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  • 1
    facet.materialart.
    Unknown
    PANGAEA
    In:  GEOMAR - Helmholtz Centre for Ocean Research Kiel
    Publication Date: 2023-03-03
    Keywords: BC; Box corer; Calculated; CTD/Rosette; CTD-RO; DATE/TIME; DEPTH, water; EBS; Elevation of event; Epibenthic sledge; Event label; GC; Gravity corer; JPI-OCEANS; JPI Oceans - Ecological Aspects of Deep-Sea Mining; JPIO-MiningImpact; Julian day; LATITUDE; Light, backscattered from particles; LONGITUDE; Miniature Autonomous Plume Recorder (MAPR); MUC; MultiCorer; Number; Ocean Floor Observation System; OFOS; Optional event label; Oxidation reduction (RedOx) potential; Pressure, water; SO242/1; SO242/1_100-1; SO242/1_100-1_GC 5; SO242/1_101-1; SO242/1_101-1_BC 18; SO242/1_103-1; SO242/1_103-1_BC 19; SO242/1_104-1; SO242/1_104-1_EBS 6; SO242/1_108-1; SO242/1_108-1_MUC 26; SO242/1_109-1; SO242/1_109-1_MUC 27; SO242/1_1-1; SO242/1_1-1_CTD 1; SO242/1_110-1; SO242/1_110-1_MUC 28; SO242/1_111-1; SO242/1_111-1_OFOS 3; SO242/1_112-1; SO242/1_112-1_OFOS 4; SO242/1_115-1; SO242/1_115-1_MUC 30; SO242/1_117-1; SO242/1_117-1_EBS 7; SO242/1_119-1; SO242/1_119-1_MUC 31; SO242/1_120-1; SO242/1_120-1_BC 21; SO242/1_121-1; SO242/1_121-1_BC 22; SO242/1_122-1; SO242/1_122-1_EBS 8; SO242/1_123-1; SO242/1_123-1_GC 6; SO242/1_124-1; SO242/1_124-1_BC 23; SO242/1_126-1; SO242/1_126-1_EBS 9; SO242/1_127-1; SO242/1_127-1_BC 24; SO242/1_128-1; SO242/1_128-1_BC 25; SO242/1_129-1; SO242/1_129-1_BC 26; SO242/1_130-1; SO242/1_130-1_MUC 32; SO242/1_131-1; SO242/1_131-1_MUC 33; SO242/1_132-1; SO242/1_132-1_GC 7; SO242/1_134-1; SO242/1_134-1_OFOS 5; SO242/1_135-1; SO242/1_135-1_OFOS 6; SO242/1_19-1; SO242/1_19-1_MUC 1; SO242/1_20-1; SO242/1_20-1_BC 1; SO242/1_22-1; SO242/1_22-1_MUC 2; SO242/1_24-1; SO242/1_24-1_MUC 3; SO242/1_26-1; SO242/1_26-1_BC 2; SO242/1_27-1; SO242/1_27-1_BC 3; SO242/1_28-1; SO242/1_28-1_MUC 4; SO242/1_31-1; SO242/1_31-1_BC 4; SO242/1_32-1; SO242/1_32-1_BC 5; SO242/1_35-1; SO242/1_35-1_MUC 7; SO242/1_37-1; SO242/1_37-1_EBS 1; SO242/1_38-1; SO242/1_38-1_GC 1; SO242/1_39-1; SO242/1_39-1_MUC 8; SO242/1_40-1; SO242/1_40-1_MUC 9; SO242/1_43-1; SO242/1_43-1_OFOS 1; SO242/1_45-1; SO242/1_45-1_EBS 2; SO242/1_46-1; SO242/1_46-1_MUC 11; SO242/1_48-1; SO242/1_48-1_BC 6; SO242/1_49-1; SO242/1_49-1_BC 7; SO242/1_51-1; SO242/1_51-1_GC 2; SO242/1_52-1; SO242/1_52-1_BC 8; SO242/1_53-1; SO242/1_53-1_BC 9; SO242/1_54-1; SO242/1_54-1_BC 10; SO242/1_56-1; SO242/1_56-1_MUC 12; SO242/1_61-1; SO242/1_61-1_MUC 13; SO242/1_62-1; SO242/1_62-1_MUC 14; SO242/1_70-1; SO242/1_70-1_MUC 17; SO242/1_71-1; SO242/1_71-1_MUC 18; SO242/1_73-1; SO242/1_73-1_MUC 19; SO242/1_74-1; SO242/1_74-1_MUC 20; SO242/1_76-1; SO242/1_76-1_OFOS 2; SO242/1_77-1; SO242/1_77-1_BC 11; SO242/1_78-1; SO242/1_78-1_BC 12; SO242/1_79-1; SO242/1_79-1_MUC 21; SO242/1_80-1; SO242/1_80-1_MUC 22; SO242/1_84-1; SO242/1_84-1_GC 3; SO242/1_85-1; SO242/1_85-1_EBS 4; SO242/1_86-1; SO242/1_86-1_BC 13; SO242/1_87-1; SO242/1_87-1_BC 14; SO242/1_89-1; SO242/1_89-1_GC 4; SO242/1_90-1; SO242/1_90-1_MUC 23; SO242/1_91-1; SO242/1_91-1_MUC 24; SO242/1_92-1; SO242/1_92-1_MUC 25; SO242/1_93-1; SO242/1_93-1_EBS 5; SO242/1_95-1; SO242/1_95-1_BC 15; SO242/1_96-1; SO242/1_96-1_BC 16; SO242/1_98-1; SO242/1_98-1_BC 17; Sonne_2; Temperature, water; West Reference Area
    Type: Dataset
    Format: text/tab-separated-values, 1136933 data points
    Location Call Number Limitation Availability
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  • 2
    facet.materialart.
    Unknown
    PANGAEA
    In:  GEOMAR - Helmholtz Centre for Ocean Research Kiel
    Publication Date: 2023-03-03
