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Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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USGS2008

Data management and digital delivery of analog data

The U.S. Geological Survey's (USGS) data archive at the Earth Resources Observation and Science (EROS) Center is a comprehensive and impartial record of the Earth's changing land surface. USGS/EROS has been archiving and preserving land remote sensing data for over 35 years. This remote sensing archive continues to grow as aircraft and satellites acquire more imagery. As a world leader in preserving data, USGS/EROS has a reputation as a technological innovator in solving challenges and ensuring that access to these collections is available. Other agencies also call on the USGS to consider their collections for long-term archive support. To improve access to the USGS film archive, each frame on every roll of film is being digitized by automated high performance digital camera systems. The system robotically captures a digital image from each film frame for the creation of browse and medium resolution image files. Single frame metadata records are also created to improve access that otherwise involves interpreting flight indexes. USGS/EROS is responsible for over 8.6 million frames of aerial photographs and 27.7 million satellite images.

Conference Paper↗

USGS1994

Topographic data requirements for EOS global change research

This document is a result of Earth Observing System Data and Information System (EOSDIS) Version 0 activities of the Land Processes Distributed Active Archive Center at the U.S. Geological Survey's EROS Data Center. A relatively small part of the Version 0 funding provided by NASA is used to address topographic data issues related to EOS. These issues include identifying and improving access to existing sources of topographic data, data generation, facilitating the use of topographic data in global change research by demonstrating derivative products, and inventorying the specific topographic data requirements of EOS investigators. There is a clear need for global topographic data in EOSDIS. Only 10 percent of the global land surface is covered by high-resolution data that are available to the global change science community. Alternative sources for new data exist or have been proposed; however, none of them alone can fulfill the data requirements by the launch of the first EOS platform in 4 years. There is no operational provider of all the source data that are required. Even if appropriate global source data existed, a concerted production effort would be necessary to ensure the existence of the requisite topographic data before EOS launch. Additionally, no funding from NASA or any other agency has been appropriated for a new mapping mission or for other means of data acquisition. This effort to document requirements is an initial step toward understanding the severity of the data shortage. It is well beyond the scope of Version 0 funding and capabilities to provide the required data in the proper timeframe. The shortage of data and the lack of a plan for providing the necessary topographic data through EOSDIS in time for launch are issues that must be addressed by the EOS program.

Open-File Report↗

USGS2009

Geographic information systems, remote sensing, and spatial analysis activities in Texas, 2008-09

Geographic information system (GIS) technology has become an important tool for scientific investigation, resource management, and environmental planning. A GIS is a computer-aided system capable of collecting, storing, analyzing, and displaying spatially referenced digital data. GIS technology is useful for analyzing a wide variety of spatial data. Remote sensing involves collecting remotely sensed data, such as satellite imagery, aerial photography, or radar images, and analyzing the data to gather information or investigate trends about the environment or the Earth's surface. Spatial analysis combines remotely sensed, thematic, statistical, quantitative, and geographical data through overlay, modeling, and other analytical techniques to investigate specific research questions. It is the combination of data formats and analysis techniques that has made GIS an essential tool in scientific investigations. This fact sheet presents information about the technical capabilities and project activities of the U.S. Geological Survey (USGS) Texas Water Science Center (TWSC) GIS Workgroup during 2008 and 2009. After a summary of GIS Workgroup capabilities, brief descriptions of activities by project at the local and national levels are presented. Projects are grouped by the fiscal year (October-September 2008 or 2009) the project ends and include overviews, project images, and Internet links to additional project information and related publications or articles.

Fact Sheet↗

USGS2025

Constraining landslide frequency across the United States to inform county-level risk reduction

