The Google Satellite Embedding dataset is a global, analysis-ready collection of learned geospatial embeddings. Each 10-meter pixel in this dataset is a 64-dimensional representation, or "embedding vector," that encodes temporal trajectories of surface conditions at and around that pixel as measured by various Earth observation instruments and datasets, over a …

Major TOM Core AlphaEarth Embeddings Subset

This is a prototype dataset. It only includes some of the AlphaEarth embeddings stored in Major TOM grid cells. This dataset is mostly aimed at experimentation and prototyping. It is particularly useful to use it along other datasets published within the Major TOM project.

  Content

Field Type Description

grid_cell string Major TOM cell

year int year of the sample

thumbnail image 3-dimensional PCA… See the full description on the dataset page: https://huggingface.co/datasets/Major-TOM/Core-AlphaEarth-Embeddings.

Sentinel2GlobalLULC is a deep learning-ready dataset of RGB images from the Sentinel-2 satellites designed for global land use and land cover (LULC) mapping. Sentinel2GlobalLULC v2.1 contains 194,877 images in GeoTiff and JPEG format corresponding to 29 broad LULC classes. Each image has 224 x 224 pixels at 10 m spatial resolution and was produced by assigning the 25th percentile of all available observations in the Sentinel-2 collection between June 2015 and October 2020 in order to remove atmospheric effects (i.e., clouds, aerosols, shadows, snow, etc.). A spatial purity value was assigned to each image based on the consensus across 15 different global LULC products available in Google Earth Engine (GEE).

Our dataset is structured into 3 main zip-compressed folders, an Excel file with a dictionary for class names and descriptive statistics per LULC class, and a python script to convert RGB GeoTiff images into JPEG format. The first folder called "Sentinel2LULC_GeoTiff.zip" contains 29 zip-compressed subfolders where each one corresponds to a specific LULC class with hundreds to thousands of GeoTiff Sentinel-2 RGB images. The second folder called "Sentinel2LULC_JPEG.zip" contains 29 zip-compressed subfolders with a JPEG formatted version of the same images provided in the first main folder. The third folder called "Sentinel2LULC_CSV.zip" includes 29 zip-compressed CSV files with as many rows as provided images and with 12 columns containing the following metadata (this same metadata is provided in the image filenames):

• Land Cover Class ID: is the identification number of each LULC class
• Land Cover Class Short Name: is the short name of each LULC class
• Image ID: is the identification number of each image within its corresponding LULC class
• Pixel purity Value: is the spatial purity of each pixel for its corresponding LULC class calculated as the spatial consensus across up to 15 land-cover products
• GHM Value: is the spatial average of the Global Human Modification index (gHM) for each image
• Latitude: is the latitude of the center point of each image
• Longitude: is the longitude of the center point of each image
• Country Code: is the Alpha-2 country code of each image as described in the ISO 3166 international standard. To understand the country codes, we recommend the user to visit the following website where they present the Alpha-2 code for each country as described in the ISO 3166 international standard:https: //www.iban.com/country-codes
• Administrative Department Level1: is the administrative level 1 name to which each image belongs
• Administrative Department Level2: is the administrative level 2 name to which each image belongs
• Locality: is the name of the locality to which each image belongs
• Number of S2 images : is the number of found instances in the corresponding Sentinel-2 image collection between June 2015 and October 2020, when compositing and exporting its corresponding image tile

For seven LULC classes, we could not export from GEE all images that fulfilled a spatial purity of 100% since there were millions of them. In this case, we exported a stratified random sample of 14,000 images and provided an additional CSV file with the images actually contained in our dataset. That is, for these seven LULC classes, we provide these 2 CSV files:

• A CSV file that contains all exported images for this class
• A CSV file that contains all images available for this class at spatial purity of 100%, both the ones exported and the ones not exported, in case the user wants to export them. These CSV filenames end with "including_non_downloaded_images".

To clearly state the geographical coverage of images available in this dataset, we included in the version v2.1, a compressed folder called "Geographic_Representativeness.zip". This zip-compressed folder contains a csv file for each LULC class that provides the complete list of countries represented in that class. Each csv file has two columns, the first one gives the country code and the second one gives the number of images provided in that country for that LULC class. In addition to these 29 csv files, we provided another csv file that maps each ISO Alpha-2 country code to its original full country name.

© Sentinel2GlobalLULC Dataset by Yassir Benhammou, Domingo Alcaraz-Segura, Emilio Guirado, Rohaifa Khaldi, Boujemâa Achchab, Francisco Herrera & Siham Tabik is marked with Attribution 4.0 International (CC-BY 4.0)

The SORCE SOLSTICE Level 3 Lyman-alpha Irradiance As-Measured Cadence product consists of all measurements of the Lyman-alpha irradiance from the SOLSTICE instrument. The SOLSTICE instrument makes measurements during each daytime orbit portion, 15 orbits per day. A complete solar spectrum is made in about 30 minutes, a quick scan mode in about 5 minutes. The spectral resolution of SOLSTICE is 0.1 nm.

