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This registry exists to help people discover and share datasets that are available via AWS resources. See recent additions and learn more about sharing data on AWS.

See all usage examples for datasets listed in this registry tagged with radar.


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GPM IMERG Early Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V07 (GPM_3IMERGHHE) at GES DISC

atmosphereclimatedatacenterforecastglobalhdfhydrologylandmetadataopendapradarwater

Version 07B is the current version of the IMERG data sets. Older versions will no longer be available and have been superseded by Version 07.The Integrated Multi-satellitE Retrievals for GPM (IMERG) is the unified U.S. algorithm that provides the multi-satellite precipitation product for the U.S. GPM team.The precipitation estimates from the various precipitation-relevant satellite passive microwave (PMW) sensors comprising the GPM constellation are computed using the 2021 version of the Goddard Profiling Algorithm (GPROF2021), then gridded, intercalibrated to the GPM Combined Ku Radar-Radiome...

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GPM IMERG Final Precipitation L3 1 month 0.1 degree x 0.1 degree V07 (GPM_3IMERGM) at GES DISC

atmosphereclimatedatacenterforecastglobalhdfhydrologylandmetadataopendapradarwater

Version 07B is the current version of the IMERG data sets. Older versions will no longer be available and have been superseded by Version 07.The Integrated Multi-satellitE Retrievals for GPM (IMERG) is the unified U.S. algorithm that provides the multi-satellite precipitation product for the U.S. GPM team.The precipitation estimates from the various precipitation-relevant satellite passive microwave (PMW) sensors comprising the GPM constellation are computed using the 2021 version of the Goddard Profiling Algorithm (GPROF2021), then gridded, intercalibrated to the GPM Combined Ku Radar-Radiome...

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GPM IMERG Final Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V07 (GPM_3IMERGHH) at GES DISC

atmosphereclimatedatacenterforecastglobalhdfhydrologylandmetadataopendapradarwater

Version 07B is the current version of the IMERG data sets. Older versions will no longer be available and have been superseded by Version 07.The Integrated Multi-satellitE Retrievals for GPM (IMERG) is the unified U.S. algorithm that provides the multi-satellite precipitation product for the U.S. GPM team.The precipitation estimates from the various precipitation-relevant satellite passive microwave (PMW) sensors comprising the GPM constellation are computed using the 2021 version of the Goddard Profiling Algorithm (GPROF2021), then gridded, intercalibrated to the GPM Combined Ku Radar-Radiome...

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GPM IMERG Late Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V07 (GPM_3IMERGHHL) at GES DISC

atmosphereclimatedatacenterforecastglobalhdfhydrologylandmetadataopendapradarwater

Version 07B is the current version of the IMERG data sets. Older versions will no longer be available and have been superseded by Version 07.\n\nThe Integrated Multi-satellitE Retrievals for GPM (IMERG) is the unified U.S. algorithm that provides the multi-satellite precipitation product for the U.S. GPM team.\n\nThe precipitation estimates from the various precipitation-relevant satellite passive microwave (PMW) sensors comprising the GPM constellation are computed using the 2021 version of the Goddard Profiling Algorithm (GPROF2021), then gridded, intercalibrated to the GPM Combined Ku Radar...

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RACECAR Dataset

autonomous racingautonomous vehiclescomputer visionGNSSimage processinglidarlocalizationobject detectionobject trackingperceptionradarrobotics

The RACECAR dataset is the first open dataset for full-scale and high-speed autonomous racing. Multi-modal sensor data has been collected from fully autonomous Indy race cars operating at speeds of up to 170 mph (273 kph). Six teams who raced in the Indy Autonomous Challenge during 2021-22 have contributed to this dataset. The dataset spans 11 interesting racing scenarios across two race tracks which include solo laps, multi-agent laps, overtaking situations, high-accelerations, banked tracks, obstacle avoidance, pit entry and exit at different speeds. The data is organized and released in bot...

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OPERA Radiometric Terrain Corrected SAR Backscatter from Sentinel-1 validated product (Version 1)

coastalearth observationgeoscienceglobalhdficelandmetadataoceansorbitradarsentinel-1soil moisturesynthetic aperture radartiffxml

The Observational Products for End-Users from Remote Sensing Analysis (OPERA) Radiometric Terrain Corrected (RTC) SAR Backscatter from Sentinel-1 (S1) validated product consists of radar backscatter normalized with respect to the topography. The product maps signals related to the physical properties of ground scattering objects, such as surface roughness and soil moisture and/or vegetation. The OPERA RTC-S1 product is derived from Copernicus Sentinel-1 Interferometric Wide (IW) Single Look Complex (SLC) data with a near global scope and temporal sampling coincident with the availability of S1...

