge&logo=youtube" alt="YouTube Profile"> "https://www.facebook.com/azhar.saleem1472/" target="_blank"> https://img.shields.io/badge/Facebook-Profile-blue?style=for-the-badge&logo=facebook" alt="Facebook Profile"> "https://www.tiktok.com/@azhar_saleem18" target="_blank"> https://img.shields.io/badge/TikTok-Profile-blue?style=for-the-badge&logo=tiktok" alt="TikTok Profile">
    "https://twitter.com/azhar_saleem18" target="_blank"> https://img.shields.io/badge/Twitter-Profile-blue?style=for-the-badge&logo=twitter" alt="Twitter Profile"> "https://www.instagram.com/azhar_saleem18/" target="_blank"> https://img.shields.io/badge/Instagram-Profile-blue?style=for-the-badge&logo=instagram" alt="Instagram Profile"> "mailto:azharsaleem6@gmail.com"> https://img.shields.io/badge/Email-Contact%20Me-red?style=for-the-badge&logo=gmail" alt="Email Contact">

    Dataset Overview

    Welcome to the Google Places Comprehensive Business Dataset! This dataset has been meticulously scraped from Google Maps and presents extensive information about businesses across several countries. Each entry in the dataset provides detailed insights into business operations, location specifics, customer interactions, and much more, making it an invaluable resource for data analysts and scientists looking to explore business trends, geographic data analysis, or consumer behaviour patterns.

    Key Features

    • Business Details: Includes unique identifiers, names, and contact information.
    • Geolocation Data: Precise latitude and longitude for pinpointing business locations on a map.
    • Operational Timings: Detailed opening and closing hours for each day of the week, allowing analysis of business activity patterns.
    • Customer Engagement: Data on review counts and ratings, offering insights into customer satisfaction and business popularity.
    • Additional Attributes: Links to business websites, time zone information, and country-specific details enrich the dataset for comprehensive analysis.

    Potential Use Cases

    This dataset is ideal for a variety of analytical projects, including: - Market Analysis: Understand business distribution and popularity across different regions. - Customer Sentiment Analysis: Explore relationships between customer ratings and business characteristics. - Temporal Trend Analysis: Analyze patterns of business activity throughout the week. - Geospatial Analysis: Integrate with mapping software to visualise business distribution or cluster businesses based on location.

    Dataset Structure

    The dataset contains 46 columns, providing a thorough profile for each listed business. Key columns include:

    • business_id: A unique Google Places identifier for each business, ensuring distinct entries.
    • phone_number: The contact number associated with the business. It provides a direct means of communication.
    • name: The official name of the business as listed on Google Maps.
    • full_address: The complete postal address of the business, including locality and geographic details.
    • latitude: The geographic latitude coordinate of the business location, useful for mapping and spatial analysis.
    • longitude: The geographic longitude coordinate of the business location.
    • review_count: The total number of reviews the business has received on Google Maps.
    • rating: The average user rating out of 5 for the business, reflecting customer satisfaction.
    • timezone: The world timezone the business is located in, important for temporal analysis.
    • website: The official website URL of the business, providing further information and contact options.
    • category: The category or type of service the business provides, such as restaurant, museum, etc.
    • claim_status: Indicates whether the business listing has been claimed by the owner on Google Maps.
    • plus_code: A sho...
  2. Digital Geologic Map of the U.S. Geological Survey Mapping in the Western...

    • catalog.data.gov
    Updated Nov 25, 2025
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    National Park Service (2025). Digital Geologic Map of the U.S. Geological Survey Mapping in the Western Portion of Amistad National Recreation Area, Texas (NPS, GRD, GRI, AMIS, WPAM digital map) [Dataset]. https://catalog.data.gov/dataset/digital-geologic-map-of-the-u-s-geological-survey-mapping-in-the-western-portion-of-amista
    Explore at:
    Dataset updated
    Nov 25, 2025
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Area covered
    Texas
    Description

    The Digital Geologic Map of the U.S. Geological Survey Mapping in the Western Portion of Amistad National Recreation Area, 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: Eddie Collins, Amanda Masterson and Tom Tremblay (Texas Bureau of Economic Geology); Rick Page (U.S. Geological Survey); Gilbert Anaya (International Boundary and Water Commission). Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation sections(s) of this metadata record (wpam_metadata.txt; available at http://nrdata.nps.gov/amis/nrdata/geology/gis/wpam_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 (wpam_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 Amistad National Recreation Area.

