API src

Found 292 results.

Related terms

Fixed-wing Magnetics NOGRAM I + II

In 1998, as part of the expedition NOGRAM I (Northern Gravity, Radio Echo Sounding and Magnetics), a flight campaign was carried out over the Lincoln Sea north of Greenland with the Polar 2 aircraft (Dornier 228-100) in cooperation with the Alfred Wegener Institute Helmholtz Center for Polar and Marine Research. A second flight campaign NOGRAM II took place in 2011 with the Polar 5 (Basler BT-67) over the Wandel Sea north of Greenland. The aim of the research was the structure and architecture of the upper Earth’s crust underneath the ice-covered offshore areas of the Morris Jesup Plateau and coastal waters north of Greenland. The airborne magnetic surveys were carried out with a flight line spacing of 3 km, and control profiles were flown every 30 km. During the two expeditions, 33000 km of line data were collected (16000 km in 1998, and 17000 km in 2011).

Absorption coefficients by non-water components at the first eight Ocean Land Colour Imager bands from a global in-situ collection of open ocean, coastal and inland surface waters matched to OLCI

This in situ data set of absorption coefficients by non-water components at the first eight Ocean Land Colour Imager (OLCI) bands (centred at 400 nm 412.5 nm, 442.5 nm, 490 nm, 510 nm, 560 nm, 620 nm, 665 nm, abbreviated as anw(400), anw(412), anw(443), anw(490), anw(510), anw(560), anw(620), and anw(665)) consists of different data sets gathered together from measurements collected in open, coastal, and inland surface waters spread around the globe and covering the time from first data delivery by OLCI on S3A in May 2016 until November 2022 which were matched to Ocean Land Colour Imager on Sentinel-3A and -3B and used in the paper by Bracher et al. (2025). We only used coincident hyperspectral absorption coefficients by particulates and coloured dissolved organic matter or non-algal particulates, phytoplankton and coloured dissolved organic matter derived from measurements on discrete water samples to ensure a similar method procedure followed and a similar uncertainty. These coincident measurements were summed up to calculate anw(λ). The collection includes publicly available data and newly collected, measured and analysed data sets from the Phytooptics group at the Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research (AWI, PI: Astrid Bracher) and Hellenic Centre for Marine Research (HCMR, PI: Andrew C. Banks). The data collection was matched that in situ data points had to fall within the 3x3 OLCI FR pixel box and a time window of + 12 hours which followed established community protocols (IOCCG 2018) and particularly EUMETSAT's OLCI matchup protocol (EUMETSAT 2022). Firstly, a pre-processing for quality control and a conversion of the considered in situ data to a common format following Valente et al. (2022) was performed. We flagged and disregarded the following data from the final quality-controlled data set which had (1) unrealistic or missing date or geographic coordinate fields, (2) poor quality (e.g., original flags) or method of observation that did not meet the criteria for the dataset (e.g., not defined in the community protocols (IOCCG 2018, 2019a, 2019b), and (3) spuriously high or low data. For the last item, the following limits were imposed: [0.0001–10] m−1 for anw(443). OLCI pixels were discarded when flagged with the recommended flags in (EUMETSAT 2022), and the remaining matchups were only considered valid if more than 50% of satellite pixels were available at remote sensing reflectance centred at band 560 nm (Rrs(560), e.g., 5 out of 9 for the 3x3 criterion) per an in situ data point, and a coefficient of variation <0.2. Dedicated matchup software developed by EUMETSAT was used to ensure that the validation process followed the established guidelines, ThoMaS (the Tool to generate Matchups of OC products with S3 OLCI https://gitlab.eumetsat.int/eumetlab/oceans/ocean-science-studies/ThoMaS). The anw(λ) data provided in hyperspectral resolution (1nm, 2nm or around 3.3 nm resolution) were transformed to the nominal OLCI bands by averaging over the specific bandwidth, following Zibordi et al. (2023). The OLCI matchup data, based on their associated RRS data at the first eight OLCI bands, were assigned to the specific optical water classes (OWCs) according to the Mélin & Vantrepotte (2015) classification. This contains 17 OWCs which range from very turbid to (OWC 1) oligotrophic to very clear waters (OWC 17). The OWC is also delivered for each matchup point (if the assignment fails the field contains "NaN". We provide also for OLCI the standard deviation of the OLCI matchup data to a in situ data point within the 3x3 pixels. For the in situ data we provide the estimate of the uncertainty for each matchup point further described in Bracher et al. (2025).

