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656 results for “albedo”
Dataset of Norwegian forest albedo carbon offset potential
<p>This dataset contains the following six files in geotiff format with additional user detail provided as a README.txt file: 1) Forest albedo effect in C-equivalent units for the present day climate 2) Forest albedo effect in C-equivalent units for the transient 21st century RCP4.5 climate 3) Forest albedo's carbon offset potential for the present day climate 4) Forest albedo's carbon offset potential for the transient 21st century RCP4.5 climate 5) Site Index (productivity class) of dominant tree species 6) Dominant tree species 7) README</p> <p>The dataset contains results and input data related the following publication: <br>Bright, R. M., Cataneo, N., Antón-Fernández, C., Eisner, S., Astrup, R., "Relevance of surface albedo to forestry policy in high latitude and altitude regions may be overvalued". <em>Environmental Research Letters, <span><a href="https://doi.org/10.1088/1748-9326/ad657e">https://doi.org/10.1088/1748-9326/ad657e</a></span></em> </p>
Dynamic Albedo of Neutrons (DAN) Simulated and Observed Die-Away Data
<p>These datasets provide the data associated with the article, "Analysis of active neutron measurements from the Mars Science Laboratory Dynamic Albedo of Neutrons instrument: Intrinsic variability, outliers, and implications for future investigations" by H. R. Kerner et al. (full citation below). The Dynamic Albedo of Neutrons (DAN) is a nuclear spectroscopy investigation onboard the Mars Science Laboratory (Curiosity) rover.</p> <p>If you use this dataset, please use the following citation: Kerner, H. R., Hardgrove, C. J., Czarnecki, S., Gabriel, T. S. J., Mitrofanov, I. G., Litvak, M. L., Sanin, A. B., and Lisov, D. I. Analysis of active neutron measurements from the Mars Science Laboratory Dynamic Albedo of Neutrons instrument: Intrinsic variability, outliers, and implications for future investigations. Under review. </p>
Spectral albedo and summer ground temperature of herbaceous and shrub tundra vegetation at Bylot Island, Canadian High-Arctic
<p>These data are in support of a preprint: </p><p>Comparing spectral albedo and NDVI of herbaceous and shrub tundra vegetation at Bylot Island, Canadian High-Arctic</p><p>Florent Domine, Maria-Belke-Brea, Ghislain Picard, Laurent Arnaud, and Esther Lévesque</p><p>To be submitted in 2023. </p><p>The spectral albedo of several vegetation assemblages on Bylot Island and in Mala River valley on nearby Baffin Island were recorded between 10 and 18 July 2015. The spectral range covered was 346 to 2400 nm. Surfaces were classified according to the main vegetation types. Classes used are graminoids, moss, Salix arctica, soil, and Salix richardsonii. S. richardsonii is the only truly erect species on Bylot Island. Transmission spectra of radiation through the S. richardsonii canopy were also recorded. S. richardsonii spectra were different depending on the location where they were measured and we present spectra for sites in active parts of an alluvial fan (Salix-G2), an inactive part of an alluvial fan (Salix-D1) and in a mesic area on Mala River Valley (Salix-M). We also present typical relative solar irradiance spectra recorded at Bylot Island during the campaign, under clear and overcast conditions. In conjunction with spectral albedo data, these irradiance spectra allow the calculation of the broadband (BB) albedo of the vegetation types and to compare BB albedo values under identical irradiance conditions. 83 spectra were recorded: 39 for S. richardsonii and 44 for low vegetation and soil. 17 transmission spectra under S. richardsonii were recorded. We present here only averages for each vegetation type. We also present averages for all low vegetation types and for all S. richardsonii spectra, to allow the calculation of the radiative impact of erect shrubs at Bylot Island. </p><p>We also present soil temperature data at 15 cm depth for the spots GRASS (mostly Salix Arctica), TUNDRA (Mostly moss), SALIX-D1 (Salix richardsonii) and SALIX-F (Salix richardsonii). SALIX-F is similar to SALIX-G2. The data are during summer 2020. </p><p>The locations of the various spots investigated are: </p><p><strong>Spot name Latitude Longitude Vegetation types found</strong></p><p>TUNDRA 73.150° -80.004° Humid and moist polygons with low vegetation dominated by mosses, graminoids, S. arctica and S. herbacea.