AndreaBozzo/ceres-open-data-index huggingface dataset:
Map georeferencing challenge training and validation data

Extracting useful and accurate information from scanned geologic and other earth science maps is a time-consuming and laborious process involving manual human effort. To address this limitation, the USGS partnered with the Defense Advanced Research Projects Agency (DARPA) to run the AI for Critical Mineral Assessment Competition, soliciting innovative solutions for automatically georeferencing and extracting features from maps. The competition opened for registration in August 2022 and concluded in December 2022. Training, validation, and evaluation data from the map georeferencing challenge are provided here, as well as competition details and a baseline solution. The data were derived from published sources and are provided to the public to support continued development of automated georeferencing and feature extraction tools.  References for all maps are included with the data.

Tags: ai, artificial-intelligence, competition, critical-mineral-resources, digitization, economy, geological-maps, geoscientificinformation, geospatial-datasets, gis, machine-learning, ml, modeling, resource-assessment, tool-development, topographic-maps, training-data, usgs-64c14e4fd34e70357a32990f
Organization: Department of the Interior
Oregon spotted frog (Rana pretiosa) captures before and after drought mitigation at Jack Creek, Oregon 2009-2021

Amphibians are among the most sensitive taxa to climate change, and species inhabiting arid and semiarid landscapes at the extremes of their range are especially vulnerable to periods of drought. The Jack Creek, Oregon, USA population of Oregon spotted frogs (Rana pretiosa) faces unique challenges occupying the highest elevation site in the species’ extant range and one that has been hydrologically transformed by loss of  American beaver (Castor canadensis). We evaluated the effect of drought mitigation (addition of excavated ponds) on relationships between local water availability, legacy beaver dams, and R. pretiosa population dynamics in the Jack Creek system. We conducted capture-mark-recapture sampling at a treatment reach with excavated ponds and 3 reference reaches over 13 years; surveys spanned a period before and after pond excavation at the treatment and one reference reach. This dataset contains capture data and covariates used in the robust design capture-mark-recapture analysis to characterize population dynamics, described in Rowe et al. 2023.

Tags: amphibians, biota, drainage-basins, droughts, ecology, ecosystem-monitoring, effects-of-climate-change, environment, freshwater-ecosystems, habitats, lakes, location, national-forest-fs, oregon, population-dynamics, upper-klamath, usgs-64c166aad34e70357a329989, wetland-ecosystems, williamson-river
Organization: Department of the Interior
Ruby Mountains and East Humboldt Range, Nevada: U-Pb zircon age and trace element data and whole-rock Pb, Sr, and Nd isotopic data

This dataset accompanies planned publication 'Paleogene mid-crustal intrusions in the Ruby Mountains Metamorphic Core Complex, northeastern Nevada' [IP-153033], to be published in Geosphere, as well as planned future publications in this region. The data encompass U-Pb zircon age and trace element data and whole-rock Pb, Sr, and Nd isotopic data from igneous and metamorphic rocks throughout the Ruby Mountains, East Humboldt Range, Lizzies Basin, Lamoille Canyon, and Angel Lake areas of northeast, Nevada. Samples were collected from this area by Allen McGrew (Univ. of Dayton), Arthur Snoke (Univ. of Wyoming), Wayne Premo (USGS) and Keith Howard (USGS), who brought them to the USGS Denver for analysis. The analyses were performed from Nov 2004 to May 2015.

Tags: amphibolite, east-humboldts-wilderness, geochronology, geology-geophysics-and-geochemistry-science-center, geoscientificinformation, isotope-geochemistry, lamoille, mass-spectrometry, mineral-resources-program, nd, nevada, orthogneiss, paragneiss, pb, radiometric-dating, ruby-mountains-wilderness, sr, u-s-geological-survey, u_, usgs-64c3f4dfd34e70357a33cf9a
Organization: Department of the Interior
North American Bat Monitoring Program (NABat) Bayesian Hierarchical Model for Winter Abundance: Predicted Population Estimates (2022 and 2023)

The dataset is comprised of historical observations and predictions of winter colony counts at known sites for three bat species (little brown bat, Myotis lucifugus; tricolored bat, Perimyotis subflavus; and big brown bat, Eptesicus fuscus). The dataset consists of two separate but related data files in tabular format (comma-separated values [.csv]). Each data set consists of predicted winter counts derived using winter status and trends modeling methods developed by the North American Bat Monitoring Program (NABat). These two predicted winter count data sets were used to inform NABat summertime status and trends analysis: 1) modeled abundance predictions for all hibernacula for all three species from 2010-2021, and 2) modeled abundance predictions for P. subflavus from 2010-2023 using updated monitoring data. Abundance predictions were derived with a combined modeling approach that applied an exponential linear interpolation model (when there were less than 4 observations per location) and a Bayesian hierarchical model (where there were 4 or more data points per location).

