The ability to detect buried mines on the seafloor remains one of the most important tasks in mine countermeasures. As such, there is a vested interest in the development of predictive models of mine burial. This research was conducted in support of the Office of Naval Research Program in Mine Burial Prediction. Repeat high-resolution multibeam bathymetry data were collected over the Indian Rocks Beach (IRB) mine burial experiment site during January through March of 2003, in order to observe in situ scour and burial of instrumented inert mines and mine-like cylinders. These data were also used to test the validity of the VIMS 2D mine burial model. A set of six high-resolution multibeam surveys were collected over the IRB experiment site. Three study sites within the IRB site were chosen: two fine sand sites, a shallow one located in ~ 13 meters of water depth and a deep site located in ~ 14 meters of water depth; and a coarse sand site in ~ 13 meters. Results from these surveys indicate that mines deployed in fine sand are upwards of 74.5% buried within two months of deployment. Mines deployed in the coarse sand showed a lesser amount of scour, burying until they presented roughly the same hydrodynamic roughness of the surrounding rippled bedforms. In general, scour around the mines formed pits ~ 0.30 meters deep, with the most pronounced scour occurring at the ends of the mine. The multibeam data were also used to test the VIMS 2D mine burial model, which estimates percent burial of cylindrical mines based on predictions of wave-induced scour. The model proved valid for use in areas of fine sand, sufficiently predicting burial over the course of the experiment. In the area of coarse sand, the model greatly overpredicted the amount of burial. This is believed to be due to the presence of ripples around the mines, which affect local bottom morphodynamics and are not accounted for in the model. This issue is currently being addressed by modelers.

Multi-beamecho sounder systemhas been around nowfor some 40 years and their use in shallow waters for the last 14 years. With modern shallow water systems running at up to 9,600 soundings/second, data collection at the rate of approximately 250 million soundings/day system is possible. Processing of Multibeam Echo sounder (MBES) data is a challenging task from both hydrographic and technological perspectives. We recognize that a completely automatic system is improbable, but propose that significant benefits can still be had if we can automatically process good quality data, and highlight areas that probably need further attention. We propose an algorithm that takes uncleaned MBES data and attempts to pick out outliers as possible as we can. The traditionalmethod that is still in use today by numerous software applications is based on a line-by-line processing approach. Automatically filtering for a depth window, by beam number, slope between points, quality flags and recently by whether the beam¡¦s error is outside the IHO order for the survey are a number of ways in which the line-by-line approach has been speeded up. The fundamental differences between our method and the previous methods are that our algorithm does not actually delete any soundings at all and transform original one dimension information into two dimensions. Finally, we use Hierarchical Clustering to classifyMBES data into outliers and normal. We develop the user interface formulti-beamecho sounder quality control. It provides almost the necessary tools and modules to perform a survey. Standard modules are Survey planning (track guidance lines, waypoints), channel design and 3D modeling, data acquisition, data QC and data processing/flagged. However, it will visualize the soundings to aid the decisionmaking process.

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Sjöfartsverket har i sitt arkiv en stor mängd backscatterdata, insamlat med multibeamekolod, som ännu inte har använts till sin fulla potential. Backscatterdata innehåller information om den reflekterade signalens styrka, även kallad amplitud. Stora mängder backscatterdata kan användas för att beskriva den akustiska bottenreflektionen. Syftet med denna undersökning är att beskriva hur variationen för amplituden varierar beroende på vilken bottentyp den reflekteras ifrån. En metod för att skapa rasterdataset med bottenhårdhet och bottentyp baserat på amplituddata ska utvecklas. Resultaten från denna metod ska sedan jämföras med kartdata från Sveriges Geologiska Undersökning (SGU). Totalt användes cirka 45 miljoner bottenpunkter i studieområdet. Varje punkt innehåller information om amplitud som systemet har registrerat från det reflekterade ekot. Dessa data behövde genomgå databehandlingar, bl.a. en vinkelkorrigering som ger ett mer trovärdigt värde av amplitud. Med hjälp av befintlig information om studieområdets sjöbotten i form av en maringeologisk karta från SGU, kunde amplitud från ett antal specifika uppskattade bottentyper studeras direkt. Resultatet uppvisar stora skillnader i amplitudens variationer. Specifika medelvärden och standardavvikelser kan urskiljas beroende av vilken specifik uppskattad bottentyp som studerades. ”Mjuk lera” gav en svagare signal med relativt låg standardavvikelse. ”Häll” och ”sten och block” reflekterade en liknade men starkare signal. Amplitudata från backscatter-informationen i hela datamängden utnyttjades för att skapa raster vars syfte var att beskriva den uppskattade bottenhårdheten. Olika raster skapades med olika parametrar beroende