100+ datasets found
  1. P

    MAPS Dataset

    • paperswithcode.com
    Updated Aug 6, 2010
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    (2010). MAPS Dataset [Dataset]. https://paperswithcode.com/dataset/maps
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    Dataset updated
    Aug 6, 2010
    Description

    MAPS – standing for MIDI Aligned Piano Sounds – is a database of MIDI-annotated piano recordings. MAPS has been designed in order to be released in the music information retrieval research community, especially for the development and the evaluation of algorithms for single-pitch or multipitch estimation and automatic transcription of music. It is composed by isolated notes, random-pitch chords, usual musical chords and pieces of music. The database provides a large amount of sounds obtained in various recording conditions.

  2. d

    Digital database of structure contour and isopach maps of multiple...

    • catalog.data.gov
    • data.usgs.gov
    • +1more
    Updated Jul 6, 2024
    + more versions
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    U.S. Geological Survey (2024). Digital database of structure contour and isopach maps of multiple subsurface units, Michigan and Illinois Basins, USA [Dataset]. https://catalog.data.gov/dataset/digital-database-of-structure-contour-and-isopach-maps-of-multiple-subsurface-units-michig-634cc
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    Dataset updated
    Jul 6, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    United States
    Description

    This digital data release presents contour data from multiple subsurface geologic horizons as presented in previously published summaries of the regional subsurface configuration of the Michigan and Illinois Basins. The original maps that served as the source of the digital data within this geodatabase are from the Geological Society of America’s Decade of North American Geology project series, “The Geology of North America” volume D-2, chapter 13 “The Michigan Basin” and chapter 14 “Illinois Basin Region”. Contour maps in the original published chapters were generated from geophysical well logs (generally gamma-ray) and adapted from previously published contour maps. The published contour maps illustrated the distribution sedimentary strata within the Illinois and Michigan Basin in the context of the broad 1st order supercycles of L.L. Sloss including the Sauk, Tippecanoe, Kaskaskia, Absaroka, Zuni, and Tejas supersequences. Because these maps represent time-transgressive surfaces, contours frequently delineate the composite of multiple named sedimentary formations at once. Structure contour maps on the top of the Precambrian basement surface in both the Michigan and Illinois basins illustrate the general structural geometry which undergirds the sedimentary cover. Isopach maps of the Sauk 2 and 3, Tippecanoe 1 and 2, Kaskaskia 1 and 2, Absaroka, and Zuni sequences illustrate the broad distribution of sedimentary units in the Michigan Basin, as do isopach maps of the Sauk, Upper Sauk, Tippecanoe 1 and 2, Lower Kaskaskia 1, Upper Kaskaskia 1-Lower Kaskaskia 2, Kaskaskia 2, and Absaroka supersequences in the Illinois Basins. Isopach contours and structure contours were formatted and attributed as GIS data sets for use in digital form as part of U.S. Geological Survey’s ongoing effort to inventory, catalog, and release subsurface geologic data in geospatial form. This effort is part of a broad directive to develop 2D and 3D geologic information at detailed, national, and continental scales. This data approximates, but does not strictly follow the USGS National Cooperative Geologic Mapping Program's GeMS data structure schema for geologic maps. Structure contour lines and isopach contours for each supersequence are stored within separate “IsoValueLine” feature classes. These are distributed within a geographic information system geodatabase and are also saved as shapefiles. Contour data is provided in both feet and meters to maintain consistency with the original publication and for ease of use. Nonspatial tables define the data sources used, define terms used in the dataset, and describe the geologic units referenced herein. A tabular data dictionary describes the entity and attribute information for all attributes of the geospatial data and accompanying nonspatial tables.

  3. d

    Google Address Data, Google Address API, Google location API, Google Map...