Tags: abundance, bats, biota, hibernacula, usgs-64c4387ad34e70357a33d983, winter-colony
Organization: Department of the Interior
Conceptual marsh units of Connecticut salt marshes

This data release contains coastal wetland synthesis products for the state of Connecticut. Metrics for resiliency, including the unvegetated to vegetated ratio (UVVR), marsh elevation, tidal range, wave power, and exposure potential to environmental health stressors are calculated for smaller units delineated from a digital elevation model, providing the spatial variability of physical factors that influence wetland health. The U.S. Geological Survey has been expanding national assessment of coastal change hazards and forecast products to coastal wetlands with the intent of providing federal, state, and local managers with tools to estimate the vulnerability and ecosystem service potential of these wetlands. For this purpose, the response and resilience of coastal wetlands to physical factors need to be assessed in terms of the ensuing change to their vulnerability and ecosystem services. This project has been funded in part by the United States Environmental Protection Agency under assistance agreement DW-014-92531201-1 to N. Ganju.

Tags: coastal-ecosystems, coastal-processes, connecticut, environment, estuary, geospatial-datasets, inlandwaters, long-island-sound, marsh-health, oceans, salt-marsh, united-states, usgs-64c40893d34e70357a33d41f, vegetation, wetland-ecosystems, wetland-functions
Organization: Department of the Interior
Grand Prairie Historical Calibration Period Groundwater-Flow Model

The Mississippi Alluvial Plain (MAP) is one of the most important agricultural regions in the United States and underlies about 32,000 square miles of Missouri, Kentucky, Tennessee, Mississippi, Louisiana, and Arkansas. The MAP region supports a multibillion-dollar agricultural industry. The MAP is part of the Mississippi Embayment with several water-bearing units that make up the Mississippi Embayment Regional Aquifer System (MERAS). These water bearing units include the Mississippi River Valley Alluvial aquifer, Claiborne aquifers and Wilcox aquifers. The Grand Prairie area has been designated as a Critical Groundwater area because of decades of groundwater declines that resulted from past and current water use. The objective of the report associated with this data release is to document and describe the construction, calibration, and results of the inset groundwater-flow model developed for the Grand Prairie Critical Groundwater Area using the latest MODFLOW-6 code. The model derived boundary conditions from the parent MERAS 3 regional model to provide higher resolution simulations in the Grand Prairie focus area. The Grand Prairie model was spatially discretized into 500-meter x 500-meter orthogonal cells on a grid. The Grand Prairie model had 19 vertical layers, 245 rows, and 206 columns and simulated the Quaternary-age alluvial aquifer with 5-m constant thickness layers and increasing thickness layers for the Tertiary-age units below the alluvial aquifer. The Grand Prairie model included 148 stress periods with a simulation period from January 1, 1900 through December 31, 2018 where stress periods: April 1, 2007 through December 31, 2018 where monthly stress periods. Areal recharge was simulated by a soil-water-balance model of the MERAS and passed to the groundwater models. The model simulated agricultural, municipal, and thermoelectric pumping. The model simulated groundwater-surface water interactions and total streamflow by adding runoff from the soil-water-balance model. The model featured high-dimensional parameterization schemes for calibration using the PEST++ Iterative Ensemble Smoother. Mean absolute residuals for calibrated priority well observations were 2.71 meters for the Grand Prairie model. Mean horizontal hydraulic conductivity for the alluvial aquifer was about 63 meters per day for the Grand Prairie model. Calibrated areal recharge was 3.4 inches for the Grand Prairie model. Primary groundwater outflows represented in the model were from agricultural wells.

Tags: arkansas, environment, geoscientificinformation, groundwater, groundwater-and-surface-water-interaction, groundwater-flow, groundwater-flow-modeling, groundwater-model, hydrogeology, inlandwaters, integrated-hydrologic-flow-modeling, mississippi-alluvial-plain, mississippi-river-valley-alluvial-aquifer, modflow, modflow-6, pest, streamflow, usgs-64c14261d34e70357a32986a, usgsgroundwatermodel, water-availability, water-budget
Organization: Department of the Interior
Map feature extraction challenge training and validation data

Extracting useful and accurate information from scanned geologic and other earth science maps is a time-consuming and laborious process involving manual human effort. To address this limitation, the USGS partnered with the Defense Advanced Research Projects Agency (DARPA) to run the AI for Critical Mineral Assessment Competition, soliciting innovative solutions for automatically georeferencing and extracting features from maps. The competition opened for registration in August 2022 and concluded in December 2022. Training, validation, and evaluation data from the map feature extraction challenge are provided here, as well as competition details and a baseline solution. The data were derived from published sources and are provided to the public to support continued development of automated georeferencing and feature extraction tools. References for all maps are included with the data.

