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At least 1,243 records · Page 69Linked to original sources

USGS2020

The Alaska Amphibious Community Seismic Experiment

The Alaska Amphibious Community Seismic Experiment (AACSE) is a shoreline‐crossing passive‐ and active‐source seismic experiment that took place from May 2018 through August 2019 along an ∼ 700    km "> ∼ 700 km ∼700 km long section of the Aleutian subduction zone spanning Kodiak Island and the Alaska Peninsula. The experiment featured 105 broadband seismometers; 30 were deployed onshore, and 75 were deployed offshore in Ocean Bottom Seismometer (OBS) packages. Additional strong‐motion instruments were also deployed at six onshore seismic sites. Offshore OBS stretched from the outer rise across the trench to the shelf. OBSs in shallow water ( ⁠ < 262    m "> < 262 m <262 m depth) were deployed with a trawl‐resistant shield, and deeper OBSs were unshielded. Additionally, a number of OBS‐mounted strong‐motion instruments, differential and absolute pressure gauges, hydrophones, and temperature and salinity sensors were deployed. OBSs were deployed on two cruises of the R/V Sikuliaq in May and July 2018 and retrieved on two cruises aboard the R/V Sikuliaq and R/V Langseth in August–September 2019. A complementary 398‐instrument nodal seismometer array was deployed on Kodiak Island for four weeks in May–June 2019, and an active‐source seismic survey on the R/V Langseth was arranged in June 2019 to shoot into the AACSE broadband network and the nodes. Additional underway data from cruises include seafloor bathymetry and sub‐bottom profiles, with extra data collected near the rupture zone of the 2018 M w "> M w Mw 7.9 offshore‐Kodiak earthquake. The AACSE network was deployed simultaneously with the EarthScope Transportable Array (TA) in Alaska, effectively densifying and extending the TA offshore in the region of the Alaska Peninsula. AACSE is a community experiment, and all data were made available publicly as soon as feasible in appropriate repositories.

Alaska↗

USGS2021

Quick and dirty (and accurate) 3-D paleoseismic trench models using coded scale bars

Structure‐from‐motion (SfM) modeling has dramatically increased the speed of generating geometrically accurate orthophoto mosaics of paleoseismic trenches, but some aspects of this technique remain time and labor intensive. Model accuracy relies on control points to establish scale, reduce distortion, and orient 3D models. Traditional SfM methods use total station or Global Navigation Satellite System (GNSS) surveys to constrain models, but collecting control points along a vertical trench wall is often inhibited by poor line of sight to the survey sensor or limited sky view and requires many hours in the field and office. We used physical scale bars printed with coded targets to constrain SfM models of a dusty, 46‐m‐long trench excavation across the Teton fault (Wyoming, U.S.A.). We present a workflow for generating quick and accurate 3D SfM models and orthophoto mosaics and compare the effectiveness of using scale bar, GNSS, and total‐station control in the models. Our results show that the scale bar model deviates from total station survey points by an average of 3.1 cm (maximum of 5.3 cm). In addition, the scale‐bar model only deviates an average of 1.7 cm (maximum 3.5 cm) when compared to the best model alternative, the SfM model controlled by the total station survey. Scale bars eliminate several hours needed to collect and incorporate control points from total station or GNSS surveys and significantly simplify the workflow, at the cost of slightly increased 3D model and orthophoto mosaic error. Our results further suggest that trench models can be constrained with at least four physical scale bars, but using five to six physical scale bars provides redundant control for field deployment and model optimization. The scale bar method for paleoseismic trenches proves to be portable and fast, minimizes the need for specialized survey equipment, and maintains model accuracy needed for mapping trench walls.