Multibeam bathymetry raw data (Kongsberg EM712 entire dataset) of RV MARIA S. MERIAN during cruise MSM99

Multibeam bathymetry raw data using the ship's own Kongsberg EM 712 multibeam echosounder was not continuously recorded during RV MARIA S. MERIAN cruise MSM99. Data was recorded on 16 days between 2021-02-26 and 2021-03-19. This dataset contains 13x survey lines (occasionally with some line crossing perpendicular to the track) in the Baltic Sea and Gulf of Bothnia. The approximate average depth of the entire dataset is around 150m, ranging from 280m to 22m. No ancillary sound velocity profiles (SVP) files from the cruise are added to this dataset. Data analysis of the multibeam raw data revealed that SVP has been changed several during the survey. This publication is conducted within the efforts of the German Marine Research Alliance in the core area 'Data management and Digitalization' (Deutsche Allianz Meeresforschung, DAM). Data are unprocessed and therefore contains incorrect depth measurements (artifacts) without further processing. Note that refraction errors can be expected due to the lack of proper SVP. Overall, it appears that the data quality is rather good since the gridded hillshade data showed relatively few obstacles. Data can be processed e.g. with the open source software package MB-System (Caress et al. 2024, https://doi.org/10.5281/zenodo.6302801).

Photosynthetic efficiency and symbiont cover of Amphistegina lobifera measured by PAM fluorometry and CLSM during a menthol-DCMU bleaching experiment (Nov–Dec 2022, Bremen, Germany)

This dataset contains experimental data from a one-month aquarium-based bleaching experiment conducted on Large Benthic Foraminifera (Amphistegina lobifera) from 16 November to 16 December 2022 at the Marine Experimental Facility of the Leibniz Centre for Tropical Marine Research (ZMT), Bremen, Germany. The aim of the experiment was to obtain symbiont-free A. lobifera individuals for future re-inoculation studies and symbiont switching experiments. The foraminifera were originally collected in May 2022 at the Interuniversity Institute for Marine Sciences (IUI) in Eilat, Israel (29°30'07.8N, 34°55'04.9E) and maintained in culture in Germany until the start of the experiment. To assess the effectiveness of two chemical agents—menthol and 3-(3,4-dichlorophenyl)-1,1-dimethylurea (DCMU)—in disrupting symbiosis, photosynthetic efficiency (measured as maximum quantum yield, Fv/Fm) was recorded every other day during the first week of the experiment using a Pulse-Amplitude-Modulated (PAM) fluorometer. Fv/Fm measurements were discontinued after the first week due to complete inhibition of photosynthesis. Symbiont coverage (%) was assessed on day one and then weekly until week four using Confocal Laser Scanning Microscopy (CLSM).

Multibeam bathymetry raw data (Kongsberg EM 712 transit dataset) of RV MARIA S. MERIAN during cruise MSM98

Multibeam bathymetry raw data was recorded in the North Sea during cruise MSM98 that took place between 2021-01-08 and 2021-01-23. The data was collected using the ship's own Kongsberg EM 712. This data is part of the DAM (German Marine Research Alliance) underway research data project.

