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Found 35 results.

Digital surface model of the watercourses Elbe and Lower Havel (Germany), DGM-W Elbe project, DOM Elbe 2022

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)

Digital terrain model of the watercourses Elbe and Lower Havel (Germany), DGM-W Elbe 2022 project

The high-resolution digital terrain model (DTM) of the waterways Elbe and Lower Havel (DGM-W Elbe 2022) comprises both the terrain on land and the bottom of rivers, channels and lakes. 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), height maps (*NHN), slope (*sl) and source flags (*sc). The data are available as GeoTIFF-files (resolution 1 meter); 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)

openSenseMap: Sensor Box RSS_outdoor

Sensebox der Rudolf Steiner Schule Siegen.

Eifel Flood 2021 - Airborne Laser Scanning (ALS) and Orthophoto Data

The GFZ Potsdam HART (Hazard and Risk Team) in cooperation with the DFG research training group 2043 NatRiskChange at Potsdam University has enabled the acquisition of Airborne Laser Scanning (ALS) and high-resolution optical data which were acquired between 22 September 2021 and 24 October 2021 by the Milan Geoservice company, Spremberg, Germany. This data acquisition took place in the Eifel regions of North Rhine-Westphalia (NRW) and Rhineland-Palatinate (RLP), which were hit by the 14 July 2021 precipitation event leading to widespread severe inundations, flash floods and caused around 185 victims and massive damage to settlements, river geometry and other geomorphic features. The high-resolution ALS and optical data acquisitions aimed at the documentation and quantification of the extent of flood related changes and destructions as well as their reappraisal before diffusion erases traces. Thus, the generated data are valuable for forensic event analysis and future attempts on flood forecasting and warning in the context of scientific and practical purposes.

Surface and subsurface characterisation of salt pans

This data collection bundles six datasets about the surface, subsurface and environmental conditions of saltpans that express polygonal patterns in their surface salt crust that are fully described in Lasser et al., 2020 (https://doi.org/10.5194/essd-2020-86). Information stems from 5 field sites at Badwater Basin and 21 field sites at Owens Lake – both in central California, US. All data was recorded during two field campaigns, from between November and December, 2016, and in January 2018. (1) Lasser, J., Goehring, L. (2020a). Grain size distributions of sand samples from Owens Lake and Badwater Basin in central California, collected in 2016 and 2018. PANGAEA - Data Publisher for Earth & Environmental Science. https://doi.org/10.1594/PANGAEA.910996 (2) Lasser, J., Goehring, L. (2020b): Subsurface salt concentration profiles and pore water density measurements from Owens Lake, central California, measured in 2018 (Version 2). PANGAEA, https://doi.org/10.1594/PANGAEA.922264 (3) Lasser, J., Goehring, L., Nield, J. M. (2020). Images and Videos from Owens Lake and Badwater Basin in central California, taken in 2016 and 2018 [Data set]. PANGAEA - Data Publisher for Earth & Environmental Science. https://doi.org/10.1594/PANGAEA.911054 (4) Lasser, J., Karius, V. (2020). Chemical characterization of salt samples from Owens Lake and Badwater Basin, central California, collected in 2016 and 2018. PANGAEA - Data Publisher for Earth & Environmental Science. https://doi.org/10.1594/PANGAEA.911239 (5) Nield, J. M., Lasser, J., Goehring, L. (2020). TLS surface scans from Owens Lake and Badwater Basin, central California, measured in 2016 and 2018 [Data set]. PANGAEA - Data Publisher for Earth & Environmental Science. https://doi.org/10.1594/PANGAEA.911233 (6) Nield, J. M., Lasser, J., Goehring, L. (2020): Temperature and humidity time-series from Owens Lake, central California, measured during one week in November 2016 (Version 2). Max Planck Institute for Dynamics and Self-Organization, PANGAEA, https://doi.org/10.1594/PANGAEA.922231

openSenseMap: Sensor Box RoS-back

Hausrückseite, 4. Stock, Innenhof

openSenseMap: Sensor Box RSS_Schueler_3

openSenseMap: Sensor Box RSS_Schueler_9

openSenseMap: Sensor Box RSS_Schueler_1

openSenseMap: Sensor Box RSS_Schueler_5

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