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USGS2025

Ultraviolet and visible remote sensing of volcanic gases

As magma rises in volcanic systems, volatile species exsolve from the silicate melt and are emitted as gases into the atmosphere. Measuring the magnitude and composition of gas emissions from volcanoes provides insights into processes occurring deep within the Earth and helps constrain the impact of volcanic degassing on atmospheric chemistry. Optical remote sensing techniques allow volcanic gas emissions to be characterized without the need to access hazardous areas near active volcanic vents. This paper reviews the state of the art in ultraviolet and visible volcanic gas remote sensing from the ground, air, and space. Special attention is given to discussing the physics of atmospheric radiative transfer on which these techniques are based. The functionality and limitations of different remote sensing instruments are examined, making clear that the ideal choice of instrumentation will depend on the volcanic system to which it is applied and the sought measurement parameters. Common algorithms for determining trace gas column densities, gas burdens, and volcanic emission rates from measurements of spectral radiance are outlined and compared, showing how some algorithms attempt to model the physics of the measurement while others maximize sensitivity. Several examples demonstrate how remote sensing measurements continue to advance our understanding of volcanic systems and their impact on the atmosphere. Finally, a few promising directions of inquiry are suggested that could lead to improvements in remote sensing instrumentation and analysis techniques. By combining spectroscopic and imaging techniques, improving our understanding of atmospheric radiative transfer, expanding the suite of target gases, and increasing the coverage and frequency of observations, we stand to significantly improve our ability to detect and quantify volcanic gas emissions and gain new insights into important Earth-system processes.

Journal of Volcanology and Geothermal Research↗

USGS2012

Venus cartography

The entire surface of the planet Venus is being mapped at global and regional scales (1:50,000,000 through 1:1,500,000) with synthetic aperture radar (SAR), radar altimeter, and radiometer measurements of physical properties from the Magellan spacecraft. The mapping includes SAR image mosaics, shaded relief maps, and topographic contour overlays made from altimetry data and by radargrammetric methods. Methods used include new techniques of radar image processing that became operational as a result of the Magellan mission. The area being mapped (at a resolution of 75 m/pixel) is roughly equivalent to that of Earth, including seafloors. The mapping is designed to support geologic and geophysical investigations.

Journal of Geophysical Research E: Planets↗

USGS2025

An automated compositing method for producing annual clear images from Landsat Collection 2 for annual NLCD production

Quality image input is fundamental to the quality of derived land cover products. Substantial time and effort are usually required to prepare images. Here, we present a novel and streamlined compositing algorithm that ingests Landsat Collection 2 Analysis Ready Data (ARD) and outputs cloud-free and gap-free composite imagery, which can be directly used for classification. This method leverages and improves the previous National Land Cover Database (NLCD) Virtual Median Value Point (VMVP) compositing method, the first part of the image preparation for NLCD 2019 operational production. The NLCD 2019 image preparation approach includes a second part, a residual cloud and cloud shadow detection and gap-filling method, to produce final cloud-free and gap-free composite imagery. The second part requires one clear reference image for each target year. Additional reference images are needed for producing reasonable observations for perennial ice/snow areas because Pixel QA (Quality Assessment) from ARD has difficulties differentiating ice/snow areas from clouds. Unlike the NLCD 2019 image preparation approach, our new compositing method, which is referred to as Automated VMVP (AVMVP), uses Landsat ARD as the only input and does not require reference images and extra steps. In this method, we developed new spectral filter criteria coupled with counts of clear observations using Pixel QA to identify potential cloud and cloud shadow observations on initially selected observations from the NLCD VMVP compositing algorithm. We also automate “gap-filling” using clear observations retrieved from a maximum of ±2 years around the target year when needed. Finally, a percentile-filtered compositing method was developed for the perennial ice/snow areas. All these steps are streamlined, pixel-based, and directly run on Landsat Collection 2 ARD. We have run successful tests on the conterminous United States (CONUS). Composite images derived from our innovative method were used to produce the CONUS Annual NLCD Collection 1 product suite that covers the period from 1985 to 2023.

conterminous United States↗

USGS2012

Advances in the simulation and automated measurement of well-sorted granular material: 2. Direct measures of particle properties

