TY - JOUR
T1 - Drones for litter mapping
T2 - An inter-operator concordance test in marking beached items on aerial images
AU - Andriolo, Umberto
AU - Gonçalves, Gil
AU - Rangel-Buitrago, Nelson
AU - Paterni, Marco
AU - Bessa, Filipa
AU - Gonçalves, Luisa M. S.
AU - Sobral, Paula
AU - Bini, Monica
AU - Duarte, Diogo
AU - Fontán-Bouzas, Ángela
AU - Gonçalves, Diogo
AU - Kataoka, Tomoya
AU - Luppichini, Marco
AU - Pinto, Luis
AU - Topouzelis, Konstantinos
AU - Vélez-Mendoza, Anubis
AU - Merlino, Silvia
N1 - UIDB/00308/2020
PTDC/EAM-REM/30324/2017
IT057-18-7252
UIDB/04292/2020
UIDB/00324/2020
ED481D2019/028
UIDP/50017/2020
UIDB/50017/2020
UI0308/UArribaS.1/2020
UI0308-D.Remota1/2020
UIDB/00308/2020
JPNP18016
2020-5211-041
Sem PDF conforme despacho.
PY - 2021/8
Y1 - 2021/8
N2 - 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.
AB - 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.
KW - Coastal pollution
KW - Plastics
KW - Remote sensing
KW - Unmanned aerial vehicle (UAV)
KW - Waste management
UR - http://www.scopus.com/inward/record.url?scp=85106577125&partnerID=8YFLogxK
U2 - 10.1016/j.marpolbul.2021.112542
DO - 10.1016/j.marpolbul.2021.112542
M3 - Article
C2 - 34052588
AN - SCOPUS:85106577125
SN - 0025-326X
VL - 169
JO - Marine Pollution Bulletin
JF - Marine Pollution Bulletin
M1 - 112542
ER -
