AndreaBozzo/ceres-open-data-index huggingface dataset:
Global Gridded Surfaces of Selected Soil Characteristics (IGBP-DIS)

The Global Gridded Surfaces of Selected Soil Characteristics (IGBP-DIS) data set contains 7 data surfaces: soil-carbon density, total nitrogen density, field capacity, wilting point, profile available water capacity, thermal capacity, and bulk density. All the surfaces are global, at a resolution of 5x5 arc-minutes, in ASCIIGRID format for ARC INFO. Each file contains a single ASCII array in a geographic (lat/long) projection. The ascii files consist of header information containing a set of keywords, followed by cell values in row-major order. These data surfaces were generated by the SoilData System, which was developed by the Global Soil Data Task of the International Geosphere-Biosphere Programme (IGBP) Data and Information Services (DIS). The SoilData System generates soil information and maps for geographic regions at soil depths and resolutions selected by the user. Derived surfaces of selected soil characteristics are suitable for modeling and inventory purposes. The data surfaces are also distributed as part of the Global Soil Data Products CD-ROM. The SoilData System uses a statistical bootstrapping approach to link the pedon records in the Global Pedon Database to the FAO/UNESCO Digital Soil Map of the World. It can generate maps and output data sets for a range of original and derived soil parameters, such as carbon and nitrogen density, thermal conductivity, and water-holding capacity, for any part of the world at user-selected depth ranges. The digital output can be at any resolution (in increments of 5').

Tags: earth-science-soils-land-surface-carbon, earth-science-soils-land-surface-nitrogen, earth-science-soils-land-surface-soil-bulk-density, earth-science-soils-land-surface-soil-chemistry, earth-science-soils-land-surface-soil-classification, earth-science-soils-land-surface-soil-horizons-profile, earth-science-soils-land-surface-soil-moisture-water-content, earth-science-soils-land-surface-soil-water-holding-capacity
Organization: National Aeronautics and Space Administration
Global Hyperspectral Imaging Spectral-library of Agricultural crops for Central Asia V001

The Global Hyperspectral Imaging Spectral-library of Agricultural crops (GHISA) is a comprehensive compilation, collation, harmonization, and standardization of hyperspectral signatures of agricultural crops of the world. This hyperspectral library of agricultural crops is developed for all major world crops and was collected by United States Geological Survey (USGS) and partnering volunteer agencies from around the world. Crops include wheat, rice, barley, corn, soybeans, cotton, sugarcane, potatoes, chickpeas, lentils, and pigeon peas, which together occupy about 65% of all global cropland areas. The GHISA spectral libraries were collected and collated using spaceborne, airborne (e.g., aircrafts and drones), and ground based hyperspectral imaging spectroscopy. The GHISA for Central Asia (GHISACASIA) Version 1 product provides dominant crop data (wheat, rice, corn, alfalfa, and cotton) in different growth stages across the Galaba and Kuva farm fields in the Syr Darya river basin in Central Asia. The GHISA hyperspectral library for the two irrigated areas was developed using Earth Observing-1 (EO-1) Hyperion hyperspectral data acquired in 2007 and ASD (Analytical Spectral Devices, Inc.) Spectroradiometer data acquired in 2006 and 2007. GHISACASIA is extracted from three Hyperion hyperspectral images and several thousands of field ASD Spectroradiometer data. Measurements were taken from 1,232 randomly chosen points scattered across the two farm sites throughout the growing season. All the processing algorithms are coded in Statistical Analysis System (SAS) format and available for download. Provided in the .xlsx files are the spectral library including image information, plot IDs, study area, instrument, Julian or acquisition date, and crop type labels for Central Asia sample fields.

