Resea ch Ideas and Ou comes 10: e119782
doi: 10.3897/ io.10.e119782
Wo kshop Repo
Repo on he Ma ine Imaging Wo kshop 2022
Ca he ine Bo emans , Jenni e M Du den , Timm Schoening , Emma J. Cu is , Lu he A Adams ,
Alexand a B anzan Albu , Au élien A naubec , Sakina-Do o hée Aya a , Reshma Babu aj , Co inne
Bassin , Mi iam Beck , Ka ha ine T. Bigham , Rachel E. Boschen-Rose , Chad Colle , Ma eo
Con ini , Paulo V.F. Co ea , Ca los Dominguez-Ca ió , Gau ie D ey us , G aeme Duncan , Maxime
Fe e a , Valen in Foulon , A iell F iedman , San osh Gaikwad , Chloe Game , Ad iana Gay án-
Caballe o , Fanny Gi a d , Michela Gius i , Mélissa Hana i-Po ie , Ke y L Howell ,
I yna Hule a a , Kiamuke I iowe , Ch is Jacke , Jan Jansen , Cla issa Ka häuse , Kakani
Ka ija , Maxime Ke nec , Gab iel Kim , Ma celo Visen ini Ki aha a , Daniel Langenkämpe , Tim
Langlois , Nadine Lan e i , Claude Jianping Li , Qi-Ran Li , Pie e-Oli ie Liabo ,
Dhugal Lindsay , Ali Loulidi , Yann Ma con , Simone Ma ini , Ashley Ma anzino , Miquel
Masso -Campos , Ma jolaine Ma abos , Lenaick Meno , Be nabé Mo eno , Ma cus Mo issey ,
Da id Naka h , Tim Na kempe , Monika Neu eld , Ma hias Obs , Ka ine Olu , Alexa
Pa imbelli , F ancesca Paso i , Dominique Pelle ie , Ma gaux Pe hi in , Nils Piechaud ,
Osca Piza o , Au un Pu se , Cla a F. Rod igues , Elena Ceballos Rome o , B ian
Schlining , Yi an Song , Heidi M. Sosik , Ma c Sou isseau , Bas ien Tao mina , Jan Tauche ,
Blai Tho n on , Loïc Van Audenhaege , Cha les on de Meden , Guillaume Wacque , Jack
Williams , Kea Wi ing , Ma in Zu owie z
‡ Uni B es , CNRS, I eme , UMR6197 Biologie e Ecologie des Ecosys èmes ma ins P o onds, Plouzané, F ance
§ Na ional Oceanog aphy Cen e, Sou hamp on, Uni ed Kingdom
| No wegian Uni e si y o Science and Technology, T ondheim, No way
¶ GEOMAR Helmhol z Cen e o Ocean Resea ch, Kiel, Ge many
# Uni e si y o Sou hamp on, Sou hamp on, Uni ed Kingdom
¤ Sou h A ican Na ional Biodi e si y Ins i u e (SANBI), Cape Town, Sou h A ica
« Uni e si y o Vic o ia, Vic o ia, Canada
» I eme , DFO, La Seyne-su -Me , F ance
˄ So bonne Uni e si é, CNRS, IRD, MNHN, Labo a oi e d’Océanog aphie e du Clima : Expé imen a ion e Analyses
Numé iques, LOCEAN-IPSL, Pa is, F ance
˅ Ins i u uni e si ai e de F ance (IUF), Pa is, F ance
¦ Di ision o Elec onics, School o Enginee ing, Cochin Uni e si y o Science and Technology, E nakulam, Ke ala, India
ˀ Schmid Ocean Ins i u e, Palo Al o, CA, Uni ed S a es o Ame ica
ˁ So bonne Uni e si é, CNRS, Labo a oi e d'Océanog aphie de Ville anche, LOV, Ville anche-su -Me , F ance
₵ Na ional Ins i u e o Wa e and A mosphe ic Resea ch (NIWA), Welling on, New Zealand
ℓ School o Biological Sciences, Vic o ia Uni e si y o Welling on, Welling on, New Zealand
₰ Ma ine Di ec o a e o he Sco ish Go e nmen , Abe deen, Uni ed Kingdom
₱ SubC Imaging, New oundland, Canada
₳ I eme , DOI, La Réunion, F ance
₴ Ocean Ne wo ks Canada, Vic o ia, BC, Canada
₣ Ins i u o de In es igação em Ciências do Ma - Okeanos, Uni e sidade dos Aço es, Ho a, Po ugal
₮ FORSSEA Robo ics, Pa is, F ance
₦ Join Na u e Conse a ion Commi ee, Pe e bo ough, Uni ed Kingdom
₭ Lab-STICC, IA & OCEAN, ENIB - Technopôle B es -I oise, Plouzané, F ance
₲ G eybi s Enginee ing, Sydney, Aus alia
‽ Labo a o y o Ben hic Ecological T ai Analysis (L-BETA), CSIR- Na ional Ins i u e o Oceanog aphy, Mumbai, India
‡ §,| ¶ # ¤
« » ˄,˅¦
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‽‽,¶ ˀˀ ₩₩ ₸₸ ‡
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© Bo emans C e al. This is an open access a icle dis ibu ed unde he e ms o he C ea i e Commons A ibu ion License (CC
BY 4.0), which pe mi s un es ic ed use, dis ibu ion, and ep oduc ion in any medium, p o ided he o iginal au ho and sou ce a e
c edi ed.
