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At least 901 records · Page 50Linked to original sources
USGS1999

Real-time control of the robotic lunar observatory telescope

The US Geological Survey operates an automated observatory dedicated to the radiometry of the Moon with the objective of developing a multispectral, spatially resolved photometric model of the Moon to be used in the calibration of Earth-orbiting spacecraft. Interference filters are used with two imaging instruments to observe the Moon in 32 passbands from 350-2500 nm. Three computers control the telescope mount and instruments with a fourth computer acting as a master system to control all observation activities. Real-time control software has been written to operate the instrumentation and to automate the observing process. The observing software algorithms use information including the positions of objects in the sky, the phase of the Moon, and the times of evening and morning twilight to decide how to observe program objects. The observatory has been operating in a routine mode since late 1995 and is expected to continue through at least 2002 without significant modifications.

Publications of the Astronomical Society of the Pa↗
USGS2025

Re-oligotrophy in the Upper Mississippi River, USA, occurred in just a few years

Ecological systems can undergo large changes and regime shifts that are either catastrophic, neutral, or desirable. Rivers worldwide have recently undergone desirable regime shifts related to re-oligotrophy, which is a notable and ongoing reduction in concentrations of total suspended solids (TSS), total N, total P, or phytoplankton. For example, the Upper Mississippi River, USA, has experienced major water-quality changes in multiple river reaches in recent decades. In this study, we sought to understand the timing and magnitude of re-oligotrophy in the Mississippi River over a 20-y period. We used 2 topological data analysis algorithms to address hypotheses related to the following questions: What were the order and timing of water-quality changes? What was the time period over which the major changes occurred? What was the magnitude of water-quality change before and after change points (i.e., specific years when water-quality conditions transitioned abruptly to new states)? We examined 6 water-quality state variables that defined the ecological regime for the Upper Mississippi River. In one river reach, we found that strong reductions in phytoplankton/chlorophyll a had occurred first (2008), followed by total P (2013), and last in TSS (2014). In a downriver reach, we found notable reductions for chlorophyll a (2007) but substantial increases in TSS (2013). In both reaches, the water-quality changes trended over ≥15 y, but the largest changes and a likely regime shift occurred in just 6 y. The timing (2007–2014) and range (~6 y) of water-quality changes were similar between the 2 river reaches, but the directionality of the regime shift indicated re-oligotrophy for the upstream reach and water-quality degradation for the downstream reach. Topological methods applied to long-term datasets can aid our understanding of re-oligotrophication and degradation processes and may help resource managers restore desirable regimes.

Freshwater Science↗
USGS2017

Limiting the effects of earthquakes on gravitational-wave interferometers

Ground-based gravitational wave interferometers such as the Laser Interferometer Gravitational-wave Observatory (LIGO) are susceptible to ground shaking from high-magnitude teleseismic events, which can interrupt their operation in science mode and significantly reduce their duty cycle. It can take several hours for a detector to stabilize enough to return to its nominal state for scientific observations. The down time can be reduced if advance warning of impending shaking is received and the impact is suppressed in the isolation system with the goal of maintaining stable operation even at the expense of increased instrumental noise. Here, we describe an early warning system for modern gravitational-wave observatories. The system relies on near real-time earthquake alerts provided by the U.S. Geological Survey (USGS) and the National Oceanic and Atmospheric Administration (NOAA). Preliminary low latency hypocenter and magnitude information is generally available in 5 to 20 min of a significant earthquake depending on its magnitude and location. The alerts are used to estimate arrival times and ground velocities at the gravitational-wave detectors. In general, 90% of the predictions for ground-motion amplitude are within a factor of 5 of measured values. The error in both arrival time and ground-motion prediction introduced by using preliminary, rather than final, hypocenter and magnitude information is minimal. By using a machine learning algorithm, we develop a prediction model that calculates the probability that a given earthquake will prevent a detector from taking data. Our initial results indicate that by using detector control configuration changes, we could prevent interruption of operation from 40 to 100 earthquake events in a 6-month time-period.

