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At least 487 records · Page 27Linked to original sources

Investigation of internal friction in fused quartz, steel, Plexiglass, and Westerly granite from 0.01 to 1.00 Hertz at 10-8 to 10-7 strain amplitude

A detailed evaluation on the method of internal friction measurement by the stress-strain hysteresis loop method from 0.01 to 1 Hz at 10 −8 to 10 −7 strain amplitude and 23.9°C is presented. Significant systematic errors in relative phase measurement can result from convex end surfaces of the sample and stress sensor and from end surface irregularities such as nicks and asperities. Preparation of concave end surfaces polished to optical smoothness having a radius of curvature >3.6×10 4 cm reduces the systematic error in relative phase measurements to <(5.5±2.2)×10 −4 radians. The values of Q E −1 (internal friction under uniaxial compression) determined from the relative phase measurements are | Q E −1 – Q s −1 |< 2.8×10 −3 for the tool steel sample and | Q E −1 – Q s −1 |< 2.2×10 −3 for the Westerly granite sample, where Q s −1 is the internal friction of the fused quartz stress sensor under uniaxial compression. These values are consistent with those inferred from the relative modulus dispersion data also presented in this paper. The polymethyl methacrylate (PMM, trade name Plexiglass) sample shows high values of internal friction ( Q E −1 ≅5×10 −2 ) with strong frequency dependence and with a maximum in Q E −1 at ≅0.4 Hz.

Journal of Geophysical Research Solid Earth↗

Strong Motion Instrumentation of Seismically-Strengthened Port Structures in California by CSMIP

The California Strong Motion Instrumentation Program (CSMIP) has instrumented five port structures. Instrumentation of two more port structures is underway and another one is in planning. Two of the port structures have been seismically strengthened. The primary goals of the strong motion instrumentation are to obtain strong earthquake shaking data for verifying seismic analysis procedures and strengthening schemes, and for post-earthquake evaluations of port structures. The wharves instrumented by CSMIP were recommended by the Strong Motion Instrumentation Advisory Committee, a committee of the California Seismic Safety Commission. Extensive instrumentation of a wharf is difficult and would be impossible without the cooperation of the owners and the involvement of the design engineers. The instrumentation plan for a wharf is developed through study of the retrofit plans of the wharf, and the strong-motion sensors are installed at locations where specific instrumentation objectives can be achieved and access is possible. Some sensor locations have to be planned during design; otherwise they are not possible to install after construction. This paper summarizes the two seismically-strengthened wharves and discusses the instrumentation schemes and objectives. ?? 2009 ASCE.

Conference Paper↗

Characterizing seasonal and diel vertical movement and habitat use of lake whitefish (Coregonus clupeaformis) in Clear Lake, Maine

Seasonal and daily vertical activity of lake whitefish Coregonus clupeaformis was studied in Clear Lake, Maine (253 ha), using acoustic telemetry from November 2004 to June 2009. Twenty adult lake whitefish were tagged with acoustic tags that had either a depth sensor or both depth and temperature sensors to assess vertical habitat use at a seasonal and daily resolution. Vertical habitat selection varied seasonally and was strongly influenced by temperature. Between December and April, when the lake was covered with ice, surface temperature was below 2&deg;C and tagged individuals occupied deep areas of the lake (&sim;15 m). After ice-out, fish ascended into shallow waters (&sim;5 m), responding to increased water temperature and possibly to greater foraging opportunity. When surface water temperatures exceeded 20&deg;C, fish descended below the developing thermocline (&sim;9 m), where they remained until surface temperatures fell below 20&deg;C; fish then ascended into shallower depths, presumably for feeding and spawning. Through the winter, fish remained in thermal habitats that were warmer than the surface temperatures; in the summer, they selected depths with thermal habitats below 15&deg;C. Though the amplitude varied greatly across seasons, lake whitefish displayed a strong diurnal pattern of activity as measured by vertical velocities. Fish were twofold more active during spring, summer, and fall than during winter. Lake whitefish exhibited diel vertical migrations, rising in the water column during nighttime and occupying deeper waters during the day. This pattern was more pronounced in the spring and fall and far less prominent during winter and summer. The strong linkage between temperature and habitat use may limit the current range of lake whitefish and may be directly impacted by climatic change.

