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Biota

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From 1 - 10 / 74
  • Standorte der Gehegewildhalter im Landkreis Diepholz

  • Digital surface model of the islands Sylt and Roem from the aerial flight 2003. Colour depth 16-bit, ground resolution 100cm, height accuracy 10cm, reference system Gauss-Krüger zone 3.

  • Standorte der Schafhalter im Landkreis Diepholz

  • This product consists of global gap free Leaf area index (LAI) time series, based on MERIS full resolution Level 1B data. It is produced as a series of 10-day composites in geographic projection at 300m spatial resolution. The processing chain comprises geometric correction, radiometric correction and pixel identification, LAI calculation with the BEAM MERIS vegetation processor, re-projection to a global grid, and temporal aggregation selecting the measurement closest to the mean value. After the LAI pre-processing we applied time series analysis to fill data gaps and filter outliers using the technique of harmonic analysis in combination with mean annual and multiannual phenological data. Data gaps are caused by clouds, sensor limitations due to the solar zenith angle (less than 10 degrees), topography and intermittent data reception. We applied our technique for the whole period of observation (Jul 2002 - Mar 2012). Validation, was performed using VALERI and BigFoot data.

  • Description: Spatial distribution of selected macrozoobenthic species in the German Bight. Data source: Data from environmental impact assessments (EIA) under the permit procedures of the Federal Maritime and Hydrographic Agency (BSH) in the North Sea EEZ and research data of the Alfred Wegener Institute (AWI), Helmholtz Centre for Polar and Marine Research; time period: 1997 to 2011, mainly spring and autumn data (EIA data), but also summer and winter data (AWI data) Sampling standards: Data of EIAs follow the standard investigation concept StUK 1-3 (BSH 2007), AWI data collected in accordance with the ICES sampling standard (Rumohr 1999). Sampling gears: mainly van Veen grabs (0.1 square metre, 30-95 kg), few stations by box corer (0.1 square metre, 160 kg), Nephrops norvegicus and Goneplax rhomboides sampled by beam trawl and dredge (1-3 m width) Sampling: 1-3 replicates per station, fixation in 4 % buffered formalin seawater solution, dredge and beam-trawl data recorded on board or subsamples frozen stored, abundance and biomass (g wet weight) per species Data analysis: science information system of benthic invertebrate data, examination of quality and plausibility, data harmonisation, product computation by AWI Product description: Grid: 5x5 km² for grab data, 10x10 square kilometre for data on N. norvegicus and G. rhomboides from beam trawl and dredge hauls; available selectable parameter: number of stations, minimum, maximum, mean, median and standard deviation of density (m-2) per species; classification method: natural jenks (Jenks Caspall algorithm), Note: The products contain a different classification of species density! Note: Please regard different value ranges! Rumohr, H. (1999). "Soft bottom macrofauna: Collection, treatment, and quality assurance of samples." ICES Techniques in Environmental Sciences, No. 27: 1-19. BSH (2007): Standard "Investigation of the Impacts of Offshore Wind Turbines on the Marine Environment (StUK 3)", Hamburg. For more information, please visit: https://gdi.bsh.de/en/data/Benthos-Density_Information_Benthos_Dichte_DE.pdf

  • Description: Spatial distribution of selected demersal fish species in the German Bight. Data source: Data from environmental impact assessments (EIA) under the permit procedures of the Federal Maritime and Hydrographic Agency (BSH) in the North Sea EEZ and research data of the Alfred Wegener Institute (AWI), Helmholtz Centre for Polar and Marine Research; time period: 2000 to 2014, mainly spring and autumn data (EIA data), but also summer and winder data (AWI data) Sampling standards: Data of EIAs follow the standard investigation concept StUK 1-3 (BSH 2007), AWI data mainly collected in accordance with the ICES sampling standard (Rumohr 1999). Sampling gears: EIA-data with 7-8 m (partly 6 m) beam trawl (haul: 15 min), AWI-data with a 2-3 m beam trawl (haul: 5-15 min); trawling speed 3-4 kn, codend mesh size 10 mm Sampling: 1 haul per station and sampling date, data were recorded on board or subsamples were stored frozen for further analysis, analysis of abundance and biomass (kg wet weight) per species Data analysis: science information system of demersal fish data, examination of quality and plausibility, data harmonisation, product computation by AWI Product description: Grid: 10x10 km²; available selectable parameter: number of stations, minimum, maximum, mean, median and standard deviation of density (km-²) per species; classification method: natural jenks (Jenks Caspall algorithm); Note: The products contain a different classification of species density! Note: Please regard different value ranges! Note: Data refer exclusively to demersal fish species spectrum! Cited literature Rumohr, H. (1999). "Soft bottom macrofauna: Collection, treatment, and quality assurance of samples." ICES Techniques in Environmental Sciences, No. 27: 1-19. BSH (2007): Standard Investigation of the Impacts of Offshore Wind Turbines on the Marine Environment (StUK 3), Hamburg.

  • This product is a vector file of the districts of the Paraguayan Chaco. It contains information on the forest cover within each district for the years 1986 until 2020. Hence, this product aggregates the information of 34 annual forest maps of the Paraguayan Chaco to a district level and provides the basis for further analysis as conducted in the following publication: https://doi.org/10.3390/f13010025

  • The product shows tree canopy cover loss in Germany between January 2018 and April 2021 at monthly temporal and 10 m spatial resolution. The basic principle behind this map is to compute monthly composites of the disturbance index (DI, Healey et al. 2005), a spectral index sensitive to forest disturbance, from all available Sentinel-2 and Landsat-8 data with less than 80 % cloud cover. These monthly composites are then compared to a median composite of the DI for 2017, which serves as a reference. After applying a threshold to the difference image, the time series of detected losses is checked for consistency. Only losses recorded continuously in all observations of a pixel until the end of the time series are considered. The dataset does not differentiate between the drivers of the losses. It depicts areas of natural disturbances (windthrow, fire, droughts, insect infestation) as well as sanitation and salvage logging, and regular forest harvest. The full description of the method and results can be found in Thonfeld et al. (2022).

  • The product contains information of tree canopy cover loss in Germany per district (Landkreis) between January 2018 and April 2021 at monthly temporal resolution. The information is aggregated at from the 10 m spatial resolution Sentinel-2 and Landsat-based raster product (Tree Canopy Cover Loss Monthly - Landsat-8/Sentinel-2 - Germany, 2018-2021). The method used to derive this product as well as the mapping results are described in detail in Thonfeld et al. (2022). The map depicts areas of natural disturbances (windthrow, fire, droughts, insect infestation) as well as sanitation and salvage logging, and regular forest harvest without explicitly differentiating these drivers. The vector files contain information about tree canopy cover loss area per forest type (deciduous, coniferous, both) and per year (2018, 2019, 2020, January-April 2021, and January 2018-April 2021) in absolute numbers and in percentages. In addition, the vector files contain the district area and the total forest area per district.

  • The dataset is based on an analysis combining Sentinel-1 (SAR), -2 (Multispectral) and GEDI (Global Ecosystem Dynamics Investigation, LiDAR) data to model vegetation structure information. The derived products show high-spatial resolution maps (10 m) of total canopy cover (cover density in %), Foliage height diversity (Fhd) index in meter, Plant area index (Pai) in meter and canopy height (rh95) in meter.

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