Seismological Research Letters↗

USGS2021

A review of timing accuracy across the Global Seismographic Network

The accuracy of timing across a seismic network is important for locating earthquakes as well as studies that use phase‐arrival information (e.g., tomography). The Global Seismographic Network (GSN) was designed with the goal of having reported timing be better than 10 ms. In this work, we provide a brief overview of how timing is kept across the GSN and discuss how clock‐quality metrics are embedded in Standard for Exchange of Earthquake Data records. Specifically, blockette 1001 contains the timing‐quality field, which can be used to identify time periods when poor clock quality could compromise timing accuracy. To verify the timing across the GSN, we compare cross‐correlation lags between collocated sensors from 1 January 2000 to 1 January 2020. We find that the mean error is less than 10 ms, with much of the difference likely coming from the method or uncertainty in the phase response of the instruments. This indicates that timing across the GSN is potentially better than 10 ms. We conclude that unless clock quality is compromised (as indicated in blockette 1001), GSN data’s timing accuracy should be suitable for most current seismological applications that require 10 ms accuracy. To assist users, the GSN network operators have implemented a “gsn_timing” metric available via the Incorporated Research Institutions for Seismology Data Management Center that helps users identify data with substandard timing accuracy (the 10 ms design goal of the GSN).

Seismological Research Letters↗

USGS2023

Global seismic networks operated by the U.S. Geological Survey

The U.S. Geological Survey (USGS) Global Seismographic Network (GSN) Program operates two thirds of the GSN, a network of state‐of‐the‐art, digital seismological and geophysical sensors with digital telecommunications. This network serves as a multiuse scientific facility and a valuable resource for research, education, and monitoring. The other one third of the GSN is funded by the National Science Foundation (NSF), and the operations of this component are overseen by EarthScope. This collaboration between the USGS, EarthScope, and NSF has allowed for the development and operations of the GSN to be a truly multiuse network that provides near real‐time open access data, facilitating fundamental discoveries by the Earth science community, supporting the earthquake hazards mission of the USGS, benefitting tsunami monitoring by the National Oceanic and Atmospheric Administration, and contributing to nuclear test monitoring and treaty verification. In this article, we describe the installation and evolution of the seismic networks operated by the USGS that ultimately led to the USGS portion of the GSN (100 stations under network codes IU, IC, and CU) as they are today and envision technological advances and opportunities to further improve the utility of the network in the future. This article focuses on the USGS‐operated component of the GSN; a companion article on the GSN stations funded by the NSF and operated by the Cecil and Ida Green Institute of Geophysics and Planetary Physics, Scripps Institution of Oceanography, University of California at San Diego by Davis et al. (2023) appears in this volume.

Seismological Research Letters↗

USGS2025

Remote single-station seismic monitoring of the July–October 2022 earthquake swarm at Tau volcano, American Samoa

From July to October 2022, a non-eruptive volcanic earthquake swarm occurred within ~15 km of Taʻū Island, located in eastern American Samoa. Felt reports from local residents were the only available information about the swarm when it started, as American Samoa lacked a seismic monitoring network. We developed a consistent single-station catalog for the entire swarm, using seismic data from the nearest station IU.AFI, ~250 km away. We applied the EQTransformer deep-learning model (Mousavi et al., 2020), automatically picking Pn and Sn arrivals on IU.AFI continuous data. We retained only events with Sn-Pn times of 22.5–25 seconds, consistent with the expected locations based on felt reports, then detected smaller swarm events with subsequent template-matching. This single-station catalog characterized the swarm’s onset and escalation to peak activity before a multi-agency field response team installed a local seismic network in mid-August 2022. This permanent seismic network captured the swarm’s decline. EQTransformer identified short S-P times on the first two locally deployed seismometers, both Raspberry Shake sensors, to constrain the swarm’s distance from Taʻū Island. Modern seismological processing methods, combined with basic observations such as felt reports, can quickly contribute useful information during an earthquake response in a poorly monitored region.

American Somoa↗

USGS1989

On the use of volumetric strain meters to infer additional characteristics of short-period seismic radiation

