SEARCH · Search USGS

Results for “Earth in Space”

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

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 235 records · Page 13Linked to original sources

USGS2021

Synoptic analysis of a decade of daily measurements of SO2 emission in the troposphere from volcanoes of the global ground-based Network for Observation of Volcanic and Atmospheric Change

Volcanic plumes are common and far-reaching manifestations of volcanic activity during and between eruptions. Observations of the rate of emission and composition of volcanic plumes are essential to recognize and, in some cases, predict the state of volcanic activity. Measurements of the size and location of the plumes are important to assess the impact of the emission from sporadic or localized events to persistent or widespread processes of climatic and environmental importance. These observations provide information on volatile budgets on Earth, chemical evolution of magmas, and atmospheric circulation and dynamics. Space-based observations during the last decades have given us a global view of Earth's volcanic emission, particularly of sulfur dioxide ( SO 2 ). Although none of the satellite missions were intended to be used for measurement of volcanic gas emission, specially adapted algorithms have produced time-averaged global emission budgets. These have confirmed that tropospheric plumes, produced from persistent degassing of weak sources, dominate the total emission of volcanic SO 2 . Although space-based observations have provided this global insight into some aspects of Earth's volcanism, it still has important limitations. The magnitude and short-term variability of lower-atmosphere emissions, historically less accessible from space, remain largely uncertain. Operational monitoring of volcanic plumes, at scales relevant for adequate surveillance, has been facilitated through the use of ground-based scanning differential optical absorption spectrometer (ScanDOAS) instruments since the beginning of this century, largely due to the coordinated effort of the Network for Observation of Volcanic and Atmospheric Change (NOVAC). In this study, we present a compilation of results of homogenized post-analysis of measurements of SO 2 flux and plume parameters obtained during the period March 2005 to January 2017 of 32 volcanoes in NOVAC. This inventory opens a window into the short-term emission patterns of a diverse set of volcanoes in terms of magma composition, geographical location, magnitude of emission, and style of eruptive activity. We find that passive volcanic degassing is by no means a stationary process in time and that large sub-daily variability is observed in the flux of volcanic gases, which has implications for emission budgets produced using short-term, sporadic observations. The use of a standard evaluation method allows for intercomparison between different volcanoes and between ground- and space-based measurements of the same volcanoes. The emission of several weakly degassing volcanoes, undetected by satellites, is presented for the first time. We also compare our results with those reported in the literature, providing ranges of variability in emission not accessible in the past. The open-access data repository introduced in this article will enable further exploitation of this unique dataset, with a focus on volcanological research, risk assessment, satellite-sensor validation, and improved quantification of the prevalent tropospheric component of global volcanic emission.

Earth System Science Data↗

USGS2007

Magnetic indices

Magnetic indices are simple measures of magnetic activity that occurs, typically, over periods of time of less than a few hours and which is recorded by magnetometers at ground‐based observatories (Mayaud, 1980 ; Rangarajan, 1989 ; McPherron, 1995 ). The variations that indices measure have their origin in the Earth's ionosphere and magnetosphere. Some indices having been designed specifically to quantify idealized physical processes, while others function as more generic measures of magnetic activity. Indices are routinely used across the many subdisciplines in geomagnetism, including direct studies of the physics of the upper atmosphere and space, for induction studies of the Earth's crust and mantle, and for removal of disturbed‐time magnetic data in studies of the Earth's deep interior and core. Here we summarize the most commonly used magnetic indices, using data from a worldwide distribution of observatories, those shown in Figure M31 and whose sponsoring agencies are given in Table M1 .

