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Aeolian saltation measurement and meteorological data over typical desert surfaces on the Alxa Plateau

The data were collected from five meteorological stations situated over typical desert surfaces on the Alxa Plateau from November 2018 to December 2019. This dataset encompassed mean daily wind speed and direction, air temperature (℃), relative humidity (RH), cumulative saltation particle counts and kinetic energy. The measurement duration at the gravel Gobi site lasted over 9 months for uncontrollable reasons. Due to the involvement of unpublished articles in high-resolution data, this dataset only provides daily data as a reference. We will supplement high-resolution data in the future.

DAVE - Measuring run on Mittellandkanal in Hannover, Germany - Canal

The dataset was collected during a measurement run on the Mittellandkanal in Hanover, Germany. The data is provided in the ros2bag mcap storage format. The bag files contain data from the following sensors  <ul> <li>Lidar</li> <li>Camera</li> <li>GPS</li> <li>Wind</li> </ul> The bag files can be played using the free foxglove studio software. A layout json file is also provided.  These bag files show parts of the canal with a focus on bridges.   This publication is a result of the research of the Center of Excellence CoSA and funded by the Federal Ministry for Digital and Transport of the Federal Republic of Germany (Id 19F2225C, DAVE).   Project website: https://www.th-luebeck.de/cosa/projekt/dave/

Measuring the Variability of Hydroxyl Emissions in Infrared Sky Spectra using SPIRou: Dataset

Abstract Subtracting the changing sky contribution from the near-infrared (NIR) spectra of faint astronomical objects is challenging and crucial to a wide range of science cases such as estimating the velocity dispersions of dwarf galaxies, studying the gas dynamics in faint galaxies, and accurate redshifts, and any spectroscopic studies of faint targets. Since the sky background varies with time and location, NIR spectral observations, especially those employing fiber spectrometers and targeting extended sources, require frequent sky-only observations for calibration. However, sky subtraction can be optimized with sufficient a priori knowledge of the sky’s variability. In this work, we explore how to optimize sky subtraction by analyzing 1075 high-resolution NIR spectra from the CFHT’s SPIRou on Maunakea, and we estimate the variability of 481 hydroxyl (OH) lines. These spectra were collected during two sets of three nights dedicated to obtaining sky observations every five and a half minutes. During the first set, we observed how the Moon affects the NIR, which has not been accurately measured at these wavelengths. We suggest that if one uses a principal component analysis reconstruction of the sky spectrum and attempts to observe targets at Y JHK mags fainter than &sim;15 and attempts a sky subtraction better than 1%, then the Moon contribution must be accounted for at Moon separation distances of at least 10◦. We also identified 126 spectral doublet, or OH lines that split into at least two components, at SPIRou’s resolution. In addition, we used Lomb-Scargle Periodograms and Gaussian process regression to estimate most OH lines vary on similar timescales, which provides a valuable input for IR spectroscopic survey strategies. The data and code developed for this study are publicly available here. Dataset description In total, we collected 1075 sky observations, which spanned from July 28th, 2018 to January 10th, 2022, or approximately 3.5 years. These observations included two sets of three days dedicated to sky measurement where each day, a sky spectrum was observed approximately every 5.5 minutes for 12 hours. These days occurred on December 14th, 15th, and 16th of 2019 and January 22nd, 23rd, and 25th 2020. These 1D extracted and flat fielded sky spectra have a wavelength range of 0.965 − 2.500μm containing 285,377 wavelength bins resampled on a uniform wavelength grid with a step of 1 km/s/pixel. Since the pixels were constant in velocity, the change in wavelength increased from 3x10^−6 − 8x10^−6 μm per pixel. All observations were affected by a steep black body curve starting at 2.1μm, which was caused by thermal emission. We also present a table of doublets identified during this study with the transition, the measured singlet line from Rousselot 2000 (mu0), the doublet lines (mu1 and mu2), and if the line was identified as a doublet (Y/N).

Magnetic diffusion in Solar atmosphere produces measurable electric fields

Stokes spectra in 397, 630, and 854 nm with a field-of-view of 10"x10" that contains the analyzed Ellerman bomb

LENS: A LEO Satellite Network Measurement Dataset - 202406 - Part 3

LENS dataset 2024-06 Part 3 Please see https://github.com/clarkzjw/LENS for the complete description of the dataset.

LENS: A LEO Satellite Network Measurement Dataset - 202406 - Part 2

LENS dataset 2024-06 Part 2 Please see https://github.com/clarkzjw/LENS for the complete description of the dataset.

LENS: A LEO Satellite Network Measurement Dataset - 202407 - Part 3

LENS dataset 2024-07 Part 3 Please see https://github.com/clarkzjw/LENS for the complete description of the dataset.

LENS: A LEO Satellite Network Measurement Dataset - 202407 - Part 2

LENS dataset 2024-07 Part 2 Please see https://github.com/clarkzjw/LENS for the complete description of the dataset.

opencc-by-sa-4.0Aug 2024View details →

LENS: A LEO Satellite Network Measurement Dataset - 202407 - Part 1

LENS dataset 2024-07 Part 1 Please see https://github.com/clarkzjw/LENS for the complete description of the dataset.