Volumetric strain meters (Sacks-Evertson design) are installed at 15 sites along the San Andreas fault system, to monitor long-term strain changes for earthquake prediction. Deployment of portable broadband, high-resolution digital recorders (GEOS) at several of the sites extends the detection band for volumetric strain to periods shorter than 5 × 10 −2 sec and permits the simultaneous observation of seismic radiation fields using conventional short-period pendulum seismometers. Simultaneous observations establish that the strain detection bandwidth extends from periods greater than 10 7 seconds to periods near 5 × 10 −2 sec with a dynamic range exceeding 140 dB. Measurements of earth-strain noise for the period band, 10 7 to 10 −2 sec, show that ground noise, not instrument noise, currently limits the measurement of strain over a bandwidth of more than eight orders of magnitude in period. Comparison of the short-period portion of earth-strain, noise spectra (20 to 5 × 10 −2 sec) with average spectra determined from pendulum seismometers, suggest that observed noise is predominantly dilatational energy. Recordings of local and regional earthquakes indicate that dilatometers respond to P energy but not direct shear energy and that straingrams can be used to resolve superimposed reflected P and S waves for inference of wave characteristics not permitted by either sensor alone. Simultaneous measurements of incident P - and S -wave amplitudes are used to introduce a technique for single-station estimates of wave field inhomogeneity, free-surface reflection coefficients and local material P velocity. Estimates of these parameters derived for the North Palm Springs earthquake ( M w 5.9) respectively for an incident P wave of 29° are −85°, 1.71, 2.9 km/sec, and for an incident S wave of 17° are 79°, 0.85, 2.9 km/sec. The empirical estimates of reflection coefficients are consistent with model estimates derived using an anelastic half-space model with incident inhomogeneous wave fields.

California↗

USGS1994

Early warning system for aftershocks

A prototype early warning system to provide San Francisco and Oakland, California a few tens-of-seconds warning of incoming strong ground shaking from already-occurred M ≧ 3.7 aftershocks of the magnitude 7.1 17 October 1989 Loma Prieta earthquake was operational on 28 October 1989. The prototype system consisted of four components: ground motion sensors in the epicentral area, a central receiver, a radio repeater, and radio receivers. One of the radio receivers was deployed at the California Department of Transportation ( CALTRANS ) headquarters at the damaged Cypress Street section of the I-880 freeway in Oakland, California on 28 October 1989 and provided about 20 sec of warning before shaking from the M 4.5 Loma Prieta aftershock that occurred on 2 November 1989 at 0550 UTC. In its first 6 months of operation, the system generated triggers for all 12 M > 3.7 aftershocks for which trigger documentation is preserved, did not trigger on any M ≦ 3.6 aftershocks, and produced one false trigger as a result of a now-corrected single point of failure design flaw. Because the prototype system demonstrated that potentially useful warnings of strong shaking from aftershocks are feasible, the USGS has completed a portable early warning system for aftershocks that can be deployed anywhere.

California↗

USGS1996

Directional topographic site response at Tarzana observed in aftershocks of the 1994 Northridge, California, earthquake: Implications for mainshock motions

The Northridge earthquake caused 1.78 g acceleration in the east-west direction at a site in Tarzana, California, located about 6 km south of the mainshock epicenter. The accelerograph was located atop a hill about 15-m high, 500-m long, and 130-m wide, striking about N78°E. During the aftershock sequence, a temporary array of 21 three-component geophones was deployed in six radial lines centered on the accelerograph, with an average sensor spacing of 35 m. Station C00 was located about 2 m from the accelerograph. We inverted aftershock spectra to obtain average relative site response at each station as a function of direction of ground motion. We identified a 3.2-Hz resonance that is a transverse oscillation of the hill (a directional topographic effect). The top/base amplification ratio at 3.2 Hz is about 4.5 for horizontal ground motions oriented approximately perpendicular to the long axis of the hill and about 2 for motions parallel to the hill. This resonance is seen most strongly within 50 m of C00. Other resonant frequencies were also observed. A strong lateral variation in attenuation, probably associated with a fault, caused substantially lower motion at frequencies above 6 Hz at the east end of the hill. There may be some additional scattered waves associated with the fault zone and seen at both the base and top of the hill, causing particle motions (not spectral ratios) at the top of the hill to be rotated about 20° away from the direction transverse to the hill. The resonant frequency, but not the amplitude, of our observed topographic resonance agrees well with theory, even for such a low hill. Comparisons of our observations with theoretical results indicate that the 3D shape of the hill and its internal structure are important factors affecting its response. The strong transverse resonance of the hill does not account for the large east-west mainshock motions. Assuming linear soil response, mainshock east-west motions at the Tarzana accelerograph were amplified by a factor of about 2 or less compared with sites at the base of the hill. Probable variations in surficial shear-wave velocity do not account for the observed differences among mainshock acceleration observed at Tarzana and at two different sites within 2 km of Tarzana.

