API src

Found 1624 results.

Similar terms

s/sma/UMA/gi

Other language confidence: 0.5492432372685484

Flächen für Saatmuschelgewinnungsanlagen im Nationalpark Schleswig-Holsteinisches Wattenmeer 2017

Der Datensatz beinhaltet die in der naturschutzrechlichen Erlaubnis der Nationalparkverwaltung genehmigten Flächen für die Saatmuschelgewinnungsanlagen durch Hängekultur

Flächen für Saatmuschelgewinnungsanlagen im Nationalpark Schleswig-Holsteinisches Wattenmeer 2021/03

Der Datensatz beinhaltet die in der naturschutzrechlichen Erlaubnis der Nationalparkverwaltung genehmigten Flächen für die Saatmuschelgewinnungsanlagen durch Hängekultur

Flächen für Saatmuschelgewinnungsanlagen im Nationalpark Schleswig-Holsteinisches Wattenmeer 2020

Der Datensatz beinhaltet die in der naturschutzrechlichen Erlaubnis der Nationalparkverwaltung genehmigten Flächen für die Saatmuschelgewinnungsanlagen durch Hängekultur

Geomorphografische Auswertungen BB

Die Serie beinhaltet Daten des LBGR über Geomorphografische Auswertungen Brandenburgs und umfasst eine Sammlung geomorphometrischer und geomorphografischer Ableitungen, die aus dem Digitalen Höhenmodell (DGM2 mit Bodenauflösung 2 x 2 m Rasterweite; Höhenauflösung von +/- 20 - 50 cm) für Brandenburg berechnet wurden. 1. Lokale Parameter: Hangneigung, Exposition, Divergenz-Konvergenz Index; 2. Komplexe Parameter: Höhe über Tiefenlinie (dicht), Höhe über Tiefenlinie (ausgedünnt), Tiefenlinien (dicht), Tiefenlinien (ausgedünnt), Kulminationslinien, Höhe unter Kulminationslinie, Potentieller Bodenfeuchteindex, Multiresolution Index for Valley Bottom Flatness; 3. Kombinierte Parameter: Scheitelbereichsindex, Terrain Classification Index for Lowlands; 4. Geomorphografische Karten: Reliefeinheiten 1, Reliefeinheiten 2 (glaziale Hochflächen undifferenziert), Reliefeinheiten 2 (glaziale Hochflächen differenziert), Senkenbereiche (klassifiziert), Geschlossene Hohlformen.

INSPIRE Elevation / GMK: Potentieller Bodenfeuchteindex BB

Der interoperable INSPIRE-Datensatz beinhaltet Daten vom LBGR über den Bodenfeuchteindex in Brandenburg, zugeordnet in das INSPIRE-Zielschema Höhenlage. Der Datensatz wird über je einen interoperablen Darstellungs- und Downloaddienst bereitgestellt. --- The compliant INSPIRE data set contains data about the soil moisture index in the State of Brandenburg from the LBGR, assigned to the INSPIRE target schema Elevation. The data set is provided via a compliant view and download service.

Potentieller Bodenfeuchteindex BB

Der Datensatz beinhaltet Daten des LBGR über den Bodenfeuchteindex und wird über je einen Darstellungs- und Downloaddienst bereitgestellt. Der Bodenfeuchteindex stellt ein dimensionsloses Maß für die potenziellen, reliefbedingten Feuchteverhältnisse des Bodens dar. Er quantifiziert die potenzielle Wasserabflussmenge in Abhängigkeit von der Einzugsgebietsgröße (potentieller Abfluss) und der Neigung (Verweildauer des abfließenden Wassers).

Internationale Quartärkarte von Europa 1:2.500.000 (IQE2500) - Blatt 13 Rabat

Die Idee, das Quartär Europas in einer Karte darzustellen, wurde erstmals 1932 auf dem 2. Kongress der INQUA (International Union for Quaternary Research) in Leningrad (St. Petersburg) diskutiert. Im Jahre 1995, also über 50 Jahre später, wurde unter Federführung der INQUA schließlich die Internationale Quartärkarte von Europa 1 : 2 500 000 (IQE2500) von der Bundesanstalt für Geowissenschaften und Rohstoffe (BGR) fertig gestellt. Die gemeinschaftlich von der BGR und INQUA herausgegebene Karte bildet verschiedene quartäre Einheiten wie Endmoränen, Grundmoränen, Kames, Drumlins, Oser und Eisrandlagen ab. Zusätzlich sind die Richtungen der Eisbewegungen, Grenzen der marinen Transgressionen und tektonische Störungen eingetragen. Bedeutende Typlokalitäten der Quartärforschung, bathymetrische Linien und die rezente Sedimentverteilung am Meeresboden werden ebenfalls dargestellt. Die Legende auf jedem der 14 Kartenblätter ist in Deutsch und, in Anhängigkeit des abgebildeten Territoriums, in Englisch, Französisch oder Russisch. Auf Blatt 15 findet sich die Generallegende für das gesamte Kartenwerk.