₩ Uni e si y o Eas Anglia, No wish, Uni ed Kingdom
₸ Ga dline L d., G ea Ya mou h, Uni ed Kingdom
‡‡ Uni e sidad Nacional Au ónoma de México (UNAM), Mexico Ci y, Mexico
§§ Mon e ey Bay Aqua ium Resea ch Ins i u e, Moss Landing, CA, Uni ed S a es o Ame ica
|| Is i u o Supe io e pe la P o ezione e la Rice ca Ambien ale (ISPRA), Roma, I aly
¶¶ Uni e si y o Plymou h, Plymou h, Uni ed Kingdom
## Facul y o Physical, Ma hema ical and Na u al Sciences o Szczecin uni e si y, Szczecin, Poland
¤¤ Fede al Uni e si y o Pe oleum Resou ces E u un, Del a S a e, Nige ia
«« CSIRO, Hoba , Aus alia
»» Aus alian Cen e o Excellence in An a c ic Science, Uni e si y o Tasmania, Hoba , Aus alia
˄˄ Woods Hole Oceanog aphic Ins i u ion, Woods Hole, MA, Uni ed S a es o Ame ica
˅˅ Ins i u Uni e si ai e Eu opéen de la Me (IUEM) - Technopôle B es I oise, Plouzané, F ance
¦¦ Uni e sidade de São Paulo, São Sebas ião, B azil
ˀˀ Biele eld Uni e si y, Biele eld, Ge many
ˁˁ Uni e si y o Wes e n Aus alia, Pe h, Aus alia
₵₵ I eme , RDT, Plouzané, F ance
ℓℓ Shenzhen Ins i u e o Ad anced Technology, Chinese Academy o Sciences, Shenzhen, China
₰₰ INNOVICES SARL, Boulogne Billancou , F ance
₱₱ I eme , DYNECO/LEBCO, Plouzané, F ance
₳₳ Japan Agency o Ma ine-Ea h Science and Technology, Yokosuka, Japan
₴₴ Geoscience Labo a o y, Facul y o Sciences Ain Chock, Uni e si y Hassan II, Casablanca, Mo occo
₣₣ MARUM – Cen e o Ma ine En i onmen al Sciences, Uni e si y o B emen, B emen, Ge many
₮₮ CNR, ISTITUTO DI SCIENZE MARINE, Le ici, I aly
₦₦ Uni e si y Co po a ion o A mosphe ic Resea ch, NOAA Ocean Explo a ion, Fo Laude dale, FL, Uni ed S a es o Ame ica
₭₭ Depa men o Ci il, Ma i ime and En i onmen al Enginee ing Facul y o Enginee ing and Physical Science, Uni e si y
o
Sou hamp on, Sou hamp on, Uni ed Kingdom
₲₲ Ma ine Ecology Depa men , Ins i u e o Oceanology Polish Academy o Sciences, Sopo , Poland
‽‽ Kiel Uni e si y, Kiel, Ge many
₩₩ Dalhousie Uni e si y, Depa men o Oceanog aphy, Hali ax, NS, Canada
₸₸ Gö ebo g Uni e si y, Go henbu g, Sweden
‡‡‡ Ryan Ins i u e & School o Na u al Sciences, Uni e si y o Galway, Galway, I eland
§§§ Ma ine Biology Labo a o y, Ghen Uni e si y, Gen , Belgium
||| I eme , UMR DECOD, HALGO, LTBH, Lo ien , F ance
¶¶¶ LOCEAN, UMR 7159, SU-CNRS-IRD-MNHN ; So bonne Uni e si é, Pa is, F ance
### Ins i u e o Ma ine Resea ch, Be gen, No way
¤¤¤ No wegian Uni e si y o Science and Technology (NTNU), T ondheim, No way
««« Uni e si y o Sydney, Sydney, Aus alia
