4.7 Article

Drones for litter mapping: An inter-operator concordance test in marking beached items on aerial images

期刊

MARINE POLLUTION BULLETIN
卷 169, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.marpolbul.2021.112542

关键词

Plastics; Unmanned aerial vehicle (UAV); Remote sensing; Waste management; Coastal pollution

资金

  1. Portuguese Foundation for Science and Technology (FCT)
  2. European Regional Development Fund (FEDER) [UIDB/00308/2020, PTDC/EAM-REM/30324/2017]
  3. University of Coimbra [IT057-18-7252]
  4. FCT, I.P. [UIDB/04292/2020]
  5. Centre for Mathematics of the University of Coimbra - Portuguese Government through FCT/MCTES [UIDB/00324/2020]
  6. Xunta de Galicia (Spain) [ED481D2019/028]
  7. FCT/MCTES [UIDP/50017/2020 + UIDB/50017/2020]
  8. Institute for Systems Engineering and Computers at Coimbra (INESC Coimbra) [UI0308/UArribaS.1/2020, UI0308-D.Remota1/2020]
  9. Portuguese Foundation for Science and Technology (FCT) through national funds (PIDDAC) [UIDB/00308/2020]
  10. New Energy and Industrial Technology Development Organization (NEDO) [JPNP18016]
  11. River Fund of the River Foundation, Japan [2020-5211-041]
  12. Fundação para a Ciência e a Tecnologia [PTDC/EAM-REM/30324/2017] Funding Source: FCT

向作者/读者索取更多资源

This study showed that for detailed categorization of litter in the environment, manual image screening should be conducted by experienced and local operators to achieve higher consistency. This provides insights for future operational improvements and optimizations of UAS-based image analysis to survey environmental pollution.
Unmanned aerial systems (UAS, aka drones) are being used to map macro-litter on the environment. Sixteen qualified researchers (operators), with different expertise and nationalities, were invited to identify, mark and categorize the litter items (manual image screening, MS) on three UAS images collected at two beaches. The coefficient of concordance (W) among operators varied between 0.5 and 0.7, depending on the litter parameter (type, material and colour) considered. Highest agreement was obtained for the type of items marked on the highest resolution image, among experts in litter surveys (W = 0.86), and within territorial subgroups (W = 0.85). Therefore, for a detailed categorization of litter on the environment, the MS should be performed by experienced and local operators, familiar with the most common type of litter present in the target area. This work provides insights for future operational improvements and optimizations of UAS-based images analysis to survey environmental pollution.

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