Main↗

Terrestrial remote sensing science and algorithms planned for EOS/MODIS

The Moderate Resolution Imaging Spectroradiometer (MODIS) will be the primary daily global monitoring sensor on the NASA Earth Observing System (EOS) satellites, scheduled for launch on the EOS-AM platform in June 1998 and the EOS-PM platform in December 2000. MODIS is a 36 channel radiometer covering 0·415-14·235 μm wavelengths, with spatial resolution from 250 m to 1 km at nadir. MODIS will be the primary EOS sensor for providing data on terrestrial biospheric dynamics and process activity. This paper presents the suite of global land products currently planned for EOSDIS implementation, to be developed by the authors of this paper, the MODIS land team (MODLAND). These include spectral albedo, land cover, spectral vegetation indices, snow and ice cover, surface temperature and fire, and a number of biophysical variables that will allow computation of global carbon cycles, hydrologic balances and biogeochemistry of critical greenhouse gases. Additionally, the regular global coverage of these variables will allow accurate surface change detection, a fundamental determinant of global change.

International Journal of Remote Sensing↗

Vegetation monitoring for Guatemala: a comparison between simulated VIIRS and MODIS satellite data

The advanced very high resolution radiometer (AVHRR) and moderate resolution imaging spectroradiometer (MODIS) data are being widely used for vegetation monitoring across the globe. However, sensors will discontinue collecting these data in the near future. National Aeronautics and Space Administration is planning to launch a new sensor, visible infrared imaging radiometer suite (VIIRS), to continue to provide satellite data for vegetation monitoring. This article presents a case study of Guatemala and compares the simulated VIIRS-Normalized Difference Vegetation Index (NDVI) with MODIS-NDVI for four different dates each in 2003 and 2005. The dissimilarity between VIIRS-NDVI and MODIS-NDVI was examined on the basis of the percent difference, the two-tailed student's t -test, and the coefficient of determination, R 2 . The per cent difference was found to be within 3%, the p -value ranged between 0.52 and 0.99, and R 2 exceeded 0.88 for all major types of vegetation (basic grains, rubber, sugarcane, coffee and forests) found in Guatemala. It was therefore concluded that VIIRS will be almost equally capable of vegetation monitoring as MODIS.

Geocarto International↗

Towards understanding relationships between atmospheric pressure variations and long-period horizontal seismic data: A case study

Variations in atmospheric pressure have long been known to introduce noise in long-period (>10 s) seismic records. This noise can overwhelm signals of interest such as normal modes and surface waves. Generally, this noise is most pronounced on the horizontal components where it arises due to tilting of the seismometer in response to changes in atmospheric pressure. Several studies have suggested methodologies for correcting unwanted pressure-induced noise using collocated microbarograph records. However, how applicable these corrections are to varying geologic settings and installation types (e.g. vault versus post-hole) is unclear. Using coefficients obtained by solving for the residuals of these corrections, we can empirically determine the sensitivity of instruments in a specific location to the influences of pressure. To better understand how long-period, pressure-induced noise changes with time and emplacement, we examine horizontal seismic records along with barometric pressure at five different Global Seismographic Network stations, all with multiple broadband seismometers. We also analyse three Streckeisen STS-2 broadband seismometers, which are collocated with a microbarograph, at the Albuquerque Seismological Laboratory. We observe periods of high magnitude-squared-coherence (γ 2 -coherence; γ 2 > 0.8) between the seismic and pressure signals which fluctuate through time, frequency, and even between seismic instruments in the same vault. These observations suggest that these tilt-generated signals are highly sensitive to very local (<10 m) site effects. However, we find that in cases where instruments are not located at a large depth (<100 m), the pressure-induced noise is polarized in a nearly constant direction that is consistent with local topographic features or the geometry of the vault. We also find that borehole instruments at a large depth (>100 m) appear to be unaffected by pressure-loading mechanisms outlined by Sorrells (1971) but possibly by Newtonian attraction. Correlating the induced-noise polarization direction with times of high coherence, we work to identify sensors that are ultimately limited by pressure-induced horizontal noise as well as period bands that can benefit from pressure corrections. We find that while the situation is complex, each sensor appears to have its own unique response to pressure. Our findings suggest that we can determine empirical relationships between pressure and induced tilt on a case by case basis.

