81 datasets found
  1. n

    Data Access Viewer - NOAA Office of Coastal Management

    • nconemap.gov
    • hub.arcgis.com
    • +1more
    Updated Aug 31, 2023
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    NC OneMap / State of North Carolina (2023). Data Access Viewer - NOAA Office of Coastal Management [Dataset]. https://www.nconemap.gov/documents/4ede1ee1ef98408ea71131b457c41af4
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    Dataset updated
    Aug 31, 2023
    Dataset authored and provided by
    NC OneMap / State of North Carolina
    Description

    The NOAA Data Access Viewer (DAV) allows for the download of elevation data shared by the NC Emergency Management. Users can customize the free downloads according to needs - projection, datum, product output (raster, points, contours), format, etc.

    Go to the NOAA Data Access Viewer
    
    
    For more information:
    
    Tips to use the NOAA DAV
    
    NOAA blog posts about the DAV
    
    NOAA blog posts about LiDAR
    
  2. Prediction Of Worldwide Energy Resources (POWER)

    • catalog.data.gov
    • datasets.ai
    • +1more
    Updated Apr 11, 2025
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    National Aeronautics and Space Administration (2025). Prediction Of Worldwide Energy Resources (POWER) [Dataset]. https://catalog.data.gov/dataset/prediction-of-worldwide-energy-resources-power
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    Dataset updated
    Apr 11, 2025
    Dataset provided by
    NASAhttp://nasa.gov/
    Description

    The POWER Project contains over 380 satellite-derived meteorology and solar energy Analysis Ready Data (ARD) at four temporal levels: hourly, daily, monthly (by year 12 months + annual averages), and climatology. The POWER Data Archive provides data at the native resolution of the source data products. The data is updated nightly to maintain Near Real Time (NRT) availability (2-3 days for meteorological parameters and 5-7 days for solar). The POWER Project targets three specific user communities: Renewable Energy (RE), Sustainable Buildings (SB), and Agroclimatology (AG). The POWER Projects provides community specific parameters, output formats, naming conventions, and units that are commonly employed by each user community. The POWER Services Catalog consists of a series of RESTful Application Programming Interfaces (API), geospatial enabled image services, and a web mapping Data Access Viewer (DAV). These three different service offerings support data discovery, access, and distribution to our user base as ARD and as direct application inputs to decision support tools.

  3. c

    Meteorological and load profile data set

    • esango.cput.ac.za
    txt
    Updated Nov 22, 2022
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    Ibukun Fajuke (2022). Meteorological and load profile data set [Dataset]. http://doi.org/10.25381/cput.21546108.v1
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    txtAvailable download formats
    Dataset updated
    Nov 22, 2022
    Dataset provided by
    Cape Peninsula University of Technology
    Authors
    Ibukun Fajuke
    License

    Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
    License information was derived automatically

    Description

    2021FEBEREC-STD-117

    The data set consists of the hourly load demand, hourly solar irradiance and hourly wind speed of a community located in Northern part of Nigeria named Bara, Kirfi Local Government area of Bauchi state, Nigeria. The hourly solar resource data and wind resource data of the community for a period of one year is obtained from an existing database of the Power Data Access Viewer of National Aeronautic and Space Administration (NASA).

  4. 2010 Lidar: Fairbanks North Star Borough, Alaska

    • fisheries.noaa.gov
    las/laz - laser
    Updated Nov 18, 2010
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    OCM Partners (2010). 2010 Lidar: Fairbanks North Star Borough, Alaska [Dataset]. https://www.fisheries.noaa.gov/inport/item/52667
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    las/laz - laserAvailable download formats
    Dataset updated
    Nov 18, 2010
    Dataset provided by
    OCM Partners
    Time period covered
    May 4, 2010
    Area covered
    Description

    The NOAA Office for Coastal Management (OCM) downloaded this lidar data from the USGS site: ftp://rockyftp.cr.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/AK_Fairbanks-NSBorough_2010/ and processed the data to be available on the Digital Coast Data Access Viewer (DAV). NOAA Office for Coastal Management processed all classifications of points to the Digital Coast Data Access Viewer...

  5. m

    Digital Elevation Model (DEM) for the State of Hawaii Statewide Coastal...

    • data.mendeley.com
    Updated Aug 25, 2019
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    Linqiang Yang (2019). Digital Elevation Model (DEM) for the State of Hawaii Statewide Coastal Highway Program Report: Maui, Hawaii [Dataset]. http://doi.org/10.17632/zdmdy8jtsw.1
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    Dataset updated
    Aug 25, 2019
    Authors
    Linqiang Yang
    License

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

    Area covered
    Maui, Hawaii
    Description

    In this project, we use the Light Detection and Ranging (LiDAR) data to create the Digital Elevation Model (DEM). The LiDAR data can be downloaded through the Data Access Viewer of NOAA ( https://coast.noaa.gov/dataviewer/#/lidar/search/). For Maui, the majority of the DEM is created using the data of 2013 U.S. Army Corps of Engineers (USACE) National Coastal Mapping Program (NCMP) Topobathy LiDAR – Local Mean Sea Level (LMSL). For some areas not covered by this data set, we use the LiDAR data from 2006 FEMA LiDAR: Hawaiian Islands and 2007 JALBTCX Hawaii LiDAR: North Coasts of Hawaii (Big Island), Kauai, Maui, Molokai, Oahu, which are accessed in the Data Access Viewer of NOAA. Please read “Description of Digital Elevation Model (DEM) for Maui, Hawaii.docx” for detailed information.