California↗

USGS1997

One minute after: Strong-motion map, effective epicenter, and effective magnitude

This article reports the recent progress on real-time seismic monitoring in Taiwan, particularly the real-time strong-motion monitoring by the Taiwan Central Weather Bureau's telemetered seismic network ( CWBSN ), which is presently aiming at rapid reporting immediately after a large earthquake occurrence. If rapid reporting can be achieved before the arrival of the strong shaking, earthquake early warning will become possible. CWBSN has achieved the generation of the intensity map, epicenter, and magnitude within 1 min of the occurrence of a large earthquake. Both rapid reporting and early warning are principally applied to large ( M ≫ 5) events; the requirement of on-scale waveform recording prompted CWBSN in 1995 to integrate strong-motion sensors (e.g., force-balance accelerometers) into its telemetered seismic monitoring system. Time-domain recursive processing is applied to the multi-channel incoming seismic signals by a group of networked personal computers to generate the intensity map. From the isoseismal contours, an effective epicenter is immediately identified that resides in the middle of the largest (usually the 100-gal) contour curve of the intensity map. An effective magnitude is also defined that can be derived immediately from the surface area covered by the largest (usually the 100-gal) contour curve. For a large event with a finite rupture surface, the epicenter and magnitude so derived are more adequate estimates of the source location and of the strength of destruction. The effective epicenter gives the center of the damage area; it stands in contrast with the conventional epicenter location, which only gives the initial point of rupture nucleation. The effective magnitude reflects more closely the earthquake damage potential, instead of the classical magnitude definition that emphasizes the total energy release. The CWBSN has achieved in obtaining the above crucial source information well within 1 min. This time can further be reduced to better than 30 sec, as illustrated by the example in this article, showing that earthquake early warning is indeed an achievable goal. The rapid reporting and early warning information is electronically transmitted to users to allow rapid response actions, with or without further human intervention.

Bulletin of the Seismological Society of America↗

USGS1999

The strain in the array is mainly in the plane (waves below ~1 Hz)

We compare geodetic and single-station methods of measuring dynamic deformations and characterize their causes in the frequency bands 0.5-1.0 Hz and 4.0-8.0 Hz. The geodetic approach utilizes data from small-aperture seismic arrays, applying techniques from geodesy. It requires relatively few assumptions and a priori information. The single-station method uses ground velocities recorded at isolated or single stations and assumes all the deformation is due to plane-wave propagation. It also requires knowledge of the azimuth and horizontal velocity of waves arriving at the recording station. Data employed come from a small-aperture, dense seismic array deployed in Geyokcha, Turkmenistan, and include seismograms recorded by broadband STS2 and short-period L28 sensors. Poor agreement between geodetic and single-station estimates in the 4.0-8.0 Hz passband indicates that the displacement field may vary nonlinearly with distance over distances of ∼50 m. STS2 geodetic estimates provide a robust standard in the 0.5-1.0 Hz passband because they appear to be computationally stable and require fewer assumptions than single-station estimates. The agreement between STS2 geodetic estimates and single-station L28 estimates is surprisingly good for the S -wave and early surface waves, suggesting that the single-station analysis should be useful with commonly available data. These results indicate that, in the 0.5 to 1.0 Hz passband, the primary source of dynamic deformation is plane-wave propagation along great-circle source-receiver paths. For later arriving energy, the effects of scattering become important. The local structure beneath the array exerts a strong control on the geometry of the dynamic deformation, implying that it may be difficult to infer source characteristics of modern or paleoearthquakes from indicators of dynamic deformations. However, strong site control also suggests that the dynamic deformations may be predictable, which would be useful for engineering seismically resistant structures.