    • datarade.ai
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    APISCRAPY, Google Address Data, Google Address API, Google location API, Google Map API, Business Location Data- 100 M Google Address Data Available [Dataset]. https://datarade.ai/data-products/google-address-data-google-address-api-google-location-api-apiscrapy
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    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset authored and provided by
    APISCRAPY
    Area covered
    Luxembourg, United Kingdom, Estonia, Andorra, China, Moldova (Republic of), Åland Islands, Monaco, Spain, Liechtenstein
    Description

    Welcome to Apiscrapy, your ultimate destination for comprehensive location-based intelligence. As an AI-driven web scraping and automation platform, Apiscrapy excels in converting raw web data into polished, ready-to-use data APIs. With a unique capability to collect Google Address Data, Google Address API, Google Location API, Google Map, and Google Location Data with 100% accuracy, we redefine possibilities in location intelligence.

    Key Features:

    Unparalleled Data Variety: Apiscrapy offers a diverse range of address-related datasets, including Google Address Data and Google Location Data. Whether you seek B2B address data or detailed insights for various industries, we cover it all.

    Integration with Google Address API: Seamlessly integrate our datasets with the powerful Google Address API. This collaboration ensures not just accessibility but a robust combination that amplifies the precision of your location-based insights.

    Business Location Precision: Experience a new level of precision in business decision-making with our address data. Apiscrapy delivers accurate and up-to-date business locations, enhancing your strategic planning and expansion efforts.

    Tailored B2B Marketing: Customize your B2B marketing strategies with precision using our detailed B2B address data. Target specific geographic areas, refine your approach, and maximize the impact of your marketing efforts.

    Use Cases:

    Location-Based Services: Companies use Google Address Data to provide location-based services such as navigation, local search, and location-aware advertisements.

    Logistics and Transportation: Logistics companies utilize Google Address Data for route optimization, fleet management, and delivery tracking.

    E-commerce: Online retailers integrate address autocomplete features powered by Google Address Data to simplify the checkout process and ensure accurate delivery addresses.

    Real Estate: Real estate agents and property websites leverage Google Address Data to provide accurate property listings, neighborhood information, and proximity to amenities.

    Urban Planning and Development: City planners and developers utilize Google Address Data to analyze population density, traffic patterns, and infrastructure needs for urban planning and development projects.

    Market Analysis: Businesses use Google Address Data for market analysis, including identifying target demographics, analyzing competitor locations, and selecting optimal locations for new stores or offices.

    Geographic Information Systems (GIS): GIS professionals use Google Address Data as a foundational layer for mapping and spatial analysis in fields such as environmental science, public health, and natural resource management.

    Government Services: Government agencies utilize Google Address Data for census enumeration, voter registration, tax assessment, and planning public infrastructure projects.

    Tourism and Hospitality: Travel agencies, hotels, and tourism websites incorporate Google Address Data to provide location-based recommendations, itinerary planning, and booking services for travelers.

    Discover the difference with Apiscrapy – where accuracy meets diversity in address-related datasets, including Google Address Data, Google Address API, Google Location API, and more. Redefine your approach to location intelligence and make data-driven decisions with confidence. Revolutionize your business strategies today!

  4. d

    Geologic map and map database of the Palo Alto 30' X 60' quadrangle,...

    • datadiscoverystudio.org
    • search.dataone.org
    • +2more
    tgz
    Updated Jun 8, 2018
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    (2018). Geologic map and map database of the Palo Alto 30' X 60' quadrangle, California. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/06f4382488dd4271a79fa787c6b31c0d/html
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    tgzAvailable download formats
    Dataset updated
    Jun 8, 2018
    Description

    description: This digital map database, compiled from previously published and unpublished data, and new mapping by the authors, represents the general distribution of bedrock and surficial deposits in the mapped area. Together with the accompanying text file (pamf.ps, pamf.pdf, pamf.txt), it provides current information on the geologic structure and stratigraphy of the area covered. The database delineates map units that are identified by general age and lithology following the stratigraphic nomenclature of the U.S. Geological Survey. The scale of the source maps limits the spatial resolution (scale) of the database to 1:62,500 or smaller.; abstract: This digital map database, compiled from previously published and unpublished data, and new mapping by the authors, represents the general distribution of bedrock and surficial deposits in the mapped area. Together with the accompanying text file (pamf.ps, pamf.pdf, pamf.txt), it provides current information on the geologic structure and stratigraphy of the area covered. The database delineates map units that are identified by general age and lithology following the stratigraphic nomenclature of the U.S. Geological Survey. The scale of the source maps limits the spatial resolution (scale) of the database to 1:62,500 or smaller.

