API src

Found 291 results.

Related terms

Multibeam bathymetry processed data (Kongsberg EM 2040 working area dataset) of RV ALKOR during cruise AL628, east of Little Belt, Baltic Sea

Multibeam bathymetry processed data (EM 2040 multibeam echosounder) of RV ALKOR during cruise AL628 in the Baltic Sea. The raw data (.kmall) were processed using QPS Qimera software (v 2.6), based on the following workflow: 0.Raw data > 1.Apply correct Sound Velocity Profiles -> 2.Create dynamic surface (shallow Mode) -> 3.Apply Spline Filter (Medium/Strong) > 4. Finalize with manual 2D and 3D editing, -> 5.Export in GeoTIFF format and projected in the UTM32N coordinate system (EPSG:32632). The produced rasters are named AL628_EM2040_'working area'_'resolution in cm'. The bathymetry dataset here is gridded at 0.25 m and 0.50 m resolution. The data products were created in the context of the DAM (German Marine Research Alliance), CONMAR research project.

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).

Wege zur Unterstützung einer nachhaltigen Entwicklung im pazifischen Ozean: ein integrierter Ansatz

Basierend auf der Bedeutung des SDG 14 für die pazifischen Inselstaaten (PICs) zielt unser Projekt - PACPATH - darauf ab, kostengünstige, effiziente und nachhaltige transdisziplinäre Prozesse, Methoden und Netzwerke zu etablieren, die es Stakeholdern wie Wissenschaftlern, Indigenen und zivilen Organisationen der PICs erlauben gemeinsame Ziele und Maßnahmen zur Erreichung der ökologischen Nachhaltigkeit zu teilen.In diesem Antrag schlagen wir vor, ein pazifisches Stakeholder-Netzwerk aufzubauen, welches sich auf zwei Pilotstandorte, Fidschi und Neukaledonien, stützt und die Auswirkungen des Klimawandels und anderer Stressfaktoren auf die Meeresumwelt und Ökosystemleistungen, sowie die Folgen für Gesellschaft, Wirtschaft und die Erreichung der SDGs untersucht. Diese Pilotstandorte werden den Rahmen und die Methodik schaffen und als Leitfaden für die Anwendung und Anpassung an andere interessierte PICs dienen.Der PACPATH-Arbeitsplan, sowie die internationale Zusammenarbeit auf Grundlage von Transdisziplinarität, Kompetenz und Fachwissen des Konsortiums werden es ermöglichen, starke Mehrwertergebnisse zu erzielen. Dies beinhaltet die Analyse der Bedeutung von SDG14 („Erhaltung und nachhaltige Nutzung der Ozeane, Meere und Meeresressourcen für eine nachhaltige Entwicklung“) für die Pazifikinseln. Es wird zudem die Verknüpfung von SDG14 mit den anderen SGDs, vor allem 13 und 15, quantifizieren, indem eine Vielzahl verschiedener akademischer bis lokaler Wissensformen integriert werden. PACPATH wird direkte und indirekte Indikatoren und interaktive Indikatorinstrumente unter Einbeziehung lokaler, nationaler und regionaler Interessengruppen, Umwelt- und Sozialwissenschaftler, Ökonomen und operativer Zentren (national und international) zusammenstellen. Im Rahmen des Co-Construction-Prozesses werden die Informationen, Ziele und transdisziplinären Fachkenntnisse ermittelt, die für den Aufbau von Forschungskapazitäten, die partizipative Forschung und die Erfassung / Definition von Indikatoren erforderlich sind. Abschließend wird das Projekt Strategien für die künftige Aufrechterhaltung des PACPATH-Netzwerks entwickeln, welche auf langfristigen Finanzierungsmöglichkeiten und nachhaltigen Strukturen beruhen.

Unterwegsdaten-2, Vorhaben: Akquise, Prozessierung, Archivierung und Veröffentlichung von ADCP-, Unterwegs- und Forschungsmissionsdaten

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