AndreaBozzo/ceres-open-data-index huggingface dataset:
Paired Air and Water Temperature Data for Two Watersheds in the Delaware River Basin

The data release consists of two companion air and water temperature datasets collected as part of the U.S. Geological Survey (USGS) Next Generation Water Observing System (NGWOS) program with data from both the Little Lehigh and White Clay Creek Watersheds in the Delaware River Basin. Data consists of 15-minute temperature data during the 7/2021 – 12/2022 study period for 21 air and 49 water locations (which include 6 continuous monitoring USGS streamgages) in the Little Lehigh Creek watershed and 8/2021 – 1/2023 for 28 air and 36 surface water locations (including 6 continuous monitoring USGS streamgages) in the White Clay Creek watershed. Datalogger installation locations for surface water locations were targeted for the middle of the channel in the main flow of both streams. Quality assurance and quality control measurements were collected prior to logger deployments and periodically, when possible, during deployment. Air and temperature datasets collected at USGS streamgages are available in this data release and not published through the USGS National Water Information System (NWIS).

Tags: air-temperature, continuous-data, delaware-river-basin, environment, pennsylvania, surface-water, usgs-655b89edd34ee4b6e05cbcce, water-quality, water-temperature
Organization: Department of the Interior
Video observations of Common Terns usurping and brooding Least Tern chicks

These videos show a pair of common terns usurping a least tern nest with chicks. These data support a paired USGS authored manuscript.

Tags: biota, chesapeake-bay, common-tern, least-tern, poplar-island, usgs-655b72dad34ee4b6e05cbc7b, usurpation
Organization: Department of the Interior
Kauaʻi Rapid ʻŌhiʻa death (ROD) Trapped Ambrosia Beetles

These data include bark and ambrosia beetle (Coleoptera: Curculionidae) species collected in cross-vane panel traps (CVPT) baited with a 1:1 methanol:ethanol lure in Northeastern ʻōhiʻa lehua (Metrosideros polymorpha) dominant forests of Kauaʻi, Hawaiʻi in 2021.

Tags: ambrosia-beetle, biota, ceratocystis, frass, hawaii, ohia, rapid-ohia-death, usgs-65580af0d34ee4b6e05c6435
Organization: Department of the Interior
Distribution of Surficial Sediments of NOAA H11310 Sidescan Sonar Mosaic in Central Narragansett Bay (H11310SEDS.SHP)

The United States Geological Survey (USGS) is working cooperatively with the National Oceanic and Atmospheric Association (NOAA) to interpret the surficial geology in estuaries along the coast of the northeastern United States. The purpose of our present study is to interpret the distributions of surficial sediments and sedimentary environments in an area of Narragansett Bay using sidescan sonar imagery, high-resolution bathymetry, and sediment data. The mosaic presented herein covers an area of the sea floor in central Narragansett Bay. The mosaic and their interpretations (represented in part by this data layer) serve many purposes, including: (1) defining the geological variability of the sea floor, which is one of the primary controls of benthic habitat diversity; (2) improving our understanding of the processes that control the distribution and transport of bottom sediments and the distribution of benthic habitats and associated infaunal community structures; and (3) providing a detailed framework for future research, monitoring, and management activities. The sidescan sonar mosaics also serve as base maps for subsequent sedimentological, geochemical, and biological observations, because precise information on environmental setting is important for selection of sampling sites and for accurate interpretation of point measurements.

Tags: atlantic-ocean, clay, cmgp, coastal-and-marine-geology-program, geoscientificinformation, geospatial-datasets, gravel, holocene, interpretation, marine-geology, mud, narragansett-bay, national-oceanic-and-atmospheric-administration, noaa, noaa-ship-rude, north-america, north-atlantic-ocean, northeast-united-states, oceans, ofr-2006-1199, open-file-report-2006-1199, polygon-shapefile, quaternary, rhode-island, sand, scientific-interpretation, sea-floor-characteristics, sidescan-sonar-interpretation, silt, surficial-sediments, u-s-east-coast, u-s-geological-survey, united-states, usgs, usgs-65570880-46de-4fd5-81eb-8030b1575e8a, whsc, woods-hole-science-center
Organization: Department of the Interior
Bathymetric and Topographic Surveys at Lucky Peak Lake Intake Structures, Boise County, Idaho, 2023

In October 2023, the U.S. Geological Survey Idaho Water Science Center (IDWSC), in cooperation with Lucky Peak Power Plant Project (LPPPP), completed bathymetric and topographic surveys at two dam intake structures using multibeam bathymetry and boat-mounted Light Detection and Ranging (LiDAR). Dam operators indicated a possibility that sediment aggradation was occurring near the intake structures that allow water to pass through the dam. The bathymetric and topographic data generally include complete coverage near the intake structures and banklines near Lucky Peak Dam.