Tags: earth-science-agricultural-plant-science-agriculture
Organization: National Aeronautics and Space Administration
Global Inventory of Methane Emissions from Fuel Exploitation V1 (GFEI_CH4)

This is a global inventory of methane emissions from fuel exploitation (GFEI) created for the NASA Carbon Monitoring System (CMS). The emission sources represented in this dataset include fugitive emission sources from oil, gas, and coal exploitation following IPCC 2006 definitions and are estimated using bottom-up methods. The inventory emissions are based on individual country reports submitted in accordance with the United Nations Framework Convention on Climate Change (UNFCCC). For those countries that do not report, the emissions are estimated following IPCC 2006 methods. Emissions are allocated to infrastructure locations including mines, wells, pipelines, compressor stations, storage facilities, processing plants, and refineries. The purpose of the inventory is to be used as a prior estimate of fuel exploitation emissions in inverse modeling of atmospheric methane observations. GFEI only includes fugitive methane emissions from oil, gas, and coal exploitation activities and does not include any combustion emissions as defined in IPCC 2006 category 1A. The CMS program is designed to make significant contributions in characterizing, quantifying, understanding, and predicting the evolution of global carbon sources and sinks through improved monitoring of carbon stocks and fluxes. The System uses NASA observations and modeling/analysis capabilities to establish the accuracy, quantitative uncertainties, and utility of products for supporting national and international policy, regulatory, and management activities. CMS data products are designed to inform near-term policy development and planning.

Tags: earth-science-atmospheric-chemistry-atmosphere-carbon-and-hydrocarbon-compounds-methane
Organization: National Aeronautics and Space Administration
Global Landslide Nowcast from LHASA L4 1 day 1 km x 1 km version 1.1 (Global_Landslide_Nowcast) at GES DISC

The Landslide Hazard Assessment for Situational Awareness (LHASA) model identifies locations with high potential for landslide occurrence at a daily temporal resolution. LHASA combines satellite‐based precipitation estimates with a landslide susceptibility map derived from information on slope, geology, road networks, fault zones, and forest loss. When rainfall is considered to be extreme and susceptibility values are moderate to very high, a “nowcast” is issued to indicate the times and places where landslides are more probable. Although the model could be run every half hour, this archive contains a daily record derived from a retrospective model run and spatial coverage is from 60°N to 60°S .

Tags: earth-science-natural-hazards-human-dimensions-landslides
Organization: National Aeronautics and Space Administration
Global Hyperspectral Imaging Spectral-library of Agricultural crops for Conterminous United States V001

The Global Hyperspectral Imaging Spectral-library of Agricultural crops (GHISA) is a comprehensive compilation, collation, harmonization, and standardization of hyperspectral signatures of agricultural crops of the world. This hyperspectral library of agricultural crops is developed for all major world crops and was collected by United States Geological Survey (USGS) and partnering volunteer agencies from around the world. Crops include wheat, rice, barley, corn, soybeans, cotton, sugarcane, potatoes, chickpeas, lentils, and pigeon peas, which together occupy about 65% of all global cropland areas. The GHISA spectral libraries were collected and collated using spaceborne, airborne (e.g., aircraft and drones), and ground based hyperspectral imaging spectroscopy. The GHISA for the Conterminous United States (GHISACONUS) Version 1 product provides dominant crop data in different growth stages for various agroecological zones (AEZs) of the United States. The GHISA hyperspectral library of the five major agricultural crops (e.g., winter wheat, rice, corn, soybeans, and cotton) for CONUS was developed using Earth Observing-1 (EO-1) Hyperion hyperspectral data acquired from 2008 through 2015 from different AEZs of CONUS using the United States Department of Agriculture (USDA) Cropland Data Layer ([CDL](https://nassgeodata.gmu.edu/CropScape/)) as reference data. GHISACONUS is comprised of seven AEZs throughout the United States covering the major agricultural crops in six different growth stages: emergence/very early vegetative (Emerge VEarly), early and mid vegetative (Early Mid), late vegetative (Late), critical, maturing/senescence (Mature Senesc), and harvest. The crop growth stage data were derived using crop calendars generated by the Center for Sustainability and the Global Environment ([SAGE](https://nelson.wisc.edu/sage/)), University of Wisconsin-Madison. Provided in the CSV file is the spectral library including image information, geographic coordinates, corresponding agroecological zone, crop type labels, and crop growth stage labels for the United States.