1. In this, the second of a pair of papers on the structure of well-sorted natural granular material (sediment), new methods are described for automated measurements from images of sediment, of: 1) particle-size standard deviation (arithmetic sorting) with and without apparent void fraction; and 2) mean particle size in material with void fraction. A variety of simulations of granular material are used for testing purposes, in addition to images of natural sediment. Simulations are also used to establish that the effects on automated particle sizing of grains visible through the interstices of the grains at the very surface of a granular material continue to a depth of approximately 4 grain diameters and that this is independent of mean particle size. Ensemble root-mean squared error between observed and estimated arithmetic sorting coefficients for 262 images of natural silts, sands and gravels (drawn from 8 populations) is 31%, which reduces to 27% if adjusted for bias (slope correction between observed and estimated values). These methods allow non-intrusive and fully automated measurements of surfaces of unconsolidated granular material. With no tunable parameters or empirically derived coefficients, they should be broadly universal in appropriate applications. However, empirical corrections may need to be applied for the most accurate results. Finally, analytical formulas are derived for the one-step pore-particle transition probability matrix, estimated from the image's autocorrelogram, from which void fraction of a section of granular material can be estimated directly. This model gives excellent predictions of bulk void fraction yet imperfect predictions of pore-particle transitions.

Journal of Geophysical Research F: Earth Surface↗

USGS2014

Seismicity, faulting, and structure of the Koyna-Warna seismic region, Western India from local earthquake tomography and hypocenter locations

Although seismicity near Koyna Reservoir (India) has persisted for ~50 years and includes the largest induced earthquake ( M 6.3) reported worldwide, the seismotectonic framework of the area is not well understood. We recorded ~1800 earthquakes from 6 January 2010 to 28 May 2010 and located a subset of 343 of the highest-quality earthquakes using the tomoDD code of Zhang and Thurber (2003) to better understand the framework. We also inverted first arrivals for 3-D Vp , Vs , and Vp / Vs and Poisson's ratio tomography models of the upper 12 km of the crust. Epicenters for the recorded earthquakes are located south of the Koyna River, including a high-density cluster that coincides with a shallow depth (<1.5 km) zone of relatively high Vp and low Vs (also high Vp / Vs and Poisson's ratios) near Warna Reservoir. This anomalous zone, which extends near vertically to at least 8 km depth and laterally northward at least 15 km, is likely a water-saturated zone of faults under high pore pressures. Because many of the earthquakes occur on the periphery of the fault zone, rather than near its center, the observed seismicity-velocity correlations are consistent with the concept that many of the earthquakes nucleate in fractures adjacent to the main fault zone due to high pore pressure. We interpret our velocity images as showing a series of northwest trending faults locally near the central part of Warna Reservoir and a major northward trending fault zone north of Warna Reservoir.

Maharashtra↗

USGS1998

Nonlinear refraction and reflection travel time tomography

We develop a rapid nonlinear travel time tomography method that simultaneously inverts refraction and reflection travel times on a regular velocity grid. For travel time and ray path calculations, we apply a wave front method employing graph theory. The first-arrival refraction travel times are calculated on the basis of cell velocities, and the later refraction and reflection travel times are computed using both cell velocities and given interfaces. We solve a regularized nonlinear inverse problem. A Laplacian operator is applied to regularize the model parameters (cell slownesses and reflector geometry) so that the inverse problem is valid for a continuum. The travel times are also regularized such that we invert travel time curves rather than travel time points. A conjugate gradient method is applied to minimize the nonlinear objective function. After obtaining a solution, we perform nonlinear Monte Carlo inversions for uncertainty analysis and compute the posterior model covariance. In numerical experiments, we demonstrate that combining the first arrival refraction travel times with later reflection travel times can better reconstruct the velocity field as well as the reflector geometry. This combination is particularly important for modeling crustal structures where large velocity variations occur in the upper crust. We apply this approach to model the crustal structure of the California Borderland using ocean bottom seismometer and land data collected during the Los Angeles Region Seismic Experiment along two marine survey lines. Details of our image include a high-velocity zone under the Catalina Ridge, but a smooth gradient zone between. Catalina Ridge and San Clemente Ridge. The Moho depth is about 22 km with lateral variations. Copyright 1998 by the American Geophysical Union.

Journal of Geophysical Research B: Solid Earth↗

USGS2010

EAARL coastal topography-western Florida, post-Hurricane Charley, 2004: seamless (bare earth and submerged.

