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.
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.
Nach Darstellung der Standortverhaeltnisse im Bereich der ca. 70 noch bestehenden Oberharzer Stauteiche - die zur Versorgung des Harzer Bergbaus mit Wasserkraft angelegt wurden - werden das Artengefuege und die Verbreitung ihrer Pflanzengesellschaften durch Tabellen bzw. Verbreitungskarten erlaeutert. Von einigen Teichen sind Vegetationskarten bzw. -transekte erarbeitet worden. Aspekte der Entwicklung des Teichgebietes bei Aenderung der Nutzung und Vorschlaege fuer die Erhaltung der auch aus kultur- und baugeschichtlicher Sicht wertvollen Anlagen runden die Arbeit ab.
Ziel des Projektes ist die Dokumentation des aktuellen Vorkommens indigener und synanthroper Pflanzensippen im Gebiet Verbreitungskarten in 1/64 Messtischblattraster). Durch Vergleich der aktuellen Verbreitung der Pflanzensippen mit historischen Quellen (Lit., Herb., hist. Karten, Luftbild) soll der Florenwandel dargestellt werden.
Datensammlung zur Verbreitung bzw. Vorkommen epixyler und epipetrischer Flechten im Gebiet von Koeln und Umgebung. Langfristiges Ziel - Erstellung einer Verbreitungskarte dieser Flechten in Abhaengigkeit von Siedlungsdichte und Immissionsbelastung.
Für das Projekt werden insbesondere stenöke oder chorologisch bedeutsame Arten ausgewählt. Bis jetzt sind Verbreitungskarten für über 220 Pilzarten publiziert worden. Ziel ist ein deutschlandweites Bestandsmonitoring für Pilze mit starker standörtlicher oder ökologischer Bindung (Bioindikationsfunktion) und eine Klassifizierung von Verbreitungstypen mitteleuropäischer Pilze.
It is well established that reduced supply of fresh organic matter, interactions of organic matter with mineral phases and spatial inaccessibility affect C stocks in subsoils. However, quantitative information required for a better understanding of the contribution of each of the different processes to C sequestration in subsoils and for improvements of subsoil C models is scarce. The same is true for the main controlling factors of the decomposition rates of soil organic matter in subsoils. Moreover, information on spatial variabilities of different properties in the subsoil is rare. The few studies available which couple near and middle infrared spectroscopy (NIRS/MIRS) with geostatistical approaches indicate a potential for the creation of spatial maps which may show hot spots with increased biological activities in the soil profile and their effects on the distribution of C contents. Objectives are (i) to determine the mean residence time of subsoil C in different fractions by applying fractionation procedures in combination with 14C measurements; (ii) to study the effects of water content, input of 13C-labelled roots and dissolved organic matter and spatial inaccessibility on C turnover in an automatic microcosm system; (iii) to determine general soil properties and soil biological and chemical characteristics using NIRS and MIRS, and (iv) to extrapolate the measured and estimated soil properties to the vertical profiles by using different spatial interpolation techniques. For the NIRS/MIRS applications, sample pretreatment (air-dried vs. freeze-dried samples) and calibration procedures (a modified partial least square (MPLS) approach vs. a genetic algorithm coupled with MPLS or PLS) will be optimized. We hypothesize that the combined application of chemical fractionation in combination with 14C measurements and the results of the incubation experiments will give the pool sizes of passive, intermediate, labile and very labile C and N and the mean residence times of labile and very labile C and N. These results will make it possible to initialize the new quantitative model to be developed by subproject PC. Additionally, we hypothesize that the sample pretreatment 'freeze-drying' will be more useful for the estimation of soil biological characteristics than air-drying. The GA-MPLS and GA-PLS approaches are expected to give better estimates of the soil characteristics than the MPLS and PLS approaches. The spatial maps for the different subsoil characteristics in combination with the spatial maps of temperature and water contents will presumably enable us to explain the spatial heterogeneity of C contents.
SWACI is a research project of DLR supported by the State Government of Mecklenburg-Vorpommern. Radio signals, transmitted by modern communication and navigation systems may be heavily disturbed by space weather hazards. Thus, severe temporal and spatial changes of the electron density in the ionosphere may significantly degrade the signal quality of various radio systems which even may lead to a complete loss of the signal. By providing specific space weather information, in particular now- and forecast of the ionospheric state, the accuracy and reliability of impacted communication and navigation systems shall be improved. According to the pioneer work of Sir E. Appleton the vertical structure of the terrestrial ionosphere may be divided into different layers (D, E, F1, F2) with different physical characteristics. The layers are primarily characterized by its height and peak electron density. The spatial plasma distribution is generated from actual TEC maps by applying a first version of the empirical electron density model NEDM-v1. In correspondence with the update rate of TEC maps the time resolution of the 3 D images is 5 minutes. For details see http://swaciweb.dlr.de/index.php?id=303&L=1 and http://presentations.copernicus.org/EGU2011-7324_presentation.pdf.
The SuK-Nord (INSPIRE) shows the geological distribution of aggregates (sand and gravel) in Northern Germany, especially north of the southernmost maximum of the Scandinavian inland ice sheet (Saalian and Elsterian glaciation). According to the Data Specifications on Mineral Resources (D2.8.III.21) and Geology (D2.8.II.4_v3.0) the content of the map is stored in two INSPIRE-compliant GML files: SuK_Nord_EarthResource_polygon.gml contains the distribution of aggreagtes (sand and gravel) as polygons. SuK_Nord_GeomorphologicFeature.gml contains the southernmost maximum of the Scandinavian inland ice sheet (Saalian and Elsterian glaciation) as lines. The GML files together with a Readme.txt file are provided in ZIP format (SuK_Nord-INSPIRE.zip). The Readme.text file (German/English) contains detailed information on the GML files content. Data transformation was proceeded by using the INSPIRE Solution Pack for FME according to the INSPIRE requirements.
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