Other language confidence: 0.7284133078524662
The 12th Sternfahrt of the ElbeXtreme and MOSES projects took place in 2024 from September 02 to 13, within the area of the German Bight (North Sea). Its objective was to get a more systematic grid of sampling data by spatially integrated onboard sensors. Therefore, the MOSES-laboratory container was installed again. Water samples were taken from the surface with a rosette or via Niskin bottles. The first part of the cruise was conducted by the research vessel (RV) Ludwig Prandtl, starting on the 2nd of September on Heligoland. From there, the crew navigated towards Cuxhaven covering some stations from previous MOSES cruises. For the next days, the ship followed a rectangular track, shifting northward each day, heading towards Heligoland again. Due to strong winds, the sampling stations were reduced to three on the last day. On Heligoland the RV Mya II took over the laboratory container and other sampling equipment for the second part of the cruise. Persistent strong winds delayed the start of the cruise until September 11. Since most of the planned stations were already covered from the RV Ludwig Prandtl, the crew decided to expand the sampling area using a more systematic zig-zag line. With the return of Mya II in the afternoon of the 13th September 2024, the campaign was successfully finished.
Dieser Datensatz enthält Informationen zur Flussmessstelle Nr. 2200 in Lahn, Solms-Oberbiel, Messstation. Auf der Webseite zur Messstelle ist ein Link zum Herunterladen der Rohdaten vorhanden.
This product displays the Cloud Optical Thickness (COT) around the globe. Clouds play a crucial role in the Earth's climate system and have significant effects on trace gas retrievals. The cloud optical thickness is retrieved from the O2-A band using the ROCINN algorithm. The TROPOMI instrument aboard the SENTINEL-5P space craft is a nadir-viewing, imaging spectrometer covering wavelength bands between the ultraviolet and the shortwave infra-red. TROPOMI's purpose is to measure atmospheric properties and constituents. It is contributing to monitoring air quality and providing critical information to services and decision makers. The instrument uses passive remote sensing techniques by measuring the Top Of Atmosphere (TOA) solar radiation reflected by and radiated from the earth and its atmosphere. The four spectrometers of TROPOMI cover the ultraviolet (UV), visible (VIS), Near Infra-Red (NIR) and Short Wavelength Infra-Red (SWIR) domains of the electromagnetic spectrum, allowing operational retrieval of the following trace gas constituents: Ozone (O3), Nitrogen Dioxide (NO2), Sulfur Dioxide (SO2), Formaldehyde (HCHO), Carbon Monoxide (CO) and Methane (CH4). Within the INPULS project, innovative algorithms and processors for the generation of Level 3 and Level 4 products, improved data discovery and access technologies as well as server-side analytics for the users are developed.
Global Cloud Fraction (CF). Clouds play a crucial role in the Earth's climate system and have significant effects on trace gas retrievals. The radiometric cloud fraction is retrieved from the UV using the OCRA algorithm. Daily observations are binned onto a regular latitude-longitude grid. The TROPOMI instrument aboard the SENTINEL-5P space craft is a nadir-viewing, imaging spectrometer covering wavelength bands between the ultraviolet and the shortwave infra-red. TROPOMI's purpose is to measure atmospheric properties and constituents. It is contributing to monitoring air quality and providing critical information to services and decision makers. The instrument uses passive remote sensing techniques by measuring the Top Of Atmosphere (TOA) solar radiation reflected by and radiated from the earth and its atmosphere. The four spectrometers of TROPOMI cover the ultraviolet (UV), visible (VIS), Near Infra-Red (NIR) and Short Wavelength Infra-Red (SWIR) domains of the electromagnetic spectrum, allowing operational retrieval of the following trace gas constituents: Ozone (O3), Nitrogen Dioxide (NO2), Sulfur Dioxide (SO2), Formaldehyde (HCHO), Carbon Monoxide (CO) and Methane (CH4). Within the INPULS project, innovative algorithms and processors for the generation of Level 3 and Level 4 products, improved data discovery and access technologies as well as server-side analytics for the users are developed.