Geophysical Journal International↗

An overview of the web-based Google Earth coincident imaging tool

The Committee on Earth Observing Satellites (CEOS) Visualization Environment (COVE) tool is a browser-based application that leverages Google Earth web to display satellite sensor coverage areas. The analysis tool can also be used to identify near simultaneous surface observation locations for two or more satellites. The National Aeronautics and Space Administration (NASA) CEOS System Engineering Office (SEO) worked with the CEOS Working Group on Calibration and Validation (WGCV) to develop the COVE tool. The CEOS member organizations are currently operating and planning hundreds of Earth Observation (EO) satellites. Standard cross-comparison exercises between multiple sensors to compare near-simultaneous surface observations and to identify corresponding image pairs are time-consuming and labor-intensive. COVE is a suite of tools that have been developed to make such tasks easier.

Conference Paper↗

ASTER satellite observations for international disaster management

When lives are threatened or lost due to catastrophic disasters, and when massive financial impacts are experienced, international emergency response teams rapidly mobilize to provide urgently required support. Satellite observations of affected areas often provide essential insight into the magnitude and details of the impacts. The large cost and high complexity of developing and operating satellite flight and ground systems encourages international collaboration in acquiring imagery for such significant global events in order to speed delivery of critical information to help those affected, and optimize spectral, spatial, and temporal coverage of the areas of interest. The International Charter-Space and Major Disasters was established to enable such collaboration in sensor tasking during times of crisis and is often activated in response to calls for assistance from authorized users. Insight is provided from a U.S. perspective into sensor support for Charter activations and other disaster events through a description of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), which has been used to support emergency situations for over a decade through its expedited tasking and near real-time data delivery capabilities. Examples of successes achieved and challenges encountered in international collaboration to develop related systems and fulfill tasking requests suggest operational considerations for new missions as well as areas for future enhancements.

Proceedings of IEEE↗

New generation hyperspectral data From DESIS compared to high spatial resolution PlanetScope data for crop type classification

Thoroughly investigating the characteristics of new generation hyperspectral and high spatial resolution spaceborne sensors will advance the study of agricultural crops. Therefore, we compared the performances of hyperspectral Deutsches Zentrum fur Luftund Raumfahrt- (DLR) Earth Sensing Imaging Spectrometer (DESIS) and high spatial resolution PlanetScope in classifying eight crop types in California's Central Valley during the 2020 growing season. The DESIS sensor onboard the International Space Station collects data at 235 hyperspectral narrowbands (HNB) each with 2.55 nm bandwidth from 400–1000 nm and 30 m spatial resolution. In contrast, PlanetScope Dove-R data have four multispectral broadbands (MBB) with 3–4 m spatial resolution. We obtained best classification accuracies using 14 DESIS HNB from the August 2020 image, with an overall accuracy of 85% and producer's and user's accuracies of 72–100% and 75–100%, respectively, for the eight crops. The best classification accuracies using PlanetScope data were obtained using an image mosaic pair from June and August 2020; this resulted in an overall accuracy of 79% and producer's and user's accuracies of 56–100% and 61–100%, respectively. Combining the best 14 DESIS HNB from August 2020 with the 4 PlanetScope MBB from August 2020 yielded an overall accuracy of 82% and producer's and user's accuracies of 65–100% and 60–94%, respectively. On one-to-one single date comparisons of DESIS versus PlanetScope data, the hyperspectral data always outperformed high spatial resolution data in crop type classification. Nevertheless, high spatial resolution data will remain invaluable in assessing within-field variability and crop biophysical/biochemical modeling in precision agriculture.