The Lyman-alpha data are stored in netCDF files containing a full year of. Each days measurements are in a separate netCDF group. Each group contains variables for irradiance, uncertainty, repeatability, long x-ray flux, short x-ray flux, spacecraft height, latitude, longitude, time, wavelength and target zenith angle, with overr 3000 measurements.

We use more than a decade of radial-velocity measurements for {alpha} Cen A, B, and Proxima Centauri from the High Accuracy Radial Velocity Planet Searcher, CTIO High Resolution Spectrograph, and the Ultraviolet and Visual Echelle Spectrograph to identify the Msin(i), and orbital periods of planets that could have been detected if they existed. At each point in a mass-period grid, we sample a simulated, Keplerian signal with the precision and cadence of existing data and assess the probability that the signal could have been produced by noise alone. Existing data places detection thresholds in the classically defined habitable zones at about Msin(i) of 53 M_{Earth}, for {alpha} Cen A, 8.4 M{Earth}, for {alpha} Cen B, and 0.47 M{Earth}_, for Proxima Centauri. Additionally, we examine the impact of systematic errors, or "red noise" in the data. A comparison of white- and red-noise simulations highlights quasi-periodic variability in the radial velocities that may be caused by systematic errors, photospheric velocity signals, or planetary signals. For example, the red-noise simulations show a peak above white-noise simulations at the period of Proxima Centauri b. We also carry out a spectroscopic analysis of the chemical composition of the {alpha} Centauri stars. The stars have super-solar metallicity with ratios of C/O and Mg/Si that are similar to the Sun, suggesting that any small planets in the {alpha} Cen system may be compositionally similar to our terrestrial planets. Although the small projected separation of {alpha} Cen A and B currently hampers extreme-precision radial-velocity measurements, the angular separation is now increasing. By 2019, {alpha} Cen A and B will be ideal targets for renewed Doppler planet surveys.

The CAMEX-4 NOAA Lyman-Alpha Hygrometer dataset was collected by the NOAA Lyman-alpha Total Water Hygrometer, which was flown during the fourth field campaign in the CAMEX series (CAMEX-4). CAMEX-4 ran from 16 August to 24 September 2001 and was based out of Jacksonville Naval Air Station, Florida, and included missions in the Gulf of America, Caribbean and Western Atlantic. The experiment focused on the study of tropical cyclone (hurricane) development, tracking, intensification, and landfalling impacts using both NASA-funded aircraft and surface remote sensing instrumentation.

Country area DEM provided as 1201x1201 pixel tiles, based on GADM v2.0 country boundaries (http://www.gadm.org/) with some island ccid, internal country boundary, and enclave amendments from gpwv4 (http://www.ciesin.columbia.edu/data/gpw-v4) and GADM v2.8, and Viewfinder Panorama SRTM based 3" topography tiles (http://viewfinderpanoramas.org/). Calculated using Earth surface area grid.

NOTE: This initial version of the Mauritania settlement extents has been superseded by the final version, "GRID3 Mauritania Settlement Extents, Version 01", now available here: https:// data.humdata.org/dataset/grid3-mauritania-settlement-extents-version-01

This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative in Mauritania.

GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/

Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2020. GRID3 Mauritania Settlement Extents Version 01, Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. DOI: https://doi.org/10.7916/d8-hzv3-f435 . Accessed DAY MONTH YEAR

This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative in Benin.

GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/

Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2020. GRID3 Benin Settlement Extents Version 01, Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. DOI: https://doi.org/10.7916/d8-b84x-g695. Accessed DAY MONTH YEAR

This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative in Togo.

GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/

Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2020. GRID3 Togo Settlement Extents Version 01, Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. DOI: https://doi.org/10.7916/d8-qdxc-0c73 . Accessed DAY MONTH YEAR

Teegarden's Star is the brightest and one of the nearest ultra-cool dwarfs in the solar neighbourhood. For its late spectral type (M7.0 V), the star shows relatively little activity and is a prime target for near-infrared radial velocity surveys such as CARMENES. As part of the CARMENES search for exoplanets around M dwarfs, we obtained more than 200 radial-velocity measurements of Teegarden's Star and analysed them for planetary signals. We find periodic variability in the radial velocities of Teegarden's Star. We studied photometric measurements to rule out stellar brightness variations mimicking planetary signals. We find evidence for two planet candidates, each with 1.1M_{Earth}_ minimum mass, orbiting at periods of 4.91d and 11.4d, respectively. No evidence for planetary transits could be found in archival and follow-up photometry. Small photometric variability is suggestive of slow rotation and old age. The two planets are among the lowest-mass planets discovered so far, and they are the first Earth-mass planets around an ultra-cool dwarf for which the masses have been determined using radial velocities.