Aerosol Index (AI) as derived from TROPOMI observations. AI is an indicator for episodic aerosol plumes from dust outbreaks, volcanic ash, and biomass burning. The TROPOMI instrument onboard the Copernicus SENTINEL-5 Precursor satellite is a nadir-viewing, imaging spectrometer that provides global measurements of atmospheric properties and constituents on a daily basis. It is contributing to monitoring air quality and climate, providing critical information to services and decision makers. The instrument uses passive remote sensing techniques by measuring the top of atmosphere solar radiation reflected by and radiated from the earth and its atmosphere. The four spectrometers of TROPOMI cover the ultraviolet (UV), visible (VIS), Near Infra-Red (NIR) and Short Wavelength Infra-Red (SWIR) domains of the electromagnetic spectrum. The operational trace gas products generated at DLR on behave ESA are: Ozone (O3), Nitrogen Dioxide (NO2), Sulfur Dioxide (SO2), Formaldehyde (HCHO), Carbon Monoxide (CO) and Methane (CH4), together with clouds and aerosol properties. This product is created in the scope of the project INPULS. It develops (a) innovative retrieval algorithms and processors for the generation of value-added products from the atmospheric Copernicus missions Sentinel-5 Precursor, Sentinel-4, and Sentinel-5, (b) cloud-based (re)processing systems, (c) improved data discovery and access technologies as well as server-side analytics for the users, and (d) data visualization services.
Soil physical-biogeochemical analyses were carried out on profiles NEP1, NEP2 and NEP3. Soil TC and TN were determined by CNS analysis, and total organic carbon (TOC) was determined by the difference between total inorganic carbon (TIC) and TC. Carbonate (CaCO₃) content was measured volumetrically using a Calcimeter and on air-dried, sieved (< 2 mm) and ground (ball mill) samples. The pH-values were measured on samples of profiles NEP1, NEP2, NEP3, which had less than 2% CaCO₃ content. Stable isotope ratios of δ¹³C and δ¹⁵N were analysed for the differentiation of C3 and C4 plants and the cultivation of legumes. The analyses were performed on air-dried, sieved (< 2mm) and ground (ball mill) samples. For ¹³C analysis, the soil samples were decarbonised with 10% HCl. In the field, separate samples were collected for the NEP1 and NEP2 profiles (28 samples in total) for analysis of urease activity and microbial biomass carbon (Cmic). Samples were stored at -18°C. Urease activity (enzyme analysis) is used to provide information on the input of urea and animal excrement. The mutual relationship between urease and Cmic was used to show and understand the past and present input of urea into the soil.
The Tree Species Germany product provides a map of dominant tree species across Germany for the year 2016 at a spatial resolution of 10 meters. The map depicts the distribution of ten tree species groups derived from multi-temporal optical Sentinel-2 data. The input features explicitly incorporate phenological information to capture seasonal vegetation dynamics relevant for species discrimination. A total of over 100,000 training and test samples were compiled from publicly accessible sources, including urban tree inventories, Google Earth Pro, Google Street View, and field observations. The final product was created by majority-voting on annual XGBoost Sentinel-2 tree species classifications (2016–2024) and filtering with forest structure data. If no clear majority vote was achieved, the class uncertain was assigned. The Tree Species Germany 2016 product achieves an overall F1-score of 0.95. For the dominant species pine, spruce, beech, and oak, class-wise F1-scores range from 0.92 to 0.99, while F1-scores for other widespread species such as birch, alder, larch, Douglas fir, fir, and other deciduous species range from 0.85 to 0.96. The product provides a consistent, high-resolution, and up-to-date representation of tree species distribution across Germany. Its transferable, cost-efficient, and repeatable methodology enables reliable large-scale forest monitoring and offers a valuable basis for assessing spatial patterns and temporal changes in forest composition in the context of ongoing climatic and environmental dynamics.
Dieser Datensatz enthält Informationen zur Flussmessstelle Nr. 2100 in Main, Bischofsheim, Messstation rechtes Ufer. Auf der Webseite zur Messstelle ist ein Link zum Herunterladen der Rohdaten vorhanden.
