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412 results for “topography”
Integrated Topography and Bathymetry for the Eastern Shore of Virginia
Description This dataset integrates elevation and bathymetry data from multiple sources into a single mostly-seamless digital elevation model (DEM) that covers the entire Eastern Shore of Virginia and its surrounding coastal waters. Data sources include airborn LiDAR, VCRLTER and ODU bathymetric surveys, NOAA navigational data, NOS oceanographic surveys, USGS NED data plus contours and features from topo quad maps, and VGIN-VBMP aerial imagery. Proposed uses for the dataset include deriving detailed watershed boundaries, hypsometric curves, tidal prisms, 3-D physical models, and input for numerical hydrodynamic simulation models. The version 2.0 DEM (August 2014) is suitable for both local- and regional-scale analyses. It has a resolution matched to the LiDAR data (3.048 m. or 10 ft.), resulting in 31,152 x 46,002 cells (5.4 Gigabyte in ESRI GRID format). Users can aggregate to coarser cell resolutions as needed. The data is projected in UTM Zone 18 North coordinates relative to the WGS84 horizontal datum. All elevations are in meters relative to the NAVD88 vertical datum. Spatially modelled conversion factors between NAVD88 and local sea level datums (MSL, MLW, MHW, etc.) based on NOAA VDATUM data are available as a separate dataset (VCR13215). See "METHODS" for full details on data sources and integration methodologies.
ICESat-2 Arctic Sea Ice Surface Topography from the University of Maryland-Ridge Detection Algorithm: April 2019, 2020, and 2021
<p>This dataset is derived from the ICESat-2 (IS-2) Global Geolocated Photon Height Product (ATL03) using the University of Maryland-Ridge Detection Algorithm (UMD-RDA). The UMD-RDA is applied to ATL03 on a per-shot basis, nominally resulting in elevation measurements at IS-2's maximum along-track resolution of ~0.7 m. From these elevation measurements, the UMD-RDA can measure various sea ice parameters including, but not limited to, individual ridge crests and their respective sail heights, the distance between ridges, and sea ice surface roughness.</p> <p><strong>********Changes in Version 2********</strong></p> <p><em>Version 2 includes a column for time (seconds since 2018-01-01) in all parameter files in addition to longitude, latitude, and parameter value.</em></p> <p><em>The full resolution UMD-RDA derived elevation data was too large to host here, but is available upon request. If you need a particular track or segment for your research please contact me with your request by email: kd</em><em>uncan at umd dot edu</em></p>
East African topography and volcanism explained by a single, migrating plume: supplementary data
<p>These data accompany the following paper:</p> <p>Hassan, R., Williams, S.E., Gurnis, M. and Müller, D., 2020. East African topography and volcanism explained by a single, migrating plume. <em>Geoscience Frontiers</em>, <em>11</em>(5), pp.1669-1680.</p> <p>The data (in simple text form) correspond to the dynamic topography and change in dynamic topography shown in Figure 7.</p>
Topography drives microgeographic adaptations of closely-related species in two tropical tree species complexes
<p>Combining LiDAR-derived topography, tree inventories, and single nucleotide polymorphisms (SNPs) from gene capture experiments, we explored genome-wide population genetic structure, covariation of environmental variables, and genotype-environment association to assess microgeographic adaptations to topography within the species complexes <em>Symphonia</em> (Clusiaceae), and <em>Eschweilera</em> (Lecythidaceae) with three species per complex and 385 and 257 individuals genotyped, respectively.</p>
Effects of topography on soil characteristics in the Andrews Experimental Forest, 1998
