AndreaBozzo/ceres-open-data-index huggingface dataset:
National Land Cover Database (NLCD) 2016 Impervious Products

The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released four
National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, and 2011.
These products provide spatially explicit and reliable information on the Nation’s land cover and land cover
change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s
land resources, the USGS has designed a new generation of NLCD products named NLCD 2016. The NLCD 2016
design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land
cover and land cover change database from 2001 to 2016 at 2–3-year intervals. Comprehensive research was
conducted and resulted in developed strategies for NLCD 2016: a streamlined process for assembling and preprocessing
Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development
and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land
cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for
generating land cover and change products; a continuous fields biophysical parameters modeling method; and
an automated scripted operational system for the NLCD 2016 production. The performance of the developed
strategies and methods were tested in twenty World Reference System-2 path/row throughout the conterminous
U.S. An overall agreement ranging from 71% to 97% between land cover classification and reference data was
achieved for all tested area and all years. Results from this study confirm the robustness of this comprehensive
and highly automated procedure for NLCD 2016 operational mapping.
Questions about the NLCD 2016 land cover product can be directed to the NLCD 2016 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.

Tags: biota, digital-spatial-data, gis, image-processing, imagerybasemapsearthcover, land-cover, land-use-land-cover-theme, national-geospatial-data-asset, ngda, u-s, u-s-geological-survey-usgs, united-states, us, usgs-5d9b9029e4b0366162922fc1
Organization: Department of the Interior
National Land Cover Database (NLCD) 2016 Land Cover Products

The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released four
National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, and 2011.
These products provide spatially explicit and reliable information on the Nation’s land cover and land cover
change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s
land resources, the USGS has designed a new generation of NLCD products named NLCD 2016. The NLCD 2016
design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land
cover and land cover change database from 2001 to 2016 at 2–3-year intervals. Comprehensive research was
conducted and resulted in developed strategies for NLCD 2016: a streamlined process for assembling and preprocessing
Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development
and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land
cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for
generating land cover and change products; a continuous fields biophysical parameters modeling method; and
an automated scripted operational system for the NLCD 2016 production. The performance of the developed
strategies and methods were tested in twenty World Reference System-2 path/row throughout the conterminous
U.S. An overall agreement ranging from 71% to 97% between land cover classification and reference data was
achieved for all tested area and all years. Results from this study confirm the robustness of this comprehensive
and highly automated procedure for NLCD 2016 operational mapping.
Questions about the NLCD 2016 land cover product can be directed to the NLCD 2016 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.

Tags: biota, digital-spatial-data, gis, image-processing, imagerybasemapsearthcover, land-cover, land-use-land-cover-theme, national-geospatial-data-asset, ngda, u-s, u-s-geological-survey-usgs, united-states, us, usgs-5d9b8ffee4b0366162922fbe
Organization: Department of the Interior
Spatially constrained inversion resistivity models

Shallow soil characteristics were mapped near Shellmound, Mississippi, using the DualEM 421 electromagnetic sensor in October 2018. Data were acquired by towing the DualEM sensor on a wheeled cart behind an ATV, with the sensor at a height of 0.432 m above the ground surface. Approximately 175 line-kilometers of data were acquired over an area of nearly four square kilometers, with 25 m separation between survey lines. Data were manually edited for noise sources such as powerlines or other buried structures, and averaged to regular output soundings every 5 m along survey lines. The processed data were inverted to recover models of electrical resistivity structure as a function of depth at each sounding location using a spatially constrained inversion. This data release contains the inverted resistivity models. Digital data of the laterally constrained inversions are provided and fields are defined in the data dictionary. Model results show typical depth of investigation from about 4 – 6 m, with spatial variability in mapped electrical resistivity characteristic of fluvial deposition of sediments in channels and scroll bar features adjacent to the Tallahatchie River and nearby abandoned meander channels.

Tags: electromagnetic-surveying, electromagnetics, engineering-sciences, environment, geology-geophysics-and-geochemistry-science-center, geophysics, geoscientificinformation, gggsc, groundwater, hydrogeology, leflore-county, mississippi, mississippi-alluvial-plain, mississippi-river-valley-alluvial-aquifer, mrva, resistivity, shellmound, tallahatchie-river, usgs-5d9cd4f5e4b0366162923941, water-resources
Organization: Department of the Interior
Estimating environmental thresholds for three classes of sagebrush condition in the western United States (2001 – 2015)

