AndreaBozzo/ceres-open-data-index huggingface dataset:
Felsenthal National Wildlife Refuge green-tree reservoir 2001 forest plot measurements

A green-tree reservoir (GTR) is a stand of bottomland hardwoods that is intentionally flooded in the fall and winter to support migrating waterfowl. Bottomland hardwood forest plots in the GTR on Felsenthal National Wildlife Refuge (FNWR) are measured every 5-6 years to monitor tree survival, growth, and mortality. This dataset presents the measurements of all the trees in 54 plots during the year 2001. Parameters measured are species, diameter, vigor class, canopy class, and whether or not the tree is a new recruit in 2001. These parameters are defined in the Entity and Attributes section of this metadata file.

Tags: arkansas, biota, bottomland-hardwoods, environment, felsenthal-national-wildlife-refuge, forest-ecosystems, green-tree-reservoir, greentree-reservoir, long-term-ecological-monitoring, plot-sampling, usgs-5d66d1a2e4b0c4f70cf04406, wetland-ecosystems
Organization: Department of the Interior
Magnetotelluric data from San Pablo Bay, California, station sp06

This dataset consists of 14 magnetotelluric (MT) stations collected in 2015 near San Pablo Bay, California along a east-northeast profile. The U.S. Geological Survey acquired these data understand fault geometry of the Hayward Fault and the Rodgers Creek Fault.

Tags: apparent-resistivity, california, cenozoic, contra-costa-county, earth-magnetic-field, electromagnetic-surveying, geology-minerals-energy-and-geophysics-science-center, geophysics, geoscientificinformation, gmegsc, impedance, magnetotelluric-surveying, magnetotellurics, mesozoic, mineral-resources-program, mrp, mt, phase, san-pablo-bay, time-series, tipper, usgs-5e4601c4e4b0ff554f662cd3
Organization: Department of the Interior
Magnetotelluric data from San Pablo Bay, California, station sp04

This dataset consists of 14 magnetotelluric (MT) stations collected in 2015 near San Pablo Bay, California along a east-northeast profile. The U.S. Geological Survey acquired these data understand fault geometry of the Hayward Fault and the Rodgers Creek Fault.

Tags: apparent-resistivity, california, cenozoic, contra-costa-county, earth-magnetic-field, electromagnetic-surveying, geology-minerals-energy-and-geophysics-science-center, geophysics, geoscientificinformation, gmegsc, impedance, magnetotelluric-surveying, magnetotellurics, mesozoic, mineral-resources-program, mrp, mt, phase, san-pablo-bay, time-series, tipper, usgs-5e460075e4b0ff554f662ccd
Organization: Department of the Interior
Magnetotelluric data from San Pablo Bay, California, station sp03

This dataset consists of 14 magnetotelluric (MT) stations collected in 2015 near San Pablo Bay, California along a east-northeast profile. The U.S. Geological Survey acquired these data understand fault geometry of the Hayward Fault and the Rodgers Creek Fault.

Tags: apparent-resistivity, california, cenozoic, contra-costa-county, earth-magnetic-field, electromagnetic-surveying, geology-minerals-energy-and-geophysics-science-center, geophysics, geoscientificinformation, gmegsc, impedance, magnetotelluric-surveying, magnetotellurics, mesozoic, mineral-resources-program, mrp, mt, phase, san-pablo-bay, time-series, tipper, usgs-5e45ffd0e4b0ff554f662cca
Organization: Department of the Interior
Magnetotelluric data from San Pablo Bay, California

This dataset consists of 14 magnetotelluric (MT) stations collected in 2015 near San Pablo Bay, California along a east-northeast profile. The U.S. Geological Survey acquired these data understand fault geometry of the Hayward Fault and the Rodgers Creek Fault.