IEEE Journal of Selected Topics in Applied Earth O↗

Estimation of forest fuel load from radar remote sensing

Understanding fire behavior characteristics and planning for fire management require maps showing the distribution of wildfire fuel loads at medium to fine spatial resolution across large landscapes. Radar sensors from airborne or spaceborne platforms have the potential of providing quantitative information about the forest structure and biomass components that can be readily translated to meaningful fuel load estimates for fire management. In this paper, we used multifrequency polarimetric synthetic aperture radar (SAR) imagery acquired over a large area of the Yellowstone National Park by the Airborne SAR sensor to estimate the distribution of forest biomass and canopy fuel loads. Semiempirical algorithms were developed to estimate crown and stem biomass and three major fuel load parameters, namely: 1) canopy fuel weight; 2) canopy bulk density; and 3) foliage moisture content. These estimates, when compared directly to measurements made at plot and stand levels, provided more than 70% accuracy and, when partitioned into fuel load classes, provided more than 85% accuracy. Specifically, the radar-generated fuel parameters were in good agreement with the field-based fuel measurements, resulting in coefficients of determination of R2 = 85 for the canopy fuel weight, R 2 = 0.84 for canopy bulk density, and R2 =0.78 for the foliage biomass. ?? 2007 IEEE.

IEEE Transactions on Geoscience and Remote Sensing↗

SSTL UK-DMC SLIM-6 data quality assessment

Satellite data from the Surrey Satellite Technology Limited (SSTL) United Kingdom (UK) Disaster Monitoring Constellation (DMC) were assessed for geometric and radiometric quality. The UK-DMC Surrey Linear Imager 6 (SLIM-6) sensor has a 32-m spatial resolution and a ground swath width of 640 km. The UK-DMC SLIM-6 design consists of a three-band imager with green, red, and near-infrared bands that are set to similar bandpass as Landsat bands 2, 3, and 4. The UK-DMC data consisted of imagery registered to Landsat orthorectified imagery produced from the GeoCover program. Relief displacements within the UK-DMC SLIM-6 imagery were accounted for by using global 1-km digital elevation models available through the Global Land One-km Base Elevation (GLOBE) Project. Positional accuracy and relative band-to-band accuracy were measured. Positional accuracy of the UK-DMC SLIM-6 imagery was assessed by measuring the imagery against digital orthophoto quadrangles (DOQs), which are designed to meet national map accuracy standards at 1 : 24 000 scales; this corresponds to a horizontal root-mean-square accuracy of about 6 m. The UK-DMC SLIM-6 images were typically registered to within 1.0-1.5 pixels to the DOQ mosaic images. Several radiometric artifacts like striping, coherent noise, and flat detector were discovered and studied. Indications are that the SSTL UK-DMC SLIM-6 data have few artifacts and calibration challenges, and these can be adjusted or corrected via calibration and processing algorithms. The cross-calibration of the UK-DMC SLIM-6 and Landsat 7 Enhanced Thematic Mapper Plus was performed using image statistics derived from large common areas observed by the two sensors.

IEEE Transactions on Geoscience and Remote Sensing↗

Impact of spectral resolution on quantifying cyanobacteria in lakes and reservoirs: A machine-learning assessment

Cyanobacterial harmful algal blooms are an increasing threat to coastal and inland waters. These blooms can be detected using optical radiometers due to the presence of phycocyanin (PC) pigments. The spectral resolution of best-available multispectral sensors limits their ability to diagnostically detect PC in the presence of other photosynthetic pigments. To assess the role of spectral resolution in the determination of PC, a large (N = 905) database of colocated in situ radiometric spectra and PC are employed. We first examine the performance of selected widely used machine-learning (ML) models against that of benchmark algorithms for hyperspectral remote sensing reflectance ( R r s ) spectra resampled to the spectral configuration of the Hyperspectral Imager for the Coastal Ocean (HICO) with a full-width at half-maximum (FWHM) of < 6 nm. Results show that the multilayer perceptron (MLP) neural network applied to HICO spectral configurations (median errors < 65%) outperforms other ML models. This model is subsequently applied to R r s spectra resampled to the band configuration of existing satellite instruments and of the one proposed for the next Landsat sensor. These results confirm that employing MLP models to estimate PC from hyperspectral data delivers tangible improvements compared with retrievals from multispectral data and benchmark algorithms (with median errors between ~73% and 126%) and shows promise for developing a globally applicable cyanobacteria measurement approach.