To investigate subsurface features in the Lower Havel River floodplain, we conducted Electrical Resistivity Tomography (ERT) transects and Electromagnetic Induction (EMI) surveys at three different depths in 2023 and 2024. These near surface geophysical methods were complemented by 24 driving core drillings to relate the electrical properties with sedimentological characteristics. Additionally, five selected sediment cores were used for subsequent geochemical lab analyses (grain size, CNS, TOC, TIC). Electromagnetic induction (EMI) was measured with a CMD-Mini Explorer (GF Instruments s.r.o., Brno, Czech Republic) in June 2023 and June 2024. We used the vertical dipole (VDP) at coil spacings of 0.32 m (VDP1), 0.71 m (VDP2) and 1.18 m (VDP3), archieving effective penetration depths of 0.5 m (VDP1), 1.0 m (VDP2) and 1.8 m (VDP3). According to the manufacturer, 70% of the signal originate from above these depths. The EMI sensors measure the apparent electrical conductivity (ECa, in mS/m). Measurements were taken by carrying the instrument about 0.2 m above ground while being directly connected to D-GPS (Leica GPS1200) for positioning. The acquisition rate was five measurements per second. Data quality was checked by measuring a reference line before and after each measurement. The area investigated by EMI in June 2023 is located to the north and northeast of the Gülpe research station. It has a total area of 12.3 ha. The reference line was located in the southern part of the study area. No drift correction had to be applied due to good data quality. Reference lines and single outliers were removed. The area investigated by EMI in June 2024 is located southeast of the research station. The survey area there is 8.1 ha in size. The reference line for the measurements there was located in the north-westernmost area of the site. No drift correction had to be applied due to good data quality. Reference lines and single outliers were removed. The Electrical Resistivity Tomography (ERT) data were acquired by using a PC controlled DC resistivity meter system (RESECS, Geoserve, Kiel, Germany). In total, we measured four ERT transects. Two transects in June 2023, where transect 1 had a total length of 259 m with an electrode spacing of 0.5 m and transect 2 had a total length of 223 m with an electrode spacing of 1 m. The measurements in 2023 were carried out under extreme dry conditions. Two further transects were measured in June 2024 with an electrode spacing of 1m, transect 3 with a total length of 207 m and transect 4 with a total length of 239 m. We applied wenner alpha and dipol-dipol configuration. The coordinates and the height of the electrodes were measured with a D-GPS (2023: TOPCON HiPer II / 2024: Leica GPS1200). Sediment cores were recovered using a hand-held Cobra Pro (Atlas Copco) core drilling system with a 60 mm diameter open corer. One-meter segments were retrieved and assessed in the field for sedimentological features, including estimations of grain size, carbonate content, humus content, and redox features (AG Boden 2005, 2024). Colour descriptions were carried out using the Munsell Soil Color Chart. The exact positions of the drilling points were recorded using a differential GPS device (TOPCON HiPer II). The cores were photographed, documented and sampled at 5–10 cm intervals for subsequent laboratory analyses. Bulk samples from five selected cores (RK1, RK3, RK13, RK15, RK17) were freeze-dried, sieved (2 mm), and weighed. Total carbon (TC), total nitrogen (TN), and total sulfur (TS) contents were measured using a CNS analyzer (Vario EL cube, Elementar). Inorganic carbon (TIC) was determined using calcimeter measurements (Scheibler method, Eijkelkamp). Organic carbon (TOC) was calculated as TOC = TC − TIC. For the grain size analyses, sediment samples were first sieved to <2 mm and subsamples of 10 g were treated with 50 ml of 35% hydrogen peroxide (H₂O₂) and gently heated to remove organic matter. Following this, 10 ml of 0.4 N sodium pyrophosphate solution (Na₄P₂O₇) was added to disperse the particles, and the suspension was subjected to ultrasonic treatment for 45 minutes. The sand fraction was analysed by dry sieving and classified into four size classes: coarse sand (2000–630 µm), medium sand (630–200 µm), fine sand (200–125 µm), and very fine sand (125–63 µm). Finer fractions were determined using X-ray granulometry (XRG) with a SediGraph III 5120 (Micromeritics). These included coarse silt (63–20 µm), medium silt (20–6.3 µm), fine silt (6.3–2.0 µm), coarse clay (2.0–0.6 µm), medium clay (0.6–0.2 µm), and fine clay (<0.2 µm).
This vector dataset is based on a 10 m resolution raster dataset that shows forest canopy cover loss (FCCL) in Germany at a monthly resolution from September 2017 to October 2025. Results at pixel level were aggregated at municipality, district, and federal state level. For the results at administrative level we differentiate between deciduous and coniferous forests. We use the stocked area map 2018 (Langner et al. 2022, https://doi.org/10.3220/DATA20221205151218 ) as a reference forest mask. We differentiate between deciduous and coniferous forests by intersecting the stocked area map with a tree species map (Blickensdoerfer et al. 2024). Pixels of the classes birch, beech, oak, alder, deciduous trees with long lifespan and deciduous trees with short lifespan were classified as deciduous forest and pixels of the classes Douglas fir, spruce, pine, larch and fir as coniferous forest. The coverage of the two datasets is not identical, which is why a few areas of the forest reference map remained unclassified. These were filled with the dominant leaf type map of the Copernicus Land Monitoring Service (CLMS 2025). Therefore, the vector data at administrative level contains information about unclassified forest areas and the total forest area as the sum of deciduous, coniferous, and unclassified forests. The FCCL confidence at pixel level is lowest at the end of the time series because the number of repeated threshold exceedance is used as a criterion to record forest canopy cover losses. Therefore, we excluded August 2024 through October 2025 from the annual and overall statistics and summarized the respective FCCL as additional attribute. The dataset provides an update of the assessment in Thonfeld et al. (2026).
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