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USGS2016

Users and uses of Landsat 8 satellite imagery—2014 survey results

Executive Summary In 2013, Landsat 8 began adding high quality, global, moderate-resolution imagery to the more than 40-year archive of Landsat imagery. To assess the potential effects of the availability of Landsat 8 imagery on users and their work, the U.S. Geological Survey (USGS) Land Remote Sensing Program (LRS) initiated a survey of Landsat users. The objectives of the survey were to 1. Characterize various Landsat user groups, such as United States (U.S.) and international users and Landsat 8 and non-Landsat 8 users; 2. Identify any differences among user groups in uses and preferences; 3. Measure the importance of and satisfaction with Landsat 8 attributes; 4. Assess the importance to users of the frequency of usable imagery; and 5. Determine any challenges in using Landsat 8. The online survey was sent to 51,617 Landsat users registered with USGS in May 2014. Almost 13,000 people responded to the survey for a response rate of 25 percent (n = 12,966). Current Landsat users (users who had used Landsat in their work in the year prior to the survey) composed 89 percent of the sample (n = 11,549) and past Landsat users composed 11 percent (n = 1,417). The results reported here apply to current Landsat users registered with the USGS Earth Resources Observation and Science (EROS) Center. Users from 161 countries responded to the survey. Of those, 19 percent were citizens or permanent residents of the United States and 81 percent resided in other countries. More than 70 percent of current users had used Landsat 8 in the year prior to the survey. The majority of Landsat 8 users (65 percent) were established users who used Landsat imagery regularly both before and after Landsat 8 imagery became available. The average current Landsat user was male, 36 years old, and highly educated, with 9 years of experience using satellite imagery or geographic information system (GIS) software. Landsat 8 users had, on average, two more years of experience than non-Landsat 8 users. Users were employed predominantly by academic institutions (65 percent), followed by private businesses (13 percent), Federal governments (10 percent), State and local governments (6 percent), and nonprofit organizations (6 percent). Of the Landsat imagery obtained in the past year by current users, on average 31 percent came from a Landsat 8 sensor. An equivalent amount came from the Landsat 7 ETM+ sensor (33 percent); slightly less came from Landsats 4 and 5 TM sensors (27 percent). Much less came from Landsats 1 through 5 MSS sensors (5 percent). Overall, more than a third of users’ work used Landsat imagery (38 percent). Of this work, on average, 37 percent of the work was operational. Landsat 8 users considered a greater proportion of their work operational than non-Landsat 8 users (39 percent compared with 29 percent). Environmental sciences and management were the most commonly selected primary applications (selected by 42 percent of users). Land use/land cover (23 percent) was the second most commonly selected primary application, followed by education (12 percent), agriculture (9 percent), and planning and development (6 percent). Landsat 8 users were asked to rank the importance of certain attributes in determining whether to use Landsat 8 imagery in their work. The archive was ranked most important, followed by cost, spatial resolution, extent of coverage, data quality, and frequency of revisit. Users were asked how satisfied they were with these same attributes as they currently apply to Landsat 8 imagery. On average, users were most satisfied with lack of cost, extent of coverage, data quality, and the archive, but they were satisfied with all attributes. Users were asked how often they needed Landsat imagery to meet various requirements for their primary application. The survey question specifically asked how often users needed usable imagery, which differs from how often they would like the Landsat satellites to acquire an image. Users were asked to identify their needed frequency of usable imagery for the following levels: 1. Threshold level—the minimum frequency of usable imagery needed to be of any value to their primary application. 2. Breakthrough level—the frequency of usable imagery that would result in a significant improvement for their primary application of the imagery. 3. Target level—the frequency of usable imagery that would only provide a limited additional increase in the expected performance for their primary application. To meet the threshold level, three-quarters of users needed usable imagery every 17 days or less frequently. At the breakthrough level, two-thirds of users (64 percent) needed a usable image every 5–16 days. The current constellation of two satellites (Landsat 7 and 8) is capable of meeting the threshold and breakthrough needs of most users at least some of the time, but a single satellite would be highly unlikely to do so. Two-fifths of users (40 percent) felt that usable imagery provided every 4 days or more frequently would meet their target level which the current Landsat constellation cannot provide. Landsat 8 users were significantly more likely than non-Landsat 8 users to need usable imagery more frequently to meet their target levels. Additionally, U.S. Landsat 8 users were significantly more likely than other Landsat users to need usable imagery more frequently in order meet both their breakthrough and target levels. To explore the effect of the availability of Landsat 8 imagery on Landsat imagery use in general, established users (those who had consistently used Landsat imagery both before and after Landsat 8 imagery became available) using Landsat 8 imagery were asked about changes in the amount of Landsat imagery they used. The majority of established users using Landsat 8 imagery (60 percent) reported an average increase of 51 percent in the number of scenes obtained after Landsat 8 imagery became available. Landsat 8 users were asked if they had encountered challenges in using Landsat 8 whereas non-Landsat 8 users were asked if such challenges had played a role in why they were not using Landsat 8 imagery. Although many users did not encounter challenges when using or trying to use Landsat 8 data, slightly less than 30 percent did encounter issues with processing the data to a usable point. The most common issue reported was not being able to create or have access to a surface reflectance corrected product. Other challenges were related to the file sizes of images being too large to download, store, or analyze. There were no statistically significant differences between Landsat 8 and non-Landsat 8 users in terms of challenges encountered when using or trying to use the imagery, which indicates that users were not unduly discouraged by the challenges they may have encountered. When asked about potential consequences of not using Landsat 8, more than half of the non-Landsat 8 users did not report detrimental effects on their work from not using the imagery. Of those who did report detrimental effects, decreased quality of work, decreased scope of work, and increased time spent on work were the most common.