Classical and Quantum Gravity↗
USGS2022

Predicting flood damage probability across the conterminous United States

Floods are the leading cause of natural disaster damages in the United States, with billions of dollars incurred every year in the form of government payouts, property damages, and agricultural losses. The Federal Emergency Management Agency oversees the delineation of floodplains to mitigate damages, but disparities exist between locations designated as high risk and where flood damages occur due to land use and climate changes and incomplete floodplain mapping. We harnessed publicly available geospatial datasets and random forest algorithms to analyze the spatial distribution and underlying drivers of flood damage probability caused by excessive rainfall and overflowing water bodies across the conterminous United States. From this, we produced the first spatially complete map of flood damage probability for the nation, along with spatially explicit standard errors for four selected cities. We trained models using the locations of historical reported flood damage events ( n = 71,434) and a suite of geospatial predictors (e.g., flood severity, climate, socio-economic exposure, topographic variables, soil properties, and hydrologic characteristics). We developed independent models for each hydrologic unit code level 2 watershed and generated a flood damage probability for each 100-m pixel. Our model classified damage or no damage with an average area under the curve accuracy of 0.75; however, model performance varied by environmental conditions, with certain land cover classes (e.g., forest) resulting in higher error rates than others (e.g., wetlands). Our results identified flood damage probability hotspots across multiple spatial and regional scales, with high probabilities common in both inland and coastal regions. The highest flood damage probabilities tended to be in areas of low elevation, in close proximity to streams, with extreme precipitation, and with high urban road density. Given rapid environmental changes, our study demonstrates an efficient approach for updating flood damage probability estimates across the nation.

Environmental Research Letters↗
USGS2023

Variability in terrestrial characteristics and erosion rates on the Alaskan Beaufort Sea coast

Arctic coastal environments are eroding and rapidly changing. A lack of pan-Arctic observations limits our ability to understand controls on coastal erosion rates across the entire Arctic region. Here, we capitalize on an abundance of geospatial and remotely sensed data, in addition to model output, from the North Slope of Alaska to identify relationships between historical erosion rates and landscape characteristics to guide future modeling and observational efforts across the Arctic. Using existing datasets from the Alaska Beaufort Sea coast and a hierarchical clustering algorithm, we developed a set of 16 coastal typologies that captures the defining characteristics of environments susceptible to coastal erosion. Relationships between landscape characteristics and historical erosion rates show that no single variable alone is a good predictor of erosion rates. Variability in erosion rate decreases with increasing coastal elevation, but erosion rate magnitudes are highest for intermediate elevations. Areas along the Alaskan Beaufort Sea coast (ABSC) protected by barrier islands showed a three times lower erosion rate on average, suggesting that barrier islands are critical to maintaining mainland shore position. Finally, typologies with the highest erosion rates are not broadly representative of the ABSC and are generally associated with low elevation, north- to northeast-facing shorelines, a peaty pebbly silty lithology, and glaciomarine deposits with high ice content. All else being equal, warmer permafrost is also associated with higher erosion rates, suggesting that warming permafrost temperatures may contribute to higher future erosion rates on permafrost coasts. The suite of typologies can be used to guide future modeling and observational efforts by quantifying the distribution of coastlines with specific landscape characteristics and erosion rates.

Alaska↗
USGS2023

Maps of active layer thickness in northern Alaska by upscaling P-band polarimetric synthetic aperture radar retrievals

Extensive, detailed information on the spatial distribution of active layer thickness (ALT) in northern Alaska and how it evolves over time could greatly aid efforts to assess the effects of climate change on the region and also help to quantify greenhouse gas emissions generated due to permafrost thaw. For this reason, we have been developing high-resolution maps of ALT throughout northern Alaska. The maps are produced by upscaling from high-resolution swaths of estimated ALT retrieved from airborne P-band synthetic aperture radar (SAR) images collected for three different years. The upscaling was accomplished by using hundreds of thousands of randomly selected samples from the SAR-derived swaths of ALT to train a machine learning regression algorithm supported by numerous spatial data layers. In order to validate the maps, thousands of randomly selected samples of SAR-derived ALT were excluded from the training in order to serve as validation pixels; error performance calculations relative to these samples yielded root-mean-square errors (RMSEs) of 7.5–9.1 cm, with bias errors of magnitude under 0.1 cm. The maps were also compared to ALT measurements collected at a number of in situ test sites; error performance relative to the site measurements yielded RMSEs of approximately 11–12 cm and bias of 2.7–6.5 cm. These data are being used to investigate regional patterns and underlying physical controls affecting permafrost degradation in the tundra biome.