»»» Al ed Wegene Ins i u e, B eme ha en, Ge many
˄˄˄ Cen e o En i onmen al and Ma ine S udies (CESAM), Depa men o Biology, Uni e si y o A ei o, A ei o, Po ugal
˅˅˅ Depa men o Ma ine Chemis y and Geochemis y, Woods Hole Oceanog aphic Ins i u ion, Woods Hole, MA, Uni ed
S a es o Ame ica
¦¦¦ Depa men o Applied Physics II, Uni e si y o Se illa, ETSIE, Se ille, Spain
ˀˀˀ I eme , DYNECO, Plouzané, F ance
ˁˁˁ Uni e si y o Kwazulu-Na al, Wes ille, Sou h A ica
₵₵₵ I eme , Uni é Li o al, Labo a oi e En i onnemen e Ressou ces, Boulogne-su -me , F ance
2Bo emans C e al
Re iewable 1
Co esponding au ho : Ca he ine Bo emans (ca he ine.bo emans@i eme . )
Recei ed: 29 Jan 2024 | Published: 18 Ma 2024
Ci a ion: Bo emans C, Du den J, Schoening T, Cu is EJ, Adams L, B anzan Albu A, A naubec A, Aya a S-D,
Babu aj R, Bassin C, Beck M, Bigham KT, Boschen-Rose RE, Colle C, Con ini M, Co ea PVF, Dominguez-
Ca ió C, D ey us G, Duncan G, Fe e a M, Foulon V, F iedman A, Gaikwad S, Game C, Gay án-Caballe o A,
Gi a d F, Gius i M, Hana i-Po ie M, Howell K, Hule a a I, I iowe K, Jacke C, Jansen J, Ka häuse C, Ka ija K,
Ke nec M, Kim G, Ki aha a M, Langenkämpe D, Langlois T, Lan e i N, Jianping Li C, Li Q-R, Liabo P-O,
Lindsay D, Loulidi A, Ma con Y, Ma ini S, Ma anzino A, Masso -Campos M, Ma abos M, Meno L, Mo eno B,
Mo issey M, Naka h D, Na kempe T, Neu eld M, Obs M, Olu K, Pa imbelli A, Paso i F, Pelle ie D, Pe hi in M,
Piechaud N, Piza o O, Pu se A, Rod igues CF, Ceballos Rome o E, Schlining B, Song Y, Sosik HM,
Sou isseau M, Tao mina B, Tauche J, Tho n on B, Van Audenhaege L, on de Meden C, Wacque G, Williams
J, Wi ing K, Zu owie z M (2024) Repo on he Ma ine Imaging Wo kshop 2022. Resea ch Ideas and Ou comes
10: e119782. h ps://doi.o g/10.3897/ io.10.e119782
Abs ac
Imaging is inc easingly used o cap u e in o ma ion on he ma ine en i onmen hanks o
he imp o emen s in imaging equipmen , de ices o ca ying came as and da a s o age in
ecen yea s. In ha con ex , biologis s, geologis s, compu e specialis s and end-use s
mus ga he o discuss he me hods and p ocedu es o op imising he quali y and quan i y
o da a collec ed om images. The 4 Ma ine Imaging Wo kshop was o ganised om 3-6
Oc obe 2022 in B es (F ance) in a hyb id mode. Mo e han a hund ed pa icipan s we e
welcomed in pe son and abou 80 people a ended he online sessions. The wo kshop was
o ganised in a single plena y session o p esen a ions ollowed by discussion sessions.
