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have improved image quality and will re duce video pro ce ssing time in 2023 A brand new Mapping Station will enable Seattle Aquarium sta and volunteers to extensively train AI mo dels in 2023 Altogether 2022 has b e en a urry of metho ds research development and implementation and we will ad vance this work in 2023 with additional surveys metho ds comparisons AI training and bull kelp habitat suitability analyses We are especial ly grateful to Kathleen Hurley Randy Edwards Jenn Stebbings George Blomberg and Ashley Townes with the Port of Seattle Maritime Environment and Sustainability for providing vessel support and enthusiasm in the eld 1 2 Inconsistent GPS p erformance 2 1 The nature of the issue and our corrective actions We have encountered inconsistent p erformance from WaterLink s Underwater GPS system At times this inconsistency manifests during a single ROV dive as exampled by Fig 1a d which visualizes the Octob er 6 th ROV surveys at Site 1 Magnolia just west of the Elliott Bay Marina Up on pro cessing the ROV telemetry information it b ecame clear that trans ects 1 and 3 were recorded accurately whereas transects 2 and 4 were

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text:
not We worked extensively with a Amund Stenseth a WaterLinked engineer who analyzed WaterLinked diagnostic logs we ge ne rated from Q 4 ROV GPS tests T wo problems b ecome apparent 1 Our acoustic GPS antenna was not b eing placed deep enough in the water the b ottom of the antenna needs to b e 1 m b elow the surface we erroneously only had it a few cm down 2 There may b e a glitch in the software governing the frequency of transmission from our U 1 acoustic transmitter and we mailed the transmitter to WaterLinked in Norway for testing However note that solving 1 ab ove pro duced highly precise tracks and it app ears this 1 m depth issue was the predominate source of error a b c d Figure 1 a Transect 1 showing accurate GPS tracks The red lines are the result of a smo other applied to the raw tracks see here for the co de and an explanation of the smo othing pro cedure b Transect 3 showing accurate GPS tracks c Transect 2 showing inaccurate GPS tracks d Transect 4 showing inaccurate GPS tracks That all b eing said

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text:
given the imp ortance of obtaining consistently accurate and precise G PS co ordinates we have taken several additional steps including At present the GPS com municates with the ROV through a network bridge on the ROV s laptop however we have found this communication to b e at times unreliable We therefore 2 have obtained and are incorp orating a BlueROV2 GPS integration kit which hardwires and will stabilize the connection b etwe en the two In order to plot a map in real time during our dive the GPS system needs access to the internet unfortunately We will therefore obtain a Verizon SIM card for the ROV laptop and via GSM cellular networks the GPS program will b e able to access Lea et maps during our dive s This will provide enhanced navigational capabilitie s that we have thus far not had access to as without internet we interpreted relative p ositioning b etween the acoustic antenna mounted on a vessel do ck and the transmitter on the ROV see Fig 2a vs b for an example of the map overlay vs relative p ositioning The SIM card will enable more precise navigational control such as via

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text:
pre designated or logged in the moment way p oints a b Figure 2 a Lea et map and way p oint functioning available when the GPS via the ROV laptop has inte rnet access b In lieu of a SIM card we view the relative p osition b etween the acoustic receiver the vessel icon and the transm itte r the blue dot We have ordered a second G PS system to accompany our second ROV b oth of which will provide redundancy and for this second system we upgraded from the acoustic antenna to an array of four separate acoustic receive rs These are the same four acoustic receivers that comprise the four pronged acoustic antenna though having the receivers as separate comp onents will enable us to expand our bas eline i e we can increase the separation area encompassing the four receivers which will provide greater prec is ion when calculating the direction and distance of the acoustic signal em anating the ROV 2 2 Transect simulation pro cedure In order to geospatially reconstruct our transects despite the numerous erroneous GPS readings we develop ed R co de to simulate ROV p osition based up on

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text:
1 compass headings from the ROV telemetry le that were recorded once p er second s 1 2 a pair of latitude and longitude co ordinates designating where the transect b egan and 3 a sample distribution containing ROV step lengths i e an aggregation of numerous samples of how far the ROV moved every second We describ e this pro cedure in brief b elow A sample distribution of ROV step lengths was generated by compiling eight ROV transects that were recorded prop erly by the GPS system We rs t applied a s mo other to all GPS tracks to remove the zig zags or slight back and forth generated by normal exp ected variation in the GPS system see the black raw vs smo othed red G PS tracks in Fig 1a d We then calculated the distance traveled i e the Euclidean distance traveled in decimal degree space every second b etween 3 all successive pairs of smo othed co ordinates The resulting distribution of ROV step lengths can b e seen in Fig 3a and see here for the co de Our simulation pro cedure see here for the co de and here for an

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explanation of the functions takes the starting latitude longitude co ordinates and then pairs every single empirically recorded compass heading with a step length that is randomly drawn with replacement from the sample distribution The e c acy of our simulation pro c edure is evidenced by plotting transects 1 and 3 from Site 1 Magnolia which were accurately recorded in black by the GPS and overlaying simulated versions of transects 1 and 3 in red atop them Fig 3b The tight concordance in b oth the heading and total length of the simulated vs real trans ects indicates our simulation pro cedure is accurate and appropriate This simulation pro cedure allowed us to consistently and accurately reconstruct the precise shap e in terms of length and changes in direction of our 2022 ROV surveys However the precision of the geospatial placement of our s imulated transects is dep endent up on the accuracy of the initial pair of latitude longitude GPS co ordinates In short some of our simulated transects sub je ctively lo ok to b e precisely mapp ed where we indeed surveyed see e g Fig 17 of Site 8 in the East Waterway whereas the

