100+ datasets found
  1. NASA Earth Observations (NEO)

    • catalog.data.gov
    • datasets.ai
    • +5more
    Updated Apr 11, 2025
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    National Aeronautics and Space Administration (2025). NASA Earth Observations (NEO) [Dataset]. https://catalog.data.gov/dataset/nasa-earth-observations-neo
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    Dataset updated
    Apr 11, 2025
    Dataset provided by
    NASAhttp://nasa.gov/
    Description

    Our mission is to help you picture climate change and environmental changes happening on our home planet. Here you can search for and retrieve satellite images of Earth. Download them; export them to GoogleEarth; perform basic analysis. Tracking regional and global changes around the world just got easier.

  2. NASA Earth Observatory Images

    • catalog.data.gov
    • datasets.ai
    • +4more
    Updated Apr 10, 2025
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    National Aeronautics and Space Administration (2025). NASA Earth Observatory Images [Dataset]. https://catalog.data.gov/dataset/nasa-earth-observatory-images
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    Dataset updated
    Apr 10, 2025
    Dataset provided by
    NASAhttp://nasa.gov/
    Description

    The Earth Observatory is part of the EOS Project Science Office located at NASA Goddard Space Flight Center.

  3. Data from: NASA Earth Exchange (NEX)

    • catalog.data.gov
    • datasets.ai
    • +4more
    Updated Apr 11, 2025
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    National Aeronautics and Space Administration (2025). NASA Earth Exchange (NEX) [Dataset]. https://catalog.data.gov/dataset/nasa-earth-exchange-nex
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    Dataset updated
    Apr 11, 2025
    Dataset provided by
    NASAhttp://nasa.gov/
    Area covered
    Earth
    Description

    The NASA Earth Exchange (NEX) represents a new platform for the Earth science community that provides a mechanism for scientific collaboration and knowledge sharing. NEX combines state-of-the-art supercomputing, Earth system modeling, workflow management, NASA remote sensing data feeds, and a knowledge sharing platform to deliver a complete work environment in which users can explore and analyze large datasets, run modeling codes, collaborate on new or existing projects, and quickly share results among the Earth Science communities.

  4. r

    NASA: Earth Science Data

    • rrid.site
    • neuinfo.org
    Updated Jan 29, 2022
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    (2022). NASA: Earth Science Data [Dataset]. http://identifiers.org/RRID:SCR_005078
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    Dataset updated
    Jan 29, 2022
    Area covered
    Earth
    Description

    The Earth Observing System Data and Information System (EOSDIS) is a major core capability within NASA''s Earth Science Data Systems Program. EOSDIS ingests, processes, archives and distributes data from a large number of Earth observing satellites. EOSDIS consists of a set of processing facilities and Earth Science Data Centers distributed across the United States and serves hundreds of thousands of users around the world, providing hundreds of millions of data files each year covering many Earth science disciplines. In order to serve the needs of a broad and diverse community of users, NASA''s Earth Science Data Systems Program is comprised of both Core and Community data system elements. Core data system elements reflect NASA''s responsibility for managing Earth science satellite mission data characterized by the continuity of research, access, and usability. The core comprises all the hardware, software, physical infrastructure, and intellectual capital NASA recognizes as necessary for performing its tasks in Earth science data system management. Community data system elements are those pieces or capabilities developed and deployed largely outside of NASA core elements and are characterized by their evolvability and innovation. Successful applicable elements can be infused into the core, thereby creating a vibrant and flexible, continuously evolving infrastructure. NASA''s Earth Science program was established to use the advanced technology of NASA to understand and protect our home planet by using our view from space to study the Earth system and improve prediction of Earth system change. To meet this challenge, NASA promotes the full and open sharing of all data with the research and applications communities, private industry, academia, and the general public. NASA was the first agency in the US, and the first space agency in the world, to couple policy and adequate system functionality to provide full and open access in a timely manner - that is, with no period of exclusive access to mission scientists - and at no cost. NASA made this decision after listening to the user community, and with the background of the then newly-formed US Global Change Research Program, and the International Earth Observing System partnerships. Other US agencies and international space agencies have since adopted similar open-access policies and practices. Since the adoption of the Earth Science Data Policy adoption in 1991, NASA''s Earth Science Division has developed policy implementation, practices, and nomenclature that mission science teams use to comply with policy tenets. Data System Standards NASA''s Earth Science Data Systems Groups anticipate that effective adoption of standards will play an increasingly vital role in the success of future science data systems. The Earth Science Data Systems Standards Process Group (SPG), a board composed of Earth Science Data Systems stakeholders, directs the process for both identification of appropriate standards and subsequent adoption for use by the Earth Science Data Systems stakeholders.