Project Description These remotely sensed, geographically referenced elevation measurements of lidar-derived seamless (bare-earth and submerged) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Coastal and Marine Geology Program (CMGP), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the western Florida coastline beachface, acquired post-Hurricane Charley on August 17 and 18, 2004. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website. Selected References Brock, J.C., Wright, C.W., Sallenger, A.H., Krabill, W.B., and Swift, R.N., 2002, Basis and methods of NASA airborne topographic mapper Lidar surveys for coastal studies: Journal of Coastal Research, v. 18, no. 1, p. 1-13. Crane, Michael, Clayton, Tonya, Raabe, Ellen, Stoker, Jason, Handley, Larry, Bawden, Gerald, Morgan, Karen, and Queija, Vivian, 2004, Report of the U.S. Geological Survey Lidar workshop sponsored by the Land Remote Sensing Program and held in St. Petersburg, FL, November 2002: U.S. Geological Survey Open-File Report 2004-1456, 72 p. Nayegandhi, Amar, Brock, J.C., and Wright, C.W., 2009, Small-footprint, waveform-resolving Lidar estimation of submerged and sub-canopy topography in coastal environments: International Journal of Remote Sensing, v. 30, no. 4, p. 861-878. Sallenger, A.H., Wright, C.W., and Lillycrop, Jeff, 2005, Coastal impacts of the 2004 hurricanes measured with airborne Lidar; initial results: Shore and Beach, v. 73, nos. 2-3, p. 10-14. Resources Included Readme.txt File

Data Series↗

USGS1997

Martian drainage densities

Drainage densities on Mars range from zero over large areas of volcanic plains to 0.3–0.5 km −1 locally on some volcanoes. These values refer to geologic units, not to drainage basins, as is normal for terrestrial drainage densities. The highest values are close to the lowest terrestrial values derived by similar techniques. Drainage densities were determined for every geologic unit portrayed on the 1:15,000,000 geologic map of Mars. Except for volcanoes the geologic unit with the highest drainage density is the dissected Noachian plains with a drainage density of 0.0074 km −1 . The average drainage density for Noachian units is 0.0032 km −1 , for Hesperian units is 0.00047 km −1 , and for Amazonian units is 0.00007 km −1 , excluding the volcanoes. These values are 2–3 orders of magnitude lower than typical terrestrial densities as determined by similar techniques from Landsat images. The low drainage densities, despite a cumulative record that spans billions of years, indicate that compared with the Earth, the channel-forming processes have been very inefficient or have operated only rarely or that the surface is extremely permeable. The high drainage density on volcanoes is attributed to a local cause, such as hydrothermal activity, rather than to a global cause such as climate change.

Journal of Geophysical Research E: Planets↗

USGS2011

Feasibility of waveform inversion of Rayleigh waves for shallow shear-wave velocity using a genetic algorithm

Conventional surface wave inversion for shallow shear (S)-wave velocity relies on the generation of dispersion curves of Rayleigh waves. This constrains the method to only laterally homogeneous (or very smooth laterally heterogeneous) earth models. Waveform inversion directly fits waveforms on seismograms, hence, does not have such a limitation. Waveforms of Rayleigh waves are highly related to S-wave velocities. By inverting the waveforms of Rayleigh waves on a near-surface seismogram, shallow S-wave velocities can be estimated for earth models with strong lateral heterogeneity. We employ genetic algorithm (GA) to perform waveform inversion of Rayleigh waves for S-wave velocities. The forward problem is solved by finite-difference modeling in the time domain. The model space is updated by generating offspring models using GA. Final solutions can be found through an iterative waveform-fitting scheme. Inversions based on synthetic records show that the S-wave velocities can be recovered successfully with errors no more than 10% for several typical near-surface earth models. For layered earth models, the proposed method can generate one-dimensional S-wave velocity profiles without the knowledge of initial models. For earth models containing lateral heterogeneity in which case conventional dispersion-curve-based inversion methods are challenging, it is feasible to produce high-resolution S-wave velocity sections by GA waveform inversion with appropriate priori information. The synthetic tests indicate that the GA waveform inversion of Rayleigh waves has the great potential for shallow S-wave velocity imaging with the existence of strong lateral heterogeneity.