Environmental Research Letters↗
USGS2001

Some considerations on the use of ecological models to predict species' geographic distributions

Peterson (2001) used Genetic Algorithm for Rule-set Prediction (GARP) models to predict distribution patterns from Breeding Bird Survey (BBS) data. Evaluations of these models should consider inherent limitations of BBS data: (1) BBS methods may not sample species and habitats equally; (2) using BBS data for both model development and testing may overlook poor fit of some models; and (3) BBS data may not provide the desired spatial resolution or capture temporal changes in species distributions. The predictive value of GARP models requires additional study, especially comparisons with distribution patterns from independent data sets. When employed at appropriate temporal and geographic scales, GARP models show considerable promise for conservation biology applications but provide limited inferences concerning processes responsible for the observed patterns.

Condor↗
USGS2021

Assessment of a claimed ultra-low frequency electromagnetic (ULFEM) earthquake precursor

The rate of occurrence of anomalous ultra-low frequency electromagnetic (ULFEM) pulses has been claimed to have increased days to weeks prior to the M5.4 2007 and M4.0 2010 Alum Rock earthquakes. We re-examine the previously reported ultra-low frequency (ULF: 0.01–10 Hz) magnetic data recorded at a QuakeFinder site located 9 km from the earthquake hypocentre, and compare to data from a nearby Stanford-USGS site located 42 km from the hypocentre, to analyse the characteristics of the pulses and assess their origin. Using pulse definitions and pulse-counting algorithms analogous to those previously reported, we corroborate the increase in pulse counts before the 2007 Alum Rock earthquake at the QuakeFinder station, but we note that the number of pulses depends on chosen temporal and amplitude detection thresholds. These thresholds are arbitrary because we lack a clear physical model or basis for their selection. We do not see the same increase in pulse counts before the 2010 Alum Rock earthquake at the QuakeFinder or Stanford-USGS stations. In addition, the majority of pulses in the QuakeFinder data and Stanford-USGS data do not match temporally, indicating the pulses lack a common origin and are not from lightning or solar-driven ionospheric/magnetospheric disturbances. Our assessment of the temporal distribution of pulse counts shows pulse counts increase during peak human activity hours, suggesting these pulses result from local cultural noise and are not tectonic in origin. The many unknowns about the character and even existence of precursory earthquake pulses means that standard numerical and statistical tests cannot easily be applied. Yet here we show that exhaustive investigation of many different aspects of ULFEM signals can be used to properly characterize their origin.

California↗
USGS2022

Fast rupture of the 2009 Mw 6.9 Canal de Ballenas earthquake in the Gulf of California dynamically triggers seismicity in California

In the Gulf of California, Mexico, the relative motion across the North America-Pacific boundary is accommodated by a series of marine transform faults and spreading centers. About 40 M>6 earthquakes have occurred in the region since 1960. On 3 August 2009, an Mw 6.9 earthquake occurred near Canal de Ballenas in the region. The earthquake was a strike-slip event with a shallow hypocenter that is likely close to the seafloor. In contrast to an adjacent M7 earthquake, this earthquake triggered a ground-motion-based earthquake early warning algorithm being tested in southern California (∼600 km away). This observation suggests that the abnormally large ground motions and dynamic strains observed for this earthquake relate to its rupture properties. To investigate this possibility, we image the rupture process and resolve the slip distribution of the event using a P-wave back-projection approach and a teleseismic, finite-fault inversion method. Results from these two independent analyses indicate a relatively simple, unilateral rupture propagation directed along-strike in the northward direction. However, the average rupture speed is estimated around 4 km/s, suggesting a possible supershear rupture. The supershear speed is also supported by a Rayleigh wave Mach cone analysis, although uncertainties in local velocity structure preclude a definitive conclusion. The Canal de Ballenas earthquake dynamically triggered seismicity at multiple sites in California, with triggering response characteristics varying from location-to-location. For instance, some of the triggered earthquakes in California occurred up to 24 hours later, suggesting that nonlinear triggering mechanisms likely have modulated their occurrence.

Baja California↗
USGS2023

Converted-wave reverse time migration imaging in subduction zone settings

We use a newly developed 2-D elastic reverse time migration (RTM) imaging algorithm based on the Helmholtz decomposition to test approaches for imaging the descending slab in subduction zone regions using local earthquake sources. Our elastic RTM method is designed to reconstruct incident and scattered wavefields at depth, isolate constituent P- and S- wave components via Helmholtz decomposition, and evaluate normalized imaging functions that leverage dominant P and S signals. This method allows us to target particular converted-wave scattering geometries, for example incident S to scattered P , which may be expected to have dominant signals in any given data set. The method is intended to be applied to dense seismic array observations that adequately capture both incident and converted wavefields. We draw a direct connection between our imaging functions and the first-order contrasts in shear wave material properties across seismic discontinuities. Through tests on synthetic data using either S → P or P → S conversions, we find that our technique can successfully recover the structure of a subducting slab using data from a dense wide-angle array of surface stations. We also calculate images with a small-aperture array to test the impact of array geometry on image resolution and interpretability. Our results show that our imaging technique is capable of imaging multiple seismic discontinuities at depth, even with a small number of earthquakes, but that limitations arise when a small aperture array is considered. In this case, the presence of artefacts makes it more difficult to determine the location of seismic discontinuities.