  5. Data from: NASA Earth Exchange Global Daily Downscaled Projections...

    • registry.opendata.aws
    Updated Sep 27, 2022
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    NASA (2022). NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6) [Dataset]. https://registry.opendata.aws/nex-gddp-cmip6/
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    Dataset updated
    Sep 27, 2022
    Dataset provided by
    NASAhttp://nasa.gov/
    License
    Area covered
    Earth
    Description

    The NEX-GDDP-CMIP6 dataset is comprised of global downscaled climate scenarios derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 6 (CMIP6) and across two of the four "Tier 1" greenhouse gas emissions scenarios known as Shared Socioeconomic Pathways (SSPs). The CMIP6 GCM runs were developed in support of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR6). This dataset includes downscaled projections from ScenarioMIP model runs for which daily scenarios were produced and distributed through the Earth System Grid Federation. The purpose of this dataset is to provide a set of global, high resolution, bias-corrected climate change projections that can be used to evaluate climate change impacts on processes that are sensitive to finer-scale climate gradients and the effects of local topography on climate conditions.

  6. NEX-DCP30: Ensemble Stats for NASA Earth Exchange Downscaled Climate...

    • developers.google.com
    Updated Jul 30, 2018
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    NASA / Climate Analytics Group (2018). NEX-DCP30: Ensemble Stats for NASA Earth Exchange Downscaled Climate Projections [Dataset]. https://developers.google.com/earth-engine/datasets/catalog/NASA_NEX-DCP30_ENSEMBLE_STATS
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    Dataset updated
    Jul 30, 2018
    Dataset provided by
    NASAhttp://nasa.gov/
    Time period covered
    Jan 1, 1950 - Dec 1, 2099
    Area covered
    Description

    The NASA NEX-DCP30 dataset is comprised of downscaled climate scenarios for the conterminous United States that are derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5, see Taylor et al. 2012) and across the four greenhouse gas emissions scenarios known as …

  7. NASA EarthData Search

    • data.cnra.ca.gov
    Updated Jul 17, 2020
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    National Aeronautics and Space Administration (2020). NASA EarthData Search [Dataset]. https://data.cnra.ca.gov/dataset/nasa-earthdata-search
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    Dataset updated
    Jul 17, 2020
    Dataset provided by
    NASAhttp://nasa.gov/
    Authors
    National Aeronautics and Space Administration
    Description

    Earthdata Search is a web application developed by NASA EOSDIS to enable data discovery, search, comparison, visualization, and access across EOSDIS' Earth Science data holdings.

  8. w

    NASA Earth Exchange Global Daily Downscaled Projections

    • data.wu.ac.at
    • cmr.earthdata.nasa.gov
    bin
    Updated Dec 31, 2100
    + more versions
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    National Aeronautics and Space Administration (2100). NASA Earth Exchange Global Daily Downscaled Projections [Dataset]. https://data.wu.ac.at/schema/data_gov/MDQ0ZmIxMTAtYmUwNy00YTQxLWI5ZmQtMTMwMDE2MjUwMzZk
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    binAvailable download formats
    Dataset updated
    Dec 31, 2100
    Dataset provided by
    National Aeronautics and Space Administration
    Area covered
    Earth, 1f96f7af4877ce6199ae860ed940f56fbe21464f
    Description

    The NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is comprised of downscaled climate scenarios for the globe that are derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and across two of the four greenhouse gas emissions scenarios known as Representative Concentration Pathways (RCPs). The CMIP5 GCM runs were developed in support of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). The NEX-GDDP dataset includes downscaled projections for RCP 4.5 and RCP 8.5 from the 21 models and scenarios for which daily scenarios were produced and distributed under CMIP5. Each of the climate projections includes daily maximum temperature, minimum temperature, and precipitation for the periods from 1950 through 2100. The spatial resolution of the dataset is 0.25 degrees (~25 km x 25 km). The NEX-GDDP dataset is provided to assist the science community in conducting studies of climate change impacts at local to regional scales, and to enhance public understanding of possible future global climate patterns at the spatial scale of individual towns, cities, and watersheds.

