AndreaBozzo/ceres-open-data-index huggingface dataset:
Disturbance History and Forest Biomass from Landsat for Six US Sites, 1985-2014

This dataset provides derived disturbance history and predicted annual forest biomass maps at 30-m resolution for six selected Landsat scenes across the Conterminous United States (CONUS) for the period 1985-2014. The focus sites are in the following states: Colorado, Maine, Minnesota, Oregon, Pennsylvania, and South Carolina. These scenes were selected to represent a wide range of forest ecosystems, which ensured that a diversity of forest type groups and forest change processes (e.g., harvest, fire, insects, and urbanization) were included. Disturbance history was derived from a Landsat time-series for each site. Each disturbance is represented by year of detection, duration, and magnitude. The cause of the disturbance was not identified. Forest biomass was measured at field plots within each of the six sites and combined with airborne LiDAR data from each site to create land validation maps. Site biomass at 30-m resolution was estimated by developing Random Forest models that include site disturbance history with the land validation maps.

Tags: earth-science-ecosystems-biosphere-terrestrial-ecosystems-forests, earth-science-land-use-land-cover-land-surface, earth-science-lidar-spectral-engineering, earth-science-vegetation-biosphere-biomass, earth-science-vegetation-biosphere-carbon
Organization: National Aeronautics and Space Administration
Digital Elevation Models for the Global Change Research Wetland, Maryland, USA, 2016

This dataset contains four alternative digital elevation models (DEMs) at 1 m resolution and model performance statistical metrics for the Global Change Research Wetland (GCReW) site on the Rhode River, a tributary of the Chesapeake Bay in Maryland, USA, for the year 2016. Three DEMs were created by using different strategies for correcting positive biases in Light Detection and Ranging (LiDAR)-based DEMs that are common in tidal wetlands. These included (1) applying a single average offset based on a literature review, (2) using the LiDAR Elevation Correction with NDVI (LEAN)-method, and (3) applying plant community-specific offsets using a local vegetation cover map. Existing LiDAR data at 1 m resolution collected in 2011 was the basis for these DEMs. The fourth DEM was created by using Empirical Bayesian Kriging to extrapolate between measured ground points. The elevation is provided in meters relative to the North American Vertical Datum of 1988 (NAVD 88). To calibrate the four approaches, the elevation of the entire marsh complex was surveyed at 20 m x 20 m resolution to document the distribution of elevation relative to tidal datums from a single year. Two Trimble R8 real-time kinematic (RTK) GPS receivers were used to survey 525 points over the complex from July 26, 2016, to August 15, 2016. Relative plant cover was also documented. Tidal datums were calculated from the nearby Annapolis, MD tidal gauge located 13 km from GCReW.

Tags: earth-science-coastal-processes-oceans-marshes, earth-science-coastal-processes-oceans-tidal-height, earth-science-topography-land-surface-terrain-elevation-digital-elevation-terrain-model-dem, earth-science-vegetation-biosphere-vegetation-cover
Organization: National Aeronautics and Space Administration
CSR TELLUS GRACE-FO Level-3 Monthly Ocean Bottom Pressure Anomaly Release 6.3 version 04

This data set is produced by the Center for Space Research (CSR) GRACE-FO (Gravity Recovery and Climate Experiment Follow-On) program and derives the ocean bottom pressure (OBP) anomaly given as equivalent water thickness. These monthly grids are derived from GRACE-FO time-variable gravity observations during the specified timespan, and relative to the specified time-mean reference period. This quantity represents sea floor pressure changes due to the integral effect of ocean and atmosphere processes, including global mean ocean bottom pressure changes (mean ocean mass and mean atmosphere mass over the global oceans). A glacial isostatic adjustment (GIA) correction has been applied, and standard corrections for geocenter (degree-1), C20 (degree-20) and C30 (degree-30) are incorporated. Post-processing filters have been applied to reduce correlated errors. Data grids are provided in ASCII/netCDF/GeoTIFF formats. <br><br> GRACE-FO was launched on 22 May 2018, and extends the original GRACE mission (2002 – 2017) and expands its legacy of scientific achievements in tracking earth surface mass changes. Version 04 (v04) of the ocean bottom pressure data uses updated and consistent C20 and Geocenter corrections (i.e., Technical Notes TN-14 and TN-13), as well as an ellipsoidal correction to account for the non-spherical shape of the Earth when mapping gravity anomalies to surface mass change. Additionally, this release 06.3 is an updated version of the Level 3 products in coordination with the release of the analogous Level 2 products used to generate them. It differs from RL06.1 only in the Level-1B accelerometer transplant data that is used for the GF2 (GRACE-FO 2) satellite; see respective L-2 data descriptions. RL06.3 uses the ACX2-L1B data products. All GRACE-FO RL06.3 Level-3 fields are fully compatible with the GRACE RL06 data.