Informative landslide hazard estimates are needed to support landslide mitigation strategies to reduce landslide risk across the United States. Whereas existing national-scale landslide susceptibility products assess where landslides are likely to occur, they do not address how often , which is a critical element of landslide hazard and risk assessments. In particular, the U.S. Federal Emergency Management Agency's National Risk Index (NRI) requires landslide frequency estimates to inform expected annual loss estimates. We present county-level landslide frequency (landslides per area per year) estimates for the 50 US states. We applied Bayesian negative binomial regression to estimate both the expected (average) reported landslide frequency and full distribution of annual landslide counts for each county. We compared a suite of models that used combinations of landslide-susceptible area, probability of potentially triggering earthquakes, frequency of potentially triggering precipitation, and ecological region as predictors. We trained our models with landslide inventory data from counties with the most comprehensive records available nationwide and used zero-inflated negative binomial distributions as an incompleteness model to correct for temporal reporting gaps. We selected a preferred frequency model to inform the NRI based on information criteria and physically plausible parameter estimates. The model showed that average annual reported landslide frequencies vary by 5 orders of magnitude across US counties, ranging from 0.002 (0.00015–0.05) landslides 1000 km −2 yr −1 in Kusilvak Census Area, Alaska, to 29 (19–46) landslides 1000 km −2 yr −1 in Lake County, California, reflecting the country's strong variations in landslide susceptibility, earthquake probability, and other factors for which ecological region serves as a proxy. Counties with estimated frequencies in the top 20 % of all counties are predominately along the West Coast of the continental United States, in mountainous regions of the Pacific Northwest and Intermountain West, in locally steep or earthquake-prone regions of the Midwest and Southeast, along the Appalachians, in southern and southeastern Alaska, and on some Hawaiian islands. By examining the number of landslides predicted in 99th percentile years for each county, we identified that 26 % of US counties likely have potential for widespread landsliding with more than 10 landslides 1000 km −2 yr −1 , even when such large events have not been reported in the training data for that county. Overall, our results better represent the range of possible landslide frequencies and spatial variations than previous national-scale estimates reported in the NRI, and our approach can inform other risk-reduction and loss-mitigation efforts across the United States and globally.

Natural Hazards and Earth System Sciences↗

USGS2016

Corrigendum to “Widespread occurrence of (per)chlorate in the Solar System” [Earth Planet. Sci. Lett. 430 (2015) 470–476]

The authors regret that two sets of data (Atacama (Rao et al., 2010) and Mars Meteorite Range (Kounaves et al., 2014)) in Fig. 2 of our article were plotted in the wrong units. The correction does not change the relationship between ClO 3 − "> ClO3− and ClO 4 − "> ClO4− ; it only shifts the magnitude of the concentrations. The conclusions of the article are not affected. The corrected Fig. 2 appears below.

Earth and Planetary Science Letters↗

USGS2001

The Landsat 7 mission: terrestrial research and applications for the 21st century

The Landsat Earth observation approach introduced in 1972 created a new way of monitoring land cover and land use globally. The Landsat 7 mission, successfully launched on April 15, 1999, continues those observations and demonstrates significant progress in precise numerical radiometry, spectral differentiation, and seasonally repetitive monitoring. Substantial improvements in calibration procedures, both prior to launch and during normal operations, have also been made to ensure long-term stability in the acquired spectral radiometry. Landsat 7 data acquisitions are being driven by a long-term data acquisition plan that was designed to ensure that substantially cloud-free, seasonal coverage would be recorded and archived in the US for all land areas of the globe. NASA competitively selected a Landsat Science Team, consisting of representatives from US universities and government agencies, to exploit the Landsat 7 record for global change research. This team is addressing the technical and analytical means to process and analyze the core of this observation record, and for the first time in the history of the Landsat mission, the technical and operational aspects of the mission are being driven by the goals of the US science community. The expected outcome of these efforts is a rapid improvement in understanding the Earth system, as well as conceptual knowledge that will underpin significant advancements in the application of this technology for commercial, operational, educational, and research purposes. Pathways to achieve effective Landsat continuity in the early decades of the 21st century are also being given careful attention, and there is no question that the lessons learned from the Landsat 7 mission will strongly influence these next-generation sensor systems.

Remote Sensing of Environment↗

USGS2020

Planetary sensor models interoperability using the community sensor model specification

This paper presents the photogrammetric foundations upon which the Community Sensor Model specification depends, describes common coordinate system and reference frame transformations that support conversion between image sensor (charge‐coupled device) coordinates to some arbitrary body coordinate, and describes the U.S. Geological Survey Astrogeology Community Sensor Model implementation ( https://github.com/USGS-Astrogeology/usgscsm ). We present a new image support data specification that provides the position, pointing, timing, and metadata information necessary to properly locate a pixel or observations location on a body and describe a system architecture designed to explicitly identify the responsibilities of software components within a larger pipeline or analytical environment. This paper concludes with a set of experiments that illustrate positional and pointing error in the sensor location and the impact on the computed surface location.