    Each of the climate projections includes monthly averaged maximum temperature, minimum temperature, and precipitation for the periods from 1950 through 2005 (Retrospective Run) and from 2006 to 2099 (Prospective Run).

  9. Satellite (MODIS) Thermal Hotspots and Fire Activity

    • wifire-data.sdsc.edu
    • emergency-lacounty.hub.arcgis.com
    Updated Mar 4, 2023
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    Esri (2023). Satellite (MODIS) Thermal Hotspots and Fire Activity [Dataset]. https://wifire-data.sdsc.edu/dataset/satellite-modis-thermal-hotspots-and-fire-activity
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    html, arcgis geoservices rest apiAvailable download formats
    Dataset updated
    Mar 4, 2023
    Dataset provided by
    Esrihttp://esri.com/
    Description

    This layer presents detectable thermal activity from MODIS satellites for the last 7 days. MODIS Global Fires is a product of NASA’s Earth Observing System Data and Information System (EOSDIS), part of NASA's Earth Science Data. EOSDIS integrates remote sensing and GIS technologies to deliver global MODIS hotspot/fire locations to natural resource managers and other stakeholders around the World.


    Consumption Best Practices:

    • As a service that is subject to Viral loads (very high usage), avoid adding Filters that use a Date/Time type field. These queries are not cacheable and WILL be subject to 'https://en.wikipedia.org/wiki/Rate_limiting' rel='nofollow ugc'>Rate Limiting by ArcGIS Online. To accommodate filtering events by Date/Time, we encourage using the included "Age" fields that maintain the number of Days or Hours since a record was created or last modified compared to the last service update. These queries fully support the ability to cache a response, allowing common query results to be supplied to many users without adding load on the service.
    • When ingesting this service in your applications, avoid using POST requests, these requests are not cacheable and will also be subject to Rate Limiting measures.

    Scale/Resolution: 1km

    Update Frequency: 1/2 Hour (every 30 minutes) using the Aggregated Live Feed Methodology

    Area Covered: World

    What can I do with this layer?
    The MODIS thermal activity layer can be used to visualize and assess wildfires worldwide. However, it should be noted that this dataset contains many “false positives” (e.g., oil/natural gas wells or volcanoes) since the satellite will detect any large thermal signal.

    Additional Information
    MODIS stands for MODerate resolution Imaging Spectroradiometer. The MODIS instrument is on board NASA’s Earth Observing System (EOS) Terra (EOS AM) and Aqua (EOS PM) satellites. The orbit of the Terra satellite goes from north to south across the equator in the morning and Aqua passes south to north over the equator in the afternoon resulting in global coverage every 1 to 2 days. The EOS satellites have a ±55 degree scanning pattern and orbit at 705 km with a 2,330 km swath width.

    It takes approximately 2 – 4 hours after satellite overpass for MODIS Rapid Response to process the data, and for the Fire Information for Resource Management System (FIRMS) to update the website. Occasionally, hardware errors can result in processing delays beyond the 2-4 hour range. Additional information on the MODIS system status can be found at MODIS Rapid Response.