  3. h

    MAP-CC

    • huggingface.co
    Updated Apr 5, 2024
    + more versions
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    Multimodal Art Projection (2024). MAP-CC [Dataset]. https://huggingface.co/datasets/m-a-p/MAP-CC
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 5, 2024
    Dataset authored and provided by
    Multimodal Art Projection
    License

    Attribution-NonCommercial-NoDerivs 4.0 (CC BY-NC-ND 4.0)https://creativecommons.org/licenses/by-nc-nd/4.0/
    License information was derived automatically

    Description

    MAP-CC

    🌐 Homepage | 🤗 MAP-CC | 🤗 CHC-Bench | 🤗 CT-LLM | 📖 arXiv | GitHub An open-source Chinese pretraining dataset with a scale of 800 billion tokens, offering the NLP community high-quality Chinese pretraining data.

      Disclaimer
    

    This model, developed for academic purposes, employs rigorously compliance-checked training data to uphold the highest standards of integrity and compliance. Despite our efforts, the inherent complexities of data and the broad spectrum of… See the full description on the dataset page: https://huggingface.co/datasets/m-a-p/MAP-CC.

  4. Google Maps Dataset

    • brightdata.com
    .json, .csv, .xlsx
    Updated Jan 8, 2023
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    Bright Data (2023). Google Maps Dataset [Dataset]. https://brightdata.com/products/datasets/google-maps
    Explore at:
    .json, .csv, .xlsxAvailable download formats
    Dataset updated
    Jan 8, 2023
    Dataset authored and provided by
    Bright Datahttps://brightdata.com/
    License

    https://brightdata.com/licensehttps://brightdata.com/license

    Area covered
    Worldwide
    Description

    The Google Maps dataset is ideal for getting extensive information on businesses anywhere in the world. Easily filter by location, business type, and other factors to get the exact data you need. The Google Maps dataset includes all major data points: timestamp, name, category, address, description, open website, phone number, open_hours, open_hours_updated, reviews_count, rating, main_image, reviews, url, lat, lon, place_id, country, and more.

  5. USGS National Map

    • maps.openlaredo.com
    • data.openlaredo.com
    • +22more
    Updated Dec 2, 2014
    + more versions
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    Esri (2014). USGS National Map [Dataset]. https://maps.openlaredo.com/maps/6d9fa6d159ae4a1f80b9e296ed300767
    Explore at:
    Dataset updated
    Dec 2, 2014
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    The USGS Topo base map service from The National Map is a combination of contours, shaded relief, woodland and urban tint, along with vector layers, such as geographic names, governmental unit boundaries, hydrography, structures, and transportation, to provide a composite topographic base map. Data sources are the National Atlas for small scales, and The National Map for medium to large scales.

  6. Human Geography Map

    • esriaustraliahub.com.au
    • data.baltimorecity.gov
    • +19more
    Updated Feb 2, 2017
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    Esri (2017). Human Geography Map [Dataset]. https://www.esriaustraliahub.com.au/maps/3582b744bba84668b52a16b0b6942544
    Explore at:
    Dataset updated
    Feb 2, 2017
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    The Human Geography Map (World Edition) web map provides a detailed vector basemap with a monochromatic style and content adjusted to support Human Geography information. Where possible, the map content has been adjusted so that it observes WCAG contrast criteria.This basemap, included in the ArcGIS Living Atlas of the World, uses 3 vector tile layers:Human Geography Label, a label reference layer including cities and communities, countries, administrative units, and at larger scales street names.Human Geography Detail, a detail reference layer including administrative boundaries, roads and highways, and larger bodies of water. This layer is designed to be used with a high degree of transparency so that the detail does not compete with your information. It is set at approximately 50% in this web map, but can be adjusted.Human Geography Base, a simple basemap consisting of land areas in a very light gray only.The vector tile layers in this web map are built using the same data sources used for other Esri Vector Basemaps. For details on data sources contributed by the GIS community, view the map of Community Maps Basemap Contributors. Esri Vector Basemaps are updated monthly.Learn more about this basemap from the cartographic designer in Introducing a Human Geography Basemap.Use this MapThis map is designed to be used as a basemap for overlaying other layers of information or as a stand-alone reference map. You can add layers to this web map and save as your own map. If you like, you can add this web map to a custom basemap gallery for others in your organization to use in creating web maps. If you would like to add this map as a layer in other maps you are creating, you may use the tile layer item referenced in this map.

