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939 records · Page 23Linked to original sources

Techniques for estimating magnitude and frequency of floods on streams in Indiana

Equations are presented for estimating the magnitude and frequency of floods at ungaged sites on unregulated and nonurban streams in Indiana. The equations were developed by multiple-regression, analysis of basin characteristics and peak-flow statistical data from 242 gaged locations in Indiana, Ohio, and Illinois. The State of Indiana was divided into seven areas on the basis of the regression analysis. A set of equations for estimating peak discharges with recurrence intervals of 2, IO, 25, 50, and 100 years was developed for each area. Significant basin characteristics in the equations are drainage area, channel length, channel slope, mean annual precipitation, storage, precipitation intensity, and a runoff coefficient. Standard errors of estimate for the equations range from 24 to 45 percent. Methods are also presented for estimating flood magnitude and frequency at sites on gaged streams. Flood-frequency data based on observed peaks are given for 270 gaged locations. Twenty of these are on regulated streams, and six are on urban streams. Basin characteristics are also included car 245 of the gaged locations on unregulated and nonurban streams. No techniques are given for estimating flood magnitude and frequency at ungaged sites on regulated or urban streams. A rainfall-runoff model was tlsed to synthesize long-term peak data at 11 gaged locations on small streams. Flood-frequency curves developed from the long-term synthetic data were combined with curves based on short-term observed data to provide weighted estimates of flood magnitude and frequency at the rainfall-runoff stations.

Indiana

Evaluation of an open earthquake early warning system in Mexico, and laboratory tests of their sensors

Microelectromechanical system (MEMS) accelerometers are useful for seismological and engineering applications because of their ability to record unsaturated large seismic signals. Recent advances in MEMS technologies enable the design of instruments with improved capabilities that also allow the recording of small signals. As a result, MEMS can be useful across a broad dynamic range and for both major earthquakes and smaller magnitude events. Here, we analyze the performance of a MEMS‐based accelerometer with the capability of real‐time data transmission. We discuss the self‐noise level, dynamic range, and sensitivity, along with the timing precision and data transmission latency, and compare these parameters to other MEMS‐based instruments. We also summarize observations from a regional network deployed in southern Mexico over a period of 3+ yr for the purpose of earthquake early warning. In addition to the sensor evaluation, we present a large, openly available data set of strong motion data from the Mexican network that comprises continuous ground‐motion records from 24 accelerometers in the period between 2017 and 2022.

Seismological Research Letters

Statistical approaches for modeling correlated grade and tonnage distributions and applications for mineral resource assessments

Correlations between grade and tonnage exist in mineral resource data compiled from published reports, but they are not always addressed during quantitative assessment of undiscovered mineral resources. Failure to account for correlated grade and tonnage distributions can result in geologically unrealistic assessment results. Current software tools simulate univariate ore tonnage and multivariate resource grades of undiscovered deposits independently. As a result, analysts are forced to rely on ad-hoc solutions to minimize the correlation issues by: 1) creating subsets of data with restricted criteria; 2) truncating grade and tonnage distributions; and 3) testing model robustness using exploratory data analysis. While these methods represent pragmatic solutions, the statistical solutions presented here provide additional options to address real correlations in grade and tonnage data used for mineral resource assessments. We present a modified version of the MapMark4 package in R that introduces two alternatives for modeling grade and tonnage distributions, consisting of a multivariate solution that accounts for correlations between ore tonnage and metal grades and an empirical solution that utilizes simple random sampling with replacement to reproduce coupled grades and tonnages from the input data. We present simulations for contained ore and metal for three case studies representing tungsten skarn, komatiite-hosted nickel, and sediment-hosted carbonate amagmatic zinc-lead (Mississippi Valley-type) deposits. Employing the methods presented here yields quantitative mineral resource assessment results that more closely reflect the empirical distributions of grades and tonnages observed in nature and expands the applicability of these tools for ongoing critical mineral resource assessments.