Tags: ai, artificial-intelligence, competition, critical-mineral-resources, digitization, economy, geological-maps, geoscientificinformation, geospatial-datasets, gis, machine-learning, ml, modeling, resource-assessment, tool-development, topographic-maps, training-data, usgs-64c14e71d34e70357a329912
Organization: Department of the Interior
3_Input files and PRMS model-run components for the releases of the precalibration, byHRU and byPOIobs Alaska  NHM-PRMS, 1980–2021

This data release contains inputs for and outputs from hydrologic simulations for the Alaska (AK) domain using the Precipitation Runoff Modeling System (PRMS) version 5.2.1.1 and the USGS National Hydrologic Model infrastructure (NHM, Regan and others, 2018). Historical simulations using the Daymet Version 4 gridded estimates of daily weather parameters (Thornton and others, 2022) were produced for the period 1980–2021. These data document the PRMS climate input data files for these simulations. Input files for the simulations include the PRMS parameter and control files. The main landing page provides additional information and data dictionaries (parameters_data_dictionary.csv and control_data_dictionary.csv) that describe the parameter and control file values. Daymet forcings include precipitation and minimum and maximum temperature at a daily time-step.
Measured streamflow data (sf_data, Table_1_AK_gages.csv) are included for 279 sites with period of records between 1980-2021. Contained in this set are data from 186 USGS streamgage locations (U.S. Geological Survey, 2022), and 93 streamgage locations from the Canadian Water Survey (HYDAT, 2024). From the original set, data from 249 sites were used as calibration targets of individual drainage areas inside the AK domain.
CONTENTS OF THIS CHILD PAGE:
1.	Precip.day = daily total precipitation climate-by-hydrologic response unit (CBH) file
2.	Tmax.day = maximum daily temperature CBH file
3.	Tmin.day = minimum daily temperature CBH file.
4.	PRMS_5.2.1.1.zip = PRMS executable version 5.2.1.1.
5.	sf_data = Daily measured USGS and Canadian Water Survey  streamflow data.
6.	AK_precalibration.control = Precalibration model control file for the AK domain precalibration release.
7.	AK_precalibration.param = Precalibration model parameter file for the AK domain precalibration release.
8.	AK_byHRU.control = byHRU model control file for the AK domain byHRU release.
9.	AK_byHRU.param = byHRU model parameter file for the AK domain byHRU release.
10. 	AK_byPOIobs.param = PRMS parameter file for the AK domain byPOIobs release
11. 	AK_byPOIobs.control = PRMS control file for the AK domain byPOIobs release
12. 	AK_NHM_PRMS.bat = batch file that can be edited to run the model.

Tags: alaska, british-columbia, canada, hydrology, inlandwaters, model, streamflow, streamflow-modeling, usgs-64c1cbebd34e70357a32a300, water-resources, yukon, yukon-territory
Organization: Department of the Interior
Supporting Data and Models for "An unexplained tsunami: Was there megathrust slip during the 2020 Mw7.6 Sand Point, Alaska, earthquake?"

This data release contains several input data and inversion output files used to model the October 19, 2020, Mw7.6 Sand Point, Alaska, earthquake and tsunami. The broadband seismic data in this data release are from globally distributed seismometers from networks G (https://doi.org/10.18715/GEOSCOPE.G), GE (https://doi.org/10.14470/TR560404), GR (https://doi.org/10.25928/mbx6-hr74), GS (https://doi.org/10.7914/SN/GS), II (https://doi.org/10.7914/SN/II), IU (https://doi.org/10.7914/SN/IU), and US (https://doi.org/10.7914/SN/US). Strong-motion accelerometer data are from network AK (https://doi.org/10.7914/SN/AK). Global Navigation Satellite System (GNSS) data are from the EarthScope (formerly UNAVCO) GNSS network (https://doi.org/10.7283/T59W0CDH, https://doi.org/10.7283/T5SF2T4X, https://doi.org/10.7283/T5VH5KS0, https://doi.org/10.7283/T5HQ3WW8, https://doi.org/10.7283/T5Z60M01, https://doi.org/10.7283/T5028PG3, https://doi.org/10.7283/T5JS9NDC, https://doi.org/10.7283/T5Q23X61, https://doi.org/10.7283/T50G3H4S, https://doi.org/10.7283/T5VX0DJ1, https://doi.org/10.7283/T5NV9G7P, https://doi.org/10.7283/T5F18WRV, https://doi.org/10.7283/T53N21DV). Coastal water level data is provided by the Intergovernmental Oceanographic Commission and operated by the National Oceanic and Atmospheric Administration (https://doi.org/10.7289/V59884XF). Deep-ocean Assessment and Reporting of Tsunamis (DART) stations are operated by the National Oceanic and Atmospheric Administration (https://doi.org/10.7289/V5F18WNS).
Results from modeling these datasets are described in the interpretive manuscript: Santellanes and others (2025) An unexplained tsunami: Was there megathrust slip during the 2020 Mw7.6 Sand Point, Alaska, earthquake? Seismica. https://doi.org/10.26443/seismica.v3i2.1336.