  7. GIBS Web Map Tile Service (WMTS)

    • catalog.data.gov
    • datasets.ai
    • +2more
    Updated Apr 10, 2025
    + more versions
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    National Aeronautics and Space Administration (2025). GIBS Web Map Tile Service (WMTS) [Dataset]. https://catalog.data.gov/dataset/gibs-web-map-tile-service-wmts
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    Dataset updated
    Apr 10, 2025
    Dataset provided by
    NASAhttp://nasa.gov/
    Description

    The WMTS implementation standard provides a standards-based solution for serviing digital maps using predefined image tiles. Through the constructs of the specification, a WMTS service advertises imagery layers (e.g. imagery product) and defines the coordinate reference system, scale, and tiling grid available for access.

  8. Community Map

    • noveladata.com
    • data.baltimorecity.gov
    • +11more
    Updated Feb 16, 2019
    + more versions
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    Esri (2019). Community Map [Dataset]. https://www.noveladata.com/maps/esri::community-map/about
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    Dataset updated
    Feb 16, 2019
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    The Community Map (World Edition) web map provides a customized world basemap that is uniquely symbolized and optimized to display special areas of interest (AOIs) that have been created and edited by Community Maps contributors. These special areas of interest include landscaping features such as grass, trees, and sports amenities like tennis courts, football and baseball field lines, and more. This basemap, included in the ArcGIS Living Atlas of the World, uses the Community vector tile layer. The vector tile layer in this web map is built using the same data sources used for other Esri Vector Basemaps. For details on data sources contributed by the GIS community, view the map of Community Maps Basemap Contributors. Esri Vector Basemaps are updated monthly.Use this MapThis map is designed to be used as a basemap for overlaying other layers of information or as a stand-alone reference map. You can add layers to this web map and save as your own map. If you like, you can add this web map to a custom basemap gallery for others in your organization to use in creating web maps. If you would like to add this map as a layer in other maps you are creating, you may use the layer items referenced in this map.

  9. OpenStreetMap

    • noveladata.com
    • data.buncombecounty.org
    • +39more
    Updated Mar 20, 2019
    + more versions
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    esri_en (2019). OpenStreetMap [Dataset]. https://www.noveladata.com/maps/c29cfb7875fc4b97b58ba6987c460862
    Explore at:
    Dataset updated
    Mar 20, 2019
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    esri_en
    Area covered
    Description

    This web map presents a vector basemap of OpenStreetMap (OSM) data hosted by Esri. Esri created this vector tile basemap from the Daylight map distribution of OSM data, which is supported by Facebook and supplemented with additional data from Microsoft. This version of the map is rendered using OSM cartography. The OSM Daylight map will be updated every month with the latest version of OSM Daylight data.OpenStreetMap is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap site:www.OpenStreetMap.org. Esri is a supporter of the OSM project and is excited to make this enhanced vector basemap available to the ArcGIS user and developer communities.