Bulletin of the Seismological Society of America↗

USGS2004

Geotechnical characterization of TriNet sites: A status report

The TriNet project, launched in 1997, created an improved, real-time seismic monitoring network in Southern California. Planning of the network began in 1995 ( e.g. , Heaton et al. , 1996 ), building on the success of the earlier TERRAscope network, which included 24 digital broadband and strong-motion instruments throughout Southern California ( e.g. , Kanamori et al. , 1993 ). At the end of the five-year TriNet project the network comprised 150 real-time digital broadband stations and another 400 strong-motion sensors, 50 of which were also real-time. This network is now recording digital broadband data for Southern California earthquakes at an unprecedented rate, data that are already proving valuable for investigations of earthquake sources and regional wave propagation, as well as earthquake response. In this report we describe an ongoing effort aimed at a full geotechnical characterization of the newly installed TriNet sets. Shallow geologic structure is known to play a substantial role in controlling the ground motions recorded at any site. Documentation of amplified ground motion at soft-sediment sites can be found among even early macroseismic observations of strong ground motions ( e.g. , Drake, 1815 ). Seismic waves are also now known to be strongly affected by deep basin structure as well ( e.g. , Frankel et al. , 1991 ; Field, 2000 ; Joyner, 2000 ). It will be necessary to understand these effects to exploit fully the rich data set being recorded at TriNet sites. Clearly, the nature of site conditions and site response at the recording sites must be understood for studies focused on ground motions and hazard from future large earthquakes, but it is also necessary to understand these effects to conduct earthquake source studies of both large and small earthquakes. Our multifaceted site characterization project involves geological/geotechnical site investigations, database development, and investigation of empirical amplification factors determined from broadband and strong-motion data recorded to date. Our goal is to complete a first-order geologic site characterization by 2005 and then employ appropriate methods to obtain direct constraint on shallow shear-wave velocity structure at each site. In the latter effort we will endeavor to find the most accurate and cost-effective methods to quantify geotechnical parameters at sites that have ranges of geologic site conditions and cultural settings. Our long-term goal is to obtain direct estimates of the average shear-wave velocity in the upper 30 m, Vs30, at each site. If velocity information is available to greater depths, for example at sites characterized under the ROSRINE project ( http://geoinfo.usc.edu/rosrine/ ), this information will be included in the database as well. The original motivation for using Vs30 to characterize near-surface velocity was pragmatic, determined by such factors as the typical reach of a drill rig in a single day. The parameter has become the accepted standard with which many seismic recording sites are characterized, however. In a recent study using mainshock and aftershock recordings at sites in the Los Angeles region, Wald and Mori ( 2000 ) observed good correlation between Vs30 and amplification at 1-7 Hz, albeit with significant scatter. The purpose of this report is threefold. First, we describe our ongoing efforts and present site characterization results collected to date for 62 broadband and strong-motion stations in and around the greater Los Angeles metropolitan region. Second, we present preliminary results that illustrate how improved geologic site characterizations can improve the correlation between site conditions and site response. Finally, we invite feedback from the community to guide our future investigations, in particular with respect to our ongoing database development efforts.

California↗

USGS2007

Enhancement of the national strong-motion network in Turkey

Two arrays comprising 20 strong-motion sensors were established in western Turkey. The 14 stations of BYTNet follow a N-S trending line about 65 km in length, normal to strands of the North Anatolian fault that runs between the cities of Bursa and Yalova. Here the dominant character of the potential fault movement is a right-lateral transform slip. The DATNet array, comprising a total of eight stations, is arranged along a 110-km-long E-W trending direction along the Menderes River valley between Denizli and Aydin. (Two stations in this array were incorporated from the existing Turkish national strong-motion network.) This is an extensional tectonic environment, and the network monitors potential large normal-faulting earthquakes on the faults in the valley.

Seismological Research Letters↗

USGS2009

A method to establish seismic noise baselines for automated station assessment

We present a method for quantifying station noise baselines and characterizing the spectral shape of out-of-nominal noise sources. Our intent is to automate this method in order to ensure that only the highest-quality data are used in rapid earthquake products at NEIC. In addition, the station noise baselines provide a valuable tool to support the quality control of GSN and ANSS backbone data and metadata. The procedures addressed here are currently in development at the NEIC, and work is underway to understand how quickly changes from nominal can be observed and used within the NEIC processing framework. The spectral methods and software used to compute station baselines and described herein (PQLX) can be useful to both permanent and portable seismic stations operators. Applications include: general seismic station and data quality control (QC), evaluation of instrument responses, assessment of near real-time communication system performance, characterization of site cultural noise conditions, and evaluation of sensor vault design, as well as assessment of gross network capabilities (McNamara et al. 2005). Future PQLX development plans include incorporating station baselines for automated QC methods and automating station status report generation and notification based on user-defined QC parameters. The PQLX software is available through the USGS (http://earthquake. usgs.gov/research/software/pqlx.php) and IRIS (http://www.iris.edu/software/ pqlx/).