Geophysical Journal International↗
USGS2013

Seismotectonic framework of the 2010 February 27 M w 8.8 Maule, Chile earthquake sequence

After the 2010 M w 8.8 Maule earthquake, an international collaboration involving teams and instruments from Chile, the US, the UK, France and Germany established the International Maule Aftershock Deployment temporary network over the source region of the event to facilitate detailed, open-access studies of the aftershock sequence. Using data from the first 9-months of this deployment, we have analyzed the detailed spatial distribution of over 2500 well-recorded aftershocks. All earthquakes have been relocated using a hypocentral decomposition algorithm to study the details of and uncertainties in both their relative and absolute locations. We have computed regional moment tensor solutions for the largest of these events to produce a catalogue of 465 mechanisms, and have used all of these data to study the spatial distribution of the aftershock sequence with respect to the Chilean megathrust. We refine models of co-seismic slip distribution of the Maule earthquake, and show how small changes in fault geometries assumed in teleseismic finite fault modelling significantly improve fits to regional GPS data, implying that the accuracy of rapid teleseismic fault models can be substantially improved by consideration of existing fault geometry model databases. We interpret all of these data in an integrated seismotectonic framework for the Maule earthquake rupture and its aftershock sequence, and discuss the relationships between co-seismic rupture and aftershock distributions. While the majority of aftershocks are interplate thrust events located away from regions of maximum co-seismic slip, interesting clusters of aftershocks are identified in the lower plate at both ends of the main shock rupture, implying internal deformation of the slab in response to large slip on the plate boundary interface. We also perform Coulomb stress transfer calculations to compare aftershock locations and mechanisms to static stress changes following the Maule rupture. Without the incorporation of uncertainties in earthquake locations, just 55 per cent of aftershock nodal planes align with faults promoted towards failure by co-seismic slip. When epicentral uncertainties are considered (on the order of just ±2–3 km), 90 per cent of aftershocks are consistent with occurring along faults demonstrating positive stress transfer. These results imply large sensitivities of Coulomb stress transfer calculations to uncertainties in both earthquake locations and models of slip distributions, particularly when applied to aftershocks close to a heterogeneous fault rupture; such uncertainties should therefore be considered in similar studies used to argue for or against models of static stress triggering.

Maule↗
USGS2015

A comparison of methods to estimate seismic phase delays--Numerical examples for coda wave interferometry

Time-shift estimation between arrivals in two seismic traces before and after a velocity perturbation is a crucial step in many seismic methods. The accuracy of the estimated velocity perturbation location and amplitude depend on this time shift. Windowed cross correlation and trace stretching are two techniques commonly used to estimate local time shifts in seismic signals. In the work presented here, we implement Dynamic Time Warping (DTW) to estimate the warping function – a vector of local time shifts that globally minimizes the misfit between two seismic traces. We illustrate the differences of all three methods compared to one another using acoustic numerical experiments. We show that DTW is comparable to or better than the other two methods when the velocity perturbation is homogeneous and the signal-to-noise ratio is high. When the signal-to-noise ratio is low, we find that DTW and windowed cross correlation are more accurate than the stretching method. Finally, we show that the DTW algorithm has better time resolution when identifying small differences in the seismic traces for a model with an isolated velocity perturbation. These results impact current methods that utilize not only time shifts between (multiply) scattered waves, but also amplitude and decoherence measurements. DTW is a new tool that may find new applications in seismology and other geophysical methods (e.g., as a waveform inversion misfit function).