  10. A Children’s Map

    • hub.arcgis.com
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    Updated May 30, 2017
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    Esri (2017). A Children’s Map [Dataset]. https://hub.arcgis.com/maps/802841aae4dd45778801cd1d375795b9
    Explore at:
    Dataset updated
    May 30, 2017
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    If you like giraffe, moose, or kangaroo you just might like this map. Welcome to a new multiscale Children’s Map of the World. It covers scales ranges 296 million to 578 thousand. See the blog Animal Crackers in My Soup! Play, explore, see if you can discover some hidden creatures. Rumour has it, there be Yeti in this map.This map was designed and created by Wesley Jones.

  11. M

    Interactive GIS Map, Dakota County, Minnesota

    • gisdata.mn.gov
    • data.wu.ac.at
    webapp
    Updated Jan 5, 2022
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    Dakota County (2022). Interactive GIS Map, Dakota County, Minnesota [Dataset]. https://gisdata.mn.gov/dataset/us-mn-co-dakota-base-dcgis
    Explore at:
    webappAvailable download formats
    Dataset updated
    Jan 5, 2022
    Dataset provided by
    Dakota County
    Area covered
    Dakota County, Minnesota
    Description


    DCGIS is an interactive map that provides increased functionality for advanced users as well as access to about 150 layers of GIS data, including parcel information, contour lines, aerial photography, county park amenities, park trails, bikeways, county road construction, roundabouts, floodplains and more. It allows you to create a map at any scale you wish.
    The Interactive GIS Map is intended for use on any device - mobile or desktop - with high speed access.

  12. Facility Finder Detail Map

    • data.chhs.ca.gov
    • data.ca.gov
    • +3more
    html, zip
    Updated Aug 23, 2024
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    Department of Health Care Access and Information (2024). Facility Finder Detail Map [Dataset]. https://data.chhs.ca.gov/dataset/facility-finder-detail-map
    Explore at:
    html, zipAvailable download formats
    Dataset updated
    Aug 23, 2024
    Dataset authored and provided by
    Department of Health Care Access and Information
    Description

    Do not delete.


    This web map is used on the OSHPD website as the detail map for facility detail pages. The map is passed an address via the URL to be placed on the map. This page shows an example of this use: https://oshpd.ca.gov/facility/university-of-california-davis-medical-center/

  13. d

    Matrixian Map (global map data)

    • datarade.ai
    Updated Oct 8, 2020
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    Matrixian (2020). Matrixian Map (global map data) [Dataset]. https://datarade.ai/data-products/matrixian-map-matrixian-group
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    Dataset updated
    Oct 8, 2020
    Dataset authored and provided by
    Matrixian
    Area covered
    France
    Description

    For many people data is seen as abstract information. It is therefore valuable to use Matrixian Map, an interactive map that shows an enormous amount of data in one figure. It helps to make complex analyzes understandable, to see new opportunities and to make data-driven decisions.

    With our large amount of consumer, real estate, mobility and logistics data we can design very extensive maps. Whether it concerns a map that shows your (potential) customers, shows on which roofs solar panels can be placed or indicates when shopping areas can be supplied, with our knowledge of households, companies and objects, almost anything is possible!

  14. h

    emoji-map

    • huggingface.co
    Updated Sep 12, 2024
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    Omar Kamali (2024). emoji-map [Dataset]. https://huggingface.co/datasets/omarkamali/emoji-map
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 12, 2024
    Authors
    Omar Kamali
    Description

    📊 Dataset Overview

    The emoji-map dataset, created by omarkamali, contains text data in parquet format. It consists of 10K-100K entries, specifically 5.03k rows. The dataset is available in the train split.

      📁 Data Structure
    

    The dataset includes two main columns: emoji and unicode_description. The emoji column contains various emoji characters, while the unicode_description column provides a textual description of each emoji.

      🔍 Sample Data
    

    Examples from the… See the full description on the dataset page: https://huggingface.co/datasets/omarkamali/emoji-map.