These we e based on dynamic polls and open ques ions ha allowed eco ding o he
imaging communi y’s cu en and u u e ideas. In addi ion, a whole day was dedica ed o
p ac ical sessions on image analysis, da a s anda disa ion and communica ion ools. The
o ma o his edi ion allowed he pa icipa ion o a wide communi y, including lowe -
income coun ies, ea ly ca ee scien is s, all wo king on labo a o y, ben hic and pelagic
imaging.
This a icle summa ises he opics add essed du ing he wo kshop, pa icula ly he
ou comes o he discussion sessions o u u e e e ence and o make he wo kshop esul s
a ailable o he open public.
Keywo ds
pho og aphy, me hod de elopmen , unde wa e , pelagic, ben hic, op ical imaging, ideo,
ocean obse a ion, emo e sensing, compu e ision, image, scien i ic communi y
h
Repo on he Ma ine Imaging Wo kshop 2022 3
Da e and place
The Ma ine Imaging Wo kshop 2022 was held a he Océanopolis in B es , F ance om 3 -
6 Oc obe 2022.
Lis o pa icipan s
The pa icipan s who wished o con ibu e o his wo kshop epo appea in he au ho ’s
lis . Please see Fig. 1 o a g oup pho o o he in-pe son pa icipan s.
In oduc ion
Ma ine imaging con inues o g ow in popula i y as a me hod o in es iga ing and
moni o ing ma ine en i onmen s. The Ma ine Imaging Wo kshop 2022 was he ou h
edi ion o he wo kshop ha was p e iously held in Sou hamp on, UK (2014; Du den e al.
(2016)), Kiel, Ge many (2017; Schoening e al. (2017)) and Vic o ia, Canada (2019). Since
he las Ma ine Imaging Wo kshop, se e al na ional and in e na ional ini ia i es ela ed o
subse s o ma ine imaging me hods ha e begun, wi h c osso e s o pa icipan s. The Big
Pic u e (Golding e al. 2021) is a UK conso ium ocused on seabed communi y moni o ing
using pho og aphy, including esea ch, go e nmen agencies and consul ancies. The
Qua e A wo kshop (unpubl. da a) was a pa ne ship be ween F ench and Aus alian
academic and go e nmen esea che s ha also ocused on me hods o seabed habi a
moni o ing. Digi al wins o en i onmen al sys ems (Baue e al. 2021) a e also likely o
inco po a e ma ine imaging soon.
Figu e 1.
In-pe son pa icipan s o he Ma ine Imaging Wo kshop 2022 (pho o c edi : Oli ie Dugo nay,
I eme ).
4Bo emans C e al
Aims o he wo kshop
The Ma ine Imaging Wo kshop aims o b ing oge he a mul idisciplina y g oup o ma ine
scien is s, enginee s, compu e scien is s and use s o p esen and discuss he la es
de elopmen s in ma ine imaging me hodology. These de elopmen s we e p esen ed by
pa icipan s h ough alks, pos e s and hands-on sessions. Keyno e alks we e gi en by D .
Edie Widde (“Imaging Deep-Sea Bioluminescence”) and P o . Ch is Lin o (“Pas , p esen
and Fu u e o Online Ci izen Science. A View om he Zooni e se”). The wo kshop
ea u ed discussion sessions o os e new ideas and collabo a ions and o challenge
pa icipan s o conside he ends in ma ine imaging and iden i y gaps.
In 2022, he wo kshop was deli e ed in a hyb id o ma o he i s ime, wi h bo h in-
pe son and online pa icipa ion. Online pa icipan s could wa ch alks ia a YouTube
pla o m and p esen alks using Zoom o asynch onously, by submi ing a eco ded alk.
They could ask ques ions by yping hem on a cha box wi hin he You ube channel. The
onsi e co-chai eleased online ques ions o he p esen e a he end o his alk, allowing
him/he o also answe online ques ions li e. Soon a e he li e alks, eco ded e sions o
hese alks we e made a ailable on ha same channel on eplay un il 31 Oc obe o a oid
ime zone con lic . All pos e s ( om bo h online and onsi e p esen e s) we e b oadcas ed
as ideos on he same channels du ing co ee and lunch b eaks. All pos e s we e made
a ailable on hose channels on eplay un il 31 Oc obe .
