Laser scanning point clouds of forest stands were acquired in southwest Germany in 2019 and 2020 from different platforms: an aircraft, an uncrewed aerial vehicle (UAV) and a ground-based tripod. The UAV-borne and airborne laser scanning campaigns cover twelve forest plots of approximately 1 ha. The plots are located in mixed central European forests close to Bretten and Karlsruhe, in the federal state of Baden-Württemberg, Germany. Terrestrial laser scanning was performed in selected locations within the twelve forest plots. Airborne and terrestrial laser scanning point clouds were acquired under leaf-on conditions, UAV-borne laser scans were acquired both under leaf-on and later under leaf-off conditions. In addition to the laser scanning campaigns, forest inventory tree properties (species, height, diameter at breast height, crown base height, crown diameter) were measured in-situ during summer 2019 in six of the twelve 1-ha plots. Single tree point clouds were extracted from the different laser scanning datasets and matched to the field measurements. For each tree entry, point clouds, tree species, position, and field-measured and point cloud-derived tree metrics are provided. For 249 trees, point clouds from all three platforms are available. The tree models form the basis of a single tree database covering a range of species typical for central European forests which is currently being established in the framework of the SYSSIFOSS project.
Vorangegangene Forschungsarbeiten konzentrierten sich auf die generelle Eignung von CRNS für das Monitoring von Schneewasserressourcen in Gebirgsregionen. Laserscanning-Messungen und Monte-Carlo-Neutronensimulationen an einem alpinen Standort im Kaunertal (Österreich) zeigten das Vorhandensein eines schneebezogenen Neutronen-Signals sogar für Schneemengen von bis zu 600 mm Wasseräquivalent der Schneedecke (SWE). Es konnte gezeigt werden, dass die Heterogenität der Schneewassergehalts bei vollständiger Schneebedeckung im Messbereich keinen Einfluss hat. Bei partiell schneefreiem Messbereich verändert sich jedoch das CRNS-Signal. Zu den aktuellen Forschungslücken gehört die Übertragbarkeit der oben genannten Ergebnisse auf (1) andere Standorte, (2) unterschiedliche Klima- und Vegetationszonen und (3) dynamische Bodenfeuchtebedingungen. In der zweiten Phase von Cosmic Sense sind Messungen in verschiedenen Klimazonen entlang von Höhengradienten geplant, um diese Aspekte abzudecken und die Abschätzung von SWE aus dem CRNS-Signal zu verbessern. Die Verwendung von Höhentransekten ermöglicht es, unterschiedliche SWE-Mengen und variierende Bedingungen mit einer Kampagne abzudecken, d.h. von Grasland über bewaldete Gebiete und alpine Wiesen bis hin zu Zonen mit spärlicher Vegetation. Alpine Standorte in Österreich mit steilen Umweltgradienten werden durch eine Kaskade von tiefer gelegenen voralpinen, Mittelgebirgs- und Tieflandstandorten in Deutschland ergänzt, die von Hydrological Modelling (HG), Vegetation (VG), Smart Coverage (SC) und Root Zone (RZ) betrieben und intensiv beobachtet werden. Die kontinuierlichen stationären Feldmessungen sollen durch kampagnenbasierte mobile Messungen in Zusammenarbeit mit Roving & Airborne (RA) ergänzt werden. Laserscanning-basierte Schneedeckenbeobachtungen und terrestrische Fotografie liefern dabei Referenzdaten zur räumlichen Verteilung von SWE und Schneebedeckung. Die gewonnenen Daten werden genutzt, um in Zusammenarbeit mit Neutron Simulations (NS) Modellierungen des Neutronentransports aufzusetzen, um allgemein gültige Ergebnisse abzuleiten. Insbesondere bilden sowohl die Feldmessungen als auch die schneebezogenen Neutronentransport-Simulationen die Grundlage für die Entwicklung des SWE-Vorwärtsoperators in enger Zusammenarbeit mit NS und HM. Schließlich werden spezifische gemeinsame Feldkampagnen zusammen mit HM und RA zur Validierung der Ergebnisse genutzt. Die Wechselwirkungen zwischen Vegetation, Schnee und Bodenfeuchte in der Wurzelzone werden zusammen mit VG und RZ analysiert. Die alpinen Standorte ermöglichen zudem auch die Erprobung von Prototypen im Rahmen von Detector Development (DD) unter alpinen Bedingungen.
