Data

Airborne electromagnetic (AEM) and magnetic survey data were collected during July and August 2022 over a distance of 3,588.5 line kilometers covering Delaware Bay and surrounding regipons in New Jersey and Delaware. Data were collected as part of the USGS Delaware River Basin Next Generation Water Observing Systems (NGWOS) project to improve understanding of groundwater salinity distributions nea

The Alaska Geochemical Database Version 4.0 (AGDB4) contains geochemical data compilations in which each geologic material sample has one best value determination for each analyzed species, greatly improving efficiency of use. The relational database includes historical geochemical data archived in the USGS National Geochemical Database (NGDB), the Atomic Energy Commission National Uranium Resourc

The U.S. Geological Survey collected ground gravity data as part of a helicopter reconnaissance campaign of the Democrat Creek alkaline complex and Deer Peak quadrangle in the Wet Mountains, Colorado. A total of 60 measurements were collected using a LaCoste and Romberg gravity meter. High accuracy geographic coordinates and elevations were collected using a survey grade Leica GS16 differential GP

This dataset accompanies planned publication titled "The Far-Field imprint of the LPIA, its demise, and the onset of a dust-house climate across the Eastern Shelf of the Permian Basin". Zircon ages presented in this dataset are from rocks collected across the eastern margin of the Permian Basin, Texas. The U-Pb zircon ages are used to investigate changes in provenance in this region as a result of

Geochemical data include major, minor and trace element results for 42 alkaline silicate igneous rock samples. Samples were collected from natural exposures/outcrops during field work in the Central Montana Alkaline Province (CMAP) during the summer of 2022. All samples were analyzed by the U.S. Geological Survey contract laboratory, SGS Labs. Major, minor, and trace elements were determined via w

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

This dataset is a compilation of samples collected from draining mine adits, including water and mineral precipitates, from several mines in California and Colorado. The Golinsky, Copper Bluff, and Afterthought Mines (located in northern California) and the Gold King mine (located in southern Colorado) have historically operated to recover metals including copper, lead, zinc, gold, silver and othe