AndreaBozzo/ceres-open-data-index huggingface dataset:
Predictive soil property map: Rock content (&gt;2mm)

These data were compiled to demonstrate new predictive mapping approaches and provide comprehensive gridded 30-meter resolution soil property maps for the Colorado River Basin above Hoover Dam. Random forest models related environmental raster layers representing soil forming factors with field samples to render predictive maps that interpolate between sample locations. Maps represented soil pH, texture fractions (sand, silt clay, fine sand, very fine sand), rock, electrical conductivity (ec), gypsum, CaCO3, sodium adsorption ratio (sar), available water capacity (awc), bulk density (dbovendry), erodibility (kwfact), and organic matter (om) at 7 depths (0, 5, 15, 30, 60, 100, and 200 cm) as well as depth to restrictive layer (resdept) and surface rock size and cover. Accuracy and error estimated using a 10-fold cross validation indicated a range of model performances with coefficient of variation (R2) for models ranging from 0.20 to 0.76 with mean of 0.52 and a standard deviation of 0.12. Models of pH, om and ec had the best accuracy (R2 &gt; 0.6). Most texture fractions, CaCO3, and SAR models had R2 values from 0.5-0.6. Models of kwfact, dbovendry, resdept, rock models, gypsum and awc had R2 values from 0.4-0.5 excepting near surface models which tended to perform better. Very fine sands and 200 cm estimates for other models generally performed poorly (R2 from 0.2-0.4), and sample size for the 200 cm models was too low for reliable model building.  More than 90% of the soils data used was sampled since 2000, but some older samples are included. Uncertainty estimates were also developed by creating relative prediction intervals, which allow end users to evaluate uncertainty easily.

Tags: accuracy-and-error-estimated, arizona, available-water-capacity, bulk-density, calcium-carbonate, colorado, colorado-river, colorado-river-basin, colorado-river-basin-above-hoover-dam, digital-soil-mapping, electrical-conductivity, environmental-conditions, environmental-raster-layers, erodibility, geoscientificinformation, gypsum, hoover-dam, interpolate, machine-learning, maps-and-atlases, nevada, new-mexico, organic-matter, predicitve-modeling, predictive-mapping, predictive-maps, random-forest-models, random-forests, restrictive-layer, rock, sodium-adsorption-ratio, soil-conductivity, soil-density, soil-forming-factors, soil-ph, soil-properties, soil-property-maps, soil-sciences, soil-texture, soils, surface-rock-cover, surface-rock-size, texture-fractions, uncertainty, usgs-5e90b31282ce172707ed7195, utah, wyoming
Organization: Department of the Interior
Predictive soil property map: Organic matter

These data were compiled to demonstrate new predictive mapping approaches and provide comprehensive gridded 30-meter resolution soil property maps for the Colorado River Basin above Hoover Dam. Random forest models related environmental raster layers representing soil forming factors with field samples to render predictive maps that interpolate between sample locations. Maps represented soil pH, texture fractions (sand, silt clay, fine sand, very fine sand), rock, electrical conductivity (ec), gypsum, CaCO3, sodium adsorption ratio (sar), available water capacity (awc), bulk density (dbovendry), erodibility (kwfact), and organic matter (om) at 7 depths (0, 5, 15, 30, 60, 100, and 200 cm) as well as depth to restrictive layer (resdept) and surface rock size and cover. Accuracy and error estimated using a 10-fold cross validation indicated a range of model performances with coefficient of variation (R2) for models ranging from 0.20 to 0.76 with mean of 0.52 and a standard deviation of 0.12. Models of pH, om and ec had the best accuracy (R2 &gt; 0.6). Most texture fractions, CaCO3, and SAR models had R2 values from 0.5-0.6. Models of kwfact, dbovendry, resdept, rock models, gypsum and awc had R2 values from 0.4-0.5 excepting near surface models which tended to perform better. Very fine sands and 200 cm estimates for other models generally performed poorly (R2 from 0.2-0.4), and sample size for the 200 cm models was too low for reliable model building.  More than 90% of the soils data used was sampled since 2000, but some older samples are included. Uncertainty estimates were also developed by creating relative prediction intervals, which allow end users to evaluate uncertainty easily.