This is the third and final data set in a series of basin-scale summer forest soil surveys. We conducted soil survey in 1998 designed to provide an accurate assessment of soil properties over the entire H.J. Andrews Experimental Forest. This dataset represents the results of that effort. Since the 1994 survey, we changed the way we measured soil field respiration rates. Initially we used the 24 hr soda-lime CO2 adsorption method in chambers with only one measurement per site. In 1998 we converted to using the Li-Cor portable respirometer with 5 measurements made per site. Since 1994, it was also discovered that there were significant edge effects to 30 meters from an edge. For this reason, all sample locations were moved at least 40 meters from the road. While conducting autocorrelation analyses, we found that for the variables studied, samples collected at 5 m intervals were not autocorrelated and could thus be considered independent for statistical analysis. Our subsequent work also allowed us to chose those variables that would most likely be influenced by topography. The previous two surveys were conducted in the late summer when the forests are dry and microbial activity at a minimum. The current study was conduced from mid June to the first of July while the soils were still moist and when microbial activity was more typical of wet months. In the other two studies, only one measurement was made per site. In the current survey, replicate samples were collected and pooled or multiple measurements were made in the field. As a result of experimental design modifications, it is thought that this represents the best and most definitive dataset of basin-scale soil properties on the HJA. In the first survey, forest floor respiration rates were measured at 130 sites covering a large portion of the HJA. The sample sites were located at 0.5 km intervals along most of the main roads. In addition to field respiration rates measured by the soda-lime method, soil and air tem
Topography extraction and topographic change measurements using PlanetScope data: Shisper Glacier (Pakistan)
<p>The study area is located in the north flank of Hunza Valley in the Central Karakoram. Shisper glacier covers ~53.7 km2 at an elevation range of 2567-611 m a.s.l. It is a surge-type glacier, which has recently gained the attention of the scientific community and disaster response agencies during its surge. In 2018, the glacier surged beyond the confluence with the outlet stream of Mochwar glacier. The blockage resulted in the creation of a lake, which then drained causing a GLOF (Glacial Lake Outbreak Flood) and has recently begun reforming. The melt water from the two glaciers feeds hydropower plants in the Hunza valley and is a major source of fresh water for agriculture. Glacier-related hazards threaten both the town of Hassanabad and the Karakoram Highway, the only paved road through the mountain range. Here we show the potential of CubSat data to monitor such glaciers, which are not easily accessible to field observation and their potential impact on power generation, water resources and infrastructure.</p> <p>We use multi-date L1B DOVE-C PlanetScope data to extract two DEMs in 2017 and 2019 over the study area in order to compute the elevation difference caused by the glacier surge.</p> <p>Supplementary material for our paper: Optimization of optical image geometric modeling, application to topography extraction and topographic change measurements using PlanetScope and SkySat imagery.</p>
CD_topography_35408_E-HYPE
Area, mean elevation, standard-deviation of elevation, mean slope, drainage density calculated for upstream area of all E-HYPE sub-basins outlets. Drainage density is defined as total length of all streams in the catchment divided by catchment area. For length of streams calculation, a stream network layer has been computed based on the HYDRO1K elevation and flow accumulation layers, using a threshold of at least 20 km2 of upstream area for starting a river. This data can be linked to the shapefile "MULTIHARO_TotalDomain_WGS84_20140428_2" available as a separate download. To do so, link the "SUBID_OUT" filed of the shapefile with the "SUBID" field of this dataset.
Extracted raw data from: Global dominance of lianas over trees is driven by forest disturbance, climate, and topography