    Attribute Information
    • Latitude and Longitude: The center point location of the 1km (approx.) pixel flagged as containing one or more fires/hotspots (fire size is not 1km, but variable). Stored by Point Geometry. See What does a hotspot/fire detection mean on the ground?
    • Brightness: The brightness temperature measured (in Kelvin) using the MODIS channels 21/22 and channel 31.
    • Scan and Track: The actual spatial resolution of the scanned pixel. Although the algorithm works at 1km resolution, the MODIS pixels get bigger toward the edge of the scan. See What does scan and track mean?
    • Date and Time: Acquisition date of the hotspot/active fire pixel and time of satellite overpass in UTC (client presentation in local time). Stored by Acquisition Date.
    • Acquisition Date: Derived Date/Time field combining Date and Time attributes.
    • Satellite: Whether the detection was picked up by the Terra or Aqua satellite.
    • Confidence: The detection confidence is a quality flag of the individual hotspot/active fire pixel.
    • Version: Version refers to the processing collection and source of data. The number before the decimal refers to the collection (e.g. MODIS Collection 6). The number after the decimal indicates the source of Level 1B data; data processed in near-real time by MODIS Rapid Response will have the source code “CollectionNumber.0”. Data sourced from MODAPS (with a 2-month lag) and processed by FIRMS using the standard MOD14/MYD14 Thermal Anomalies algorithm will have a source code “CollectionNumber.x”. For example, data with the version listed as 5.0 is collection 5, processed by MRR, data with the version listed as 5.1 is collection 5 data processed by FIRMS using Level 1B data from MODAPS.
    • Bright.T31: Channel 31 brightness temperature (in Kelvins) of the hotspot/active fire pixel.
    • FRP: Fire Radiative Power. Depicts the pixel-integrated fire radiative power in MW (MegaWatts). FRP provides information on the measured radiant heat output of detected fires. The amount of radiant heat energy liberated per unit time (the Fire Radiative Power) is thought to be related to the rate at which fuel is being consumed (Wooster et. al. (2005)).
    • DayNight: The standard processing algorithm uses the solar zenith angle (SZA) to threshold the day/night value; if the SZA exceeds 85 degrees it is assigned a night value. SZA values less than 85 degrees are assigned a day time value. For the NRT algorithm the day/night flag is assigned by ascending (day) vs descending (night) observation. It is expected that the NRT assignment of the day/night flag will be amended to be consistent with the standard processing.
    • Hours Old: Derived field that provides age of record in hours between Acquisition date/time and latest update date/time. 0 = less than 1 hour ago, 1 = less than 2 hours ago, 2 = less than 3 hours ago, and so on.
    Revisions
    • June 22, 2022: Added 'HOURS_OLD' field to enhance Filtering data. Added 'Last 7 days' Layer to extend data to match time range of VIIRS offering. Added Field level descriptions.
    This map is provided for informational purposes and is not monitored 24/7 for accuracy and

  10. n

    SMAP_L1B_SIGMA_NAUGHT_LOW_RES_QA_V003

    • cmr.earthdata.nasa.gov
    • access.earthdata.nasa.gov
    • +4more
    + more versions
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    SMAP_L1B_SIGMA_NAUGHT_LOW_RES_QA_V003 [Dataset]. https://cmr.earthdata.nasa.gov/search/concepts/C1243129847-ASF.html
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    Time period covered
    Feb 12, 2015 - Present
    Area covered
    Earth
    Description

    SMAP Level 1B Sigma Naught Low Res Data Quality Info Version 3

  11. g

    NASA Earth Observatory Images

    • gimi9.com
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    NASA Earth Observatory Images [Dataset]. https://gimi9.com/dataset/data-gov_nasa-earth-observatory-images/
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    Description

    🇺🇸 미국

  12. a

    NASA Earth Observations (NEO) WMS

    • catalogue.arctic-sdi.org
    Updated Dec 24, 2023
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    (2023). NASA Earth Observations (NEO) WMS [Dataset]. https://catalogue.arctic-sdi.org/geonetwork/srv/search?keyword=nasa
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    Dataset updated
    Dec 24, 2023
    Area covered
    Earth
    Description

    Remote sensing imagery from NASA Earth Observations (NEO).

  13. NASA Prediction of Worldwide Energy Resources (POWER)

    • registry.opendata.aws
    Updated Jun 1, 2022
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    NASA (2022). NASA Prediction of Worldwide Energy Resources (POWER) [Dataset]. https://registry.opendata.aws/nasa-power/
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    Dataset updated
    Jun 1, 2022
    Dataset provided by
    NASAhttp://nasa.gov/
    Description

    NASA's goal in Earth science is to observe, understand, and model the Earth system to discover how it is changing, to better predict change, and to understand the consequences for life on Earth. The Applied Sciences Program, within the Earth Science Division of the NASA Science Mission Directorate, serves individuals and organizations around the globe by expanding and accelerating societal and economic benefits derived from Earth science, information, and technology research and development.