    Keywords: Calculated; CTD/Rosette; CTD-RO; DATE/TIME; DEPTH, water; Elevation of event; Event label; JPI-OCEANS; JPI Oceans - Ecological Aspects of Deep-Sea Mining; JPIO-MiningImpact; Julian day; LATITUDE; Light, backscattered from particles; LONGITUDE; Miniature Autonomous Plume Recorder (MAPR); MUC; MultiCorer; Number; Ocean Floor Observation System; OFOS; Optional event label; Oxidation reduction (RedOx) potential; Pressure, water; Remote operated vehicle; Remote operated vehicle elevator; ROV; ROV_E; SO242/2; SO242/2_138-1; SO242/2_139-1; SO242/2_142-1; SO242/2_151-1; SO242/2_153-1; SO242/2_154-1; SO242/2_155-1; SO242/2_157-1; SO242/2_163-1; SO242/2_166-1; SO242/2_169-1; SO242/2_172-1; SO242/2_176-1; SO242/2_179-1; SO242/2_183-1; SO242/2_188-1; SO242/2_190-1; SO242/2_191-1; SO242/2_194-1; SO242/2_196-1; SO242/2_198-1; SO242/2_202-1; SO242/2_205-1; SO242/2_207-1; SO242/2_208-1; SO242/2_211-1; SO242/2_213-1; SO242/2_216-1; SO242/2_219-1; SO242/2_222-1; SO242/2_224-1; SO242/2_232-1; SO242/2_235-1; Sonne_2; South Pacific Ocean, Peru Basin; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 1548428 data points
    Location Call Number Limitation Availability
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  • 3
    Publication Date: 2023-03-28
    Description: The raw images (available on request) have been captured using a Canon 8-15mm fisheye lens and therefore they have a wide field of view, which results in a dark image boundary as the lights did not illuminate the outer sectors well. The images in this dataset have then been undistorted to virtual images that an ideal perspective camera with only 90 degrees horizontal field of view would have seen from the same position. To achieve this, the color of each pixel in the ideal image is obtained by - computing the ray in space associated with this virtual pixel (using rectilinear un-projection) - projecting this ray into the original fisheye image (using equidistant projection), yielding a sub-pixel position - interpolating the colors of the neighboring pixels Technically, the undistortion has been performed using the tool https://svn.geomar.de/dsm-general/trunk/src/BIAS/Tools/biasproject.cpp (at revision 418, and earlier, compatible revisions). Manual image annotation is available here: https://annotate.geomar.de/volumes/257
    Keywords: Acoustic Doppler Current Profiling (ADCP); Autonomous underwater vehicle; AUV; AUV forward velocity; AUV starboard velocity; AUV vertical velocity; Chlorophyll a; Conductivity; CTD, SEA-BIRD SBE 49; DATE/TIME; DEA; DEPTH, water; Digital camera, Canon EOS 6D, Fisheye lens; DISCOL Experimental Area; Distance; File format; File name; File size; Fluorometer, WET Labs, ECO FLNTU; Ground visibility (1=yes/0=no); Heading; Image brightness; JPI-OCEANS; JPI Oceans - Ecological Aspects of Deep-Sea Mining; JPIO-MiningImpact; LATITUDE; LONGITUDE; Pitch angle; Roll angle; Salinity; SO242/1; SO242/1_25-1; SO242/1_25-1_AUV 3; Sonne_2; Sound velocity in water; Temperature, water; Time, relative; Turbidity (Nephelometric turbidity unit); Uniform resource locator/link to image
    Type: Dataset
    Format: text/tab-separated-values, 67961 data points
    Location Call Number Limitation Availability
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  • 4
    Publication Date: 2023-03-28