Journal of Applied Geophysics↗

USGS2002

Imaging the mantle beneath Iceland using integrated seismological techniques

Using a combination of body wave and surface wave data sets to reveal the mantle plume and plume head, this study presents a tomographic image of the mantle structure beneath Iceland to 400 km depth. Data comes primarily from the PASSCAL-HOTSPOT deployment of 30 broadband instruments over a period of 2 years, and is supplemented by data from the SIL and ICEMELT networks. Three sets of relative teleseismic body wave arrival times are generated through cross correlation: S and SKS arrivals at 0.03–0.1 Hz, and P and PKIKP arrivals at 0.03–0.1 and 0.8–2.0 Hz. Prior to inversion the crustal portion of the travel time anomalies is removed using the crustal model ICECRTb. This step has a significant effect on the mantle velocity variations imaged down to a depth of ∼250 km. Inversion of relative arrival times only provides information on lateral velocity variations. Surface waves are therefore used to provide absolute velocity information for the uppermost mantle beneath Iceland. The average wave number for the Love wave fundamental mode at 0.020 and 0.024 Hz is measured and used to invert for the average S velocity. Combination of the body wave and surface wave information reveals a predominantly horizontal low-velocity anomaly extending from the Moho down to ∼250 km depth, interpreted as a plume head. Below the plume head a near-cylindrical low-velocity anomaly with a radius of ∼100 km and peak V P and V S anomalies of −2% and −4%, respectively, extends down to the maximum depth of resolution at 400 km. Within the plume head, in the uppermost mantle above the core of the plume, there is a relatively high velocity with a maximum V P and V S anomaly of +2%. This high-velocity anomaly may be the result of the extreme degree of melt extraction necessary to generate the thick (46 km) crust in central Iceland. Comparison of the plume volumetric flux implied by our images, the crustal generation rate, and the degree of melting suggested by rare earth element inversions, suggests that (1) mantle material must be flowing horizontally away from the plume core faster than the overlying lithosphere and (2) the bulk of the plume material does not participate in melting beneath Iceland.

Journal of Geophysical Research B: Solid Earth↗

USGS2022

Bathymetry retrieval from CubeSat image sequences with short time lags

The rapid expansion of CubeSat constellations could revolutionize the way inland and nearshore coastal waters are monitored from space. This potential stems from the ability of CubeSats to provide daily imagery with global coverage at meter-scale spatial resolution. In this study, we explore the unique opportunity to improve the retrieval of bathymetry offered by CubeSats, specifically those of the PlanetScope constellation. The orbital design of the PlanetScope constellation enables the acquisition of image sequences with short time lags (from seconds to hours). This characteristic allows multiple images to be captured during a short period of steady bathymetric conditions, especially in dynamic environments like rivers. We hypothesize that taking the ensemble mean of a CubeSat image sequence can enhance bathymetry retrieval compared to standard single-image analysis. Along with the existing optimal band ratio analysis (OBRA) algorithm, we also use a new neural network-based depth retrieval (NNDR) technique to infer bathymetry from both individual and time-averaged images. The two methodologies are evaluated using field data from five different river reaches with depths up to 15 m and both top-of-atmosphere (TOA) radiance and bottom-of-atmosphere (BOA) surface reflectance PlanetScope data products. Despite low spectral resolution and concerns about the radiometric quality of CubeSat imagery, accuracy assessment based on in-situ comparisons indicates the potential (0.52 < R 2 < 0.7 for the NNDR method) of PlanetScope imagery to retrieve depths up to ∼ 10 m in clear water conditions. The proposed image averaging consistently improves bathymetry retrieval over single image analysis. The NNDR technique was found to outperform OBRA, illustrating the importance of leveraging all spectral bands through machine learning approaches. TOA data provided more robust bathymetry results than BOA data for the OBRA technique, but the NNDR technique was minimally impacted by the type of data product.

International Journal of Applied Earth Observation↗

USGS2014

Establishing the Antarctic Dome C community reference standard site towards consistent measurements from Earth observation satellites

