https://researchdata.se/en/catalogue Search results en This data contains the digital elevation models with 0.5 m resolution and polyline shapefiles with the location of channels from the 12 study areas used in this study. It also has the scripts to generate the datasets used to train the machine learning model to classify channels into ditches and streams, and calculate the hydrological indices. The code to train the model is also included, along with the models obtained. For the ground truth data, the channels were mapped differently based on their type: ditches were manually digitized based on the visual analysis of some topographic indices and orthophotos obtained from the DEM. Streams were mapped by initially detecting all natural channel heads, then tracing the downstream channels, and finally manually editing them based on orthophotos. We recommend using Docker to set the environment. Tue, 23 Jun 2026 08:38:56 GMT https://researchdata.se/en/catalogue/dataset/2025-170 https://researchdata.se/en/catalogue/dataset/2025-170 Swedish University of Agricultural Sciences Mariana Busarello William Lidberg Anneli Ågren Florian Westphal From August 9 - September 19, 2025, the icebreaker Oden carried out an expedition with the Canadian icebreaker CCGS Louis S. St-Laurent to map the seabed in the Arctic Ocean, which took place within the framework of the UNCLOS program (United Nations Convention on the Law of the Sea). In symbiosis with this, an extensive Early Career Scientist program also took place on board, consisting of the course The Arctic Ocean Climate System. Mon, 16 Feb 2026 15:16:51 GMT https://researchdata.se/en/catalogue/dataset/2025-249 https://researchdata.se/en/catalogue/dataset/2025-249 Swedish Polar Research Secretariat Enh. för fartygsbaserat forskningsstöd Polarforskningssekretariatet This dataset includes three csv files (PLS_data.csv, 145 rows × 244 columns, High_Resolution_Data_PCA.csv, 145 rows × 73 columns, Soil_moisture_composition.csv, 145 rows × 82 columns) and one .rmd file. The csv files contain catchment characteristics derived from conventional spatial data ( land use, soil type, mean climatic variables, etc...) and high resolution spatial data (stream and ditch network and SLU soil moisture map). The .rmd takes the data for these 145 catchments and performs statistical analysis using PCA and PLS regression. For the .rmd file R is necessary to run the script. For more detailed information, see the readme.md file. Information about the R session is in sessionInfo.txt. Mon, 01 Dec 2025 14:13:46 GMT https://researchdata.se/en/catalogue/dataset/2024-112 https://researchdata.se/en/catalogue/dataset/2024-112 Swedish University of Agricultural Sciences Anna Lackner This dataset contains the SLU Forage Availability Map. This dataset contains 12 maps, distributed as .tif files. They show the predicted abundance of the pine (Pinus sylvestris), rowan (Sorbus aucuparia), oak (Quercus spp.), willow (Salix caprea), aspen (Populus tremula) and birch (Betula spp.) trees from 10 cm height to 4 cm diameter at breast height across the country using data from the Swedish National Forest Inventory and remote sensing datasets. Map products are aggregated to a 1ha and a 1km2 scale and show the average amount of trees estimated per spatial unit. For more information on the development of this dataset, please see the article: https://doi.org/10.1016/j.jag.2025.104850 For access to the 10x10m maps, contact the authors. Tue, 04 Nov 2025 15:22:50 GMT https://researchdata.se/en/catalogue/dataset/2025-259 https://researchdata.se/en/catalogue/dataset/2025-259 Swedish University of Agricultural Sciences Lukas Graf Inka Bohlin Per-Ola Hedwall Jonas Dahlgren Annika M. Felton The GIS-based Time model of Gothenburg aims to map the process of urban development in Gothenburg since 1960 and in particular to document the changes in the spatial form of the city - streets, buildings and plots - through time. Major steps have in recent decades been taken when it comes to understanding how cities work. Essential is the change from understanding cities as locations to understanding them as flows (Batty 2013)1. In principle this means that we need to understand locations (or places) as defined by flows (or different forms of traffic), rather than locations only served by flows. This implies that we need to understand the built form and spatial structure of cities as a system, that by shaping flows creates a series of places with very specific relations to all other places in the city, which also give them very specific performative potentials. It also implies the rather fascinating notion that what happens in one place is dependent on its relation to all other places (Hillier 1996)2. Hence, to understand the individual place, we need a model of the city as a whole. Extensive research in this direction has taken place in recent years, that has also spilled over to urban design practice, not least in Sweden, where the idea that to understand the part you need to understand the whole is starting to be established. With the GIS-based Time model for Gothenburg that we present here, we address the next challenge. Place is not only something defined by its spatial relation to all other places in its system, but also by its history, or its evolution over time. Since the built form of the city