Tags: bathymetry, boise-river, deposition, elevation, geomorphology, hydrographic-dataset, hydrology, hypack, hysweep, id, idaho, inlandwaters, lucky-peak-lake, multibeam-sonar, scour, topography, usa, usgs, usgs-65569bd7d34ee4b6e05c513c
Organization: Department of the Interior
2022 Organic Matter Research Lab Sacramento, California Vectorized Fluorescence Data

The U.S. Geological Survey (USGS) California Water Science Center (CAWSC) Organic Matter Research Laboratory (OMRL) provides laboratory services and support to regional and national projects in the analysis of organic matter using the latest methods in absorbance and fluorescence spectroscopy. Optical measurements such as absorbance and fluorescence are used to gain insight into dissolved organic matter (DOM) composition, and can also serve as proxies for more expensive and difficult to obtain measurements. These techniques are relatively rapid and inexpensive and allow for the comprehensive tracking of DOM dynamics in aquatic ecosystems ranging from rivers and lakes to estuaries to open marine systems. 
Laboratory fluorescence measurements collected on the Aqualog can provide validation or verification of field-based instrument fluorescence measurements where the sensor arrays are encompassed by the full Aqualog array (Booth and others, 2023). This approach may be superior to the other correction approaches where interferences are large, especially in cases where the field sensor measurements constitute less than 10% of the fully corrected value. For projects that already collect discrete samples during field sensor maintenance visits, the cost and effort is minimal for the data quality benefit.
Data presented here were analyzed by the U.S Geological Survey California Water Science Center Organic Matter Research Lab, Sacramento CA. This release contains vectorized fluorescence data measured on the Aqualog ® fluorometer January-December 2022.

Tags: aqualog, california, california-water-science-center, climatologymeteorologyatmosphere, dissolved-organic-matter, fdom, fluorescence, hydrology, organic-matter-research-laboratory, sacramento, usgs-65566177d34ee4b6e05c4b38
Organization: Department of the Interior
Attribution of fish sampling data to NHDPlus HR catchments within the Chesapeake Bay Watershed

This data release links fish survey data from a suite of programs in the Chesapeake Bay watershed to the NHDPlus High Resolution Region 02 networks, hereafter referred to as NHDPlusHR. The data set contains site name, survey program, coordinates of sample, ancillary information such as sample date and site location information where available, and HR Permanent Identifier. It also includes a confidence classification category for each of NHD assignment based on a set of pre-determined rules. In total there were 15 confidence categories ranging from high confidence to low confidence. We caution the use of sampling points which were given anything other than "high" confidence in their assignment to a given NHD catchment/flowline to avoid spurious/inappropriate attribution of geospatial data to fish data samples represented herein and refer the potential user to the Confidence Dictionary.csv which describes the criteria for each confidence category.

Tags: aquatic-biology, aquatic-ecosystems, biota, district-of-columbia-national-district, ecology, freshwater-ecosystems, hydrology, ichthyology, maryland-state, new-york-state, pennsylvania-state, usgs-655cdbbcd34ee4b6e05cc4fb, virginia-state, west-virginia-state
Organization: Department of the Interior
Bottom Trawl Catch Alewife Densities and Ages in Lakes Michigan and Huron

This data release provides catch-per-unit-effort (CPUE) data by age-class for alewife (Alosa pseudoharengus) based on bottom trawl surveys from Lake Michigan (1973-2022) or Lake Huron (1976-2004). These data are associated with a study that sought to evaluate whether alewife populations across the Great Lakes are synchronous in their time series.