<p>In a meta-analysis, we use an unprecedented dataset, representing 556 unique locations worldwide, distributed across 44 countries and six continents to show for the first time that lianas (woody vines) thrive relatively better than trees when forests are disturbed, temperature increase, precipitation decrease, and particularly in tropical lowlands. We demonstrate that liana dominance can persist for decades post-disturbance and hinder the recovery of disturbed forests, especially when climate favours lianas. With implications for the global carbon sink, our findings suggest that degraded tropical forests with environmental conditions favouring lianas should be the highest priority to consider for restoration management.</p>
Ice thickness and bed topography of all Scandinavian glaciers and ice caps
<p>Files showing the ice thickness (m) and subglacial bed elevation (m) for all Scandinavian (i.e. Norwegian and Swedish) glaciers and ice caps. Coordinate system is epsg:25833</p> <p>Related publication which should be referenced when this data is used is </p> <div> <div> <div>Frank T, van Pelt W. Ice volume and thickness of all Scandinavian glaciers and ice caps. <em>Journal of Glaciology</em>. Published online 2024:1-34. doi:10.1017/jog.2024.25 <div> </div> </div> </div> </div>
Detrended topography of the Moon
<p>These data sets represent detrended global topography of the Moon. Detrended topography is useful for photogeological analysis of subtle gently sloping features in generally smooth parts of the lunar surface. File _<strong>readme.pdf</strong> contains detailed description of the data sets. </p>
Data set for the article "Tides, topography, and seagrass cover controls on the spatial distribution of Pinna nobilis on a coastal lagoon tidal flat"
<p>Data set includes: coordinates of the GNSS points (reference system WGS84 UTM33N); density of P. nobilis and cover of C.nodosa detected in the orthophoto in the 25m<sup>2</sup> cells; tidal levels measured (and, for comparison, simulated with the hydrodynamic model) corrected with respect to the IGM datum; number of emersions and flood duration for different levels of the tidal flat; statistics. The first Excel sheet includes a detailed description of the data.</p>
Evolution of Indian Ocean Paleoceanography and South-East Asian Climate during the Miocene in response to change in regional topography
<p>This directory contain outputs of 9 paleo-climate simulations performed with the IPSL-CM5A2 and PISCES-v2 models. The simulations have used in a paper to be published in Nature Geoscience (2022) entitled "Divergent South Asian Monsoon Rainfall and Wind Histories due to topography effects" (Sarr et al.) that investigates the co-evolution of Arabian Sea upwelling and South Asian Monsoon rainfall and winds over the Miocene. It includes simulations with both early Miocene and late Miocene paleogeography.</p> <p>SimulationsOutputs.tar directory contains NetCDF files with ocean, ocean biogeochemistry and atmosphere variables. Data are monthly average over the last 100 years of each simulation.</p> <p>TopoMiocene.tar contains the paleogeographies used for the simulations.</p> <p> More informations on output contents can be find in README_detailsOutput.md document as well as within the Methods section of the publication.</p> <p>PISCES_update.tar contains updated routines for the PISCES-offline model (Aumont et al., 2015) that have been used for the publication. It contains a REAME.md file that explain how to include those updates within the reference code.</p> <p> </p>
Supplementary data - Modelling the role of dynamic topography and eustasy in the evolution of the Great Artesian Basin
<p>This data repository contains the supplementary data for the paper:</p> <p><strong>Modelling the role of dynamic topography and eustasy in the evolution of the Great Artesian Basin.</strong></p> <p>Carmen Braz<sup>1</sup>, Sabin Zahirovic<sup>1</sup>, Tristan Salles<sup>1</sup>, Nicolas Flament<sup>2</sup>, Lauren Harrington<sup>1</sup>, R. Dietmar Müller<sup>1</sup></p> <p><sup>1</sup> EarthByte Group, School of Geosciences, The University of Sydney, Sydney, Australia</p> <p><sup>2</sup> GeoQuEST Research Centre, School of Earth and Environmental Sciences, University of Wollongong, Wollongong, NSW, Australia</p> <p><em>Basin Research, https://doi.org/10.1111/bre.12606</em></p> <p>Included in this supplement are:</p> <ul> <li> All input files required for running Badlands models M1-M4</li> <li> Badlands digital output for preferred model M4</li> <li> Animations of topography and erosion-deposition through time for all four models presented in the paper </li> <li> Sediment layers for all time steps for preferred model M4 provided as netcdf grids.</li> </ul>
