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{

 "id": "10.5066/p96bqqq6",
 "attributes": {
   "doi": "10.5066/p96bqqq6",
   "identifiers": [],
   "creators": [
     {
       "name": "Carl J Legleiter",
       "nameType": "Personal",
       "affiliation": [
         "United States Geological Survey"
       ],
       "nameIdentifiers": [
         {
           "schemeUri": "https://orcid.org",
           "nameIdentifier": "https://orcid.org/0000-0003-0940-8013",
           "nameIdentifierScheme": "ORCID"
         }
       ]
     },
     {
       "name": "Michael Dille",
       "nameType": "Personal",
       "affiliation": [],
       "nameIdentifiers": [
         {
           "schemeUri": "https://orcid.org",
           "nameIdentifier": null,
           "nameIdentifierScheme": "ORCID"
         }
       ]
     },
     {
       "name": "Cian B Dawson",
       "nameType": "Personal",
       "affiliation": [
         "United States Geological Survey"
       ],
       "nameIdentifiers": [
         {
           "schemeUri": "https://orcid.org",
           "nameIdentifier": "https://orcid.org/0000-0001-7659-2944",
           "nameIdentifierScheme": "ORCID"
         }
       ]
     },
     {
       "name": "Paul J Kinzel",
       "nameType": "Personal",
       "affiliation": [
         "United States Geological Survey"
       ],
       "nameIdentifiers": [
         {
           "schemeUri": "https://orcid.org",
           "nameIdentifier": "https://orcid.org/0000-0002-6076-9730",
           "nameIdentifierScheme": "ORCID"
         }
       ]
     }
   ],
   "titles": [
     {
       "title": "Remotely sensed data from a reach of the Sacramento River near Glenn, California, used to perform Particle Image Velocimetry (PIV) within the Robot Operating System (ROS)"
     }
   ],
   "publisher": "U.S. Geological Survey",
   "container": {},
   "publicationYear": 2023,
   "subjects": [
     {
       "subject": "hydrology"
     },
     {
       "subject": "remote sensing"
     },
     {
       "subject": "geomorphology"
     },
     {
       "subject": "water resources"
     }
   ],
   "contributors": [],
   "dates": [
     {
       "date": "2023",
       "dateType": "Issued"
     }
   ],
   "language": null,
   "types": {
     "ris": "DATA",
     "bibtex": "misc",
     "citeproc": "dataset",
     "schemaOrg": "Dataset",
     "resourceType": "Dataset",
     "resourceTypeGeneral": "Dataset"
   },
   "relatedIdentifiers": [
     {
       "relationType": "IsCitedBy",
       "relatedIdentifier": "https://doi.org/10.1016/j.softx.2024.101711",
       "relatedIdentifierType": "DOI"
     }
   ],
   "relatedItems": [],
   "sizes": [],
   "formats": [],
   "version": null,
   "rightsList": [],
   "descriptions": [
     {
       "description": "This data release provides an example data set to accompany the manuscript titled "A Robot Operating System (ROS) package for mapping flow fields in rivers via Particle Image Velocimetry (PIV)", submitted to the journal Software X. This ROS *.bag file contains remotely sensed data acquired during an Uncrewed Aircraft System (UAS) flight along a reach of the Sacramento River near Glenn, California, USA, on September 16, 2022. Cooperators on this project include the Intelligent Robotics Group from the National Aeronautics and Space Administration (NASA) Ames Research Center and the National Oceanographic and Atmospheric Administration (NOAA) Southwest Fisheries Science Center.\n\nThe file bag6xs600.bag contains a single topic named "/camera/image_raw" of the standard ROS message type sensor_msgs/Image. The individual messages published on this topic are frames acquired by an Allied Vision Mako G-503C color (RGB) camera at a rate of approximately 4 Hz. This camera was one of several included in an experimental payload designed for measuring streamflow. For this test flight, the payload was deployed from a DJI Matrice M600 hovering approximately 137 m above the river surface. The data are not geo-referenced but the pixel size of the images is approximately 0.078 m.\n\nTo simply view the data, the Foxglove Studio program linked below (https://foxglove.dev/download) provides a convenient platform. To actually read the bag file and perform PIV, please refer to the USGS GitLab repository for the ROSPIV network (https://code.usgs.gov/wma/osd/trivia/-/tree/ROSPIV/ROSPIV?ref_type=heads), which includes a document outlining how to set up ROS on a Windows computer, a user's guide for the ROSPIV network, and a demo script for illustrating its application using the bag file provided in this data release.",
       "descriptionType": "Abstract"
     }
   ],
   "geoLocations": [],
   "fundingReferences": [],
   "url": "https://www.sciencebase.gov/catalog/item/64f8926ed34ed30c205464b7",
   "contentUrl": null,
   "metadataVersion": 2,
   "schemaVersion": "http://datacite.org/schema/kernel-4",
   "source": "mds",
   "isActive": true,
   "state": "findable",
   "reason": null,
   "viewCount": 0,
   "downloadCount": 0,
   "referenceCount": 0,
   "citationCount": 1,
   "partCount": 0,
   "partOfCount": 0,
   "versionCount": 0,
   "versionOfCount": 0,
   "created": "2023-10-30T19:02:13Z",
   "registered": "2023-10-30T19:02:14Z",
   "published": null,
   "updated": "2024-04-02T15:53:11Z"
 },
 "relationships": {
   "client": {
     "data": {
       "id": "usgs.prod",
       "type": "clients"
     }
   }
 },
 "type": "dois"

}

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