  5. Data from: A-MAPS: Augmented MAPS Dataset with Rhythm and Key Annotations

    • zenodo.org
    • data.niaid.nih.gov
    zip
    Updated Nov 19, 2021
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    Adrien Ycart; Emmanouil Benetos; Adrien Ycart; Emmanouil Benetos (2021). A-MAPS: Augmented MAPS Dataset with Rhythm and Key Annotations [Dataset]. http://doi.org/10.5281/zenodo.1317039
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    zipAvailable download formats
    Dataset updated
    Nov 19, 2021
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Adrien Ycart; Emmanouil Benetos; Adrien Ycart; Emmanouil Benetos
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The MAPS dataset is one of the most used benchmark dataset for automatic music transcription. We propose here an updated version of the ground truth MIDI files, containing, on top of the original pitch, onset and offsets, additional annotations.

    The annotations include:

    • Tempo curve

    • Time signature

    • Durations of notes in fraction of a quarter note (some of them are approximate)

    • Key signature (always written as the major relative)

    • Sustain pedal activation

    • Separate left and right hand staff

    • Text annotations from the score (tempo indications, coda...).

    If you use these annotations in a published research project, please cite:
    Adrien Ycart and Emmanouil Benetos. “A-MAPS: Augmented MAPS Dataset with Rhythm and Key Annotations” 19th International Society for Music Information Retrieval Conference Late Breaking and Demo Papers, September 2018, Paris, France.

    More information is available at: http://c4dm.eecs.qmul.ac.uk/ycart/a-maps.html

  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WASHINGTON COUNTY, ID USA

    • catalog.data.gov
    • datadiscoverystudio.org
    Updated Nov 8, 2023
    + more versions
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    Federal Emergency Management Agency (Point of Contact) (2023). DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WASHINGTON COUNTY, ID USA [Dataset]. https://catalog.data.gov/dataset/digital-flood-insurance-rate-map-database-washington-county-id-usa
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    Dataset updated
    Nov 8, 2023
    Dataset provided by
    Federal Emergency Management Agencyhttp://www.fema.gov/
    Area covered
    Washington County, United States
    Description

    The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual- chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). The file is georeferenced to earth?s surface using the UTM projection and coordinate system. The specifications for the horizontal control of DFIRM data files are consistent with those required for mapping at a scale of 1:12,000.

  7. Statewide Crop Mapping

    • data.cnra.ca.gov
    • s.cnmilf.com
    • +1more
    data, html +3
    Updated Mar 3, 2025
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    California Department of Water Resources (2025). Statewide Crop Mapping [Dataset]. https://data.cnra.ca.gov/dataset/statewide-crop-mapping
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    rest service, zip(140021333), shp(126828193), zip(159870566), shp(126548912), shp(107610538), zip(144060723), data, html, zip(169400976), zip(98690638), zip(179113742), zip(94630663), zip(88308707)Available download formats
    Dataset updated
    Mar 3, 2025
    Dataset authored and provided by
    California Department of Water Resourceshttp://www.water.ca.gov/
    Description

    NOTICE TO PROVISIONAL 2023 LAND USE DATA USERS: Please note that on December 6, 2024 the Department of Water Resources (DWR) published the Provisional 2023 Statewide Crop Mapping dataset. The link for the shapefile format of the data mistakenly linked to the wrong dataset. The link was updated with the appropriate data on January 27, 2025. If you downloaded the Provisional 2023 Statewide Crop Mapping dataset in shapefile format between December 6, 2024 and January 27, we encourage you to redownload the data. The Map Service and Geodatabase formats were correct as posted on December 06, 2024.

    Thank you for your interest in DWR land use datasets.

    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.

    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.