changes over time, often by cities growing but at times also by cities shrinking, the spatial relation between places changes over time. If cities tend to grow, and most often by extending their periphery, it means that most places get a more central location over time. If this is a general tendency, it does not mean that all places increase their centrality to an equal degree. Depending on the structure of the individual city’s spatial form, different places become more centrally located to different degrees as well as their relative distance to other places changes to different degrees. The even more fascinating notion then becomes apparent; places move over time! To capture, study and understand this, we need a "time model". The GIS-based time model of Gothenburg consists of: • 12 GIS-layers of the street network, from 1960 to 2015, in 5-year intervals • 12 GIS-layers of the buildings from 1960 to 2015, in 5-year intervals - Please note that this dataset has been moved to a separate catalog post (https://doi.org/10.5878/t8s9-6y15) and unpublished due to licensing restrictions on its source dataset. • 12 GIS- layers of the plots from1960 to 2015, in 5-year intervals In the GIS-based Time model, for every time-frame, the combination of the three fundamental components of spatial form, that is streets, plots and buildings, provides a consistent description of the built environment at that particular time. The evolution of three components can be studied individually, where one could for example analyze the changing patterns of street centrality over time by focusing on the street network; or, the densification processes by focusing on the buildings; or, the expansion of the city by way of occupying more buildable land, by focusing on plots. The combined snapshots of street centrality, density and land division can provide insightful observations about the spatial form of the city at each time-frame; for example, the patterns of spatial segregation, the distribution of urban density or the patterns of sprawl. The observation of how the interrelated layers of spatial form together evolved and transformed through time can provide a more complete image of the patterns of urban growth in the city. The Time model was created following the principles of the model of spatial form of the city, as developed by the Spatial Morphology Group (SMoG) at Chalmers University of Technology, within the three-year research project ‘International Spatial Morphology Lab (SMoL)’. The project is funded by Älvstranden Utveckling AB in the framework of a larger cooperation project called Fusion Point Gothenburg. The data is shared via SND to create a research infrastructure that is open to new study initiatives. 1. Batty, M. (2013), The New Science of Cities, Cambridge: MIT Press. 2. Hillier, B., (1996), Space Is the Machine. Cambridge: University of Cambridge - 12 GIS-layers of the street network in Gothenburg, from 1960 to 2015, in 5-year intervals. File format: shapefile (.shp), MapinfoTAB (.TAB). The coordinate system used is SWEREF 99TM, EPSG:3006. - 12 GIS-layers of plots in Gothenburg, from 1960 to 2015, in 5-year intervals. Only built upon plots (plots with buildings) are included. File format: shapefile (.shp), MapinfoTAB (.TAB). The coordinate system used is SWEREF 99TM, EPSG:3006. See the attached Technical Documentation for the description and further details on the production of the datasets. See the attached Report for the description of the related research project. Fri, 12 Sep 2025 08:58:29 GMT https://researchdata.se/en/catalogue/dataset/snd1154-1 https://researchdata.se/en/catalogue/dataset/snd1154-1 Chalmers University of Technology Ioanna Stavroulaki Lars Marcus Meta Berghauser Pont Ehsan Abshirini Jan Sahlberg Alice Örnö Ax This is the training and testing data used to train a Residual Attention UNet for segmentation and detection of road culverts. The data consists of pairs of images with the size 256x256 pixels where one image is a labeled mask and the other a image with four channels containing the remote sensing data. The remote sensing data is a combination of topographical data extracted from arial laser scanning and ortophotos from arial imagery. An extensive culvert survey was conducted in 25 watersheds in central Sweden by the Swedish Forest Agency during the snow-free periods of 2014–2017. A total of 24,083 culverts were mapped with a handheld GPS with a horizontal accuracy of 0.3 m. Densely populated urban areas with underground drainage systems were excluded from the survey (0.3% of the combined area). The coordinates of both ends of each culvert were measured, and metrics such as diameter, length, material, working condition, and sediment accumulation were collected for most of the culverts. Additional metrics, such as the elevation difference between the outlet and stream water level, were manually measured with a ruler. The inventoried watersheds were split up into training and testing data, where 20 watersheds (23,304 culverts) were used for training, and five watersheds (5,208 culverts) were used for testing. A compact laser-based system (Leica ALS80-HP-8236) was used to collect the ALS data from an aircraft flying at 2888–3000 m. The ALS point clouds had a point density of 1–2 points m-2 and were divided into tiles with a size of 2.5 x 2.5 km each. A DEM with 