  6. U.S. Coastal Lidar Elevation Data - Including the Great Lakes and...

    • data.wu.ac.at
    html
    Updated Oct 19, 2016
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    National Oceanic and Atmospheric Administration, Department of Commerce (2016). U.S. Coastal Lidar Elevation Data - Including the Great Lakes and Territories, 1996 - present [Dataset]. https://data.wu.ac.at/schema/data_gov/NDA5ZGQwYzQtMzk4YS00ZTkyLTg1NmEtYjgxMTc3ZTA1YzFm
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    htmlAvailable download formats
    Dataset updated
    Oct 19, 2016
    Dataset provided by
    United States Department of Commercehttp://commerce.gov/
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    License

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

    Area covered
    United States, 5c59a237c465a2a8e46e25308444dc7f0539731b
    Description

    The NOAA Coastal Services Center manages and distributes lidar data for the coastal United States, including territorial possessions via the Digital Coast Data Access Viewer web-mapping application. The data span from the mid-1990's to the present and were collected using several different sensors. The collection includes data from topographic and bathymetric lidar sensors. Data are available for shoreline strips to full county coverage and larger. The products have been delivered to the CSC in various formats, projections, datums, and units. Once received, the data are reviewed, checked for errors, and standardized in a single format, projection, and datum. The NOAA National Geophysical Data Center serves as the long-term archive of these data.

  7. 2024 IN DNR Lidar DEM: Indiana Coastline

    • catalog.data.gov
    • fisheries.noaa.gov
    Updated Jul 4, 2025
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    NOAA Office for Coastal Management (Point of Contact, Custodian) (2025). 2024 IN DNR Lidar DEM: Indiana Coastline [Dataset]. https://catalog.data.gov/dataset/2024-in-dnr-lidar-dem-indiana-coastline
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    Dataset updated
    Jul 4, 2025
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Area covered
    Indiana
    Description

    Original Product: These are Digital Elevation Model (DEM) data as part of the required deliverables for the lidar project. Class 2 (Ground) lidar points in conjunction with the hydro breaklines were used to create a 1 ft hydro-flattened Raster DEM. Original Dataset Geographic Extent: Cook county, Illinois; Lake, LaPorte, and Porter counties, Indiana; and Berrien county, Michigan; covering approximately 120 square miles. Original Dataset Description: The lidar project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.35 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base Lidar Specification. The data was developed based on a horizontal projection/datum of NAD83(HARN), Indiana West Feet, and vertical datum of NAVD88 (GEOID18) Feet. Lidar data was delivered as processed Classified LAS 1.4 files, formatted to 2139 individual 1250 ft x 1250 ft tiles clipped to the DPA, as tiled Intensity Images and tiled bare-earth DEMs; all tiled to the same 1250 ft x 1250 ft schema. Original Dataset Ground Conditions: Lidar was collected in April 2024, while no snow was on the ground and rivers were at or below normal levels. Sanborn Map Company, Inc. established a total of 25 accuracy check points, 20 in Bare Earth and Urban landcovers (20 NVA points), 5 in Tall Grass and Brushland/Low Trees categories (5 VVA points), that were used to assess the vertical accuracy of the data. This dataset was provided to the NOAA Office for Coastal Management (OCM) by the Indiana Dept. of Natural Resources to make the data available for bulk and custom downloads from the NOAA Digital Coast Data Access Viewer.

  8. 2025 SCDVA Lidar DEM: Charleston County, SC

    • catalog.data.gov
    • fisheries.noaa.gov
    Updated Sep 19, 2025
    + more versions
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    NOAA Office for Coastal Management (Point of Contact, Custodian) (2025). 2025 SCDVA Lidar DEM: Charleston County, SC [Dataset]. https://catalog.data.gov/dataset/2025-scdva-lidar-dem-charleston-county-sc
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    Dataset updated
    Sep 19, 2025
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Area covered
    Charleston County, South Carolina
    Description