Geophysical Journal International↗
USGS2015

Spatial-temporal variation of low-frequency earthquake bursts near Parkfield, California

Tectonic tremor (TT) and low-frequency earthquakes (LFEs) have been found in the deeper crust of various tectonic environments globally in the last decade. The spatial-temporal behaviour of LFEs provides insight into deep fault zone processes. In this study, we examine recurrence times from a 12-yr catalogue of 88 LFE families with ∼730 000 LFEs in the vicinity of the Parkfield section of the San Andreas Fault (SAF) in central California. We apply an automatic burst detection algorithm to the LFE recurrence times to identify the clustering behaviour of LFEs (LFE bursts) in each family. We find that the burst behaviours in the northern and southern LFE groups differ. Generally, the northern group has longer burst duration but fewer LFEs per burst, while the southern group has shorter burst duration but more LFEs per burst. The southern group LFE bursts are generally more correlated than the northern group, suggesting more coherent deep fault slip and relatively simpler deep fault structure beneath the locked section of SAF. We also found that the 2004 Parkfield earthquake clearly increased the number of LFEs per burst and average burst duration for both the northern and the southern groups, with a relatively larger effect on the northern group. This could be due to the weakness of northern part of the fault, or the northwesterly rupture direction of the Parkfield earthquake.

California↗
USGS2015

Using a modified time-reverse imaging technique to locate low-frequency earthquakes on the San Andreas Fault near Cholame, California

We present a new method to locate low-frequency earthquakes (LFEs) within tectonic tremor episodes based on time-reverse imaging techniques. The modified time-reverse imaging technique presented here is the first method that locates individual LFEs within tremor episodes within 5 km uncertainty without relying on high-amplitude P-wave arrivals and that produces similar hypocentral locations to methods that locate events by stacking hundreds of LFEs without having to assume event co-location. In contrast to classic time-reverse imaging algorithms, we implement a modification to the method that searches for phase coherence over a short time period rather than identifying the maximum amplitude of a superpositioned wavefield. The method is independent of amplitude and can help constrain event origin time. The method uses individual LFE origin times, but does not rely on a priori information on LFE templates and families.We apply the method to locate 34 individual LFEs within tremor episodes that occur between 2010 and 2011 on the San Andreas Fault, near Cholame, California. Individual LFE location accuracies range from 2.6 to 5 km horizontally and 4.8 km vertically. Other methods that have been able to locate individual LFEs with accuracy of less than 5 km have mainly used large-amplitude events where a P-phase arrival can be identified. The method described here has the potential to locate a larger number of individual low-amplitude events with only the S-phase arrival. Location accuracy is controlled by the velocity model resolution and the wavelength of the dominant energy of the signal. Location results are also dependent on the number of stations used and are negligibly correlated with other factors such as the maximum gap in azimuthal coverage, source–station distance and signal-to-noise ratio.

California↗
USGS2013

SSR_pipeline: a bioinformatic infrastructure for identifying microsatellites from paired-end Illumina high-throughput DNA sequencing data

SSR_pipeline is a flexible set of programs designed to efficiently identify simple sequence repeats (e.g., microsatellites) from paired-end high-throughput Illumina DNA sequencing data. The program suite contains 3 analysis modules along with a fourth control module that can automate analyses of large volumes of data. The modules are used to 1) identify the subset of paired-end sequences that pass Illumina quality standards, 2) align paired-end reads into a single composite DNA sequence, and 3) identify sequences that possess microsatellites (both simple and compound) conforming to user-specified parameters. The microsatellite search algorithm is extremely efficient, and we have used it to identify repeats with motifs from 2 to 25bp in length. Each of the 3 analysis modules can also be used independently to provide greater flexibility or to work with FASTQ or FASTA files generated from other sequencing platforms (Roche 454, Ion Torrent, etc.). We demonstrate use of the program with data from the brine fly Ephydra packardi (Diptera: Ephydridae) and provide empirical timing benchmarks to illustrate program performance on a common desktop computer environment. We further show that the Illumina platform is capable of identifying large numbers of microsatellites, even when using unenriched sample libraries and a very small percentage of the sequencing capacity from a single DNA sequencing run. All modules from SSR_pipeline are implemented in the Python programming language and can therefore be used from nearly any computer operating system (Linux, Macintosh, and Windows).