0.5 m resolution was created from the ALS point clouds using a TIN gridding approach implemented in Whitebox tools 2.2.0. The topographical index max downslope elevation change was calculated from the DEM using Whitebox Tools . Max downslope elevation change represents the maximum elevation drop between each grid cell and its neighbouring cells within a DEM. This typically resulted in values between 0 and 10. Orthophotos from aerial imagery captured at the same time as the lidar data is also included. The orthophotos had three bands (red, green and blue) in 8-bit color depth and had a resolution of 0.5 m. The LiDAR data and orthophotos were downloaded from the Swedish mapping, cadastral and land registration authority. The topographical data and the ortophotos were merged into 8-bit four band images where the first three band is red, green and blue, and the last band is max downslope elevation change. The merged images where then split into smaller tiles with the size 256x256 pixels. The trained model was used to predict culverts in Sweden and the file PredictedCulvertsByIsobasins.zip contains the predicted culverts stored as shapefiles split by the watersheds in the file "isobasins.zip". Tue, 25 Feb 2025 07:27:20 GMT https://researchdata.se/en/catalogue/dataset/2024-140 https://researchdata.se/en/catalogue/dataset/2024-140 Swedish University of Agricultural Sciences William Lidberg In August – September 2024, the North of Greenland expedition with IB Oden went to Northern Greenland and the adjacent Arctic Ocean, including the Lincoln Sea. The expedition is based on the research theme GEOEO, which is carried out within the Polar Research Process. The North of Greenland 2024 expedition addresses scientific questions focused on providing new knowledge on the marine cryosphere’s dynamic history and response to future climate change, including implications for marine and terrestrial ecosystems in North Greenland and the adjacent Arctic Ocean and the North Greenland Ice Sheet’s contribution to global sea-level rise. This dataset contains meteorological, oceanographic, and ship data collected during the international expedition GEOEO 2024. The data includes: Meteorological variables: Air temperature, humidity, wind direction/speed, atmospheric pressure, cloud height/cloudiness, and photosynthetically active radiation (PAR). Oceanographic variables: Sea water temperature, conductivity, salinity, and sound velocity. Ship data: Position, speed, course, heading, and water depth. A file titled "Parameterlist ShipData GEOEO 2024" describes the variables. Quality Information: No additional processing or quality checks have been performed on the data. Users should take this into account when handling and analyzing the data. Tue, 11 Feb 2025 09:17:55 GMT https://researchdata.se/en/catalogue/dataset/2024-645 https://researchdata.se/en/catalogue/dataset/2024-645 Swedish Polar Research Secretariat Quick-clay landslides are common geohazards in Nordic countries and Canada. The presence of potential quick clays is confirmed using geotechnical investigations, but near-surface geophysical methods, such as seismic and resistivity surveys, can also help identifying coarse-grained materials associated to the development of quick clays. We present the results of four reflection seismic profiles next to the Göta River in Sweden, along which many quick-clay landslide scars exist. An extensive coarse-grained layer exists in the sedimentary sequence and is interpreted and modeled in a regional context. Hydrological modeling of the coarse-grained layer is performed. Magnetic data are also studied within this investigation. Four reflection seismic profiles collected in 2013 (line 5 has two parts, cabled geophones and wireless stations). Fri, 17 Jan 2025 10:38:53 GMT https://researchdata.se/en/catalogue/dataset/snd1079-1 https://researchdata.se/en/catalogue/dataset/snd1079-1 Uppsala University Silvia Salas Romero Alireza Malehmir Ian Snowball Benoît Dessirier Wind and temperature profiles as well as wind and temperature turbulence statistics from the Marsta observatory. 2020-2022. Wed, 30 Oct 2024 10:27:13 GMT https://researchdata.se/en/catalogue/dataset/2024-531 https://researchdata.se/en/catalogue/dataset/2024-531 Uppsala University Johan Arnqvist The dataset contains questionnaire survey data from the evaluation of a Digital Twin Viewer (CDTE) for the city of Gothenburg. The questionnaire collects background information about the users and their familiarity with digital twins or other digital tools, their evaluation of the usability and usefulness of the City Digital Twin and general reflections on the characteristics and the maintenance of the viewer platform. Data is collected through two assessment workshops: First, a workshop with 22 stakeholders representing the city energy provider, the planning and environmental department of the municipality, property companies both municipal and private, and researchers; and second, a workshop with 70 master students with a background in architecture and urban planning as part of a course on sustainable development and stakeholder engagement. Mon, 14 Oct 2024 13:24:12 GMT https://researchdata.se/en/catalogue/dataset/2024-435 https://researchdata.se/en/catalogue/dataset/2024-435 Chalmers University of Technology Liane Thuvander Daniela Maiullari Giliam Dokter