    The Prediction Of Worldwide Energy Resources (POWER) Project, funded through the Applied Sciences Program at NASA Langley Research Center, gathers NASA Earth observation data and parameters related to the fields of surface solar irradiance and meteorology to serve the public in several free, easy-to-access and easy-to-use methods. POWER helps communities become resilient amid observed climate variability by improving data accessibility, aiding research in energy development, building energy efficiency, and supporting agriculture projects.

    The POWER project contains over 380 satellite-derived meteorology and solar energy Analysis Ready Data (ARD) at four temporal levels: hourly, daily, monthly, and climatology. The POWER data archive provides data at the native resolution of the source products. The data is updated nightly to maintain near real time availability (2-3 days for meteorological parameters and 5-7 days for solar). The POWER services catalog consists of a series of RESTful Application Programming Interfaces, geospatial enabled image services, and web mapping Data Access Viewer. These three service offerings support data discovery, access, and distribution to the project’s user base as ARD and as direct application inputs to decision support tools.

    The latest data version update includes hourly-based source ARD, in addition to enhanced daily, monthly, annual, and climatology data. The daily time series for meteorology is available from 1981, while solar-based parameters start in 1984. The hourly source data are from Clouds and the Earth's Radiant Energy System (CERES) and Global Modeling and Assimilation Office (GMAO), spanning from 1984 for meteorology and from 2001 for solar-based parameters. The hourly data equips users with the ARD needed to model building system energy performance, providing information directly amenable to decision support tools introducing the industry standard EnergyPlus Weather file format.

  14. c

    NASA Near Earth Objects Information Dataset

    • cubig.ai
    Updated Jun 28, 2025
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    CUBIG (2025). NASA Near Earth Objects Information Dataset [Dataset]. https://cubig.ai/store/products/493/nasa-near-earth-objects-information-dataset
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    Dataset updated
    Jun 28, 2025
    Dataset authored and provided by
    CUBIG
    License

    https://cubig.ai/store/terms-of-servicehttps://cubig.ai/store/terms-of-service

    Area covered
    Earth
    Measurement technique
    Privacy-preserving data transformation via differential privacy, Synthetic data generation using AI techniques for model training
    Description

    1) Data Introduction • The NASA Near Earth Objects Information Dataset is a structured astronomy dataset containing detailed information about Near-Earth Objects (NEOs), including their orbits, size, absolute magnitude, and observation history.

    2) Data Utilization (1) Characteristics of the NASA Near Earth Objects Information Dataset: • Key features include object ID, name, absolute magnitude, estimated diameter, orbit type, perihelion and aphelion distances, and the first and last observation dates. Most of the observed objects are asteroids and comets passing near Earth’s orbit. • Each object's orbit is calculated based on accumulated observations collected over years, including various orbital parameters such as perihelion, aphelion distances, and orbit classification.

    (2) Applications of the NASA Near Earth Objects Information Dataset: • Training orbital classification models for NEOs: Machine learning models can be trained to classify the orbit type of a given celestial body using diverse orbital features. • Space hazard analysis and mission planning: The dataset can also be used to assess the potential impact risks of NEOs and to support asteroid exploration missions by analyzing physical properties and orbital characteristics.

  15. a

    Aerosol Optical Imagery Services from NASA GIBS

    • hub.arcgis.com
    • amerigeo.org
    • +3more
    Updated Nov 17, 2021
    + more versions
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    AmeriGEOSS (2021). Aerosol Optical Imagery Services from NASA GIBS [Dataset]. https://hub.arcgis.com/maps/416d291bf95c45058dadd6235d343e64
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    Dataset updated
    Nov 17, 2021
    Dataset authored and provided by
    AmeriGEOSS
    Area covered
    Description