Tags: apparent-resistivity, california, cenozoic, contra-costa-county, earth-magnetic-field, electromagnetic-surveying, geology-minerals-energy-and-geophysics-science-center, geophysics, geoscientificinformation, gmegsc, impedance, magnetotelluric-surveying, magnetotellurics, mesozoic, mt, natural-hazards-program, nhp, phase, san-pablo-bay, time-series, tipper, usgs-5e45fc5ae4b0ff554f662cbe
Organization: Department of the Interior
Discharge, nutrient, and suspended sediment data for selected streams in the Lake Tahoe watershed

A time series of nutrient and mean daily discharge data were used to create models of daily concentration and loads for selected streams of the Lake Tahoe watershed.  A total of 15 sites have records ranging from as early as 1972 to 2017.  Nutrients in the data set include nitrate, ammonium, Kjeldahl Nitrogen, orthophosphate, and total phosphorus. Total suspended sediment concentrations are also included.  Discharge data are included as mean daily values in cubic meters per second. The data were used to produce daily and annual models of concentrations and loads and associated daily and annual loads of these constituents. Trends in these constituents were also calculated.   The U.S. Geological Survey model, Weighted Regressions on Time Discharge and Season (WRTDS) was used for these calculations. The data set and associated models of concentrations, loads, and trends are described in a companion journal article (Trends in nitrogen, phosphorus, and sediment concentrations and loads in streams draining to Lake Tahoe, California, Nevada, U.S.A.) published in Science of the Total Environment (https://doi.org/10.1016/j.scitotenv.2020.141815).

Tags: nutrient-content, stream-water, usgs-5e4483a3e4b0ff554f642171, water-quality
Organization: Department of the Interior
Lidar data for natural release experiment at the USGS Debris Flow Flume 17 May 2017

Lidar data was collected on 17 May 2017 at the USGS debris-flow flume to monitor the movement of a constructed landslide experiment.  A static prism of sediment was emplaced behind a retaining wall at the top of the flume.  Water was added via sprinklers to the surface and also via pipes to the subsurface, in order to saturate the sediment mass.  The sediment mass eventually failed as a debris flow and moved down the flume.  Lidar data was collected from a Riegl VZ-400 terrestrial laser scanner to capture the mass failure.  The lidar unit was modified to scan a narrow swath (approximately 1 mm) along the full profile of the constructed sediment mass.   The lidar scan rate was set to re-scan every 0.017 s or at a rate of 60 Hz.  The data contained herein ecapsulates entire lidar point cloud from the time before prior to movement through full failure of the sediment mass.  The points are organized in rows.  The columns are: ['xM', 'yM', 'zM', 'rangeM', 'thetaDEG', 'phiDEG', 'riegl_ref', 'timestampSEC', 'Line'] .  The 'xM', 'yM', 'zM' values are the x, y, and z real world UTM coordinates with units of meters. The 'rangeM' is the distance of each point from the scanner with units of meters.  The vertical angle of the lidar scanner is shown as 'thetaDEG' with units of degrees.  Similarly, the horizontal angle of the lidar scanner is shown as 'phiDEG' with units of degrees. The 'riegl_ref' represents reflectance value computed from the intensity. The timestamp is the number of seconds since the beginning of the scan.  The 'Line' column represents all the points that belong to a single lidar profile swath.

Tags: debris-flow, lidar, usgs-5e4435ece4b0edb47be9cc49
Organization: Department of the Interior
Jonathan Davis Wetland Restoration (BA-20): 2018 land-water classification

The Louisiana State Legislature created the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) in order to conserve, restore, create and enhance Louisiana's coastal wetlands. The wetland restoration plans developed pursuant to these acts specifically require an evaluation of the effectiveness of each coastal wetlands restoration project in achieving long-term solutions to arresting coastal wetlands loss. This data set includes mosaicked aerial photographs for the Jonathan Davis Wetland Restoration (BA-20) project for 2018. This data is used as a basemap land-water classification. It also serves as a visual tool for project managers to help them identify any obvious problems or land loss within their project boundary. To better evaluate the effectiveness of restoration efforts, a land-water classification is performed on specific CWPPRA sites to help assess landscape changes.