Video transects were done using the A.IKANBILISTM hovering autonomous underwater vehicle (HAUV) of the company BeeX (https://beex.sg/a-ikanbilis/), which flew over the reefs along predefined transects at a depth of 0.5m above seabed and at a speed of 1 m s-1. From the dive videos of the HAUV, SBIs were extracted every second. Each SBI features two parallel laser lines 30 cm away from each other. The camera used was a GoPro, the videos and pictures were taken perpendicularly to the seabed. The seabed images provide insights into the general composition of key species, higher systematic groups and ecological guilds. The images contain information on how benthic species are associated to each other. Transect files include individual images, whereas metadata of each image includes diving depth, date/time of transect. Geographical coordinates and time of individual images is unavailable, images have a resolution of 300dpi and a size of 9 to 13 MB.
Video transects were done using the A.IKANBILISTM hovering autonomous underwater vehicle (HAUV) of the company BeeX (https://beex.sg/a-ikanbilis/), which flew over the reefs along predefined transects at a depth of 0.5m above seabed and at a speed of 1 m s-1. From the dive videos of the HAUV, SBIs were extracted every 5 seconds. SBIs, each SBI features two parallel laser lines 25 cm away from each other. The camera used was a GoPro, the videos and pictures were taken perpendicularly to the seabed. The seabed images provide insights into the general composition of key species, higher systematic groups and ecological guilds. The images contain information on how benthic species are associated to each other. Transect files include individual images, whereas metadata of each image includes diving depth, date/time of transect. Geographical coordinates of some individual images is unavailable, images have a resolution of 300dpi and a size of 7 to 13 MB.
Dieser Datensatz enthält die Straßenbreiten im Freiburger Stadtgebiet, von Bordsteinunterkante zu Bordsteinunterkante, dargestellt als Breitenlinien. Die Straßenbreiten wurden aus den 3D-Punktwolken der Befahrung des Frühjahr 2024 automatisiert abgeleitet, indem die Unterkante der Bordsteine auf beiden Straßenseite identifiziert und lokalisiert wurden. An den Stellen, an denen auf einer oder beiden Seiten der Bordstein nicht identifiziert werden konnte, erfolgte keine Breitebestimmung. Die automatisierte Ableitung wurde nicht manuell nachgearbeitet. Bei groben Verschmutzungen am Fahrbahnrand, Bordsteinabsenkungen, ggf. parkenden Autos und verschiedenem "Straßenmobiliar" (z.B. Poller) kann es daher sein, dass ein "falscher Bordstein" identifiziert wurde und es daher zu einer fehlerhaften Breitebestimmung kam. Wir empfehlen daher die gleichzeitige Einblendung von Luftbildern um eine schnelle Einordnung der Bestimmung vorzunehmen.
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).
This dataset contains geochemical variables measured in six depth profiles from ombrotrophic peatlands in North and Central Europe. Peat cores were taken during the spring and summer of 2022 from Amtsvenn (AV1), Germany; Drebbersches Moor (DM1), Germany; Fochteloër Veen (FV1), the Netherlands; Bagno Kusowo (KR1), Poland; Pichlmaier Moor (PI1), Austria and Pürgschachen Moor (PM1), Austria. The cores AV1, DM1 and KR1 were taken using a Wardenaar sampler (Royal Eijkelkamp, Giesbeek, the Netherlands) and had diameter of 10 cm. The cores FV1, PM1 and PI1 had an 8 cm diameter and were obtained using an Instorf sampler (Royal Eijkelkamp, Giesbeek, the Netherlands). The cores FV1, DM1 and KR1 were 100 cm, core AV1 was 95 cm, core PI1 was 85 cm and core PM1 was 200 cm. The cores were subsampeled in 1 cm (AV1, DM1, KR1, FV1) and 2 cm (PI1, PM1) sections. The subsamples were milled after freeze drying in a ballmill using tungen carbide accesoires. X-Ray Fluorescence (WD-XRF; ZSX Primus II, Rigaku, Tokyo, Japan) was used to determine Al (μg g-1), As (μg g-1), Ba (μg g-1), Br (μg g-1), Ca (g g-1), Cl (μg g-1), Cr (μg g-1), Cu (μg g-1), Fe (g g-1), K (g g-1), Mg (μg g-1), Mn (μg g-1), Na (μg g-1), P (μg g-1), Pb (μg g-1), Rb (μg g-1), S (μg g-1), Si (μg g-1), Sr (μg g-1), Ti (μg g-1) and Zn (μg g-1). These data were processed and calibrated using the iloekxrf package (Teickner & Knorr, 2024) in R. C, N and their stable isotopes were determined using an elemental analyser linked to an isotope ratio mass spectrometer (EA-3000, Eurovector, Pavia, Italy & Nu Horizon, Nu Instruments, Wrexham, UK). C and N were given in units g g-1 and stable isotopes were given as δ13C and δ15N for stable isotopes of C and N, respectively. Raw data C, N and stable isotope data were calibrated with certified standard and blank effects were corrected with the ilokeirms package (Teickner & Knorr, 2024). Using Fourier Transform Mid-Infrared Spectroscopy (FT-MIR) (Agilent Cary 670 FTIR spectromter, Agilent Technologies, Santa Clara, Ca, USA) humification indices (HI) were determined. Spectra were recorded from 600 cm-1 to 4000 cm-1 with a resolution of 2 cm-1 and baselines corrected with the ir package (Teickner, 2025) to estimate relative peack heights. The HI (no unit) for each sample was calculated by taking the ratio of intensities at 1630 cm-1 to the intensities at 1090 cm-1. Bulk densities (g cm-3) were estimated from FT-MIR data (Teickner et al., in preparation).
This dataset contains geochemical variables measured in six depth profiles from ombrotrophic peatlands in North and Central Europe. Peat cores were taken during the spring and summer of 2022 from Amtsvenn (AV1), Germany; Drebbersches Moor (DM1), Germany; Fochteloër Veen (FV1), the Netherlands; Bagno Kusowo (KR1), Poland; Pichlmaier Moor (PI1), Austria and Pürgschachen Moor (PM1), Austria. The cores AV1, DM1 and KR1 were taken using a Wardenaar sampler (Royal Eijkelkamp, Giesbeek, the Netherlands) and had diameter of 10 cm. The cores FV1, PM1 and PI1 had an 8 cm diameter and were obtained using an Instorf sampler (Royal Eijkelkamp, Giesbeek, the Netherlands). The cores FV1, DM1 and KR1 were 100 cm, core AV1 was 95 cm, core PI1 was 85 cm and core PM1 was 200 cm. The cores were subsampeled in 1 cm (AV1, DM1, KR1, FV1) and 2 cm (PI1, PM1) sections. The subsamples were milled after freeze drying in a ballmill using tungen carbide accesoires. X-Ray Fluorescence (WD-XRF; ZSX Primus II, Rigaku, Tokyo, Japan) was used to determine Al (μg g-1), As (μg g-1), Ba (μg g-1), Br (μg g-1), Ca (g g-1), Cl (μg g-1), Cr (μg g-1), Cu (μg g-1), Fe (g g-1), K (g g-1), Mg (μg g-1), Mn (μg g-1), Na (μg g-1), P (μg g-1), Pb (μg g-1), Rb (μg g-1), S (μg g-1), Si (μg g-1), Sr (μg g-1), Ti (μg g-1) and Zn (μg g-1). These data were processed and calibrated using the iloekxrf package (Teickner & Knorr, 2024) in R. C, N and their stable isotopes were determined using an elemental analyser linked to an isotope ratio mass spectrometer (EA-3000, Eurovector, Pavia, Italy & Nu Horizon, Nu Instruments, Wrexham, UK). C and N were given in units g g-1 and stable isotopes were given as δ13C and δ15N for stable isotopes of C and N, respectively. Raw data C, N and stable isotope data were calibrated with certified standard and blank effects were corrected with the ilokeirms package (Teickner & Knorr, 2024). Using Fourier Transform Mid-Infrared Spectroscopy (FT-MIR) (Agilent Cary 670 FTIR spectromter, Agilent Technologies, Santa Clara, Ca, USA) humification indices (HI) were determined. Spectra were recorded from 600 cm-1 to 4000 cm-1 with a resolution of 2 cm-1 and baselines corrected with the ir package (Teickner, 2025) to estimate relative peack heights. The HI (no unit) for each sample was calculated by taking the ratio of intensities at 1630 cm-1 to the intensities at 1090 cm-1. Bulk densities (g cm-3) were estimated from FT-MIR data (Teickner et al., in preparation).
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