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At least 361 records · Page 20Linked to original sources
USGS2002

Seasonal comparisons of sea ice concentration estimates derived from SSM/I, OKEAN, and RADARSAT data

The Special Sensor Microwave Imager (SSM/I) microwave satellite radiometer and its predecessor SMMR are primary sources of information for global sea ice and climate studies. However, comparisons of SSM/I, Landsat, AVHRR, and ERS-1 synthetic aperture radar (SAR) have shown substantial seasonal and regional differences in their estimates of sea ice concentration. To evaluate these differences, we compared SSM/I estimates of sea ice coverage derived with the NASA Team and Bootstrap algorithms to estimates made using RADARSAT, and OKEAN-01 satellite sensor data. The study area included the Barents Sea, Kara Sea, Laptev Sea, and adjacent parts of the Arctic Ocean, during October 1995 through October 1999. Ice concentration estimates from spatially and temporally near-coincident imagery were calculated using independent algorithms for each sensor type. The OKEAN algorithm implemented the satellite's two-channel active (radar) and passive microwave data in a linear mixture model based on the measured values of brightness temperature and radar backscatter. The RADARSAT algorithm utilized a segmentation approach of the measured radar backscatter, and the SSM/I ice concentrations were derived at National Snow and Ice Data Center (NSIDC) using the NASA Team and Bootstrap algorithms. Seasonal and monthly differences between SSM/I, OKEAN, and RADARSAT ice concentrations were calculated and compared. Overall, total sea ice concentration estimates derived independently from near-coincident RADARSAT, OKEAN-01, and SSM/I satellite imagery demonstrated mean differences of less than 5.5% (S.D.<9.5%) during the winter period. Differences between the SSM/I NASA Team and the SSM/I Bootstrap concentrations were no more than 3.1% (S.D.<5.4%) during this period. RADARSAT and OKEAN-01 data both yielded higher total ice concentrations than the NASA Team and the Bootstrap algorithms. The Bootstrap algorithm yielded higher total ice concentrations than the NASA Team algorithm. Total ice concentrations derived from OKEAN-01 and SSM/I satellite imagery were highly correlated during winter, spring, and fall, with mean differences of less than 8.1% (S.D.<15%) for the NASA Team algorithm, and less than 2.8% (S.D.<13.8%) for the Bootstrap algorithm. Respective differences between SSM/I NASA Team and SSM/I Bootstrap total concentrations were less than 5.3% (S.D.<6.9%). Monthly mean differences between SSM/I and OKEAN differed annually by less than 6%, with smaller differences primarily in winter. The NASA Team and Bootstrap algorithms underestimated the total sea ice concentrations relative to the RADARSAT ScanSAR no more than 3.0% (S.D.<9%) and 1.2% (S.D.<7.5%) during cold months, and no more than 12% and 7% during summer, respectively. ScanSAR tended to estimate higher ice concentrations for ice concentrations greater than 50%, when compared to SSM/I during all months. ScanSAR underestimated total sea ice concentration by 2% compared to the OKEAN-01 algorithm during cold months, and gave an overestimation by 2% during spring and summer months. Total NASA Team and Bootstrap sea ice concentration estimates derived from coincident SSM/I and OKEAN-01 data demonstrated mean differences of no more than 5.3% (S.D.<7%), 3.1% (S.D.<5.5%), 2.0% (S.D.<5.5%), and 7.3% (S.D.<10%) for fall, winter, spring, and summer periods, respectively. Large disagreements were observed between the OKEAN and NASA Team results in spring and summer for estimates of the first-year (FY) and multiyear (MY) age classes. The OKEAN-01 algorithm and data tended to estimate, on average, lower concentrations of young or FY ice and higher concentrations of total and MY ice for all months and seasons. Our results contribute to the growing body of documentation about the levels of disparity obtained when seasonal sea ice concentrations are estimated using various types of satellite data and algorithms.