Tags: aerial-photography, ba-20, conservation, cwppra, digital-elevation-models, ecosystem-monitoring, geographic-information-systems, gulf-of-mexico, image-collections, image-mosaics, louisiana, louisiana-coastal, remote-sensing, usgs-5e4403b7e4b0edb47be84c52, wetland-ecosystems, wetland-restoration
Organization: Department of the Interior
Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 385903107210800; Muddy Creek above Paonia Reservoir, Colorado

This model archive summary documents the suspended-sediment concentration (SSC) model developed to estimate 15-minute SSC at Muddy Creek above Paonia Reservoir, U.S. Geological Survey (USGS) site number 385903107210800.  The methods used follow USGS guidance as referenced in relevant Office of Surface Water Technical Memorandum (TM) 2016.07 and Office of Water Quality TM 2016.10, and USGS Techniques and Methods, book 3, chap. C5 (Landers and others, 2016). A total of 438 suspended-sediment samples were collected during the calibration period. Forty-one of these samples (22 equal-width-interval [EWI] samples and 19 single-point pump samples) were used in the model calibration dataset. These 41 samples were collected over the range of observed streamflow, Sediment Corrected Backscatter (SCB), and Sediment Attenuation Coefficient (SAC) conditions. Samples used in calibration were plotted on duration curve plots for streamflow from March 2005 to November 2016 (Colorado Division of Water Resources data from 2005 to 2014, and USGS data for 2015–16), and SAC for the period of record. The plots indicate that samples were collected for the observed range of conditions at the site. Suspended-sediment concentrations at this site were computed from a calibrated regression model between SSC and SAC. Streamflow, SCB, dummy variables, and seasonality were also examined as potential variables. An ordinary least squares linear regression model was developed using the ‘stats’ and ‘smwrStats’ packages in R (R Core Team, 2018). Streamflow, SCB, SAC, dummy variable, and seasonality were examined as potential explanatory variables for estimating SSC. A square root transformed SAC was selected as the explanatory variable.

Tags: colorado, gunnison-county, inlandwaters, mathematical-modeling, regression-analysis, sediment-acoustics, sediment-discharge, sediment-transport, stream-discharge, surface-water, suspended-material-water, usgs-5e432f0de4b0edb47be84696, water-sampling
Organization: Department of the Interior
Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 09132095; Anthracite Creek above Mouth near Somerset, Colorado

This model archive summary documents the suspended-sediment concentration (SSC) model developed to estimate 15-minute SSC at Anthracite Creek above Mouth near Somerset, U.S. Geological Survey (USGS) site number 09132095. The methods used follow USGS guidance as referenced in relevant Office of Surface Water Technical Memorandum (TM) 2016.07 and Office of Water Quality TM 2016.10, USGS Techniques and Methods, book 3, chap. C5 (Landers and others, 2016), and USGS Techniques and Methods, book 3, chap. C4 (Rasmussen and others, 2009). A total of 399 suspended-sediment samples were collected during the calibration period (43 cross-section and 356 single-station samples). Forty-one of these samples with associated streamflow and turbidity were used in the model calibration dataset. These 41 samples were collected over the range of observed streamflow and turbidity conditions. Samples used in calibration were plotted on duration curve plots for streamflow from March 25, 2015 to October 31, 2017 and turbidity from March 21, 2015 to October 31, 2017. The plots indicate that samples were collected for the observed range of conditions at the site. Suspended-sediment concentrations at this site were computed from a calibrated regression model between SSC and turbidity. An ordinary least squares linear regression model was developed using the ‘stats’ and ‘smwrStats’ packages in R (R Core Team, 2018). Streamflow, Sediment Corrected Backscatter (SCB), Sediment Attenuation Coefficient (SAC), and turbidity were examined as potential explanatory variables for estimating SSC. A natural log transformed turbidity was selected as the best explanatory variable.

Tags: colorado, gunnison-county, inlandwaters, mathematical-modeling, regression-analysis, sediment-acoustics, sediment-discharge, sediment-transport, stream-discharge, surface-water, suspended-material-water, usgs-5e432ef0e4b0edb47be84693, water-sampling
Organization: Department of the Interior
A national dataset of rasterized building footprints for the U.S.