Multibeam bathymetry raw data (R2Sonic SONIC 2024 entire dataset) of RV ELISABETH MANN BORGESE during cruise EMB304

Multibeam bathymetry raw data using the ship's own R2Sonic SONIC 2024 Wideband multibeam echosounder was not continuously recorded during RV ELISABETH MANN BORGESE (EMB) cruise EMB304. Data was recorded on 3 separate days (2022-10-25, 2022-10-29, 2017-10-30. This dataset contains a survey in the Baltic Sea. The system settings of the device were set prior to the cruise and data acquisition was not entirely monitored during the survey time. This publication is conducted within the efforts of the German Marine Research Alliance in the core area 'Data management and Digitalization' (Deutsche Allianz Meeresforschung, DAM). This dataset is considered to be a test dataset for the incorporation of data from EMB into PANGAEA. The software QINSy from QPS was used for data recording. Data is stored with the regular QINSy data format .db and the auxiliary .xtf data format. Data are not compatible with the open source software package MB-System (Caress, D. W., and D. N. Chayes, MB-System: Mapping the Seafloor, http://www.mbari.org/products/research-software/mb-system/, 2022), therefore - as up to this publication date – professional software like CARIS HIPS/SIPS or QPS QIMERA is needed the post-process the data. Thus, individual data files could not be georeferenced by reading out the files itself using open-source software. Data files contained empty spaces " " in the file names. All files had to be renamed using underscores "_", since PANGAEA database does not allow the usage of spaces " " in file names. Data are unprocessed and therefore contain incorrect depth measurements (artifacts). Note that refraction errors can be expected due to the lack of accurate sound velocity profiles (SVP). Overall, it appears that the data quality differs. The gridded hillshade from data acquired on 2022-10-25 showed relatively many obstacles at the slant beams (bad data quality). Data acquired on 2022-10-29 show in general relatively less obstacles (very good data quality) with elongated structures on the seafloor without a distinct pattern. Data acquired on 2022-10-30 show in general a few obstacles (moderate data quality).

Multibeam bathymetry raw data (Kongsberg EM 122 entire dataset) of RV MARIA S. MERIAN during cruise MSM85

Multibeam bathymetry raw data was recorded in the Atlantic during cruise MSM85 that took place between 2019-07-23 and 2019-08-13. The data was collected using the ship's own Kongsberg EM 122. This data is part of the DAM (German Marine Research Alliance) underway research data project.

Water column raw data (Kongsberg EM712 entire dataset) of RV MARIA S. MERIAN during cruise MSM98

Water column raw data using the ship's own Kongsberg EM 712 multibeam echosounder was almost continuously recorded during RV MARIA S. MERIAN cruise MSM98. Data was recorded on 15 days between 2021-01-08 and 2021-01-22 located in the North Sea in shallow water. The corresponding .all files are published via https://doi.pangaea.de/10.1594/PANGAEA.937616 and https://doi.pangaea.de/10.1594/PANGAEA.928946 . This publication is conducted within the efforts of the German Marine Research Alliance in the core area 'Data management and Digitalization' (Deutsche Allianz Meeresforschung, DAM).

Pan-Arctic Visualization of Landscape Change (2003-2022), Arctic PASSION Permafrost Service