IEEE Transactions in Geoscience and Remote Sensing↗

Across-track tilt concept for sun glint mitigation in future Earth-observing missions

Sun glint is a major limitation for spaceborne optical remote sensing of aquatic environments, particularly in tropical and subtropical regions. By dominating the at-sensor radiance, sun glint complicates atmospheric correction and reduces the quality of aquatic reflectance products derived across Earth observation missions. This study presents a machine learning framework to quantify sun glint probability and evaluates the across-track tilt observational concept as a potential sun glint mitigation approach for satellite remote sensing missions. More than 14,000 cloud-free Landsat 8 and 9 scenes were analyzed to quantify glint occurrence as a function of sun-sensor geometry, latitude, and season. Logistic regression and machine learning models identified solar zenith angle (SZA), wind speed, and viewing zenith angle (VZA) as the primary predictors of sun glint probability, achieving >98% classification accuracy. Sun glint contamination was found to be negligible for SZA > 40° but frequent at SZA <35°, particularly in forward-scattering geometries. Introducing a 3° across-track westward tilt reduces the proportion of glint-contaminated pixels by ~21% in tropical and subtropical regions, while larger tilts of 6°, 9°, and 12° yield reductions of 43%, 59%, and 74%, respectively. These findings underscore the value of incorporating glint mitigation strategies in future Earth observing mission designs. A modest across-track tilt, combined with post-acquisition glint detection and correction, offers a practical pathway to increasing the availability of high-quality aquatic observations for monitoring inland and coastal water quality and ecosystems.

IEEE Transactions on Geoscience and Remote Sensing↗

Vocal activity as a low cost and scalable index of seabird colony size

Although wildlife conservation actions have increased globally in number and complexity, the lack of scalable, cost-effective monitoring methods limits adaptive management and the evaluation of conservation efficacy. Automated sensors and computer-aided analyses provide a scalable and increasingly cost-effective tool for conservation monitoring. A key assumption of automated acoustic monitoring of birds is that measures of acoustic activity at colony sites are correlated with the relative abundance of nesting birds. We tested this assumption for nesting Forster's terns (Sterna forsteri) in San Francisco Bay for 2 breeding seasons. Sensors recorded ambient sound at 7 colonies that had 15–111 nests in 2009 and 2010. Colonies were spaced at least 250 m apart and ranged from 36 to 2,571 m 2 . We used spectrogram cross-correlation to automate the detection of tern calls from recordings. We calculated mean seasonal call rate and compared it with mean active nest count at each colony. Acoustic activity explained 71% of the variation in nest abundance between breeding sites and 88% of the change in colony size between years. These results validate a primary assumption of acoustic indices; that is, for terns, acoustic activity is correlated to relative abundance, a fundamental step toward designing rigorous and scalable acoustic monitoring programs to measure the effectiveness of conservation actions for colonial birds and other acoustically active wildlife.

California↗

Improved vertical streambed flux estimation using multiple diurnal temperature methods in series

Analytical solutions that use diurnal temperature signals to estimate vertical fluxes between groundwater and surface water based on either amplitude ratios ( A r ) or phase shifts (Δ ϕ ) produce results that rarely agree. Analytical solutions that simultaneously utilize A r and Δ ϕ within a single solution have more recently been derived, decreasing uncertainty in flux estimates in some applications. Benefits of combined ( A r Δ ϕ ) methods also include that thermal diffusivity and sensor spacing can be calculated. However, poor identification of either A r or Δ ϕ from raw temperature signals can lead to erratic parameter estimates from A r Δ ϕ methods. An add-on program for VFLUX 2 is presented to address this issue. Using thermal diffusivity selected from an A r Δ ϕ method during a reliable time period, fluxes are recalculated using an A r method. This approach maximizes the benefits of the A r and A r Δ ϕ methods. Additionally, sensor spacing calculations can be used to identify periods with unreliable flux estimates, or to assess streambed scour. Using synthetic and field examples, the use of these solutions in series was particularly useful for gaining conditions where fluxes exceeded 1 m/d.