Tags: accuracy-and-error-estimated, arizona, available-water-capacity, bulk-density, calcium-carbonate, colorado, colorado-river, colorado-river-basin, colorado-river-basin-above-hoover-dam, digital-soil-mapping, electrical-conductivity, environmental-conditions, environmental-raster-layers, erodibility, geoscientificinformation, gypsum, hoover-dam, interpolate, machine-learning, maps-and-atlases, nevada, new-mexico, organic-matter, predicitve-modeling, predictive-mapping, predictive-maps, random-forest-models, random-forests, restrictive-layer, rock, sodium-adsorption-ratio, soil-conductivity, soil-density, soil-forming-factors, soil-ph, soil-properties, soil-property-maps, soil-sciences, soil-texture, soils, surface-rock-cover, surface-rock-size, texture-fractions, uncertainty, usgs-5e90b2f182ce172707ed7072, utah, wyoming
Organization: Department of the Interior
Plague causes fragmentation of prairie dog colonies in Conata Basin, South Dakota from 1993 – 2015

This data was used to investigate the invasion of a non-native disease, plague, to a keystone species, prairie dogs, in Conata Basin, South Dakota, United States. We documented the resulting extent of fragmentation and habitat loss in western grasslands using colony boundaries mapped by the USFS every one to three years from 1993 - 2015.  Specifically, we assessed how the arrival of plague in 2008, affected the size, shape, and aggregation of prairie dog colonies, an animal species known to be highly susceptible to plague. As expected the colony complex and the patches in colonies became smaller and more fragmented after the arrival of plague; the total area of each colony and the average area per patch within a colony decreased, the number of patches per colony increased, and average contiguity of each patch decreased, leading to habitat fragmentation.

Tags: biota, buffalo-gap-national-grassland, conata-basin-south-dakota, plague, prairie-dog, scuiridae, usgs-5e8f49c482cee42d134adf90, usgs-ema-low-mr-landscape-ecology
Organization: Department of the Interior
High-Resolution Aeromagnetic Survey of the Cle Elum Area, Washington

This data release provides access to a low-altitude, aeromagnetic survey of a part of central Washington centered approximately 22 km west-southwest of Ellensburg.  The  survey includes the cities of Ellensburg, Cle Elum, and Yakima and is referred to as the Cle Elum aeromagnetic survey.  The Cle Elum aeromagnetic survey extends from the Columbia Plateau westward to the eastern Cascade Range and illuminates magnetic anomalies associated with folds and faults of the Yakima folds, including the Umtanum Ridge, Saddle Mountains, and Frenchman Hills anticlines.  These data were acquired during August and September, 2008, by Firefly Aviation, Ltd., working under contract to the U.S. Geological Survey.  Total magnetic field values were acquired using a fixed-wing aircraft flown at a target elevation 150 m above terrain.  The nominal flying height was based on a best fit, pre-planned, three-dimensional draped surface 155 m above terrain, subject to aircraft climb and descent limitations. Flight lines were spaced 400 m apart and directed east-west.  Tie lines were spaced 4000 m apart, and directed north-south.  A total of 26,680 line-kilometers were acquired.  The details of the Cle Elum aeromagnetic survey are described in the document, CleElem_Tech_report.pdf available for download in this data release.

Tags: aeromagnetic-surveying, cle-elum, crust-earth, earthquakes, geoscientificinformation, kittitas, magnetic-anomaly, magnetic-field-earth, magnetometer-measurement, neotectonic-processes, usgs-5e8f363382cee42d134adf28, yakima
Organization: Department of the Interior
Nanoscale Molecular Composition of Solid Bitumen from the Eagle Ford Group Across a Natural Thermal Maturity Gradient

