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Apr 26, 2024 - GIScience / Geoinformatics Research Group
Schultz, Michael; Li, Hao; Wu, Zhaoyhan; Wiell, Daniel; Auer, Michael; Zipf, Alexander, 2024, "OpenStreetMap land use for Europe "Research Data"", https://doi.org/10.11588/data/IUTCDN, heiDATA, V1
OSMLanduse data is a scientific dataset generated within the scope of the Horizon 2020 - LandSense project. It is a classification of Sentinel-2 imagery using a deep learning model trained on OSM landuse and landcover features. The data might contain errorneous classifications. T... |
Apr 17, 2023 - GIScience / Geoinformatics Research Group
Knoblauch, Steffen; Li, Hao; Lautenbach, Sven; Elshiaty, Yara; Rocha, Antônio A. de A.; Resch, Bernd; Arifi, Dorian; Jänisch, Thomas; Ivonne Morales; Zipf, Alexander, 2023, "Semi-supervised water tank detection to support vector control of emerging infectious diseases transmitted by Aedes Aegpyti [Research Data]", https://doi.org/10.11588/data/7LLXFP, heiDATA, V1
WATER TANK DETECTION MODEL OF JOURNAL PAPER (Semi-supervised water tank detection to support vector control of emerging infectious diseases transmitted by Aedes Aegypti) The disease transmitting mosquito Aedes Aegypti is an increasing global threat. It breeds in small artificial... |
Jul 21, 2022 - 3D Spatial Data Processing
Shinoto, Maria; Doneus, Michael; Haijima, Hideyuki; Weiser, Hannah; Zahs, Vivien; Kempf, Dominic; Daskalakis, Gwydion; Höfle, Bernhard; Nakamura, Naoko, 2022, "3D Point Cloud from Nakadake Sanroku Kiln Site Center, Japan: Sample Data for the Application of Adaptive Filtering with the AFwizard", https://doi.org/10.11588/data/TJNQZG, heiDATA, V2
This data set represents 3D point clouds acquired with LiDAR technology and related files from a subregion of 150*436 sqm in the ancient Nakadake Sanroku Kiln Site Center in South Japan. It is a densely vegetated mountainous region with varied topography and vegetation. The data... |
Li, Hao; Zech, Johannes; Ludwig, Christina; Fendrich, Sascha; Shapiro, Aurelie; Schultz, Michael; Zipf, Alexander, 2021, "Automatic mapping of national surface water with OpenStreetMap and Sentinel-2 MSI data using deep learning [Research Data]", https://doi.org/10.11588/data/AAKAF9, heiDATA, V1
DATASET FOR JOURNAL PAPER (https://doi.org/10.1016/j.jag.2021.102571) Large-scale mapping activities can benefit from the vastly increasing availability of earth observation (EO) data, especially when combined with volunteered geographical information (VGI) using machine learning... |
Ritter, Simon; Leberecht, Kerstin; Eschenröder, Julian; Scholz, Christian, 2021, "Hells Bells project - results of sampling campaign in February 2020", https://doi.org/10.11588/data/GYLDH5, heiDATA, V2, UNF:6:1Ua7KESTWxO3lRrcac/mWQ== [fileUNF]
This data set compiles the results of water chemical analyses as well as bulk chemical analyses of the particles suspended in the water columns of cenotes (sinkholes) obtained during a sampling campaign in Mexico in February 2020. Three stratified cenotes from North-Eastern Yucat... |
Isenbeck-Schröter, Margot; Ritter, Simon Michael, 2020, "Datensatz zum Verbundprojekt GeoSpeicher.bw: Geothermische Speicherung in Baden-Württemberg", https://doi.org/10.11588/data/GLQLSH, heiDATA, V1, UNF:6:yuWXTkgSzO/g/grDjaWLDg== [fileUNF]
Datensatz zu Abschlussbericht des Verbundprojekts GeoSpeicher.bw: Geothermische Speicherung in Baden-Württemberg Teilprojekt Heidelberg: Einfluss der Einspeicherung von Wärme im oberflächennahen Aquifer auf die Hydrogeochemie des Aquifers (Geospeicher.HD) |