på ändamål. Gemensamt för alla skapade raster är att de är uppbyggda med metoden ”flytande beräkning” som möjliggjorde en mer utjämning. Resultatet av medelvärde och standardavvikelse från varje enskild bottentyp utnyttjades för att utföra en klassning av bottentyper på ett skapat raster lämpad för just bottentypsklassificering. För att få ett mer noggrannare medelvärde och standardavvikelse studerades ett 68 % konfidensintervall för de olika bottentyperna. De bottentyper som valdes för klassningen var ”mjuk lera”, ”sand, grus och sten”, ”häll”, ”sten och block” och även ”lägre amplituder”. ”Häll” och ”sten och block” klassades samma eftersom deras fysikaliska egenskaper gör att deras värden ligger nära varandra vilket gjorde det svårt att urskilja dem.”Lägre amplituder” utnyttjades för att identifiera områden som har lägre reflektionsförmåga än mjuk lera. Vilken bottentyp det är kan endast provtagning ge svar på. Med hjälp av tolkning av skapade raster och den maringeologiska kartan så korrigerades intervallen och användes som klassning. Resultatet från klassningen visar tydligt att områden kan urskiljas i kartbilden. Majoriteten av klassningarna resulterade i typen mjuk lera. En jämförelse av klassningen med den maringeologiska kartan visar att stora skillnader finns mellan dem. Mjuk lera gav en överensstämmelse på 86 %, sand, grus och sten 30 % och häll, sten och block 52,5 %, vilket gav en total överenstämmelse på 56,2 %. Jämförelse utfördes även med 9 provtagningspunkter som fanns tillgängliga i området. Det visade en total överenstämmelse på 89 %. Undersökningen visar att amplitud från havsbottnen korrelerar med bottentypen det är. Noterbart är att metoden för bottentypsklassificering som utvecklats i denna studie inte har kunnat kvalitetsgranskas med ett trovärdigt resultat, p.g.a. av statistiskt för få provtagningspunkter att jämföra mot. Studien visar dock att med mer data och noggrannare referensdata kan en mer automatisk klassningsmetod utvecklas. / The Swedish Maritime Administration (Sjöfartsverket) has a large amount of backscatter data collected with multibeam echosounder in their archive that has not been fully used despite its great potential. Backscatter data contains information about the strength of the reflected signal, often called amplitude strength. Large amounts of backscatter data could be used to describe the acoustic bottom reflection. The purpose of this study is to describe how the variation of the amplitude strength varies dependent on which estimated bottom types the data reflects from. Also a method will be produced which purpose is to create gridded dataset of estimated bottom hardness and bottom type based on amplitude data and compare this method with official data from the Geological Survey of Sweden (SGU).A total number of 45 million depths (data points) were used in the study area. Every data point contains information about the amplitude strength that the system has recovered from the reflective echo. This data needed to be preprocessed, including an angle correction that produces a more reliable value of the amplitude strength. With existing information about the bottom from the study area, in this case a marine geological map from SGU, the amplitude from some estimated specified bottom types could be studied. The result shows differences in their variation. Specific values of mean and standard deviation could be distinguished by which estimated specific bottom types that were studied.The amplitude strength from the backscatter information of the complete data set was used to create a raster that describes the estimated bottom-hardness. Different raster were created with various parameters dependent on the purpose. All of the created raster data had in common that it was created using a technique called “flow calculation” which result in more equalization.The mean and standard deviation for every individual estimated bottom type were used to create interval for classification of the bottom types. To achieve a more accurate estimation of the mean and standard deviation for the bottom types, a 68 % confidence interval were used. The classes that were chosen for classification was “soft clay”, “sand, gravel and stone”, “solid rock”, “stone and block” and “lower amplitudes”. “Solid rock” and “stone and block” were combined in the same class because of their similar physical properties. “Lower amplitudes” were chosen in order to indicate areas where the amplitude strength from the reflective echo was lower than “soft clay”.The result of the intervals was adjusted by an examination of the raster data and the marine geological map and was then used for classification.The result from the classification shows that areas of different bottom types could be distinguished in the map. The majority of the classification was of the type “soft clay”. A comparison between the classification and the marine geological map showed some differences. “Soft clay” matched with 86 %, “sand, gravel and stone” 30 %, “solid rock, stone and block” 52,5 % and the total matched with 56,2 %. Comparisons between 9 samplings in the area were made. The result shows that the classification-accuracy is 89 %.The study shows that the amplitude strength correlates to the bottom type. Note that too few samplings for bottom classification were used in the study and thus the results are not fully reliable. The study, however, shows that with larger amount of data and more accurate reference data a better automatic classification method could be developed.