Open-File Report↗

USGS2018

Using heat as a tracer to determine groundwater seepage in the Indian River Lagoon, Florida, April–November, 2017

The U.S. Geological Survey, in cooperation with the St. Johns River Water Management District, conducted a study to examine water fluxes in two small study areas in the Indian River Lagoon. Vertical arrays of temperature sensors were placed at multiple locations in the lagoon bed to measure temperature time series in the vertical profile. These data at one of the study areas, Eau Gallie, were used in two numerical models, 1DTempPro and VFLUX, to estimate seepage flux rates into the lagoon. 1DTempPro uses an inverse-modeling approach to calibrate groundwater flux to the measured temperature time series. VFLUX isolates the fundamental frequency signal in the temperature data and utilizes the resulting amplitude and phase differences between sensor locations to determine vertical water flux. Field measurements were made during two time periods, March 23 to April 28, 2017, and June 1 to November 3, 2017. Simulating the first, drier period at one location with 1DTempPro helped determine reasonable seepage fluctuations and provided guidelines for choosing which temperature sensor pairs used in the VFLUX simulations would produce the best results. VFLUX simulations at eight locations indicated daily average seepage flux rates of less than 20 centimeters per day (cm/d) and substantial seepage flux out to a distance of at least 110 meters from shore. The spatial variation in average seepage flux rates within 40 meters of shore seemed large, ranging from about 3 to 20 cm/d. In the VFLUX application using the June 1–November 3, 2017 data, the seepage flux has a higher magnitude and fluctuation than the first simulation period, making the isolation of the fundamental temperature frequency signal in the temperature data difficult. However, useful partial or full simulations were achieved at 6 of the 10 locations. The storm surge of Hurricane Irma on September 10, 2017, changed the depths of the sensors relative to the lagoon bed and disrupted the ability of VFLUX to compute seepage flux for the posthurricane period. The June 1 to November 3, 2017, computed seepage flux rates were higher than those for the March 24 to April 28, 2017, period and were sometimes as great as 40 cm/d, and more than 60 cm/d at one location. The seepage time-series data collected during Hurricane Irma indicates a downward seepage flux as a result of the storm surge, followed by upwelling from precipitation recharge inland. The average seepage flux rates are higher than those during the March–April period and are over 25 cm/d near the coast and about 20 cm/d 130 meters offshore.

Florida↗

USGS2021

System characterization report on the China-Brazil Earth Resources Satellite-4A (CBERS–4A)

Executive Summary This report addresses system characterization of the China-Brazil Earth Resources Satellite-4A (CBERS–4A) multispectral remote sensing satellite and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence in 2021. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions. CBERS–4A is a joint Chinese-Brazilian medium-resolution satellite launched in December 2019 by the China National Space Agency/National Institute for Space Research (Brazil) on a Chang Zheng 4B rocket from the Taiyuan Satellite Launch Center for Earth resources monitoring. The CBERS–4A mission continues the CBERS mission that has been in continual operation since the launch of CBERS–1 in 1999. The CBERS–4A satellite was designed and built by Academia Chinesa de Tecnologia Espacial/National Institute for Space Research and uses the Phoenix-Eye bus. CBERS–4A carries the multispectral camera and wide field imager sensors for medium-resolution land imaging and the wide swath panchromatic and multispectral camera sensor for high-resolution land imaging. This assessment focused on the multispectral camera sensor only. More information on CBERS sensors is available in the “ 2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium ” and at https://www.gov.br/pt-br/servicos/obter-imagens-de-sensoriamento-remoto-da-terra-geradas-pelo-satelite-cbers-04a . The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that CBERS–4A provides an interior (band-to-band) geometric performance in the range of −0.02 to −0.16 pixel; an exterior geometric accuracy performance of −22.02 (−1.47 pixels) to −16.06 meters (−1.07 pixels); a radiometric accuracy performance of –0.006 to 0.925 (offset and slope); and a spatial performance for relative edge response in the range of 0.39 to 0.44, for full width at half maximum in the range of 2.38 to 2.56 pixels, and for a modulation transfer function at a Nyquist frequency in the range of 0.001 to 0.013.