Solid bitumen is a petrographically-defined secondary organic matter residue produced during petroleum generation and subsequent oil transformation. The presence of solid bitumen impacts many shale reservoir properties including porosity, permeability, and hydrocarbon generation and storage, amongst others. Furthermore, solid bitumen reflectance is an important parameter for assessing the thermal maturity of formations with little to no vitrinite. While the molecular composition of solid bitumen will strongly impact associated parameters such as the development of organic matter porosity, hydrocarbon generation, and optical reflectance, assessing the molecular composition of solid bitumen in situ within shale reservoirs can be challenged by small grain sizes (often 1 m in diameter) and the inherent heterogeneity of shale formations. Here we employ the recently developed atomic force microscopy-based infrared spectroscopy (AFM-IR) to investigate solid bitumen molecular composition in situ within shale samples from the Late Cretaceous Eagle Ford Group possessing Type II-S kerogen that span a natural thermal maturity gradient from early oil-generation to the dry gas window. The application of AFM-IR allows for the rapid collection of thousands of measurements with ~50 nm resolution from the interrogated solid bitumen grains. Our results indicate that: (i) solid bitumen from the lower Eagle Ford displays both intra- and intergranular molecular variation, (ii) this molecular variation tends to, but not universally, decrease with an increase in thermal maturity, and (iii) the solid bitumen composition between samples, from an atomic ratio perspective, is more similar than analysis of kerogen isolates would indicate. These findings are discussed with perspective toward understanding the impact of thermal stress on the composition of secondary organic matter within the Eagle Ford Shale and highlight the growing awareness that organic matter heterogeneity within petroliferous mudrocks extends down to the nanoscale regime.

Tags: atomic-force-microscopy-based-infrared-spectroscopy-afm-ir, oil-and-gas-resources, organic-matter, shale, unconventional-oil-and-gas, usgs-5e8e101582cee42d13479c25
Organization: Department of the Interior
Predictive soil property map: Gypsum content

These data were compiled to demonstrate new predictive mapping approaches and provide comprehensive gridded 30-meter resolution soil property maps for the Colorado River Basin above Hoover Dam. Random forest models related environmental raster layers representing soil forming factors with field samples to render predictive maps that interpolate between sample locations. Maps represented soil pH, texture fractions (sand, silt clay, fine sand, very fine sand), rock, electrical conductivity (ec), gypsum, CaCO3, sodium adsorption ratio (sar), available water capacity (awc), bulk density (dbovendry), erodibility (kwfact), and organic matter (om) at 7 depths (0, 5, 15, 30, 60, 100, and 200 cm) as well as depth to restrictive layer (resdept) and surface rock size and cover. Accuracy and error estimated using a 10-fold cross validation indicated a range of model performances with coefficient of variation (R2) for models ranging from 0.20 to 0.76 with mean of 0.52 and a standard deviation of 0.12. Models of pH, om and ec had the best accuracy (R2 &gt; 0.6). Most texture fractions, CaCO3, and SAR models had R2 values from 0.5-0.6. Models of kwfact, dbovendry, resdept, rock models, gypsum and awc had R2 values from 0.4-0.5 excepting near surface models which tended to perform better. Very fine sands and 200 cm estimates for other models generally performed poorly (R2 from 0.2-0.4), and sample size for the 200 cm models was too low for reliable model building.  More than 90% of the soils data used was sampled since 2000, but some older samples are included. Uncertainty estimates were also developed by creating relative prediction intervals, which allow end users to evaluate uncertainty easily.

Tags: accuracy-and-error-estimated, arizona, available-water-capacity, bulk-density, calcium-carbonate, colorado, colorado-river, colorado-river-basin, colorado-river-basin-above-hoover-dam, digital-soil-mapping, electrical-conductivity, environmental-conditions, environmental-raster-layers, erodibility, geoscientificinformation, gypsum, hoover-dam, interpolate, machine-learning, maps-and-atlases, nevada, new-mexico, organic-matter, predicitve-modeling, predictive-mapping, predictive-maps, random-forest-models, random-forests, restrictive-layer, rock, sodium-adsorption-ratio, soil-conductivity, soil-density, soil-forming-factors, soil-ph, soil-properties, soil-property-maps, soil-sciences, soil-texture, soils, surface-rock-cover, surface-rock-size, texture-fractions, uncertainty, usgs-5e90b2c382ce172707ed6ede, utah, wyoming
Organization: Department of the Interior
Predictive soil property map: Fine sand content