1. Antarctic krill (Euphausia superba) form aggregations known as swarms that vary greatly in size and density. Six acoustic surveys were conducted as part of multidisciplinary studies at two study sites, the western and eastern core boxes (WCB and ECB), during the 1997, 1998 and 1999 austral summers, at South Georgia. A quantitative, automated, image processing algorithm was used to identify swarms, and calculate swarm descriptors, or metrics. In contrast to acoustic surveys of aggregations of other pelagic species, a strong correlation (r = 0.88, p = 0.02, 95% C.I.= 0.24 to 0.99) between the number of krill swarms and the mean areal krill density [rho.hat] was found. Multivariate analysis was used to partition swarms into three types, based on contrasting morphological and internal krill density parameters. Swarm types were distributed differently between inter-surveys and between on and off-shelf regions. This swarm type variation has implications for krill predators, by causing spatial heterogeneity in swarm detectability, suggesting that for optimal foraging to occur, predators must engage in some sort of adaptive foraging strategy. 2. Krill predator-prey interactions were found to occur at multiple spatial and temporal scales, in a nested, or hierarchical structure. At the largest inter-survey scale, an index of variability, I, was developed to compare variation in survey-scale predator sightings, sea temperature and [rho.hat]. Using I and a two-way ANOVA, core box, rather than year, was found to be a more important factor in determining species distribution. The absence of Blue-petrels (Halobaena caerulea) and the elevated number of Antarctic fur seals (Arctocephalus gazella) suggest that 1998 was a characterised by colder than average water surrounding South Georgia, and a high [rho.hat] in the ECB. At the smaller, intra-survey scales (<80 km, <5 day), the characteristic scale (distances in which predator group size, or krill density were similar, L_s) were determined. For krill and predators L_s varied by survey and the L_s of krill also varied by depth within a survey. Overlap in L_s were stronger between predator species than between a predator species and krill, indicating predators were taking foraging cues from the activity of predators, rather than from the underlying krill distribution. No relationship was found between swarm characteristics and predator activity, suggesting either there is no relationship between krill swarms and predators, or that the predator and acoustic observation techniques may not be appropriate to detect such a relationship. 3. To overcome the 2-D sampling limitations of conventional echosounders, a multibeam echosounder (MBE) observed entire swarms in three-dimensions. Swarms found in the nearshore environment of Livingston Island situated in the South Shetland Islands, exhibited only a narrow range of surface area to volume ratios or roughnesses (R = 3.3, CV = 0.23), suggesting that krill adopt a consistent group behaviour to maintain swarm shape. Generalized additive models (GAM) suggested that the presence of air-breathing predators influenced the shape of a krill swarm (R decreased in the presence of predators: the swarm became more spherical). A 2D distance sampling framework was used to estimate the abundance, N, and associated variance of krill swarms. This technique took into account angular and range detectability (half-normal, [sigma_r.hat] = 365.00 m, CV = 0.16) and determined the vertical distribution of krill swarms to be best approximated by a beta-distribution ([alpha.hat] = 2.62, [CV.hat] = 0.19; [beta.hat] = 2.41, [CV.hat] = 0.15), giving the abundance of swarms in survey region as [N.hat] = 5,062 ([CV.hat] = 0.35). This research represents a substantial contribution to developing estimation of pelagic biomass using MBEs. 4. When using a single- or split-beam missing pings occur when the transmit or receive cycles are interrupted, often by aeration of the water column, under the echosounder transducer during rough weather. A thin-plate regression spline based approach was used to model the missing krill data, with knots chosen using a branch and bound algorithm. This method performs well for acoustic observations of krill swarms where data are tightly clustered and change rapidly. For these data the technique outperformed the standard MGCV GAM, and the technique is applicable for estimating acoustically derived biomass from line transect surveys.

