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51 results for “geomorphology”
Data from: Contribution of small isolated habitats in creating refuges from biological invasions along a geomorphological gradient of floodplain waterbodies
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Data from: How big of an effect do small dams have? Using geomorphological footprints to quantify spatial impact of low-head dams and identify patterns of across-dam variation
Longitudinal connectivity is a fundamental characteristic of rivers that can be disrupted by natural and anthropogenic processes. Dams are significant disruptions to streams. Over 2,000,000 low-head dams (<7.6 m high) fragment United States rivers. Despite potential adverse impacts of these ubiquitous disturbances, the spatial impacts of low-head dams on geomorphology and ecology are largely untested. Progress for research and conservation is impaired by not knowing the magnitude of low-head dam impacts. Based on the geomorphic literature, we refined a methodology that allowed us to quantify the spatial extent of low-head dam impacts (herein dam footprint), assessed variation in dam footprints across low-head dams within a river network, and identified select aspects of the context of this variation. Wetted width, depth, and substrate size distributions upstream and downstream of six low-head dams within the Upper Neosho River, Kansas, United States of America were measured. Total dam footprints averaged 7.9 km (3.0-15.3 km) or 287 wetted widths (136-437 wetted widths). Estimates included both upstream (mean: 6.7 km or 243 wetted widths) and downstream footprints (mean: 1.2 km or 44 wetted widths). Altogether the six low-head dams impacted 47.3 km (about 17%) of the mainstem in the river network. Despite differences in age, size, location, and primary function, the sizes of geomorphic footprints of individual low-head dams in the Upper Neosho river network were relatively similar. The number of upstream dams and distance to upstream dams, but not dam height, affected the spatial extent of dam footprints. In summary, ubiquitous low-head dams individually and cumulatively altered lotic ecosystems. Both characteristics of individual dams and the context of neighboring dams affected low-head dam impacts within the river network. For these reasons, low-head dams require a different, more integrative, approach for research and management than the individualistic approach that has been applied to larger dams.
Investigating the effects of retaining riparian forest buffer zones of differing width on stream channel geomorphology
<b>Description: </b><p>To monitor temporal stream shape change over a gradient of RBZ widths, channel cross section measurements were continued at preestablished points that have been present since 2011. The points are marked with 0.4-metre-long PVC pipes that are spray painted yellow for easier identification and surrounding bedrock or roots are also marked at the exact location of the pipes in case a pipe should be eroded away in future. Channel cross sections were calculated using a standardised method. Cross- sectional area (CSA) measurement was repeated for every pre-established cross section point along the stream. These were located 250 m apart and numbered 4- 10, depending on the accessibility of the trails upstream. The stream with a '0 metre' buffer, for instance, had only four measurement points due to a steep waterfall which could not be passed. The CSA of these stream points were re-measured on a yearly basis in 2011 - 2014, 2018 and 2019.</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/210"><b>Investigating the effects of retaining riparian forest buffer zones of differing width on stream channel geomorphology. </b></a></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3476390">here</a></p><p><b>Files: </b>This consists of 1 file: Template_cross_sections.xlsx</p><p><b>Template_cross_sections.xlsx</b></p><p>This file contains dataset metadata and 1 data tables:</p><ol><li><p><b>Stream cross section measurements</b> (described in worksheet CrossSections)</p><p>Description: Cross section measurements</p><p>Number of fields: 7</p><p>Number of data rows: 8377</p><p>Fields: </p><ul><li><b>Identity</b>: Original site label in field data (Field type: id)</li><li><b>Stream</b>: Stream transect (Field type: location)</li><li><b>Site</b>: Location of stream cross section (Field type: location)</li><li><b>DistanceAcross</b>: Distance across the stream at which the measurement was taken (Field type: numeric)</li><li><b>Height</b>: Stream depth (Field type: numeric)</li><li><b>BaseMaterial</b>: Ground cover at the measurement point (Field type: categorical)</li><li><b>Date</b>: Date cross section was measured (Field type: date)</li></ul></li></ol><p><b>Date range: </b>2011-01-12 to 2019-03-30</p><p><b>Latitudinal extent: </b>4.6314 to 4.7345</p><p><b>Longitudinal extent: </b>117.4554 to 117.6414</p>
Figure 6 from: Tilley L, Berning B, Erdei B, Fassoulas C, Kroh A, Kvaček J, Mergen P, Michellier C, Miller C, Rasser M, Schmitt R, Kovar-Eder J (2019) Hazards and disasters in the geological and geomorphological record: a key to understanding past and future hazards and disasters. Research Ideas and Outcomes 5: e34087. https://doi.org/10.3897/rio.5.e34087
Figure 6 A tektite that originates from the distal ejecta (strewn field) of the Ries impact, found in the Czech Republic. Tektites from the Ries impact are called moldavites. Ruler at the bottom of the image = 6.6 cm [Inventory number NHMV_J677]. Photo courtesy of L. Ferrière, Natural History Museum Vienna.
Drone-based geomorphology mapping of Borebreen in Svalbard, 2024
<p>This database contains drone-based mapping data of geomorphological areas in front of Borebreen, Svalbard, Norway. The dataset was generated using a structure-from-motion (SfM) method using drone-based imagery. The data was processed with Agisoft Metashape and the processed data consists of digital elevation models (DEMs) in georeferenced .TIF file format, orthomosaic maps in georeferenced .TIF file format, and textured 3D models in .STL file format. In addition, a process report in .PDF file format is included for each dataset. Mapping was conducted with a DJI Mavic 3 Pro Enterprise. The mapping was conducted August/September 2024. </p>
Data for "Hydrodynamic and Geomorphological Responses of Tidal Flats to Extreme Climate Events with Implications for Coastal Managements"
<p>Data used for the plots can be found:</p> <p>1) <strong>uav_z.mat </strong>is used for producing figure 2 and 3.</p> <p>2) <strong>timeseries.mat </strong>is used for producing figure 5 and 6.</p>
Data from: How big of an effect do small dams have? Using geomorphological footprints to quantify spatial impact of low-head dams and identify patterns of across-dam variation
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Dataset - River geomorphology and fish diversity around the Manseriche Gorge, the last Andean crossing is in peril
<p>The dataset includes the results from the manuscript "River geomorphology and fish diversity around the Manseriche Gorge, the last Andean crossing is in peril", by Abad et al. (2024) submitted to Water Resources Research, AGU.</p>
Literary_Geomorphology_Visualizing_Literary_Spatiality_OHSH
<p>This repo contains the data and code needed to reproduce the visualizations in the "Literary Geomorphology" section of the article "Visualizing Literary Spatiality" by Anders Skare Malvik and Barbara Piatti. Here you will find 10 textfiles (10 novels), a spreadsheet with all geomorphemes found in these novels, and two Jupyter Notebook files with code to visualize the distribution of the geomorphemes in the novels. For details, please consult the readme file and contact Anders Skare Malvik.</p>
Geomorphological maps of fourteen craters located on the north pole of Mercury
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Supplementary Tables for Geomorphology of gullies at the Haughton Impact Structure, Devon Island, Canadian High Arctic
<p>Data describing the input and results from the FAMD and HCPC model for "Geomorphology of gullies at the Haughton Impact Structure, Devon Island, Canadian High Arctic"</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.