This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative in Sierra Leone.

GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/

Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2020. GRID3 Sierra Leone Settlement Extents Version 01, Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. DOI: https://doi.org/10.7916/d8-p5mw-9282. Accessed DAY MONTH YEAR

This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative in Chad.

GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/

Suggested Data Set Citation:

Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2020. GRID3 Chad Settlement Extents Version 01, Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. DOI: https://doi.org/10.7916/d8-7gwt-nc47. Accessed DAY MONTH YEAR

This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative in The Gambia.

GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/

Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2020. GRID3 The Gambia Settlement Extents Version 01, Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. DOI: https://doi.org/10.7916/d8-7wzh-5792. Accessed DAY MONTH YEAR

TWINS, Two Wide-angle Imaging Neutral-atom Spectrometers, is a Mission of Opportunity under NASA's Small Explorer, SMEX, Program. TWINS-1 and TWINS-2 are the Designations for NASA-Sponsored Instruments flying on Unspecified Non-NASA U.S. Government Spacecraft. The TWINS-1 Instrument High Voltages were turned on in April 2007 and the TWINS-2 High Voltages were turned in May 2008; the Exact Launch Dates are not available. The Data, including both Science Data and Spacecraft Ephemeris and Attitude Information, from the two NASA-Funded Science Instruments are publicly available to the Scientific Research Community. See https://earth.esa.int/web/eoportal/satellite-missions/t/twins/ TWINS is a Stereo Mission whose overall Scientific Objective is to establish the Global Connectivities and Causal Relationships between Processes in Different Regions of the Earth's Magnetosphere. To meet this Goal, TWINS-1 and TWINS-2 provide Stereoscopic Neutral Atom Imaging of the Magnetosphere from Two Widely Spaced, High-Altitude, High-Inclination Spacecraft. TWINS Instrumentation includes an Energetic Neutral Atom, ENA, Imager to capture Charge-Exchange-Produced Neutral Atoms over a Broad Energy Range, approximately from 1 keV ro 100 keV, and a Lyman-alpha Detector to measure the Density of the Neutral Hydrogen Geocorona needed for Extraction of Magnetospheric Ion Fluxes from Neutral Atom Data. The TWINS-1 and TWINS-2 Instruments are identical. Each Spacecraft carrying TWINS Instruments is in a Molniya Orbit, 63.4°, 7.2 Re Apogee, 1000 km Perigee and Period 12 hr. The TWINS Spacecraft are 3-Axis stabilized and with Nadir-Pointing. Each acquires Image Data with Time Resolution of 60 s. The Time required to change Actuator Direction between Scans, an Interval with no Data Collection, was 25 s from June 2008 to July 2009, and 12 s at all other Times. This gives an Effective Cadence of 72 or 85 s. The Nominal Design Lifetime for each Instrument is four Years. TWINS operates only during the Apogee Portion of each Orbit, when the Spacecraft is above the Radiation Belts. The TWINS Lyman-alpha Detector consists of two independent Sensors to measure Lyman-alpha Radiation being emitted by Neutral Hydrogen Atoms. The Sensors oriented at Angles of 40° with respect to the Actuator Spin Axis. Each Sensor has a Full Width, Half Maximum, FWHM, Field-of-View of 4°, defined by Collimation Hole Baffles, uses Lyman-alpha Interference Filters as Narrow Band Transmissions Filters, and applies a KBr or CsI Photodiode for Photon Detection. The Lyman-alpha Detector is located on the rotating Actuator Platform to provide Full 360° Azimuthal Angle Coverage Time resolution is 60 s.

This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative in Equatorial Guinea.

GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/

Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2020. GRID3 Equatorial Guinea Settlement Extents Version 01, Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. DOI: https://doi.org/10.7916/d8-s7ze-ya13. Accessed DAY MONTH YEAR

This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative in Mozambique.

GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/

Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2020. GRID3 Mozambique Settlement Extents Version 01, Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. DOI: https://doi.org/10.7916/d8-v3zn-yf15. Accessed DAY MONTH YEAR