We employed decision-tree mapping models in two formats to establish a time series (2001 - 2015) of sagebrush condition class in the western United States. The formats were predictive and descriptive, and each model produced distinct spatially explicit datasets. The predictive model mapped the probability of sagebrush recovery, tipping point (environmental degradation), or stable classes. The descriptive model mapped rules that were defined by environmental thresholds. The thresholds were defined by the interaction between the independent variables and the dependent variable. Mapping areas of stability and areas of change using machine-learning algorithms allows both the identification of dominant abiotic variables that drive ecosystem dynamics and the variables’ important thresholds. The sagebrush recovery class, on average, covers areas of mid elevations (1602 m) for sagebrush ecosystems, warm 30-yr July maximum temperatures, and 30-yr March precipitation averages equal to 26.26 mm. The tipping point class covers areas with a mean elevation value about 100 m lower than the recovery class. The stable class occurs at the highest elevations of all classes, averaging 1939 m. Both the tipping point and the stable classes were more mesic in March and cooler in July than the recovery class. These defined variable averages can be used to understand current dynamics of sagebrush condition and to predict where future transitions may occur under changing conditions.

Tags: annual-invasive-grass, california, climate, decision-tree-model, geoscientificinformation, idaho, machine-learning, montana, nevada, oregon, sagebrush, usgs-5d9b6fbbe4b036616291af1e, utah, western-u-s
Organization: Department of the Interior
Process-guided deep learning water temperature predictions: 3b Sparkling Lake inputs

This dataset includes model inputs that describe local weather conditions for Sparkling Lake, WI. Weather data comes from two sources: locally measured (2009-2017) and gridded estimates (all other time periods). There are two comma-delimited files, one for weather data (one row per model timestep) and one for ice-flags, which are used by the process-guided deep learning model to determine whether to apply the energy conservation constraint (the constraint is not applied when the lake is presumed to be ice-covered). The ice-cover flag is a modeled output and therefore not a true measurement (see "Predictions" and "pb0" model type for the source of this prediction). This dataset is part of a larger data release of lake temperature model inputs and outputs for 68 lakes in the U.S. states of Minnesota and Wisconsin (http://dx.doi.org/10.5066/P9AQPIVD).

Tags: biota, climate-change, deep-learning, environment, hybrid-modeling, inlandwaters, machine-learning, modeling, reservoirs, temperate-lakes, temperature, thermal-profiles, united-states, us, usgs-5d98e0dbe4b0c4f70d1186f3, water, wi, wisconsin
Organization: Department of the Interior
Process-guided deep learning water temperature predictions: 3c All lakes historical inputs

This dataset includes model inputs that describe weather conditions for the 68 lakes included in this study. Weather data comes from gridded estimates (Mitchell et al. 2004). There are two comma-separated files, one for weather data (one row per model timestep) and one for ice-flags, which are used by the process-guided deep learning model to determine whether to apply the energy conservation constraint (the constraint is not applied when the lake is presumed to be ice-covered). The ice-cover flag is a modeled output and therefore not a true measurement (see "Predictions" and "pb0" model type for the source of this prediction). This dataset is part of a larger data release of lake temperature model inputs and outputs for 68 lakes in the U.S. states of Minnesota and Wisconsin (http://dx.doi.org/10.5066/P9AQPIVD).

Tags: biota, climate-change, deep-learning, environment, hybrid-modeling, inlandwaters, machine-learning, minnesota, mn, modeling, reservoirs, temperate-lakes, temperature, thermal-profiles, united-states, us, usgs-5d98e0a3e4b0c4f70d1186ee, water, wi, wisconsin
Organization: Department of the Interior
Aquatic community and environmental data for 14 rivers and streams in the Milwaukee Metropolitan Sewerage District Planning Area, 2004-13.

In 2004, 2007, 2010, and 2013, the U.S. Geological Survey sampled benthic algae and invertebrates, and fish to assess the condition of the aquatic communities and water quality in 14 wadable streams near Milwaukee, Wisconsin. Additional community sampling was also done at a subset of three sites in 2011 and 2012 to assess temporal variation. Selected environmental (physical and chemical) data in the streams were collected to evaluate potential relations to the biota and the ecological health of the streams. Physical and chemical data included land-use/land cover; streamflow from USGS gages (except at two creeks that were not gaged); stream habitat; microhabitat at invertebrate collection points (depth, velocity, dominant substrate, embeddedness); water quality (except at two creeks that were not gaged); field measurements of specific conductance and light attenuation; and benthic chlorophyll a, pheophytin, and ash-free dry biomass.

Tags: algae, aquatic-community, biota, environmental-stressors, fish, invertebrates, milwaukee, river, southeastern-wisconsin, stream, usgs-5d97a332e4b0c4f70d117fb4
Organization: Department of the Interior
Hurricane Isaias Overwash Extents

The National Assessment of Coastal Change Hazards project at the U.S. Geological Survey (USGS) exists to understand and predict storm impacts to our nation's coastlines. This geospatial dataset defines the alongshore extent of overwash sediments deposited along the coast of the Carolinas and attributed to coastal processes during [Atlantic Basin] Hurricane Isaias, which made landfall in the U.S. on August 4, 2020.