Orientador: Mauricio Galo / Resumo: Um Levantamento Hidrográfico (LH) tem como principal meta a obtenção de dados para a edição e atualização de documentos náuticos, estes, voltados à segurança das atividades de navegação. Objetivando padronizar parâmetros de incerteza das cartas náuticas, a Organização Hidrográfica Internacional (OHI) define níveis mínimos de confiança para diferentes ordens. A sugestão dessas especificações foi internalizada pela Marinha do Brasil, responsável pela produção das cartas náuticas brasileiras, na NORMAM-25. Um desses parâmetros é a Incerteza Vertical Total máxima permitida, um indicador de qualidade da medição da profundidade. A informação de profundidade influencia no calado máximo permitido a uma embarcação para transitar em uma região com segurança, o que pode impactar inclusive nas limitações de transações comerciais em terminais portuários, uma vez que as profundidades estimadas com acurácia potencializam os parâmetros de operação dos portos. Por se tratar de um ambiente dinâmico, seja por ação da própria natureza ou devido a atividades antrópicas, a atualização de uma carta náutica deve ser uma preocupação constante. Como complemento à tradicional técnica de levantamento por meio de um ecobatímetro acoplado a embarcações, há a opção de se realizar um LH com o emprego da tecnologia LiDAR (Light Detection And Ranging) a partir de aeronaves, por meio de um aerolevantamento batimétrico por LiDAR (ALB – Airborne LASER Bathymetry), que operam com pulsos LASER na região verde do e... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: A Hydrographic Survey (HS) has as main goal to obtain data for editing and updating nautical documents, these, focused on the safety of navigation. In order to establish a standard of uncertainty parameters for nautical charts, the International Hydrographic Organization (IHO) defines minimum levels of confidence for different orders. The suggestion of these specifications was acknowledged by the Brazilian Navy, institution responsible to produce Brazilian nautical charts, as described in NORMAM-25. One such parameter is the maximum allowed Total Vertical Uncertainty, a quality indicator of the depth measurement. Depth information influences the maximum operational draft for a vessel to safely travel in a region, causing impact on port operations and limiting the commercial transactions. Accurately estimated depths enhance the operational parameters of the ports. Due to the aim of representing a dynamic environment, whether as consequence of the action of nature itself or because of anthropic activities, updating a nautical chart must be a constant concern. As a complement to the traditional survey technique conducted with a boat-coupled echosounder, there is the option of performing a HS using LiDAR (Light Detection And Ranging) technology from aircraft, through LiDAR aerial bathymetry (ALB - Airborne LASER Bathymetry), which operate with LASER pulses in the green region of the electromagnetic spectrum. Considering these points, this work analyzed the differences between the... (Complete abstract click electronic access below) / Mestre

<p>Fledermaus is software where different kind of analysis with spatial data can be done. The main area where to use Fledermaus is related to hydrographical surveys. This study is aimed to test and analyse the way Swedish Maritime Administration (Sjöfartsverket) uses Fledermaus. Through step by step explaining how to do when measuring sea bed conditions from a vessel, this text is possible to use as a manual for the applications that are mentioned in this report.</p><p>Another thing that is treated is the squat effect that belongs to vessel dynamic motions. Test of visualization that concerning squat in Fledermaus is done, but with a negative result when squat in a perspective to show motions in height that can be up to about a metre is very hard in a terrain model of thousands of metres. By further tests by arranging the input data, several interesting diagrams have been created through Microsoft Excel where graphs show that the depths are affecting the squat effect. This is showed in same diagram but with two different scales to show the relationship between how a point at the vessel moves in height compared to the depth under the vessel when the vessel is navigating in the sea.</p> / <p>Fledermaus är en programvara där olika analyser med rumsliga data kan genomföras. Största användningsområdet är att använda Fledermaus till mätningar som är relaterade till sjömätning. Den här studien är inriktad till att testa och analysera applikationer som Sjöfartsverket använder sig av i Fledermaus. Genom att steg för steg förklara hur Fledermaus ska användas när bottenförhållanden ska mätas sett från ett fartyg, så blir texten även möjlig att använda som en manual till de applikationer i Fledermaus som är nämnda i denna rapport.</p><p>Det andra som behandlas är squateffekten som tillhör ett fartygs dynamiska rörelser. Test av visualisering som behandlar squat i Fledermaus är genomförd, dock med negativt resultat då squat i ett perspektiv med att visa rörelser i höjd som kan uppgå till runt en meter är väldigt svårt i en terrängmodell som sträcker sig tusentals meter. Dock genom vidare tester genom behandling av indata, har flertalet intressanta diagram skapats genom Microsoft Excel där kurvor visar att djupet inverkar på squateffekten. Detta visas genom att i samma diagram fast med två olika skalor visa förhållandet mellan hur en punkt på båten rör sig i höjd jämfört med att djupet under fartyget ändras då fartyget gör fart genom vattnet.</p>

