Skip to main content
U.S. flag

An official website of the United States government

Data

Browse real-time data, data releases and more. 

Data Management

Data Management

Data Releases

Data Releases

Real-time Data

Real-time Data

All Data

Filter Total Items: 16713

Historic Water Chemistry Data for Thermal Features, Streams, and Rivers in the Yellowstone National Park Area, 1883-2021 Historic Water Chemistry Data for Thermal Features, Streams, and Rivers in the Yellowstone National Park Area, 1883-2021

Yellowstone National Park (YNP; Wyoming, Montana, and Idaho, USA) contains more than 10,000 hydrothermal features, several lakes, and four major watersheds. For more than 140 years, researchers at the U.S. Geological Survey and other scientific institutions have investigated the chemical compositions of hot springs, geysers, fumaroles, mud pots, streams, rivers, and lakes in YNP and...

Digital database for the Surficial Geologic Map of the Owlshead Mountains 30' X 60' Quadrangle, Inyo and San Bernardino Counties, California Digital database for the Surficial Geologic Map of the Owlshead Mountains 30' X 60' Quadrangle, Inyo and San Bernardino Counties, California

This geodatabase contains all of the map information used to publish the Surficial Geologic Map of the Owlshead Mountains 30’ X 60’ Quadrangle,Inyo and San Bernardino Counties, California: U.S. Geological Survey Scientific Investigations Map SIM-3496. The geodatabase and associated map delineate primarily surficial geology and neotectonics structure across the entire extent of this...

Bumble bees and flowering plants in Glacier National Park 2023 Bumble bees and flowering plants in Glacier National Park 2023

USGS personnel surveyed bumble bees and flowering plants in and around Glacier National Park during the summer of 2023. These data include 1) a .csv file of all bumble bee - plant interactions observed across surveys and 2) all flowering plants observed in bloom across all surveys.

Code, imagery, and annotations for training a deep learning model to detect wildlife in aerial imagery Code, imagery, and annotations for training a deep learning model to detect wildlife in aerial imagery

There are 3 child zip files included in this data release. 01_Codebase.zip contains a codebase for using deep learning to filter images based on the probability of any bird occurrence. It includes instructions and files necessary for training, validating, and testing a machine learning detection algorithm. 02_Imagery.zip contains imagery that were collected using a Partenavia P68 fixed...

Idealized COAWST model cases for testing sensitivity of sediment transport and marsh accretion to vegetation, wave, and sediment parameters Idealized COAWST model cases for testing sensitivity of sediment transport and marsh accretion to vegetation, wave, and sediment parameters

Marshes may drown if they are unable to accrete sediment at the rate of sea level rise, but predicting the rate of sediment accretion at different marshes is challenging because many processes (e.g. tidal range, wave frequency) and conditions (e.g. available sediment, vegetation density, shape of the marsh edge) impact it. The Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST...

Lifespan of marsh units in New York salt marshes Lifespan of marsh units in New York salt marshes

Lifespan of salt marshes in New York are calculated using conceptual marsh units defined by Defne and Ganju (2018) and Welk and others (2019, 2020a, 2020b, 2020c). The lifespan calculation is based on estimated sediment supply and sea-level rise (SLR) predictions after Ganju and others (2020). Sea level predictions are local estimates which correspond to the 0.3, 0.5, and 1.0 meter...
Was this page helpful?