Exposure to ultrafine aerosol particles (UFPs) can cause adverse effects on human health, local environment and climate. Air traffic is associated with the emission of high numbers of UFPs, which results in increased UFP number concentrations close to airports. So far, the spatial distribution and variability of UFPs is poorly understood in the atmospheric boundary layer. The uncrewed aerial system (UAS) ALADINA (Application of Lightweight Aircraft for Detecting In-situ Aerosols, e.g. Altstädter et al., 2015) was operated close to the largest airport in Germany at Frankfurt airport (FRA) between 11 and 19 October 2024. The dataset provides airborne in-situ observations of the spatial distribution of aerosol particle number concentration with different sizes and meteorological parameters of temperature, humidity, wind, surface temperature and short-wave irradiance, as well as accurate position and orientation of ALADINA. Data are available from 26 measurement flights, comprising a number of 122 vertical profiles between ground and a maximum altitude of 750 m above mean sea level (ASL) and about 70 horizontal legs at different but constant altitude, e.g. in 100 m altitude intervals. Details about the ALADINA measurements will be provided in a publication (Harm-Altstädter et al., in prep.) soon.
Exposure to ultrafine aerosol particles (UFPs) can cause adverse effects on human health, local environment and climate. Air traffic is associated with the emission of high numbers of UFPs, which results in increased UFP number concentrations close to airports. So far, the spatial distribution and variability of UFPs is poorly understood in the atmospheric boundary layer. The uncrewed aerial system (UAS) ALADINA (Application of Lightweight Aircraft for Detecting In-situ Aerosols, e.g. Altstädter et al., 2015) was operated close to the largest airport in Germany at Frankfurt airport (FRA) between 11 and 19 October 2024. The dataset provides airborne in-situ observations of the spatial distribution of aerosol particle number concentration with different sizes and meteorological parameters of temperature, humidity, wind, surface temperature and short-wave irradiance, as well as accurate position and orientation of ALADINA. Data are available from 26 measurement flights, comprising a number of 122 vertical profiles between ground and a maximum altitude of 750 m above mean sea level (ASL) and about 70 horizontal legs at different but constant altitude, e.g. in 100 m altitude intervals. Details about the ALADINA measurements will be provided in a publication (Harm-Altstädter et al., in prep.) soon.
In den Planungshinweiskarten werden die bioklimatischen Belastungen innerhalb der einzelnen Stadtteile dargestellt und entsprechende Planungsempfehlungen gegeben. Die Planungshinweiskarten sind als Instrument konzipiert, um eine klimaökologische Bewertung von Flächen zu ermöglichen und so die Lebensqualität im urbanen und ländlichen Raum im Hinblick auf menschliche Gesundheit und gesunde Lebensbedingungen zu verbessern. Sie berücksichtigen insbesondere die Wechselwirkungen zwischen Klima, Umwelt und den jeweiligen Nutzungskategorien. Im „Wirkraum“ (urbaner Raum) erfolgt die Bewertung der thermischen Belastung auf Grundlage der bodennahen Lufttemperatur sowie der Physiologisch Äquivalenten Temperatur (PET), die die Wärmebelastung im Außenraum misst. Während die UHI (Urban Heat Island) in der Nacht einen wesentlichen Aspekt darstellt, spielt tagsüber die gefühlte Temperatur (PET) eine zentrale Rolle. Daher wird zwischen der thermischen Belastung am Tag und in der Nacht unterschieden. Der „Ausgleichsraum“ umfasst Grün- und Freiflächen, landwirtschaftliche Flächen und Wälder, die unabhängig von Siedlungsflächen anhand ihres Kaltluftpotenzials bewertet werden. In den Bewertungs- und Planungshinweiskarten wird jedoch insbesondere ihre stadtklimatische Funktion hervorgehoben, insbesondere ihre Rolle für den nächtlichen Kaltlufthaushalt sowie ihre Empfindlichkeit gegenüber Nutzungsänderungen. Für die bioklimatische Bedeutung der Flächen im Ausgleichsraum wird zwischen der Belastung am Tag und in der Nacht über die UHI-Werte unterschieden, da die Effekte hierrüber am deutlichsten sichtbar werden.