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text:
starting co ordinates of othe r transects lo oks a little o see e g Fig 11 where transect 4 should b e a bit to the north west as to also overlap with the submerged pip e Lastly note that these issues with the GPS will all b e resolved for our winter and summ er 2023 surveys a b c Figure 3 a Sample distribution of ROV step lengths calculated from the distance traveled b e twee n s uc cessive GPS co ordinates from transects acc urately recorded by the GPS This distribution was randomly sampled with replacement to generate our simulated step lengths b Transects 1 3 plotted as accurately recorded by the GPS red line and as simulated in black The tight concordance b etween the real and simulated data provides evidence that our simulation pro cedure is e ective c Transects 1 3 as accurately recorded by the GPS red lines alongside simulated transects 2 4 black lines Compare the simulated transects 2 4 to the real transects erro neously recorded by the GPS in Fig 1 c d 4 3 Metho dological development 3 1 Additional hardware and AI analyses We recently Q4

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text:
2022 obtained additional hardware that will enable us to ramp up b oth our eld and analytical op erations January 18 20 th we will assemble our sec ond Blue Rob otics BlueROV2 alongside Port of Seattle p ersonnel who will as semble their rst a joint build that will allow us to do cument via e g time lapse photography the pro cess of bringing life to a ROV The Seattle Aquarium s second ROV will provide c ritical redundancy for eld op erations preventing delays from leaks equipment failure or bugs asso ciated with the ROV s multiple complex electrical and structural systems Both Megan and Zach have obtained new Dell XPS 15 laptops from the Seattle Aquarium s IT department with hardware maximized for video pro cessing Q4 2022 we also received and are now installing the Mapping S tation a Corsair Vengeance i 7400 maximized to supp ort the intensive graphics and pro cessing required to run AI mo dels using visual imagery The Mapping Station will greatly facilitate the expansion of our AI analyses by providing a dedicated platform and lo cation where Seattle Aquarium sta and volunteers can b ecome trained and scheduled to

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text:
conduc t the manual annotations required to extensive ly train our AI mo dels Regarding the AI analyses since the August rep ort we have started using VIAME to p erform ob je ct detection i e to identify conspicuous individuals from the forward and downward facing imagery In particular we are now training VIAME to detect bull kelp from the forward imagery providing metrics of abundance for single stip es and small 2 3 stip es medium 3 5 stip es and large 5 stip es bundles Fig 4a We continue to use CoralNet to charac te riz e p ercent cover of colonial aggregated taxa as well as substrate typ e Fig 4c d a full list of our CoralNet p erce nt cover categories can b e downloaded here a b c d Figure 4 a Ob ject detection of bull kelp s tip es and bundles using VIAME o shore of Site 6 b Ob ject detection of a Mottled Se a Star Evasterias troschelii and a Brown Ro ck sh Sebastes auriculatus at Site 4 c d Percent cover classi cation via CoralNet at Sites 6 and 4 5 3 2 Camera settings video editing

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text:
We have shifted away from PowerDirector 365 and now use DaVinci Resolve Studio DRS to edit our ROV videos Throughout most of 2022 we shot video using the Auto white balance se tting of the GoPro 10 This pro duced vibrant auto calculated colors most of the time yet there were frequent o c curre nc es where the imagery would b e come was he d out towards the green end of the color sp ectrum esp ecially when to o much light either ambient or arti cial was present Fig 5a The Auto setting also generally resulted in substantial RGB color balance variation Megan has led the charge with video p ost pro cessing and she identi ed metho ds of color correcting the green washed out clips Fig 5b However these color corrections were time consuming so in Novemb er and Decemb er we b egan exp erimenting with di erent GoPro white balance settings The Native setting has risen ab ove the othe rs in terms of image delity the raw im agery app ears fairly muted e g see Fig 5c and color correction is required in p ost pro cessing Fig 5d However Native

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text:
do es not get thrown o in high light contexts nor do es it exhibit RGB color balancing variation which means 1 we do not need to color correct num erous individual clips and instead apply a single color correc tion to the entire video greatly exp editing video pro cessing time and 2 we can crank up the b enthic facing lights to higher p owers which provides more uniform lighting and sup erior image quality and consistency a b c d Figure 5 a An image using the Auto white balance setting where to o much light caused the GoPro to ush towards the green end of the sp ec trum b The same image as in a but color corrected using PowerDirector c An im age using the Native white balance setting that pro duces a muted image intended for correction in p ost pro duction d The same image as in c but color corrected using DRS 6 3 3 Area of sea o or surveyed Given 1 we know the ROV s altitude ab ove the sea o or via the Ping Sonar Altimeter that pro duces an altitude value every 1 s and 2

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text:
published eld of view information for the GoPro 10 s camera lens we calculate d the relationship b etween ROV altitude and the are a of sea o or lmed Fig 6a and see here for information ab out the co de With this information we can plot and map spatially explicit measurements of area surveyed along each transect We also used these measurements to calculate survey e ort m 2 sec and other parameters b elow se e Fig 10 and see here for an example of a pro cessed ROV telemetry le Note that as we can calculate area lmed p er s till image once our AI algorithms have b een more extensively trained our abundance and p ercent cover metrics will b e density p er m 2 estimates a b Figure 6 a The relationship b etween ROV altitude and the GoPro camera s eld of view including horizontal width blue line and height red line in meters as well as total area of sea o or b olded black in units of meters squared We aim to keep the ROV 1 m ab ove the sea o or which corresp onds to 3 43

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