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HeideBench: A Multispectral UAV Time-Series Benchmark for Forest Crown Phenology in Dölauer Heide

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.

Tree Species - Sentinel-1/2 - Germany, 2022

The Tree Species Germany product provides a map of dominant tree species across Germany for the year 2022 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, radar data from Sentinel-1, and a digital elevation model. The input features explicitly incorporate phenological information to capture seasonal vegetation dynamics relevant for species discrimination. A total of over 80,000 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 classification was generated using an XGBoost machine learning algorithm. The Tree Species Germany product achieves an overall F1-score of 0.89. For the dominant species pine, spruce, beech, and oak, class-wise F1-scores range from 0.76 to 0.98, while F1-scores for other widespread species such as birch, alder, larch, Douglas fir, and fir range from 0.88 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.

Physical oceanography during ALKOR cruise AL563

Conductivity-temperature-depth profiles were measured using a ADM-CTD SN MOCNET during RV ALKOR cruise AL563. The CTD was equipped with duplicate sensors for temperature, conductivity and oxygen. The oxygen sensor (galvanic oxygen micro-sensor (AMT)) was exchanged in the beginning of the year. The sensors are used throughout the year and no post-cruise calibration is applied. All other sensors of the CTD are calibrated irregularly. Data were connected to the station book of the specific cruise as available in the DSHIP database.

Timeseries of physical oceanography in the Baltic Sea from 2011-2022

Conductivity-temperature-depth profiles were measured using a CTD during RV ALKOR cruises. The CTD was equipped with duplicate sensors for temperature, conductivity and oxygen. All sensors are calibrated irregularly. Data were connected to the station book of the specific cruise as available in the DSHIP database.

Physical oceanography during ALKOR cruise AL580

Conductivity-temperature-depth profiles were measured using a ADM-CTD SN MOCNET during RV ALKOR cruise AL580. The CTD was equipped with duplicate sensors for temperature, conductivity and oxygen. The oxygen sensor (galvanic oxygen micro-sensor (AMT)) was exchanged in the beginning of the year. The sensors are used throughout the year and no post-cruise calibration is applied. All other sensors of the CTD are calibrated irregularly. Data were connected to the station book of the specific cruise as available in the DSHIP database.

Tree Species - Sentinel-2 - Germany, 2016

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.

IceLines - Sentinel-1 - Antarctica

IceLines (Ice Shelf and Glacier Front Time Series) is an automated calving front monitoring service providing monthly ice shelf front time series of major Antarctic ice shelves. The provided time series allows to discover the dynamics of ice shelf front changes and calving events. The front positions are automatically derived from Sentinel-1 data based on a deep neuronal network called HED-U-Net. The time series covers the timespan 2014 to today (partly limited due to Sentinel-1 data availability). Incorrectly extracted fronts are truncated which might lead to gaps in the time series especially between December to March due to strong surface melt. Annual averages are calculated based on the extracted monthly fronts (excluding the summer months) and provide more robust results due to temporal aggregation

Physical oceanography during ALKOR cruise AL571

Conductivity-temperature-depth profiles were measured using a Seabird SBE 911plus CTD during RV ALKOR cruise AL571. The CTD was equipped with duplicate sensors for temperature (SBE3plus), conductivity (SBE4) and oxygen (SBE43). Temperature, conductivity and oxygen sensors are calibrated by the manufacturer once a year before being mounted in January. They are used throughout the year and no post-cruise or in-situ calibration is applied. All other sensors are calibrated irregularly. Data were connected to the station book of the specific cruise as available in the DSHIP database.

Physical oceanography during ALKOR cruise AL544

Conductivity-temperature-depth profiles were measured using a CTD during RV ALKOR cruise AL544. The CTD was equipped with duplicate sensors for temperature, conductivity and oxygen. All sensors are calibrated irregularly. Data were connected to the station book of the specific cruise as available in the DSHIP database.

Physical oceanography during ALKOR cruise AL509

Conductivity-temperature-depth profiles were measured using a CTD during RV ALKOR cruise AL509. The CTD was equipped with duplicate sensors for temperature, conductivity and oxygen. All sensors are calibrated irregularly. Data were connected to the station book of the specific cruise as available in the DSHIP database.

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