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134 results for “surface area”
Temporal trends of surface water area in India's rivers and basins
<p>This dataset quantifies the extent and annual rate of change in surface water area (SWA) in India's rivers and basins over a period of 30 years from 1991 to 2020. Visit <a title="Surface Water Trends - India" href="https://sites.google.com/view/surface-water-trends-india/" target="_blank" rel="noopener">Surface Water Trends - India</a> for an interactive web interface to explore these results, and for additional data and information.</p> <p>It is derived from the <a href="https://global-surface-water.appspot.com/" target="_blank" rel="noopener">Global Surface Water Explorer</a> which maps terrestrial surface water globally using historical Landsat satellite imagery. (Pekel, J. et al., Nature 540, 418-422 (2016). (doi:10.1038/nature20584)). The data files contain zipped archives of shapefiles and CSV (comma separated values) files.</p> <p>Shapefiles are one for each season (dry, wet and permanent) and scale (river basin and reach) of our analysis, and contain annual trends in surface water area. To open and explore them in a GIS software (eg. QGIS), un-ZIP them and include them as vector datasets.</p> <p>CSV files are one for each scale (river basin and reach (transect)) of our analysis, and contain time series of surface water areas from 1991 to 2020. To open and explore them, for analysis or to explore in a table editing software, un-ZIP them and read them in.</p> <p>Refer to 00_README.txt for details on feature and table attributes in the files. </p>
Surface Area of River and Lakes (SARL)
<p>The Surface Area of River and Lakes (SARL) dataset has been developed to show the 38-years of seasonal and permanent water surface area change in rivers and lakes.</p>
Dataset: Surface waters in socially vulnerable areas are disproportionately under-monitored for nutrients in the U.S. South Atlantic-Gulf Region
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Rutor Glacier Surface Area - 2021
<p>Shape file of the Rutor glacier extension based on an orthophoto of September 2021.</p>
The reconstructed surface water area time series (2000-2019) dataset for lakes >1 km2 in China
<p>This repository contains the <strong>revised version</strong> of the supplementary data for the paper: <strong>Reconstruction of long-term high-resolution lake variability: Algorithm improvement and applications in China </strong>(https://www.sciencedirect.com/science/article/pii/S0034425723003267?via%3Dihub). </p> <p>Specifically, this dataset documents the reconstructed surface water area time series for all studied lakes in China during the period of 2000-2019. In the prior version of the dataset, there was an erroneous assignment of IDs to each lake. This issue has been rectified in the revised version, ensuring that the updated IDs now accurately correspond to the actual GLAKES_ID for each of the GLAKES lake polygons.</p> <p>For more detailed information of the dataset, please refer to the README file.</p>
Water table depth dynamics and surface soil moisture content from three Scottish peatland areas (2021-2022)
<p>This compilation of datasets from three monitoring sites on peatland in Scotland includes water table depth dynamics and surface soil moisture content and covers the period 2021-2022. Further data will be added on an annual basis. This is version 2 of the dataset, which corrects a small number of data QC issues (see README).</p>
Playa-Montmany, et al.: The thermoregulatory role of relative bill and leg surface areas in a Mediterranean population of Great tit
<p>There is growing evidence on the role of legs and bill as 'thermal windows' in birds coping with heat stress. However, there is a lack of empirical work examining the relationship between the relative bill and/or leg surface areas and key thermoregulatory traits such as the limits of the thermoneutral zone (TNZ) or the cooling efficiency at high temperatures. Here, we explored this relationship in a Mediterranean population of Great tit (<i>Parus major</i>) facing increasing thermal stress in its environment. The lower and upper critical limits of the TNZ were found to be 17.7 ± 1.6°C and 34.5 ± 0.7°C, respectively, and the basal metabolic rate was 0.96 ± 0.12 ml