As he ou h edi ion o he se ies, he Ma ine Imaging Wo kshop 2022 aimed o inc ease
he di e si y o pa icipan s o e p e ious wo kshops in wo impo an ways. The i s was
o inc ease he global each o he wo kshop, pa icula ly o include pa icipan s om lowe -
and middle-income coun ies. This aim was suppo ed by he a ailabili y o online
pa icipa ion and bu sa ies o e ed o a endance. The second was o b oaden he
discussion o include wide applica ions o ma ine imaging. P e ious Ma ine Imaging
Wo kshops ocused on ben hic en i onmen s, al hough many aspec s o ma ine imaging
a e b oadly applicable. The 2022 wo kshop aimed o include mo e pa icipan s ocused on
pelagic applica ions o ma ine imaging.
Key ou comes and discussions
A endance and scope
The wo kshop consis ed o 188 pa icipan s: 110 in pe son and 78 online. Mo e han 25%
o he pa icipan s (48 indi iduals) iden i ied as ea ly ca ee esea che s, 13 o which
ecei ed bu sa ies o a end. Pa icipan s wo ked p ima ily in academia/ esea ch (167).
The es included 17 pa icipan s om indus y, h ee om go e nmen /policy and one om
consul ancies. In-pe son pa icipan s included 50 om he hos coun y, 35 om he es o
Eu ope, 17 om he Ame icas, ou om Asia and ou om A ica. Online pa icipan s
numbe ed 44 om Eu ope, 22 om Ame icas, ou om Asia, six om Oceania and wo
om A ica.
Repo on he Ma ine Imaging Wo kshop 2022 5
A o al o 84 abs ac s p epa ed by 358 au ho s we e accep ed, wi h 51 alks and 33
pos e s p esen ed. Con ibu ions we e g ouped in o he ollowing i e hemed sessions:
• Session 1: Pla o ms, op ical senso s and (unde wa e ) image acquisi ion,
calib a ion and p ep ocessing (8 alks, 7 pos e s);
• Session 2: Tools o image anno a ion (8 alks, 5 pos e s);
• Session 3: Au oma ed image p ocessing (9 alks, 9 pos e s);
• Session 4: Quali y con ol, s anda disa ion and sha ing o image y da a (12 alks, 5
pos e s);
• Session 5: Scien i ic ad ancemen s in biology and geology using (unde wa e )
image y da a (14 alks, 7 pos e s);
Discussion session hemes we e mo e o less ela ed o hese session hemes. Hands-on
(in e ac i e) sessions we e conduc ed on anno a ion pla o ms SQUIDLE+ (Williams and
F iedman 2015) and BIIGLE 2.0 (Langenkämpe e al. 2017), o ganism iden i ica ion
SMa TaR-ID (Howell e al. 2019), FAIR da a managemen o image me ada a (Schoening
e al. 2022), p oduc ion o 3D image mosaics (A naubec e al. 2023) and he Imme Sea
Lab i ual eali y p ojec ( an by Maxime Ke nec and Loic Van Audenhaege). All o hese
sessions we e a ailable o in-pe son pa icipan s, wi h a subse also conduc ed in hyb id o
include online pa icipan s.
New discussion session o ma and analysis o o ing
The discussion sessions a e a popula componen o he Ma ine Imaging Wo kshop
acco ding o pas pa icipan eedback. A p e ious wo kshops, discussions we e held in
small g oups, bu , due o he enue space and online pa icipa ion, discussions we e held
in a single g oup in 2022. An elec onic pla o m (Slido) was employed o conduc polling
and eco d discussion ideas and o acili a e o ing o quan i y suppo o hose ideas.
Each session had mul iple elec onic ques ions; he i s ques ions we e open polls wi h
mul iple choice answe s and he second ques ions we e open-ended. In esponse o an
open-ended ques ion, pa icipan s could sugges ideas and o e o o he ideas while
polling was open; ideas sugges ed ea ly in he session we e likely o ecei e mo e o es
han hose sugges ed la e . The elec onic ques ions and o es we e used as p omp s o
e bal discussion by in pe son pa icipan s. This new o ma enabled online pa icipan s o
con ibu e h ough he polls, bu mean ha e bal discussion by in-pe son pa icipan s was
subs an ially educed compa ed o p e ious wo kshops.