    GIBS Available Imagery Products, last modified by on The GIBS imagery archive includes approximately 1000 imagery products representing visualized science data from the NASA Earth Observing System Data and Information System (EOSDIS). Each imagery product is generated at the native resolution of the source data to provide "full resolution" visualizations of a science parameter. GIBS works closely with the science teams to identify the appropriate data range and color mappings, where appropriate, to provide the best quality imagery to the Earth science community. Many GIBS imagery products are generated by the EOSDIS LANCE near real-time processing system resulting in imagery available in GIBS within 3.5 hours of observation. These products and others may also extend from present to the beginning of the satellite mission. In addition, GIBS makes available supporting imagery layers such as data/no-data, water masks, orbit tracks, and graticules to improve imagery usage.The GIBS team is actively engaging the NASA EOSDIS Distributed Active Archive Centers (DAACs) to add more imagery products and to extend their coverage throughout the life of the mission. The remainder of this page provides a structured view of the layers currently available within GIBS grouped by science discipline and science observation. For information regarding how to access these products, see the GIBS API section of this wiki. For information regarding how to access these products through an existing client, refer to the Map Library and GIS Client sections of this wiki. If you are aware of a science parameter that you would like to see visualized, please contact us at support@earthdata.nasa.gov. https://wiki.earthdata.nasa.gov/display/GIBS/GIBS+Available+Imagery+Products#expand-AerosolOpticalDepth29ProductsNASA GIS API for Developers https://wiki.earthdata.nasa.gov/display/GIBS/GIBS+API+for+Developers

  16. EarthData MERRA2 CO

    • kaggle.com
    Updated Jul 18, 2020
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    Gabriel Preda (2020). EarthData MERRA2 CO [Dataset]. https://www.kaggle.com/gpreda/earthdata-merra2-co/tasks
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 18, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Gabriel Preda
    Description

    Context

    Satellite data, measured using MERRA2. MERRA2 stands for Modern-**E**ra Retrospective analysis for Research and Applications, Version 2.

    Data files

    Each data file contains the measurement data for entire Earth, for a specific month. The year and month is specified in the file name, with the pattern YYYYMM. The data is from Jan 2019 to April 2020.

    Data format

    The data is in nc4 format. You can learn how to read such format from here: How to read and plot NetCDF MERRA-2 data in Python.

  17. Goddard Earth Sciences Data and Information Services Center (GES DISC)

    • data.nasa.gov
    • s.cnmilf.com
    • +2more
    Updated Mar 31, 2025
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    nasa.gov (2025). Goddard Earth Sciences Data and Information Services Center (GES DISC) [Dataset]. https://data.nasa.gov/dataset/goddard-earth-sciences-data-and-information-services-center-ges-disc
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    Dataset updated
    Mar 31, 2025
    Dataset provided by
    NASAhttp://nasa.gov/
    Area covered
    Earth
    Description

    The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) is the home (archive) of Precipitation, Atmospheric Chemistry and Dynamics, and information, as well as data and information from other related disciplines.

  18. c

    NASA Nearest Earth Objects Dataset

    • cubig.ai
    Updated May 20, 2025
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    CUBIG (2025). NASA Nearest Earth Objects Dataset [Dataset]. https://cubig.ai/store/products/244/nasa-nearest-earth-objects-dataset
    Explore at:
    Dataset updated
    May 20, 2025
    Dataset authored and provided by
    CUBIG
    License

    https://cubig.ai/store/terms-of-servicehttps://cubig.ai/store/terms-of-service

    Area covered
    Earth
    Measurement technique
    Privacy-preserving data transformation via differential privacy, Synthetic data generation using AI techniques for model training
    Description

    1) Data Introduction • The NASA - Nearest Earth Objects dataset is a compiled collection of asteroids classified as Near-Earth Objects (NEOs). It contains various astronomical features such as name, orbiting body, absolute magnitude, relative velocity, estimated minimum and maximum diameters, and miss distance from Earth. It also includes a binary target variable (hazardous) indicating whether each object is considered potentially dangerous.

    2) Data Utilization (1) Characteristics of the NASA - Nearest Earth Objects Dataset: • The dataset includes numerical data based on various physical characteristics such as absolute magnitude, relative velocity, closest approach distance, and object size. • The target variable hazardous is binary, where 1 indicates a hazardous object and 0 indicates a non-hazardous object.

    (2) Applications of the NASA - Nearest Earth Objects Dataset: • Development of Space Hazard Detection Models: The dataset can be used to train classification models that predict potentially dangerous objects based on velocity, distance, and size. • Astronomical Data Analysis Practice: Suitable for data exploration and visualization tasks in astronomy and space science fields using real-world observational data from NASA.