Seismological Research Letters↗

USGS2011

Some possible causes of and corrections for STS-1 response changes in the Global Seismographic Network

The Global Seismographic Network (GSN) (Figure 1) plays a key role in providing seismic data for global earthquake monitoring ( e.g. , Benz et al. 2005), earthquake science ( e.g. , Tsai et al. 2005), and studies of Earth structure ( e.g. , Dalton et al. 2008). One of the key GSN design goals is to "provide high fidelity digital recordings of all teleseismic ground motions (adequate to resolve at or near ambient noise up to the largest teleseismic signals over the bandwidth from free oscillations (10 -4 Hz) to teleseismic body waves (up to approximately 15 Hz))" (GSN ad hoc Design Goals Subcommittee 2002). To help meet this goal, Streckeisen STS-1 seismometers were deployed at 80 GSN stations. Some of the GSN sensors have been deployed for more than 25 years. Several recent studies (Davis et al. 2005; Ekström et al. 2006; Davis and Berger 2007) have examined the question of overall calibration of the GSN. Ekström et al. (2006) indicated that a number of sites showed anomalous responses and suggested a gradual decay in the sensitivity. We have investigated the anomalous responses at several GSN sites. At least some of the problems observed by Ekström et al. (2006) may be attributed to humid air leaking into the feedback electronics of the STS-1 seismometers, which produces lower than normal sensitivities near the long-period corner of the instrument (360 seconds period). It appears that even though the feedback electronics boxes are designed to be sealed, water vapor can penetrate their interior after they have been exposed to highly humid seismometer vault air for extended periods. Highly humid air was also found to be present inside some STS-1 bell-jars (especially horizontal instruments) after loss of vacuum, resulting in corrosion and leakage between electrical conductors in connectors.

Seismological Research Letters↗

USGS1998

High-resolution multibeam bathymetry of East and West Flower Gardens and Stetson Banks, Gulf of Mexico

The 1990s have seen rapid advances in seafloor mapping technology. Multibeam sonars are now capable of mapping a wide range of water depths with beams as narrow as 1°, and provide up to a 150° swath. When these multibeam sonars are coupled with an extremely accurate vehicle motion sensor and very precise navigation, they are capable of producing unprecedented images of the seafloor. This technology was used in December 1997 to map the East and West Flower Gardens and Stetson Banks, Gulf of Mexico. The results from this survey provide the most accurate maps of these areas yet produced and reveal features at submeter resolution never mapped in these areas before. The digital data provide a database that should become the fundamental base maps for all subsequent work in this recently established National Marine Sanctuary.

Gulf of Mexico Science↗

USGS1997

NDVI, C3 and C4 production, and distributions in Great Plains grassland land cover classes

The distributions of C 3 and C 4 grasses were used to interpret the distribution, seasonal performance, and potential production of grasslands in the Great Plains of North America. Thirteen major grassland seasonal land cover classes were studied with data from three distinct sources. Normalized Difference Vegetation Index (NDVI) data derived from the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) sensor were collected for each pixel over a 5-yr period (1989–1993), analyzed for quantitative attributes and seasonal relationships, and then aggregated by land cover class. Data from the State Soil Geographic (STATSGO) database were used to identify dominant plant species contributing to the potential production in each map unit. These species were identified as C 3 or C 4 , and contributions to production were aggregated to provide estimates of the percentage of C 3 and C 4 production for each intersection of the STATSGO map units and the seasonal land cover classes. Carbon isotope values were obtained at specific sites from the soil organic matter of the upper horizon of soil cores and were related to STATSGO estimates of potential production. The grassland classes were distributed with broad northwest-to-southeast orientations. Some classes had large variations in C 3 and C 4 composition with high proportions of C 4 species in the south and low proportions in the north. This diversity of photosynthetic types within land cover classes that cross regions of different temperature and precipitation results in similar seasonal patterns and magnitudes of NDVI. The easternmost class, 65, containing tallgrass prairie components, bluestem, Indiangrass, and switchgrass, possessed the highest maximum NDVI and time-integrated NDVI values each year. Grassland classes varied over 5 yr from a high integrated NDVI mean of 4.9 in class 65 in the east to a low of 1.2 in class 76 (sand sage, blue grama, wheatgrass, and buffalograss) in the southwest. Although environmental conditions varied widely during the 5 yr, the rankings of class performance were consistent across years for these NDVI metrics. Land cover classes were less consistent in time of onset, which was often earlier in areas in the north dominated by C 3 grasses than in areas to the south dominated by C 4 grasses. At the level of seasonal land cover classes, no significant relationship was found between the proportions of C 3 and C 4 species and estimates of potential production derived from the STATSGO database or inferred from the seasonal patterns of NDVI. The isotopic data from specific sites and the potential production data from STATSGO suggest similar patterns of high proportional production by C 4 species throughout the south and a decline in proportional production north of the central Great Plains. The land cover classes integrate ecosystem units that encompass a wide diversity of species and C 3 and C 4 proportions and provide a classification that consistently captures significant ecosystem parameters for the Great Plains.