Tags: alewife, alosa-pseudohargengus, biota, bottom-trawl, fish, freshwater-ecosystems, inlandwaters, lake-huron, lake-michigan, population-dynamics, usgs-65563793d34ee4b6e05c474d
Organization: Department of the Interior
LANDFIRE 2022 40 Scott and Burgan Fire Behavior Fuel Models (FBFM40) Puerto Rico US Virgin Islands

LANDFIRE's (LF) 2022 40 Scott and Burgan Fire Behavior Fuel Models (FBFM40) product represents distinct distributions of fuel loadings found among surface fuel components (live and dead), size classes, and fuel types (Scott &amp; Burgan 2005). The fuel models are described by the most common fire carrying fuel type (grass, brush, timber, or slash), loading and surface area-to-volume ratio by size class and component, fuel bed depth, and moisture of extinction. FBFM40 contains more fuel models for every fuel type than 13 Anderson Fire Behavior Fuel Models (FBFM13), and the number of fuel models representing relatively high dead fuel moisture content is increased. In FBFM40 fuel models with an herbaceous component are dynamic, to simulate curing, rather than remaining constant. To create this product, expert rulesets were developed to understand how different types of disturbance would change pre-disturbance fuel models to post disturbance fuels, based on the severity and time since disturbance. These rulesets are represented in the LF Total Fuel Change Tool and Database for both disturbed and non-disturbed areas. In the LF 2022 update, non-disturbed fuels are the same as LF 2016 Remap for natural vegetation. 
To designate disturbed areas where FBFM40 is modified, the aggregated Annual Disturbance products from 2013 to 2022 in the Fuel Disturbance (FDist) product are used. All existing disturbances between 2013-2022 are represented in the LF 2022 update, and the products are intended to be used in 2023 (the year of release). The “capable” year terminology used in LF 2020 and LF 2016 Remap is no longer specified, due to reduction in latency from when a disturbance occurs to the release date of fuel products accounting for that disturbance. However, users should still consider adjusting fuel layers for disturbances that occurred after the end of the 2022 fiscal year (after October 1st, 2022) when using the LF 2022 fuel products. Because those changes would not be accounted for. Learn more about LF 2022 at https://landfire.gov/lf_230.php .

Tags: biota, fbfm, fbfm40, fire-behavior-fuel-model-40, fires, geographic-information-systems, geospatial-datasets, hazard-preparedness, ia, image-collections, imagerybasemapsearthcover, insular-areas, landfire-2022, lf-2022, oconus, puerto-rico, raster-digital-data, remote-sensing, scott-and-burgan-fire-behavior-fuel-model, u-s-forest-service-usfs, u-s-geological-survey-usgs, united-states, us, us-virgin-islands, usgs-655549c3d34ee4b6e05c4686
Organization: Department of the Interior
LANDFIRE 2022 13 Anderson Fire Behavior Fuel Models (FBFM13) Puerto Rico US Virgin Islands

LANDFIRE's (LF) 2022 13 Anderson Fire Behavior Fuel Models (FBFM13) product represents distinct distributions of fuel loadings found among surface fuel components (live and dead), size classes, and fuel types (Anderson 1982). The fuel models are described by the most common fire carrying fuel type (grass, brush, timber, or slash), loading and surface area-to-volume ratio by size class and component, fuel bed depth, and moisture of extinction. LF FBFM13 can be used for fire spread related characteristic models. To create this product, expert rulesets were developed to understand how different types of disturbance would change pre-disturbance fuel models to post disturbance fuels, based on the severity and time since disturbance. These rulesets are represented in the LF Total Fuel Change Tool and Database. In the LF 2022 update, non-disturbed fuels are the same as LF 2016 Remap for natural vegetation. 
To designate disturbed areas where FBFM13 is modified, the aggregated Annual Disturbance products from 2013 to 2022 in the Fuel Disturbance (FDist) product are used. All existing disturbances between 2013-2022 are represented in the LF 2022 update, and the products are intended to be used in 2023 (the year of release). The “capable” year terminology used in LF 2020 and LF 2016 Remap is no longer specified, due to reduction in latency from when a disturbance occurs to the release date of fuel products accounting for that disturbance. However, users should still consider adjusting fuel layers for disturbances that occurred after the end of the 2022 fiscal year (after October 1st, 2022) when using the LF 2022 fuel products. Because those changes would not be accounted for. Learn more about LF 2022 at https://landfire.gov/lf_230.php .