Applied Computing and Geosciences

Comparing subduction ground-motion models to observations for Cascadia

We evaluate Cascadia subduction ground-motion models (GMMs), considered for the 2023 US National Seismic Hazard Model (NSHM) update, by comparing observations to model predictions. The observations comprise regional recordings from intraslab earthquakes, including contributions from 2021 and 2022 events in southern Cascadia and global records from interface earthquakes. Since the 2018 NSHM update, new GMMs for Cascadia have been published by the Next Generation Attenuation (NGA)-Subduction Project that require independent evaluation. In the regional intraslab comparisons, we highlight a characteristic frequency dependence for Cascadia data, with short periods having lower ground motions and longer periods being comparable to other subduction zones. We evaluate differences in northern and southern Cascadia and find that the NGA-Subduction GMMs developed using southern Cascadia data perform better in this region than the model that did not consider these data. We compare ground-motion variability in Cascadia with the NGA-Subduction model predictions and find differences at short periods ( T = 0.1 s) due to the use of global versus regional data in the development of these models. Moreover, the within-event component of aleatory variability from the GMMs overpredicts the standard deviation of Cascadia recordings at very short periods ( T < 0.05 s). Using global interface earthquakes as a proxy to evaluate the Cascadia GMMs, we find long-period overprediction from a simulation-based GMM and some of the empirical GMMs. When comparing recent observations, we find a similar misfit to GMMs and the 2010 and 2022 Ferndale earthquakes. Finally, we observe different basin amplification factors arising in different subsets of the data, which indicate that differences in basin factors between empirical GMMs could arise from the data selection choices by the developers. As part of evaluating the regional basin terms, we apply basin amplification factors from the magnitude 9 Cascadia earthquake simulations to the empirical GMMs for interface earthquakes. The comparisons presented in this study indicate that the NGA-Subduction GMMs for Cascadia perform well relative to observations and older subduction GMMs.

British Columbia, California, Oregon, Washington

Evaluating machine learning approaches to identify and predict oil and gas produced water lithium concentrations

Recently, the demand for battery-grade lithium has substantially increased, largely due to electrification of the transportation sector. The search for new lithium sources has turned to produced waters (frequently brines), a large-volume wastewater by-product of oil and gas extraction. Geochemical analysis indicates the presence of varying concentrations of lithium from produced water samples collected across the United States and represented in the U.S. Geological Survey’s National Produced Water Geochemical Database, as well as mixtures of Marcellus Shale produced water included in the Pennsylvania Department of Environmental Protection’s Oil and Gas Well Waste Reports. We first examined whether the geochemical signature of the lithium-bearing produced waters is sufficiently distinct so that machine learning (ML) can be used to correctly classify samples to the formation of origin. The produced water sample data used to assess classification accuracy were from the Marcellus Shale, Utica Shale and Point Pleasant Formation (Utica), and Smackover Formation oil and gas wells. Further, we evaluated the potential for ML to accurately classify Marcellus Shale produced water spatially (i.e., northeast versus southwest Pennsylvania). We then investigated whether ML algorithms applied to a suite of geochemical concentration data (i.e. Ba, Br, Cl, K, Mg, Sr) may be used to predict the lithium concentration of an unknown sample. Finally, we applied an estimated economic lithium grade cutoff of 150 milligrams per liter (mg/l) and assessed the utility of ML to predict whether a produced water sample would fall above or below the grade cutoff based on the suite of geochemical parameters. Four machine learning algorithms—Random Forest (RF), Gradient Boosting Trees (GBT), Extreme Boosting (XGBoost), and Deep Neural Networks (DNN) were assessed. This study successfully demonstrates that all four machine learning methods can precisely and accurately estimate lithium concentrations and geologic formation classification. The products of this study contribute to the growing body of knowledge aimed at expanding the lithium resource base within the United States.

Alabama, Arkansas, Florida, Georgia, Louisiana, Mi

A case study of maximum depositional ages from terrestrial sandstones near the Cretaceous—Paleogene transition, western Williston Basin, USA

We present a new Bayesian method for deriving maximum depositional ages from detrital K-feldspar using total-fusion 40 Ar/ 39 Ar data. Individual analyses weighted by K/Ca ratio, age uncertainty, and percent radiogenic argon prioritize a result to come from accurately measured volcanic sources. Results from this method applied to sandstones from the Hell Creek region of northeastern Montana show that detrital K-feldspar maximum depositional ages align closely with detrital U-Pb zircon ages as well as tephra based chronostratigraphic constraints from both 40 Ar/ 39 Ar and U-Pb data. An age model informed by maximum depositional ages and available tephra data provides an estimate of 1.74 ± 1.04 Ma for the duration of deposition for the Hell Creek Formation. Combined age model and maximum depositional age data suggest ≤ 1.84 Ma of missing time is represented by the Hell Creek and Fox Hills formational disconformity, coinciding with the final regression of the Western Interior seaway.

