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{
    "pk": 62871,
    "title": "Remote Sensing of Primary Producers in the Bay–Delta",
    "subtitle": null,
    "abstract": "Remote-sensing methods are being used to study a growing number of issues in the San Francisco Estuary, such as (1) detecting the optical properties of chlorophyll-a concentrations and dissolved organic matter to assess productivity and the nature of carbon inputs, (2) creating historical records of invasive aquatic vegetation expansion through space and time, (3) identifying origins and expansions of invasions, and (4) supporting models of greenhouse-gas sequestration by expanding restoration projects. Technological capabilities of remote sensing have likewise expanded to include a wide array of opportunities: from boat-mounted sensors, human-operated low-flying planes, and aerial drones, to freely accessible satellite imagery. Growing interest in coordinating these monitoring methods in the name of collaboration and cost-efficiency has led to the creation of diverse expert teams such as the Remote Imagery Collaborative, and monitoring frameworks such as the Interagency Ecological Program Aquatic Vegetation Monitoring Framework and Wetland Regional Monitoring Program. This paper explores the emerging technologies and applications of various methods for studying primary producers, with an emphasis on remote sensing.",
    "language": "en",
    "license": {
        "name": "Creative Commons Attribution 4.0",
        "short_name": "CC BY 4.0",
        "text": "Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.\n\nNo additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.",
        "url": "https://creativecommons.org/licenses/by/4.0"
    },
    "keywords": [
        {
            "word": "remote sensing, satellite, UAS, multispectral, hyperspectral, LiDAR, SAR, primary producers, vegetation, phytoplankton"
        }
    ],
    "section": "Research Article",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/82k2j1s9",
    "frozenauthors": [
        {
            "first_name": "Erin",
            "middle_name": "",
            "last_name": "Hestir",
            "name_suffix": "",
            "institution": "University of California, Merced\nMerced, CA 95343 USA",
            "department": ""
        },
        {
            "first_name": "Iryna",
            "middle_name": "",
            "last_name": "Dronova",
            "name_suffix": "",
            "institution": "University of California, Berkeley\nBerkeley, CA 94720 USA",
            "department": ""
        }
    ],
    "date_submitted": "2023-02-02T14:51:54-05:00",
    "date_accepted": "2023-02-02T14:51:54-05:00",
    "date_published": "2023-02-04T03:00:00-05:00",
    "render_galley": null,
    "galleys": [
        {
            "label": "",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/jmie_sfews/article/62871/galley/48555/download/"
        }
    ]
}