Open-File Report↗

USGS1983

General characteristics and availability of Landsat 3 and heat capacity mapping mission thermal infrared data

Two satellite systems launched by the National Aeronautics and Space Administration (NASA) in 1978 carried sensors which operated in the thermal infrared (IR) region of the electromagnetic spectrum, The final IR radiation data provide spectral information about the physical properties of the Earth's surficial materials not duplicated in either the visible or reflective IR wavelength regions. Landsat 3, launched on March 5, 1978, contained a thermal sensor as part of the multispectral scanner (MSS) system. The sensor operated in the 10.4- to 12.6-?m (band 8) wavelength region and produced imagery with a ground resolution of approximately 235 m. Launched on April 26) 1978) the Heat Capacity Mapping Mission (HCMM) spacecraft carried a sensor, the heat capacity mapping radiometer (HCMR) which operated in the 10.5- to 12.5?m wavelength region and produced imagery with a ground resolution of approximately 600 m at nadir. The HCMM satellite acquired over 6,600 data passes of visible (0.55-1.1 ?m), as well as thermal IR data, over North America, Europe, and Australia. General characteristics and availability of Landsat 3 and HCMM thermal IR data are discussed. Landsat 3 reflected IR band 7 (0.55-1.1 ?m) and Landsat 3 band 8 thermal data acquired over the eastern and western United States are analyzed and compared with HCMM visible, thermal IR, thermal inertia, and day-night temperature difference imagery for geologic applications. Digitally processed and enhanced HCMM data (high-pass filters, diagonal derivatives, and band ratios), produced by the U.S. Geological Survey, Flagstaff) Ariz., are presented for geologic interpretation.

Open-File Report↗

USGS1996

Summary of suspended-solids concentration data, San Francisco Bay, California, water year 1994

Suspended-solids concentration data were collected in San Francisco Bay during water year 1994. Optical backscatterance sensors and water samples were used to monitor suspended solids continuously at two sites in Suisun Bay, two sites in Central San Francisco Bay, and three sites in South San Francisco Bay. Sensors were positioned at two depths at each site. In addition, a shallow-water instrument package was deployed in South San Francisco Bay three times for periods of several weeks to measure suspended-solids concentration and water velocity. Water samples were collected periodically and were analyzed for concentrations of suspended solids. The results of the analyses were used to calibrate the electrical output of the optical backscatterance sensors. This report presents the data-collection methods used and summarizes the suspended-solids concentration data collected from October 1993 through September 1994. Calibration plots and edited data for each sensor also are presented.

California↗

USGS1996

Summary of suspended-solids concentration data, San Francisco Bay, California, Water Year 1995

Suspended-solids concentration data were collected in San Francisco Bay during water year 1995 (October 1, 1994September 30, 1995). Optical backscatterance sensors and water samples were used to monitor suspended solids continuously at two sites in Suisun Bay, two sites in Central San Francisco Bay, and three sites in South San Francisco Bay. Sensors were positioned at two depths at each site. Water samples were collected periodically and were analyzed for concentrations of suspended solids. The results of the analyses were used to calibrate the electrical output of the optical backscatterance sensors. This report presents the data-collection methods used and summarizes the suspended-solids concentration data collected from October 1994 through September 1995. Calibration plots and edited data for each sensor also are presented.

Open-File Report↗

USGS1998

Summary of suspended-solids concentration data, San Francisco Bay, California, water year 1996

Suspended-solids concentration data were collected in San Francisco Bay during water year 1996 (October 1, 1995?September 30, 1996). Optical backscatterance sensors and water samples were used to monitor suspended solids at three sites in Suisun Bay, three sites in Central San Francisco Bay, and three sites in South San Francisco Bay. Sensors were positioned at two depths at most sites. Water samples were collected periodically and were analyzed for concentrations of suspended solids. The results of the analyses were used to calibrate the electrical output of the optical backscatterance sensors. This report presents the data-collection methods used and summarizes the suspended-solids concentration data collected from October 1995 through September 1996. Calibration plots and plots of edited data for each sensor also are presented.

Open-File Report↗

USGS2010

Bedload-surrogate monitoring technologies

Advances in technologies for quantifying bedload fluxes and in some cases bedload size distributions in rivers show promise toward supplanting traditional physical samplers and sampling methods predicated on the collection and analysis of physical bedload samples. Four workshops held from 2002 to 2007 directly or peripherally addressed bedload-surrogate technologies, and results from these workshops have been compiled to evaluate the state-of-the-art in bedload monitoring. Papers from the 2007 workshop are published for the first time with this report. Selected research and publications since the 2007 workshop also are presented. Traditional samplers used for some or all of the last eight decades include box or basket samplers, pan or tray samplers, pressure-difference samplers, and trough or pit samplers. Although still useful, the future niche of these devices may be as a means for calibrating bedload-surrogate technologies operating with active- and passive-type sensors, in many cases continuously and automatically at a river site. Active sensors include acoustic Doppler current profilers (ADCPs), sonar, radar, and smart sensors. Passive sensors include geophones (pipes or plates) in direct contact with the streambed, hydrophones deployed in the water column, impact columns, and magnetic detection. The ADCP for sand and geophones for gravel are currently the most developed techniques, several of which have been calibrated under both laboratory and field conditions. Although none of the bedload-surrogate technologies described herein are broadly accepted for use in large-scale monitoring programs, several are under evaluation. The benefits of verifying and operationally deploying selected bedload-surrogate monitoring technologies could be considerable, providing for more frequent and consistent, less expensive, and arguably more accurate bedload data obtained with reduced personal risk for use in managing the world's sedimentary resources. Twenty-six papers are published for the first time as part of the 2007 International Bedload-Surrogate Monitoring Workshop (listed in table 2 in alphabetical order by name of first author). Sequential page numbering of the papers begins on page 38, after the last page of the report. The report plus the 26 papers comprise 430 pages.