Groundwater↗

Use of behavioral and physiological indicators to evaluate Scaphirhynchus sturgeon spawning success

Thirty gravid, female shovelnose sturgeon ( Scaphirhynchus platorynchus ) were captured in the Lower Missouri River in March 2004 to evaluate the effectiveness of physiology, telemetry and remote sensor technology coupled with change point analysis in identifying when and where Scaphirhynchus sturgeon spawn. Captured sturgeons were instrumented with ultrasonic transmitters and with archival data storage tags (DST) that recorded temperature and pressure. Female sturgeon were tracked through the suspected spawning period. Thereafter, attempts were made to recapture fish to evaluate spawning success. At the time of transmitter implantation, blood and an ovarian biopsy were taken. Reproductive hormones and cortisol were measured in blood. Polarization indices and germinal vesicle breakdown were assessed on the biopsied oocytes to determine readiness to spawn. Behavioral data collected using telemetry and DST sensors were used to determine the direction and magnitude of possible spawning-related movements and to identify the timing of potential spawning events. Upon recapture observations of the ovaries and blood chemistry provided measures of spawning success and comparative indicators to explain differences in observed behavior. Behavioral and physiological indicators of spawning interpreted along with environmental measures may assist in the determination of variables that may cue sturgeon reproduction and the conditions under which sturgeon successfully spawn.

Journal of Applied Ichthyology↗

Landsat Data Continuity Mission, now Landsat-8: six months on-orbit

The Landsat Data Continuity Mission (LDCM) with two pushbroom Earth-imaging sensors, the Operational Land Imager (OLI) and the Thermal InfraRed Sensor (TIRS), was launched on February 11, 2013. Its on-orbit check out period or commissioning phase lasted about 90 days. During this phase the spacecraft and its instruments were activated, operationally tested and their performance verified. In addition, during this period, the spacecraft was temporarily placed in an intermediary orbit where it drifted relative to the Landsat-7 spacecraft, providing near simultaneous imaging for about 3 days, allowing data comparison and cross calibration. After this tandem-imaging period, LDCM was raised to its final altitude and placed in the position formerly occupied by Landsat-5, i.e., 8 days out of phase with Landsat-7, with about a 10:10 AM equatorial crossing time. At the end of commissioning, the satellite was transferred to the United States Geological Survey (USGS), officially renamed Landsat-8 and declared operational. Data were made available to the public beginning May 31, 2013. The performance of the satellite and two instruments has generally been excellent as evidenced in the quality of the distributed data products. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Conference Paper↗

Landsat 9: Ready for Launch

Landsat 9 is in its final preparations for launch from Vandenberg Space Force Base on 16 September 2021. It has completed its environmental testing at Northrop Grumman Space (NGSP) in Gilbert, Arizona and has been transported to its California launch site. It will be launched into a 705 km orbit replacing Landsat 7 to provide 8-day Earth land mass coverage in concert with Landsat 8. Landsat 8 carries the first Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS); Landsat 9 carries the second of each: OLI-2 and TIRS-2. Once launched it will undergo a 90-day activation, checkout, characterization and calibration, a.k.a. commissioning phase before transitioning to operations. For a several-day period during this commissioning phase, Landsat 9 will under-fly Landsat 8, allowing near simultaneous data collection by both sensors of common Earth targets. These data will be used to compare the radiometric calibrations of the instruments and allow for adjustments of processing parameters to provide more consistent data products.

Conference Paper↗