    Description: The raw images (available on request) have been captured using a Canon 8-15mm fisheye lens and therefore they have a wide field of view, which results in a dark image boundary as the lights did not illuminate the outer sectors well. The images in this dataset have then been undistorted to virtual images that an ideal perspective camera with only 90 degrees horizontal field of view would have seen from the same position. To achieve this, the color of each pixel in the ideal image is obtained by - computing the ray in space associated with this virtual pixel (using rectilinear un-projection) - projecting this ray into the original fisheye image (using equidistant projection), yielding a sub-pixel position - interpolating the colors of the neighboring pixels Technically, the undistortion has been performed using the tool https://svn.geomar.de/dsm-general/trunk/src/BIAS/Tools/biasproject.cpp (at revision 418, and earlier, compatible revisions). Manual image annotation is available here: https://annotate.geomar.de/volumes/258
    Keywords: Acoustic Doppler Current Profiling (ADCP); Autonomous underwater vehicle; AUV; AUV forward velocity; AUV starboard velocity; AUV vertical velocity; Chlorophyll a; Conductivity; CTD, SEA-BIRD SBE 49; DATE/TIME; DEA; DEPTH, water; Digital camera, Canon EOS 6D, Fisheye lens; DISCOL Experimental Area; Distance; File format; File name; File size; Fluorometer, WET Labs, ECO FLNTU; Ground visibility (1=yes/0=no); Heading; Image brightness; JPI-OCEANS; JPI Oceans - Ecological Aspects of Deep-Sea Mining; JPIO-MiningImpact; LATITUDE; LONGITUDE; Pitch angle; Roll angle; Salinity; SO242/1; SO242/1_33-1; SO242/1_33-1_AUV 4; Sonne_2; Sound velocity in water; Temperature, water; Time, relative; Turbidity (Nephelometric turbidity unit); Uniform resource locator/link to image
    Type: Dataset
    Format: text/tab-separated-values, 251089 data points
    Location Call Number Limitation Availability
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  • 5
    Publication Date: 2023-03-28
    Description: The raw images (available on request) have been captured using a Canon 8-15mm fisheye lens and therefore they have a wide field of view, which results in a dark image boundary as the lights did not illuminate the outer sectors well. The images in this dataset have then been undistorted to virtual images that an ideal perspective camera with only 90 degrees horizontal field of view would have seen from the same position. To achieve this, the color of each pixel in the ideal image is obtained by - computing the ray in space associated with this virtual pixel (using rectilinear un-projection) - projecting this ray into the original fisheye image (using equidistant projection), yielding a sub-pixel position - interpolating the colors of the neighboring pixels Technically, the undistortion has been performed using the tool https://svn.geomar.de/dsm-general/trunk/src/BIAS/Tools/biasproject.cpp (at revision 418, and earlier, compatible revisions). Manual image annotation is available here: https://annotate.geomar.de/volumes/262
    Keywords: Acoustic Doppler Current Profiling (ADCP); Autonomous underwater vehicle; AUV; AUV forward velocity; AUV starboard velocity; AUV vertical velocity; Chlorophyll a; Conductivity; CTD, SEA-BIRD SBE 49; DATE/TIME; DEA; DEPTH, water; Digital camera, Canon EOS 6D, Fisheye lens; DISCOL Experimental Area; Distance; File format; File name; File size; Fluorometer, WET Labs, ECO FLNTU; Ground visibility (1=yes/0=no); Heading; Image brightness; JPI-OCEANS; JPI Oceans - Ecological Aspects of Deep-Sea Mining; JPIO-MiningImpact; LATITUDE; LONGITUDE; Pitch angle; Roll angle; Salinity; SO242/1; SO242/1_94-1; SO242/1_94-1_AUV 12; Sonne_2; Sound velocity in water; Temperature, water; Time, relative; Turbidity (Nephelometric turbidity unit); Uniform resource locator/link to image
    Type: Dataset
    Format: text/tab-separated-values, 480791 data points
    Location Call Number Limitation Availability
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  • 6