LENS: A LEO Satellite Network Measurement Dataset - 202406 - Part 1

LENS dataset 2024-06 Part 1 Please see https://github.com/clarkzjw/LENS for the complete description of the dataset.

LENS: A LEO Satellite Network Measurement Dataset - 202407 - Part 4

LENS dataset 2024-07 Part 4 Please see https://github.com/clarkzjw/LENS for the complete description of the dataset.

Contrail altitude estimation using GOES-16 ABI data and deep learning: Dataset of contrails collocated with CALIOP satellite measurements

Open the record for dataset details and reuse information.

DAVE - Measuring run on Mittellandkanal in Hannover, Germany - Lock entrance

The dataset was collected during a measurement run on the Mittellandkanal in Hanover, Germany. The data is provided in the ros2bag mcap storage format. The bag files contain data from the following sensors  <ul> <li>Lidar</li> <li>Camera</li> <li>GPS</li> <li>Wind</li> </ul> The bag file can be played using the free foxglove studio software. A layout json file is also provided.  This bag file shows the lock Anderten in the canal.   This publication is a result of the research of the Center of Excellence CoSA and funded by the Federal Ministry for Digital and Transport of the Federal Republic of Germany (Id 19F2225C, DAVE).   Project website: https://www.th-luebeck.de/cosa/projekt/dave/

Surfaces/regoliths used in the training and testing of the deep neural network for surface reconstruction from simulated exospheric measurements

This dataset contains the surfaces/regoliths in terms of elemental surface composition used in v2.0 - v2.5 of the paper collection: "Conceptual framework for the application of deep neural networks to surface composition reconstruction from Mercury’s exosphere".

Inputs and outputs for exospheric simulations used in the deep neural network for surface reconstruction from simulated exospheric measurements

This dataset contains the inputs and outputs of the exospheric simulations performed for v2.0 - v2.5 of the paper collection: "Conceptual framework for the application of deep neural networks to surface composition reconstruction from Mercury’s exosphere".

Inputs and outputs for the training and testing of a deep neural network for surface reconstruction from simulated exospheric measurements

This dataset contains inputs (datasets) and outputs (trainings and tests) used in v2.0 - v2.5 of the paper collection: "Conceptual framework for the application of deep neural networks to surface composition reconstruction from Mercury’s exosphere".

MACADAMIA Sloan Digital Sky Survey Asteroid Photometry, Measurements, and Images

This dataset contains data from the Multi-Archive Catalog of Asteroid Detections And Measurements for Interactive Access (MACADAMIA), specifically of numbered asteroids observed serendipitously by the Sloan Digital Sky Survey (SDSS). photometry_archive_20201027.db is a SQLite database containing data corresponding to a search of the SDSS image archive conducted on 2020 May 1 of all numbered asteroids known at the time, which yielded 2.84 million search results, 1.98 million detections that were determined to actually be within the field of view of the identified image, and 993,777 successfully measured detections.  Preview images of all detections and non-detections where the object was determined to be within the field of view of an identified image are collected in the detection_previews_*tar.gz files in this dataset, indexed by detection_id in the photometry database and listed under preview_image_file in the detection_data table. photometry_archive_20210927.db contains an update to the SDSS search, containing data corresponding to a search of the SDSS image archive conducted on 2021 July 2 of all numbered asteroids known at the time, which yielded 2.96 million search results, 2.06 million detections that were determined to actually be within the field of view of the identified image, and 1.02 million successfully measured detections.  Previews of additional detections identified in this updated search may not be available due to data loss in a system failure in August 2023.

Genetic fine-mapping results for 56 NMR metabolites measured in 246,683 UK Biobank participants

Fine-mapping credible sets for 56 metabolites measured in 246,683 UK Biobank participants using the Nightingale Health platform. Fine-mapping was performed using the https://github.com/AlasooLab/reGSusie workflow. The 56_metabolites_finemapping_credible_sets.tsv file contains the fine-mapped credible sets for all 56 metabolites. The *_coloc5_final.tsv.gz files contain the log Bayes factors for each metabolite in each fine-mapped region.

From forest strategy to measures: what are forest owner attitudes & area size responses toward climate-proof forest management in Sweden and the Netherlands?

The anonymous datasets from Swedish (records of 98 responses) and Dutch forest climate surveys (records of 241 responses), which are used for the statistical Kruskal Wallis tests, are freely available and accessible via this repository database (https://zenodo.org), as prescribed by the FAIR data policy of the Forclimit project sponsors.  The surveys and the Small Scale Forestry article are deliverables of the European 2017-2020 Forclimit project "Mobilizing and monitoring climate positive efforts in the forest sector" The umbrella of the project is FACCE ERA-GAS, i.e. ERA-NET co-fund for monitoring & mitigation of GHG from agriculture and sylviculture (Horizon2020, award # 696356). The other co-funders are the Dutch research council 'NWO' (grant award # 516-095-7542) and its Swedish equivalent 'FORMAS' (grant award # 2017-01751).

Selected quantitative measurements of Ceratitis capitata embryonic development

Selected quantitative measurements of Ceratitis capitata embryonic development (processed image data, Mathematica notebooks, as well as intermediate measurement and visualization files)