    BERKELEY, CHARLESTON, ORANGEBURG LIDAR DATA COLLECTION Lidar Data Acquisition and Processing Production Task Charleston County Contract Number: 6004 RFQ Number: 6004-25C Woolpert Order No: 10020258 CONTRACTOR: Woolpert Lidar data is a remotely sensed high-resolution elevation data collected by an airborne platform. The lidar sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The lidar systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. This task order requires lidar data to be acquired over Charleston County (+/- 1,197 square miles). This lidar data set is comprised of lidar point cloud data, raster DEMs, raster DSMs, raster intensity imagery, and GPS flight line trajectory data. The task required the lidar data to be collected at a nominal pulse spacing (NPS) of 1.15 feet. The lidar dataset was produced using a horizontal datum/projection of NAD83, State Plane South Carolina, International Feet and a vertical datum of NAVD88 (Geoid 18), International Feet. Tidal areas in Charleston's data acquisition were collected within +/- 2 hours of low tide. Additional deliverables include control data and tile index in Esri shapefile format, lidar processing and survey reports in PDF format, and project-level FGDC CSDGM metadata in XML format. This data was provided to the NOAA Office for Coastal Management (OCM) by the Charleston County Public Works Department, for the purpose of making the data publicly available for custom and bulk downloads from the NOAA Digital Coast Data Access Viewer.

  9. Rainfall Timeseries data

    • kaggle.com
    zip
    Updated Aug 22, 2022
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    Pooja Gupta (2022). Rainfall Timeseries data [Dataset]. https://www.kaggle.com/datasets/poojag718/rainfall-timeseries-data/discussion
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    zip(3395 bytes)Available download formats
    Dataset updated
    Aug 22, 2022
    Authors
    Pooja Gupta
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Data Source

    Prediction of Worldwide Energy Resources (POWER) project provides meteorological data from NASA research for support of renewable energy, building energy efficiency and agricultural support. NASA has an Earth Science research program with satellite systems providing research data that are important to study of climate and climate process. These data contain long-term climate averaged estimates and surface solar energy fluxes.

    Data Collection

    Data is collected from Power Data Access Viewer The POWER Meteorological data is prediction or observation given by NASA's GMAO MERRA-2 assimilation model. The data collected is monthly frequency data for a particular latitude and longitude in Mumbai for the period 2000 – 2020. The data consists of the following variables: • Specific Humidity • Relative Humidity: • Temperature • Precipitation (The data consist of precipitation as monthly sum of rainfall )

  10. 2022 USGS Lidar DEM: Douglas County, MN

    • fisheries.noaa.gov
    geotiff +1
    Updated Jan 1, 2024
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    OCM Partners (2024). 2022 USGS Lidar DEM: Douglas County, MN [Dataset]. https://www.fisheries.noaa.gov/inport/item/78339
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    not applicable, geotiffAvailable download formats
    Dataset updated
    Jan 1, 2024
    Dataset provided by
    OCM Partners
    License

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

    Time period covered
    Apr 27, 2022
    Area covered
    Description

    Breakline-enforced 0.5m Digital Elevation Models (DEM) derived from airborne lidar data.

    This metadata record supports the data entry in the NOAA Digital Coast Data Access Viewer (DAV). For this data set, the DAV is leveraging the GeoTIFF files hosted by USGS on Amazon Web Services.

  11. Time Series Solar Irradiance for Indian Cities

    • kaggle.com
    zip
    Updated Jun 16, 2025
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    Meeenaxi (2025). Time Series Solar Irradiance for Indian Cities [Dataset]. https://www.kaggle.com/datasets/meenakshihihihihi/time-series-solar-irradiance-for-indian-cities
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    zip(780217 bytes)Available download formats
    Dataset updated
    Jun 16, 2025
    Authors
    Meeenaxi
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    This dataset contains hourly meteorological and solar irradiance data for three major Indian cities — Ahmedabad, Bengaluru, and Mumbai — extracted from the NASA POWER (Prediction Of Worldwide Energy Resources) platform.

    It is curated for use in renewable energy forecasting, climate analysis, and solar power potential modeling, and is suitable for both academic and commercial machine learning applications.

    Cities Covered

    Ahmedabad (Gujarat) Bengaluru (Karnataka) Mumbai (Maharashtra)

    Time Resolution Hourly Data from June 2023 to june 2025

    Features Included The following features have been extracted for each city: ALLSKY_SFC_SW_DWN: All Sky Surface Shortwave Downward Irradiance (W/m²) CLRSKY_SFC_SW_DWN: All Sky Insolation Clearness Index (unitless) SOLZEN: Integrated Solar Zenith Angle (degrees) ALLSKY_SFC_PAR_TOT: All Sky Photosynthetically Active Radiation Total (MJ/m²) UVAF: UVA Radiation (W/m²) UVBF: UVB Radiation (W/m²) UV_INDEX: UV Index T2M: Air Temperature at 2 meters (°C) PRECTOTCORR: Precipitation (mm/hr) PS: Surface Pressure (kPa)

    Use Cases This dataset is ideal for: Time series forecasting of solar irradiance Renewable energy production models ML models for weather pattern analysis Urban climate monitoring

    Environmental research on solar exposure and health

    Data Source & License All data has been obtained via the NASA POWER API, a public resource managed by NASA's Earth Science Division. Source: NASA POWER Project

    Link : https://power.larc.nasa.gov/data-access-viewer/ fbclid=IwAR1yPlfK_3RPZbL3RWwHIrizUeq8SugivFCDN7ASnIeuC8lfO-3TJSlrlRg