  8. COS-B Map Product Catalog - Dataset - NASA Open Data Portal

    • data.staging.idas-ds1.appdat.jsc.nasa.gov
    • data.nasa.gov
    Updated Mar 7, 2025
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    nasa.gov (2025). COS-B Map Product Catalog - Dataset - NASA Open Data Portal [Dataset]. https://data.staging.idas-ds1.appdat.jsc.nasa.gov/dataset/cos-b-map-product-catalog
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    Dataset updated
    Mar 7, 2025
    Dataset provided by
    NASAhttp://nasa.gov/
    Description

    The European Space Agency's satellite COS-B was dedicated to gamma-ray astronomy in the energy range 50 MeV to 5 Gev and carried a single spark chamber telescope with approximately a 20 degree field of view. COS-B operated in a highly eccentric polar orbit with apogee around 90000 km between 17 August 1975 and 25 April 1982. During this operational lifetime, COS-B made 65 observations, 15 of which were devoted to high (>20 deg) galactic latitudes. This database is a collection of maps created from the 65 COS-B observation files. The original observation files can be accessed within BROWSE by changing to the COSBRAW database. For each of the COS-B observation files, the analysis package FADMAP was run and the resulting maps, plus GIF images created from these maps, were collected into this database. Each map is a 120 x 120 pixel FITS format image with 0.5 degree pixels. The user may reconstruct any of these maps within the captive account by running FADMAP from the command line after extracting a file from within the COSBRAW database. The parameters used for selecting data for these product map files are embedded keywords in the FITS maps themselves. These parameters are set in FADMAP, and for the maps in this database are set as 'wide open' as possible. That is, except for selecting on each of 4 energy ranges, all other FADMAP parameters were set using broad criteria. To find more information about how to run FADMAP on the raw event's file, the user can access help files within the COSBRAW database or can use the 'fhelp' facility from the command line to gain information about FADMAP. This is a service provided by NASA HEASARC .

  9. f

    Additional File 1. Database of systematic reviews and maps and descriptive...

    • figshare.com
    xlsx
    Updated Sep 29, 2020
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    Neal Haddaway; Charles Gray; Matthew Grainger (2020). Additional File 1. Database of systematic reviews and maps and descriptive information about their database formats. [Dataset]. http://doi.org/10.6084/m9.figshare.13019186.v1
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    xlsxAvailable download formats
    Dataset updated
    Sep 29, 2020
    Dataset provided by
    figshare
    Authors
    Neal Haddaway; Charles Gray; Matthew Grainger
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Database of systematic reviews and maps and descriptive information about their database formats.

  10. c

    USGS National Geologic Map Database Collection

    • s.cnmilf.com
    • data.usgs.gov
    • +1more
    Updated Jul 6, 2024
    + more versions
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    U.S. Geological Survey (2024). USGS National Geologic Map Database Collection [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/usgs-national-geologic-map-database-collection
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    Dataset updated
    Jul 6, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Description

    The National Geologic Map Database (NGMDB) is a Congressionally mandated national archive of geoscience maps, reports, and stratigraphic information. The Geologic Mapping Act of 1992 and its Reauthorizations calls for the U.S. Geological Survey and the Association of American State Geologists (AASG) to cooperatively build this national archive, according to technical and scientific standards whose development is coordinated by the NGMDB. The NGMDB consists of a comprehensive set of publication citations, stratigraphic nomenclature, downloadable content in raster and vector formats, unpublished source information, and guidance on standards development. The NGMDB contains information on more than 110,000 maps and related geoscience reports published from the early 1800s to the present day, by more than 630 agencies, universities, associations, and private companies.

  11. USGS National Map

    • data.openlaredo.com
    • data.olatheks.org
    • +19more
    html
    Updated Apr 11, 2025
    + more versions
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    USGS National Map [Dataset]. https://data.openlaredo.com/dataset/usgs-national-map
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    htmlAvailable download formats
    Dataset updated
    Apr 11, 2025
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    GIS Portal
    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.