Supplementary Data - "Analysis of Venusian Wrinkle Ridge Morphometry Using Stereo-Derived Topography: A Case Study from Southern Eistla Regio"
<p>Supplementary data for the manuscript entitled "Analysis of Venusian Wrinkle Ridge Morphometry Using Stereo-Derived Topography: A Case Study from Southern Eistla Regio".</p> <p>Includes data for topographic profiles of wrinkle ridges ("wrinkleridge_profiledata.xlsx"), COULOMB model inputs ("COULOMB_modelinputs.xlsx") and outputs ("COULOMB_modeloutputs.xlsx"), and GIS shapefile data for mapped wrinkle ridges (files labelled "allwrinkleridges" and "studiedwrinkleridges"), topographic profile lines (files labelled "topographicprofilelines"), and the regional profile (files labelled "regionalprofile"). </p>
Data for the Manuscripts of "Variability of Jakarta Rain-Rate Characteristics Associated with the Madden-Julian Oscillation and Topography" and "Subdaily Rain-Rate Properties in Western Java Analyzed Using C-Band Doppler Radar"
<p>This archive consists of the post-processed data of C-Band Doppler Radar (CDR) over Jakarta and surrounding regions for the studies of "Variability of Jakarta Rain-Rate Characteristics Associated with the Madden-Julian Oscillation and Topography" and "Subdaily Rain-Rate Properties in Western Java Analyzed Using C-Band Doppler Radar".</p> <p>The dataset is a gridded rainfall data derived from the local relationship of Z (reflectivity) from the CDR and rainfall (R) from stations. The derived rainfall data are in daily estimates from 2009 to 2012 with the format in NetCDF files.</p> <p>The CDR data were obtained from the projects “Hydrometeorological Array for Intraseasonal Variation-Monsoon Automonitoring (HARIMAU)” (JFY 2005-2009), and the Science Technology Research Partnership for Sustainable Development (SATREPS) “Maritime Continent Center of Excellence (MCCOE) (JFY 2009-2013) of the Japan Science and Technology Agency (JST)/Japan International Cooperation Agency(JICA) under a collaboration of the Agency for the Assessment and Application of Technology (BPPT)-Indonesia and Japan Agency for Marine-earth Science and Technology (JAMSTEC)-Japan.</p>
Bedrock surface topography of Latvia
<p>A new map and digital bedrock surface elevation model of Latvia is presented with a horizontal resolution of 250 m. The local bedrock comprises largely undisturbed layers of Palaeozoic and Mesozoic sedimentary rocks covered by up to 200 m thick Quaternary strata composed mostly of glacigenic and marine sediments. The bedrock surface elevation model and the corresponding map were created by tessellation interpolation of the bedrock surface based on more than 20,000 boreholes and constrained by the present land surface. The known locations of paleo-incisions buried under Quaternary cover are indicated. <br> <br> The presented map is prepared as a georeferenced dataset comprising four raster bands: elevation of the bedrock surface above sea level, locations of boreholes used for the construction of the elevation of the bedrock surface, locations, where buried valleys in geological boreholes were uncovered, and thickness of Quaternary sediments:</p> <ul> <li>Band_1 - digital elevation model of the bedrock surface topography of Latvia,</li> <li>Band_2 - thickness of Quaternary sequence,</li> <li>Band_3 - well locations marking the top of the bedrock, used to construct the map (count per cell),</li> <li>Band_4 - well locations interpreted to be recovering paleo incisions (count per cell).</li> </ul> <p>This research is funded by the Latvian Council of Science, project “Spatial and temporal prediction of groundwater drought with mixed models for multilayer sedimentary basin under climate change”, project No. lzp-2019/1-0165.</p>
High-resolution topography and layer attitude measurements over Juventae Chasma (Valles Marineris, Mars)