Tags: earth-science-agricultural-plant-science-agriculture
Organization: National Aeronautics and Space Administration
Global Landslide Nowcast from LHASA L4 1 day 1 km x 1 km version 2.0.0 (Global_Landslide_Nowcast) at GES DISC

The Global Landslide Nowcast addresses the need for real-time situational awareness of landslide hazard. The Landslide Hazard Assessment for Situational Awareness model (LHASA) combines satellite rainfall estimates from the Global Precipitation Measurement mission (GPM) with soil moisture estimates from the Soil Moisture Active Passive (SMAP) satellite and other factors to produce a map of locations where rainfall-triggered landslide activity is probable. Due to the latency of the rainfall data, the nowcast is a near-real time product with a minimum latency of 5 hours. Although the model could be run every half hour, this archive contains a daily record derived from a retrospective model run. The Global Landslide Nowcast version 2.0.0 retains replaces the heuristic decision tree from version 1.0 with a machine learning model. Instead of merging all factors other than precipitation into a susceptibility map, LHASA 2.0 takes in each variable as a separate input layer. The most important change is the replacement of the categorical nowcast with a probabilistic output. This will enable users to adjust the threshold to suit their specific application and geographic location.

Tags: earth-science-natural-hazards-human-dimensions-landslides
Organization: National Aeronautics and Space Administration
Global Mangrove Distribution, Aboveground Biomass, and Canopy Height

This dataset characterizes the global distribution, biomass, and canopy height of mangrove-forested wetlands based on remotely sensed and in situ field measurement data. Estimates of (1) mangrove aboveground biomass (AGB), (2) maximum canopy height (height of the tallest tree), and (3) basal-area weighted height (individual tree heights weighted in proportion to their basal area) for the nominal year 2000 were derived across a 30-meter resolution global mangrove ecotype extent map using remotely-sensed canopy height measurements and region-specific allometric models. Also provided are (4) in situ field measurement data for selected sites across a wide variety of forest structures (e.g., scrub, fringe, riverine and basin) in mangrove ecotypes of the global equatorial region. Within designated plots, selected trees were identified to species and diameter at breast height (DBH) and tree height was measured using a laser rangefinder or clinometer. Tree density (the number of stems) can be estimated for each plot and expressed per unit area. These data were used to derive plot-level allometry among AGB, basal area weighted height (Hba), and maximum canopy height (Hmax) and to validate the remotely sensed estimates.

Tags: earth-science-ecosystems-biosphere-aquatic-ecosystems-wetlands, earth-science-ecosystems-biosphere-marine-ecosystems-coastal, earth-science-vegetation-biosphere-biomass, earth-science-vegetation-biosphere-canopy-characteristics
Organization: National Aeronautics and Space Administration
Global Monthly Mean Leaf Area Index Climatology, 1981-2015

This dataset provides a global 0.25 degree x 0.25 degree gridded monthly mean leaf area index (LAI) climatology as averaged over the period from August 1981 to August 2015. The data were derived from the Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) LAI3g version 2, a bi-weekly data product from 1981 to 2015 (GIMMS-LAI3g version 2). The LAI3g version 2 (raw) data were first regridded from 1/12 x 1/12 degree to 0.25 x 0.25 degree resolution, then processed to remove missing and unreasonable values, scaled to obtain LAI values, and the bi-weekly LAI values were averaged for every month. Finally, the monthly long-term mean LAI (1981-2015) was calculated.

Tags: earth-science-vegetation-biosphere-leaf-characteristics-leaf-area-index-lai, earth-science-vegetation-biosphere-vegetation-index-normalized-difference-vegetation-index-ndvi
Organization: National Aeronautics and Space Administration
High Resolution Global Contiguous SIF Estimates from OCO-2 SIF and MODIS, Version 2

This dataset provides spatially-contiguous global mean daily solar-induced chlorophyll fluorescence (SIF) estimates at 0.05 degree (approximately 5 km at the equator) spatial and 16-day temporal resolution from September 2014 through July 2020. This product was derived from Orbiting Carbon Observatory-2 (OCO-2) SIF observations and produced by training an artificial neural network (ANN) on the native OCO-2 SIF observations and MODIS BRDF-corrected seven-band surface reflectance along OCO-2's orbits. The trained ANN model was then applied to predict mean daily SIF (mW/m2/nm/sr) in OCO-2's gap regions based on MODIS reflectance and landcover. This framework was stratified by biomes and 16-day time steps. This dataset's high resolution and global contiguous coverage will greatly enhance the synergy between satellite SIF and photosynthesis measured on the ground at consistent spatial scales. Potential applications of this dataset include advancing dynamic drought monitoring and mitigation, informing agricultural planning and yield estimation, and providing a benchmark for upcoming satellite missions with SIF capabilities at higher spatial resolutions.