Establishing satellite measurement consistency by using common desert sites has become increasingly more important not only for climate change detection but also for quantitative retrievals of geophysical variables in satellite applications. Using the Antarctic Dome C site (75°06′S, 123°21′E, elevation 3.2 km) for satellite radiometric calibration and validation (Cal/Val) is of great interest owing to its unique location and characteristics. The site surface is covered with uniformly distributed permanent snow, and the atmospheric effect is small and relatively constant. In this study, the long-term stability and spectral characteristics of this site are evaluated using well-calibrated satellite instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS). Preliminary results show that despite a few limitations, the site in general is stable in the long term, the bidirectional reflectance distribution function (BRDF) model works well, and the site is most suitable for the Cal/Val of reflective solar bands in the 0.4–1.0 µm range. It was found that for the past decade, the reflectivity change of the site is within 1.35% at 0.64 µm, and interannual variability is within 2%. The site is able to resolve calibration biases between instruments at a level of ~1%. The usefulness of the site is demonstrated by comparing observations from seven satellite instruments involving four space agencies, including OrbView-2–SeaWiFS, Terra–Aqua MODIS, Earth Observing 1 (EO-1) – Hyperion, Meteorological Operational satellite programme (MetOp) – Advanced Very High Resolution Radiometer (AVHRR), Envisat Medium Resolution Imaging Spectrometer (MERIS) – dvanced Along-Track Scanning Radiometer (AATSR), and Landsat 7 Enhanced Thematic Mapper Plus (ETM+). Dome C is a promising candidate site for climate quality calibration of satellite radiometers towards more consistent satellite measurements, as part of the framework for climate change detection and data quality assurance for the Global Earth Observation System of Systems (GEOSS).

Canadian Journal of Remote Sensing↗

USGS2019

Lithospheric signature of late Cenozoic extension in electrical resistivity structure of the Rio Grande rift, New Mexico, USA

We present electrical resistivity models of the crust and upper mantle from two‐dimensional (2‐D) inversion of magnetotelluric (MT) data collected in the Rio Grande rift, New Mexico, USA. Previous geophysical studies of the lithosphere beneath the rift identified a low‐velocity zone several hundred kilometers wide, suggesting that the upper mantle is characterized by a very broad zone of modified lithosphere. In contrast, the surface expression of the rift (e.g., high‐angle normal faults and synrift sedimentary units) is confined to a narrow region a few tens of kilometers wide about the rift axis. MT data are uniquely suited to probing the depths of the lithosphere that fill the gap between surface geology and body wave seismic tomography, namely the middle to lower crust and uppermost mantle. We model the electrical resistivity structure of the lithosphere along two east‐west trending profiles straddling the rift axis at the latitudes of 36.2 and 32.0°N. We present results from both isotropic and anisotropic 2‐D inversions of MT data along these profiles, with a strong preference for the latter in our interpretation. A key feature of the anisotropic resistivity modeling is a broad (~200‐km wide) zone of enhanced conductivity (<20 Ωm) in the middle to lower crust imaged beneath both profiles. We attribute this lower crustal conductor to the accumulation of free saline fluids and partial melt, a direct result of magmatic activity along the rift. High‐conductivity anomalies in the midcrust and upper mantle are interpreted as fault zone alteration and partial melt, respectively.

New Mexico↗

USGS2007

Oahu: perspective from space

Satellite remote sensing provides us with a unique perspective from space. This perspective is synoptic in nature and provides regional views of most of the land areas of the earth. The orbital characteristics of the Landsat system are such that repetitive imagery of the same area may be obtained. Because of the permanent nature of the imagery, it may be retrieved for comparative analysis at any time. Comparisons of this image of Oahu with maps of the island (for example, the Oahu, Hawaii, 1:250,000-scale topographic map) will enable the reader to readily identify the place names discussed in this article and permit a more detailed interpretation of the image.

Hawaii↗

USGS2022

Quantifying large-scale surface change using SAR amplitude images: Crater morphology changes during the 2019-2020 Shishaldin Volcano eruption

Morphological processes often induce meter-scale elevation changes. When a volcano erupts, tracking such processes provides insights into the style and evolution of eruptive activity and related hazards. Compared to optical remote-sensing products, synthetic aperture radar (SAR) observes surface change during inclement weather and at night. Differential SAR interferometry estimates phase change between SAR acquisitions and is commonly applied to quantify deformation. However, large deformation or other coherence loss can limit its use. We develop a new approach applicable when repeated digital elevation models (DEMs) cannot be otherwise retrieved. Assuming an isotropic radar cross-section, we estimate meter-scale vertical morphological change directly from SAR amplitude images via an optimization method that utilizes a high-quality DEM. We verify our implementation through simulation of a collapse feature that we modulate onto topography. We simulate radar effects and recover the simulated collapse. To validate our method, we estimate elevation changes from TerraSAR-X stripmap images for the 2011–2012 eruption of Mount Cleveland. Our results reproduce those from two previous studies; one that used the same dataset, and another based on thermal satellite data. By applying this method to the 2019–2020 eruption of Shishaldin Volcano, Alaska, we generate elevation change time series from dozens of co-registered TerraSAR-X high-resolution spotlight images. Our results quantify previously unresolved cone growth in November 2019, collapses associated with explosions in December–January, and further changes in crater elevations into spring 2020. This method can be used to track meter-scale morphology changes for ongoing eruptions with low latency as SAR imagery becomes available.