Remote Sensing of Environment↗
USGS2021

Optical properties of water for prediction of wastewater contamination, human-associated bacteria, and fecal indicator bacteria in surface water at three watershed scales

Relations between spectral absorbance and fluorescence properties of water and human-associated and fecal indicator bacteria were developed for facilitating field sensor applications to estimate wastewater contamination in waterways. Leaking wastewater conveyance infrastructure commonly contaminates receiving waters. Methods to quantify such contamination can be time consuming, expensive, and often nonspecific. Human-associated bacteria are wastewater specific but require discrete sampling and laboratory analyses, introducing latency. Human sewage has fluorescence and absorbance properties different than those of natural waters. To assist real-time field sensor development, this study investigated optical properties for use as surrogates for human-associated bacteria to estimate wastewater prevalence in environmental waters. Three spatial scales were studied: Eight watershed-scale sites, five subwatershed-scale sites, and 213 storm sewers and open channels within three small watersheds (small-scale sites) were sampled (996 total samples) for optical properties, human-associated bacteria, fecal indicator bacteria, and, for selected samples, human viruses. Regression analysis indicated that bacteria concentrations could be estimated by optical properties used in existing field sensors for watershed and subwatershed scales. Human virus occurrence increased with modeled human-associated bacteria concentration, providing confidence in these regressions as surrogates for wastewater contamination. Adequate regressions were not found for small-scale sites to reliably estimate bacteria concentrations likely due to inconsistent local sanitary sewer inputs.

Michigan, New York, Ohio, Wisconsin↗
USGS2004

Comparison of MODIS and AVHRR 16-day normalized difference vegetation index composite data

Normalized difference vegetation index (NDVI) data derived from visible and near-infrared data acquired by the MODIS and AVHRR sensors were compared over the same time periods and a variety of land cover classes within the conterminous USA. The relationship between the AVHRR derived NDVI values and those of future sensors is critical to continued long term monitoring of land surface properties. The results indicate that the 16-day composite values are quite similar over the 23 intervals of 2001 that were analyzed, and a linear relationship exists between the NDVI values from the two sensors. The composite AVHRR NDVI data were associated with over 90% of the variation in the MODIS NDVI values. Copyright 2004 by the American Geophysical Union.

Geophysical Research Letters↗
USGS2023

UAS-Based Observations of Infrasound Directionality at Stromboli Volcano, Italy

Infrasound (low frequency sound waves) can be used to monitor and characterize volcanic eruptions. However, infrasound sensors are usually placed on the ground, thus providing a limited sampling of the acoustic radiation pattern that can bias source size estimates. We present observations of explosive eruptions from a novel uncrewed aircraft system (UAS)-based infrasound sensor platform that was strategically hovered near the active vents of Stromboli volcano, Italy. We captured eruption infrasound from short-duration explosions and jetting events. While potential vertical directionality was inconclusive for the short-duration explosion, we find that jetting events exhibit vertical sound directionality that was observed with a UAS close to vertical. This directionality would not have been observed using only traditional deployments of ground-based infrasound sensors, but is consistent with jet noise theory. This proof-of-concept study provides unique information that can improve our ability to characterize and quantify the directionality of volcanic eruptions and their associated hazards.

Stromboli Volcano↗
USGS2010

Evaluation of the energy budget method of determining evaporation at Williams Lake, Minnesota, using alternative instrumentation and study approaches

Best estimates of evaporation at Williams Lake, north central Minnesota, were determined by the energy budget method using optimum sensors and optimum placement of sensors. These best estimates are compared with estimates derived from using substitute data to determine the effect of using less accurate sensors, simpler methods, or remotely measured data. Calculations were made for approximately biweekly periods during five open water seasons. For most of the data substitutions that affected the Bowen ratio, new values of evaporation differed little from best estimates. The three data substitution methods that caused the largest deviations from the best evaporation estimates were (1) using changes in the daily average surface water temperature as an indicator of the lake heat storage term, (2) using shortwave radiation, air temperature, and atmospheric vapor pressure data from a site 110 km away, and (3) using an analog surface water temperature probe. Recalculations based on these data substitutions resulted in differences from the best estimates as much as 89%, 21%, and 10%, respectively. The data substitution method that provided evaporation values that most closely matched the best estimates was measurement of the lake heat storage term at one location in the lake, rather than at 16 locations. Evaporation values resulting from this substitution method usually were within 2% of the best estimates.