Tags: earth-science-ecological-dynamics-biosphere-ecosystem-functions-primary-production, earth-science-vegetation-biosphere-chlorophyll, earth-science-vegetation-biosphere-leaf-characteristics, earth-science-vegetation-biosphere-solar-induced-fluorescence
Organization: National Aeronautics and Space Administration
Global Leaf Area Index from Field Measurements, 1932-2000

Approximately 1000 published estimates of leaf area index (LAI) from nearly 400 unique field sites, covering the period 1932-2000, have been compiled into a single data set. LAI is a key parameter for global and regional models of biosphere/atmosphere exchange of carbon dioxide, water vapor, etc. This data set provides a benchmark of typical values and ranges of LAI for a variety of biomes and land cover types, in support of model development and validation of satellite-derived remote sensing estimates of LAI and other vegetation parameters. The LAI data are linked to a bibliography of over 300 original-source references. These historical LAI data are mostly from natural and semi-natural (managed) ecosystems, although some agricultural estimates are also included. Caution is advised in using these data; they were collected using a wide range of methodologies and assumptions and may not be comparable among sites. Some attempts have been made to detect and flag the outliers in this data set, according to different biome/land cover classes. Needleleaf (coniferous) forests are by far the most commonly measured biome/land cover types in this compilation, with 22% of the measurements from temperate evergreen needleleaf forests, and boreal evergreen needleleaf forests and crops the next most common (about 9% each). About 40% of the records in the data set were published in the past 10 years (1991-2000), with a further 20% collected between 1981 and 1990. Mean LAI (+/- standard deviation), distributed between 15 biome/land cover classes, ranged from 1.31 +/- 0.85 for deserts to 8.72 +/- 4.32 for tree plantations, with evergreen forests (needleleaf and broadleaf) displaying the highest LAI among the natural vegetation classes. Further information on this data set is available from the link below: Leaf Area Index Data Citation: Cite this data set as follows: Scurlock, J. M. O., G. P. Asner, and S. T. Gower. 2001. Global Leaf Area Index from Field Measurements, 1932-2000. Available on-line [http://www.daac.ornl.gov] from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A.

Tags: earth-science-vegetation-biosphere-canopy-characteristics, earth-science-vegetation-biosphere-leaf-characteristics-leaf-area-index-lai
Organization: National Aeronautics and Space Administration
Global Monthly Climatology for the Twentieth Century (New et al.)

This is a data set of mean monthly surface climate data over global land areas, excluding Antarctica, for nearly all of the twentieth century. The data set is gridded at 0.5 degree latitude/longitude resolution and includes seven variables: precipitation, mean temperature, diurnal temperature range, wet-day frequency, vapour pressure, cloud cover, and ground-frost frequency. All variables have mean monthly values for the period 1901-1995, several have data as recent as 1998, and more data will be added by the data originators. In constructing the monthly grids the authors used an anomaly approach which attempts to maximize station data in space and time (New et al., 2000). In this technique, grids of monthly historic anomalies are derived relative to a standard normal period. Station measurement data for the years 1961-1990, extracted from the monthly data holdings of the Climatic Research Unit and the Global Historic Climatology Network (GHCN), served as the normal period (New et al., 1999). The anomaly grids were then combined with high-resolution mean monthly climatology to arrive at fields of estimated historical monthly surface climate. Data users are encouraged to see the companion file New et al. (2000) for a complete description of this technique and potential applications and limitations of the data set. For additional information, refer to the IPCC Data Distribution Centre. Access to the complete year-by-year monthly data set or to data more recent than posted here can be achieved by making a request with the Climate Impacts LINK Project at the Climatic Research Unit (email: d.viner@uea.ac.uk, web site: www.cru.uea.ac.uk/link ).