This dataset comprises global upper thermospheric cross-track neutral wind measurements obtained from accelerometer data of the CHAMP satellite during its almost ten year’s lifetime from 2001 to 2009. One key scientific instrument on-board CHAMP was a sensitive triaxial accelerometer. It was located at the spacecraft's centre of mass and sampled effectively accelerations due to non-gravitational forces with an accuracy of ~3×10^-9 ms^-2 (Doornbos et al., 2010). The along-track air drag measurements resulted in thermospheric mass density estimations, while the instrument was sensitive enough to deduce also the horizontal neutral wind component from the cross-track accelerations. The CHAllenging Minisatellite Payload (CHAMP) spacecraft circled the Earth from July 2000 to September 2010 on a near-polar orbit (inclination 87.3°). Each orbit period took about 93 minutes at an altitude of initially 455 km, and decaying to about 320 km in 2009. Due to CHAMP's precession, the satellite achieved full coverage of all local times within about 131 days in each case. This work was part of a study in 2007-2009 (Doornbos et al., 2009) funded by the European Space Agency’s General Studies Program which aimed at a more precise estimation of the non-gravitational forces, considering the precise satellite geometry and its optical and mechanical surface properties. To obtain the actual air drag forces, the modelled accelerations due to radiation pressure forces from the sun, the Earth's albedo, and the Earth's infrared radiation had to be computed and removed from the calibrated and edited accelerometer data to get the observed aerodynamic acceleration vector. The modelling of the radiation pressure forces comprised several nontrivial components like the modelling of eclipse and semi-shadow conditions for solar radiation pressure, values for the reflectivity and infrared emissivity of Earth surface elements, and models of the geometry and optical properties of the satellite surfaces (Doornbos et al., 2010). The detailed description of supersonic flow of the neutral gas particles across the satellite's surface and its reflection requires a model of the gas–surface interaction, which specifies the angular distribution and energy flux of the reflected particles. One has to make assumptions and educated guesses, because information on the gas–surface interaction, as well as in situ observations of aerodynamic model parameters like air temperature and neutral gas species' concentrations should be measured by independent instruments on the accelerometer-carrying satellite. Here, we relied on the empirical atmosphere model NRLMSISE-00 (Picone et al., 2002) and the rarefied aerodynamic equations for flat panels, derived by Sentman (1961). These equations take into account the random thermal motion of the incident particles and assume a completely diffuse distribution of the reflected particle flux. The energy flux accommodation coefficient alpha (Moe et al., 2004), which determines whether the particles retain their mean kinetic energy (alpha = 0) or acquire the temperature of the spacecraft surface wall (alpha = 1), was found to be optimally chosen with alpha = 0.8 for this data set. This thermospheric cross-track neutral wind data set consists of a series of annual CDF data files for both CHAMP wind measurements (subfolder: CH_PN_R03_denswind_iter2_Sentman_alpha08) and CHAMP orbital data (subfolder: CH_orbit_GEO_RSO). The CDF data files are documented in the header. The complete dataset contains more than 25 million data points with a temporal cadence of 10 sec. In addition to the data, we are providing supplementary Figures to Aruliah et al. (2019, subfolder: 2019-001_Foerster-Doornbos_Figures). They are complementary, in particular, to Figs. 1-4 of this paper, but additionally show the original data as “cloud” of data points in the background of the statistical averages. Each figure plot (png-format) has an accompanying txt-file of the same name (except the extension) with ASCII tables of the hourly statistical averages and their standard deviations. The data were used in various previous publications mainly with respect to high-latitude upper thermosphere studies (Förster et al., 2008, 2011) and investigations of the interhemispheric coupling processes of the magnetosphere, ionosphere, and thermosphere (Förster et al., 2017). Actually, this data publication serves as supplement to Aruliah et al. (2019).

This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative in Somalia.

GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/

Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2020. GRID3 Somalia Settlement Extents Version 01, Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. DOI: https://doi.org/10.7916/d8-4n5t-wd59. Accessed DAY MONTH YEAR

We detect Ly{alpha} absorption from the escaping atmosphere of HD63433c, a R=2.67R{Earth}, P=20.5day mini-Neptune orbiting a young (440Myr) solar analog in the Ursa Major Moving Group. Using Hubble Space Telescope (HST)/Space Telescope Imaging Spectrograph, we measure a transit depth of 11.1{+/-}1.5% in the blue wing and 8{+/-}3% in the red. This signal is unlikely to be due to stellar variability, but should be confirmed by an upcoming second transit observation with HST. We do not detect Ly{alpha} absorption from the inner planet, a smaller R=2.15R{Earth} mini-Neptune on a 7.1day orbit. We use Keck/NIRSPEC to place an upper limit of 0.5% on helium absorption for both planets. We measure the host star's X-ray spectrum and mid-ultraviolet flux with XMM-Newton, and model the outflow from both planets using a 3D hydrodynamic code. This model provides a reasonable match to the light curve in the blue wing of the Ly{alpha} line and the helium nondetection for planet c, although it does not explain the tentative red wing absorption or reproduce the excess absorption spectrum in detail. Its predictions of strong Ly{alpha} and helium absorption from b are ruled out by the observations. This model predicts a much shorter mass-loss timescale for planet b, suggesting that b and c are fundamentally different: while the latter still retains its hydrogen/helium envelope, the former has likely lost its primordial atmosphere.