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Global Cache of Japan

atmosphereclimateclimate modelclimate projectionsclimate riskearth observationforecasthydrologymeteorologicaloceansradarsatellite imageryspace weatherweather

Global real-time Earth system data deemed by the World Meteorological Organisation (WMO) as essential for provision of services for the protection of life and property and for the well-being of all nations. Data is sourced from all WMO Member countries / territories and retained for 24-hours. JMA operate this Global Cache service curating and publishing the dataset on behalf of WMO.

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OPERA Radiometric Terrain Corrected SAR Backscatter from Sentinel-1 Static Layers validated product (Version 1)

coastalcogearth observationgeoscienceglobalicelandmetadataoceansorbitradarsentinel-1synthetic aperture radartiffxml

The Observational Products for End-Users from Remote Sensing Analysis (OPERA) Radiometric Terrain Corrected (RTC) SAR Backscatter from Sentinel-1 (S1) Static Layers (RTC-S1-STATIC) validated product contains static radar geometry layers associated with the OPERA Radiometric Terrain Corrected (RTC) SAR Backscatter from Sentinel-1 (S1) (RTC-S1) validated product. Due to the S1 mission’s narrow orbital tube, radar-geometry layers such as incidence angle, local incidence angle, number of looks, and RTC Area Normalization Factor (ANF) vary slightly over time for each position on the ground, and th...

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GPM DPR Precipitation Profile L2A 1.5 hours 5 km V07 (GPM_2ADPR) at GES DISC

atmospherecontaminationdatacenterearth observationglobalhdfmetadataopendapradarwater

Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07. .2ADPR provides single- and dual-frequency-derived precipitation estimates from the Ku and Ka radars of the Dual-Frequency Precipitation Radar (DPR) on the core GPM spacecraft. The output consists of three main classes of precipitation products: those derived from the Ku-band frequency over a wide swath (245 km), those derived from the Ka-band frequency over a narrow swath (125 km), and those derived from the dual-frequency data over the narrow swath. The Ka-ban...

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  • How to Read IMERG Data Using Python by James Acker, Jerome Alfred, Helen Amos, Chris Battisto, Thomas Hearty, Alexis Hunzinger, Lena Iredell, Christoph Keller, Binita KC, Carlee Loeser, Ariana Louise, Kristan Morgan, Dieu My T. Nguyen, Dana Ostrenga, Xiaohua Pan, Kanan Patel, Brianna R. Pagán, Andrey Savtchenko, Elliot Sherman, Suhung Shen, Jian Su,Joseph Wysk, Rupesh Shrestha.
  • How to Access GES DISC Data Using Python by James Acker, Jerome Alfred, Helen Amos, Chris Battisto, Thomas Hearty, Alexis Hunzinger, Lena Iredell, Christoph Keller, Binita KC, Carlee Loeser, Ariana Louise, Kristan Morgan, Dieu My T. Nguyen, Dana Ostrenga, Xiaohua Pan, Kanan Patel, Brianna R. Pagán, Andrey Savtchenko, Elliot Sherman, Suhung Shen, Jian Su,Joseph Wysk, Rupesh Shrestha.

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OPERA Coregistered Single-Look Complex from Sentinel-1 Static Layers validated product (Version 1)

coastalearth observationhdficelandmetadataoceansorbitradarsentinel-1synthetic aperture radarxml

The Observational Products for End-Users from Remote Sensing Analysis (OPERA) Coregistered Single-Look Complex (CSLC) from Sentinel-1 (S1) Static Layers (CSLC-S1-STATIC) validated product contains static radar geometry layers associated with the OPERA Coregistered Single-Look Complex (CSLC) from Sentinel-1 (S1) validated product. Due to the S1 mission’s narrow orbital tube, radar-geometry layers vary slightly over time for each position on the ground, and therefore are considered static. These static layers are provided separately from the OPERA CSLC-S1 product, as they are produced only once ...

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OPERA Coregistered Single-Look Complex from Sentinel-1 validated product (Version 1)

coastalearth observationhdficelandmetadataoceansorbitradarsentinel-1synthetic aperture radarxml

The Observational Products for End-Users from Remote Sensing Analysis (OPERA) Coregistered Single-Look Complex (CSLC) from Sentinel-1 validated product consists of Single Look Complex (SLC) images which contain both amplitude and phase information of the complex radar return. The amplitude is primarily determined by ground surface properties (e.g., terrain slope, surface roughness, and physical properties), and phase primarily represents the distance between the radar and ground targets corrected for the geometrical distance between the two based on the knowledge from Digital Elevation Model a...