We present HeideBench, a very-high-resolution multispectral uncrewed aerial vehicle dataset for forest crown phenology collected over a forest patch in Dölauer Heide, Halle (Saale), Germany. Dölauer Heide is currently dominated by pine plantations (Kiefernforste), which cover the largest area but are increasingly affected by dieback, while its potential natural vegetation is sessile oak–hornbeam forest rich in small-leaved lime (Albrecht et al., 1993). In addition to these pine stands, the area contains near-natural mixed deciduous forests with oaks, birches, and beeches, making it a particularly relevant setting for observing seasonal canopy development under contrasting forest structures and ongoing ecological transition. Against this background, HeideBench provides repeated observations of the same forest patch through the growing season. The dataset contains 18 georeferenced multispectral GeoTIFF orthomosaics acquired between 6 March 2025 and 5 November 2025, spanning a 244-day seasonal period from early spring to late autumn. The acquisitions have a median revisit interval of 14 days, with intervals ranging from 4 to 27 days, and an average ground sampling distance of 5.53 cm per pixel. The valid imaging footprint covers approximately 32.1 ha and is bounded by 11.902653–11.911325°E and 51.499959–51.508576°N. Data were collected using a DJI Mavic 3M Enterprise uncrewed aerial vehicle equipped with four multispectral cameras measuring green (560 nm), red (650 nm), red-edge (730 nm), and near-infrared (860 nm) reflectance, in that order. Flights used a real-time kinematic (RTK) positioning module for centimeter-level geolocation, and all data are provided in coordinate reference system EPSG:25832. Imagery was processed with Agisoft Metashape 2.3.1 to generate calibrated multispectral orthomosaics. The dataset further includes 5,885 crop-safe individual tree crown instance segmentations over the same footprint, extracted with the DeepTrees software package (Khan et al., 2025). HeideBench is intended to support crown-centric analyses of seasonal canopy development, temporal representation learning, phenology-aware feature extraction, and the evaluation of tree crown delineation under seasonal change. HeideBench is a result of the Dynamic Platform Project titled "PhenoEmbed: Multispectral UAV AI Embeddings for phenology-aware tree crown delineation" of the Integration Platform 1: "Sustainable future land use" (IP1) at the Helmholz Centre for Environmental Research (UFZ) in Leipzig, Germany.
Exposure to ultrafine aerosol particles (UFPs) can cause adverse effects on human health, local environment and climate. Air traffic is associated with the emission of high numbers of UFPs, which results in increased UFP number concentrations close to airports. So far, the spatial distribution and variability of UFPs is poorly understood in the atmospheric boundary layer. The uncrewed aerial system (UAS) ALADINA (Application of Lightweight Aircraft for Detecting In-situ Aerosols, e.g. Altstädter et al., 2015) was operated close to the largest airport in Germany at Frankfurt airport (FRA) between 11 and 19 October 2024. The dataset provides airborne in-situ observations of the spatial distribution of aerosol particle number concentration with different sizes and meteorological parameters of temperature, humidity, wind, surface temperature and short-wave irradiance, as well as accurate position and orientation of ALADINA. Data are available from 26 measurement flights, comprising a number of 122 vertical profiles between ground and a maximum altitude of 750 m above mean sea level (ASL) and about 70 horizontal legs at different but constant altitude, e.g. in 100 m altitude intervals. Details about the ALADINA measurements will be provided in a publication (Harm-Altstädter et al., in prep.) soon.
Mit Hilfe dieser Daten können besonders stark aufgeheizte Stadtteile genauso wie kühlere, klimatisch ausgeglichenere Zonen identifiziert werden. Der Urban Heat Island (UHI)-Effekt beschreibt das Phänomen, dass sich der städtische Raum gegenüber den umliegenden ländlichen Regionen vermehrt aufheizt. Dieser Effekt ist vor allem im Sommer und in der Nacht deutlicher ausgeprägt und kann negative Auswirkungen auf die Gesundheit und das Wohlbefinden der städtischen Bevölkerung haben. Die vermehrte Wärmeansammlung im städtischen Gebiet ist von verschiedenen Faktoren abhängig. Dabei spielt u.a. der Anteil an Bebauung, Bodenversiegelung, der Begrünungsgrad, die verwendeten Baumaterialien und anthropogene Wärmeerzeugung eine wichtige Rolle. Aufgrund der deutlicheren Ausprägung dieses Überwärmungseffekts in der Nacht sind die UHI-Daten in zwei Kategorien unterteilt: UHI-Index am Tag und UHI-Index in der Nacht. Der UHI-Index wird in Kelvin angegeben und beschreibt den Unterschied zwischen städtischen und ländlichen Temperaturen.