Minnesota↗
USGS2017

Fusing MODIS with Landsat 8 data to downscale weekly normalized difference vegetation index estimates for central Great Basin rangelands, USA

Data fused from distinct but complementary satellite sensors mitigate tradeoffs that researchers make when selecting between spatial and temporal resolutions of remotely sensed data. We integrated data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra satellite and the Operational Land Imager sensor aboard the Landsat 8 satellite into four regression-tree models and applied those data to a mapping application. This application produced downscaled maps that utilize the 30-m spatial resolution of Landsat in conjunction with daily acquisitions of MODIS normalized difference vegetation index (NDVI) that are composited and temporally smoothed. We produced four weekly, atmospherically corrected, and nearly cloud-free, downscaled 30-m synthetic MODIS NDVI predictions (maps) built from these models. Model results were strong with R 2 values ranging from 0.74 to 0.85. The correlation coefficients ( r ≥ 0.89) were strong for all predictions when compared to corresponding original MODIS NDVI data. Downscaled products incorporated into independently developed sagebrush ecosystem models yielded mixed results. The visual quality of the downscaled 30-m synthetic MODIS NDVI predictions were remarkable when compared to the original 250-m MODIS NDVI. These 30-m maps improve knowledge of dynamic rangeland seasonal processes in the central Great Basin, United States, and provide land managers improved resource maps.

Great Basin rangelands↗
USGS2022

Characteristics, relationships and precision of direct acoustic-to-seismic coupling measurements from local explosions

Acoustic energy originating from explosions, sonic booms, bolides and thunderclaps have been recorded on seismometers since the 1950s. Direct pressure loading from the passing acoustic wave has been modelled and consistently observed to produce ground deformations of the near surface that have retrograde elliptical particle motions. In the past decade, increased deployments of colocated seismometers and infrasound sensors have driven efforts to use the transfer function between direct acoustic-to-seismic coupling to infer near-surface material properties including seismic velocity structure and elastic moduli. In this study, we use a small aperture (≈600 m) array of broadband seismometers installed in different manners and depths in both granite and sedimentary overburden to understand the fundamental nature and repeatability of seismic excitation from 1 to 15 Hz using horizontally propagating acoustic waves generated by 97 local (2–10 km) explosions. In agreement with modelling, we find that the ground motions induced by acoustic-to-seismic coupling attenuate rapidly with depth. We confirm the modelled relation between acoustic and ground motion amplitudes, but show that within one acoustic wavelength, the uncertainty in the transfer coefficient between seismic and acoustic energy at a given seismic station increases linearly with separation distance between the seismic and acoustic sensor. We attribute this observation to the rapid decorrelation of the infrasonic wavefield across small spatial scales and recommend colocating seismic and infrasound sensors for use in studies seeking to invert for near-surface material properties. Additionally, contrary to acoustic-to-seismic coupling theory and prior observations, we find that seismometers emplaced in granite do not record retrograde elliptical particle motions in response to direct pressure loading. We rule out seismometer tilt effects as a likely source of this observations and suggest that existing models of acoustic-to-seismic excitation may be too simplistic for seismometers placed in high rigidity materials.