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OPERA Dynamic Surface Water Extent from Sentinel-1 (Version 1)

cogdatacenterearth observationgloballandorbitradarsentinel-1surface waterwater

This dataset contains Level-3 Dynamic OPERA Surface Water Extent from Sentinel-1 (DSWx-S1) product version 1. DSWx-S1 provides near-global geographical mapping of surface water extent over land at a spatial resolution of 30 meters over the Military Grid reference System (MGRS) grid system, with a temporal revisit frequency between 6-12 days. Using Sentinel-1 radar observations, DSWx-S1 maps open inland water bodies greater than 3 hectares and 200 meters in width, irrespective of cloud conditions and daylight illumination that often pose challenges to optical sensors. Forward production of the...

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ABoVE: Bias-Corrected IMERG Monthly Precipitation for Alaska and Canada, 2000-2020

atmospherecogcogearth observationgloballandradar

This dataset is a modification to the Integrated Multi-satellitE Retrievals for GPM (IMERG) Final Run microwave-only, daily precipitation Version 06 data. It provides bias-corrected IMERG monthly precipitation data for Alaska and Canada from June 2000 through December 2020 in Cloud-Optimized GeoTIFF (*.tif) format. Data are provided in the units of mm/day. NASA's IMERG data product is one of the most advanced satellite precipitation products with a 0.1-degree spatial resolution and near global coverage. This dataset bias-corrected IMERG's HQprecipitation precipitation estimates, which ...

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MAN TruckScenes

autonomous vehiclescomputer visiondeep learningGPSIMUlidarlogisticsmachine learningobject detectionobject trackingperceptionradarroboticstransportation

A large scale multimodal dataset for Autonomous Trucking. Sensor data was recorded with a heavy truck from MAN equipped with 6 lidars, 6 radars, 4 cameras and a high-precision GNSS. MAN TruckScenes allows the research community to come into contact with truck-specific challenges, such as trailer occlusions, novel sensor perspectives, and terminal environments for the first time. It comprises more than 740 scenes of 20s each within a multitude of different environmental conditions. Bounding boxes are available for 27 object classes, 15 attributes, and a range of more than 230m. The scenes are t...

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Met Office UK Radar Observations on a 2-year rolling archive

atmospheregeospatialh5hdf5precipitationradarweather

The United Kingdom Composite, Surface Rain Rate Estimate is an international radar composite produced by Met Office (UK). This is a composite, radar reflectivity derived, surface rain rate estimate product in HDF5 code from stations covering the United Kingdom.

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OPERA Surface Displacement from Sentinel-1 validated product (Version 1)

earth observationlandmetadatanetcdforbitradarsentinel-1synthetic aperture radarxmlzarr

The Level-3 OPERA Sentinel-1 Surface Displacement (DISP) product is generated through interferometric time-series analysis of Level-2 Coregistered Sentinel-1 Single Look Complex (CSLC) datasets. Using a hybrid Persistent Scatterer (PS) and Distributed Scatterer (DS) approach, this product quantifies Earth's surface displacement in the radar line-of-sight. The DISP products enable the detection of anthropogenic and natural surface changes, including subsidence, tectonic deformation, and landslides. The OPERA DISP suite comprises complementary datasets derived from Sentinel-1 and NISAR input...

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SENTINEL-1A_DUAL_POL_GRD_HIGH_RES

agriculturecoastalearth observationearthquakesecosystemsicelandland coverland usemetadataoceansradarsentinel-1stacsurface watersynthetic aperture radartiffurbanwater

Sentinel-1A Dual-pol ground projected high and full resolution images Read our doc on how to get AWS Credentials to retrieve this data: https://sentinel1.asf.alaska.edu/s3credentialsREADME

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SENTINEL-1A_SLC

coastalearthquakesecosystemsicelandland coverland usemetadataoceansorbitradarsentinel-1stacsurface watersynthetic aperture radartiffurbanwater

Sentinel-1A slant-range product Read our doc on how to get AWS Credentials to retrieve this data: https://sentinel1.asf.alaska.edu/s3credentialsREADME

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SENTINEL-1B_DUAL_POL_GRD_HIGH_RES

agriculturecoastalearthquakesecosystemsicelandland coverland usemetadataoceansradarsentinel-1stacsurface watersynthetic aperture radartiffurbanwater

Sentinel-1B Dual-pol ground projected high and full resolution images Read our doc on how to get AWS Credentials to retrieve this data: https://sentinel1.asf.alaska.edu/s3credentialsREADME

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SENTINEL-1B_SLC

agriculturecoastalearthquakesecosystemsicelandland coverland usemetadataoceansorbitradarsentinel-1stacsurface watersynthetic aperture radartiffurbanwater

Sentinel-1B slant-range product Read our doc on how to get AWS Credentials to retrieve this data: https://sentinel1.asf.alaska.edu/s3credentialsREADME

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