  19. a

    Precipitation Imagery Services from NASA GIBS

    • amerigeo.org
    • climate.amerigeoss.org
    • +4more
    Updated Nov 18, 2021
    + more versions
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    AmeriGEOSS (2021). Precipitation Imagery Services from NASA GIBS [Dataset]. https://www.amerigeo.org/maps/ffc464325234442991c0228c4387605b
    Explore at:
    Dataset updated
    Nov 18, 2021
    Dataset authored and provided by
    AmeriGEOSS
    Area covered
    Description

    The Global Imagery Browse Services (GIBS) system is a core EOSDIS component which provides a scalable, responsive, highly available, and community standards based set of imagery services. These services are designed with the goal of advancing user interactions with EOSDIS’ inter-disciplinary data through enhanced visual representation and discovery.The GIBS imagery archive includes approximately 1000 imagery products representing visualized science data from the NASA Earth Observing System Data and Information System (EOSDIS). Each imagery product is generated at the native resolution of the source data to provide "full resolution" visualizations of a science parameter. GIBS works closely with the science teams to identify the appropriate data range and color mappings, where appropriate, to provide the best quality imagery to the Earth science community. Many GIBS imagery products are generated by the EOSDIS LANCE near real-time processing system resulting in imagery available in GIBS within 3.5 hours of observation. These products and others may also extend from present to the beginning of the satellite mission. In addition, GIBS makes available supporting imagery layers such as data/no-data, water masks, orbit tracks, and graticules to improve imagery usage.The GIBS team is actively engaging the NASA EOSDIS Distributed Active Archive Centers (DAACs) to add more imagery products and to extend their coverage throughout the life of the mission. The remainder of this page provides a structured view of the layers currently available within GIBS grouped by science discipline and science observation. For information regarding how to access these products, see the GIBS API section of this wiki. For information regarding how to access these products through an existing client, refer to the Map Library and GIS Client sections of this wiki. If you are aware of a science parameter that you would like to see visualized, please contact us at support@earthdata.nasa.gov.

  20. MODIS Thermal (Last 7 days)

    • wifire-data.sdsc.edu
    Updated Mar 3, 2023
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    Esri (2023). MODIS Thermal (Last 7 days) [Dataset]. https://wifire-data.sdsc.edu/dataset/modis-thermal-last-7-days
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    html, zip, csv, arcgis geoservices rest api, kml, geojsonAvailable download formats
    Dataset updated
    Mar 3, 2023
    Dataset provided by
    Esrihttp://esri.com/
    Description

    This layer presents detectable thermal activity from MODIS satellites for the last 7 days. MODIS Global Fires is a product of NASA’s Earth Observing System Data and Information System (EOSDIS), part of NASA's Earth Science Data. EOSDIS integrates remote sensing and GIS technologies to deliver global MODIS hotspot/fire locations to natural resource managers and other stakeholders around the World.


    Consumption Best Practices:

    • As a service that is subject to Viral loads (very high usage), avoid adding Filters that use a Date/Time type field. These queries are not cacheable and WILL be subject to 'https://en.wikipedia.org/wiki/Rate_limiting' rel='nofollow ugc'>Rate Limiting by ArcGIS Online. To accommodate filtering events by Date/Time, we encourage using the included "Age" fields that maintain the number of Days or Hours since a record was created or last modified compared to the last service update. These queries fully support the ability to cache a response, allowing common query results to be supplied to many users without adding load on the service.
    • When ingesting this service in your applications, avoid using POST requests, these requests are not cacheable and will also be subject to Rate Limiting measures.

    Scale/Resolution: 1km

    Update Frequency: 1/2 Hour (every 30 minutes) using the Aggregated Live Feed Methodology

    Area Covered: World

    What can I do with this layer?
    The MODIS thermal activity layer can be used to visualize and assess wildfires worldwide. However, it should be noted that this dataset contains many “false positives” (e.g., oil/natural gas wells or volcanoes) since the satellite will detect any large thermal signal.