  15. a

    Parcel Map - Public

    • accessauburn-auburnme.hub.arcgis.com
    • presentation-auburnme.hub.arcgis.com
    • +1more
    Updated Nov 1, 2019
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    AccessAuburn (2019). Parcel Map - Public [Dataset]. https://accessauburn-auburnme.hub.arcgis.com/maps/4d8678df85254eeb85cdb08a85f15782
    Explore at:
    Dataset updated
    Nov 1, 2019
    Dataset authored and provided by
    AccessAuburn
    Area covered
    Description

    Auburn Maine's parcel Inquiry map with optional zoning and high-resolution aerial photography. Optional zoning layers. Map provides detailed assessing data for each parcel as well as links to WebPro assessing records and Google Street View. Users can search for parcels using parcel ID, location, or owner name. Advanced search options provide ability to select and buffer parcels with an optional export to csv file.

  16. OpenStreetMap (Blueprint)

    • data-sarasota.opendata.arcgis.com
    • datasets.ai
    • +14more
    Updated Aug 30, 2019
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    Esri (2019). OpenStreetMap (Blueprint) [Dataset]. https://data-sarasota.opendata.arcgis.com/maps/46a87c20f09e4fc48fa3c38081e0cae6
    Explore at:
    Dataset updated
    Aug 30, 2019
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    Mature Support Notice: This item is in mature support as of December 2024. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version. See blog for more information. This web map presents a vector basemap of OpenStreetMap (OSM) data hosted by Esri. It presents the map in a cartographic style is like a blueprint technical drawing. Created from the sunsetted Daylight map distribution, data updates supporting this layer are no longer available.OpenStreetMap is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap site: www.OpenStreetMap.org. Esri is a supporter of the OSM project.

  17. N

    USGS National Geologic Map Database

    • catalog.newmexicowaterdata.org
    html
    Updated Oct 23, 2023
    + more versions
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    US Geological Survey (2023). USGS National Geologic Map Database [Dataset]. https://catalog.newmexicowaterdata.org/dataset/usgs-national-geologic-map-database
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Oct 23, 2023
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    License

    Open Data Commons Attribution License (ODC-By) v1.0https://www.opendatacommons.org/licenses/by/1.0/
    License information was derived automatically

    Description

    Distributed archive of standardized geoscience information.

  18. a

    National Riparian Area Base Map

    • data-usfs.hub.arcgis.com
    • datasetcatalog.nlm.nih.gov
    • +8more
    Updated Jan 28, 2021
    + more versions
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    U.S. Forest Service (2021). National Riparian Area Base Map [Dataset]. https://data-usfs.hub.arcgis.com/datasets/16f0db417a1a4e529e92cb74b86fea34
    Explore at:
    Dataset updated
    Jan 28, 2021
    Dataset authored and provided by
    U.S. Forest Service
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Description

    This imagery layer shows national riparian areas for the conterminous United States. Riparian areas are an important natural resource with high biological diversity. These ecosystems contain specific vegetation and soil characteristics which support irreplaceable values and multiple ecosystem functions and are very responsive to changes in land management activities. Delineating and quantifying riparian areas is an essential step in riparian monitoring, planning, management, and policy decisions. USDA Forest Service supports the development and implementation of a national context framework with a multi-scale approach to define riparian areas utilizing free available national geospatial datasets.Why was this layer created? To estimate 50-year flood height riparian areas to support statistical analysis, map display, and model parameterization.Provide a framework and an end product to stakeholders and apply the information into management actions and strategies.Multi-scale approach to provide a national and regional report map. Create a product for managers to easily understand where to apply the information at various scales.Develop a national context inventory of riparian areas and their condition within national forests and rangelands.How was this layer created? Using freely available data.Develop cost effective modeling approach & technique.Multi-scale (national, regional, & local).Promote technology transfer to train/reach out to our partners.Fifty-year flood heights were estimated using U.S. Geological Survey (USGS) stream gage information. NHDPlus version 2.1 was used as the hydrologic framework to delineate riparian areas. The U.S. Fish and Wildlife Service's National Wetland Inventory and USGS 10-meter digital elevation models were also used in processing these data.The data are '1' if in the riparian zone and 'NoData' if outside the riparian zone. When displayed on a map, riparian zone cells are color-coded 'blue' with 25% transparency.For additional information regarding methodologies for modeling and processing these data, see Abood et al. (2012) and the National Riparian Areas Base Map StoryMapData Download: https://www.fs.usda.gov/rds/archive/catalog/RDS-2019-0030