Tags: anderson-fire-behavior-fuel-model, biota, fbfm, fbfm13, fire-behavior-fuel-model-13, fires, geographic-information-systems, geospatial-datasets, hazard-preparedness, ia, image-collections, imagerybasemapsearthcover, insular-areas, landfire-2022, lf-2022, oconus, puerto-rico, raster-digital-data, remote-sensing, u-s-forest-service-usfs, u-s-geological-survey-usgs, united-states, us, us-virgin-islands, usgs-65554945d34ee4b6e05c4680
Organization: Department of the Interior
LANDFIRE 2022 Fuel Disturbance (FDist) Puerto Rico US Virgin Islands

LANDFIRE (LF) disturbance products are developed to provide temporal and spatial information related to landscape change. LF 2022 Fuel Disturbance (FDist) uses the latest Annual Disturbance products from the effective disturbance years of 2013 to 2022. FDist is created from LF 2022 Historical Disturbance (HDist) which in turn aggregates the Annual Disturbance products. FDist groups similar disturbance types, severities and time since disturbance categories which represent disturbance scenarios within the fuel environment. FDist is used in conjunction with Fuel Vegetation Type (FVT), Cover (FVC), and Height (FVH) to calculate Canopy Cover (CC), Canopy Height (CH), Canopy Bulk Density (CBD), Canopy Base Height (CBH), Fire Behavior Fuel Models 13 Anderson (FBFM13) and 40 Scott and Burgan (FBFM40). 
FDist is developed using the aggregated Annual Disturbance products from 2013 to 2022. All existing disturbances between 2013-2022 are represented in the LF 2022 update, and the products are intended to be used in 2023 (the year of release). The “capable” year terminology used in LF 2020 and LF 2016 Remap is no longer specified, due to reduction in latency from when a disturbance occurs to the release date of fuel products accounting for that disturbance. However, users should still consider adjusting fuel layers for disturbances that occurred after the end of the 2022 fiscal year (after October 1st, 2022) when using the LF 2022 fuel products. Because those changes would not be accounted for. Learn more about LF 2022 at https://landfire.gov/lf_230.php .

Tags: biota, disturbance, fdist, fires, fuel-disturbance, geographic-information-systems, geospatial-datasets, hazard-preparedness, ia, image-collections, imagerybasemapsearthcover, insular-areas, landfire-2022, lf-2022, oconus, puerto-rico, raster-digital-data, remote-sensing, u-s-forest-service-usfs, u-s-geological-survey-usgs, united-states, us, us-virgin-islands, usgs-6555488bd34ee4b6e05c467a
Organization: Department of the Interior
LANDFIRE 2022 Fuel Vegetation Height (FVH) Puerto Rico US Virgin Islands

LANDFIRE (LF) 2022 Fuel Vegetation Height (FVH) represents the LF Existing Vegetation Height (EVH) product, modified to represent pre-disturbance EVH in areas where disturbances have occurred over the past 10 years. EVH is mapped as continuous estimates of canopy height for tree, shrub, and herbaceous lifeforms with a potential range of 0-100m. Continuous EVH values are binned to align with fuel model assignments when creating FVH. FVH is an input for fuel transitions related to disturbance. Fuel products in LF 2022 were created with LF 2016 Remap vegetation in non-disturbed areas. 
To designate disturbed areas where FVH is modified, the aggregated Annual Disturbance products from 2013 to 2022 in the Fuel Disturbance (FDist) product are used. All existing disturbances between 2013-2022 are represented in the LF 2022 update, and the products are intended to be used in 2023 (the year of release). The “capable” year terminology used in LF 2020 and LF 2016 Remap is no longer specified, due to reduction in latency from when a disturbance occurs to the release date of fuel products accounting for that disturbance. However, users should still consider adjusting fuel layers for disturbances that occurred after the end of the 2022 fiscal year (after October 1st, 2022) when using the LF 2022 fuel products. Because those changes would not be accounted for. Learn more about LF 2022 at https://landfire.gov/lf_230.php .

Tags: biota, evh, existing-vegetation-height, fires, fuel-vegetation-height, fvh, geographic-information-systems, geospatial-datasets, hazard-preparedness, ia, image-collections, imagerybasemapsearthcover, insular-areas, landfire-2022, lf-2022, oconus, puerto-rico, raster-digital-data, remote-sensing, u-s-forest-service-usfs, u-s-geological-survey-usgs, united-states, us, us-virgin-islands, usgs-65554516d34ee4b6e05c465e
Organization: Department of the Interior
LANDFIRE 2022 Existing Vegetation Type (EVT) Puerto Rico US Virgin Islands