Book chapter↗

USGS1976

ERTS-1, a new window on our planet

The launch, on July 23, 1972, of the first Earth Resources Technology Satellite (ERTS-1) by the National Aeronautics and Space Administration was a major step forward in extending man 's ability to inventory the Earth 's resources and to evaluate objectively his impact upon the environment. ERTS spacecraft represent the first step in merging space and remote-sensing technologies into a system for inventorying and managing the Earth 's resources. Examples presented in this book demonstrate ERTS ' vast potential for inventorying resources, monitoring environmental conditions, and measuring changes. Such information is essential for the full evaluation of the Federal lands and determining their future use, as well as for improved planning of overall land use throughout the United States and the world. Ten bureaus of the U.S. Department of Interior have roles in the ERTS project. Nearly all of these participating bureaus are represented in almost 100 papers included in this book. Chapter 3 is entitled ' Applications to Water Resources ' and contains 23 separate sections. (Woodard-USGS)

Professional Paper↗

USGS2023

Exploring the influence of input feature space on CNN-based geomorphic feature extraction from digital terrain data

Many studies of Earth surface processes and landscape evolution rely on having accurate and extensive data sets of surficial geologic units and landforms. Automated extraction of geomorphic features using deep learning provides an objective way to consistently map landforms over large spatial extents. However, there is no consensus on the optimal input feature space for such analyses. We explore the impact of input feature space for extracting geomorphic features from land surface parameters (LSPs) derived from digital terrain models (DTMs) using convolutional neural network (CNN)-based semantic segmentation deep learning. We compare four input feature space configurations: (a) a three-layer composite consisting of a topographic position index (TPI) calculated using a 50 m radius circular window, square root of topographic slope, and TPI calculated using an annulus with a 2 m inner radius and 10 m outer radius, (b) a single illuminating position hillshade, (c) a multidirectional hillshade, and (d) a slopeshade. We test each feature space input using three deep learning algorithms and four use cases: two with natural features and two with anthropogenic features. The three-layer composite generally provided lower overall losses for the training samples, a higher F1-score for the withheld validation data, and better performance for generalizing to withheld testing data from a new geographic extent. Results suggest that CNN-based deep learning for mapping geomorphic features or landforms from LSPs is sensitive to input feature space. Given the large number of LSPs that can be derived from DTM data and the variety of geomorphic mapping tasks that can be undertaken using CNN-based methods, we argue that additional research focused on feature space considerations is needed and suggest future research directions. We also suggest that the three-layer composite implemented here can offer better performance in comparison to using hillshades or other common terrain visualization surfaces and is, thus, worth considering for different mapping and feature extraction tasks.

Earth and Space Science↗

USGS2021

Hyperspectral narrowband data propel gigantic leap in the earth remote sensing

Hyperspectral narrowbands (HNBs) capture data as nearly continuous “spectral signatures” rather than a “few spectral data points” along the electromagnetic spectrum as with multispectral broadbands (MBBs). Almost all of satellite remote sensing of the Earth in the twentieth century was conducted using MBB data from sensors such as the Landsat-series, Advanced Very High-Resolution Radiometer (AVHRR), SPOT (Système Pour l’Observation de la Terre), and the Indian Remote Sensing (IRS) satellites. These systems typically provide 4 to 9 broad spectral wavebands spread from 400 to 2500 nm, often with one or two additional bands in the thermal range. Significant advances in the study of the Earth have been made based on these data [Thenkabail et al., 2018a,b,c,d; Thenkabail et al., 2015a,b,c]. Possibilities of great advances that can be made using HNB data over MBB data are well established based on studies conducted using hyperspectral sensors such as the hand-held spectroradiometers, the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), and spaceborne Earth Observing -1 (EO-1) Hyperion [Thenkabail 2018a,b,c,d]. The twenty-first century is already seeing the dawn of hyperspectral imaging data from sensors such as the German Aerospace Center’s (DLR’s) DESIS (DLR Earth Sensing Imaging Spectrometer) onboard the MUSES (Multi-User System for Earth Sensing) platform on the International Space Station (ISS), the polar-orbiting Italian Space Agency’s (ASI) PRISMA (PRecursore IperSpettrale della Missione Applicativa), and many other upcoming sensors such as the NASA Surface Biology and Geology (SBG) [Thenkabail et al., 2018a,b,c,d]. These satellites acquire data in hundreds of narrow spectral bands of 1 to 10 nm width, typically between 400 to 2500 nm; also future planned missions will be extending HNBs to the thermal (9,000 to 14,000 nm) electromagnetic spectrum. This expansion creates a quantum leap in new data, new information, and myriad possible new applications in the study of the Earth in addition to great advances in existing applications. Given the above, the objective of this article is to provide insights on the gigantic leap in our understanding, modeling, mapping, and monitoring of the Earth that can be made using HNB relative to MBB by focusing on agricultural and vegetation applications. We will address this in four aspects: 1. Comparison between HNB and MBB data; 2. Spectral libraries of agricultural crops; 3. HNB data analysis in general; and 4. HNB analysis using machine learning (ML) and cloud computing.