  12. Esri Community Maps AOIs

    • cacgeoportal.com
    Updated Feb 1, 2019
    + more versions
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    Esri (2019). Esri Community Maps AOIs [Dataset]. https://www.cacgeoportal.com/maps/12431f51f19e4d2582eefcdc76392f87
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    Dataset updated
    Feb 1, 2019
    Dataset authored and provided by
    Esrihttp://esri.com/
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    This layer features special areas of interest (AOIs) that have been contributed to Esri Community Maps using the new Community Maps Editor app. The data that is accepted by Esri will be included in selected Esri basemaps, including our suite of Esri Vector Basemaps, and made available through this layer to export and use offline. Export DataThe contributed data is also available for contributors and other users to export (or extract) and re-use for their own purposes. Users can export the full layer from the ArcGIS Online item details page by clicking the Export Data button and selecting one of the supported formats (e.g. shapefile, or file geodatabase (FGDB)). User can extract selected layers for an area of interest by opening in Map Viewer, clicking the Analysis button, viewing the Manage Data tools, and using the Extract Data tool. To display this data with proper symbology and metadata in ArcGIS Pro, you can download and use this layer file.Data UsageThe data contributed through the Community Maps Editor app is primarily intended for use in the Esri Basemaps. Esri staff will periodically (e.g. weekly) review the contents of the contributed data and either accept or reject the data for use in the basemaps. Accepted features will be added to the Esri basemaps in a subsequent update and will remain in the app for the contributor or others to edit over time. Rejected features will be removed from the app.Esri Community Maps Contributors and other ArcGIS Online users can download accepted features from this layer for their internal use or map publishing, subject to the terms of use below.

  13. W

    DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MATANUSKA-SUSITNA BOROUGH, AK,...

    • cloud.csiss.gmu.edu
    • catalog.data.gov
    Updated Mar 6, 2021
    + more versions
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    United States (2021). DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MATANUSKA-SUSITNA BOROUGH, AK, USA [Dataset]. https://cloud.csiss.gmu.edu/uddi/dataset/digital-flood-insurance-rate-map-database-matanuska-susitna-borough-ak-usa
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    Dataset updated
    Mar 6, 2021
    Dataset provided by
    United States
    Area covered
    Matanuska-Susitna Borough, Alaska, United States
    Description

    The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual- chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). The file is georeferenced to earth?s surface using the State Plane coordinate system. The specifications for the horizontal control of DFIRM data files are consistent with those required for mapping at a scale of 1:12,000.

  14. d

    PRELIM DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SAN BERNARDINO COUNTY, CA

    • catalog.data.gov
    Updated Jul 1, 2021
    + more versions
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    FEMA, Map Service Center (Point of Contact) (2021). PRELIM DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SAN BERNARDINO COUNTY, CA [Dataset]. https://catalog.data.gov/pt_BR/dataset/prelim-digital-flood-insurance-rate-map-database-san-bernardino-county-ca
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    Dataset updated
    Jul 1, 2021
    Dataset provided by
    FEMA, Map Service Center (Point of Contact)
    Area covered
    San Bernardino County, California
    Description

    The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual- chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA).The file is georeferenced to earth's surface using the State Plane projection and coordinate system. The specifications for the horizontal control of DFIRM data files are consistent with those required for mapping at a scale of 1:12,000.

  15. g

    High Resolution Population Density Data - Map View

    • globalmidwiveshub.org
    Updated Aug 11, 2021
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    Direct Relief (2021). High Resolution Population Density Data - Map View [Dataset]. https://www.globalmidwiveshub.org/datasets/high-resolution-population-density-data-map-view
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    Dataset updated
    Aug 11, 2021
    Dataset authored and provided by
    Direct Relief
    Description

    This map is just one of the many data visualizations on the Global Midwives Hub, a digital resource with open data, maps, and mapping applications (among other things), to support advocacy for improved maternal and newborn services, supported by the International Confederation of Midwives (ICM), UNFPA, WHO, and Direct Relief.