Earth and Space Science↗

USGS1998

Review of magnetic field monitoring near active faults and volcanic calderas in California: 1974-1995

Differential magnetic fields have been monitored along the San Andreas fault and the Long Valley caldera since 1974. At each monitoring location, proton precession magnetometers sample total magnetic field intensity at a resolution of 0.1 nT or 0.25 nT. Every 10 min, data samples are transmitted via satellite telemetry to Menlo Park, CA for processing and analysis. The number of active magnetometer sites has varied during the past 21 years from 6 to 25, with 12 sites currently operational. We use this network to identify magnetic field changes generated by earthquake and volcanic processes. During the two decades of monitoring, five moderate earthquakes (M5.9 to M7.3) have occurred within 20 km of magnetometer sites located along the San Andreas fault and only one preseismic signal of 1.5 nT has been observed. During moderate earthquakes, coseismic magnetic signals, with amplitudes from 0.7 nT to 1.3 nT, have been identified for 3 of the 5 events. These observations are generally consistent with those calculated from simple seismomagnetic models of these earthquakes and near-fault coseismic magnetic field disturbances rarely exceed one nanotesla. These data are consistent with the concept of low shear stress and relatively uniform displacement of the San Andreas fault system as expected due to high pore fluid pressure on the fault. A systematic decrease of 0.8-1 nT/year in magnetic field has occurred in the Long Valley caldera since 1989. These magnetic field data are similar in form to observed geodetically measured displacements from inflation of the resurgent dome. A simple volcanomagnetic model involving pressure increase of 50 MPa/a at a depth of 7 km under the resurgent dome can replicate these magnetic field observations. This model is derived from the intrusion model that best fits the surface deformation data. ?? 1998 Elsevier Science B.V.

Physics of the Earth and Planetary Interiors↗

USGS2008

Evaluation of candidate Landsat Data Gap Sensors

The capabilities of the currently operational Landsat satellites may be lost before the launch of the follow-on Landsat Data Continuity Mission (LDCM), thus producing a gap in the Landsat data record and the National Satellite Land Remote Sensing Data Archive (NSLRSDA). In anticipation of a gap, the Federal agencies responsible for Landsat program management, the National Aeronautics and Space Administration (NASA) and the Department of Interior (DOI) U. S. Geological Survey (USGS), convened a Landsat Data Gap Study Team (LDGST). The study team assessed the basic characteristics of multiple systems and identified sensors aboard the China-Brazil Earth Resources Satellite (CBERS-2) and the Indian Remote Sensing (IRS-P6) ResourceSat-1 satellite as the most promising sources of Landsat-like data. The sensors include the combination of CBERS-2 Infrared Multi-spectral Scanner (IRMSS) and High Resolution Charged Coupled Device (CCD), as well as the IRS-P6 Advanced Wide Field Sensor (AWiFS) and the IRS-P6 Linear Imaging Self Scanning Sensor (LISS-III). The study team concluded that more robust technical evaluations of data and sensor performance are required before gap mitigation strategies can be fully formulated. A technical report is made available that summarizes the results from those evaluations, including the initial data characterization and science utility evaluation. The report can be accessed at http://calval.cr.usgs.gov/LDGST.php.

Conference Paper↗

USGS2007

Geographic information systems, remote sensing, and spatial analysis activities in Texas, 2002-07

Geographic information system (GIS) technology has become an important tool for scientific investigation, resource management, and environmental planning. A GIS is a computer-aided system capable of collecting, storing, analyzing, and displaying spatially referenced digital data. GIS technology is particularly useful when analyzing a wide variety of spatial data such as with remote sensing and spatial analysis. Remote sensing involves collecting remotely sensed data, such as satellite imagery, aerial photography, or radar images, and analyzing the data to gather information or investigate trends about the environment or the Earth's surface. Spatial analysis combines remotely sensed, thematic, statistical, quantitative, and geographical data through overlay, modeling, and other analytical techniques to investigate specific research questions. It is the combination of data formats and analysis techniques that has made GIS an essential tool in scientific investigations. This document presents information about the technical capabilities and project activities of the U.S. Geological Survey (USGS) Texas Water Science Center (TWSC) GIS Workgroup from 2002 through 2007.

Fact Sheet↗

USGS2019

Comment on “Particle fluxes in groundwater change subsurface rock chemistry over geologic time”

Over the last decade, studies at the Shale Hills Critical Zone Observatory (Shale Hills) have greatly expanded knowledge of weathering in previously understudied, shale-mantled terrains, as well as Earth's Critical Zone as a whole. Among the many discoveries made was the importance of redistribution and losses of micron-sized particles during development of shale-derived soils. A geochemical fingerprint of this process for Al and Fe was illustrated quantitatively by Jin et al. (2010). Subsequent papers, too numerous to list in a Comment, built upon this new recognition by evaluating the spatial and temporal aspects element mobilization. Recently, Kim et al. (2018) examined the composition of suspended, generally micron-sized particles in the Shale Hills stream, along with the dissolved load, across seasons and ranges of discharge. One prominent conclusion from Kim et al. (2018) is that Zr is essentially immobile at Shale Hills. Such a broad conclusion is in direct contradiction with one from Bern and Yesavage (2018) that Zr has been mobilized from soils at Shale Hills, and the losses relative to soil parent material are significant (median 41%). The point is important, because assuming Zr immobility is necessary to index gains and losses of other elements using the open-chemical-system transport function ( τ ). Both papers draw upon patterns and calculations using elemental concentration data from Shale Hills and attempt to construct conceptual frameworks to explain the results. Here, the argument is made that the understanding of substantial Zr mobility from soils at Shale Hills described by Bern and Yesavage (2018) is more accurate. Additionally, issues with adaptations of the standard τ equations used in Kim et al. (2018) and some previous papers are also addressed.