Tags: earth-science-ocean-pressure-oceans-water-pressure-ocean-bottom-pressure
Organization: National Aeronautics and Space Administration
DISCOVER-AQ California Deployment B-200 Aircraft In Situ Meteorological and Navigational Data

DISCOVERAQ_California_MetNav_AircraftInSitu_B200_Data contains in situ meteorological and navigational data collected onboard NASA's B-200 aircraft during the California (San Joaquin Valley) deployment of NASA's DISCOVER-AQ field study. This product contains the B-200 navigational data collected via the APPLANIX. This data product contains data for only the California deployment and data collection is complete. Understanding the factors that contribute to near surface pollution is difficult using only satellite-based observations. The incorporation of surface-level measurements from aircraft and ground-based platforms provides the crucial information necessary to validate and expand upon the use of satellites in understanding near surface pollution. Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) was a four-year campaign conducted in collaboration between NASA Langley Research Center, NASA Goddard Space Flight Center, NASA Ames Research Center, and multiple universities to improve the use of satellites to monitor air quality for public health and environmental benefit. Through targeted airborne and ground-based observations, DISCOVER-AQ enabled more effective use of current and future satellites to diagnose ground level conditions influencing air quality. DISCOVER-AQ employed two NASA aircraft, the P-3B and King Air, with the P-3B completing in-situ spiral profiling of the atmosphere (aerosol properties, meteorological variables, and trace gas species). The King Air conducted both passive and active remote sensing of the atmospheric column extending below the aircraft to the surface. Data from an existing network of surface air quality monitors, AERONET sun photometers, Pandora UV/vis spectrometers and model simulations were also collected. Further, DISCOVER-AQ employed many surface monitoring sites, with measurements being made on the ground, in conjunction with the aircraft. The B200 and P-3B conducted flights in Baltimore-Washington, D.C. in 2011, Houston, TX in 2013, San Joaquin Valley, CA in 2013, and Denver, CO in 2014. These regions were targeted due to being in violation of the National Ambient Air Quality Standards (NAAQS).

Tags: earth-science-altitude-atmosphere
Organization: National Aeronautics and Space Administration
DISCOVER-AQ California Deployment Oildale Ground Site Data

DISCOVERAQ_California_Ground_Oildale_Data contains data collected at the Oildale ground site during the California (San Joaquin Valley) deployment of NASA's DISCOVER-AQ field study. This data product contains data for only the California deployment and data collection is complete. Understanding the factors that contribute to near surface pollution is difficult using only satellite-based observations. The incorporation of surface-level measurements from aircraft and ground-based platforms provides the crucial information necessary to validate and expand upon the use of satellites in understanding near surface pollution. Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) was a four-year campaign conducted in collaboration between NASA Langley Research Center, NASA Goddard Space Flight Center, NASA Ames Research Center, and multiple universities to improve the use of satellites to monitor air quality for public health and environmental benefit. Through targeted airborne and ground-based observations, DISCOVER-AQ enabled more effective use of current and future satellites to diagnose ground level conditions influencing air quality. DISCOVER-AQ employed two NASA aircraft, the P-3B and King Air, with the P-3B completing in-situ spiral profiling of the atmosphere (aerosol properties, meteorological variables, and trace gas species). The King Air conducted both passive and active remote sensing of the atmospheric column extending below the aircraft to the surface. Data from an existing network of surface air quality monitors, AERONET sun photometers, Pandora UV/vis spectrometers and model simulations were also collected. Further, DISCOVER-AQ employed many surface monitoring sites, with measurements being made on the ground, in conjunction with the aircraft. The B200 and P-3B conducted flights in Baltimore-Washington, D.C. in 2011, Houston, TX in 2013, San Joaquin Valley, CA in 2013, and Denver, CO in 2014. These regions were targeted due to being in violation of the National Ambient Air Quality Standards (NAAQS).