</p><p>PLAINE 73.167° -79.915° Low vegetation and bare soil patches caused by cryoturbation (mudboils) with mosses, graminoids and S. arctica.</p><p>GRASS 73.158° -79.907° Low vegetation between patches of S. richardsonii dominated by S. arctica, with litter, mosses, graminoids and occasional bare soil. </p><p>SALIX-D1 73.158° -79.907° Scattered patches of S. richardsonii <35 cm tall. Understory is mosses, graminoids, litter, S. arctica and bare soil.</p><p>SALIX-M 73.006° -80.685° Mesic area with patches of S. richardsonii 35 to 40 cm tall. Understory includes moss, graminoids and litter. Between patches: herb tundra with graminoids and mosses. The area is not within an alluvial fan.</p><p>SALIX-G2 73.168° -79.812° Extended area in an alluvial fan with S. richardsonii >40 cm. Understory includes litter, mosses, graminoids, bare soil, S. arctica and S. reticulata.</p><p>SALIX-F 73.182° -79.745° Similar to SALIX-G2. Ground temperature is monitored there. No spectral data were recorded at that site. </p><p> </p><p> </p>
Global Daily Surface Blue-sky Albedo Climatology and Land Cover Climatology Dataset from 20-year MODIS Products (CMG)
<p>Surface albedo plays a critical role in climate, hydrological, and biogeochemical modeling and weather forecasting. Therefore, precisely mapping surface albedo climatology globally is necessary to better parameterize environmental systems. We generated a new global surface blue-sky actual and snow-free albedo climatology dataset from 20-year MODIS products from the Google Earth Engine (GEE). </p> <p>The 500m global surface blue-sky daily albedo climatology dataset is available at .... After reprojection and aggregation, the global Climate Modeling Grid (CMG) albedo climatology datasets at 0.05° and 0.5° are available here. All of the published datasets include historical and snow-free blue-sky albedo climatology data. For application convenience, the land cover climatology of MODIS product (MCD12Q1) is also generated and attached in the CMG files. The International Geosphere-Biosphere Programme (IGBP) and PFT classification results of MCD12Q1 since 2001 were reprojected and aggregated to 0.05° and 0.5° by find mode in each aggregation group. In order to check the heterogeneity of the land cover climatology, the percentage of the dominant type in each aggregation group was also calculated.</p>
What Controls the Mean East–West Sea Surface Temperature Gradient in the Equatorial Pacific: The Role of Cloud Albedo
<p>Climatologies for the climate model simulations performed by Burls and Fedorov 2014, Journal of Climate, <a href="https://doi.org/10.1175/JCLI-D-13-00255.1">https://doi.org/10.1175/JCLI-D-13-00255.1</a>. This table shows how the names of the simulation files provided in this dataset relate to the experiment names provided in Table 1 of Burls and Fedorov (2014, JOC).</p> <table> <thead> <tr> <th scope="col">Experiment # in Article (Table 1)</th> <th scope="col">Name of Files</th> </tr> </thead> <tbody> <tr> <td>1</td> <td>PreInd_T31_gx3v7*.nc</td> </tr> <tr> <td>2</td> <td>80p_op_LWP_1590deg_T31_gx3v7*.nc</td> </tr> <tr> <td>3</td> <td>60p_op_LWP_1590deg_T31_gx3v7*.nc</td> </tr> <tr> <td>4</td> <td>40p_op_LWP_1590deg_T31_gx3v7*.nc</td> </tr> <tr> <td>5</td> <td>20p_op_LWP_1590deg_T31_gx3v7*.nc</td> </tr> <tr> <td>6</td> <td>20p_LWP_1590deg_T31_gx3v7*.nc</td> </tr> <tr> <td>7</td> <td>40p_LWP_1590deg_T31_gx3v7*.nc</td> </tr> <tr> <td>8</td> <td>60p_LWP_1590deg_T31_gx3v7*.nc</td> </tr> <tr> <td>9</td> <td>80p_LWP_1590deg_T31_gx3v7*.nc</td> </tr> <tr> <td>10</td> <td>20p_ILWP_1590deg_tropx2_T31_gx3v7*.nc</td> </tr> <tr> <td>11</td> <td>40p_ILWP_1590deg_tropx2_T31_gx3v7*.nc</td> </tr> <tr> <td>12</td> <td>60p_ILWP_1590deg_tropx2_T31_gx3v7*.nc</td> </tr> <tr> <td>13</td> <td>80p_ILWP_1590deg_tropx2_T31_gx3v7*.nc</td> </tr> <tr> <td>14</td> <td>20p_ILWP_1590deg_tropx4_T31_gx3v7*.nc</td> </tr> <tr> <td>15</td> <td>40p_ILWP_1590deg_tropx4_T31_gx3v7*.nc</td> </tr> <tr> <td>16</td> <td>60p_ILWP_1590deg_tropx4_T31_gx3v7*.nc</td> </tr> <tr> <td>17</td> <td>80p_ILWP_1590deg_tropx4_T31_gx3v7*.nc</td> </tr> <tr> <td>18</td> <td>20p_ILWP_3060deg_tropx8_T31_gx3v7*.nc</td> </tr> <tr> <td>19</td> <td>40p_ILWP_3060deg_tropx8_T31_gx3v7*.nc</td> </tr> <tr> <td>20</td> <td>60p_ILWP_3060deg_tropx8_T31_gx3v7*.nc</td> </tr> <tr> <td>21</td> <td>80p_ILWP_3060deg_tropx8_T31_gx3v7*.nc</td> </tr> <tr> <td>22</td> <td>PreInd_0.9x1.25_gx1v6*.nc</td> </tr> <tr> <td>23</td> <td>40p_LWP_1590deg_0.9x1.25_gx1v6*.nc</td> </tr> <tr> <td>24</td> <td>60p_LWP_1590deg_0.9x1.25_gx1v6*.nc</td> </tr> <tr> <td>25</td> <td>40p_ILWP_1590deg_tropx2_0.9x1.25_gx1v6*.nc</td> </tr> <tr> <td>26</td> <td>60p_ILWP_1590deg_tropx2_0.9x1.25_gx1v6*.nc</td> </tr> </tbody> </table> <p>Article