Montana

High-resolution landscape-scale maps of nutrients, phytoplankton, and related water-quality constituents in Suisun Bay and the Sacramento–San Joaquin Delta, California, during 2018—Results from high-resolution underway surveys

We examined the abundance and distribution of nutrients and phytoplankton in the tidal aquatic environments of the Sacramento–San Joaquin Delta (Delta) and Suisun, Grizzly, and Honker Bays in California by completing three spatial surveys that used continuous underway high frequency (1 hertz) measurements and sampling onboard a high-speed boat. Surveys were conducted in May, July, and October 2018. Water was sampled continuously during surveys to simultaneously collect information about the concentration and spatial distribution of all major nutrient forms together with information about the major classes of phytoplankton and associated standard field measurements of water quality, such as dissolved oxygen, dissolved organic matter, pH, salinity, specific conductance, turbidity, and water temperature. The results show a greater than 50-fold variation in nutrient and phytoplankton concentrations across space and time, providing evidence of the dynamic environmental processes that shape the ways nutrients interact with and affect Delta aquatic habitats.

Data Report

Interplay between tectonics and submarine mass transport deposits in Cortes Basin: New high-resolution geophysics in the Outer California Borderland

The Outer California Borderland (OCB) is an active transform plate boundary offshore Southern California, where the relationship between faulting and submarine mass transport deposits (MTDs) remains poorly understood. Onshore paleoseismic data provide high-resolution earthquake records, whereas marine geophysical data capture longer-term histories. Offshore fault systems pose hazards to infrastructure and dense coastal populations, particularly when linked to submarine landslides. We present new high-resolution geophysical data set (cruise SR2303), including bathymetric and CHIRP sub-bottom data integrated with legacy seismic reflection data and chronostratigraphic constraints from ODP Site 1012 to examine Quaternary MTD recurrence and tectonic controls in the Cortes Basin, OCB. Bathymetry shows deformational features, including slide scarps and previously unmapped fault segments with evidence of Holocene activity. CHIRP profiles reveal 10 stacked MTDs in the East Cortes Basin and 8 in the West Cortes Basin, spanning ∼752 ka with an average recurrence of ∼83.6 ± 1 ka. Acoustic imaging shows 7 MTD intervals coinciding with fault offset increments and fault growth suggesting earthquake-triggered mass wasting. A strong association between MTD occurrences and sea-level extremes also supports glacio-eustatic contribution to slope failure. Stratigraphic correlations suggest quasi-synchronous MTDs across the eastern and western areas, likely triggered by larger eathquakes in the Quaternary. Although the identified MTDs occur relatively far from the Southern California coast, they still pose a potential tsunamigenic hazard requiring further assessment. Moreover, if linked to earthquakes along major strike-slip faults, for example, the Ferrelo fault, the MTDs may provide valuable proxies to constrain rupture scenarios and fault connectivity within the understudied OCB.

California

Developing international standards and guidelines for disseminating and validating simulated ground motions

We are leading an effort to develop international standards and guidelines for curating, disseminating, and validating simulated ground-motion data. This effort is organized as a working group within the Consortium of Organizations for Strong Motion Observation Systems (COSMOS). In 2022 we held online workshops on 7 and 8 June and 20 October. The first workshop focused on curating and disseminating simulated ground-motion data. The second workshop focused on validating simulated ground-motions for engineering applications. About 100 people participated in each of the workshops with strong representation from North America, Europe, and western Asia. In the coming year, we intend to form a technical committee to draft the international guidelines and standards while continuing to engage stakeholders from across the globe through online and in-person meetings. The key points from the workshops include: (1) Numerous groups are generating simulated earthquake ground motions and making them openly available; however there is very little coordination among groups to provide consistent interfaces for searching and retrieving data; (2) Standardizing interfaces for metadata and data access should consider agile approaches that can adapt to changing capabilities and user needs while building upon existing efforts; (3) A distributed architecture is preferred by most participants to allow institutions to host and manage their own data while broadcasting their holdings to a combined catalog; (4) Validation of ground-motion simulations applies to the entire workflow for simulating earthquake ground-motions, including the rupture model, seismic velocity model, and seismic wave propagation software; (5) Metrics to evaluate the validation are application dependent; more research is needed to tie structural response characteristics to ground-motion characteristics; and (6) Validation results should provide a clear, transparent, and quantitative assessment of the simulated ground motions.