Photogrammetric Engineering and Remote Sensing.↗

USGS2020

Using NASA Earth observations and Google Earth Engine to map winter cover crop conservation performance in the Chesapeake Bay watershed

Winter cover crops such as barley, rye, and wheat help to improve soil structure by increasing porosity, aggregate stability, and organic matter, while reducing the loss of agricultural nutrients and sediments into waterways. The environmental performance of cover crops is affected by choice of species, planting date, planting method, nutrient inputs, temperature, and precipitation. The Maryland Department of Agriculture (MDA) oversees an agricultural cost-share program that provides farmers with funding to cover costs associated with planting winter cover crops, and the U.S. Geological Survey (USGS) and the U.S. Department of Agriculture-Agricultural Research Service (USDA-ARS) have partnered with the MDA to develop satellite remote sensing techniques for measuring cover crop performance. The MDA has developed the capacity to digitize field boundaries for all fields enrolled in their cover crop programs (>26,000 fields per year) to support a remote sensing performance analysis at a statewide scal,e and has requested assistance with the associated imagery processing from the National Aeronautics and Space Administration (NASA). Using the Google Earth Engine (GEE) cloud computing platform, scripts were developed to process Landsat 5/7/8 and Harmonized Sentinel-2 imagery to measure winter cover crop performance. We calibrated cover crop performance models using linear regression between satellite vegetation indices and USGS / USDA-ARS field sampling data collected on Maryland farms between 2006 and 2012 (1298 samples). Satellite-derived Normalized Difference Vegetation Index (NDVI) values showed significant correlation with the natural logarithm of cover crop biomass ( p ≤0.01, R 2 = 0.56) and with observed percent vegetative ground cover (p ≤0.01, R 2 = 0.68). The GEE scripts were used to composite seasonal maximum NDVI values for each enrolled cover crop field and calculate performance metrics for the winter and spring seasons of three enrollment years (2014–15, 2015–16, and 2017–18) for four Maryland counties. Results from winter 2017–18 demonstrate that rye and barley fields had higher biomass than wheat fields, and that early planting, along with planting methods that increase seed-soil contact, increased performance. The processing capabilities of GEE will support the MDA in scaling up remote sensing performance analysis statewide, providing information to evaluate the environmental outcomes associated with various agronomic management strategies. The tool can be modified for different seasonal cutoffs, utilize new sensors to capture phenology in winter and spring, and scale to larger regions for use in adaptive management of winter cover crops planted for environmental benefit.

Maryland↗

USGS1990

What do we mean by accuracy in geomagnetic measurements?

High accuracy is what distinguishes measurements made at the world's magnetic observatories from other types of geomagnetic measurements. High accuracy in determining the absolute values of the components of the Earth's magnetic field is essential to studying geomagnetic secular variation and processes at the core mantle boundary, as well as some magnetospheric processes. In some applications of geomagnetic data, precision (or resolution) of measurements may also be important. In addition to accuracy and resolution in the amplitude domain, it is necessary to consider these same quantities in the frequency and space domains. New developments in geomagnetic instruments and communications make real-time, high accuracy, global geomagnetic observatory data sets a real possibility. There is a growing realization in the scientific community of the unique relevance of geomagnetic observatory data to the principal contemporary problems in solid Earth and space physics. Together, these factors provide the promise of a 'renaissance' of the world's geomagnetic observatory system. ?? 1990.