Scientific Investigations Report↗

USGS2013

Sources and characteristics of organic matter in the Clackamas River, Oregon, related to the formation of disinfection by-products in treated drinking water

This study characterized the amount and quality of organic matter in the Clackamas River, Oregon, to gain an understanding of sources that contribute to the formation of chlorinated and brominated disinfection by-products (DBPs), focusing on regulated DBPs in treated drinking water from two direct-filtration treatment plants that together serve approximately 100,000 customers. The central hypothesis guiding this study was that natural organic matter leaching out of the forested watershed, in-stream growth of benthic algae, and phytoplankton blooms in the reservoirs contribute different and varying proportions of organic carbon to the river. Differences in the amount and composition of carbon derived from each source affects the types and concentrations of DBP precursors entering the treatment plants and, as a result, yield varying DBP concentrations and species in finished water. The two classes of DBPs analyzed in this study-trihalomethanes (THMs) and haloacetic acids (HAAs)-form from precursors within the dissolved and particulate pools of organic matter present in source water. The five principal objectives of the study were to (1) describe the seasonal quantity and character of organic matter in the Clackamas River; (2) relate the amount and composition of organic matter to the formation of DBPs; (3) evaluate sources of DBP precursors in the watershed; (4) assess the use of optical measurements, including in-situ fluorescence, for estimating dissolved organic carbon (DOC) concentrations and DBP formation; and (5) assess the removal of DBP precursors during treatment by conducting treatability "jar-test" experiments at one of the treatment plants. Data collection consisted of (1) monthly sampling of source and finished water at two drinking-water treatment plants; (2) event-based sampling in the mainstem, tributaries, and North Fork Reservoir; and (3) in-situ continuous monitoring of fluorescent dissolved organic matter (FDOM), turbidity, chlorophyll- a , and other constituents to continuously track source-water conditions in near real-time. Treatability tests were conducted during the four event-based surveys to determine the effectiveness of coagulant and powdered activated carbon (PAC) on the removal of DBP precursors. Sample analyses included DOC, total particulate carbon (TPC), total and dissolved nutrients, absorbance and fluorescence spectroscopy, and, for regulated DBPs, concentrations of THMs and HAAs in finished water and laboratory-based THM and HAA formation potentials (THMFP and HAAFP, respectively) for source water and selected locations throughout the watershed. The results of this study may not be typical given the record and near record amounts of precipitation that occurred during spring that produced streamflow much higher than average in 2010-11. Although there were algal blooms, lower concentrations of chlorophyll- a were observed in the water column during the study period compared to historical data. Concentrations of DBPs in finished (treated) water averaged 0.024 milligrams per liter (mg/L) for THMs and 0.022 mg/L for HAAs; maximum values were about 0.040 mg/L for both classes of DBPs. Although DBP concentrations were somewhat higher within the distribution system, none of the samples collected for this study or for the quarterly compliance monitoring by the water utilities exceeded levels permissible under existing U.S. Environmental Protection Agency (USEPA) regulations: 0.080 mg/L for THMs and 0.060 mg/L for HAAs. DOC concentrations were generally low in the Clackamas River, typically about 1.0-1.5 mg/L. Concentrations in the mainstem occasionally increased to nearly 2.5 mg/L during storms; DOC concentrations in tributaries were sometimes much higher (up to 7.8 mg/L). The continuous in-situ FDOM measurements indicated sharp rises in DOC concentrations in the mainstem following rainfall events; concentrations were relatively stable during summer base flow. Even though the first autumn storm mobilized appreciable quantities of carbon, higher concentrations of DBPs in finished water were observed 3-weeks later, after the ground was saturated from additional rainfall. The majority of the DOC in the lower Clackamas River appears to originate from the upper basin, suggesting terrestrial carbon was commonly the dominant source. Lower-basin tributaries typically contained the highest concentrations of DOC and DBP precursors and contributed substantially to the overall loads in the mainstem during storms. During low-flow periods, tributaries were not major sources of DOC or DBP precursors to the Clackamas River. Although the dissolved fraction of organic carbon contributed the majority of DBP precursors, at times the particulate fraction (inorganic sediment and organic particles including detritus and algal material) contributed a substantial fraction of DBP precursors. Considering just the main-stem sites, on average, 10 percent of THMFP and 32 percent of HAAFP were attributed to particulate carbon. This finding suggests water-treatment methods that remove particles prior to chlorination would reduce finished-water DBP concentrations to some degree. Overall, concentrations of THM and HAA precursors were closely linked to DOC concentrations; laboratory DBP formation potentials (DBPFPs) clearly showed that THMFP and HAAFP were greatest in the downstream tributaries that contained elevated carbon concentrations. However, carbon-normalized "specific" formation potentials for THMs and HAAs (STHMFP and SHAAFP, respectively) revealed changes in carbon character over time that affected the two types of DBP classes differently. HAA precursors were elevated in waters containing aromatic-rich soil-derived material arising from forested areas. In contrast, THM precursors were associated with carbon having a lower aromatic content; highest STHMFP occurred in autumn 2011 in the mainstem from North Fork Reservoir downstream to LO DWTP. This pattern suggests the potential for a link between THM precursors and algal-derived carbon. The highest STHMFP value was measured within North Fork Reservoir, indicating reservoir derived carbon may be important for this class of DBPs. Weak correlations between STHMFP and SHAAFP emphasize that precursor sources for these types of DBPs may be different. This highlights not only that different locations within the watershed produce carbon with different reactivity (specific DBPFP), but also that different management approaches for each class of DBP precursors could be required for control. Treatability tests conducted on source water during four basin-wide surveys demonstrated that an average of about 40 percent of DOC can be removed by coagulation. While the decrease in THMFP following coagulation was similar to DOC, the decrease in HAAFP was much greater (approximately 70 percent), indicating coagulation is particularly effective at removing HAA precursors'likely because of the aromatic nature of the carbon associated with HAA precursors. Several findings from this study have direct implications for managing drinking-water resources and for providing useful information that may help improve treatment-plant operations. For example, the use of in-situ fluorometers that measure FDOM provided an excellent proxy for DOC concentration in this system and revealed short-term, rapid changes in DOC concentration during storm events. In addition, the strong correlation between FDOM values measured in-situ and HAA5 concentrations in finished water may permit estimation of continuous HAA concentrations, as was done here. As part of this study, multiple in-situ FDOM sensors were deployed continuously and in real-time to characterize the composition of dissolved organic matter. Although the initial results were promising, additional research and engineering developments will be needed to demonstrate the full utility of these sensors for this purpose. In conclusion, although DBPFPs were strongly correlated to DOC concentration, some DBPs formed from particulate carbon, including terrestrial leaf material and algal material such as planktonic species of blue-green algae and sloughed filaments, stalks, and cells of benthic algae. Different precursor sources in the watershed were evident from the data, suggesting specific actions may be available to address some of these sources. In-situ measurements of FDOM proved to be an excellent proxy for DOC concentration as well as HAA formation during treatment, which suggests further development and refinement of these sensors have the potential to provide real-time information about complex watershed processes to operators at the drinking-water treatment plants. Follow-up studies could examine the relative roles that terrestrial and algal sources have on the DBP precursor pool to better understand how watershed-management activities may be affecting the transport of these compounds to Clackamas River drinking-water intakes. Given the low concentrations of algae in the water column during this study, additional surveys during more typical river conditions could provide a more complete understanding of how algae contribute DBP precursors. Further development of FDOM-sensor technology can improve our understanding of carbon dynamics in the river and how concentrations may be trending over time. This study was conducted in collaboration with Clackamas River Water and the City of Lake Oswego water utilities. Other research partners included Oregon Health and Science University in Hillsboro, Oregon, Alexin Laboratory in Tigard, Oregon, U.S. Geological Survey National Research Program Laboratory in Denver, Colorado, and the U.S. Geological Survey Water Science Centers in Portland, Oregon, and Sacramento, California. This project was supported with funding from Clackamas River Water, City of Lake Oswego, the U.S. Geological Survey, and the Water Research Foundation.