Colored dissolved organic matter (CDOM) absorption coefficients in the sea-surface microlayer and the underlying water during a mesocosm phytoplankton bloom in 2023

The effects of a phytoplankton bloom and photobleaching on colored dissolved organic matter (CDOM) in the sea-surface microlayer (SML) and the underlying water (ULW) were studied in a month-long mesocosm study, in May and June of 2023, at the Institute for Chemistry and Biology of the Marine Environment (ICBM) in Wilhelmshaven, Germany. The mesocosm study was conducted by the DFG research group BASS (Biogeochemical processes and Air–sea exchange in the Sea-Surface microlayer, Bibi et al., 2025) in the Sea Surface Facility (SURF) of the ICBM. The facility contains an 8 m × 1.5 m × 0.8 m large outdoor basin with a retractable roof, which was closed at night and during rain events. The basin was filled with North Sea water from the adjacent Jade Bay. Homogeneity of the ULW in the basin was achieved by constant mixing of the water column. The daily SML and ULW samples were collected alternating in the morning, about 1 h after sunrise, and in the afternoon, about 10 h after sunrise. The alternation of sampling times intended to capture a potential effect of sun-exposure duration on DOM transformations and elucidated the day and night variability of the layers. The SML was collected via glass plate sampling (Cunliffe and Wurl, 2014). The ULW was sampled via a submerged tube and a connected syringe suction system in 0.4 m depth. The removed sample volume was refilled with Jade Bay water every day. SML and ULW samples were filtered through pre-flushed 0.7 µm Whatman GF/F and 0.2 nucleopore filters into brown bottles and were stored dark and at 4 °C until measurement within weeks of the study. The brown bottles were previously combusted at 500 °C. CDOM was measured with three liquid waveguide capillary cells (LWCC, WPI, USA) of different pathlengths (10 cm, 50 cm, 250 cm) to increase the measurement sensitivity following the protocols of Röttgers et al. (2024) using a spectral detector (Avantes, Netherlands) for a total spectral range from 230 to 750 nm. A sodium chloride (NaCl) solution was used for the salinity correction. The blank-corrected absorbance spectra were then converted into Napierian absorption coefficients (Bricaud et al., 1981).

Wissenschaftlich-technische Untersuchungen zu Sicherheitsaspekten neuer Reaktoren und Reaktorkonzepte

PARAFAC components and fluorescent dissolved organic matter (FDOM) indices on organic matter transformation processes in the sea-surface microlayer and the underlying water during a mesocosm phytoplankton bloom in 2023

The effects of a phytoplankton bloom and photobleaching on colored dissolved organic matter (CDOM) in the sea-surface microlayer (SML) and the underlying water (ULW) were studied in a month-long mesocosm study, in May and June of 2023, at the Institute for Chemistry and Biology of the Marine Environment (ICBM) in Wilhelmshaven, Germany. The mesocosm study was conducted by the DFG research group BASS (Biogeochemical processes and Air–sea exchange in the Sea-Surface microlayer, Bibi et al., 2025) in the Sea Surface Facility (SURF) of the ICBM. The facility contains an 8 m × 1.5 m × 0.8 m large outdoor basin with a retractable roof, which was closed at night and during rain events. The basin was filled with North Sea water from the adjacent Jade Bay. Homogeneity of the ULW in the basin was achieved by constant mixing of the water column. The daily SML and ULW samples were collected alternating in the morning, about 1 h after sunrise, and in the afternoon, about 10 h after sunrise. The alternation of sampling times intended to capture a potential effect of sun-exposure duration on DOM transformations and elucidated the day and night variability of the layers. The SML was collected via glass plate sampling (Cunliffe and Wurl, 2014). The ULW was sampled via a submerged tube and a connected syringe suction system in 0.4 m depth. The removed sample volume was refilled with Jade Bay water every day. SML and ULW samples were filtered through pre-flushed 0.7 µm Whatman GF/F and 0.2 nucleopore filters into clear 40 ml SUPELCO bottles. These bottles were acid-washed twice and combusted at 500 °C for 5 h. The samples were stored dark and at 4 °C and measured within a few months of the study. FDOM was measured using a Aqualog fluorescence spectrometer (Horiba Scientific, Japan) with 10 seconds integration time and high gain of the CCD (charge-coupled device) sensor within an excitation range from 240 to 500 nm, and an emission range from 209.15 to 618.53 nm. The Aqualog measures fluorescence as well as absorption. The resulting data includes an excitation-emission-matrix (EEM) of the blank (MilliQ Starna cuvette), an EEM of the sample, and the absorption values of the sample. The raw exported Aqualog data was corrected for errors and lamp shifts. The corrected EEM data is then decomposed by PARAFAC (Murphy et al., 2013) for its underlying fluorophore components. Before running the PARAFAC routine, the corrected data needed to undergo a correction process by subtracting the blank from the sample EEM and canceling the influences of the inner-filter effect (IFE, Parker & Rees, 1962; Kothawala et al., 2013). The fluorescence intensity of the IFE-corrected EEM is calibrated by using the Raman scatter peak of water (Lawaetz & Stedmon, 2009). For PARAFAC the corrected data was processed using the drEEM and NWAY toolbox (version 0.6.5; Murphy et al., 2013) in MATLAB (R2020b). A 4-component model was validated with the validation style S4C6T3 for the split half analysis with nonnegativity constraints and 1-8e as the convergence criteria with 50 random starts and a maximum number of 2500 iterations. The resulting final model had a core consistency of 82.04 and the explained percentage was 99.54%. Furthermore, four fluorescence indices were calculated from the corrected EEM data (HIX – Humification index, Zsolnay et al., 1999; BIX – Biological index, Huguet et al., 2009; REPIX – Recently produced index, Parlanti et al., 2000, Drozdowska et al., 2015; ARIX, Murphy, 2025).

1 2 3 4 5161 162 163