  16. A

    Data from: User's guide for Bristol Bay land cover maps

    • data.amerigeoss.org
    • data.wu.ac.at
    pdf
    Updated Jul 25, 2019
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    United States[old] (2019). User's guide for Bristol Bay land cover maps [Dataset]. https://data.amerigeoss.org/ar/dataset/users-guide-for-bristol-bay-land-cover-maps
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    pdfAvailable download formats
    Dataset updated
    Jul 25, 2019
    Dataset provided by
    United States[old]
    Area covered
    Bristol Bay
    Description

    The purpose of this Users Guide is to explain how to use the land cover maps and field data generated by the Bristol Bay Land Cover Mapping Project. The complete data base for the Bristol Bay Land Cover Mapping Project consists of several field data and digital data products.

  17. C

    National Hydrography Data - NHD and 3DHP

    • data.cnra.ca.gov
    • data.ca.gov
    • +3more
    Updated Jul 1, 2025
    + more versions
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    California Department of Water Resources (2025). National Hydrography Data - NHD and 3DHP [Dataset]. https://data.cnra.ca.gov/dataset/national-hydrography-dataset-nhd
    Explore at:
    pdf, csv(12977), zip(73817620), pdf(3684753), website, zip(13901824), pdf(4856863), web videos, zip(578260992), pdf(1436424), zip(128966494), pdf(182651), zip(972664), zip(10029073), zip(1647291), pdf(1175775), zip(4657694), pdf(1634485), zip(15824984), zip(39288832), arcgis geoservices rest api, pdf(437025), pdf(9867020)Available download formats
    Dataset updated
    Jul 1, 2025
    Dataset authored and provided by
    California Department of Water Resources
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    The USGS National Hydrography Dataset (NHD) downloadable data collection from The National Map (TNM) is a comprehensive set of digital spatial data that encodes information about naturally occurring and constructed bodies of surface water (lakes, ponds, and reservoirs), paths through which water flows (canals, ditches, streams, and rivers), and related entities such as point features (springs, wells, stream gages, and dams). The information encoded about these features includes classification and other characteristics, delineation, geographic name, position and related measures, a "reach code" through which other information can be related to the NHD, and the direction of water flow. The network of reach codes delineating water and transported material flow allows users to trace movement in upstream and downstream directions. In addition to this geographic information, the dataset contains metadata that supports the exchange of future updates and improvements to the data. The NHD supports many applications, such as making maps, geocoding observations, flow modeling, data maintenance, and stewardship. For additional information on NHD, go to https://www.usgs.gov/core-science-systems/ngp/national-hydrography.

    DWR was the steward for NHD and Watershed Boundary Dataset (WBD) in California. We worked with other organizations to edit and improve NHD and WBD, using the business rules for California. California's NHD improvements were sent to USGS for incorporation into the national database. The most up-to-date products are accessible from the USGS website. Please note that the California portion of the National Hydrography Dataset is appropriate for use at the 1:24,000 scale.

    For additional derivative products and resources, including the major features in geopackage format, please go to this page: https://data.cnra.ca.gov/dataset/nhd-major-features Archives of previous statewide extracts of the NHD going back to 2018 may be found at https://data.cnra.ca.gov/dataset/nhd-archive.

    In September 2022, USGS officially notified DWR that the NHD would become static as USGS resources will be devoted to the transition to the new 3D Hydrography Program (3DHP). 3DHP will consist of LiDAR-derived hydrography at a higher resolution than NHD. Upon completion, 3DHP data will be easier to maintain, based on a modern data model and architecture, and better meet the requirements of users that were documented in the Hydrography Requirements and Benefits Study (2016). The initial releases of 3DHP include NHD data cross-walked into the 3DHP data model. It will take several years for the 3DHP to be built out for California. Please refer to the resources on this page for more information.

    The FINAL,STATIC version of the National Hydrography Dataset for California was published for download by USGS on December 27, 2023. This dataset can no longer be edited by the state stewards. The next generation of national hydrography data is the USGS 3D Hydrography Program (3DHP).

    Questions about the California stewardship of these datasets may be directed to nhd_stewardship@water.ca.gov.

  18. g

    Geospatial data for the Vegetation Mapping Inventory Project of American...