The high-resolution digital surface model (DSM1, DOM1) of the watercourses Elbe and Lower Havel is based on the airborne laser scanning data, undertaken from 06 January 2022 to 18 March 2022 in the Elbe area and from 20 to 22 December 2021 in the Havel area. It was produced and published by Germany’s Federal Institute of Hydrology (BfG), on behalf of the River Basin Community Elbe (RBC Elbe, FGG Elbe). The work was supported by the German Federal Waterways and Shipping Administration (WSV) and the surveying offices and water management administrations of six German states - Saxony, Saxony-Anhalt, Brandenburg, Lower Saxony, Mecklenburg-Vorpommern and Schleswig-Holstein. The data cover both the area around the inland water stretches of the Elbe from the Czech-German border to the village of Zollenspieker (part of the city of Hamburg) and the Lower Havel waterway from the town of Rathenow to its confluence with the Elbe. Since the dataset has a large coverage of 4,043 km², it is split into 62 sections. They were either labelled *HW in case of flood relevant areas (in German: “hochwasser-relevante Gebiete”) or *AU in case of historical floodplains (in German: “Altauengebiete”). Financing was divided according to these categories: In the HW areas, the project was co-funded by BfG, the WSV and the federal states, while in the AU areas, BfG covered all project costs. For each section we provide hillshade (*HS) and height maps (*NHN). The data are available in a raster resolution of 1 meter in GeoTiff format; Coordinate reference frame: ETRS89.DREF91.R16; Coordinate projection: UTM Zone 33N; EPSG-Code: 25833; Height reference system: DHHN2016, national vertical reference frame in Germany (2022). For further information please contact us. Citation short: BfG et al. / i.A. FGG Elbe (2025)
This dataset contains high-resolution (5 cm/pixel) orthomosaics and digital elevation models (DEMs) from unoccupied aerial vehicle (UAV) surveys of biogenic structures in the German Wadden Sea. Two Pacific oyster reefs (Kaiserbalje, Nordland) and one blue mussel bed (Nordstrand) were monitored between 2020 and 2022. The data, processed via structure from motion (SfM) and georeferenced, are provided as raster files (*.tiff), ready for GIS analysis. The Random Forest (RF) classification shapefiles support the mapping of biogenic structures. This dataset facilitates research on biogenic structure growth, sediment dynamics, and geomorphological processes in intertidal environments
Exposure to ultrafine aerosol particles (UFPs) can cause adverse effects on human health, local environment and climate. Air traffic is associated with the emission of high numbers of UFPs, which results in increased UFP number concentrations close to airports. So far, the spatial distribution and variability of UFPs is poorly understood in the atmospheric boundary layer. The uncrewed aerial system (UAS) ALADINA (Application of Lightweight Aircraft for Detecting In-situ Aerosols, e.g. Altstädter et al., 2015) was operated close to the largest airport in Germany at Frankfurt airport (FRA) between 11 and 19 October 2024. The dataset provides airborne in-situ observations of the spatial distribution of aerosol particle number concentration with different sizes and meteorological parameters of temperature, humidity, wind, surface temperature and short-wave irradiance, as well as accurate position and orientation of ALADINA. Data are available from 26 measurement flights, comprising a number of 122 vertical profiles between ground and a maximum altitude of 750 m above mean sea level (ASL) and about 70 horizontal legs at different but constant altitude, e.g. in 100 m altitude intervals. Details about the ALADINA measurements will be provided in a publication (Harm-Altstädter et al., in prep.) soon.
Exposure to ultrafine aerosol particles (UFPs) can cause adverse effects on human health, local environment and climate. Air traffic is associated with the emission of high numbers of UFPs, which results in increased UFP number concentrations close to airports. So far, the spatial distribution and variability of UFPs is poorly understood in the atmospheric boundary layer. The uncrewed aerial system (UAS) ALADINA (Application of Lightweight Aircraft for Detecting In-situ Aerosols, e.g. Altstädter et al., 2015) was operated close to the largest airport in Germany at Frankfurt airport (FRA) between 11 and 19 October 2024. The dataset provides airborne in-situ observations of the spatial distribution of aerosol particle number concentration with different sizes and meteorological parameters of temperature, humidity, wind, surface temperature and short-wave irradiance, as well as accurate position and orientation of ALADINA. Data are available from 26 measurement flights, comprising a number of 122 vertical profiles between ground and a maximum altitude of 750 m above mean sea level (ASL) and about 70 horizontal legs at different but constant altitude, e.g. in 100 m altitude intervals. Details about the ALADINA measurements will be provided in a publication (Harm-Altstädter et al., in prep.) soon.
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