Tags: earth-science-atmospheric-chemistry-atmosphere-carbon-and-hydrocarbon-compounds
Organization: National Aeronautics and Space Administration
CMS: Forest Aboveground Biomass from FIA Plots across the Conterminous USA, 2009-2019

This dataset provides forest biomass estimates for the conterminous United States based on data from the USDA Forest Inventory and Analysis (FIA) program. FIA maintains uniformly measured field plots across the conterminous U.S. This dataset, derived from field survey data from 2009-2019, includes statistical estimates of biomass at the finest scale (64,000-hectare hexagons) allowed by FIA's sample density. Estimates include the mean (and standard error of the mean) biomass for both live and dead trees, calculated using three sets of allometric equations. There is also an estimate of the area of forestland in each hexagon. These data can be useful for assessing the accuracy of remotely sensed biomass estimates.

Tags: earth-science-ecosystems-biosphere-terrestrial-ecosystems-forests, earth-science-vegetation-biosphere-biomass, earth-science-vegetation-biosphere-carbon
Organization: National Aeronautics and Space Administration
CYGNSS Level 1 Full Delay Doppler Map Data Record

This Level 1 (L1) dataset contains the Full Delay Doppler Map (DDM) sensor data from the Delay Doppler Mapping Instrument aboard the CYGNSS satellite constellation. The primary CYGNSS instrument, also known as the Delay-Doppler Mapping Instrument (DDMI), measures the incoming radio frequency (RF) streams from three input antenna channels (2 nadir oriented science antennas and one zenith oriented navigation antenna) and processes them in real time into DDMs, which are two-dimensional maps of the signal scattered from the Earth surface as a function of propagation time delay and Doppler frequency shift. DDMs are normally sampled over a restricted range of delay and Doppler values centered on the values at the specular point of reflection. The bit resolution of scattered signal strength is also truncated by a lossy data compression algorithm. Full DDMs are sampled over a wider range of delay and Doppler values and retain their full (lossless) bit resolution. Full DDM data records are typically 10-15 min in duration and are initiated by ground commands to coincide with an overpass by one of the spacecraft of a target area of interest.

Tags: earth-science-radar-spectral-engineering-sensor-counts
Organization: National Aeronautics and Space Administration
CYGNSS Level 1 Raw Intermediate Frequency Data Record

This Level 1 (L1) dataset contains the Raw Intermediate Frequency (IF) sensor data from the Delay Doppler Mapping Instrument aboard the CYGNSS satellite constellation. The primary CYGNSS instrument, also known as the Delay-Doppler Mapping Instrument (DDMI), digitizes the incoming radio frequency (RF) streams from three input antenna channels (2 nadir oriented science antennas and one zenith oriented navigation antenna). The Raw IF data included in this data record are the raw sensor counts, retrieved prior to any digital signal processing, thus providing the highest possible resolution in delay and doppler space allowing for the construction of high resolution Delay Doppler Map (DDM) data. Raw IF data records are 30-90 sec in duration, with 60 sec being typical, and are initiated by ground commands to coincide with an overpass by one of the spacecraft of a target area of interest.

Tags: earth-science-radar-spectral-engineering-sensor-counts
Organization: National Aeronautics and Space Administration
CYGNSS Level 1 Science Data Record Version 3.0