Geophysical Journal International↗
USGS2018

Rayleigh wave ellipticity measurement uncertainty across the IRIS/USGS and New China Digital Seismograph Networks

Long-period Rayleigh wave horizontal to vertical amplitude (H/V) ratios at a station provide information about local earth structure that is complementary to phase velocity. However, a number of studies have observed that significant scatter appears in these measurements making it difficult to use H/V ratio measurements to resolve earth structure. Some of the scatter in these measurements has been attributed to local geological structure while some has remained unaccounted for. Most Global Seismographic Network (GSN) stations contain two nearby high-quality broad-band seismometers (e.g. in the same vault, but on different piers or in different boreholes). For each broad-band sensor in the IRIS/USGS component of the GSN, we estimate H/V ratios of fundamental mode Rayleigh waves using M > 6.5 earthquakes from 2001 to 2018 (around 19 000 measurements). We compute these ratios at a number of discrete periods (25, 50, 75, 100 and 150 s) and find that for well-isolated Rayleigh waves (windows where the correlation coefficients between radial and the phase-shifted vertical components are greater than 0.9) significant scatter in H/V ratios occurs between colocated sensors (greater than 25 per cent at 100 s period). This suggests the scatter in H/V ratio measurements can be at least partially attributed to extremely local phenomena such as sensor emplacement in the vault. We also find that H/V ratios can vary as a function of event backazimuth, indicating that care must be taken when computing average ratios for a station, as a large number of events from a given region could bias H/V ratio measurements at a station.

Geophysical Journal International↗
USGS2010

Global positioning system and associated technologies in animal behaviour and ecological research

Biologists can equip animals with global positioning system (GPS) technology to obtain accurate (less than or equal to 30 m) locations that can be combined with sensor data to study animal behaviour and ecology. We provide the background of GPS techniques that have been used to gather data for wildlife studies. We review how GPS has been integrated into functional systems with data storage, data transfer, power supplies, packaging and sensor technologies to collect temperature, activity, proximity and mortality data from terrestrial species and birds. GPS 'rapid fixing' technologies combined with sensors provide location, dive frequency and duration profiles, and underwater acoustic information for the study of marine species. We examine how these rapid fixing technologies may be applied to terrestrial and avian applications. We discuss positional data quality and the capability for high-frequency sampling associated with GPS locations. We present alternatives for storing and retrieving data by using dataloggers (biologging), radio-frequency download systems (e.g. very high frequency, spread spectrum), integration of GPS with other satellite systems (e.g. Argos, Globalstar) and potential new data recovery technologies (e.g. network nodes). GPS is one component among many rapidly evolving technologies. Therefore, we recommend that users and suppliers interact to ensure the availability of appropriate equipment to meet animal research objectives.

Philosophical Transactions of the Royal Society B:↗
USGS1998

ASTER preflight and inflight calibration and the validation of level 2 products

Describes the preflight and inflight calibration approaches used for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). The system is a multispectral, high-spatial resolution sensor on the Earth Observing System's EOS-AM1 platform. Preflight calibration of ASTER uses well-characterized sources to provide calibration and preflight round-robin exercises to understand biases between the calibration sources of ASTER and other EOS sensors. These round-robins rely on well-characterized, ultra-stable radiometers. An experiment field in Yokohama, Japan, showed that the output from the source used for the visible and near-infrared (VNIR) subsystem of ASTER may be underestimated by 1.5%, but this is still within the 4% specification for the absolute, radiometric calibration of these bands. Inflight calibration will rely on vicarious techniques and onboard blackbodies and lamps. Vicarious techniques include ground-reference methods using desert and water sites. A recent joint field campaign gives confidence that these methods currently provide absolute calibration to better than 5%, and indications are that uncertainties less than the required 4% should be achievable at launch. The EOS-AM1 platform will also provide a spacecraft maneuver that will allow ASTER to see the Moon, allowing further characterization of the sensor. A method for combining the results of these independent calibration results is presented. The paper also describes the plans for validating the Level 2 data products from ASTER. These plans rely heavily upon field campaigns using methods similar to those used for the ground-reference, vicarious calibration methods.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2026

Evaluation of submersible pressure transducers for streamflow monitoring in small streams