Fo each discussion heme, he esul s o polls a e p esen ed i s , ollowed by summa ies
o he eco ded esponses (ideas and o es) o each discussion/open-ended ques ion. To
summa ise he o ing da a, spu ious commen s (e.g. ‘ es ing online pla o m’, ‘Hello’) we e
emo ed, hen he emaining esponses we e assessed as ollows. The o al numbe o
sugges ed ideas and o es we e epo ed. Sugges ed ideas we e also g ouped in o
common hemes, wi h o es agg ega ed. The mos popula sugges ions (e.g. >10 o es),
whe e no ewo hy o no ep esen ed by he common hemes, we e no ed. Raw da a a e
p esen ed in Suppl. ma e ial 1.
6Bo emans C e al
A o al o 11 ques ions we e asked in he polls, wi h an a e age o i e mul iple-choice
esponses pe ques ion. The numbe o o es pe ques ion anged om 52 o 88
(a i hme ic mean 71 o 0.38 pe pa icipan ). A o al o 14 open-ended ques ions we e
asked ac oss he i e discussion sessions, p omp ing 411 ideas submi ed and 1903 o es.
The numbe o ideas pe ques ion anged om 13 o 45 (a i hme ic mean 29), while he
numbe o o es pe ques ion anged om 71 o 194 (a i hme ic mean 126 o 0.67 pe
pa icipan ).
This elec onic o ing acili a ed he in eg a ion o online pa icipan s in o he discussion
along wi h in-pe son a endees and he quan i ica ion o s eng h o opinion/ eeling abou
pa icula ideas. I may also ha e made he discussion mo e equi able, by educing he
dominance o some oices. Howe e , i educed he back-and- o h discussion ha
cha ac e ised p e ious wo kshops, which mean ha ideas we e no de eloped beyond
sho poin s.
Session 1: Ex en o imaging
Polling
See Fig. 2 o polling esul s o ques ion 1: "Wha a e he ba ie s o inc easing he ex en
o imaging he oceans?". See Fig. 3 o polling esul s o ques ion 2: "Ha e you used
c owd-sou ced ma ine image da a?". See Fig. 4 o polling esul s o ques ion 3: "Which
a ea/ olume does all image da a you ha e e e wo ked wi h co e ?".
Figu e 2.
Polling esul s o discussion session 1 "Ex en o imaging", ques ion 1: "Wha a e he ba ie s
o inc easing he ex en o imaging he oceans?".
Repo on he Ma ine Imaging Wo kshop 2022 7
How can we inc ease he spa ial/ empo al/ esolu ion ex en o imaging in he
oceans?
A o al o 37 ideas we e submi ed, wi h 184 o es. The mos popula g oup o ideas was
o da a sha ing, wi h 10 ideas and 87 o es. The ideas in ol ed acili a ing sha ed
Figu e 3.
Polling esul s o discussion session 1 "Ex en o imaging", ques ion 2: "Ha e you used c owd-
sou ced ma ine image da a?".
Figu e 4.
Polling esul s o discussion session 1 "Ex en o imaging", ques ion 3: "Which a ea/ olume
does all image da a you ha e e e wo ked wi h co e ?".
8Bo emans C e al
da ase s suppo ed by so wa e, ools o combining mul iple da a sou ces and da a
agg ega o s o b oke s be ween eposi o ies. Th ee o he ou mos popula indi idual
ideas (> 10 o es each) we e ela ed o sha ing: “sha ed da ase s” (34 o es), “suppo ing
a pe manen ne wo k o acili a e da a, ech and expe sha ing” (16 o es), “sha e
collec ed da a” (15 o es). Ideas ela ed o equipmen imp o emen s we e also popula (10
ideas wi h 39 o es), including new echnology de elopmen (e.g. ARGOs o sea loo
imaging, echnology o educe cos s), en al o imaging equipmen , mo e use o
au onomous pla o ms and making in o ma ion abou imaging sys ems mo e widely
a ailable. Collabo a ion and pa ne ship we e hemes o 8 ideas wi h 24 o es, including
inc eased collabo a ion be ween scien is s and wi h indus y and cen alising
unde s anding o knowledge gaps. The concep o da a s anda ds was he heme o 3
ideas wi h 21 o es and he ou h mos popula indi idual idea “S anda ds (e.g. i do!)” (12
o es). O he ideas ou side hese g oupings (6 ideas wi h 13 o es) we e ocused on use -
iendly au oma ed image analysis so wa e (and wi h use - iendly in e aces), benchma ks
and g ound- u hing/ alida ion, inc eased use o acous ic da a o pho o su ey design and
capaci y building.