Tags: cmhrp, coastal-and-marine-hazards-and-resources-program, coastal-processes, environment, geoscientificinformation, hazards, marine-geology, ocean-sciences, oceans, sand-deposits, sedimentation, spcmsc, st-petersburg-coastal-and-marine-science-center, state-of-north-carolina, state-of-south-carolina, u-s-geological-survey, usgs, usgs-5d97664f-9024-4c51-9417-5785833d3b99
Organization: Department of the Interior
GIS Features of the Transboundary Geospatial Fabric (TGF)

The Transboundary Geospatial Fabric (TGF) is a dataset of spatial modeling units consistent with the Geospatial Fabric for National Hydrologic Modeling (abbreviated within this document as GFv1, Viger and Bock, 2014). These features were derived from National Hydrography Dataset Plus High Resolution data (NHDPlus HR, U.S. Geological Survey [USGS], 2018) in the following conterminous United States (CONUS) - Canada transboundary four-digit Hydrologic Units (HUC4): 0101, 0105, 0108, 0901, 0902, 0903, 0904, 1005, 1006, 1701, 1702, and 1711. The data described here include the following vector feature classes: points of interest (POIs), a stream network (nsegment), major waterbodies (waterbodies), and hydrologic response units (nhru).  These feature classes are contained within the Environmental Systems Research Institute (ESRI) geodatabase format (TGF.gdb).

Tags: canada, geographic-information-systems, geoscientificinformation, hydrologic-modeling, hydrologic-response-unit, inlandwaters, points-of-interest, routing-network, united-states, usgs-5d967365e4b0c4f70d113923
Organization: Department of the Interior
Evaluation of an acoustic fish deterrent system in shallow water application at the Emiquon Preserve, Lewistown, IL Data

This dataset assesses the responses of native (largemouth bass Micropterus salmoide and bluegill Lepomis macrochirus) and invasive (silver carp Hypophthalmichthys. Molitrix) fishes to an acoustic stimulus (playback of a 100 hp boat motor. Fish were collected from the Illinois River and Emiquon Preserve and implanted with a Passive Integrated Transponder (PIT) tag. Fish movement was monitored using PIT antennas installed in a water control structure (WCS) that connects the Emiquon Preserve to the Illinois River.

Tags: acoustic-deterrent, biota, emiquon-preserve, emiquon-preserve-il, illinois-river, lewistown-il, silver-carp, underwaterssound, usgs-5d964576e4b0c4f70d110f37
Organization: Department of the Interior
Composite Burn Index (CBI) Data for the Conterminous US, Collected Between 1996 and 2018

These data provide on the ground estimates of burn severity as estimated by the Composite Burn Index (CBI).  Data were collected between 1996 and 2018 for fires that burned during this time period.  Landsat imagery was used to develop regression relationships between the Normalized Burn Ratio (NBR) and differenced NBR (dNBR).

Tags: biota, burn-severity, fire-damage, fires, location, remote-sensing, usgs-5d963705e4b0c4f70d110ee6
Organization: Department of the Interior
Insect catch rates and angler success data during Bug Flows at Glen Canyon Dam, 2012-2018

These data were compiled to evaluate the effects of low steady weekend flows on emergent aquatic insects during the first year of experimental Bug Flows below Glen Canyon Dam (2018) and recreation in Glen Canyon in the second year of Bug Flows (2019). Bug Flows are experimental flows that were released from Glen Canyon Dam in 2018 and 2019. The flows consist of low steady flows on weekends and have the goal of increasing aquatic insect production. These data were compiled for an outreach article providing Citizen Scientists with an update on ongoing research evaluating the effects of Bug Flows. Midge and caddisfly data were collected by Citizen Scientists using light traps. Angler data were collected under a paired sampling design wherein each angler fished both Friday and Saturday and/or Sunday and Monday in June and August of 2019. While this data release is only a subset of ongoing data collection and analysis, it is important to provide outreach and progress updates to community partners engaged in Citizen Science powered research.

Tags: abundance-data, aquatic-ecosystems, arizona, biogeography, biota, catch-rates, citizen-science, colorado-river, distribution-of-species, ecological-distribution, ecology, glen-canyon-dam, grand-canyon, hydrology, hydropsyche, insects, light-traps, measurements, morphology-biological, net-spinning-caddisflies, relative-abundance, species-distribution, usgs-5d962e20e4b0c4f70d110ece, water-temperature
Organization: Department of the Interior
Simulated eDNA Occurrence data and Stan summaries of data

Resource managers conduct landscape-level monitoring using environmental DNA (eDNA). These managers must contend with imperfect detection in samples and sub-samples (i.e., molecular analyses). This imperfect detection impacts their ability to both detect species and estimate occurrence. Although occurrence (synonymously occupancy) models can estimate these probabilities, most models and guidance for their application do not consider three levels. This simulated dataset assumes sites are occupied (probably psi =1, Z = 1 ) and simulates sample (probability theta, A = 0,1) and subsample (probability p, Y = 0, 1) occurrence probabilies and detections (1)/non-detections (0).