Oregon↗

USGS2016

Documentation and hydrologic analysis of Hurricane Sandy in New Jersey, October 29–30, 2012

In 2012, a late season tropical depression developed into a tropical storm and later a hurricane. The hurricane, named “Hurricane Sandy,” gained strength to a Category 3 storm on October 25, 2012, and underwent several transitions on its approach to the mid-Atlantic region of the eastern coast of the United States. By October 28, 2012, Hurricane Sandy had strengthened into the largest hurricane ever recorded in the North Atlantic and was tracking parallel to the east coast of United States, heading toward New Jersey. On October 29, 2012, the storm turned west-northwest and made landfall near Atlantic City, N.J. The high winds and wind-driven storm surge caused massive damage along the entire coastline of New Jersey. Millions of people were left without power or communication networks. Many homes were completely destroyed. Sand dunes were eroded, and the barrier island at Mantoloking was breached, connecting the ocean with Barnegat Bay. Several days before the storm made landfall in New Jersey, the U.S. Geological Survey (USGS) made a decision to deploy a temporary network of storm-tide sensors and barometric pressure sensors from Virginia to Maine to supplement the existing USGS and National Oceanic and Atmospheric Administration (NOAA) networks of permanent tide monitoring stations. After the storm made landfall, the USGS conducted a sensor data recovery and high-water-mark collection campaign in cooperation with the Federal Emergency Management Agency (FEMA). Peak storm-tide elevations documented at USGS tide gages, tidal crest-stage gages, temporary storm sensor locations, and high-water-mark sites indicate the area from southern Monmouth County, N.J., north through Raritan Bay, N.J., had the highest peak storm-tide elevations during this storm. The USGS tide gages at Raritan River at South Amboy and Raritan Bay at Keansburg, part of the New Jersey Tide Telemetry System, each recorded peak storm-tide elevations of greater than 13 feet (ft)—more than 5 ft higher than the previously recorded period-of-record maximum. A comparison of peak storm-tide elevations to preliminary FEMA Coastal Flood Insurance Study flood elevations indicated that these areas experienced the highest recurrence intervals along the coast of New Jersey. Analysis showed peak storm-tide elevations exceeded the 100-year FEMA flood elevations in many parts of Middlesex, Union, Essex, Hudson, and Bergen Counties, and peak storm-tide elevations at many locations in Monmouth County exceeded the 500-year recurrence interval. A level 1 HAZUS (HAZards United States) analysis was done for the counties in New Jersey affected by flooding to estimate total building stock losses. The aggregated total building stock losses estimated by HAZUS for New Jersey, on the basis of the final inundation verified by USGS high-water marks, was almost $19 billion. A comparison of Hurricane Sandy with historic coastal storms showed that peak storm-tide elevations associated with Hurricane Sandy exceeded most of the previously documented elevations associated with the storms of December 1992, March 1962, September 1960, and September 1944 at many coastal communities in New Jersey. This scientific investigation report was prepared in cooperation with FEMA to document flood processes and flood damages resulting from this storm and to assist in future flood mitigation actions in New Jersey.