Wha ole can capaci y building and ci izen science ha e in inc easing he
ex en ?
A o al o 30 ideas we e submi ed, wi h 161 o es. Using capaci y building and ci izen
science o gene a e anno a ions was by a he mos popula heme, wi h 17 ideas and 110
o es. The ideas (la gely o ci izen science) included gene a ing anno a ions om mo e
images, om exis ing and new da ase s and o asks no equi ing speciali y knowledge
(e.g. inding majo e en s, li e o high le el axonomic g oups). Capaci y building and
ci izen science we e also seen as way o build public in e es and go e nmen unding o
ma ine science (6 ideas, 36 o es). O he ideas ou side hese wo main g oups (7 ideas, 16
o es) included linking o ele ision shows o ci izen scien is s, engaging he compu e
science communi y and inc easing he global ex en o obse a ions.
Whe e should we go and image (mo e)?
A o al o 45 ideas we e submi ed, wi h 184 o es. “E e ywhe e and anywhe e” was he
mos popula g oup o ideas, exp essed as 6 ideas wi h 68 o es, including he need o
epea ed measu emen s/moni o ing. Speci ic a eas we e sugges ed as 13 ideas, wi h 40
o es, including he A c ic/An a c ic, Indian/A lan ic/Sou he n Oceans, Mekong Ri e ,
A ican con inen al wa e s and sea loo beyond na ional ju isdic ion. The pelagic ealm was
he subjec o 4 sugges ed ideas ha ga ne ed 24 o es, including he coas al, midwa e
and deep pelagic. Concep s o selec ing loca ions, based on need o p essing
en i onmen al easons, we e submi ed as 6 ideas wi h 18 o es, including ele ance o
clima e change, biodi e si y and seabed mining. Fi e ideas ela ed o ocean ea u es, wi h
11 o es, such as seamoun s, enches and canyons, deep-sea en pe iphe ies and
oxygen minimum zones. A wide a ie y o ideas we e submi ed ha de ied g ouping (11
ideas, 27 o es), including shallow and deep wa e , lakes, a i icial s uc u es and e en he
ex a e es ial oceans o icy moons!
Repo on he Ma ine Imaging Wo kshop 2022 9
Session 5: Fu u e o ma ine imaging
Polling
See Fig. 12 o polling esul s o ques ion 1: "Whe e ha e you seen he bigges p og ess o
ma ine imaging du ing his wo kshop?.
Wha ole can ou communi y play o ma ine imaging o e he nex en
yea s?
This ques ion p omp ed high engagemen , wi h he mos ideas o he session (33) and he
mos o es o any open-ended ques ion (194). By a he mos popula g oup o ideas (14
ideas, 118 o es) ela ed o collabo a ion, including sha ing ideas and expe ise and
sha ing/ alida ing each o he ’s da a and wo k lows. A second g oup o ideas (8 ideas, 48
o es) sugges ed ha he g oup could con ibu e o he echnical aspec s o me hod
de elopmen , including s anda disa ion (44 o es). Con inued hos ing o wo kshops,
including bo h he Ma ine Imaging Wo kshop and echnical wo kshops o so wa e ools
was ano he g oup o ideas (2 ideas, 17 o es). Ano he g oup o ideas (7 ideas, 4 o es)
ela ed o engagemen wi h o he s, including wi h o he scien i ic ields and da a ypes and
wi h o he g oups o people (e.g. hose local o s udy si es, school pupils, gene al
audience). A miscellaneous idea included s a ing a jou nal o jou nal heme on ma ine
imaging echniques.
Figu e 12.
Polling esul s o discussion session 5 "Fu u e o ma ine imaging", ques ion 1: "Whe e ha e
you seen he bigges p og ess o ma ine imaging du ing his wo kshop?.