Physics of the Earth and Planetary Interiors↗

USGS1972

Image resolutions for ERTS, SKYLAB and GEMINI/APOLLO

Early in 1972 the first Earth Resource Technology Satellite (ERTS-A) is scheduled for launch in near-polar orbit. It will carry three return-beam-vidicon (RBV) TB cameras and a multispectral scanner (MSS). In 1973 a post-Apollo manned space flight called SKYLAB will orbit the earth at an inclination of 50° to the Equator. In addition to other sensors it will carry a battery of six multispectral cameras identified as experiment S190. This paper compares the images expected from ERTS and SKYLAB with those already obtained from GEMINI/APOLLO, all in terms of the photographic criterion of resolution. Recently provided data have led to several changes in the resolution of ERTS-A forecast a year ago (Colvocoresses, 1970).

Photogrammetric Engineering↗

USGS2023

Using simulated GEDI waveforms to evaluate the effects of beam sensitivity and terrain slope on GEDI L2A relative height metrics over the Brazilian Amazon Forest

The vertical structure of forests provides important parameters for estimating aboveground biomass (AGB) and it can be measured by LiDAR sensors. The Global Ecosystem Dynamics Investigation (GEDI) full-waveform LiDAR sensor collects data systematically over the Earth’s surface from the International Space Station. Since GEDI became operational, it has collected billions of ~25 m diameter footprints. This massive dataset has been used to create higher level gridded and non-grided products. However, GEDI’s ~25 m footprints can be subject to errors associated with effects of geolocation, terrain slope, and beam sensitivity, among others, which are likely transferred to the downstream products. This study aims to (1) evaluate the effect of beam sensitivity and terrain slope on the accuracy of relative heights (RH) of GEDI product L2A version 2 through comparison with discrete-return airborne LiDAR data collected over transects in the Brazilian Amazon Forest biome, (2) assess GEDI’s geolocation uncertainty and investigate its combined effects with beam sensitivity and terrain slope, and (3) re-evaluate beam sensitivity and terrain slope effects on the GEDI L2A RHs using footprints that were geolocation-adjusted through a simple novel approach. The analysis separates GEDI footprints by acquisition time, i.e., daytime, nighttime, and combined (all-data). The discrete-return airborne LiDAR point clouds are used to derive terrain slope within the GEDI footprints, and to simulate GEDI waveforms and derive RHs comparable to the GEDI L2A product. Results indicate that terrain slope only causes significant effects on GEDI data collected during daytime because solar radiation affects waveform signal-to-noise ratio. Beam sensitivity causes significant effects on nighttime and all-data GEDI L2A RHs. If geolocation uncertainty is considered, the effects of beam sensitivity and terrain slope have just minor changes. Geolocation-adjusted data continue showing significant effects on nighttime and all-data RH differences caused by beam sensitivity but produce unbiased results. This study improves the understanding of how beam sensitivity, terrain slope and their combined effect with geolocation uncertainty may affect the GEDI L2A RH collected over the Brazilian Amazon forest during daytime and nighttime.

Brazilian Amazon Forest↗

USGS2014

A large mantle water source for the northern San Andreas Fault System: A ghost of subduction past

Recent research indicates that the shallow mantle of the Cascadia subduction margin under near-coastal Pacific Northwest U.S. is cold and partially serpentinized, storing large quantities of water in this wedge-shaped region. Such a wedge probably formed to the south in California during an earlier period of subduction. We show by numerical modeling that after subduction ceased with the creation of the San Andreas Fault System (SAFS), the mantle wedge warmed, slowly releasing its water over a period of more than 25 Ma by serpentine dehydration into the crust above. This deep, long-term water source could facilitate fault slip in San Andreas System at low shear stresses by raising pore pressures in a broad region above the wedge. Moreover, the location and breadth of the water release from this model gives insights into the position and breadth of the SAFS. Such a mantle source of water also likely plays a role in the occurrence of Non-Volcanic Tremor (NVT) that has been reported along the SAFS in central California. This process of water release from mantle depths could also mobilize mantle serpentinite from the wedge above the dehydration front, permitting upward emplacement of serpentinite bodies by faulting or by diapiric ascent. Specimens of serpentinite collected from tectonically emplaced serpentinite blocks along the SAFS show mineralogical and structural evidence of high fluid pressures during ascent from depth. Serpentinite dehydration may also lead to tectonic mobility along other plate boundaries that succeed subduction, such as other continental transforms, collision zones, or along present-day subduction zones where spreading centers are subducting.