  19. Digital Geologic-GIS Map of Mount Rainier National Park, Washington (NPS,...

    • catalog.data.gov
    • datasets.ai
    • +1more
    Updated Nov 11, 2025
    + more versions
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    National Park Service (2025). Digital Geologic-GIS Map of Mount Rainier National Park, Washington (NPS, GRD, GRI, MORA, MORA_geology digital map) adapted from a U.S. Geological Survey Miscellaneous Geologic Investigations Map by Fiske, Hopson and Waters (1964) [Dataset]. https://catalog.data.gov/dataset/digital-geologic-gis-map-of-mount-rainier-national-park-washington-nps-grd-gri-mora-mora-g
    Explore at:
    Dataset updated
    Nov 11, 2025
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Area covered
    Mount Rainier
    Description

    The Digital Geologic-GIS Map of Mount Rainier National Park, Washington is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (mora_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 map file (.mapx) file and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (mora_geology.mxd) and individual 10.1 layer (.lyr) 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 10.1 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.) this file (mora_geology.gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (mora_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 (mora_geology_metadata_faq.pdf). Please read the mora_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: http://www.google.com/earth/index.html. 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: 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 (mora_geology_metadata.txt or mora_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 1:62,500 and United States National Map Accuracy Standards features are within (horizontally) 31.8 meters or 104.2 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, 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). The GIS data projection is NAD83, UTM Zone 10N, however, for the KML/KMZ format the data is projected upon export to WGS84 Geographic, the native coordinate system used by Google Earth.

  20. Statewide Crop Mapping

    • data.cnra.ca.gov
    • data.ca.gov
    • +1more
    data, gdb, html, pdf +3
    Updated Sep 29, 2025
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    California Department of Water Resources (2025). Statewide Crop Mapping [Dataset]. https://data.cnra.ca.gov/dataset/statewide-crop-mapping
    Explore at:
    gdb(85891531), shp(107610538), zip(140021333), zip(169400976), data, zip(98690638), shp(126828193), gdb(76631083), shp(126548912), zip(144060723), gdb(86655350), zip(88308707), gdb(86886429), zip(159870566), zip(94630663), rest service, zip(189880202), html, zip(179113742), pdf(353198)Available download formats
    Dataset updated
    Sep 29, 2025
    Dataset authored and provided by
    California Department of Water Resourceshttp://www.water.ca.gov/
    Description

    The California Department of Water Resources (DWR) has been collecting land use data throughout the state and using it to develop agricultural water use estimates for statewide and regional planning purposes, including water use projections, water use efficiency evaluations, groundwater model developments, climate change mitigation and adaptations, and water transfers. These data are essential for regional analysis and decision making, which has become increasingly important as DWR and other state agencies seek to address resource management issues, regulatory compliances, environmental impacts, ecosystem services, urban and economic development, and other issues. Increased availability of digital satellite imagery, aerial photography, and new analytical tools make remote sensing-based land use surveys possible at a field scale that is comparable to that of DWR’s historical on the ground field surveys. Current technologies allow accurate large-scale crop and land use identifications to be performed at desired time increments and make possible more frequent and comprehensive statewide land use information. Responding to this need, DWR sought expertise and support for identifying crop types and other land uses and quantifying crop acreages statewide using remotely sensed imagery and associated analytical techniques. Currently, Statewide Crop Maps are available for the Water Years 2014, 2016, 2018- 2022 and PROVISIONALLY for 2023.

    For the latest Land Use Legend, 2022-DWR-Standard-Land-Use-Legend-Remote-Sensing-Version.pdf, please see the Data and Resources section below.

    Historic County Land Use Surveys spanning 1986 - 2015 may also be accessed using the CADWR Land Use Data Viewer: https://gis.water.ca.gov/app/CADWRLandUseViewer.

    For Regional Land Use Surveys follow: https://data.cnra.ca.gov/dataset/region-land-use-surveys.