    License: CC0 1.0 Universal (Public Domain)

  12. 2024 USACE SAM Topographic Lidar DEM: Lake Seminole (AL, FL, GA)

    • catalog.data.gov
    • fisheries.noaa.gov
    Updated Jun 26, 2025
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    NOAA Office for Coastal Management (Point of Contact, Custodian) (2025). 2024 USACE SAM Topographic Lidar DEM: Lake Seminole (AL, FL, GA) [Dataset]. https://catalog.data.gov/dataset/2024-usace-sam-topographic-lidar-dem-lake-seminole-al-fl-ga
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    Dataset updated
    Jun 26, 2025
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Area covered
    Florida, Lake Seminole
    Description

    Original Data: These files contain rasterized topographic lidar elevations generated from data collected using a Teledyne ALTM Galaxy PRIME sensor. Native lidar data is not generally in a format accessible to most Geographic Information Systems (GIS). Specialized in-house and commercial software packages are used to process the native lidar data into 3-dimensional positions that can be imported into GIS software for visualization and further analysis. Horizontal positions are referenced to the North American Datum of 1983 Universal Transverse Mercator Zone 16 North (NAD83 UTM Zone 16N). Vertical positions are referenced to the NAD83 (2011) ellipsoid and provided in meters. The National Geodetic Survey's (NGS) GEOID18 model is used to transform the vertical positions from ellipsoid to orthometric heights referenced to the North American Vertical Datum of 1988 (NAVD88). The 3-D position data are sub-divided into a series of LAS files, which are tiled into 1-km by 1-km boxes defined by the Military Grid Reference System. The data were provided to the NOAA Office for Coastal Management (OCM) by the USACE Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) to make the data publicly available for bulk and custom downloads from the NOAA Digital Data Access Viewer (DAV).

  13. 2024 IN DNR Lidar: Indiana Coastline

    • catalog.data.gov
    • fisheries.noaa.gov
    Updated Jul 4, 2025
    + more versions
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    NOAA Office for Coastal Management (Point of Contact, Custodian) (2025). 2024 IN DNR Lidar: Indiana Coastline [Dataset]. https://catalog.data.gov/dataset/2024-in-dnr-lidar-indiana-coastline
    Explore at:
    Dataset updated
    Jul 4, 2025
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Area covered
    Indiana
    Description

    Original Product: These lidar data are processed Classified LAS 1.4 files, formatted to 2139 individual 1250 ft x 1250 ft tiles clipped to the DPA; used to create intensity images, 3D breaklines, and hydro-flattened DEMs as necessary. Original Dataset Geographic Extent: Cook county, Illinois; Lake, LaPorte, and Porter counties, Indiana; and Berrien county, Michigan; covering approximately 120 square miles. Original Dataset Description: The lidar project called for the planning, acquisition, processing, and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.35 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base Lidar Specification. The data was developed based on a horizontal projection/datum of NAD83(HARN), Indiana West Feet, and vertical datum of NAVD88 (GEOID18) Feet. Lidar data was delivered as processed Classified LAS 1.4 files, formatted to 2139 individual 1250 ft x 1250 ft tiles clipped to the DPA, as tiled Intensity Images and tiled bare-earth DEMs; all tiled to the same 1250 ft x 1250 ft schema. Original Dataset Ground Conditions: Lidar was collected in April 2024, while no snow was on the ground and rivers were at or below normal levels. Sanborn Map Company, Inc. established a total of 25 accuracy check points, 20 in Bare Earth and Urban landcovers (20 NVA points), 5 in Tall Grass and Brushland/Low Trees categories (5 VVA points), that were used to assess the vertical accuracy of the data. This dataset was provided to the NOAA Office for Coastal Management (OCM) by the Indiana Dept. of Natural Resources to make the data available for bulk and custom downloads from the NOAA Digital Coast Data Access Viewer.

  14. a

    DAV/ElevationFootprints

    • home-pugonline.hub.arcgis.com
    Updated Oct 23, 2023
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    The PUG User Group (2023). DAV/ElevationFootprints [Dataset]. https://home-pugonline.hub.arcgis.com/maps/pugonline::elevation-120m/about
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    Dataset updated
    Oct 23, 2023
    Dataset authored and provided by
    The PUG User Group
    Area covered
    Description

    This map service presents spatial information about Elevation Data Access Viewer services across the United States and Territories in the Web Mercator projection. The service was developed by the National Oceanic and Atmospheric Administration (NOAA), but may contain data and information from a variety of data sources, including non-NOAA data. NOAA provides the information “as-is” and shall incur no responsibility or liability as to the completeness or accuracy of this information. NOAA assumes no responsibility arising from the use of this information. The NOAA Office for Coastal Management will make every effort to provide continual access to this service but it may need to be taken down during routine IT maintenance or in case of an emergency. If you plan to ingest this service into your own application and would like to be informed about planned and unplanned service outages or changes to existing services, please register for our Data Services Newsletter (http://coast.noaa.gov/digitalcoast/publications/subscribe). For additional information, please contact the NOAA Office for Coastal Management (coastal.info@noaa.gov).