    Publication Date: 2023-03-28
    Description: The raw images (available on request) have been captured using a Canon 8-15mm fisheye lens and therefore they have a wide field of view, which results in a dark image boundary as the lights did not illuminate the outer sectors well. The images in this dataset have then been undistorted to virtual images that an ideal perspective camera with only 90 degrees horizontal field of view would have seen from the same position. To achieve this, the color of each pixel in the ideal image is obtained by - computing the ray in space associated with this virtual pixel (using rectilinear un-projection) - projecting this ray into the original fisheye image (using equidistant projection), yielding a sub-pixel position - interpolating the colors of the neighboring pixels Technically, the undistortion has been performed using the tool https://svn.geomar.de/dsm-general/trunk/src/BIAS/Tools/biasproject.cpp (at revision 418, and earlier, compatible revisions). Manual image annotation is available here: https://annotate.geomar.de/volumes/259
    Keywords: Acoustic Doppler Current Profiling (ADCP); Autonomous underwater vehicle; AUV; AUV forward velocity; AUV starboard velocity; AUV vertical velocity; Chlorophyll a; Conductivity; CTD, SEA-BIRD SBE 49; DATE/TIME; DEPTH, water; Digital camera, Canon EOS 6D, Fisheye lens; Distance; File format; File name; File size; Fluorometer, WET Labs, ECO FLNTU; Ground visibility (1=yes/0=no); Heading; Image brightness; JPI-OCEANS; JPI Oceans - Ecological Aspects of Deep-Sea Mining; JPIO-MiningImpact; LATITUDE; LONGITUDE; Pitch angle; Reference Area South; Roll angle; Salinity; SO242/1; SO242/1_41-1; SO242/1_41-1_AUV 5; Sonne_2; Sound velocity in water; Temperature, water; Time, relative; Turbidity (Nephelometric turbidity unit); Uniform resource locator/link to image
    Type: Dataset
    Format: text/tab-separated-values, 29820 data points
    Location Call Number Limitation Availability
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  • 7
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    Unknown
    PANGAEA
    In:  GEOMAR - Helmholtz Centre for Ocean Research Kiel
    Publication Date: 2023-01-13
    Description: A hierarchically ordered distribution of 3D-points was created with matlab. It contains 120,000 datapoints in five hierarchical levels with one to four child nodes per parent. Data values for the three axes range betwwen 0 and 1. The structure can be seen in the attached figure. In each hierarchical level different distributions of datapoints are implemented. This allows to test classifiers under various conditions. The most common distribution in the dataset is a simple gaussian distributed point cloud. Other sampled distributions are a spherical distribution (sphere in 3D), or a circular (donut) distribution along different axes. XOR distributions are implemented in different patterns, e.g. four batches with crossed classes or eight batches with two or four classes. The most complex data distribution is the springroll, where the datapoints are intertwined into one another. To create indistinguishable cases, where the prediction of a classifier is supposed to perform bad, some datapoints are just randomly intermixed with another class. The .csv-file contains four columns: label | x-coordinate | y-coordinate | z-coordinate The label for each sample provides all hierarchical information needed. Each label is composed of five digits, one for each hierarchical level. As an example: Sample '11421': Hierarchical level 1: class 1 Hierarchical level 2: class 1 Hierarchical level 3: class 4 Hierarchical level 4: class 2 Hierarchical level 5: class 1