    For County Land Use Surveys follow: https://data.cnra.ca.gov/dataset/county-land-use-surveys.

    For a collection of ArcGIS Web Applications that provide information on the DWR Land Use Program and our data products in various formats, visit the DWR Land Use Gallery: https://storymaps.arcgis.com/collections/dd14ceff7d754e85ab9c7ec84fb8790a.

    Recommended citation for DWR land use data: California Department of Water Resources. (Water Year for the data). Statewide Crop Mapping—California Natural Resources Agency Open Data. Retrieved “Month Day, YEAR,” from https://data.cnra.ca.gov/dataset/statewide-crop-mapping.

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Azhar Saleem (2024). 🌎 Location Intelligence Data | From Google Map [Dataset]. https://www.kaggle.com/datasets/azharsaleem/location-intelligence-data-from-google-map
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🌎 Location Intelligence Data | From Google Map

Geo-Spatial Analytics Ready: Comprehensive Mapping Data from Google Maps

Explore at:
zip(1911275 bytes)Available download formats
Dataset updated
Apr 21, 2024
Authors
Azhar Saleem
License

Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically

Description

👨‍💻 Author: Azhar Saleem

"https://github.com/azharsaleem18" target="_blank"> https://img.shields.io/badge/GitHub-Profile-blue?style=for-the-badge&logo=github" alt="GitHub Profile"> "https://www.kaggle.com/azharsaleem" target="_blank"> https://img.shields.io/badge/Kaggle-Profile-blue?style=for-the-badge&logo=kaggle" alt="Kaggle Profile"> "https://www.linkedin.com/in/azhar-saleem/" target="_blank"> https://img.shields.io/badge/LinkedIn-Profile-blue?style=for-the-badge&logo=linkedin" alt="LinkedIn Profile">
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Dataset Overview

Welcome to the Google Places Comprehensive Business Dataset! This dataset has been meticulously scraped from Google Maps and presents extensive information about businesses across several countries. Each entry in the dataset provides detailed insights into business operations, location specifics, customer interactions, and much more, making it an invaluable resource for data analysts and scientists looking to explore business trends, geographic data analysis, or consumer behaviour patterns.

Key Features

  • Business Details: Includes unique identifiers, names, and contact information.
  • Geolocation Data: Precise latitude and longitude for pinpointing business locations on a map.
  • Operational Timings: Detailed opening and closing hours for each day of the week, allowing analysis of business activity patterns.
  • Customer Engagement: Data on review counts and ratings, offering insights into customer satisfaction and business popularity.
  • Additional Attributes: Links to business websites, time zone information, and country-specific details enrich the dataset for comprehensive analysis.

Potential Use Cases

This dataset is ideal for a variety of analytical projects, including: - Market Analysis: Understand business distribution and popularity across different regions. - Customer Sentiment Analysis: Explore relationships between customer ratings and business characteristics. - Temporal Trend Analysis: Analyze patterns of business activity throughout the week. - Geospatial Analysis: Integrate with mapping software to visualise business distribution or cluster businesses based on location.

Dataset Structure

The dataset contains 46 columns, providing a thorough profile for each listed business. Key columns include:

  • business_id: A unique Google Places identifier for each business, ensuring distinct entries.
  • phone_number: The contact number associated with the business. It provides a direct means of communication.
  • name: The official name of the business as listed on Google Maps.
  • full_address: The complete postal address of the business, including locality and geographic details.
  • latitude: The geographic latitude coordinate of the business location, useful for mapping and spatial analysis.
  • longitude: The geographic longitude coordinate of the business location.
  • review_count: The total number of reviews the business has received on Google Maps.
  • rating: The average user rating out of 5 for the business, reflecting customer satisfaction.
  • timezone: The world timezone the business is located in, important for temporal analysis.
  • website: The official website URL of the business, providing further information and contact options.
  • category: The category or type of service the business provides, such as restaurant, museum, etc.
  • claim_status: Indicates whether the business listing has been claimed by the owner on Google Maps.
  • plus_code: A sho...
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