  15. a

    DAV/ElevationFootprints redo

    • home-pugonline.hub.arcgis.com
    Updated Oct 23, 2023
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    The PUG User Group (2023). DAV/ElevationFootprints redo [Dataset]. https://home-pugonline.hub.arcgis.com/items/d17a526a6cbc40ed8e51da55849aa8d4
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    Dataset updated
    Oct 23, 2023
    Dataset authored and provided by
    The PUG User Group
    Description

    This map service presents spatial information about Elevation Data Access Viewer services across the United States and Territories in the Web Mercator projection. The service was developed by the National Oceanic and Atmospheric Administration (NOAA), but may contain data and information from a variety of data sources, including non-NOAA data. NOAA provides the information “as-is” and shall incur no responsibility or liability as to the completeness or accuracy of this information. NOAA assumes no responsibility arising from the use of this information. The NOAA Office for Coastal Management will make every effort to provide continual access to this service but it may need to be taken down during routine IT maintenance or in case of an emergency. If you plan to ingest this service into your own application and would like to be informed about planned and unplanned service outages or changes to existing services, please register for our Data Services Newsletter (http://coast.noaa.gov/digitalcoast/publications/subscribe). For additional information, please contact the NOAA Office for Coastal Management (coastal.info@noaa.gov).

  16. H

    Bangladesh Weather Dataset (1901 - 2023)

    • dataverse.harvard.edu
    Updated Sep 9, 2024
    + more versions
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    Sajratul Yakin Rubaiat (2024). Bangladesh Weather Dataset (1901 - 2023) [Dataset]. http://doi.org/10.7910/DVN/ZP8IEJ
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 9, 2024
    Dataset provided by
    Harvard Dataverse
    Authors
    Sajratul Yakin Rubaiat
    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

    Area covered
    Bangladesh
    Description

    📊 Dataset README (Updated with Temporal Coverage) 📈 Overview 🌐 This README document provides detailed information about a dataset that combines temperature 🌡️ and rainfall 🌧️ data. The temperature data is sourced from NASA's POWER Project, and the rainfall data is obtained from the Humanitarian Data Exchange (HDX) website, specifically focusing on Bangladesh rainfall data. Temperature Data Source 🔥 Source: NASA's POWER (Prediction of Worldwide Energy Resources) Data Access Viewer URL: NASA POWER Data Access Viewer Description: The POWER Project provides solar and meteorological data sets, primarily intended for renewable energy, sustainable buildings, agriculture, and other related applications. The temperature data from this source is a part of NASA's global meteorological data. Rainfall Data Source 🌧️ Source: Humanitarian Data Exchange (HDX) URL: Bangladesh Rainfall Data - HDX Description: HDX hosts various humanitarian data including climate and weather-related datasets. The rainfall data for Bangladesh is part of their collection, providing detailed subnational rainfall statistics. Dataset Description 📝 Composition 📊 The dataset is a combination of the temperature and rainfall data, aligned by date to facilitate joint analysis. The key components are: Temperature Data (tem): Represents the monthly average temperature, presumably in degrees Celsius. Rainfall Data (rain): Indicates monthly total rainfall, presumably measured in millimeters. Structure 🏗️ The dataset is structured into a CSV file with the following columns: tem: Average temperature for the month. Month: The month for the data point, ranging from 1 (January) to 12 (December). Year: The year of the data point. rain: Total rainfall for the month. Temporal Coverage 📆 Earliest Date: 1901 Latest Date: 2023 This dataset provides a historical perspective on climate trends from the earliest year of 1901 to the most recent data available up to 2023. Usage and Applications 🚀 This dataset is particularly useful for studying climatic patterns, seasonal changes, and long-term climate trends. Applications include but are not limited to: Climatological research and climate change studies. Agricultural planning and forecasting. Environmental and ecological studies. Resource management and planning in sectors sensitive to climatic variations. Limitations and Considerations 🚧 Geographical Specificity: The rainfall data is specific to Bangladesh and may not represent global patterns. Data Integration: The temperature and rainfall data come from two different sources; users should consider potential discrepancies in data collection methods and accuracy. Updates and Maintenance 🔄 Data Update Frequency: Check the source websites for the update frequency and availability of more recent data. Last Updated: Refer to the source websites for the last update date of the data. Licensing and Usage Rights ©️ Users should refer to the respective source websites for information on licensing and usage rights. It is important to adhere to the terms and conditions set by the data providers. Contact Information 📞 For specific queries related to the temperature or rainfall data, users should contact the respective data providers through their official communication channels provided on their websites.