Compact streamgages requiring minimal infrastructure and equipped with submersible pressure transducers (PTs) are increasingly used to monitor small streams, yet disparate implementations obscure their accuracy under real-world conditions. This study isolated instrumentation-derived uncertainty in stage monitoring by co-locating various combinations of commercial vented and unvented PTs with seven U.S. Geological Survey (USGS) reference streamgages on small streams. Multi-year PT stage records from compact streamgages, collected and corrected following USGS protocols, were compared to concurrent reference observations. Vented PTs demonstrated an average measurement uncertainty of ±0.005 m and mean absolute percent error (MAPE) of ±0.2%. Unvented PTs exhibited higher uncertainty, averaging ±0.009 m and ±0.4% MAPE. Although both sensor types had stage errors up to ±0.3 m, 95% of vented PT and unvented PT observations were within 0.01 and 0.02 m of reference stage, respectively. Analysis of additional unvented PTs revealed stage errors of up to ±1.2% when using barometric sensors within 15 km of the in-water sensor. Propagation of stage error to discharge using reference rating models resulted in cumulative discharge MAPEs of ±4.5% for vented and ±5.5% for unvented PTs. These findings highlight PTs as practical alternatives to reference instrumentation when deployed with standardized procedures, potentially expanding access to reliable streamflow data.

conterminous United States↗
USGS2018

Modelling sound attenuation in heterogeneous environments for improved bioacoustic sampling of wildlife populations

Acoustic sampling methods are becoming increasingly important in biological monitoring. Sound attenuation is one of the most important dynamics affecting the utility of acoustic data as it directly affects the probability of detection of individuals by acoustic sensor arrays and especially the localization of acoustic signals necessary in telemetry studies. Therefore, models of sound attenuation are necessary to make efficient use of acoustic data in ecological monitoring and assessment applications. Models of attenuation in widespread use are based on Euclidean distance between source and sensor, which is justified under spherical attenuation of sound waves in homogeneous environments. In this paper, I develop a model of sound attenuation based on a non‐Euclidean cost‐weighted distance metric which contains attenuation coefficients that characterize the attenuation of sound due to environmental heterogeneity in the vicinity of an acoustic sensor array. I show that parameters of the proposed attenuation model can be estimated by maximum likelihood using experimental data from an array of fixed sources, thus allowing investigators who use bioacoustic methods to devise explicit models of sound attenuation in situ and apply them to localization of sources and density estimation. In addition, drawing on analogy with spatial capture–recapture models, I argue that parameters of the non‐Euclidean model of attenuation can be estimated when source locations are unknown . Thus, the models can be applied to real field studies which require estimation of attenuation parameters or localization of signals. Models of heterogeneous sound attenuation allow more accurate descriptions of acoustic monitoring data, and therefore should produce more accurate estimates of ecological parameters of interest, including source locations, density, and movement trajectories. Moreover, the ability to test specific hypotheses about the effects of habitat and landscape structure on sound attenuation can improve the design of acoustic monitoring arrays and lead to more efficient deployment of acoustic sensing technology.

Methods in Ecology and Evolution↗
USGS2016

Radiometric calibration updates to the Landsat collection

The Landsat Project is planning to implement a new collection management strategy for Landsat products generated at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center. The goal of the initiative is to identify a collection of consistently geolocated and radiometrically calibrated images across the entire Landsat archive that is readily suitable for time-series analyses. In order to perform an accurate land change analysis, the data from all Landsat sensors must be on the same radiometric scale. Landsat 7 Enhanced Thematic Mapper Plus (ETM+) is calibrated to a radiance standard and all previous sensors are cross-calibrated to its radiometric scale. Landsat 8 Operational Land Imager (OLI) is calibrated to both radiance and reflectance standards independently. The Landsat 8 OLI reflectance calibration is considered to be most accurate. To improve radiometric calibration accuracy of historical data, Landsat 1-7 sensors also need to be cross-calibrated to the OLI reflectance scale. Results of that effort, as well as other calibration updates including the absolute and relative radiometric calibration and saturated pixel replacement for Landsat 8 OLI and absolute calibration for Landsat 4 and 5 Thematic Mappers (TM), will be implemented into Landsat products during the archive reprocessing campaign planned within the new collection management strategy. This paper reports on the planned radiometric calibration updates to the solar reflective bands of the new Landsat collection.