Conference Paper

The 3D National Topography Model Call for Action—Part 2: The Next Generation 3D Elevation Program

The three-dimensional (3D) National Topography Model initiative to integrate elevation and hydrography data includes the next generation of hydrography data from the 3D Hydrography Program and the next generation of elevation data from the 3D Elevation Program (3DEP). The first-ever collection of light detection and ranging (lidar) data for the nation (IfSAR for Alaska) provides a critical baseline reference, and the addition of multiple repeat elevation mapping projects as part of the next generation of 3DEP would substantially expand analysis capabilities. As the U.S. Geological Survey (USGS) is closing in on our goal of complete coverage with 3DEP data available or in progress for 98.3 percent of the Nation at the end of fiscal year 2024, the USGS is already transitioning to the next generation of 3DEP. Based on the 3D Nation Study results and input from a broad range of stakeholders, the USGS National Geospatial Program has finalized a new design for 3DEP that provides increased lidar quality levels and refresh rates. The new program is designed with more flexibility to meet changing user needs and take advantage of improvements in mapping technologies. The program will aim to expand the level of interagency coordination for topobathymetric lidar acquisition for inland rivers. The next generation of 3DEP will also aim to emphasize research, including advancing program design, products, and services and engaging and leveraging the evolving 3D industry. Research goals also include becoming more flexible in meeting user needs and taking advantage of evolving remote-sensing technologies. The program also plans to move from focusing on producing standard products to producing a concept of a 3D Nation Ecosystem with a variety of inputs, products, and services.

Circular

A synthesis engine for constructing geologic maps of the United States

The geologic history of the United States is cataloged in thousands of geologic maps produced during many decades. However, the disparate nature of these individual maps makes it challenging to assess resources, research geologic histories, or characterize natural hazards holistically across the Nation. The U.S. House of Representatives 2020 appropriations bill for the U.S. Department of the Interior (H.R. 116-100) requires the U.S. Geological Survey to “bring together detailed national and continental-resolution [two-dimensional] and [three-dimensional] information produced throughout the Survey and by [F]ederal and [S]tate partners.” In response to this directive, this report presents a compilation and synthesis of geologic maps across the United States in the form of a relational database. The synthesis database includes thematic maps that synthesize the Nation’s geology, and retains the original input maps as well as linkages to standardized vocabularies to aid the discoverability of geologic information. Specifically, the synthesis database is targeted toward producing four National-resolution maps for the conterminous United States: Quaternary geology, the geology at the Earth’s surface, pre-Quaternary geology, and Precambrian geology. In addition, the synthesis database includes the infrastructure necessary to expand to additional resolutions in the future.

conterminous United States

On-demand global Landsat evapotranspiration product: Development, evaluation, and dissemination

Global actual evapotranspiration (ET) is one of the essential climate variables needed to understand and manage the relationships among food, energy, and water resources. The U.S. Geological Survey Earth Resources Observation and Science (EROS) Center launched a provisional ET product in 2020, offering on-demand, field-scale global coverage derived from Landsat data through the EROS Science Processing Architecture (ESPA) platform. The ESPA interface provides ET data for cloud-free Landsat overpasses starting in 1982 with Landsat 4 through the current Landsat 9. The ET data are delivered as a Provisional Level-3 Science product created using the Operational Simplified Surface Energy Balance (SSEBop) model. Landsat surface temperature and reference ET are the main model drivers along with vegetation index and net radiation for model parameterization. A large volume of Landsat-based ET orders (e.g., over 1,200,000 images from June 2020 through December 2025) around the world indicate increasing awareness and application of the ET data. The ESPA platform enables land and water resource managers and researchers to access a first-order ET product without requiring advanced knowledge of remote sensing technology or evapotranspiration modeling. We present the methodology and workflow of the on-demand Landsat ET product and its performance evaluations over diverse hydro-climatic settings. The product can help estimate field-scale consumptive water use and thus quickly and consistently assess historical water use, allocation, and budget to inform water management under changing environments. Future ET data aggregated to monthly and seasonal time scales are expected to enhance integration with decision-making tools and procedures.

Remote Sensing of Environment

Large springs in the Valley and Ridge Province in Tennessee

Approximately 2,700 miscellaneous discharge measurements for 171 large springs in 28 counties of East Tennessee, predominantly within the Valley and Ridge physiographic province, were analyzed statistically and results tabulated to summarize data useful to the Appalachian Valleys-Piedmont Regional Aquifer System Analysis study. The number of measurements at each spring ranged from 1 to 65. Information from each spring includes station numbers, latitude, longitude, spring name and where data are sufficient, an estimate of the mean discharge and the discharge exceeded by 75%, 50%, and 25% of the miscellaneous measurements. Data are referenced to locations on a 1:1,000 ,000-scale map. The highest mean spring discharge was 32.2 cu ft/sec (14,5000 gallons/min).