abstract:</p> <p>The mean east–west sea surface temperature gradient along the equator is a key feature of tropical climate. Tightly coupled to the atmospheric Walker circulation and the oceanic east–west thermocline tilt, it effectively defines tropical climate conditions. In the Pacific, its presence permits the El Niño–Southern Oscillation phenomenon. What determines this temperature gradient within the fully coupled ocean–atmosphere system is therefore a central question in climate dynamics, critical for understanding past and future climates. Using a comprehensive coupled model [Community Earth System Model (CESM)], the authors demonstrate how the meridional gradient in cloud albedo between the tropics and midlatitudes (Δα) sets the mean east–west sea surface temperature gradient in the equatorial Pacific. To change Δα in the numerical experiments, the authors change the optical properties of clouds by modifying the atmospheric water path, but only in the shortwave radiation scheme of the model. When Δα is varied from approximately −0.15 to 0.1, the east–west SST contrast in the equatorial Pacific reduces from 7.5°C to less than 1°C and the Walker circulation nearly collapses. These experiments reveal a near-linear dependence between Δα and the zonal temperature gradient, which generally agrees with results from the Coupled Model Intercomparison Project phase 5 (CMIP5) preindustrial control simulations. The authors explain the close relation between the two variables using an energy balance model incorporating the essential dynamics of the warm pool, cold tongue, and Walker circulation complex.</p>
Winter Season Spectral Snowpack Albedo Data For the Caldor and Creek Fires
<p>* Description: The file "Caldor_Creek_Fires_Winter_Snow_Albedo_Spectrometer_Dataset.csv" is a comma-delimited file containing the spectral snowpack albedo measurements from the Caldor and Creek Fires in California and the associated burn severities at the location of each measurement.</p> <p> </p> <p>Data and File Overview</p> <p>======================</p> <p>Summary Metrics</p> <p>---------------</p> <p>* File count: 1</p> <p>* Total file size: 909 KB </p> <p>* Range of individual file sizes: 909 KB </p> <p>* File formats: .csv</p> <p> </p> <p>Naming Conventions</p> <p>------------------</p> <p>* File naming scheme: One file that includes all dates, all burn severities, all wavelengths.</p> <p>* Format(s): Comma-separated value (.csv) file</p> <p>* Size(s): 909 KB</p> <p>* Dimensions: 17,209 rows x 6 columns</p> <p>* Variables:</p> <p> * Measurement_Number: An index of the measurement number, unitless</p> <p> * wavelength: The wavelength of light (units in nanometers) for which albedo sample ranging from 350-2500 nm</p> <p> * Type: Measurement type is albedo in various burn severity environments (_hb is high burn severity, _mb is moderate burn severity, _ub is unburned, with the last letter corresponding to the month (J is January, F is February, A is April). NA corresponds to estimated January unburned data for the Caldor Fire where unburned albedo for April in the Creek Fire was adjusted downwards by 0.04 to account for less grain-size growth (Colbeck 1982, Rev. Geophys., https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/RG020i001p00045). </p> <p> * Albedo: The albedo (unitless), is a measurement of the solar radiation reflected by the snow surface divided by the radiation incident on its surface. In other words, albedo is the fraction of the incident sunlight reflected by the snow.</p> <p> * month: The month when the measurement was taken</p> <p> * burn: Burn severity at measurement location based upon classifications (High, Medium,, Unburned) from the Monitoring Trends in Burn Severity Dataset (https://mtbs.gov/). NA corresponds to the estimated unburned data for the Caldor Fire using April unburned data in the Creek Fire.