Literature DB >> 30503448

Monitoring of beach litter by automatic interpretation of unmanned aerial vehicle images using the segmentation threshold method.

Zhongcong Bao1, Jinming Sha2, Xiaomei Li3, Terefe Hanchiso4, Eshetu Shifaw5.   

Abstract

This study was aimed at monitoring beach litter using an unmanned aerial vehicle (UAV) in the coastal city of Fuzhou, China. The data analysis shows that the optical images obtained by digital cameras on the UAV can help to identify and monitor beach litter using remote sensing and GIS technologies. The threshold method can effectively segment the UAV image in the beach area. It is useful for quickly monitoring the distribution of beach litter in the area of interest, and hence it can help to provide effective technical support for the investigation and assessment of coastal beach litter.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Keywords:  Beach litter; Coastal pollution; Image segmentation; Remote sensing; Threshold method; UAV

Mesh:

Year:  2018        PMID: 30503448     DOI: 10.1016/j.marpolbul.2018.08.009

Source DB:  PubMed          Journal:  Mar Pollut Bull        ISSN: 0025-326X            Impact factor:   5.553


  2 in total

1.  MARIDA: A benchmark for Marine Debris detection from Sentinel-2 remote sensing data.

Authors:  Katerina Kikaki; Ioannis Kakogeorgiou; Paraskevi Mikeli; Dionysios E Raitsos; Konstantinos Karantzalos
Journal:  PLoS One       Date:  2022-01-07       Impact factor: 3.240

2.  Quantification of floating riverine macro-debris transport using an image processing approach.

Authors:  Tomoya Kataoka; Yasuo Nihei
Journal:  Sci Rep       Date:  2020-02-10       Impact factor: 4.379

  2 in total

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