<p>Stereo-derived topography over mounds in Juventae Chasma (Valles Marineris, Mars), including derived measurements (ASCII .csv and .xls). File naming in measurements follows the numbering of NASA MRO HiRiSE stereo pairs.</p> <p>Please note for all DTMs</p> <p>Format: GeoTiff<br> Projection: Equirectangular<br> Datum: Mars 2000 Sphere</p> <p>Bit depth: 32bit</p> <p>Spatial resolution: 1m/pixel</p> <p>HiRise images avalable at:https://hirise.lpl.arizona.edu/<br> (use one of the image numbers listed below in the search box)</p> <p>Stereo pairs:</p> <p>HiRISE 1 (PSP_002590_1765_RED-PSP_002946_1765_RED-DEM_cyli.tif)<br> PSP_002590_1765<br> PSP_002946_1765</p> <p><br> HiRISE 2 (PSP_006915_1760_RED-PSP_007060_1760_RED-DEM_cyli.tif)<br> PSP_006915_1760<br> PSP_007060_1760</p> <p>HiRISE 3 (ESP_015934_1760_RED-ESP_016646_1760_RED-DEM_cyli.tif)<br> ESP_016646_1760<br> ESP_015934_1760</p> <p>HiRISE 4 (ESP_020470_1755_RED-ESP_014378_1755_RED-DEM_cyli.tif)<br> ESP_020470_1755<br> ESP_014378_1755</p> <p>HiRISE 5 (PSP_002379_1755_RED-PSP_002023_1755_RED-DEM_cyli.tif)<br> PSP_002379_1755<br> PSP_002023_1755</p> <p>HiRISE 6 (ESP_016567_1755_RED-ESP_017279_1755_RED-DEM_cyli.tif)<br> ESP_016567_1755<br> ESP_017279_1755</p> <p>HiRISE 7 (PSP_003790_1755_RED-PSP_004291_1755_RED-DEM_cyli.tif)<br> PSP_003790_1755<br> PSP_004291_1755</p> <p>HiRISE 8 (ESP_016145_1775_RED-ESP_017424_1775_RED-DEM_cyli.tif)<br> ESP_016145_1775<br> ESP_017424_1775</p> <p>HiRISE 9 (PSP_008708_1780_RED-PSP_008998_1780_RED-DEM_cyli.tif)<br> PSP_008708_1780<br> PSP_008998_1780</p> <p>HiRISE 10 (ESP_011688_1760_RED-ESP_019613_1760_RED-DEM_cyli.tif)<br> ESP_019613_1760<br> ESP_011688_1760</p>
High-resolution digital topography and layer attitude measurements over Juventae Chasma (Valles Marineris, Mars)
<p>Stereo-derived topography over mounds in Juventae Chasma (Valles Marineris, Mars), including derived measurements (ASCII .csv and .xls). File naming in measurements follows the numbering of NASA MRO HiRiSE stereo pairs.</p> <p>Please note for all DTMs</p> <p>Format: GeoTiff<br> Projection: Equirectangular<br> Datum: Mars 2000 Sphere</p> <p>Bit depth: 32bit</p> <p>Spatial resolution: 1m/pixel</p> <p>HiRise images avalable at:https://hirise.lpl.arizona.edu/<br> (use one of the image numbers listed below in the search box)</p> <p>Stereo pairs:</p> <p>HiRISE 1 (PSP_002590_1765_RED-PSP_002946_1765_RED-DEM_cyli.tif)<br> PSP_002590_1765<br> PSP_002946_1765</p> <p><br> HiRISE 2 (PSP_006915_1760_RED-PSP_007060_1760_RED-DEM_cyli.tif)<br> PSP_006915_1760<br> PSP_007060_1760</p> <p>HiRISE 3 (ESP_015934_1760_RED-ESP_016646_1760_RED-DEM_cyli.tif)<br> ESP_016646_1760<br> ESP_015934_1760</p> <p>HiRISE 4 (ESP_020470_1755_RED-ESP_014378_1755_RED-DEM_cyli.tif)<br> ESP_020470_1755<br> ESP_014378_1755</p> <p>HiRISE 5 (PSP_002379_1755_RED-PSP_002023_1755_RED-DEM_cyli.tif)<br> PSP_002379_1755<br> PSP_002023_1755</p> <p>HiRISE 6 (ESP_016567_1755_RED-ESP_017279_1755_RED-DEM_cyli.tif)<br> ESP_016567_1755<br> ESP_017279_1755</p> <p>HiRISE 7 (PSP_003790_1755_RED-PSP_004291_1755_RED-DEM_cyli.tif)<br> PSP_003790_1755<br> PSP_004291_1755</p> <p>HiRISE 8 (ESP_016145_1775_RED-ESP_017424_1775_RED-DEM_cyli.tif)<br> ESP_016145_1775<br> ESP_017424_1775</p> <p>HiRISE 9 (PSP_008708_1780_RED-PSP_008998_1780_RED-DEM_cyli.tif)<br> PSP_008708_1780<br> PSP_008998_1780</p> <p>HiRISE 10 (ESP_011688_1760_RED-ESP_019613_1760_RED-DEM_cyli.tif)<br> ESP_019613_1760<br> ESP_011688_1760</p>
New glacier thickness and bed topography maps for Svalbard - Dataset
<p>The dataset includes three Geotiff files that include:</p> <p>1) A bed topography map of Svalbard (heights in m a.s.l.) [Bed_map.tiff]</p> <p>2) An ice thickness map of Svalbard (in m) [Thickness_map.tiff]</p> <p>3) A mask file that with values from 0-3 indicating non-glacier areas (0), glaciers modelled with the Parallel Ice Sheet model (1), glaciers modelled with the Instructed Glacier Model (2), and surging glaciers (3). </p> <p>For a description of the methods used to generate the datasets, we refer to the manuscript "A new glacier thickness and bed map for Svalbard", to be submitted to The Cryosphere Discussions.</p>
Tailoring PVDF Membranes Surface Topography and Hydrophobicity by a Sustainable Two-Steps Phase Separation Process: dataset
<p>This is the dataset related to the article published in ACS Sustainable Chemistry & Engineering “Tailoring PVDF Membranes Surface Topography and Hydrophobicity by a Sustainable Two-Steps Phase Separation Process” DOI: 10.1021/acssuschemeng.8b01407</p>
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