1 to 10 of 64 Results
Dec 7, 2023 - Carbon Cycle Group
Maier, Fabian; Levin, Ingeborg; Hammer, Samuel; Conil, Sébastien; Preunkert, Susanne, 2023, "14C-based ΔffCO2 estimates for Heidelberg and OPE and input data for the Rhine Valley ffCO2 inversion (2019-2020)", https://doi.org/10.11588/data/GRSSBN, heiDATA, V1
These data files show the Δ14CO2, CO2 and CO measurements as well as the 14C-based ΔffCO2 estimates of the flask samples collected in Heidelberg (HEI, 2019-2020) and at the ICOS site Observatoire pérenne de l'environnement (OPE, Sep. 2020 - Mar. 2021). Moreover, modelled ΔffCO2 a... |
Jan 15, 2020 - 3D Spatial Data Processing
Herfort, Benjamin; Anders, Katharina; Marx, Sabrina; Eberlein, Stefan; Höfle, Bernhard, 2020, "3D Micro-Mapping of Subsidence Stations [Source Code and Data]", https://doi.org/10.11588/data/OU8YA1, heiDATA, V1
This dataset comprises the source code to reproduce the 3D micro-mapping tool for plane adjustment at subsidence stations. In this project, users adjust a plane (height and orientation) at the positions of fixed poles, so-called subsidence stations, to provide information on the... |
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... |
Data publications of the 3D Spatial Data Processing Group at the Institute of Geography at Heidelberg University. |
Aug 4, 2017 - 3D Spatial Data Processing
Herfort, Benjamin; Eberlein, Stefan, 2017, "3D-MAPP: 3D-MicroMapping of Big 3D Geo-Datasets in the Web", https://doi.org/10.11588/data/Y4V85F, heiDATA, V1
The research project 3D-MAPP develops a web-based methodology to obtain digital geodata via the combination of data analysis by human and machine. Through a quick and easy-to-use 3D Web visualization users are able – in a few seconds – to solve 3D micro mapping tasks, which can h... |
Schmithüsen, Dominik; Chambers, Scott; Fischer, Bernd; Gilge, Stefan; Hattaka, Juha; Kazan, Victor; Neubert, Rolf; Paatero, Jussi; Ramonet, Michel; Schlosser, Clemens; Schmid, Sabine; Vermeulen, Alex; Levin, Ingeborg, 2017, "A European-wide 222Radon and 222Radon progeny comparison study [Dataset]", https://doi.org/10.11588/data/10098, heiDATA, V2
Although atmospheric 222Radon (222Rn) activity concentration measurements are currently performed world-wide, they are being made by many different laboratories and with fundamentally different measurement principles, so compatibility issues can limit their utility for regional-t... |
Nov 4, 2022 - Biogeochemistry
Einzmann, Teresa; Schroll, Moritz; Kleint, Jan Frederik; Greule, Markus; Keppler, Frank, 2022, "Application of concentration and 2-dimensional stable isotope measurements of methane to constrain sources and sinks in a seasonally stratified freshwater lake [data]", https://doi.org/10.11588/data/KLFDVF, heiDATA, V1, UNF:6:v5med6vrABS01PP8hfg5JQ== [fileUNF]
Methane (CH4) emissions from aquatic systems have recently been comprised to account for up to 50 % of global CH4 emissions, with lakes representing one of the largest CH4 source within this pool. However, there is large uncertainty associated with CH4 emissions from freshwater e... |
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... |
Mar 13, 2023
Data publications from the Project Belspo GEN-EX |