Tags: earthquake-occurrences, seismology, usgs-64c4162cd34e70357a33d4ab
Organization: Department of the Interior
Data for improved understanding of the susceptibility of Lake Superior to threats from groundwater contamination

This data release contains a data compilation and analysis of the hydrogeology in the U.S. portion of the Lake Superior watershed, for the purpose of providing background data for future study and modeling of groundwater and contaminant movement in the watershed.  The data support an analysis of groundwater contributions to the water budget of Lake Superior and provide hydrogeologic context for future modeling and sampling of groundwater in the region.  The data release contains three child items: Baseflow analysis for tributaries to Lake Superior from 1946 to 2020; Geohydrology data for groundwater analysis in the Lake Superior Watershed; and Groundwater wells from Minnesota, Wisconsin, and Michigan state databases and the U.S. Geological (USGS) National Water Information System (NWIS) database with static water level data within 10km of the Lake Superior watershed.

Tags: base-flow, geoscientificinformation, groundwater, groundwater-wells, hydrogeology, lake-superior, michigan, minnesota, usgs-64c27303d34e70357a32f3ba, water-budgets, wisconsin
Organization: Department of the Interior
Pronghorn probability of occurrence in the Wyoming Basins Ecoregional Assessment area

Probability map of pronghorn occurrence in relation to vegetation, abiotic, and anthropogenic features.

Tags: biota, colorado, environment, geoscientificinformation, geospatial-datasets, idaho, modeling, montana, probability-of-occurrence, pronghorn, scientific-interpretation, shrubland-ecosystems, usgs-6488cb3bd34ef77fcafe4007, utah, western-united-states, wyoming
Organization: Department of the Interior
Predictions and supporting data for network-wide 7-day ahead forecasts of water temperature in the Delaware River Basin: 5) model code

This data release contains the forcings and outputs of 7-day ahead maximum water temperature forecasting models that makes predictions at 70 river reaches in the upper Delaware River Basin. This section includes code that prepares data for model training and forecasts maximum stream temperature using neural network models. Finally, the code evaluates the models using various accuracy and uncertainty metrics.

Tags: deep-learning, environment, forecast, hybrid-modeling, inlandwaters, machine-learning, modeling, new-york, ny, pa, pennsylvania, reservoirs, streams, temperature, united-states, us, usgs-6487548dd34ef77fcafe1753, water, water-resources
Organization: Department of the Interior
Demographic parameter estimates for San Francisco gartersnakes (Thamnophis sirtalis tetrataenia) for fitting an Integral Projection Model

A study comparing reintroduction scenarios for the San Francisco gartersnake (Thamnophis sirtalis tetrataenia), an endangered subspecies native to San Mateo County and Santa Cruz County in northern California. Models for snake survival, growth, fecundity, and reproductive status were used to construct a demographic population model. Data are posterior distributions for demographic parameters from Markov Chain Monte Carlo sampling in hierarchical Bayesian models.

Tags: biota, california, ecology, modeling, population-dynamics, reptiles, san-mateo-county, usgs-6488b49fd34ef77fcafe3eab
Organization: Department of the Interior
White-tailed jackrabbit distribution in the Wyoming Basins Ecoregional Assessment area

Map of white-tailed jackrabbit distribution developed from a probability of occurrence map created using multi-scale vegetation, abiotic, and anthropogenic features.

