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    Review of 'BoatNet: Automated Small Boat Composition Detection using Deep Learning on Satellite Imagery'

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    BoatNet: Automated Small Boat Composition Detection using Deep Learning on Satellite ImageryCrossref
    A model titled BoatNet for quantifying small boat fleet emission inventories is introduced.
    Average rating:
        Rated 4.5 of 5.
    Level of importance:
        Rated 4 of 5.
    Level of validity:
        Rated 4 of 5.
    Level of completeness:
        Rated 4 of 5.
    Level of comprehensibility:
        Rated 5 of 5.
    Competing interests:
    None

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    BoatNet: Automated Small Boat Composition Detection using Deep Learning on Satellite Imagery

    Tracking and measuring national carbon footprints is one of the keys to achieving the ambitious goals set by countries. According to statistics, more than 10% of global transportation carbon emissions result from shipping. However, accurate tracking of the emissions of the small boat segment is not well established. Past research has begun to look into the role played by small boat fleets in terms of Greenhouse Gases (GHG), but this either relies on high-level technological and operational assumptions or the installation of Global navigation satellite system (GNSS) sensors to understand how this vessel class behaves. This research is undertaken mainly in relation to fishing and recreational boats. With the advent of open-access satellite imagery and its ever-increasing resolution, it can support innovative methodologies that could eventually lead to the quantification of GHG emissions. This work used deep learning algorithms to detect small boats in three cities in the Gulf of California in Mexico. The work produced a methodology named BoatNet that can detect, measure and classify small boats with leisure boats and fishing boats even under low-resolution and blurry satellite images, achieving an accuracy of 93.9% with a precision of 74.0%. Future work should focus on attributing a boat activity to fuel consumption and operational profile to estimate small boat GHG emissions in any given region. The data curated and produced in this study is freely available at https://github.com/theiresearch/BoatNet.
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      Review information

      10.14293/S2199-1006.1.SOR-EARTH.ADNS0R.v1.RKPWLF
      This work has been published open access under Creative Commons Attribution License CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com.

      Earth & Environmental sciences,Computer science,Statistics,Geosciences
      Small boats activity,Object Detection,Statistics,Climate Change,Energy,Deep Learning,Transfer Learning,Climate,Policy and law,The Environment,Sustainable development
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      The authors adequatly addressed or responded to all given comments and suggestions. 

      I have no further recommendations and agree to release this version for publication.

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