This Level 1 (L1) dataset contains the Version 3.0 geo-located Delay Doppler Maps (DDMs) calibrated into Power Received (Watts) and Bistatic Radar Cross Section (BRCS) expressed in units of m2 from the Delay Doppler Mapping Instrument aboard the CYGNSS satellite constellation. This version supersedes Version 2.1; https://doi.org/10.5067/CYGNS-L1X21 . Other useful scientific and engineering measurement parameters include the DDM of Normalized Bistatic Radar Cross Section (NBRCS), the Delay Doppler Map Average (DDMA) of the NBRCS near the specular reflection point, and the Leading Edge Slope (LES) of the integrated delay waveform. The L1 dataset contains a number of other engineering and science measurement parameters, including sets of quality flags/indicators, error estimates, and bias estimates as well as a variety of orbital, spacecraft/sensor health, timekeeping, and geolocation parameters. At most, 8 netCDF data files (each file corresponding to a unique spacecraft in the CYGNSS constellation) are provided each day; under nominal conditions, there are typically 6-8 spacecraft retrieving data each day, but this can be maximized to 8 spacecraft under special circumstances in which higher than normal retrieval frequency is needed (i.e., during tropical storms and or hurricanes). Latency is approximately 6 days (or better) from the last recorded measurement time. Here is a summary of improvements the calibration and processing changes to the Version 3.0 data: 1) the transmitted GPS signal strength in the direction of the DDM scattering surface is determined in real time from measurements of the direct signal from the GPS satellite to the CYGNSS navigation receiver, allowing for the BRCS calibration to be corrected for variations in GPS transmit power; 2) the NBRCS has been validated using comparisons with a large population of modeled values derived from coincident ocean surface roughness spectra produced by the NOAA WAVEWATCH-3 oceanographic wave model; 3) L1 calibration parameters have been adjusted to produce a best fit to the model population.

Tags: earth-science-radar-spectral-engineering-radar-cross-section-bistatic-radar-cross-section, earth-science-radar-spectral-engineering-radar-reflectivity-zenith-signal-power
Organization: National Aeronautics and Space Administration
CYGNSS Level 1 Calibrated Raw IF Version 1.0

The CYGNSS Level 1 Calibrated Raw IF Version 1.0 dataset is produced by the CYGNSS Science Team of the University of Michigan, and it contains the first release, Version 1.0, of the CYGNSS Calibrated Raw Intermediate Frequency (IF) based L1 Product. CYGNSS was launched on 15 December 2016, it is a NASA Earth System Science Pathfinder Mission that was launched with the purpose of collecting the first frequent space‐based measurements of surface wind speeds in the inner core of tropical cyclones. Originally made up of a constellation of eight micro-satellites, the observatories provide nearly gap-free Earth coverage using an orbital inclination of approximately 35° from the equator, with a mean (i.e., average) revisit time of seven hours and a median revisit time of three hours. <br><br> This product includes several established signal coherence detectors, including the power-ratio P<sub>ratio</sub>, complex zero-Doppler delay waveform and full entropy E<sub>full</sub>, and a novel fast entropy detector E<sub>fast</sub>. Both entropy detectors are provided with two temporal resolutions: 2 ms and 50 ms. Several scattered signal strength products are included: Signal-to-Noise Ratio SNR, reflected power P<sub>g</sub>, reflectivity Γ, and Normalized Bistatic Radar Cross-Section NBRCS. Each of these products is derived using a coherent integration time of T<sub>c </sub>= 1 ms and incoherent integration times of N<sub>inc</sub> = 1000, 500, 250, 100, 50, and 2 ms. Signal strength time series at the shorter (2 and 50 ms) times provides excellent detection of land-water transitions in heterogeneous scenes. Delay Doppler Maps (DDMs) are also generated with high delay (∆τ = 1/16 chip) and Doppler (∆f= 50 Hz) resolution. This suite of coherence detection methods can be used to detect the presence of small inland water bodies.

Tags: earth-science-radar-spectral-engineering-sensor-counts
Organization: National Aeronautics and Space Administration
CYGNSS Level 2 Ocean Surface Heat Flux Climate Data Record Version 1.1