    • gimi9.com
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    Geospatial data for the Vegetation Mapping Inventory Project of American Memorial Park | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_geospatial-data-for-the-vegetation-mapping-inventory-project-of-american-memorial-park/
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    Description

    The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for American Memorial Park. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. To produce the spatial database and map layer, 0.6-meter, 4-band Quickbird satellite imagery from 2006 was provided by PACN. By comparing the signatures on the imagery to field and ground data 27 map classes (16 vegetated, three barren, and eight land-use / land-cover) were developed and directly crosswalked or matched to their corresponding NVC plant associations. The interpreted and remotely sensed data were converted to Geographic Information System (GIS) databases and maps were printed, field tested, reviewed, and revised. The final map layer was accessed for thematic accuracy by overlaying 48 independent accuracy assessment points.

  19. d

    DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MAHNOMEN COUNTY, MINNESOTA, USA.

    • datadiscoverystudio.org
    Updated Nov 14, 2017
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    (2017). DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MAHNOMEN COUNTY, MINNESOTA, USA. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/04a747eb075c4e5da180730272fcc551/html
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    Dataset updated
    Nov 14, 2017
    Area covered
    United States
    Description

    description: The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk; classificatons used are the 1-percent-annual-chance flood event, the 0.2-percent- annual-chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). The file is georeferenced to earth's surface using the UTM projection and coordinate system. The specifications for the horizontal control of DFIRM data files are consistent with those required for mapping at a scale of 1:12,000.; abstract: The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk; classificatons used are the 1-percent-annual-chance flood event, the 0.2-percent- annual-chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). The file is georeferenced to earth's surface using the UTM projection and coordinate system. The specifications for the horizontal control of DFIRM data files are consistent with those required for mapping at a scale of 1:12,000.

  20. d

    Market Research Data | Global Map data | Geographic data | Address and Zip...

    • datarade.ai
    .csv
    Updated Oct 19, 2024
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    GeoPostcodes (2024). Market Research Data | Global Map data | Geographic data | Address and Zip Code Database | Geocoded [Dataset]. https://datarade.ai/data-products/geopostcodes-market-research-data-map-data-geographic-dat-geopostcodes
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    .csvAvailable download formats
    Dataset updated
    Oct 19, 2024
    Dataset authored and provided by
    GeoPostcodes
    Area covered
    Poland, Saint Barthélemy, Christmas Island, Monaco, Korea (Democratic People's Republic of), Papua New Guinea, South Sudan, Tokelau, Slovenia, Sierra Leone
    Description

    A global self-hosted Market Research dataset containing all administrative divisions, cities, addresses, and zip codes for 247 countries. All geospatial data is updated weekly to maintain the highest data quality, including challenging countries such as China, Brazil, Russia, and the United Kingdom.

    Use cases for the Global Zip Code Database (Market Research data)

    • Address capture and validation

    • Map and visualization

    • Reporting and Business Intelligence (BI)

    • Master Data Mangement

    • Logistics and Supply Chain Management

    • Sales and Marketing

    Data export methodology

    Our map data packages are offered in variable formats, including .csv. All geographic data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.

    Product Features

    • Fully and accurately geocoded

    • Administrative areas with a level range of 0-4

    • Multi-language support including address names in local and foreign languages

    • Comprehensive city definitions across countries

    For additional insights, you can combine the map data with:

    • UNLOCODE and IATA codes

    • Time zones and Daylight Saving Times

    Why do companies choose our Market Research databases

    • Enterprise-grade service

    • Reduce integration time and cost by 30%

    • Weekly updates for the highest quality

    Note: Custom geographic data packages are available. Please submit a request via the above contact button for more details.

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(2010). MAPS Dataset [Dataset]. https://paperswithcode.com/dataset/maps

MAPS Dataset

Midi Aligned Piano Dataset

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Dataset updated
Aug 6, 2010
Description

MAPS – standing for MIDI Aligned Piano Sounds – is a database of MIDI-annotated piano recordings. MAPS has been designed in order to be released in the music information retrieval research community, especially for the development and the evaluation of algorithms for single-pitch or multipitch estimation and automatic transcription of music. It is composed by isolated notes, random-pitch chords, usual musical chords and pieces of music. The database provides a large amount of sounds obtained in various recording conditions.

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