  17. U.S. Great Lakes Collaborative Benthic Habitat Mapping Project Map: GLRI...

    • noaa.hub.arcgis.com
    Updated Feb 21, 2025
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    NOAA GeoPlatform (2025). U.S. Great Lakes Collaborative Benthic Habitat Mapping Project Map: GLRI Acquisition [Dataset]. https://noaa.hub.arcgis.com/maps/19241ad4c4da47eaae4e82c24ef5da20
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    Dataset updated
    Feb 21, 2025
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Authors
    NOAA GeoPlatform
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    THIS MAP IS NOT AUTHORITATIVE. SEE TERMS OF USE BELOW.This web map was developed by the National Oceanic and Atmospheric Administration’s (NOAA) Office for Coastal Management and is featured in the U.S. Great Lakes Collaborative Benthic Habitat Mapping Common Operating Dashboard in support of the Collaborative Benthic Habitat Mapping in the Nearshore Waters of the Great Lakes Basin Project. This multi-year, multi-agency project is funded through the Great Lakes Restoration Initiative (GLRI) and focuses on new bathymetric data (airborne lidar and vessel based sonar) acquisition, validation, and benthic habitat characterization mapping of the nearshore waters (0-80 meters) in the U.S. Great Lakes. This project also contributes to the regional Lakebed 2030 campaign, which aims to have high-density bathymetric data available for the entirety of the Great Lakes by 2030. This web map contains data layers reflecting the current status of bathy data coverage in the nearshore (0-80 meters) of the U.S. Great Lakes, including acquisition (lidar and multibeam sonar), ground-truthing/validation, and benthic habitat mapping and characterization. Acquisition layers include coverage areas that have been acquired and are available for public use (green) as well as those that have been acquired, but are not yet available or are still in progress (orange). The nearshore water depth layers (0-25 and 25-80 meters) were created using the National Centers for Environmental Information (NCEI) Great Lakes Bathymetry (3-second resolution) grid extracts. The 0 to 25 meter nearshore water depth layer represents areas where bathymetric lidar data acquisition could ideally be conducted, depending on water condition and turbidity. The 25 to 80 meter layer shows locations where acoustic data acquisition can occur. See below for information on additional data layers. All data originally projected in the following coordinate system: EPSG:3175, NAD 1983 Great Lakes and St Lawrence Albers.This map will continue to be updated as new information is made available.Source Data for Bathy Coverage Layers - Acquired/Available:Topobathy and Bathy Lidar (NOAA's Data Access Viewer: https://coast.noaa.gov/dataviewer/#/; U.S. Interagency Elevation Inventory (USIEI): https://coast.noaa.gov/inventory/). Multibeam Sonar (National Centers for Environmental Information (NCEI) Bathymetric Data Viewer: https://www.ncei.noaa.gov/maps/bathymetry/; NOAA's Data Access Viewer: https://coast.noaa.gov/dataviewer/#/; U.S. Interagency Elevation Inventory (USIEI): https://coast.noaa.gov/inventory/; USGS ScienceBaseCatalog: https://www.sciencebase.gov/catalog/item/656e229bd34e7ca10833f950)Source Data for Bathy Coverage Layers - GLRI AOIs (2020-2024):Acquisition: NOAA Office for Coastal ManagementValidation/CMECS Characterizations: NOAA National Centers for Coastal Ocean Science (NCCOS)Source Data for Bathy Coverage Layers - In Progress and Planned:NOAA Office of Coast Survey Plans: https://gis.charttools.noaa.gov/arcgis/rest/services/Hydrographic_Services/Planned_Survey_Areas/MapServer/0NOAA Office for Coastal ManagementSource Data for Nearshore Water Depths:NOAA's National Centers for Environmental Information (NCEI) Great Lakes Bathymetry (3-second resolution) grid extracts: https://www.ncei.noaa.gov/maps/grid-extract/Source Data for Spatial Prioritization Layers:Great Lakes Spatial Priorities Study Results Jun 2021. https://gis.charttools.noaa.gov/arcgis/rest/services/IOCM/GreatLakes_SPS_Results_Jun_2021/MapServerMapping priorities within the proposed Wisconsin Lake Michigan National Marine Sanctuary (2018). https://gis.ngdc.noaa.gov/arcgis/rest/services/nccos/BiogeographicAssessments_WILMPrioritizationResults/MapServerThunder Bay National Marine Sanctuary Spatial Prioritization Results (2020). https://gis.ngdc.noaa.gov/arcgis/rest/services/nccos/BiogeographicAssessments_TBNMSPrioritizationResults/MapServerSource Data for Supplemental Data Layers:International Boundary Commission U.S./Canada Boundary (version 1.3 from 2018): https://www.internationalboundarycommission.org/en/maps-coordinates/coordinates.phpNational Oceanic and Atmospheric Administration (NOAA) HydroHealth 2018 Survey: https://wrecks.nauticalcharts.noaa.gov/arcgis/rest/services/Hydrographic_Services/HydroHealth_2018/ImageServerNational Oceanic and Atmospheric Administration (NOAA) Marine Protected Areas (MPA) Inventory 2023-2024: https://www.fisheries.noaa.gov/inport/item/69506National Oceanic and Atmospheric Administration (NOAA) National Marine Sanctuary Program Boundaries (2021): https://services2.arcgis.com/C8EMgrsFcRFL6LrL/arcgis/rest/services/ONMS_2021_Boundaries/FeatureServerNational Oceanic and Atmospheric Administration (NOAA) U.S. Bathymetry Gap Analysis: https://noaa.maps.arcgis.com/home/item.html?id=4d7d925fc96d47d9ace970dd5040df0aU.S. Environment Protection Agency (EPA) Areas of Concern: https://services.arcgis.com/cJ9YHowT8TU7DUyn/arcgis/rest/services/epa_areas_of_concern_glahf_viewlayer/FeatureServerU.S. Geological Survey (USGS) Great Lakes Subbasins: https://www.sciencebase.gov/catalog/item/530f8a0ee4b0e7e46bd300dd Latest update: February 20, 2025