New Jersey↗

USGS2021

Total phosphorus loadings for the Cedar River at Palo, Iowa, 2009–20

In support of nutrient reduction efforts, total phosphorus loads and yields were computed using turbidity-surrogate and LOAD ESTimator (LOADEST) models for the Cedar River at Palo, Iowa, for January 1, 2009, to December 15, 2020. Sample data were used to create a total phosphorus concentration turbidity-surrogate model. Total phosphorus loads also were computed from two streamflow-based LOADEST load models for the periods 2009–20 and 2016–20. The 2009–20 model was used for comparison with previously published loads at this site. The 2016–20 LOADEST model was used with the turbidity-surrogate model before sensor deployment and during periods of missing sensor data to obtain a more complete annual total phosphorus load. This report presents computed loads and methods needed to compute site-specific loads accurately and track annual progress toward nutrient reduction goals within the State. A comparison of loads from Weighted Regressions on Time, Discharge, and Season; LOADEST; and surrogate models indicated substantial differences at this site among these methods. Changes in both monitoring approaches (high-frequency sensor and surrogate data) and changes in load-calculation methods present potential challenges in assessing trends, such as assessment of load reduction. Annual total phosphorus loads for the Cedar River at Palo, Iowa, ranged from 1,370 to 2,360 U.S. short tons per year for 2018–20, based on the turbidity-surrogate model with gaps in sensor data filled with the 2016–20 LOADEST model. Annual total phosphorus yields for the Cedar River ranged from 0.67 to 1.16 pounds per acre per year for 2018–20. Although this load estimate is lower than previous estimates for the benchmark period of 2006–10, when normalized by streamflow, nearly all the apparent reduction can be attributed to differences in the load-calculation methods.

Palo↗

USGS2024

Special topic—Unoccupied aircraft systems

Introduction Unoccupied aircraft systems (UAS) increasingly support volcano monitoring and eruption response activities in the United States and abroad (James and others, 2020). Advances in UAS platforms and miniaturization of sensors over the past decade have expanded the use of this technology for a wide range of applications within volcanology (Jordan, 2019; James and others, 2020). UAS can greatly enhance existing ground-, aerial-, and satellite-based observation and in situ monitoring networks at volcanoes by providing new avenues for data collection in terms of access, resolution, and timing. UAS can collect data in difficult and hazardous environments, reducing risk to occupied aircraft and (or) ground crews; support the generation of dense time series of data through frequent, low-cost, high-resolution surveys; and provide real-time, on-demand measurements at volcanic systems for indicators such as gas, thermal output, and topographic change without the need to wait for contracted aerial flight services or satellite orbit intervals. During the 2018 response to the Kīlauea eruption on the Island of Hawaiʻi, UAS were used extensively and successfully to monitor, track, investigate, and (or) warn of ongoing volcanic activity (fig. L1; Neal and others, 2019). Throughout the eruption, the UAS team was able to provide data products rapidly to emergency managers for situational awareness and to scientists for quantitative hazard assessment (Diefenbach and others, 2018). Over the course of 4 months, more than 1,200 UAS missions were flown and yielded critical data that included (1) live video to emergency operations centers in Hilo and Honolulu for situational awareness; (2) gas emission rates, compositions, and concentrations; (3) repeat nadir videos over sections of the lava channel to support measurements of lava effusion rate; (4) oblique videos for hazards assessment and outreach; and (5) photogrammetry surveys to create very high-resolution topographic models and orthophoto mosaics (Diefenbach and others, 2018). In coming years, the U.S. Geological Survey (USGS) Volcano Hazards Program (VHP) plans to expand its fleet of UAS, associated sensors, and remote pilots to enhance volcano monitoring and response capabilities. Currently (2023), USGS operational capabilities are restricted to small class UAS (sUAS; less than [<] 55 pounds) that are limited in range, payload capacity, and flight duration. Additionally, USGS-piloted platforms are restricted to the U.S. Department of the Interior Office of Aviation Services approved fleet, which includes a limited number of small and medium multi-rotor aircraft and vertical take-off and landing fixed-wing aircraft ( https://www.doi.gov/aviation/uas/fleet ). Each type of platform has advantages and disadvantages. Small rotor-wing quadcopters are fast to deploy, can be carried in a backpack, and are highly maneuverable, but are typically only equipped with a small camera and have a minimal flight range. Medium rotor-wing hexacopters can carry larger payloads (< 20 kilograms [kg]) and varied sensors, but, with the drawback of minimal flight time (<30 minutes), they typically have similar range capabilities to their smaller counterparts and are not as easily deployable. Fixed-wing platforms provide relatively long endurance (<60 minutes) and range and, with the vertical take-off and landing capabilities, can launch and land in relatively small spaces; however, they have less maneuverability and hovering capability than the rotor-wing platforms. Although the 2018 Kīlauea response showed the benefit of the current UAS fleet, all platforms have limited range [<10 kilometers (km)], such that operators must be stationed relatively close to the region of interest. To expand UAS monitoring capabilities, VHP staff have been working closely with industry partners and the National Aeronautics and Space Administration to develop a next-generation UAS for volcano monitoring (Kern and others, 2020). This ruggedized, mid-range (>20 km), multiparametric (gas and photogrammetry) UAS has been developed to meet volcano monitoring needs, particularly at less accessible, more dangerous stratovolcanoes. It is expected in the coming years that additional UAS platforms with new and smaller sensors will expand our capabilities to meet the Nation’s volcano monitoring objectives.

