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Dataset results
5 results for “surface backscattering”
Data archive for journal paper "Assimilation of Sentinel-1 Backscatter into a Land Surface Model with River Routing and Its Impact on Streamflow Simulations in Two Belgian Catchments"
<p>The datasets archived here include data assimilation results presented in the journal paper, "Assimilation of Sentinel-1 Backscatter into a Land Surface Model with River Routing and Its Impact on Streamflow Simulations in Two Belgian Catchments" (https://doi.org/10.1175/JHM-D-22-0198.1). The output was produced by combining land surface modeling (Noah-MP with HYMAP river routing) and Sentinel-1 backscatter data, applying a 1D Ensemble Kalman Filter using the NASA Land Information System. We provide Netcdf daily output files for 6 different experiments</p><p>- OLfd and OLgw: model-only (open-loop, OL) for two different model settings (fd: free drainage and gw: SIMTOP groundwater option) <br>- DASMfd and DASMgw: data assimilation (DA) with soil moisture (SM) updating for two different model settings (fd: free drainage and gw: SIMTOP groundwater option) <br>- DASMLAIfd and DASMLAIgw: data assimilation (DA) with soil moisture (SM) and leaf area index (LAI) updating for two different model settings (fd: free drainage and gw: SIMTOP groundwater option) </p><p>Each experiment directory contains five subdirectories (DAOBS, EnKF, ROUTING, RTM, SURFACEMODEL) with corresponding outputs as described in https://nasa-lis.github.io/LISF/LIS_users_guide/LIS_users_guide.html</p>
Satellite monthly surface chlorophyll-a concentration, particulate backscattering, Secchi Disk depth, Mixed Layer Depth, Sea Surface Temperature at 25 km resolution optimally interpolated for the North Atlantic Ocean (1998-2018)
<p>Satellite monthly records of surface chlorophyll-a concentration (CHL), particulate backscattering at 443nm (bbp), Secchi Disk depth (zsd), Mixed Layer Depth (MLD), Sea Surface Temperature (SST) at 25 km resolution optimally interpolated via Multivariate Singular Spectrum Analysis (MSSA) for the North Atlantic Ocean for the period 1998-2018. This dataset has been used for the article "Ultra-oligotrophic waters expansion in the North Atlantic Subtropical Gyre revealed by 21 years of satellite observations" Leonelli et al. 2022, where details of interpolation method are fully explained.</p>
Dataset for Surface waves prediction based on acoustic backscattering
<p>Underwater acoustic measurements dataset is represented by three types of files “.raw", “.mat", ".dat" as follows:<br> * “.raw" format also represented by three types of data.<br> - “...search.raw" files contain complex envelop from all hydrophones calculated at four emitted frequencies<br> - “...chan.raw" files is a signal in a wide band from one of the hydrophones - for control and noise analysis.<br> - the largest files are the raw wideband signal from all hydrophones. One such file was saved per eight-hour sound emission cycle.<br> * Spectrogram files are saved in MATLAB format “.mat” v7 . Phasing of the antenna array (all-round view) and calculation of window spectra near each emitted pulse was carried out.<br> * ".dat" files contain features of the average spectrum of the backscattered signal.<br> * Direct measurements of surface wave characteristics, made by a Datawell DWR-G4 wave-rider buoy, accompanied the acoustic measurements. This data is included too.</p> <p>In this archive, we upload all available files of the "dat" and "mat" type and a limited number of "raw" files. You may unpack all ".tar.gz" files into one folder, preserving the directory tree, existing in the archives.</p> <p>Users should refer to the included “.pdf” file for the data format description and to a published preprint for a description of the experimental conditions and instrumentation characteristics. See [arXiv:arXiv:2204.10153] via <a href="https://arxiv.org/abs/2204.10153">https://arxiv.org/abs/2204.10153</a> (Also check when the link is updated to the journal paper) </p> <p>The authors are grateful to their colleges, who helped during the expedition. Data acquisition would be impossible without their contribution. This research was supported by the Russian Science Foundation, grant number 20-77-10081 (the expedition and motivation for study) and the State Contract with the Ministry of Education and Science of the Russian Federation, grant number 0030-2021-0017 (the instruments for underwater acoustic measurements).</p>
Using generalized regression neural network to retrieve bare surface soil moisture from Radarsat-2 backscatter observations, regard less of roughness effect
<p>Description of soil moisture, correlation length, and RMS height from ground measurements of 147 sampling sites, full-polarized backscattering coefficients extracted from Radarsat-2 scene corresponding to those ground measurement sites.</p>
S-MODE DopplerScatt Level 1 Surface Doppler and Radar Backscatter Version 1
This dataset contains concurrent airborne DopplerScatt radar retrievals of surface vector winds and ocean currents from the Sub-Mesoscale Ocean Dynamics Experiment (S-MODE) during a pilot campaign conducted approximately 300 km offshore of San Francisco over two weeks in October 2021. S-MODE aims to understand how ocean dynamics acting on short spatial scales influence the vertical exchange of physical and biological variables in the ocean. DopplerScatt is a Ka-band (35.75 GHz) scatterometer with a swath width of 24 km that records Doppler measurements of the relative velocity between the platform and the surface. It is mounted on a B200 aircraft which flies daily surveys of the field domain during deployments, and data is used to give larger scale context, and also to compare with in-situ measurements of velocities and divergence. Level 1 data includes geolocated physical measurements for a measurement footprint, which are the basis for the DopplerScatt L2 surface winds and currents estimates. Data are available in netCDF format and are ordered by measurement acquisition time and radar range, and are not on a geospatial grid.
ScienceDex guides
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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.