Colorado, Kansas, Montana, Nebraska, New Mexico, N↗

USGS2026

Cyanobacteria Assessment Network: Pilot study with Sentinel-2 derived chlorophyll data

Harmful algal blooms (HABs) affect global water quality, limiting uses like recreation and consumption because of excessive algal biomass and toxin production. These blooms cause surface scums, taste and odor issues, hypoxia, and negative health and socioeconomic impacts. The US Army Corps of Engineers (USACE) manages over 400 lakes and reservoirs and seeks to improve monitoring of HABs through Sentinel-2 (S2) satellite imagery. The purpose of this project is to develop workflows for a national chlorophyll-a product with 20 m spatial resolution, enabling HAB monitoring for over 270,000 lakes and reservoirs. The 1-year pilot study established a federal partnership to conduct preliminary S2 processing steps, using datasets from Florida, Ohio, and Oregon. Key steps included in situ data aggregation, data assimilation, S2 algorithm evaluation, spatial and temporal compositing, satellite sensor cross-validation, and web hosting of an example prototype product. The study covers 29 USACE reservoirs, with cross-validation using Sentinel-3 (S3) data from 212 lakes. The multiagency initiative aligns with federal agency missions to protect health and the environment, supports acts like the 2017 Harmful Algal Bloom and Hypoxia Research and Control Act, and has annual potential avoided costs of $42 million.

contiguous United States↗

USGS2012

Limitations and potential of satellite imagery to monitor environmental response to coastal flooding

Storm-surge flooding and marsh response throughout the coastal wetlands of Louisiana were mapped using several types of remote sensing data collected before and after Hurricanes Gustav and Ike in 2008. These included synthetic aperture radar (SAR) data obtained from the (1) C-band advance SAR (ASAR) aboard the Environmental Satellite, (2) phased-array type L-band SAR (PALSAR) aboard the Advanced Land Observing Satellite, and (3) optical data obtained from Thematic Mapper (TM) sensor aboard the Land Satellite (Landsat). In estuarine marshes, L-band SAR and C-band ASAR provided accurate flood extent information when depths averaged at least 80 cm, but only L-band SAR provided consistent subcanopy detection when depths averaged 50 cm or less. Low performance of inundation mapping based on C-band ASAR was attributed to an apparent inundation detection limit (>30 cm deep) in tall Spartina alterniflora marshes, a possible canopy collapse of shoreline fresh marsh exposed to repeated storm-surge inundations, wind-roughened water surfaces where water levels reached marsh canopy heights, and relatively high backscatter in the near-range portion of the SAR imagery. A TM-based vegetation index of live biomass indicated that the severity of marsh dieback was linked to differences in dominant species. The severest impacts were not necessarily caused by longer inundation but rather could be caused by repeated exposure of the palustrine marsh to elevated salinity floodwaters. Differential impacts occurred in estuarine marshes. The more brackish marshes on average suffered higher impacts than the more saline marshes, particularly the nearshore coastal marshes occupied by S. alterniflora.

Journal of Coastal Research↗