O<sub>2</sub> min<sup>-1 </sup>on average. The evaporative water loss (EWL) inflection point was established at 31.85 ± 0.27°C<sup> </sup>and was not significantly different from the value of the upper critical limit. No significant relationship was observed between the relative bill or tarsi size and TNZ critical limits, breadth, mass-independent VO<sub>2</sub> or mass-independent EWL at any environmental temperature (from 10°C to 40°C). However, Great tit males (but not females) with larger tarsi areas (a proxy of leg surface area) showed higher cooling efficiencies at 40°C. We found no support for the hypothesis that the bill surface area plays a significant role as a thermal window in Great tits, but the leg surface areas may play a role in males' physiological responses to high temperatures. On the one hand, we argue that the studied population occupies habitats with available microclimates and fresh water for drinking during summer, so active heat dissipation by EWL might be favored instead of dry heat loss through the bill surface. Conversely, male dominance behaviors could imply a greater dependence on cutaneous evaporative water loss through the upper leg surfaces as a consequence of higher exposure to harsh environmental conditions than faced by females.</p>
High-surface-area corundum nanoparticles by PDC process
<p>Source data for "High-surface-area corundum nanoparticles by resistive hotspot-induced phase transformation".</p>
Water table dynamics and surface soil moisture from an experimental peatland restoration area (Forsinard, Scotland, UK), 2017-2022/2023
<p>This dataset is from an experiment aimed to understand the changes in water level and soil moisture dynamics after rewetting of formerly afforested blanket bog areas. Specifically, it was aiming to test whether the water table and soil moisture dynamics in these areas return to those of control areas that had never been drained or afforested. The data span the period of summer 2017- summer 2022/2023, with gaps in individual time series marked with -9999 entries.</p>
Set of photos (123) of surface artifacts and cranium bones in the Iroungou burial cave, Mouila area, Gabon
<p>Photographs (annotated) of all 182 artifacts (iron currency knives, hoes, iron and copper bracelets, rings, kindu, gong) and 51 cranium bones visible on the ground during the initial visit of the Iroungou burial cave, Mouila area, Gabon, on september 23, 2018.</p>
A Non-destructive Method to Create a Time Series of Surface Area for Coral Using 3D Photogrammetry (Data)
<p>This is the underlying data for the publication "A Non-destructive Method to Create a Time Series of Surface Area for Coral Using 3D Photogrammetry" by Daniel D Conley and Erin N. R. Hollander published in 2021.</p>
Comparison among three different Digital Surface Models and their respective hydraulic outcomes in the flood-prone urban area of Navaluenga (Ávila, Spain)
<p>Three different Digital Surface Models (DSMs) generated from LiDAR data are presented. The LiDAR information has been considered as raw data (DSM3) and subjected to some transformations to better represent the urban environment (DSM1). DSM2 is an intermediate state between DSM1 and DSM3. </p> <p>On the other hand, a hydraulic model has been run for each DSM and for two return periods (25 and 500 years), obtaining in all cases the graphical outputs of depths, velocities, Froude numbers and hazard. </p> <p>The different DSMs are named DSM1, DSM2 and DSM3, which can be downloaded in TIN format. The hydraulic outputs associated with the different DSMs can be downloaded in raster format and are named as follows: the Digital Surface Model to which it refers, the return period considered and the type of hydraulic output (depth, velocity, Froude number and hazard).</p> <p>DSM1: Digital Surface Model 1 (TIN format).<br> dsm1_25depth: Depths obtained by considering the DSM1 and the flow associated with the 25-years return period (raster format).<br> dsm1_25froud: Froude numbers obtained by considering the DSM1 and the flow associated with the 25-years return period (raster format).<br> dsm1_25haz: Hazard obtained by considering the DSM1 and the flow associated with the 25-years return period (raster format).