Scientific Investigations Report↗

USGS2025

Assessing the potential for evaluation of wildland fire models using remotely sensed data—Summary proceedings from a U.S. Geological Survey workshop in 2024

On September 19, 2024, the U.S. Geological Survey (USGS) held a virtual workshop titled “Potential for Evaluation of Fire Models with Remote Sensing Data Workshop” to assess the feasibility of using remotely sensed datasets to evaluate next-generation wildland fire behavior models. Remote sensing and fire modelling experts gathered to: (1) assess the suitability of a variety of classified, commercial, and publicly available remotely sensed datasets for advancing fire model evaluation; (2) develop ideas on how to integrate remotely sensed data products with fire model inputs and outputs; and (3) identify any barriers and limitations to performing an evaluation of next-generation fire models. The USGS National Civil Applications Center, USGS Earth Resources Observation and Science Center, and USGS Fort Collins Ecosystem Science Center presented information on remote sensing datasets for three Arizona wildfire case studies. The development teams of the Fire Dynamics Simulator and QUIC-Fire fire behavior models presented their models and current evaluation methodologies. Interspersed with these presentations were discussions regarding how to expand current wildfire remote sensing data collection efforts beyond operational needs to assist in future fire modeling. Workshop participants agreed that several of the remote sensing datasets have potential for wildfire model evaluation. However, participants also identified several barriers and complications to performing a model evaluation including key gaps in wildfire datasets; uncertainties related to model fire-atmosphere reinitiation; lack of ground truthing and atmospheric correction of remotely sensed datasets; and differences in spatial, geolocation, radiometric, and temporal resolutions between the datasets and models. Further, the absence of standardized methodologies for image interpretation, poor understanding of sensor capabilities and limitations, and a lack of automation also hinder model evaluation efforts. Based on feedback from this workshop, USGS fire modelers are considering a project to address the uncertainties related to fire model reinitiation and encouraging fire practitioners to collaborate with remote sensing experts on wildland fires to improve data collection for a broader community of practice. Additionally, multiagency efforts are in development for a comprehensive cross-sensor validation and ground-truth campaign to test spatial, spectral, and geolocation sensor capabilities, determine limitations, and identify observational gaps for future sensor development and acquisition.

Arizona↗

USGS2019

Guidelines and standard procedures for high-frequency groundwater-quality monitoring stations—Design, operation, and record computation

High-frequency water-quality monitoring stations measure and transmit data, often in near real-time, from a wide range of aquatic environments to assess the quality of the Nation’s water resources. Common instrumentation for high-frequency water-quality data collection uses a multi-parameter sonde, which typically has sensors that measure and record water temperature, specific conductance, pH, and dissolved oxygen. Nitrate, turbidity, and fluorescent dissolved organic matter can also be monitored at high frequency. High-frequency groundwater-quality monitoring stations provide high-resolution time-series data to improve understanding of the timing of water-quality changes in the subsurface, especially for aquifer systems with short groundwater-residence times. High-frequency time-series data are used to monitor surface-water to groundwater interaction, quantify contaminant transport rates, and study water-quality variability in relation to variability of precipitation and groundwater pumping rates. High-frequency monitoring for contaminants or their surrogates have the added benefit of providing an early warning to protect valuable or sensitive aquifer resources. High-frequency time-series data also reveal short-term trends in groundwater quality, which may not be identifiable from monthly or annual sampling programs which facilitate the interpretation of decadal conditions. Systematic application of water-quality sonde operational procedures and a standard record-computation process are part of the required quality assurance for producing and documenting complete and accurate high-frequency groundwater-quality monitoring records. To collect quality high-frequency groundwater times-series data, water-quality sondes and sensors require careful field operation, cleaning, and calibration, as well as specific procedures for data computation, evaluation, review, and publication of final records. This report provides guidelines for the use of water-quality sondes and sensors for high-frequency groundwater-quality monitoring and updates the guidance pertaining to standardized records computation procedures for a wide range of groundwater environments. This report builds on previous continuous surface-water-quality monitoring guidance documentation for water temperature, specific conductance, pH, dissolved oxygen, and nitrate. The specific groundwater-quality monitoring guidelines presented in this report address station selection, design, installation, and operations; sonde and sensor inspections and cleaning and calibration methods; troubleshooting procedures; data evaluations, data corrections, and record computations; and record review, approval, and auditing procedures for the groundwater environment.

