Data Releases
The data collected and the techniques used by USGS scientists should conform to or reference national and international standards and protocols if they exist and when they are relevant and appropriate. For datasets of a given type, and if national or international metadata standards exist, the data are indexed with metadata that facilitates access and integration.
Filter Total Items: 16380
Deep learning classification of manganese and iron mines and prospects in the Lewisburg 30 x 60 minute quadrangle Deep learning classification of manganese and iron mines and prospects in the Lewisburg 30 x 60 minute quadrangle
Manganese is a designated critical mineral, being industrially utilized for producing steel and batteries, including in the production of electric vehicles (Rozelle and others, 2021). The central Appalachian Valley and Ridge hosts hundreds of manganese and iron oxide mines that served steel production until their abandonment in the mid-twentieth century (Lesure, 1957; Pegau, 1958). Many...
Mercury Concentrations and Light Stable Isotope Values for Invasive Black and White Tegus from the Greater Everglades, 2022-2024 Mercury Concentrations and Light Stable Isotope Values for Invasive Black and White Tegus from the Greater Everglades, 2022-2024
This dataset details mercury (Hg) concentrations and carbon, nitrogen, and sulfur isotopes for Black and White tegus (Salvator merianae) collected in and around Everglades National Park between 2022 and 2024. Tegus (n = 115) were collected from 54 sites. Mercury in tegu muscle tissue ranged from 4.1 to 1200 ng g-1. Additional matrices such as livers and blood were measured on a subset of...
Mercury Concentrations in Burmese Pythons Across the Greater Everglades Region in Florida from 2001 to 2022 Mercury Concentrations in Burmese Pythons Across the Greater Everglades Region in Florida from 2001 to 2022
Burmese Pythons are an invasive reptilian species that has spread throughout southern Florida. Mercury (Hg) concentration in python tail muscles were examined across the Great Everglades region in two periods, 2001 - 2011 and 2014 - 2019. The python samples collected spanned a large range of habitats, including wetland, forested, and urban areas. In 2022 tissues from the offspring six...
USGS National and Global Oil and Gas Assessment Project—Provinces of Mexico, Belize, and Guatemala—Assessment Unit Boundaries, Assessment Input Data, and Fact Sheet Data Tables USGS National and Global Oil and Gas Assessment Project—Provinces of Mexico, Belize, and Guatemala—Assessment Unit Boundaries, Assessment Input Data, and Fact Sheet Data Tables
This data release contains the boundaries of assessment units, assessment input data, and resulting fact sheet data tables for the assessment of undiscovered conventional oil and gas resources in the provinces of Mexico, Belize, and Guatemala. The assessment unit is the fundamental unit used in the National and Global Oil and Gas Assessment Project for the assessment of undiscovered oil...
Oceanographic and hydrographic monitoring data of a shallow-water placement of dredged sediment in South San Francisco Bay, California, 2023-2025 Oceanographic and hydrographic monitoring data of a shallow-water placement of dredged sediment in South San Francisco Bay, California, 2023-2025
The U.S. Geological Survey Pacific Coastal and Marine Science Center collected oceanographic and hydrographic monitoring data for a pilot project to place dredged sediment in bay shallows to nourish marshes conducted by the US Army Corps of Engineers, San Francisco District. Dredged material was placed in the shallows of South San Francisco Bay during December 2023. Monitoring spanned...
Daily predictions of water temperature for streams across the contiguous United States (1979-2021) Daily predictions of water temperature for streams across the contiguous United States (1979-2021)
This model application data release provides the data processing and model code used to generate predictions of daily stream water temperature across the contiguous United States from 1979-2021. We used a recurrent graph convolutional network (RGCN) algorithm to make daily stream temperature predictions. Stream water temperature observations, along with forcing data consisting of daily