Conference Paper↗
USGS2008

MODIS and SeaWIFS on-orbit lunar calibration

The Moon plays an important role in the radiometric stability monitoring of the NASA Earth Observing System's (EOS) remote sensors. The MODIS and SeaWIFS are two of the key instruments for NASA's EOS missions. The MODIS Protoflight Model (PFM) on-board the Terra spacecraft and the MODIS Flight Model 1 (FM1) on-board the Aqua spacecraft were launched on December 18, 1999 and May 4, 2002, respectively. They view the Moon through the Space View (SV) port approximately once a month to monitor the long-term radiometric stability of their Reflective Solar Bands (RSB). SeaWIFS was launched on-board the OrbView-2 spacecraft on August 1, 1997. The SeaWiFS lunar calibrations are obtained once a month at a nominal phase angle of 7??. The lunar irradiance observed by these instruments depends on the viewing geometry. The USGS photometric model of the Moon (the ROLO model) has been developed to provide the geometric corrections for the lunar observations. For MODIS, the lunar view responses with corrections for the viewing geometry are used to track the gain change for its reflective solar bands (RSB). They trend the system response degradation at the Angle Of Incidence (AOI) of sensor's SV port. With both the lunar observation and the on-board Solar Diffuser (SD) calibration, it is shown that the MODIS system response degradation is wavelength, mirror side, and AOI dependent. Time-dependent Response Versus Scan angle (RVS) Look-Up Tables (LUT) are applied in MODIS RSB calibration and lunar observations play a key role in RVS derivation. The corrections provided by the RVS in the Terra and Aqua MODIS data from the 412 nm band are as large as 16% and 13%, respectively. For SeaWIFS lunar calibrations, the spacecraft is pitched across the Moon so that the instrument views the Moon near nadir through the same optical path as it views the Earth. The SeaWiFS system gain changes for its eight bands are calibrated using the geometrically-corrected lunar observations. The radiometric corrections to the SeaWiFS data, after more than ten years on orbit, are 19% at 865 nm, 8% at 765 nm, and 1-3% in the other bands. In this report, the lunar calibration algorithms are reviewed and the RSB gain changes observed by the lunar observations are shown for all three sensors. The lunar observations for the three instruments are compared using the USGS photometric model. The USGS lunar model facilitates the cross calibration of instruments with different spectra bandpasses whose measurements of the Moon differ in time and observing geometry.

Conference Paper↗
USGSDate not supplied

Simulation of the long term radiometric responses of the Terra MODIS and EO-1 ALI using Hyperion spectral responses over Railroad Valley Playa in Nevada (RVPN)

The Earth Observing-1 (EO-1) Hyperion instrument provides 220 spectral bands with wavelengths between 400 and 2500 nm at 30 m spatial resolution, which covers a 7.5 km by 100 km area on the ground. The EO-1 spacecraft has another multispectral sensor called the Advanced Land Imager (ALI), which has 10 spectral bands with wavelengths between 400 and 2350 nm at 30 m spatial resolution. The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Terra spacecraft was launched in Dec., 1999, and flies approximately 30 minutes behind EO-1. Nearsimultaneous observations from Terra MODIS, EO-1 ALI and Hyperion over a well characterized Railroad Valley Playa in Nevada (RVPN) target are chosen for this study. A uniform region of interest (ROI) within the playa within latitudes and longitudes of 38.48 and -115.71 to 38.53 and -115.66 was chosen for this analysis. A representation of the ground spectra during every near-simultaneous acquisition of MODIS and ALI is obtained using EO-1 Hyperion data. Using the EO-1 Hyperion derived top-of-atmosphere (TOA) reflectance profile along with the ALI and MODIS relative spectral responses (RSR), simulated reflectance for the matching band pairs is calculated. The Hyperion simulated TOA reflectance results are compared to the measured TOA reflectance trends of ALI and MODIS. The long-term measured versus simulated reflectance results are used to examine the relationships and calibration differences between the ALI and MODIS sensors.