The Bing Maps team at Microsoft released a U.S.-wide vector building dataset in 2018, which includes over 125 million building footprints for all 50 states in GeoJSON format. This dataset is extracted from aerial images using deep learning object classification methods. Large-extent modelling (e.g., urban morphological analysis or ecosystem assessment models) or accuracy assessment with vector layers is highly challenging in practice. Although vector layers provide accurate geometries, their use in large-extent geospatial analysis comes at a high computational cost. We used High Performance Computing (HPC) to develop an algorithm that calculates six summary values for each cell in a raster representation of each U.S. state: (1) total footprint coverage, (2) number of unique buildings intersecting each cell, (3) number of building centroids falling inside each cell, and area of the (4) average, (5) smallest, and (6) largest area of buildings that intersect each cell. These values are represented as raster layers with 30m cell size covering the 48 conterminous states, to better support incorporation of building footprint data into large-extent modelling.
This Project is funded by NASA’s Biological Diversity and Ecological Forcasting program;  Award # 80NSSC18k0341

Tags: building-footprint, built-environment, conterminous-u-s, density, land-cover, land-use, united-states, usgs-5e432067e4b0edb47be84657
Organization: Department of the Interior
A national dataset of rasterized building footprints for the U.S.

The Bing Maps team at Microsoft released a U.S.-wide vector building dataset in 2018, which includes over 125 million building footprints for all 50 states in GeoJSON format. This dataset is extracted from aerial images using deep learning object classification methods. Large-extent modelling (e.g., urban morphological analysis or ecosystem assessment models) or accuracy assessment with vector layers is highly challenging in practice. Although vector layers provide accurate geometries, their use in large-extent geospatial analysis comes at a high computational cost. We used High Performance Computing (HPC) to develop an algorithm that calculates six summary values for each cell in a raster representation of each U.S. state: (1) total footprint coverage, (2) number of unique buildings intersecting each cell, (3) number of building centroids falling inside each cell, and area of the (4) average, (5) smallest, and (6) largest area of buildings that intersect each cell. These values are represented as raster layers with 30 m cell size covering the 48 conterminous states, to better support incorporation of building footprint data into large-extent modelling. We also identify errors in the original building dataset where buildings are systematically over- or undercounted, providing further guidance for their use in geospatial analysis.
This Project is funded by NASA’s Biological Diversity and Ecological Forcasting program;  Award # 80NSSC18k0341

Tags: building-footprint, built-environment, conterminous-u-s, density, land-cover, land-use, united-states, usgs-5e432002e4b0edb47be84652
Organization: Department of the Interior
Magnetotelluric data from San Pablo Bay, California, station sp15

This dataset consists of 14 magnetotelluric (MT) stations collected in 2015 near San Pablo Bay, California along a east-northeast profile. The U.S. Geological Survey acquired these data understand fault geometry of the Hayward Fault and the Rodgers Creek Fault.

Tags: apparent-resistivity, california, cenozoic, contra-costa-county, earth-magnetic-field, electromagnetic-surveying, geology-minerals-energy-and-geophysics-science-center, geophysics, geoscientificinformation, gmegsc, impedance, magnetotelluric-surveying, magnetotellurics, mesozoic, mineral-resources-program, mrp, mt, phase, san-pablo-bay, time-series, tipper, usgs-5e460645e4b0ff554f662ceb
Organization: Department of the Interior
Tracking disturbance and inundation to identify wetland loss

Global trends in wetland degradation and loss have created an
urgency to monitor wetland extent, as well as track the distribution
and causes of wetland loss. Satellite imagery can be used to monitor
wetlands over time, but few efforts have attempted to distinguish
anthropogenic wetland loss from climate-driven variability in
wetland extent. We present an approach to concurrently track land
cover disturbance and inundation extent across the Mid-Atlantic
region, United States, using the Landsat archive in Google Earth
Engine. Disturbance was identified as a change in greenness, using a
harmonic linear regression approach, or as a change in growing
season brightness. Inundation extent was mapped using a modified
version of the U.S. Geological Survey’s Dynamic Surface Water
Extent (DSWE) algorithm. Annual (2015 to 2018) disturbance averaged
0.32 percent (1095 km2 per year) of the study area per year and was most
common in forested areas. While inundation extent showed substantial
interannual variability, the co-occurrence of disturbance and
declines in inundation extent represented a minority of both change
types, totaling 109 km2 over the four-year period, and 186 km2,
using the National Wetland Inventory dataset in place of the
Landsat-derived inundation extent. When the annual products were
evaluated with permitted wetland and stream fill points, 95 percent of the
fill points were detected, with most found by the disturbance
product (89 percent) and fewer found by the inundation decline product
(25 percent). The results suggest that mapping inundation alone is unlikely
to be adequate to find and track anthropogenic wetland loss.
Alternatively, remotely tracking both disturbance and inundation can
potentially focus efforts to protect, manage, and restore wetlands.