Pennsylvania↗

USGS2012

Using geochemistry to identify the source of groundwater to Montezuma Well, a natural spring in Central Arizona, USA: Part 2

Montezuma Well is a unique natural spring located in a sinkhole surrounded by travertine. Montezuma Well is managed by the National Park Service, and groundwater development in the area is a potential threat to the water source for Montezuma Well. This research was undertaken to better understand the sources of groundwater to Montezuma Well. Strontium isotopes ( 87 Sr/ 86 Sr) indicate that groundwater in the recharge area has flowed through surficial basalts with subsequent contact with the underlying Permian aged sandstones and the deeper, karstic, Mississippian Redwall Limestone. The distinctive geochemistry in Montezuma Well and nearby Soda Springs (higher concentrations of alkalinity, As, B, Cl, and Li) is coincident with added carbon dioxide and mantle-sourced He. The geochemistry and isotopic data from Montezuma Well and Soda Springs allow for the separation of groundwater samples into four categories: (1) upgradient, (2) deep groundwater with carbon dioxide, (3) shallow Verde Formation, and (4) mixing zone. δ 18 O and δD values, along with noble gas recharge elevation data, indicate that the higher elevation areas to the north and east of Montezuma Well are the groundwater recharge zones for Montezuma Well and most of the groundwater in this portion of the Verde Valley. Adjusted groundwater age dating using likely 14 C and δ 13 C sources indicate an age for Montezuma Well and Soda Springs groundwaters at 5,400–13,300 years, while shallow groundwater in the Verde Formation appears to be older (18,900). Based on water chemistry and isotopic evidence, groundwater flow to Montezuma Well is consistent with a hydrogeologic framework that indicates groundwater flow by (1) recharge in higher elevation basalts to the north and east of Montezuma Well, (2) movement through the upgradient Permian and Mississippian units, especially the Redwall Limestone, and (3) contact with a basalt dike/fracture system that provides a mechanism for groundwater to flow to the surface. While the exact nature of the groundwater flow connections is still uncertain, the available data indicate that flow to Montezuma Well may be more susceptible to future groundwater development in the Redwall Limestone than from any other geologic unit. Overall, the shallow groundwater in the surrounding Verde Formation appears to be largely disconnected from deeper groundwater flowing to Montezuma Well.

Arizona↗

USGS2026

An overview of the NASA Adaptation and Response in Drylands field experiment scoping study

Drylands cover 41% of Earth’s land surface, support 36% of the global population, and contribute 60% of global food production. Despite these ecosystems’ importance and high vulnerability to droughts and heatwaves, drylands remain some of the most understudied systems on Earth. Monitoring drylands is challenging due to their complex ecosystem structure of visible soil mixed with diverse plant species that respond rapidly to weather and climate. In 2023 and 2024, a NASA scoping study was conducted for a proposed dryland terrestrial ecology field campaign called Adaptation and Response in Drylands (ARID). Thereafter, the NASA ARID scoping team submitted their campaign proposal to NASA Headquarters, providing a study design for how field, aircraft, and satellite measurements, as well as modeling, would address the most critical fundamental and applied science questions in drylands. The extensive study plan was created by and for the drylands research community – including remote sensors, modelers, experimentalists, and ecologists from across the world – and the overall approach can be further utilized and changed for different uses and data information needs. Here, we summarize the ARID research road map, including its main objectives, field campaign strategy, data end-user support strategy, and U.S. and global community engagement.