    Type: Dataset
    Format: application/zip, 1.2 MBytes
    Location Call Number Limitation Availability
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  • 8
    Publication Date: 2023-01-13
    Description: The cruise SO268 was designed to assess the environmental impacts of deep-sea mining of polymetallic nodules in the Clarion-Clipperton Fracture Zone (CCZ). Therefore, a dredging experiment was conducted on 11 April 2019 between 6:30 to 19:00 UTC. To monitor the dispersion of the generated plume, 15 sensors were distributed around the dredge tracks. Three of them are presented in this study.
    Keywords: JPI Oceans - Ecological Aspects of Deep-Sea Mining; JPIO-MiningImpact
    Type: Dataset
    Format: application/zip, 3 datasets
    Location Call Number Limitation Availability
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  • 9
    facet.materialart.
    Unknown
    PANGAEA
    In:  GEOMAR - Helmholtz Centre for Ocean Research Kiel | Supplement to: Schoening, Timm; Köser, Kevin; Greinert, Jens (2018): An acquisition, curation and management workflow for sustainable, terabyte-scale marine image analysis. Scientific Data, 5, 180181, https://doi.org/10.1038/sdata.2018.181
    Publication Date: 2023-01-13
    Description: Optical imaging is a common technique in ocean research. Diving robots, towed cameras, drop-cameras and TV-guided sampling gear: all produce image data of the underwater environment. Technological advances like 4K cameras, autonomous robots, high-capacity batteries and LED lighting now allow systematic optical monitoring at large spatial scale and shorter time but with increased data volume and velocity. Volume and velocity are further increased by growing fleets and emerging swarms of autonomous vehicles creating big data sets in parallel. This generates a need for automated data processing to harvest maximum information. Systematic data analysis benefits from calibrated, geo-referenced data with clear metadata description, particularly for machine vision and machine learning. Hence, the expensive data acquisition must be documented, data should be curated as soon as possible, backed up and made publicly available. Here, we present a workflow towards sustainable marine image analysis. We describe guidelines for data acquisition, curation and management and apply it to the use case of a multi-terabyte deep-sea data set acquired by an autonomous underwater vehicle.
    Keywords: JPI Oceans - Ecological Aspects of Deep-Sea Mining; JPIO-MiningImpact
    Type: Dataset
    Format: application/zip, 21 datasets
    Location Call Number Limitation Availability
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  • 10
    Publication Date: 2023-01-13
    Description: Images were acquired by the DeepSurvey Camera on board GEOMAR's AUV Abyss. Nodules were delineated by the CoMoNoD algorithm [see related to references]. Result files are computed per AUV dive. Nodule detections below 5cm^2 are neglected as are detections above 707cm^2. Abundance statistics are computed per m^2 and gridded per m^2 as well. For overlapping images, max-pooling has been applied to select the values reported in the result files. Pixel values in the rendered maps correspond to the units reported in the ASCI files (median-nodule-size: cm^2, nodule-number: m^-2, percent-coverage: %, sorting, skewness and pixel-contributions are unit-free).
    Keywords: JPI Oceans - Ecological Aspects of Deep-Sea Mining; JPIO-MiningImpact
    Type: Dataset
    Format: application/zip, 18 datasets
    Location Call Number Limitation Availability
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