Tags: biota, colorado, distribution, environment, environment-and-conservation, geoscientificinformation, geospatial-datasets, idaho, modeling, montana, scientific-interpretation, shrubland-ecosystems, united-states, usgs-6488cb5bd34ef77fcafe400d, utah, white-tailed-jackrabbit, wyoming
Organization: Department of the Interior
Projected coastal flooding depths for 1-, 20-, and 100-year return interval storms and 0.00, +0.25, +0.50, +1.00, +1.50, +2.00, and +3.00 meter sea-level rise scenarios in American Samoa

This data release provides flood depth GeoTIFFs based on sea-level rise and wave-driven total water levels for the coast of the American  Samoa’s most populated islands of Tutuila, Ofu-Olosega, and Tau. Oceanographic, coastal engineering, ecologic, and geospatial data and tools were combined to evaluate the increased risks of storm-induced coastal flooding in the populated American Samoan Islands due to climate change and sea-level rise. We followed risk-based valuation approaches to map flooding due to waves and storm surge at 10-m2 resolution along the coastlines for annual (1-year), 20-year, and 100-year return-interval storm events and +0.25 m, +0.50 m, +1.00 m, +1.50 m, +2.00 m, and +3.00 m sea-level rise scenarios.

Tags: climate-change, cmhrp, coastal-and-marine-hazards-and-resources-program, coastal-processes, earth-sciences, effects-of-climate-change, environment, environmental-equity, environmental-justice, flooding, floods, geoscientificinformation, geospatial-datasets, mathematical-modeling, oceans, ofu-island, olosega-island, pacific-coastal-and-marine-science-center, pcmsc, physical-habitats-and-geomorphology, predictions, sea-level-change, spatial-analysis, storms, tau-island, territory-of-american-samoa, tutuila-island, u-s-geological-survey, usgs, usgs-64821e9cd34eac007b580e16, waves
Organization: Department of the Interior
Projected coastal flooding extents for 1-, 20-, and 100-year return interval storms and 0.00, +0.25, +0.50, +1.00, +1.50, +2.00, and +3.00 meter sea-level rise scenarios in American Samoa

This data release provides flooding extent polygons based on sea-level rise and wave-driven total water levels for the coast of American Samoa's most populated islands of Tutuila, Ofu-Olosega, and Tau. Oceanographic, coastal engineering, ecologic, and geospatial data and tools were combined to evaluate the increased risks of storm-induced coastal flooding due to climate change and sea-level rise. We followed risk-based valuation approaches to map flooding due to waves and storm surge at 10-m2 resolution along these islands' coastlines for annual (1-year), 20-year, and 100-year return-interval storm events and +0.25 m, +0.50 m, +1.00 m, +1.50 m, +2.00 m, and +3.00 m sea-level rise scenarios.

Tags: climate-change, cmhrp, coastal-and-marine-hazards-and-resources-program, coastal-processes, earth-sciences, effects-of-climate-change, environment, environmental-equity, environmental-justice, flooding, floods, geoscientificinformation, geospatial-datasets, mathematical-modeling, oceans, ofu-island, olosega-island, pacific-coastal-and-marine-science-center, pcmsc, physical-habitats-and-geomorphology, predictions, sea-level-change, spatial-analysis, storms, tau-island, territory-of-american-samoa, tutuila-island, u-s-geological-survey, usgs, usgs-64821eb3d34eac007b580e19, waves
Organization: Department of the Interior
Lark sparrow distribution in the Wyoming Basins Ecoregional Assessment area

Map of Lark sparrow distribution developed from an abundance map created using multi-scale vegetation, abiotic, and anthropogenic features.

Tags: biota, colorado, distribution, environment, environment-and-conservation, geoscientificinformation, geospatial-datasets, idaho, lark-sparrow, modeling, montana, scientific-interpretation, shrubland-ecosystems, united-states, usgs-6488c1ddd34ef77fcafe3f73, utah, wyoming
Organization: Department of the Interior
Harvester Ant probability of occurrence in the Wyoming Basins Ecoregional Assessment area

Probability map of Harvester Ant occurrence in relation to vegetation, abiotic, and anthropogenic features.

Tags: biota, colorado, environment, geoscientificinformation, geospatial-datasets, harvester-ant, idaho, modeling, montana, probability-of-occurrence, scientific-interpretation, shrubland-ecosystems, usgs-6488c093d34ef77fcafe3f65, utah, western-united-states, wyoming
Organization: Department of the Interior
Deer mouse probability of occurrence in the Wyoming Basins Ecoregional Assessment area

Probability map of deer mouse occurrence in relation to vegetation, abiotic, and anthropogenic features.

Tags: biota, colorado, deer-mouse, environment, geoscientificinformation, geospatial-datasets, idaho, modeling, montana, probability-of-occurrence, scientific-interpretation, shrubland-ecosystems, usgs-6488c32ed34ef77fcafe3f88, utah, western-united-states, wyoming
Organization: Department of the Interior