</p> <p> * Missing data codes: No missing data is presented.</p> <p> </p> <p>Dates and Locations</p> <p>-------------------</p> <p>* Dates of data collection: Surface albedo collected in 27-28 February 2021, 1 April 2021, and 21 January 2022</p> <p>* Geographic locations of data collection: Data collected within the Caldor Fire perimeter in the central Sierra Nevada, California-Nevada (January 2022) and the Creek Fire perimeter, California (February and April 2021).</p> <p> </p> <p>Setup</p> <p>-----</p> <p>* Recommended software/tools to open file: parentage- R Studio; file can be opened using any text editor or programming language (e.g., R Studio, MATLAB, Python, TextMate, Microsoft Excel, etc)</p> <p> </p>
Dataset for "Joint optimization of land carbon uptake and albedo can help achieve moderate instantaneous and long-term cooling effects"
<p>Data and Code for 'Joint optimization of land carbon uptake and albedo can help achieve moderate instantaneous and long-term cooling effects' by Graf et al. (Communications Earth and Environment)</p>
[Dataset] Spatial and temporal variability of the 365-nm albedo of Venus observed by the camera on board Venus Express
<p>This is the derived data, presented in a publication entitled "Spatial and temporal variability of the 365-nm albedo of Venus observed by the camera on board Venus Express" (JGR:Planet, doi: 10.1029/2019JE006271). See the paper for details. See 'Readme.txt' for the file descriptions.</p>
Precipitating Solar Wind Hydrogen at Mars: Improved Calculations of the Backscatter and Albedo with MAVEN Observations
<p>These files contain the derived data products used in the paper, including the penetrating and backscatter energy spectra and directional fluxes. See Readme.txt for a description of the data that is stored in each file.</p>
Data of LAI-L20C in Vegetation masking effect on future warming and snow albedo feedback in a boreal forest region of northern Eurasia according to MIROC-ESM
<p>Data of LAI-L20C experiment in the research paper: Vegetation masking effect on future warming and snow albedo feedback in a boreal forest region of northern Eurasia according to MIROC-ESM.</p> <p>The paper was submitted to JGR-Atmosphere.</p> <p>Variables are limited to those used in the paper.</p> <ul> <li>snow water equivalent (swe)</li> <li>snow cover fraction (snc)</li> <li>clear-sky downward shortwave radiation at surface (rsdscs)</li> <li>clear-sky upward shortwave radiation at surface (rsuscs)</li> <li>surface air temperature (tas)</li> </ul> <p>See the paper for the detail.</p>
Supporting data for "Modeling the albedo neutron decay source of radiation belt electrons and protons"
<p>Data sets are provided in support of the publication to appear in JGR-Space Physics. They include tabulated values of computed albedo neutron flux above the atmosphere, and of resulting radiation belt electron and proton source functions. Data format is described in the README files.</p>
Climate Response to ~23% Albedo Reduction in IPSL-CM5A2-LR
<p>The dataset consists of IPSL-CM5A2-LR outputs from a present-day control (pdControl, Con) and 23% Arctic sea ice albedo reduction experiment (Alb). Both sets of experiments are annual means for 200 years of simulation. The Con has 12 members from two restarts (7 and 5) and the Alb experiment has 14 members from the same restarts (9 and 5). Annual datasets include: Winter (JFM) and summer (JAS) sea ice area fraction (SIA), Atlantic overturning streamfunction (zomsfatl,msftrho), sea level pressure (SLP), sea surface temperature (TOS), sea surface salinity (SOS), barotropic streamfunction (BSF), zonal windstress (TAUX), and meridional windstress (TAUY). Since there are two restarts from different model years, the time axis has been changed to count years of the experiment (i.e. 1,2,3,...200). The anomalies of the Alb experiment are also provided taking into account the respective control. The missing data is recorded as nan.</p> <p>The datasets are created from the IPSL-CM5A-LR output files, using CDO and Python3 commands to combine and create annual averages.</p>
Daily 1 km seamless Antarctic sea ice albedo product from VIIRS data