This dataset contains the first release, Version 1.1, of the CYGNSS Level 2 Ocean Surface Heat Flux Climate Data Record (CDR), which provides the time-tagged and geolocated ocean surface heat flux parameters with 25x25 kilometer footprint resolution with 1-2 month latency from the Delay Doppler Mapping Instrument (DDMI) aboard the CYGNSS satellite constellation. The Cyclone Global Navigation Satellite System (CYGNSS) is a NASA Earth System Science Pathfinder Mission designed to collect the first frequent space-based measurements of surface wind speeds in the inner core of tropical cyclones. The Coupled Ocean-Atmosphere Response Experiment (COARE) version 3.5 algorithm combines CYGNSS L2 CDR v1.1 ocean surface wind speed estimates with the auxiliary parameters provided by the NASA Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) to produce latent and sensible heat fluxes and their respective transfer coefficients. More information on how the data is produced and validated can be found in the dataset user guide (see Documentation tab). More information on the CYGNSS mission, spacecraft, instrumentation and related datasets is available here: https://podaac.jpl.nasa.gov/CYGNSS. Additional information on the CYGNSS L2 CDR v1.1 wind speed dataset is available here: https://doi.org/10.5067/CYGNS-L2C11.

Tags: earth-science-ocean-heat-budget-oceans-heat-flux-ocean-surface-latent-and-sensible-heat-fluxes, earth-science-ocean-temperature-oceans-sea-surface-temperature
Organization: National Aeronautics and Space Administration
Data from NASA Langley Airborne Lidar flights.

Data from the 1982 NASA Langley Airborne Lidar flights following the eruption of El Chichon beginning in July 1982 and continuing to January 1984. Data in ASCII format.

Tags: earth-science-aerosols-atmosphere-aerosol-backscatter, earth-science-altitude-atmosphere
Organization: National Aeronautics and Space Administration
CYGNSS Level 2 Climate Data Record Version 1.1

This dataset contains the Version 1.1 CYGNSS Level 2 Climate Data Record which provides the time-tagged and geolocated average wind speed (m/s) and mean square slope (MSS) with 25x25 kilometer resolution from the Delay Doppler Mapping Instrument aboard the CYGNSS satellite constellation. The reported sample locations are determined by the specular points corresponding to the Delay Doppler Maps (DDMs). A subset of DDM data used in the direct processing of the average wind speed and MSS is co-located inside of the Level 2 data files. Only one netCDF data file is produced each day (each file containing data from up to 8 unique CYGNSS spacecraft) with a latency of approximately 1 to 2 months from the last recorded measurement time. The Version 1.1 CDR represents is a collection of reanalysis products derived from the SDR v3.0 Level 1 data (https://doi.org/10.5067/CYGNS-L1X30 ). Calibration accuracy and long term stability are improved relative to SDR v3.0 (https://doi.org/10.5067/CYGNS-L2X30 ) using the same trackwise correction algorithm as was used by CDR v1.0 (https://doi.org/10.5067/CYGNS-L2C10 ), which was derived from SDR v2.1 Level 1 data (https://doi.org/10.5067/CYGNS-L1X21 ). Details of the algorithm are provided in the Trackwise Corrected CDR Algorithm Theoretical Basis Document. CDR Level 2 and 3 products (ocean surface wind speed, mean square slope, and latent and sensible heat flux) are generated from the CDR L1 data using the v3.0 SDR data processing algorithms. These products also exhibit improved calibration accuracy and stability over SDR v3.0. Trackwise correction is applied to the two primary CYGNSS L1 science data products, the normalized bistatic radar cross section (NBRCS) and the leading edge slope of the Doppler-integrated delay waveform (LES). The correction compensates for small errors in the Level 1 calibration, due e.g. to uncertainties in the GPS transmitting antenna gain patterns and the CYGNSS receiving antenna gain patterns. CDR v1.1 does not include a Young Seas with Limited Fetch (YSLF) wind speed product and investigators requiring wind speed measurements in and near the inner core of tropical cyclones should use the SDR v3.0 YSLF wind speed product. A YSLF wind speed product is omitted because the trackwise correction algorithm, which constrains the average value of the L1 data using MERRA-2 reanalysis wind speeds, is inherently biased toward fully developed sea state conditions. The constraint improves wind speed retrieval performance in fully developed seas but produces underestimates in YSLF conditions. It should also be noted that the trackwise correction algorithm cannot be successfully applied to all SDR v3.0 L1 data so there is also some loss of samples that were present in SDR v3.0.

Tags: earth-science-ocean-winds-oceans-surface-winds, earth-science-ocean-winds-oceans-surface-winds-ocean-surface-wind-speed
Organization: National Aeronautics and Space Administration