<br> dsm1_25veloc: Velocities obtained by considering the DSM1 and the flow associated with the 25-years return period (raster format). <br> dsm1_500depth: Depths obtained when considering the DSM1 and the flow associated with the 500-years return period (raster format).<br> dsm1_500froud: Froude numbers obtained by considering the DSM1 and the flow associated with the 500-years return period (raster format).<br> dsm1_500haz: Hazard obtained by considering the DSM1 and the flow associated with the 500-years return period (raster format).<br> dsm1_500veloc: Velocities obtained by considering the DSM1 and the flow associated with the 500-years return period (raster format).</p> <p>DSM2: Digital Surface Model 2 (TIN format).<br> dsm2_25depth: Depths obtained by considering the DSM2 and the flow associated with the 25-years return period (raster format).<br> dsm2_25froud: Froude numbers obtained by considering the DSM2 and the flow associated with the 25-years return period (raster format).<br> dsm2_25haz: Hazard obtained by considering the DSM2 and the flow associated with the 25-years return period (raster format).<br> dsm2_25veloc: Velocities obtained by considering the DSM2 and the flow associated with the 25-years return period (raster format). <br> dsm2_500depth: Depths obtained by considering the DSM2 and the flow associated with the 500-years return period (raster format).<br> dsm2_500froud: Froude numbers obtained by considering the DSM2 and the flow associated with the 500-years return period (raster format).<br> dsm2_500haz: Hazard obtained by considering the DSM2 and the flow associated with the 500-years return period (raster format).<br> dsm2_500veloc: Velocities obtained by considering the DSM2 and the flow associated with the 500-years return period (raster format).</p> <p>DSM3: Digital Surface Model 2 (TIN format).<br> dsm3_25depth: Depths obtained by considering the DSM3 and the flow associated with the 25-years return period (raster format).<br> dsm3_25froud: Froude numbers obtained by considering the DSM3 and the flow associated with the 25-years return period (raster format).<br> dsm3_25haz: Hazard obtained by considering the DSM3 and the flow associated with the 25-years return period (raster format).<br> dsm3_25veloc: Velocities obtained by considering the DSM3 and the flow associated with the 25-years return period (raster format). <br> dsm3_500depth: Depths obtained by considering the DSM3 and the flow associated with the 500-years return period (raster format).<br> dsm3_500froud: Froude numbers obtained by considering the DSM3 and the flow associated with the 500-years return period (raster format).<br> dsm3_500haz: Hazard obtained by considering the DSM3 and the flow associated with the 500-years return period (raster format).<br> dsm3_500veloc: Velocities obtained by considering the DSM3 and the flow associated with the 500-years return period (raster format).</p>
urban impervious surface area (UISA) data in Shanghai in 2015 and 2018
<p>This data cite from Kuang, W., Zhang, S., Li, X., and Lu, D. (2000–2018). A 30 M Resolution Dataset of China’s Urban Impervious Surface Area and green Space, 2000-2018. Earth Syst. Sci. Data 13, 63–82. doi:10.5194/essd-13-63-2021</p>
RT Dataset -- Updated radiative transfer model for Titan in the near-infrared wavelength range: Validation against Huygens atmospheric and surface measurements and application to the Cassini/VIMS observations of the Dragonfly landing area
<p>This dataset contains all Radiative Transfer (RT) results made for the paper.</p> <p>The data are stored in 5 zipped-folders names with the Cassini/VIMS cube flyby and id, or explicitly for Huygens/ULIS calibrated observations:</p> <ul> <li>TB_C1481624349_1</li> <li>T40_C1578266417_1</li> <li>T38_C1575509158_1</li> <li>T40_C1578263500_1</li> <li>T40_C1578263152_1</li> <li>ULIS_observations</li> </ul> <p>The TB_C1481624349_1 folder contains the Cassini/VIMS cube over HLS, the HLS end-member (End_member.txt), the surface albedo retrieved by Karkoschka et al. (2016) corrected for the photometry (HLS_Karkoschka_2016_spectrum.txt), and the inverted surface albedo (Surface_albedo.txt).</p> <p>In these folders, each VIMS pixel is stored in a .txt file with the following pattern:</p> <p><CUBE_ID>_<PIXEL_SAMPLE>_<PIXEL_LINE> .txt</p> <p>It starts with a header describing the observation: </p> <ul> <li>CUBE_ID: the VIMS cube id (`C1234567890_1` format)</li> <li>SAMPLE: the pixel sample number.