Conference Paper↗
USGS1980

High throughput Landsat imagery film recorder

The Earth Resources Observation Systems (EROS) Data Center is responsible for processing, archiving, reproducing, and distributing satellite and aircraft remotely-sensed Earth imagery data in both film and digital format. Landsat Multispectral Scanner (MSS) and Return Beam Vidicon (RBV) sensor data alone represents a daily recording requirement of 23 billion pixels on 1000 feet of film. New satellites and sensors may double this amount of data within two years. To handle these requirements, the EROS Data Center installed an operational, multi-mode, programmable, high throughput, high resolution laser-beam film recording system directly on-line to the primary digital image processing computer. This system employs an Argon-Ion laser light source, electro-optic modulator, and rotating mirror to expose film in a flat-field line-scanned format at rates up to 400 lines per second. Laboratory-type requirements, such as a geometric fidelity of ± 0.05% and density repeatability within ± 0.05D, are maintained in a high-throughput production environment. To provide for future sensor formats, the scan rate, scanning spot size, film velocity, laser power, and number of overscans are firmware programmable for up to 16 on-line, auto-matically selectable configurations.

Conference Paper↗
USGS2019

On the utilization of synthetic and measured earthquake ground motions for designing building monitoring systems in the near-field of major faults

Agencies and research groups engaged in studying measures for enhancing the resiliency of communities have recently placed emphasis on the need for extensive implementation of monitoring systems for rapid post-event assessment of structural integrity. Designing a monitoring system for a building requires a thorough knowledge of its potential nonlinear dynamic behavior with an associated localization of interstory drift. Extending this task across a regional scale becomes even more challenging because of the heterogeneity of the buildings inventory and the limited knowledge of the characteristics of the demand especially for sites located in the near-field of a major fault. The existing observational database of near-field ground motion records is in fact too limited to constitute a comprehensive basis for full understanding of the potential range of structural response variability at different locations near a major fault. In addition, current insight into monitoring system design typically relies on linear structural models and sensors deployed on a limited number of floors. In this context, this paper presents first results of a study that combines synthetic earthquake ground motions generated from a massively parallel regional-scale geophysics wave propagation model at frequencies of engineering interest (0-5 Hz) with nonlinear tall building models. The objective is to gain new insight into the potential impact of localization of nonlinearities in structures subjected to realistic near-field earthquakes and develop a methodology that optimizes the deployment of sensors at the building and site level. In addition to the large database of synthetic motions, available real records are also employed to compare and contrast with the trends observed using synthetic ground motions. Preliminary results confirm a tendency of the demand to localize in specific portions of the structure, especially when nonlinearities occur. The building analyses provide guidance for various sensor deployment configurations associated with different probability of error in measuring structural drifts.

Conference Paper↗
USGS2009

Observing rotational and translational ground motions at the HGSD station in Taiwan from 2007 to 2008

Because of a lack of suitable instruments, rotational ground motions have not been observed until the last decade. Rotational measurements in the near field of earthquakes in Japan ( Takeo, 1998 ) indicate that rotational ground motions are many times larger than expected from the classical elasticity theory. After failing to obtain useful rotational ground motions (using similar rotational sensors as Takeo did), we deployed a far more sensitive rotational velocity sensor (R-1) at the HGSD station in eastern Taiwan. From 7 December 2004 to 12 November 2006, several hundreds of earthquakes were recorded during our Phase 1 operation. This was mostly a learning exercise to solve field operation problems; Phase 1 operations ended when our two R-1 sensors ceased to operate. A K2+R1 instrument was deployed in the spring of 2007 to start our Phase 2 operation. From 8 May 2007 to 17 February 2008, we observed 52 local earthquakes with good rotational velocity signals (with signal-to-noise ratio >∼5), together with excellent translational acceleration signals (with signal-to-noise ratio >∼10). Unfortunately, field operation was interrupted due to flooding of the HGSD station site in mid-February 2008; we just resumed normal operation in June 2008.

Bulletin of the Seismological Society of America↗