  18. a

    DAV/LandcoverFootprints

    • home-pugonline.hub.arcgis.com
    Updated Oct 23, 2023
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    The PUG User Group (2023). DAV/LandcoverFootprints [Dataset]. https://home-pugonline.hub.arcgis.com/maps/pugonline::landcover-11-25m/about
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    Dataset updated
    Oct 23, 2023
    Dataset authored and provided by
    The PUG User Group
    Area covered
    Description

    This map service presents spatial information about Landcover Data Access Viewer services across the United States and Territories in the Web Mercator projection. The service was developed by the National Oceanic and Atmospheric Administration (NOAA), but may contain data and information from a variety of data sources, including non-NOAA data. NOAA provides the information “as-is” and shall incur no responsibility or liability as to the completeness or accuracy of this information. NOAA assumes no responsibility arising from the use of this information. The NOAA Office for Coastal Management will make every effort to provide continual access to this service but it may need to be taken down during routine IT maintenance or in case of an emergency. If you plan to ingest this service into your own application and would like to be informed about planned and unplanned service outages or changes to existing services, please register for our Data Services Newsletter (http://coast.noaa.gov/digitalcoast/publications/subscribe). For additional information, please contact the NOAA Office for Coastal Management (coastal.info@noaa.gov).

  19. U.S. Great Lakes Collaborative Benthic Habitat Mapping Project Map: Planned...

    • noaa.hub.arcgis.com
    Updated Feb 21, 2025
    + more versions
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    NOAA GeoPlatform (2025). U.S. Great Lakes Collaborative Benthic Habitat Mapping Project Map: Planned Acquisition [Dataset]. https://noaa.hub.arcgis.com/maps/6159fc338a284a6a8fdaacd8fd94f048
    Explore at:
    Dataset updated
    Feb 21, 2025
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Authors
    NOAA GeoPlatform
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    THIS MAP IS NOT AUTHORITATIVE. SEE TERMS OF USE BELOW.This web map was developed by the National Oceanic and Atmospheric Administration’s (NOAA) Office for Coastal Management and is featured in the U.S. Great Lakes Collaborative Benthic Habitat Mapping Common Operating Dashboard in support of the Collaborative Benthic Habitat Mapping in the Nearshore Waters of the Great Lakes Basin Project. This multi-year, multi-agency project is funded through the Great Lakes Restoration Initiative (GLRI) and focuses on new bathymetric data (airborne lidar and vessel based sonar) acquisition, validation, and benthic habitat characterization mapping of the nearshore waters (0-80 meters) in the U.S. Great Lakes. This project also contributes to the regional Lakebed 2030 campaign, which aims to have high-density bathymetric data available for the entirety of the Great Lakes by 2030. This web map contains data layers reflecting the current status of bathy data coverage in the nearshore (0-80 meters) of the U.S. Great Lakes, including acquisition (lidar and multibeam sonar), ground-truthing/validation, and benthic habitat mapping and characterization. Acquisition layers include coverage areas that have been acquired and are available for public use (green) as well as those that have been acquired, but are not yet available or are still in progress (orange). The nearshore water depth layers (0-25 and 25-80 meters) were created using the National Centers for Environmental Information (NCEI) Great Lakes Bathymetry (3-second resolution) grid extracts. The 0 to 25 meter nearshore water depth layer represents areas where bathymetric lidar data acquisition could ideally be conducted, depending on water condition and turbidity. The 25 to 80 meter layer shows locations where acoustic data acquisition can occur. See below for information on additional data layers. All data originally projected in the following coordinate system: EPSG:3175, NAD 1983 Great Lakes and St Lawrence Albers.This map will continue to be updated as new information is made available.Source Data for Bathy Coverage Layers - Acquired/Available:Topobathy and Bathy Lidar (NOAA's Data Access Viewer: https://coast.noaa.gov/dataviewer/#/; U.S. Interagency Elevation Inventory (USIEI): https://coast.noaa.gov/inventory/). Multibeam Sonar (National Centers for Environmental Information (NCEI) Bathymetric Data Viewer: https://www.ncei.noaa.gov/maps/bathymetry/; NOAA's