Tags: earth-science-atmospheric-temperature-atmosphere-surface-temperature-air-temperature, earth-science-atmospheric-temperature-atmosphere-surface-temperature-maximum-minimum-temperatur, earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators-water-vapor, earth-science-clouds-atmosphere-cloud-properties-cloud-frequency, earth-science-precipitation-atmosphere-precipitation-amount, earth-science-weather-events-atmosphere-freeze-frost
Organization: National Aeronautics and Space Administration
Global Mean Sea Level Trend from Integrated Multi-Mission Ocean Altimeters TOPEX/Poseidon, Jason-1, OSTM/Jason-2, Jason-3, and Sentinel-6 Version 5.2

This dataset contains the Global Mean Sea Level (GMSL) trend generated from the Integrated Multi-Mission Ocean Altimeter Data for Climate Research Version 5.2. The GMSL trend is a 1-dimensional time series of globally averaged Sea Surface Height Anomalies (SSHA) from TOPEX/Poseidon, Jason-1, OSTM/Jason-2, Jason-3, and Sentinel-6A that covers September 1992 to present with a lag of up to 4 months. The data are reported as variations relative to a 20-year TOPEX/Jason collinear mean. Bias adjustments and cross-calibrations were applied to ensure SSHA data are consistent across the missions; Glacial Isostatic Adjustment (GIA) was also applied. The data are available as a table in ASCII format. Changes between the version 5.1 and version 5.2 releases are described in detail in the user handbook.

Tags: earth-science-sea-surface-topography-oceans-sea-surface-height
Organization: National Aeronautics and Space Administration
Global Navigation Satellite System (GNSS) Final Ionosphere Products from NASA CDDIS

Satellite and receiver clock products derived from analysis of Global Navigation Satellite System (GNSS) data. These products are the generated by analysis centers in support of the International GNSS Service (IGS) and combined by the IGS analysis coordinator to form the official IGS real-time clock product (daily). This product is used for comparison purposes.

Tags: earth-science-geodetics-solid-earth
Organization: National Aeronautics and Space Administration
Global Navigation Satellite System (GNSS) Final Clocks Products from NASA CDDIS

Satellite and receiver clock products derived from analysis of Global Navigation Satellite System (GNSS) data. These products are the generated by analysis centers in support of the International GNSS Service (IGS) and combined by the IGS analysis coordinator to form the official IGS final clock product (weekly).

Tags: earth-science-geodetics-solid-earth, earth-science-geodetics-solid-earth-techniques-gnss-global-navigation-satellite-systems, earth-science-not-provided-not-provided
Organization: National Aeronautics and Space Administration
Global Navigation Satellite System (GNSS) High-rate (1-second sampling, sub-hourly files) Observation Data from NASA CDDIS

Global Navigation Satellite System (GNSS) data consists of the U.S. Global Positioning System (GPS) and the Russian GLObal NAvigation Satellite System (GLONASS) (plus other international systems) data sets. The Global Positioning System, developed by the U.S. Department of Defense, has been fully operational since 1994. GPS consists of a constellation of 24 satellites and three active spares each traveling in a 12 hour circular orbit, 20,200 kilometers above the Earth. The satellites are positioned so that six are observable nearly 100 percent of the time from any point on the Earth. The GLObal NAvigation Satellite System (GLONASS), managed and deployed by the Russian Federation, is similar to the U. S. Global Positioning System (GPS) in terms of the satellite constellation, orbits, and signal structure. GNSS receivers detect, decode, and process signals from the GNSS satellites. The satellites transmit the ranging codes on two radio-frequency carriers, allowing the locations of GNSS r

Tags: earth-science-atmospheric-pressure-atmosphere-gravity-wave, earth-science-geodetics-solid-earth, earth-science-geodetics-solid-earth-coordinate-reference-system, earth-science-geodetics-solid-earth-coordinate-reference-system-country-regional-coordinate-ref, earth-science-geodetics-solid-earth-ellipsoid-characteristics, earth-science-geodetics-solid-earth-geoid-characteristics, earth-science-geodetics-solid-earth-techniques-gnss-global-navigation-satellite-systems, earth-science-gravity-gravitational-field-solid-earth-control-surveys, earth-science-gravity-gravitational-field-solid-earth-polar-motion-annual-elliptical-component, earth-science-gravity-gravitational-field-solid-earth-polar-motion-chandler-circular-component, earth-science-gravity-gravitational-field-solid-earth-satellite-orbits-revolution-orbital-posit
Organization: National Aeronautics and Space Administration