<p><strong>Summary</strong>:<strong> </strong>In the context of climate change, the sea ice albedo feedback mechanism makes the albedo of Antarctic sea ice a crucial element in polar environmental evolution and global climate models. Existing albedo products for Antarctic sea ice are limited, with a coarse spatiotemporal resolution, and numerous data gaps due to persistent cloud cover. This study uses the Multiband Reflectance Iteration (MBRI) algorithm, which retrieves the Antarctic sea ice albedo using reflectance data from the Visible Infrared Imaging Radiometer Suite (VIIRS). Moreover, the study reconstructs the albedo of cloudy-sky pixels by integrating spatiotemporal information and physical models. A new 1 km daily seamless albedo product for Antarctic sea ice has been developed, covering the period from 2012 to 2021. The results, validated against the automatic weather stations data from the Baseline Surface Radiation Network (BSRN), reveal that the proposed product has higher accuracy, finer spatiotemporal resolution, and superior spatial continuity compared to existing products. The algorithms used fully account for the anisotropy of the sea ice surface, and the high spatiotemporal resolution enables this dataset to enable quantitative analysis of both overall and localized Antarctic sea ice changes. This dataset is valuable for studying the radiation balance of Antarctic sea ice and conducting research in climate modeling. Uncertainty of the dataset is available at https://doi.org/10.5281/zenodo.15067607.</p> <p><strong>Spatial resolution</strong>: 1 km</p> <p><strong>Temporal resolution</strong>: daily (2012-2021)</p> <p><strong>Format</strong>: GeoTIFF</p> <p><strong>Projection</strong>: This dataset adopts Sinusoidal projection and is gridded using the MODIS Sinusoidal Tile Grid</p> <p><strong>How to name and use data files</strong>: The dataset has a longitude range of 180°W to 180°E and a latitude range of 50°S to 80°S, covering 53 tiles (v14: h06~h29; v15: 09~h26; V16: h11~h17, h21~h24). The GeoTIFF file contains a band that represents the shortwave sea ice albedo under clear-sky or cloudy-sky conditions, with 16-bit integer values of 0-10000 and a scale factor of 0.0001. The ocean water and Antarctic continent are set to a filling value of -1. The file name is "Antarctic_Sea_Ice_Albedo_ {yyyyddd}_ {hv}.tif ”, where yyyy represents year, ddd represents day of the year, and hv represents the number of the tile. For example, "Antarctic_Sea_Ice_Albedo_2014270_h18v15.tif" represents the sea ice albedo data of the h18v15 area on the 270th day of 2014. </p> <p><strong>Contacts</strong>: Weifeng Hao (haowf@whu.edu.cn), Chao Ma (macwhu@whu.edu.cn)</p> <p> </p> <p> </p>
Snow Albedo Measurements in Mountainous Regions Using a Dual-sensor Unmanned Aerial Vehicle (UAV)
<p>We used a commercially available UAV (drone) to measure the albedo of the Earth in snowy, mountainous environments. These data represent four initial flights conducted during the spring of 2019 in SW Montana, USA. These UAV-based measurements of albedo allow us to measure a larger and more varied area than do measurements from a stationary tower. </p>
Digital Elevation Models from Planetary Flyby Images of Mercury and the Moon with Shape and Albedo from Shading
<p>Supplemantary material to Krüll, I., Wohlfarth, K., Tenthoff, M., Wöhler, C., Galluzzi, V., Wright, J., Benkhoff, J., and Zender, J.: Shape and Albedo from Shading with Planetary Flyby Images of Mercury and the Moon, Europlanet Science Congress 2024, Berlin, Germany, 8–13 Sep 2024, EPSC2024-247, https://doi.org/10.5194/epsc2024-247, 2024.</p> <p><strong>Abstract</strong></p> <p>Surface reconstruction of planetary bodies such as the Moon and Mercury is crucial for geomorphological analysis, reflectance normalization, thermal modeling, rover landing site planning, and outreach activities. Stereo algorithms and Shape-and-Albedo-from-Shading (SAfS) are well-established methods for planetary 3D reconstruction. SAfS refines the surface slopes of a stereo Digital Elevation Model (DEM) and typically yields 3D models at image resolution. This approach is well-validated for scientifically calibrated instruments that observe the planetary body under favorable conditions. This work applied the SAfS algorithm to more challenging