Data Access Viewer: https://coast.noaa.gov/dataviewer/#/; U.S. Interagency Elevation Inventory (USIEI): https://coast.noaa.gov/inventory/; USGS ScienceBaseCatalog: https://www.sciencebase.gov/catalog/item/656e229bd34e7ca10833f950)Source Data for Bathy Coverage Layers - GLRI AOIs (2020-2024):Acquisition: NOAA Office for Coastal ManagementValidation/CMECS Characterizations: NOAA National Centers for Coastal Ocean Science (NCCOS)Source Data for Bathy Coverage Layers - In Progress and Planned:NOAA Office of Coast Survey Plans: https://gis.charttools.noaa.gov/arcgis/rest/services/Hydrographic_Services/Planned_Survey_Areas/MapServer/0NOAA Office for Coastal ManagementSource Data for Nearshore Water Depths:NOAA's National Centers for Environmental Information (NCEI) Great Lakes Bathymetry (3-second resolution) grid extracts: https://www.ncei.noaa.gov/maps/grid-extract/Source Data for Spatial Prioritization Layers:Great Lakes Spatial Priorities Study Results Jun 2021. https://gis.charttools.noaa.gov/arcgis/rest/services/IOCM/GreatLakes_SPS_Results_Jun_2021/MapServerMapping priorities within the proposed Wisconsin Lake Michigan National Marine Sanctuary (2018). https://gis.ngdc.noaa.gov/arcgis/rest/services/nccos/BiogeographicAssessments_WILMPrioritizationResults/MapServerThunder Bay National Marine Sanctuary Spatial Prioritization Results (2020). https://gis.ngdc.noaa.gov/arcgis/rest/services/nccos/BiogeographicAssessments_TBNMSPrioritizationResults/MapServerSource Data for Supplemental Data Layers:International Boundary Commission U.S./Canada Boundary (version 1.3 from 2018): https://www.internationalboundarycommission.org/en/maps-coordinates/coordinates.phpNational Oceanic and Atmospheric Administration (NOAA) HydroHealth 2018 Survey: https://wrecks.nauticalcharts.noaa.gov/arcgis/rest/services/Hydrographic_Services/HydroHealth_2018/ImageServerNational Oceanic and Atmospheric Administration (NOAA) Marine Protected Areas (MPA) Inventory 2023-2024: https://www.fisheries.noaa.gov/inport/item/69506National Oceanic and Atmospheric Administration (NOAA) National Marine Sanctuary Program Boundaries (2021): https://services2.arcgis.com/C8EMgrsFcRFL6LrL/arcgis/rest/services/ONMS_2021_Boundaries/FeatureServerNational Oceanic and Atmospheric Administration (NOAA) U.S. Bathymetry Gap Analysis: https://noaa.maps.arcgis.com/home/item.html?id=4d7d925fc96d47d9ace970dd5040df0aU.S. Environment Protection Agency (EPA) Areas of Concern: https://services.arcgis.com/cJ9YHowT8TU7DUyn/arcgis/rest/services/epa_areas_of_concern_glahf_viewlayer/FeatureServerU.S. Geological Survey (USGS) Great Lakes Subbasins: https://www.sciencebase.gov/catalog/item/530f8a0ee4b0e7e46bd300dd Latest update: February 20, 2025

  20. 2015 ILHMP Lidar: Ford, Iroquois, Livingston Counties, IL

    • fisheries.noaa.gov
    las/laz - laser +1
    Updated Jan 1, 2015
    + more versions
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    OCM Partners (2015). 2015 ILHMP Lidar: Ford, Iroquois, Livingston Counties, IL [Dataset]. https://www.fisheries.noaa.gov/inport/item/73747
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    not applicable, las/laz - laserAvailable download formats
    Dataset updated
    Jan 1, 2015
    Dataset provided by
    OCM Partners
    Time period covered
    Mar 31, 2015
    Area covered
    Description

    This project involved fixed wing aerial LIDAR data collected at a contracted point spacing of 0.70 meters for the Illinois Counties of Ford, Iroquois and Livingston totaling approximately 2,740 square miles. This classified LAS Data was created from the final controled swath data.

    This metadata record supports the data entry in the NOAA Digital Coast Data Access Viewer (DAV). For this data s...

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NC OneMap / State of North Carolina (2023). Data Access Viewer - NOAA Office of Coastal Management [Dataset]. https://www.nconemap.gov/documents/4ede1ee1ef98408ea71131b457c41af4

Data Access Viewer - NOAA Office of Coastal Management

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Dataset updated
Aug 31, 2023
Dataset authored and provided by
NC OneMap / State of North Carolina
Description

The NOAA Data Access Viewer (DAV) allows for the download of elevation data shared by the NC Emergency Management. Users can customize the free downloads according to needs - projection, datum, product output (raster, points, contours), format, etc.

Go to the NOAA Data Access Viewer


For more information:

Tips to use the NOAA DAV

NOAA blog posts about the DAV

NOAA blog posts about LiDAR
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