Tags: biota, environmental-dna, numerical-modeling, usgs-5d96239be4b0c4f70d110ebe
Organization: Department of the Interior
USGS National and Global Oil and Gas Assessment Project - Piceance and Uinta Basins, Mesaverde Group Tight Gas Assessment Unit Boundaries and Assessment Input Data Forms

This data release contains the boundaries of assessment of undiscovered continuous tight-gas resources in the Mesaverde Group and Wasatch Formation, Uinta-Piceance Province, Utah and Colorado.  The Assessment Unit is the fundamental unit used in the National Assessment Project for the assessment of undiscovered oil and gas resources.  The Assessment Unit is defined within the context of the higher-level Total Petroleum System.  The Assessment Unit is shown herein as a geographic boundary interpreted, defined, and mapped by the geologist responsible for the province and incorporates a set of known or postulated oil and (or) gas accumulations sharing similar geologic, geographic, and temporal properties within the Total Petroleum System, such as source rock, timing, migration pathways, trapping mechanism, and hydrocarbon type.  The Assessment Unit boundary is defined geologically as the limits of the geologic elements that define the Assessment Unit, such as limits of reservoir rock, geologic structures, source rock, and seal lithologies.  The only exceptions to this are Assessment Units that border the Federal-State water boundary.  In these cases, the Federal-State water boundary forms part of the Assessment Unit boundary.  Methodology of assessments are documented in USGS Data Series 547 for continuous assessments (https://pubs.usgs.gov/ds/547) and USGS DDS69-D, Chapter 21 for conventional assessments (https://pubs.usgs.gov/dds/dds-069/dds-069-d/REPORTS/69_D_CH_21.pdf).  See supplemental information for a detailed list of files included this data release.

Tags: assessment-unit, continuous-assessment-unit, earth-science, energy-resources, geology, geoscientificinformation, national-assessment-of-oil-and-gas, natural-gas, natural-gas-resources, natural-resources, noga2000, oil, oil-resources, oilgas, petroleum, piceance-mesaverde-tight-gas, resource-assessment, state-of-colorado, state-of-utah, u-s-a, u-s-geological-survey, uinta-mesaverde-tight-gas, uinta-piceance-basin-province, unconventional-assessment-unit, united-states, united-states-of-america, usgs, usgs-5d961fd5e4b0c4f70d110e3c, usgs-world-energy-region-5
Organization: Department of the Interior
Bed-Sediment Results for Currituck Sound, North Carolina, 2011-17

The U.S. Geological Survey, in cooperation with the North Carolina Turnpike Authority, conducted a study to establish baseline water-quality conditions and bed-sediment chemistry in Currituck Sound, North Carolina, prior to construction of the Mid-Currituck Bridge. This Data Release contains the associated data described in the Open-File Report, “Characterization of Water-Quality and Bed-Sediment Conditions in Currituck Sound, North Carolina, Prior to the Mid-Currituck Bridge Construction, 2011-18”. These datasets contain information on analytical constituents measured in samples, surface-water environmental and quality-assurance sample results, bed-sediment environmental and quality-assurance sample results, phytoplankton taxonomy data, and water-velocity measurement results. Data were collected from August 2011 to January 2018 at five sites distributed along the planned alignment of the Mid-Currituck Bridge in Currituck Sound, North Carolina.

Tags: bed-sediment, currituck-county, inorganic-constituents, north-carolina, organic-compounds, usgs-5d961289e4b0c4f70d110e1e
Organization: Department of the Interior
Benthic macroinvertebrates abundance data for the study of urbanization effects in the Delaware Water Gap National Recreation Area, (2006)

This database contains aquatic benthic macroinvertebrate abundance data derived from samples collected from 33 75-meter stream site locations within the Delaware Water Gap National Recreation area in September of 2006. The database contains two separate table files (i.e., entities) in csv format: 1) Macroinvertebrate site abundance data and 2) site location data. For macroinvertebrate data, six samples were collected within 2-3 riffle areas within each site location with Portable Invertebrate Box Samplers (0.1-m2 sample area, 350 micron mesh collecting nets). Where possible, organisms were identified to the genus taxonomic level using a stereoscope except for organisms of the family Chironomidae and class Oliogochaeta, which were mounted on slides and identified with compound microscopes. For each site, data from six samples compiled into a single site abundance value for each taxon. Site location data consists of UTM coordinates (NAD 1983, UTM zone 18N) for the 33 sample sites.

Tags: benthic-macroinvertebrates, headwater-streams, usgs-5d960fc6e4b0c4f70d110e18
Organization: Department of the Interior