LANDFIRE's (LF) 2022 update (LF 2022) Existing Vegetation Type (EVT) represents the current distribution of the terrestrial ecological systems classification developed by NatureServe for the western hemisphere. In this context, a terrestrial ecological system is defined as a group of plant community types that tend to co-occur within landscapes with similar ecological processes, substrates, and/or environmental gradients. EVT also includes ruderal or semi-natural vegetation types within the U.S. National Vegetation Classification [(NVC) https://usnvc.org/]. See the EVT product page (https://www.landfire.gov/evt.php) for more information about ecological systems and NVC classifications.  
EVT is mapped using decision tree models, field data, Landsat imagery, topography, and biophysical gradient data. Decision tree models are developed separately for tree, shrub, and herbaceous lifeforms which are then used to produce a lifeform specific EVT product. These models are generated for each Environmental Protection Agency (EPA) Level III Ecoregion (https://www.epa.gov/eco-research/ecoregions). Riparian, alpine, sparse, and other site-specific EVTs are constrained by predetermined masks. Urban and developed areas are derived from the National Land Cover Database (NLCD), and the latest Microsoft Building Footprint dataset. Agricultural lands originate from the 2022 Cropland Data Layer (CDL) and the 2019 California Statewide Crop Mapping layer. Burnable developed classes are identified from building footprint dataset thresholds. LF 2022 retains circa 2016 EVT labels except where shifts in urban, agriculture, and developed classes occur. While Existing Vegetation Cover (EVC) and Height (EVH) are updated using transition rulesets with ST-Sim to account for disturbances, EVT remains unchanged, therefore EVT lifeform is not synchronized to the EVC/EVH lifeform as in some previous versions. LF uses EVT as an input for LF 2022 Fuel Vegetation Type (FVT).

Tags: evt, existing-vegetation-type, farming, fires, geographic-information-systems, geospatial-datasets, hazard-preparedness, ia, image-collections, imagerybasemapsearthcover, insular-areas, landfire-2022, lf-2022, oconus, puerto-rico, raster-digital-data, remote-sensing, u-s-forest-service-usfs, u-s-geological-survey-usgs, united-states, us, us-virgin-islands, usgs-65554468d34ee4b6e05c4650
Organization: Department of the Interior
LANDFIRE 2022 Forest Canopy Cover (CC) Puerto Rico US Virgin Islands

LANDFIRE's (LF) 2022 Forest Canopy Cover (CC) describes the percent cover of the tree canopy in a stand. CC is a vertical projection of the tree canopy cover onto an imaginary horizontal plane. CC supplies information for fire behavior models to determine the probability of crown fire initiation, provide input in the spotting model, calculate wind reductions, and to calculate fuel moisture conditioning. To create this product, plot level CC values are calculated using the canopy fuel estimation software, Forest Vegetation Simulator (FVS). Pre-disturbance CC and Canopy Height (CH) are used as predictors of disturbed CC using a linear regression equation per Fuel Vegetation Type (FVT), disturbance type/severity, and time since disturbance. CC is used in the calculation of Canopy Bulk Density (CBD) and Canopy Base Height (CBH). In LF 2022, fuel products are created with LF 2016 Remap vegetation in areas that were un-disturbed in the last ten years. 
To designate disturbed areas where CC is modified, the aggregated Annual Disturbance products from 2013 to 2022 in the Fuel Disturbance (FDist) product are used. All existing disturbances between 2013-2022 are represented in the LF 2022 update, and the products are intended to be used in 2023 (the year of release). The “capable” year terminology used in LF 2020 and LF 2016 Remap is no longer specified, due to reduction in latency from when a disturbance occurs to the release date of fuel products accounting for that disturbance. However, users should still consider adjusting fuel layers for disturbances that occurred after the end of the 2022 fiscal year (after October 1st, 2022) when using the LF 2022 fuel products. Because those changes would not be accounted for. Learn more about LF 2022 at https://landfire.gov/lf_230.php .

Tags: biota, canopy-cover, cc, fires, geographic-information-systems, geospatial-datasets, hazard-preparedness, ia, image-collections, imagerybasemapsearthcover, insular-areas, landfire-2022, lf-2022, oconus, puerto-rico, raster-digital-data, remote-sensing, u-s-forest-service-usfs, u-s-geological-survey-usgs, united-states, us, us-virgin-islands, usgs-655542b1d34ee4b6e05c4635
Organization: Department of the Interior