These data were compiled to demonstrate new predictive mapping approaches and provide comprehensive gridded 30-meter resolution soil property maps for the Colorado River Basin above Hoover Dam. Random forest models related environmental raster layers representing soil forming factors with field samples to render predictive maps that interpolate between sample locations. Maps represented soil pH, texture fractions (sand, silt clay, fine sand, very fine sand), rock, electrical conductivity (ec), gypsum, CaCO3, sodium adsorption ratio (sar), available water capacity (awc), bulk density (dbovendry), erodibility (kwfact), and organic matter (om) at 7 depths (0, 5, 15, 30, 60, 100, and 200 cm) as well as depth to restrictive layer (resdept) and surface rock size and cover. Accuracy and error estimated using a 10-fold cross validation indicated a range of model performances with coefficient of variation (R2) for models ranging from 0.20 to 0.76 with mean of 0.52 and a standard deviation of 0.12. Models of pH, om and ec had the best accuracy (R2 &gt; 0.6). Most texture fractions, CaCO3, and SAR models had R2 values from 0.5-0.6. Models of kwfact, dbovendry, resdept, rock models, gypsum and awc had R2 values from 0.4-0.5 excepting near surface models which tended to perform better. Very fine sands and 200 cm estimates for other models generally performed poorly (R2 from 0.2-0.4), and sample size for the 200 cm models was too low for reliable model building.  More than 90% of the soils data used was sampled since 2000, but some older samples are included. Uncertainty estimates were also developed by creating relative prediction intervals, which allow end users to evaluate uncertainty easily.

Tags: accuracy-and-error-estimated, arizona, available-water-capacity, bulk-density, calcium-carbonate, colorado, colorado-river, colorado-river-basin, colorado-river-basin-above-hoover-dam, digital-soil-mapping, electrical-conductivity, environmental-conditions, environmental-raster-layers, erodibility, geoscientificinformation, gypsum, hoover-dam, interpolate, machine-learning, maps-and-atlases, nevada, new-mexico, organic-matter, predicitve-modeling, predictive-mapping, predictive-maps, random-forest-models, random-forests, restrictive-layer, rock, sodium-adsorption-ratio, soil-conductivity, soil-density, soil-forming-factors, soil-ph, soil-properties, soil-property-maps, soil-sciences, soil-texture, soils, surface-rock-cover, surface-rock-size, texture-fractions, uncertainty, usgs-5e90b2a582ce172707ed6de8, utah, wyoming
Organization: Department of the Interior
Predictive soil property map: Erodability

These data were compiled to demonstrate new predictive mapping approaches and provide comprehensive gridded 30-meter resolution soil property maps for the Colorado River Basin above Hoover Dam. Random forest models related environmental raster layers representing soil forming factors with field samples to render predictive maps that interpolate between sample locations. Maps represented soil pH, texture fractions (sand, silt clay, fine sand, very fine sand), rock, electrical conductivity (ec), gypsum, CaCO3, sodium adsorption ratio (sar), available water capacity (awc), bulk density (dbovendry), erodibility (kwfact), and organic matter (om) at 7 depths (0, 5, 15, 30, 60, 100, and 200 cm) as well as depth to restrictive layer (resdept) and surface rock size and cover. Accuracy and error estimated using a 10-fold cross validation indicated a range of model performances with coefficient of variation (R2) for models ranging from 0.20 to 0.76 with mean of 0.52 and a standard deviation of 0.12. Models of pH, om and ec had the best accuracy (R2 &gt; 0.6). Most texture fractions, CaCO3, and SAR models had R2 values from 0.5-0.6. Models of kwfact, dbovendry, resdept, rock models, gypsum and awc had R2 values from 0.4-0.5 excepting near surface models which tended to perform better. Very fine sands and 200 cm estimates for other models generally performed poorly (R2 from 0.2-0.4), and sample size for the 200 cm models was too low for reliable model building.  More than 90% of the soils data used was sampled since 2000, but some older samples are included. Uncertainty estimates were also developed by creating relative prediction intervals, which allow end users to evaluate uncertainty easily.

Tags: accuracy-and-error-estimated, arizona, available-water-capacity, bulk-density, calcium-carbonate, colorado, colorado-river, colorado-river-basin, colorado-river-basin-above-hoover-dam, digital-soil-mapping, electrical-conductivity, environmental-conditions, environmental-raster-layers, erodibility, geoscientificinformation, gypsum, hoover-dam, interpolate, machine-learning, maps-and-atlases, nevada, new-mexico, organic-matter, predicitve-modeling, predictive-mapping, predictive-maps, random-forest-models, random-forests, restrictive-layer, rock, sodium-adsorption-ratio, soil-conductivity, soil-density, soil-forming-factors, soil-ph, soil-properties, soil-property-maps, soil-sciences, soil-texture, soils, surface-rock-cover, surface-rock-size, texture-fractions, uncertainty, usgs-5e90b27d82ce172707ed6c87, utah, wyoming
Organization: Department of the Interior
U-Pb data for inherited cassiterite in "Tin Granites", an example from the Yazov Granite, Eastern Siberia