California↗

USGS2014

Can we estimate total magnetization directions from aeromagnetic data using Helbig's integrals?

An algorithm that implements Helbig’s (1963) integrals for estimating the vector components ( m x , m y , m z ) of the magnetic dipole moment from the first order moments of the vector magnetic field components (Δ X , Δ Y , Δ Z ) is tested on real and synthetic data. After a grid of total field aeromagnetic data is converted to vector component grids using Fourier filtering, Helbig’s infinite integrals are evaluated as finite integrals in small moving windows using a quadrature algorithm based on the 2-D trapezoidal rule. Prior to integration, best-fit planar surfaces must be removed from the component data within the data windows in order to make the results independent of the coordinate system origin. Two different approaches are described for interpreting the results of the integration. In the “direct” method, results from pairs of different window sizes are compared to identify grid nodes where the angular difference between solutions is small. These solutions provide valid estimates of total magnetization directions for compact sources such as spheres or dipoles, but not for horizontally elongated or 2-D sources. In the “indirect” method, which is more forgiving of source geometry, results of the quadrature analysis are scanned for solutions that are parallel to a specified total magnetization direction.

Earth, Planets and Space↗

USGS2014

Utility of aeromagnetic studies for mapping of potentially active faults in two forearc basins: Puget Sound, Washington, and Cook Inlet, Alaska

High-resolution aeromagnetic surveys over forearc basins can detect faults and folds in weakly magnetized sediments, thus providing geologic constraints on tectonic evolution and improved understanding of seismic hazards in convergent-margin settings. Puget Sound, Washington, and Cook Inlet, Alaska, provide two case histories. In each lowland region, shallow-source magnetic anomalies are related to active folds and/or faults. Mapping these structures is critical for understanding seismic hazards that face the urban regions of Seattle, Washington, and Anchorage, Alaska. Similarities in aeromagnetic anomaly patterns and magnetic stratigraphy between the two regions suggest that we can expect the aeromagnetic method to yield useful structural information that may contribute to earth-hazard and energy resource investigations in other forearc basins.

Alaska, Washington↗

USGS2014

The 2000 revision of the joint UK/US geomagnetic field models and an IGRF 2000 candidate model

The method of derivation of the joint UK/US spherical harmonic geomagnetic main-field and secular-variation models is presented. Early versions of these models, with the main field truncated at degree 10, are the UK/US candidates for the IGRF 2000 model. The main-field model describes the Earth’s magnetic field at the 2000.0 epoch, while the secular-variation model predicts the evolution of this field between 2000.0 and 2005.0. A revised 1995.0 main-field model was also generated. Regional models for the continental US, Alaska and Hawaii were also produced as a by-product of the UK/US global modelling effort.

Earth, Planets and Space↗

USGS2014

Northward migration of the Cascadia forearc in the northwestern U.S. and implications for subduction deformation

Geologic and paleomagnetic data from the Cascadia forearc indicate long-term northward migration and clockwise rotation of an Oregon coastal block with respect to North America. Paleomagnetic rotation of coastal Oregon is linked by a Klamath Mountains pole to geodetically and geologically determined motion of the Sierra Nevada block to derive a new Oregon Coast—North America (OC-NA) pole of rotation and velocity field. This long-term velocity field, which is independent of Pacific Northwest GPS data, is interpreted to be the result of Basin-Range extension and Pacific-North America dextral shear. The resulting Oregon Coast pole compares favorably to those derived solely from GPS data, although uncertainties are large. Subtracting the long-term motion from forearc GPS velocities reveals ENE motion with respect to an OC reference frame that is parallel to the direction of Juan de Fuca-OC convergence and decreases inland. We interpret this to be largely the result of subduction-related deformation. The adjusted mean GPS velocities are generally subparallel to those predicted from elastic dislocation models for Cascadia, but more definitive interpretations await refinement of the present large uncertainty in the Sierra Nevada block motion.