Tennessee

Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2023

As part of a long-term cooperative program to monitor water quality within the Scituate Reservoir drainage area, the U.S. Geological Survey, in cooperation with Providence Water (formerly the Providence Water Supply Board), collected streamflow and water-quality data in tributaries to the Scituate Reservoir, Rhode Island. Streamflow and concentrations of chloride and sodium estimated from records of specific conductance for 16 tributaries were used to calculate loads of chloride and sodium during water year 2023 (October 1, 2022, through September 30, 2023). Water-quality samples were collected by Providence Water at 38 sampling stations on tributaries to the Scituate Reservoir during water year 2023. These water-quality data are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields of selected water-quality constituents for water year 2023. Annual mean streamflows for monitoring stations in this study ranged from 0.47 to 34.4 cubic feet per second during water year 2023. At the 16 continuous-record streamgages, tributaries transported about 3,000 metric tons of chloride and 1,900 metric tons of sodium to the Scituate Reservoir; annual chloride yields for the tributaries ranged from 19 to 200 metric tons per square mile, and annual sodium yields ranged from 13 to 120 metric tons per square mile. At the stations where water-quality samples were collected by Providence Water, the medians of the median daily loads were 65,000 million colony forming units per day for coliform bacteria, 870 million colony forming units per day for Escherichia coli , 200 kilograms per day for chloride, 8.2 grams per day as nitrogen for nitrite, 520 grams per day as nitrogen for nitrate, and 300 grams per day as orthophosphate for phosphate. The medians of the median yields were 25,000 million colony forming units per day per square mile for coliform bacteria, 600 million colony forming units per day per square mile for Escherichia coli , 65 kilograms per day per square mile for chloride, 4.6 grams per day per square mile as nitrogen for nitrite, 180 grams per day per square mile as nitrogen for nitrate, and 180 grams per day per square mile as orthophosphate for phosphate.

Rhode Island

Computational electromagnetic geophysics for groundwater system studies: A review on established practices and recent advances

Identifying effective solutions for locating groundwater resources and ensuring the quality of drinking water is increasingly urgent, given the challenges posed by climate change and population growth. This review investigates electromagnetic geophysical imaging techniques, in both time- and frequency-domain, that can provide valuable insights for groundwater assessment. We explore computational electromagnetic methods used to evaluate electromagnetic data and several recent hydrogeophysical case studies. As open-source frameworks for modeling electromagnetic geophysical problems become available, a broader range of researchers can interpret their data with computationally advanced software. We provide an overview of documented open-source codes for evaluating electromagnetic data and analyze various hydrological targets in relation to their electromagnetic surveying technique and the computational method applied. Furthermore, we evaluate the potential of advanced computational techniques, including three-dimensional modeling, non-deterministic inversion and machine learning, to couple geophysical with numerical groundwater modeling and apply it in groundwater system studies. Despite obstacles such as complexity and resource demands, our findings indicate that the quantification and integration of predictive uncertainties from both electromagnetic and hydrological data and simulations would significantly improve the reliability of hydrogeophysical models. This can lead to a deeper understanding of groundwater systems and improved management practices.

Journal of Hydrology

High-pass corner frequency selection and review tool for use in ground-motion processing

Raw seismological waveform data contain noise from the instrument’s surroundings and the instrument itself that can dominate recordings at low and high frequencies. To use these data in ground‐motion modeling, the effects of noise on the signals must be reduced and the signals’ usable frequency range identified. We present automated procedures to efficiently reduce low‐frequency noise that are implemented in the software package gmprocess. These procedures check for, and as needed remove, low‐frequency artifacts in the displacement record using polynomial fits, which can be used in combination with existing signal‐to‐noise ratio (SNR)‐based corner‐frequency selection procedures. The automated selections are then efficiently verified and refined using a graphical user interface (GUI) that plots relevant ground‐motion time series and spectra and tracks modifications to signal processing parameters. We demonstrate these procedures using recordings from the 2020 M 5.1 Sparta, North Carolina, and the 2013 M 4.7 southern Ontario earthquakes. Data processed with the SNR‐only and polynomial criteria for these events contain displacement artifacts in 37% and 23% of processed traces, respectively. Records with remaining artifacts are corrected manually using the GUI. These processing steps illustrate the workflow for efficient data processing with quality control.