Zircon (ZrSiO4) and cassiterite (SnO2) samples were collected by the U.S. Geological Survey (USGS) from the Yazov Granite, Transbaikalia region, Eastern Siberia, Russia.  Samples (in the form of mounted loose grains) were prepared and analyzed for direct age dating on a laser ablation inductively coupled plasma mass spectrometer (LA–ICPMS) system at the USGS in Denver, Colorado from February 2017 to June 2019.  The data indicate that high tin concentrations in the Yazov Granite are caused by inheritance of older cassiterite crystals and may imply that these granites cannot be genetically related to primary tin ore deposits of the region.  These results have broad implications in understanding how critical elements, like tin, are enriched in rare-metal granites.

Tags: cassiterite, geochronology, geology-geophysics-and-geochemistry-science-center, geoscientific-information, gggsc, la-icpms, laser-ablation-inductively-coupled-plasma-mass-spectrometer, lead, mineral-deposits, mineral-resources-program, mrp, russia, siberia, thorium, transbaikalia, u-pb, u-s-geological-survey, uranium, uranium-lead-analysis, usgs, usgs-5e8df35782cee42d13469634, yazov-granite, zircon
Organization: Department of the Interior
Chemistry Data from Southern Florida Canals Collected in Support of the Aquatic Cycling of Mercury in the Everglades Project

Several canals in southern Florida run from Lake Okeechobee through the Everglades Agricultural Area (EAA) and feed water to the northern Everglades.  Agricultural and water-management practices affect the water quality of these canals.  Fertilizers added in the EAA flow into the canals and are transported to treatment areas which remove much of the phosphorous in the water, but are not as effective in removing dissolved sulfate.  Elevated sulfate concentrations, found downstream in the Water Conservation Areas in the northern Everglades, can stimulate sulfur-reducing bacteria which can also convert inorganic mercury to methyl mercury, a bioaccumulative neurotoxin. 
Chemistry data at 25 canal sites in southern Florida were sampled for water properties (temperature, pH, specific conductance), sulfur isotopes, major anions and cations, nutrients (including ammonium and orthophosphate), and trace metals.  Data collection began in 1996 with a small subset of sites, and has continued through 2019.  Funding for this data collection was provided by the USGS Priority Ecosystems Studies Program for South Florida (Nick Aumen, Program Executive).

Tags: broward-county, contaminant-transport, datasets, miami-dade-county, nonpoint-source-pollution, palm-beach-county, sulfur, surface-water-quality, the-everglades, usgs-5e8dc75f82cee42d134677f2
Organization: Department of the Interior
Base Control Points enhanced with airborne electromagnetic (AEM) surveys of the principal aquifer for portions of the North Platte, South Platte, and Twin Platte Natural Resources Districts, western Nebraska

The U.S. Geological Survey and its partners have collaborated to complete airborne geophysical 
surveys for areas of the North and South Platte River valleys and Lodgepole Creek in western 
Nebraska. The objective of the surveys was to map the aquifers and bedrock topography of 
selected areas to help improve the understanding of groundwater-surface-water relationships 
to be used in water management decisions. Frequency-domain (2008 and 2009) and time-domain 
(2010) helicopter electromagnetic surveys were completed, using a unique survey flight line design, 
to collect resistivity data that can be related to lithologic information for refinement of groundwater 
model inputs.  To make the geophysical data useful for multidimensional groundwater models, 
numerical inversion is necessary to convert the measured data into a depth-dependent subsurface 
resistivity model.  This inversion model, in conjunction with sensitivity analysis, geological ground 
truth (boreholes), and geological interpretation, is used to characterize hydrogeologic features.  
The two- and three- dimensional interpretation provides the groundwater modeler with a high-resolution 
hydrogeologic framework and a quantitative estimate of framework uncertainty.  This method of 
creating hydrogeologic frameworks improved the understanding of the actual flow path orientation 
by redefining the location of the paleochannels and associated bedrock highs. The improved models 
represent the hydrogeology at a level of accuracy not achievable using previous data sets.

Tags: environment, geoscientificinformation, imagerybasemapsearthcover, inlandwaters, nebraska, ogallala, scottsbluff, sidney, usgs-5e8d89de-786d-4d58-9b39-d7ecef8a24ff
Organization: Department of the Interior