In March of 2000, March of 2001, and April of 2002, multibeam bathymetry and backscatter data were collected, which revealed several low-temperature hydrothermal submarine springs in the Mudhole Submarine Springs (MHSS) area that were investigated by SCUBA divers. High-resolution multibeam sonar provides a precise way of defining the geomorphology of the seafloor. The bathymetry data were used to understand (1) vent geomorphology and how it varied from vent to vent; (2) spatial patterns of active vents compared to extinct vents and known land springs identified by Kohout (1977) and Breland (1980); and (3) potential correlations between geochemical and geomorphological characteristics of the vents in the study area. SCUBA observations show that MHSS, Spring #3, New Spring, Northern Rusty, Rusty, and Near Rusty are active springs, while Dormant Spring and Sinister Spring were extinct or inactive at the time of the March 2001 cruise.During the April 2002 cruise the locations of Rusty Spring, New Spring and MHSS were confirmed. Two submarine springs, Creature Hole and Sparky Lee were also confirmed. Spring #3 is the deepest spring and Dormant Spring is the shallowest. There appears to be a rough spatial correlation between vents located on land and the vents on the seafloor, in which all known vents are either to the west or north of Lake Okeechobee. Vent distribution in the MHSS study area appears to correlate with the structural pattern of the local seafloor. Backscatter data and SCUBA observations show that fine to medium grain siliciclastic sediment bands overlie limestone hardbottom in a NE-SW orientation. Although vent geomorphologies are generally distinctive, vent activities generally correlate with the steepness of vent depressions.Most active vents had slopes of 6 degrees or greater, with the exception of Rusty Spring and Near Rusty Spring whose slopes ranged from 2.5 degrees and 6 degrees; whereas all the inactive vents had slopes of 5 degrees or less. Most active vents have "V"-shaped profiles versus the "U"-shaped profiles of most of the inactive vents. The inactive springs have shallower maximum depths and shallower ambient seafloor depths than the active vents.

Fledermaus is software where different kind of analysis with spatial data can be done. The main area where to use Fledermaus is related to hydrographical surveys. This study is aimed to test and analyse the way Swedish Maritime Administration (Sjöfartsverket) uses Fledermaus. Through step by step explaining how to do when measuring sea bed conditions from a vessel, this text is possible to use as a manual for the applications that are mentioned in this report. Another thing that is treated is the squat effect that belongs to vessel dynamic motions. Test of visualization that concerning squat in Fledermaus is done, but with a negative result when squat in a perspective to show motions in height that can be up to about a metre is very hard in a terrain model of thousands of metres. By further tests by arranging the input data, several interesting diagrams have been created through Microsoft Excel where graphs show that the depths are affecting the squat effect. This is showed in same diagram but with two different scales to show the relationship between how a point at the vessel moves in height compared to the depth under the vessel when the vessel is navigating in the sea. / Fledermaus är en programvara där olika analyser med rumsliga data kan genomföras. Största användningsområdet är att använda Fledermaus till mätningar som är relaterade till sjömätning. Den här studien är inriktad till att testa och analysera applikationer som Sjöfartsverket använder sig av i Fledermaus. Genom att steg för steg förklara hur Fledermaus ska användas när bottenförhållanden ska mätas sett från ett fartyg, så blir texten även möjlig att använda som en manual till de applikationer i Fledermaus som är nämnda i denna rapport. Det andra som behandlas är squateffekten som tillhör ett fartygs dynamiska rörelser. Test av visualisering som behandlar squat i Fledermaus är genomförd, dock med negativt resultat då squat i ett perspektiv med att visa rörelser i höjd som kan uppgå till runt en meter är väldigt svårt i en terrängmodell som sträcker sig tusentals meter. Dock genom vidare tester genom behandling av indata, har flertalet intressanta diagram skapats genom Microsoft Excel där kurvor visar att djupet inverkar på squateffekten. Detta visas genom att i samma diagram fast med två olika skalor visa förhållandet mellan hur en punkt på båten rör sig i höjd jämfört med att djupet under fartyget ändras då fartyget gör fart genom vattnet.