Seismological Research Letters

ECCOE Landsat quarterly Calibration and Validation report—Quarter 1, 2024

Executive Summary The U.S. Geological Survey Earth Resources Observation and Science Calibration and Validation (Cal/Val) Center of Excellence (ECCOE) focuses on improving the accuracy, precision, calibration, and product quality of remote-sensing data, leveraging years of multiscale optical system geometric and radiometric calibration and characterization experience. The ECCOE Landsat Cal/Val Team continually monitors the geometric and radiometric performance of active Landsat missions and makes calibration adjustments, as needed, to maintain data quality at the highest level. This report provides observed geometric and radiometric analysis results for Landsats 8 and 9 for quarter 1 (January–March), 2024. All data used to compile the Cal/Val analysis results presented in this report are freely available from the U.S. Geological Survey EarthExplorer website: https://earthexplorer.usgs.gov . This quarterly report is the third to include analysis results for Landsat 9, which was launched in September 2021. The inclusion of Landsat 9 analysis results was dependent on two factors: a complete reprocessing of the Landsat 9 data archive and enough time elapsing to begin formulating lifetime trends. In April 2023, all Landsat 9 image data acquired since the satellite’s launch were reprocessed to take advantage of calibration updates identified by the ECCOE Landsat Cal/Val Team. Additional information about the Landsat 9 reprocessing effort is available at https://www.usgs.gov/landsat-missions/news/upcoming-reprocessing-all-landsat-9-data . Additional information about Landsat 9 prelaunch, commissioning, and early on-orbit imaging performance is available at https://www.mdpi.com/journal/remotesensing/special_issues/15B4V2K92K . This quarterly report is the first to not include analysis results for Landsat 7 because Enhanced Thematic Mapper Plus imaging was suspended on January 19, 2024, after the satellite transitioned into full sunlight. The satellite has been drifting since early 2022 after being lowered from the nominal orbit altitude, and the transition into full sunlight is a result of the satellite operating in its extended science mission. Additional information about the imaging suspension is available at https://www.usgs.gov/landsat-missions/news/landsat-7-imaging-suspended . Additional information about the Landsat 7 extended science mission is available at https://www.usgs.gov/landsat-missions/landsat-7-extended-science-mission .

Open-File Report

ECCOE Landsat quarterly Calibration and Validation report—Quarter 2, 2024

Executive Summary The U.S. Geological Survey Earth Resources Observation and Science Calibration and Validation (Cal/Val) Center of Excellence (ECCOE) focuses on improving the accuracy, precision, calibration, and product quality of remote-sensing data, leveraging years of multiscale optical system geometric and radiometric calibration and characterization experience. The ECCOE Landsat Cal/Val Team continually monitors the geometric and radiometric performance of active Landsat missions and makes calibration adjustments, as needed, to maintain data quality at the highest level. This report provides observed geometric and radiometric analysis results for Landsats 8 and 9 for quarter 2 (April–June) of 2024. All data used to compile the Cal/Val analysis results presented in this report are freely available from the U.S. Geological Survey EarthExplorer website: https://earthexplorer.usgs.gov . This is the fourth quarterly report to include analysis results for Landsat 9, which was launched in September 2021. The inclusion of Landsat 9 analysis results was dependent on two factors: a complete reprocessing of the Landsat 9 data archive and enough time elapsing to begin formulating lifetime trends. In April 2023, all Landsat 9 image data acquired since the satellite’s launch were reprocessed to take advantage of calibration updates identified by the ECCOE Landsat Cal/Val Team. Additional information about the Landsat 9 reprocessing effort is available at https://www.usgs.gov/landsat-missions/news/upcoming-reprocessing-all-landsat-9-data . Additional information about Landsat 9 prelaunch, commissioning, and early on-orbit imaging performance is available at https://www.mdpi.com/journal/remotesensing/special_issues/15B4V2K92K . This is the second quarterly report that does not include analysis results for Landsat 7 because Enhanced Thematic Mapper Plus imaging was suspended on January 19, 2024, after the satellite transitioned into full sunlight. The satellite has been drifting since early 2022 when it was lowered from the nominal orbit altitude, and the transition into full sunlight is a result of the satellite operating in its extended science mission. Additional information about the imaging suspension is available at https://www.usgs.gov/landsat-missions/news/landsat-7-imaging-suspended . Additional information about the Landsat 7 extended science mission is available at https://www.usgs.gov/landsat-missions/landsat-7-extended-science-mission .

Open-File Report