British Columbia, Washington↗

USGS2014

Precise hypocenter locations of midcrustal low-frequency earthquakes beneath Mt. Fuji, Japan

Midcrustal low-frequency earthquakes (MLFs) have been observed at seismic stations around Mt. Fuji, Japan. In September - December 2000 and April - May 2001, abnormally high numbers of MLFs occurred. We located hypocenters for the 80 MLFs during 1998-2003 by using the hypoDD earthquake location program (Waldhauser and Ellsworth, 2000). The MLF hypocenters define an ellipsoidal volume some 5 km in diameter ranging from 11 to 16 km in focal depth. This volume is centered 3 km northeast of the summit and its long axis is directed NW-SE. The direction of the axis coincides with the major axis of tectonic compression around Mt. Fuji. The center of the MLF epicenters gradually migrated upward and 2-3 km from southeast to northwest during 1998-2001. We interpret that the hypocentral migration of MLFs reflects magma movement associated with a NW-SE oriented dike beneath Mt. Fuji.

Mt. Fuji↗

USGS2008

Deformation of the Augustine Volcano, Alaska, 1992-2005, measured by ERS and ENVISAT SAR interferometry

The Augustine Volcano is a conical-shaped, active stratovolcano located on an island of the same name in Cook Inlet, about 290 km southwest of Anchorage, Alaska. Augustine has experienced seven significant explosive eruptions - in 1812, 1883, 1908, 1935, 1963, 1976, 1986, and in January 2006. To measure the ground surface deformation of the Augustine Volcano before the 2006 eruption, we applied satellite radar interferometry using Synthetic Aperture Radar (SAR) images from three descending and three ascending satellite tracks acquired by European Remote Sensing Satellite (ERS) 1 and 2 and the Environment Satellite (ENVISAT). Multiple interferograms were stacked to reduce artifacts caused by atmospheric conditions, and we used a singular value decomposition method to retrieve the temporal deformation history from several points on the island. Interferograms during 1992 and 2005 show a subsidence of about 1-3 cm/year, caused by the contraction of pyroclastic flow deposits from the 1986 eruption. Subsidence has decreased exponentially with time. Multiple interferograms between 1992 and 2005 show no significant inflation around the volcano before the 2006 eruption. The lack of a pre-eruption deformation signal suggests that the deformation signal from 1992 to August 2005 must have been very small and may have been obscured by atmospheric delay artifacts.

Alaska↗

USGS2014

The tsunami source area of the 2003 Tokachi-oki earthquake estimated from tsunami travel times and its relationship to the 1952 Tokachi-oki earthquake

We estimate the tsunami source area of the 2003 Tokachi-oki earthquake (Mw 8.0) from observed tsunami travel times at 17 Japanese tide gauge stations. The estimated tsunami source area ( ∼ 1.4 × 10 4 km 2 ) coincides with the western-half of the ocean-bottom deformation area ( ∼ 2.52 × 10 4 km 2 ) of the 1952 Tokachi-oki earthquake (Mw 8.1), previously inferred from tsunami waveform inversion. This suggests that the 2003 event ruptured only the western-half of the 1952 rupture extent. Geographical distribution of the maximum tsunami heights in 2003 differs significantly from that of the 1952 tsunami, supporting this hypothesis. Analysis of first-peak tsunami travel times indicates that a major uplift of the ocean-bottom occurred approximately 30 km to the NNW of the mainshock epicenter, just above a major asperity inferred from seismic waveform inversion.

Earth, Planets and Space↗

USGS2014

Preface

No abstract available.

Earth, Planets and Space↗