    Additional Information
    MODIS stands for MODerate resolution Imaging Spectroradiometer. The MODIS instrument is on board NASA’s Earth Observing System (EOS) Terra (EOS AM) and Aqua (EOS PM) satellites. The orbit of the Terra satellite goes from north to south across the equator in the morning and Aqua passes south to north over the equator in the afternoon resulting in global coverage every 1 to 2 days. The EOS satellites have a ±55 degree scanning pattern and orbit at 705 km with a 2,330 km swath width.

    It takes approximately 2 – 4 hours after satellite overpass for MODIS Rapid Response to process the data, and for the Fire Information for Resource Management System (FIRMS) to update the website. Occasionally, hardware errors can result in processing delays beyond the 2-4 hour range. Additional information on the MODIS system status can be found at MODIS Rapid Response.

    Attribute Information
    • Latitude and Longitude: The center point location of the 1km (approx.) pixel flagged as containing one or more fires/hotspots (fire size is not 1km, but variable). Stored by Point Geometry. See What does a hotspot/fire detection mean on the ground?
    • Brightness: The brightness temperature measured (in Kelvin) using the MODIS channels 21/22 and channel 31.
    • Scan and Track: The actual spatial resolution of the scanned pixel. Although the algorithm works at 1km resolution, the MODIS pixels get bigger toward the edge of the scan. See What does scan and track mean?
    • Date and Time: Acquisition date of the hotspot/active fire pixel and time of satellite overpass in UTC (client presentation in local time). Stored by Acquisition Date.
    • Acquisition Date: Derived Date/Time field combining Date and Time attributes.
    • Satellite: Whether the detection was picked up by the Terra or Aqua satellite.
    • Confidence: The detection confidence is a quality flag of the individual hotspot/active fire pixel.
    • Version: Version refers to the processing collection and source of data. The number before the decimal refers to the collection (e.g. MODIS Collection 6). The number after the decimal indicates the source of Level 1B data; data processed in near-real time by MODIS Rapid Response will have the source code “CollectionNumber.0”. Data sourced from MODAPS (with a 2-month lag) and processed by FIRMS using the standard MOD14/MYD14 Thermal Anomalies algorithm will have a source code “CollectionNumber.x”. For example, data with the version listed as 5.0 is collection 5, processed by MRR, data with the version listed as 5.1 is collection 5 data processed by FIRMS using Level 1B data from MODAPS.
    • Bright.T31: Channel 31 brightness temperature (in Kelvins) of the hotspot/active fire pixel.
    • FRP: Fire Radiative Power. Depicts the pixel-integrated fire radiative power in MW (MegaWatts). FRP provides information on the measured radiant heat output of detected fires. The amount of radiant heat energy liberated per unit time (the Fire Radiative Power) is thought to be related to the rate at which fuel is being consumed (Wooster et. al. (2005)).
    • DayNight: The standard processing algorithm uses the solar zenith angle (SZA) to threshold the day/night value; if the SZA exceeds 85 degrees it is assigned a night value. SZA values less than 85 degrees are assigned a day time value. For the NRT algorithm the day/night flag is assigned by ascending (day) vs descending (night) observation. It is expected that the NRT assignment of the day/night flag will be amended to be consistent with the standard processing.
    • Hours Old: Derived field that provides age of record in hours between Acquisition date/time and latest update date/time. 0 = less than 1 hour ago, 1 = less than 2 hours ago, 2 = less than 3 hours ago, and so on.
    Revisions
    • June 22, 2022: Added 'HOURS_OLD' field to enhance Filtering data. Added 'Last 7 days' Layer to extend data to match time range of VIIRS offering. Added Field level descriptions.
    This map is provided for informational purposes and is not monitored 24/7 for accuracy and

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National Aeronautics and Space Administration (2025). NASA Earth Observations (NEO) [Dataset]. https://catalog.data.gov/dataset/nasa-earth-observations-neo
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NASA Earth Observations (NEO)

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Dataset updated
Apr 11, 2025
Dataset provided by
NASAhttp://nasa.gov/
Description

Our mission is to help you picture climate change and environmental changes happening on our home planet. Here you can search for and retrieve satellite images of Earth. Download them; export them to GoogleEarth; perform basic analysis. Tracking regional and global changes around the world just got easier.

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