1 to 3 of 3 Results
Apr 26, 2024
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
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... |
Oct 12, 2021
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... |