This raster dataset, in Cloud Optimized GeoTIFF format (COG), provides information on land surface changes at the pan-arctic scale. Multispectral Landsat-5 TM, Landsat-7 ETM+, and Landsat-8 OLI imagery (cloud-cover less than 80%, months July and August) was used for detecting disturbance trends (associated with abrupt permafrost degradation) between 2003 and 2022. For each satellite image we calculated the Tasseled Cap multi-spectral index to translate the spectral reflectance signal to the semantic information Brightness, Greenness, and Wetness. In order to characterize change information, we calculated the linear trend of the Brightness, Greenness and Wetness over two decades on the individual pixel level. The final map product therefore contains information on the direction and magnitude of change for all three Tasseled Cap parameters in 30m spatial resolution across the pan-arctic permafrost domain. Features detected include coastal erosion, lake drainage, infrastructure expansion, and fires. The general processing methodology was developed by Fraser et al. 2014 and adapted and expanded by Nitze et al. 2016 and Nitze et al. 2018. Here we upscaled the processing to the circum-arctic permafrost region and the recent 20-year period from 2003 through 2022. The service covers the permafrost region up to 81° North: Alaska (USA), Canada, Greenland, Iceland, Norway, Sweden, Finland, Russia, Mongolia, and China. For Russia and China, regions not containing permafrost were excluded. The data has been processed in Google EarthEngine within the research projects ERC PETA-CARB, ESA CCI+ Permafrost, NSF Permafrost Discovery Gateway, and EU Arctic PASSION. The dataset is a contribution to the 'Panarctic requirements-driven Permafrost Service' of the Arctic PASSION project (see references). Changes in the Tasseled Cap indices Brightness, Greenness, and Wetness are displayed in the image bands red, green, and blue, respectively. Here, coastal erosion (a trend of a land surface transitioning to a water surface) is depicted in dark blue colors, while coastal accretion (a trend of a water surface transitioning to a land surface) is depicted in bright orange colors. Drained lakes appear in bright yellow or orange colors, depending on the soil conditions and vegetation regrowth. Fire scars are a further common feature, which can appear in different colors, depending on the time of the fire and pre-fire land cover. The data can be explored via the Arctic Landscape EXplorer (ALEX, see references) and is available as a public web map service (WMS, see references), both hosted by Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research.

Pan-Arctic Visualization of Landscape Change (2005-2024), Arctic PASSION Permafrost Service

This raster dataset, in Cloud Optimized GeoTIFF format (COG), provides information on land surface changes at the pan-arctic scale. Multispectral Landsat-5 TM, Landsat-7 ETM+, Landsat-8 OLI, and Landsat-9 OLI-2 imagery (cloud-cover less than 70%, months July and August) was used for detecting disturbance trends (associated with abrupt permafrost degradation) between 2005 and 2024. For each satellite image, we calculated the Tasseled Cap multi-spectral index to translate the spectral reflectance signal to the semantic information Brightness, Greenness, and Wetness. In order to characterize change information, we calculated the linear trend of Brightness, Greenness, and Wetness over two decades at the individual pixel level, based on annually aggregated data. The final map product therefore contains information on the direction and magnitude of change for all three Tasseled Cap parameters at 30 m spatial resolution across the pan-arctic permafrost domain. Features detected include coastal erosion, lake drainage, infrastructure expansion, and fires. The general processing methodology was developed by Fraser et al. (2014) and adapted and expanded by Nitze et al. (2016, 2018). Here, we upscaled the processing to the circum-arctic permafrost region and applied it to the recent 20-year period from 2005 through 2024. The service covers the permafrost region up to 81° North: Alaska (USA), Canada, Greenland, Iceland, Norway, Sweden, Finland, Russia, Mongolia, and China. For Russia and China, regions not containing permafrost were excluded. The data have been processed in Google Earth Engine as part of the research projects ERC PETA-CARB, ESA CCI+ Permafrost, NSF Permafrost Discovery Gateway, and EU Arctic PASSION. The dataset is a contribution to the 'Pan-Arctic Requirements-Driven Permafrost Service' of the Arctic PASSION project (see References). Changes in the Tasseled Cap indices – Brightness, Greenness, and Wetness – are displayed in the image bands red, green, and blue, respectively. Here, coastal erosion (a trend of a land surface transitioning to a water surface) is depicted in dark blue tones, while coastal accretion (a trend of a water surface transitioning to a land surface) is depicted in bright orange colors. Drained lakes are shown in bright yellow or orange colors, depending on the soil conditions and vegetation regrowth. Fire scars are a further common feature, appearing in different colors depending on the time of the fire and the pre-fire land cover. The data can be explored via the Arctic Landscape EXplorer (ALEX; see References) and are available as a public web map service (WMS; see References), both hosted by Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research.

1 2 3 4 5 … 28 29 30