planetary flyby images acquired with uncalibrated off-the-shelf cameras. We investigated three scenarios: a fly-by image of the Moon captured by a GoPro during the Artemis I mission, a fly-by image of Mercury which was obtained with a monitoring camera during BepiColombo’s third flyby, and a telescope image taken in Wetter, Germany. We qualitatively and quantitatively assessed the algorithm's performance. The results of the two flyby images indicate that, despite the challenging conditions, the SAfS algorithm could reconstruct the surface up to image resolution and increase the level of detail of the input DEM. The reconstructed DEM of the telescope image is the one with the lowest resolution. All in all, our flyby-derived DEMs are accurate. They provide excellent outreach products, as demonstrated by ESA's BepiColombo flyby movie: https://www.esa.int/Science_Exploration/Space_Science/BepiColombo/BepiColombo_s_third_Mercury_flyby_the_movie</p> <p><strong>Dataset<br></strong></p> <p>We applied the SAfS algorithm to different Regions of Interest (ROIs) in the flyby and telescope images. The ROIs are marked in Artemis_Flyby_ROIs.png, Bepicolombo_Flyby3_ROIs.png and Moon_Telescope_ROIs.png, respectively. For each ROI a DEM is provided centered on the latitude and longitude (0-360, positive east) in the filename. Furthermore a Red/ Blue Stereo anaglyph of the original image was created with the SAfS DEM (for this purpose the height has been exaggerated).</p> <p> </p>
"Albedo effect" experiment
<p>This dataset is relative to the "albedo effect" experiment that has been carried out in the winter 2016/2017 in Balme, Turin, Italy, during project MeteoMet 2. <br> The experiment consists in two measurement points, 20 m apart, in an open flat field, each hosting 6 different meteorological temperature sensors and shields in a pair, so that each of the systems in one measurement point has an identical twin in the other measurement point. Each measurement point also hosts an albedometer to measure incident and reflected radiation and hygrometers. In a third measurement point, wind speed is measured.<br> The difference between the two main measurement points is that on point "a", snow was left for the whole winter, while on point "b" it was removed in 4 occasions (30 November, 22 December 2016, 20 January and 23 February 2017). The height of the snow never exceeded 40 cm.</p>
An operational methodology for validating satellite-based snow albedo measurements using a UAV
<p>This dataset contains all data supporting the conclusions of the manuscript entitled "An operational methodology for validating satellite-based snow albedo measurements using a UAV", submitted to Frontiers in Remote Sensing on August 30, 2021.</p>
Snow melt onset date estimates derived from CLARA-A2 SAL surface albedo dataset
<p>Snow melt onset date estimates for the Northern Hemisphere, 1982-2015. Derived from the CLARA-A2 SAL surface albedo dataset. Version for manuscript review.</p>
Derived data supporting the analysis of surface albedo changes from Mars 2020 observations: Probabilistic distribution of the Amplitude Spectral Densities of Supercam microphone recordings and Monte-Carlo dust devil simulations.
<p>These files contain derived data used in the analysis submitted for publication in Journal of Geophysical Research: Planets, entitled "Dust Lifting Through Surface Albedo Changes at Jezero Crater, Mars" by Vicente-Retortillo et al. The article was initially submitted on November 14, 2022, and the revised version on March 1, 2023.</p> <p>Files include the derived data and information needed to generate Figures 4 (Microphone_Data.mat and Plot_ASD_from_Microphone_Data) and 6 (remaining files) of the article.</p>
Using neural networks to model Main Belt Asteroid albedos as a function of their proper orbital elements
<p>This repository contains a copy of the following repository https://github.com/r-zachary-murray/Asteroid-Albedos. It contains weights for an ensemble of neural nets trained on the Asteroid Family Portal proper elements and NEOWISE albedos. These weights can be used to predict albedos of asteroids based of their proper elements. Example.ipynb contains an ipython notebook that shows how these predictions can be made.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.