</li> <li>LINE: the pixel line number.</li> <li>LONG: the pixel longitude (in degree).</li> <li>LAT: the pixel latitude (in degree).</li> <li>INC: the surface incident angle (in degree).</li> <li>EMI: the surface emergent angle (in degree).</li> <li>PHASE: the surface phase angle (in degree).</li> </ul> <p>For the Selk crater cubes (T40_C1578266417_1, T38_C1575509158_1, T40_C1578263500_1, T40_C1578263152_1), the header also contains the spatial sampling and the radiative transfer model outputs: </p> <ul> <li>Spatial sampling (km/pix).</li> <li>Fh: the haze scaling factor.</li> <li>Fm: the mist scaling factor.</li> <li>1-sigma (Fh): the 1-sigma uncertainty on Fh.</li> <li>1-sigma (Fm): the 1-sigma uncertainty on Fm.</li> <li>Reduced chi2: the reduced chi2. </li> </ul> <p>Then contains the observed spectra:</p> <ul> <li>Column 1: the VIMS channel central wavelength (in micrometers).</li> <li>Column 2: the VIMS pixel I/F.</li> <li>Column 3: the VIMS pixel I/F 1-sigma uncertainty. </li> </ul> <p>For the Selk crater cubes (T40_C1578266417_1, T38_C1575509158_1, T40_C1578263500_1, T40_C1578263152_1), 3 columns are added for: </p> <ul> <li>Column 4: the surface albedo.</li> <li>Column 5: the upper 1-sigma uncertainty on the surface albedo.</li> <li>Column 6 : the lower 1-sigma uncertainty on the surface albedo.</li> </ul> <p>The ULIS folder contains the Huygens/ULIS calibrated observations (in I/F) and the simulations with 1-sigma uncertainties as a function of the altitude (in km):</p> <ul> <li>Column 1: the VIMS channel central wavelength (in micrometers), stopped at the end of the Huygens/ULIS wavelength range.</li> <li>Column 2: the ULIS I/F.</li> <li>Column 3 : the simulated I/F.</li> <li>Column 4: the lower 1-sigma uncertainty on the simulation.</li> <li>Column 5 : the upper 1-sigma uncertainty on the simulation.</li> </ul>
Code from: When and where do waterbirds need water? Inferring candidate restoration areas from spatio-temporal variation in surface water availability
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Playa-Montmany, et al.: The thermoregulatory role of relative bill and leg surface areas in a Mediterranean population of Great tit
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Modulation of gill surface area does not correlate with oxygen loss in Chitala ornata
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2m Digital Surface Model From Photogrammetric Data, Niwot Ridge LTER Project Area, Colorado
Citation: Manley, W.F., Parrish, E.G., and Lestak, L.R., 2009, High-Resolution Orthorectified Imagery and Digital Elevation Models for Study of Environmental Change at Niwot Ridge and Green Lakes Valley, Colorado: Niwot Ridge LTER, INSTAAR, University of Colorado at Boulder, digital media. This dataset is a Digital Surface Model (DSM) for the Niwot Ridge Long Term Ecological Research (LTER) project area at 2 m resolution. The DSM is derived from the first reflective surface that was created from 12 micron digital stereo aerial photography. Elevation points were automatically filtered to represent bare earth conditions and then interpolated to a 2 meter raster dataset. A shaded relief model was then generated. The DSM and shaded relief model covers a total area of 98 km2 and is available in Environmental Systems Research Institute's (ESRI's) GRID format for a total dataset size of 125 MB. They share a UTM zone 13 projection, NAD83 horizontal datum and NAVD88 vertical datum, with FGDC-compliant metadata. The DSM is available through an unrestricted public license, and can be obtained online or on DVD by request (see Distributor contact information below). Imagery available in this series includes orthorectified aerial photography for 1953, 1972, 1985, 1990, 1999, 2000, 2002, 2004, 2006 and 2008. Together, the digital elevation models and imagery will be of interest to land managers, scientists, and others for observation and analysis of natural features and ecosystems. NOTE: This EML metadata file does not contain important geospatial data processing information. Before using any NWT LTER geospatial data read the arcgis metadata XML file in either ISO or FGDC compliant format, using ArcGIS software (ArcCatalog > description), or by viewing the .xml file provided with the geospatial dataset.