Tags: chesapeake-bay, delaware, delmarva-peninsula, harmonic-regression, landsat, maryland, pennsylvania, permit, surface-water, usgs-5e430b15e4b0edb47be845ce, virginia, washington-d-c, west-virginia, wetland-fill
Organization: Department of the Interior
Digital elevation model (DEM) of the Sacramento River Deep Water Ship Channel (DWSC), Sacramento-San Joaquin Delta, California

This metadata describes a digital elevation model (DEM) created from bathymetric and topographic data collected between 2017 and 2019 in the Sacramento River Deep Water Ship Channel (DWSC), northern Sacramento-San Joaquin Delta, California.
We merged the newly collected bathymetric and topographic data presented in this data release (DOI:10.5066/P9AQSRVH) with 2019 surveys by the California Department of Water Resources (DWR) and 2017 USGS Sacramento Delta Lidar, to produce a seamless digital elevation model of the DWSC at a grid resolution of 1 m.

Tags: altimetry, bathymetry, bathymetry-and-elevation, bathymetry-measurement, cmhrp, coastal-and-marine-hazards-and-resources-program, digital-elevation-models, field-observation, geographic-information-systems, geoscientificinformation, geospatial-datasets, lidar, marine-geophysics, multibeam-sonar, pacific-coastal-and-marine-science-center, pcmsc, sacramento-river, sacramento-river-deep-water-ship-channel, sacramento-san-joaquin-delta, san-joaquin-river, sea-floor-characteristics, seabed, seafloor-topography, state-of-california, topographic-mapping, topography, u-s-geological-survey, usgs, usgs-5e42feace4b0edb47be8458d
Organization: Department of the Interior
Acoustic-backscatter data collected in the Cache Slough Complex and the Sacramento River Deep Water Ship Channel, California, during field activity 2018-684-FA

Acoustic-backscatter data were collected during a 2018 swath survey in the Cache Slough Complex and the Sacramento River Deep Water Ship Channel, California. Data were collected by the U.S. Geological Survey (USGS) during USGS field activity 2018-684-FA, using interferometric bathymetric sidescan sonar systems mounded to the USGS R/V San Lorenzo and the R/V Kelpfly. The backscatter data are provided as GeoTIFF images.

Tags: cache-slough, cache-slough-complex, cmhrp, coastal-and-marine-hazards-and-resources-program, field-observation, geoscientificinformation, geospatial-datasets, habitat, marine-geophysics, multibeam-echo-sounder, multibeam-sonar, pacific-coastal-and-marine-science-center, pcmsc, sacramento-river, sacramento-river-deep-water-ship-channel, sacramento-san-joaquin-delta, san-joaquin-river, sea-floor-acoustic-reflectivity, sea-floor-characteristics, seabed, state-of-california, substrate, u-s-geological-survey, usgs, usgs-5e42fe05e4b0edb47be84586
Organization: Department of the Interior
LCMAP Reference Data Product 1984-2018 land cover and land use attributes aggregate data and metadata (ver. 1.2, November 2021)

This product contains plot location data in a .shp format as well as annual land cover, land use, and change process variables for each reference data plot in a separate .csv table.  The same information available in the.csv file is also provided in a .xlsx format. 
The LCMAP Reference Data Product was utilized for evaluation and validation of the Land Change Monitoring, Assessment, and Projection (LCMAP) land cover and land cover change products. The LCMAP Reference Data Product includes the collection of an independent dataset of 25,000 randomly-distributed 30-meter by 30-meter plots across the conterminous United States (CONUS). This dataset was collected via manual image interpretation to aid in validation of the land cover and land cover change products as well as area estimates. The LCMAP Reference Data Product collected variables related to primary and secondary land use, primary and secondary land cover(s), change processes, and other ancillary variables annually across CONUS from 1984-2018.
First posted - May 1, 2020 (available from author)
Revised - September 21, 2021 (version 1.1)
Revised - November 17, 2021 (version 1.2)

Tags: environment, image-analysis, land-change-monitoring-assessment-and-projection, land-use-and-land-cover, land-use-change, landsat, lcmap, location, time-series-datasets, usgs-5e42e54be4b0edb47be84535
Organization: Department of the Interior