Journal of Heredity↗
USGS2024

Pasture and diurnal temperature are key predictors of regional Plains Spotted Skunk (Spilogale interrupta) distribution

The Plains Spotted Skunk ( Spilogale interrupta ) is a small carnivore native to central North America that has experienced significant population reductions, and there is a lack of information about the species that could inform conservation. Our study aimed to address knowledge gaps about the distribution and habitat associations of the species in South Dakota using species distribution modeling. We used species location data collected from state natural resource managers, trappers, and members of online social media groups dedicated to hunting and wildlife conservation; environmental predictors; and 6 predictive modeling algorithms (i.e., artificial neural networks, artificial classification tree analysis, generalized boosting models, maximum entropy, multivariate adaptive regression splines, and random forests) to develop climate and landcover ensemble distribution models. The most important climate and landcover predictors were mean temperature diurnal range (i.e., average monthly differences between daily high and low temperatures) and proportion of area classified as pasture. Ensemble model concordance identified approximately 31,300 km 2 of potential Plains Spotted Skunk habitat primarily in eastern South Dakota and between the watersheds of the Missouri and James rivers. Our results offer insights that can guide conservation and inform effective management strategies for conserving Plains Spotted Skunk populations in the northern Great Plains. The promotion of low-intensity agricultural practices such as maintaining pastures, farm buildings, fences rows, and the management of woodland encroachment may improve habitat suitability and facilitate the recovery of plains spotted skunks in the region.

South Dakota↗
USGS2025

Satellite imagery can predict bird species occupancy and inform multispecies management in pine savannas

Multispecies management can contribute to meeting growing challenges of preserving biodiversity, yet current game and threatened species management often focuses on individual species. Satellite imagery available at high spatial and temporal resolution provides a potential tool to overcome the challenge posed by multispecies management of linking patterns of habitat use among species. We sought to determine whether satellite imagery could be used to describe patterns of species occupancy and inform multispecies management in pine savannas in Georgia, USA. We conducted point-count surveys at 7 sites in 2022 for 3 bird species: Colinus virginianus (Northern Bobwhite), Dryobates borealis (Red-cockaded Woodpecker), and Peucaea aestivalis (Bachman’s Sparrow). We built single-season occupancy models comparing a set of models using covariates collected from field vegetation surveys and another set using covariates extracted from Sentinel-2 satellite imagery. We then used a multi-objective optimization algorithm to identify quasi-optimal management solutions (i.e., sets of covariate values from top satellite imagery metric models). We found that models created using satellite imagery performed well at predicting occupancy of all 3 species as measured by the area under the receiver operating characteristic curve (AUC > 0.8) and had higher AUC scores than field-derived habitat covariate-based models. We found combinations of metrics that could result in high rates of predicted probability of occupancy for all species (within 86% of highest possible occupancy probability), but these combinations did not exist at any of the sites. Our results demonstrate that (1) satellite imagery can allow users to build reliable occupancy models without intensive field-based vegetation surveys; and (2) C. virginianus , D. borealis, and P. aestivalis in pine savanna ecosystems could be simultaneously managed through more frequent burning, changes in canopy cover or by producing suitable heterogeneity of habitats after identifying an appropriate scale of management.

Georgia↗
USGS2026

Cyanobacterial bloom occurrence and emergency department visits for asthma or wheeze, Wisconsin, 2017–2019

Background: Cyanobacterial harmful algal blooms (cyanoHABs) pose risks to human and animal health. Methods: We investigated the relationship between cyanoHABs and asthma or wheeze-related emergency department (ED) visits near three Wisconsin cities (Green Bay, Madison, and Oshkosh) during 2017–2019. CyanoHAB exposure was approximated using the Cyanobacterial Assessment Network remotely sensed satellite indicator of cyanobacterial biomass, a chlorophyl algorithm (Chl BS ) aggregated by water-adjacent ZIP Code Tabulation Areas (ZCTA), and distance weighted from the nearest waterbody. Weekly counts of ED visits for asthma or wheeze were aggregated by ZCTA. Poisson generalized linear models estimated the association between the weekly number of ED visits and weekly Chl BS, adjusting for maximum temperature, dewpoint, fine particulate matter (PM 2.5 ), month, and correlation within ZCTA. Results: During 2017–2019, 7,057 ED visits for asthma or wheeze occurred in the study area (42 ZCTAs). Peaks in Chl BS occurred between June and October, with higher values in Lake Winnebago and Lake Mendota compared to Green Bay. Chl BS was not associated with ED visits for asthma or wheeze (adjusted rate ratio = 1.00, 95% confidence interval = 0.99, 1.00), and the presence of onshore winds did not change this result. Monthly aggregations of ED visits and Chl BS showed a monotonic trend between increasing Chl BS and ED visits during July–September. Conclusion: This study demonstrates the utility of remote sensing data in environmental health research. Future studies could explore individual-level exposure and outcomes to refine health risks associated with cyanoHABs.

Wisconsin↗