16 Bo emans C e al
Whe e a e decisions equi ed ha block ou p og ess in ma ine imaging?
This ques ion p omp ed he leas engagemen o his session: 21 ideas and 90 o es. The
mos popula g oup o ideas (9 ideas, 64 o es) ocused on he need o da a uni ica ion
and s anda ds o bo h image y, me ada a, da a p o enance and models. A ela ed g oup
o ideas (2 ideas, 9 o es) sugges ed uni ica ion o s anda disa ion o so wa e and
wo k lows. A small g oup (4 ideas, 8 o es) iden i ied unding and cos s as a block.
Miscellaneous ideas included equi ing ins i u ional buy-in and leade ship, de eloping
la ge eams and inc eased in e ope abili y/ es ing o p ocesses o ind blocks.
Whe e do you see ma ine imaging en yea s om now?
This ques ion ga ne ed 32 ideas and 144 o es. Th ee ideas (29 o es) sugges ed ha we
would s ill be wo king on some cu en challenges in ma ine imaging, including s ill alking
abou s anda disa ion (24 o es), s uggling wi h image s o age and mul iscale imaging.
Many ideas sugges ed signi ican p og ess using AI (7 ideas, 27 o es), including i s
ubiqui ous use o anno a ion and inc eased accu acy and he sugges ion o ull sen ience.
Ano he g oup o ideas ocused on inc ease imaging (4 ideas, 10 o es), including
inc eased use o au oma ed unde wa e ehicles, inc eased image esolu ion and ha ing
cap u ed > 100 billion images. En husiasm o he u he de elopmen o he ma ine
imaging communi y was e idence om he 6 ideas and 41 o es cas , including mo e
connec ion be ween compu e scien is s/enginee s/biologis s (22 o es) and inc easing he
communi y di e si y mo e gene ally (19 o es). Miscellaneous ideas included de eloping
low-cos imaging solu ions and inc eased di e si y o unding sou ces, inc eased
connec ion wi h he public and o he applica ions o ma ine imaging (mo ing away om
biodi e si y applica ions).
Conclusions
The Ma ine Imaging Wo kshop 2022 was a success ul and ui ul edi ion ga he ing expe s
o he ma ine image y ield and allowing a b oad audience o be included (e.g. s uden s
and young esea che s). Discussions and hands-on sessions we e highly app ecia ed and
bene i ed o bo h online and on-si e pa icipan s. The opics o he wo kshop co e ed
me hods and echnologies o all ypes o unde wa e op ical imaging in pelagic and
ben hic en i onmen s, p o iding knowledge and moni o ing solu ions o ma ine
ecosys ems. This e en boos ed exchanges be ween in e na ional scien is s in he ield o
ma ine imaging. The collabo a ions ini ia ed o s eng hened will undoub ully gi e bi h o
mo e ambi ious p ojec s in he nea u u e.
We look o wa d o econ ening he esea ch and enginee ing communi y a he nex
imaging wo kshop.
Repo on he Ma ine Imaging Wo kshop 2022 17
Acknowledgemen s
We hank IFREMER o hos ing he wo kshop and he local and scien i ic o ganising
commi ees o hei e o s in p epa ing he e en . We hank he e en sponso s:
FORSSEA ROBOTICS, Schmid Ocean Ins i u e, ISblue, SubC Imaging, In e na ional
Seabed Au ho i y, Dépa emen du Finis è e, B es Me opole and ZEISS. We hank all
pa icipan s who con ibu ed o he e en and o his a icle h ough hei ac i e pa icipa ion
du ing he wo kshop discussion sessions. We hank Océanopolis and Guy Bescond's eam
o hei high-quali y logis ical and echnical se ices.
Hos ing ins i u ion
IFREMER
Au ho con ibu ions
All au ho s con ibu ed o wo kshop discussions and w i ing his epo .
Con lic s o in e es
The au ho s ha e decla ed ha no compe ing in e es s exis .
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Supplemen a y ma e ial
Suppl. ma e ial 1: Discussion ques ion esponse da a
Au ho s: Ma ine Imaging Wo kshop pa icipan s
Da a ype: Ideas and polls esul s
B ie desc ip ion: Expo s o Slido iles a e polling and Q&A sessions.
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Repo on he Ma ine Imaging Wo kshop 2022 19
