{
    "tag": 11990,
    "title": "GNSS locations of lakebed images collected near Dollar Point, Lake Tahoe, CA, March 10 and 11, 2021",
    "pubdate": "20210930",
    "sername": null,
    "series_name": null,
    "issue": "DOI:10.5066\/P9V44ZYS",
    "publish": null,
    "publisher_name": null,
    "onlink": "https:\/\/cmgds.marine.usgs.gov\/catalog\/pcmsc\/DataReleases\/CMGDS_DR_tool\/DR_P9V44ZYS\/2021-607-FA_Image_Locations_metadata.faq.html",
    "format": null,
    "email": null,
    "descript": "This text file (2021-607-FA_Image_Locations.txt) provides the GNSS antenna location for underwater images collected near Dollar Point, Lake Tahoe, CA, using a recently developed towed-surface vehicle with multiple downward-looking underwater cameras. The GNSS antenna location for the time of each image capture is presented with greater precision than is stored in the individual image\u2019s EXIF header due to decimal place limitations of the EXIF format.",
    "lang": null,
    "journal": null,
    "pwid": null,
    "originator": [
        {
            "name": "Hatcher, Gerald A.",
            "role": "Author"
        },
        {
            "name": "Warrick, Jonathan A.",
            "role": "Author"
        },
        {
            "name": "Kranenburg, Christine J.",
            "role": "Author"
        },
        {
            "name": "Dal Ferro, Peter",
            "role": "Author"
        }
    ],
    "index_term": [
        {
            "thcode": 2,
            "code": "474",
            "name": "geospatial datasets",
            "scope": "Collections of related digital information that are geographically referenced."
        },
        {
            "thcode": 2,
            "code": "2090",
            "name": "lakebed characteristics",
            "scope": "Characteristics of the bottom of inland bodies of water."
        },
        {
            "thcode": 2,
            "code": "981",
            "name": "remote sensing",
            "scope": "Acquiring information about a natural feature or phenomenon, such as the Earth's surface, without actually being in contact with it. USGS remote sensing is usually carried out with airborne or spaceborne sensors or cameras."
        },
        {
            "thcode": 2,
            "code": "2265",
            "name": "structure from motion",
            "scope": "Mathematical analysis, using photogrammetric principles, of multiple images that depict the same subject from different angles to derive geometrical information and relationships in three-dimensional space that are not inherent in any single image. Often used for deriving land elevation or large scale orthoimagery from a collection of aerial photographs."
        },
        {
            "thcode": 2,
            "code": "1281",
            "name": "visible light imaging",
            "scope": "Remote sensing methods using electromagnetic radiation which is visible to the human eye to react with the coating on a photographic plate or film."
        },
        {
            "thcode": 15,
            "code": "012",
            "name": "inlandWaters",
            "scope": "Inland water features, drainage systems and characteristics, for example rivers and glaciers, salt lakes, water utilization plans, dams, currents, floods and flood hazards, water quality, hydrographic charts, watersheds, wetlands, hydrography"
        },
        {
            "thcode": 23,
            "code": "3",
            "name": "Distributions",
            "scope": "Locations or patterns of a feature of interest across space and (or) time. These data can include point data, lines, polygons, and temporal data at any scale relevant to CMSP and can be produced by observation, interpolation, or modeling. Distributions can also include maps or statistics of climatology, the environmental values that are expected to be observed at the present time."
        },
        {
            "thcode": 23,
            "code": "27",
            "name": "Habitat",
            "scope": "Habitat includes data that describe repeatable combinations of biota and associated chemical, physical, or geological features in a distinct place, which, as in the CMECS Biotic Component, generally are named for the dominant taxa living there. Habitat also includes biotopes in accordance with CMECS. Examples include seagrass beds, deep-water corals, benthos, nekton, plankton, mussel beds. Distributions for Habitat data subject types include records of biotic associations, habitats, or biotopes obtained through direct observation, imagery, collection, or other methods; Distributions also include biotope maps, predicted maps of present-day habitats (for example, the Northwest Atlantic Marine Ecoregional Assessment, Mapping European Seabed Habitats), and other compilations or interpretations from observed data. Assessments include ecological valuation indices, presence, quantity (hectares), or percentage of identified high-value habitats; other purpose-driven, regionally-specific indicators of ecological value; classifications of areas as critical habitat; ecological services models; evaluations of habitat condition; and place-based indices of susceptibility and vulnerability to disturbance. Predictions are the results of models or projections of future distributions, values, or impacts; anticipated changes produced by natural and human processes; future projections of cumulative impacts of single or multiple stressors; and scenario-testing habitat loss\/gain models and predictions of related ecological or economic effects under different management strategies."
        },
        {
            "thcode": 61,
            "code": "417",
            "name": "Global Positioning System (GPS) observations",
            "scope": "the use of satellite signals from the Global Positioning System to determine the precise location of a terrestrial receiver."
        },
        {
            "thcode": 61,
            "code": "145",
            "name": "lake bed",
            "scope": "the bottom of a lake."
        }
    ],
    "place_term": [],
    "image": [],
    "fan": [
        "2021-607-FA"
    ]
}