Drylands↗

USGS2009

Review of FEWS NET biophysical monitoring requirements

The Famine Early Warning System Network (FEWS NET) provides monitoring and early warning support to decision makers responsible for responding to famine and food insecurity. FEWS NET transforms satellite remote sensing data into rainfall and vegetation information that can be used by these decision makers. The National Aeronautics and Space Administration has recently funded activities to enhance remote sensing inputs to FEWS NET. To elicit Earth observation requirements, a professional review questionnaire was disseminated to FEWS NET expert end-users; it focused upon operational requirements to determine additional useful remote sensing data and, subsequently, to assess whether such data would be beneficial as FEWS NET biophysical supplementary inputs. The review was completed by over 40 experts from around the world. Reviewers were asked to evaluate the relative importance of environmental variables and spatio-temporal requirements for Earth science data products, in particular for rainfall and vegetation products. The results showed that spatio-temporal resolution requirements are complex and need to vary according to place, time, and hazard; that high resolution remote sensing products continue to be in demand; and that rainfall and vegetation products are valued as data that provide actionable food security information.

Environmental Research Letters↗

USGS1990

Land use and land cover digital data from 1:250,000- and 1:100,000- scale maps

The Earth Science Information Centers (ESIC) distribute digital cartographic/geographic data files produced by the U.S. Geological Survey (USGS) as part of the National Mapping Program. The data files are grouped into four basic types. The first type, called a Digital Line Graph (DLG), is line map information in digital form. These data files include information on planimetric base categories, such as transportation, hydrography, and boundaries. The second type, called a Digital Elevation Model (DEM), consists of a sampled array of elevations for ground positions that are usually at regularly spaced intervals. The third type, Land Use and Land Cover digital data, provide information on nine major classes of land use such as urban, agricultural, or forest as well as associated map data such as political units and Federal land ownership. The fourth type, the Geographic Names Information System, provides primary information for known places, features, and areas in the United States identified by a proper name.

Data Users Guide↗

USGS2002

Operating the EOSDIS at the land processes DAAC managing expectations, requirements, and performance across agencies, missions, instruments, systems, and user communities

NASA developed the Earth Observing System (EOS) during the 1990'S. At the Land Processes Distributed Active Archive Center (LP DAAC), located at the USGS EROS Data Center, the EOS Data and Information System (EOSDIS) is required to support heritage missions as well as Landsat 7, Terra, and Aqua. The original system concept of the early 1990'S changed as each community had its say - first the managers, then engineers, scientists, developers, operators, and then finally the general public. The systems at the LP DAAC - particularly the largest single system, the EOSDIS Core System (ECS) - are changing as experience accumulates, technology changes, and each user group gains influence. The LP DAAC has adapted as contingencies were planned for, requirements and therefore plans were modified, and expectations changed faster than requirements could hope to be satisfied. Although not responsible for Quality Assurance of the science data, the LP DAAC works to ensure the data are accessible and useable by influencing systems, capabilities, and data formats where possible, and providing tools and user support as necessary. While supporting multiple missions and instruments, the LP DAAC also works with and learns from multiple management and oversight groups as they review mission requirements, system capabilities, and the overall operation of the LP DAAC. Stakeholders, including the Land Science community, are consulted regularly to ensure that the LP DAAC remains cognizant and responsive to the evolving needs of the user community. Today, the systems do not look or function as originally planned, but they do work, and they allow customers to search and order of an impressive amount of diverse data.

Conference Paper↗

USGS2001

Geophysics: Silent slip on the Cascadia subduction interface

G eodetic satellites of the Global Positioning System (GPS) now permit continuous recording of surface motions around earthquake faults and volcanoes with millimeter precision. Data from distinct points on Earth's surface can be combined to infer the locations of the sources of deformation at depth in the crust. These data are radically altering our understanding of earthquake processes, justifying ambitious new sensor arrays to image active deformation sources in Earth's crust. In recent years, large continuous GPS arrays have been deployed in Japan and southern California, and smaller networks have been installed in other seismically active regions. On page 1525 of this issue ( 1 ), Dragert et al. provide a glimpse of the kinds of insights we can expect from these arrays.

Cascadia subduction zone↗

USGS1981

Remote sensing: a tool for park planning and management

Remote sensing may be defined as the science of imaging or measuring objects from a distance. More commonly, however, the term is used in reference to the acquisition and use of photographs, photo-like images, and other data acquired from aircraft and satellites. Thus, remote sensing includes the use of such diverse materials as photographs taken by hand from a light aircraft, conventional aerial photographs obtained with a precision mapping camera, satellite images acquired with sophisticated scanning devices, radar images, and magnetic and gravimetric data that may not even be in image form. Remotely sensed images may be color or black and white, can vary in scale from those that cover only a few hectares of the earth's surface to those that cover tens of thousands of square kilometers, and they may be interpreted visually or with the assistance of computer systems. This article attempts to describe several of the commonly available types of remotely sensed data, to discuss approaches to data analysis, and to demonstrate (with image examples) typical applications that might interest managers of parks and natural areas.

Parks↗