2m Digital Surface Shaded Relief Model From Photogrammetric Data, Niwot Ridge LTER Project Area, Colorado
Citation: Manley, W.F., Parrish, E.G., and Lestak, L.R., 2009, High-Resolution Orthorectified Imagery and Digital Elevation Models for Study of Environmental Change at Niwot Ridge and Green Lakes Valley, Colorado: Niwot Ridge LTER, INSTAAR, University of Colorado at Boulder, digital media. This dataset is a Digital Surface Model (DSM) shaded relief for the Niwot Ridge Long Term Ecological Research (LTER) project area at 2 m resolution. The DSM is derived from the first reflective surface that was created from 12 micron digital stereo aerial photography. Elevation points were automatically filtered to represent bare earth conditions and then interpolated to a 2 meter raster dataset. A shaded relief model was then generated. The DSM and shaded relief model covers a total area of 98 km2 and is available in Environmental Systems Research Institute's (ESRI's) GRID format for a total dataset size of 125 MB. They share a UTM zone 13 projection, NAD83 horizontal datum and NAVD88 vertical datum, with FGDC-compliant metadata. The DSM products are available through an unrestricted public license, and can be obtained online or on DVD by request (see Distributor contact information below). Imagery available in this series includes orthorectified aerial photography for 1953, 1972, 1985, 1990, 1999, 2000, 2002, 2004, 2006 and 2008. Together, the digital elevation models and imagery will be of interest to land managers, scientists, and others for observation and analysis of natural features and ecosystems. NOTE: This EML metadata file does not contain important geospatial data processing information. Before using any NWT LTER geospatial data read the arcgis metadata XML file in either ISO or FGDC compliant format, using ArcGIS software (ArcCatalog > description), or by viewing the .xml file provided with the geospatial dataset.
Data from: Macroevolution of desiccation-related morphology in plethodontid salamanders as inferred from a novel surface area to volume ratio estimation approach
Evolutionary biologists have long been interested in the macroevolutionary consequences of various selection pressures, yet physiological responses to selection across deep time are not well understood. In this paper, we investigate how a physiologically-relevant morphological trait, surface area to volume ratio (SA:V) of lungless salamanders, has evolved across broad regional and climatic variation. SA:V directly impacts an organisms' ability to retain water, leading to the expectation that smaller SA:Vs would be advantageous in arid, water-limited environments. To explore the macroevolutionary patterns of SA:V, we first develop an accurate method for estimating SA:V from linear measurements. Next, we investigate the macroevolutionary patterns of SA:V across 257 salamander species, revealing that higher SA:Vs phylogenetically correlate with warmer, wetter climates. We also observe higher SA:V disparity and rate of evolution in tropical species, mirrored by higher climatic disparity in available and occupied tropical habitats. Taken together, these results suggest that the tropics have provided a wider range of warmer, wetter climates for salamanders to exploit, thereby relaxing desiccation pressures on SA:V. Overall, this paper provides an accurate, efficient method for quantifying salamander SA:V, allowing us to demonstrate the power of physiological selection pressures in influencing the macroevolution of morphology.
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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.