Alaska↗

USGS2008

Eruption dynamics at Mount St. Helens imaged from broadband seismic waveforms: Interaction of the shallow magmatic and hydrothermal systems

The current eruption at Mount St. Helens is characterized by dome building and shallow, repetitive, long-period (LP) earthquakes. Waveform cross-correlation reveals remarkable similarity for a majority of the earthquakes over periods of several weeks. Stacked spectra of these events display multiple peaks between 0.5 and 2 Hz that are common to most stations. Lower-amplitude very-long-period (VLP) events commonly accompany the LP events. We model the source mechanisms of LP and VLP events in the 0.5-4 s and 8-40 s bands, respectively, using data recorded in July 2005 with a 19-station temporary broadband network. The source mechanism of the LP events includes: 1) a volumetric component modeled as resonance of a gently NNW-dipping, steam-filled crack located directly beneath the actively extruding part of the new dome and within 100 m of the crater floor and 2) a vertical single force attributed to movement of the overlying dome. The VLP source, which also includes volumetric and single-force components, is 250 m deeper and NNW of the LP source, at the SW edge of the 1980s lava dome. The volumetric component points to the compression and expansion of a shallow, magma-filled sill, which is subparallel to the hydrothermal crack imaged at the LP source, coupled with a smaller component of expansion and compression of a dike. The single-force components are due to mass advection in the magma conduit. The location, geometry and timing of the sources suggest the VLP and LP events are caused by perturbations of a common crack system.

Journal of Geophysical Research B: Solid Earth↗

USGS2013

Multi-temporal maps of the Montaguto earth flow in southern Italy from 1954 to 2010

Historical movement of the Montaguto earth flow in southern Italy has periodically destroyed residences and farmland, and damaged the Italian National Road SS90 and the Benevento-Foggia National Railway. This paper provides maps from an investigation into the evolution of the Montaguto earth flow from 1954 to 2010. We used aerial photos, topographic maps, LiDAR data, satellite images, and field observations to produce multi-temporal maps. The maps show the spatial and temporal distribution of back-tilted surfaces, flank ridges, and normal, thrust, and strike-slip faults. Springs, creeks, and ponds are also shown on the maps. The maps provide a basis for interpreting how basal and lateral boundary geometries influence earth-flow behavior and surface-water hydrology.

Montaguto Earth Flow↗

USGS2013

Radiometric cross-calibration of EO-1 ALI with L7 ETM+ and Terra MODIS sensors using near-simultaneous desert observations

The Earth Observing-1 (EO-1) satellite was launched on November 21, 2000, as part of a one-year technology demonstration mission. The mission was extended because of the value it continued to add to the scientific community. EO-1 has now been operational for more than a decade, providing both multispectral and hyperspectral measurements. As part of the EO-1 mission, the Advanced Land Imager (ALI) sensor demonstrates a potential technological direction for the next generation of Landsat sensors. To evaluate the ALI sensor capabilities as a precursor to the Operational Land Imager (OLI) onboard the Landsat Data Continuity Mission (LDCM, or Landsat 8 after launch), its measured top-of-atmosphere (TOA) reflectances were compared to the well-calibrated Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) and the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) sensors in the reflective solar bands (RSB). These three satellites operate in a near-polar, sun-synchronous orbit 705 km above the Earth's surface. EO-1 was designed to fly one minute behind L7 and approximately 30 minutes in front of Terra. In this configuration, all the three sensors can view near-identical ground targets with similar atmospheric, solar, and viewing conditions. However, because of the differences in the relative spectral response (RSR), the measured physical quantities can be significantly different while observing the same target. The cross-calibration of ALI with ETM+ and MODIS was performed using near-simultaneous surface observations based on image statistics from areas observed by these sensors over four desert sites (Libya 4, Mauritania 2, Arabia 1, and Sudan 1). The differences in the measured TOA reflectances due to RSR mismatches were compensated by using a spectral band adjustment factor (SBAF), which takes into account the spectral profile of the target and the RSR of each sensor. For this study, the spectral profile of the target comes from the near-simultaneous EO-1 Hyperion data over these sites. The results indicate that the TOA reflectance measurements for ALI agree with those of ETM+ and MODIS to within 5% after the application of SBAF.

Arabia↗