Techniques and Methods↗

USGS1995

Use of fathometers and electrical-conductivity probes to monitor riverbed scour at bridge piers

Two methods, a fathometer system and an electrical- conductivity probe system, were developed to monitor scour at bridge piers. The scour-monitoring systems consisted of a sensor (fathometer or electrical- conductivity probe), power supply, data logger, relay, and system program. The fathometer system was installed and tested at a bridge over the Leipsic River at Leipsic, Delaware, and at a bridge over Sinepuxent Bay near Ocean City. Maryland. Field data collected indicate that fathometers can be used to identify and monitor the riverbed elevation if post processing of the data and trends in the data are used to determine the riverbed location in relation to the transducer. The accuracy of the system is approximately the same as the resolution of the fathometer. Signal scatter can be a major source of error in the data. The electrical- conductivity probe system was installed and tested at a bridge over the Pamunkey River near Hanover, Virginia. The approximate elevation of the riverbed is determined by comparing conductivities of the surface-water flow with conductivities of submerged bed material from sensors located in each. Field data collected indicate that an electrical- conductivity probe, as tested, has limited usefulness in identifying and monitoring the riverbed elevation during high flows. As the discharge increases, the concentration of sediment in the surface-water flow increases, especially near the riverbed. Conductivities, measured at the sensors in the surface-water flow could not be distinguished from conductivities measured at the shallowest sensor in the submerged bed material.

Water-Resources Investigations Report↗

USGS1996

Comparison of Bowen-ratio, eddy-correlation, and weighing-lysimeter evapotranspiration for two sparse-canopy sites in eastern Washington

This report compares evapotranspiration estimated with the Bowen-ratio and eddy-correlation methods with evapotranspiration measured by weighing lysimeters for two sparse-canopy sites in eastern Washington. The sites are located in a grassland area (grass lysimeter site) and a sagbrush- covered area (sage lysimeter site) on the Arid Lands Ecology Reserve in Benton County, Washington. Lysimeter data were collected at the sites from August 1990 to November 1994. Bowen-ratio data were collected for varying periods from May 1993 to November 1994. Additional Bowen-ratio data without interchanging air- temperature and vapor-pressure sensors to remove sensor bias (fixed-sensor system) were collected from October 1993 to June 1994. Eddy-correlation data were collected at the grass lysimeter site from March to April 1994, and at the sage lysimeter site from April to May 1994. The comparisons of evapotranspiration determined by the various methods differed considerably, depending on the periods of record being compared and the sites being analyzed. The year 1993 was very wet, with about 50 percent more precipitation than average; 1994 was a very dry year, with only about half the average precipitation. The study showed that on an annual basis, at least in 1994, Bowen-ratio evapotranspiration closely matched lysimeter evapotranspiration. In 1993, Bowen-ratio and lysimeter evapotranspiration comparisons were variable. Evapotranspiration estimated with the Bowen-ratio method averaged 5 percent more than evapotranspiration measured by lysimeters at the grass lysimeter site from October 1993 to November 1994, and 3 percent less than lysimeters at the sage lysimeter site from November 1993 to October 1994. From March 24 to April 5, 1994, at the grass lysimeter site, the Bowen-ratio method estimated 11 percent less, the Bowen-ratio method utilizing the fixed sensor system about 7 percent more, and the eddy-correlation method about 28 percent less evapotranspiration than the lysimeters measured. From May 7 to June 18, 1993, however, the Bowen-ratio method estimated only 54 percent of the evapotranspiration measured by lysimeters at the grass lysimeter site. This large difference possibly may be attributed to Bowen-ratio instrument variability or error, to the density of grasses in the lysimeters being greater than in the surrounding area, or to heating effects on the lysimeters. From September 1 to October 31, 1993, the Bowen-ratio method estimated more than 450 percent more evapotranspiration than was measured by lysimeters at the sage lysimeter site. This difference may have been due to conditions in the lysimeters at the sage lysimeter site that were unrepresentative of natural conditions. The Bowen-ratio instruments measured evapotrans- piration over sagebrush plants outside the lysimeters, which were blooming very heavily, possibly using supplemental ground water or spring water from nearby upslope areas. The sagebrush plants contained by the lysimeters showed very little evapotranspiration, possibly because they were root-bound and had already used all available water. Also, plants in the lysimeters would not have been able to access any supplemental water available to plants outside the confines of the lysimeters. Earlier in 1993, from June 17 to July 12, the Bowen-ratio method estimated only 1 percent less evapotranspiration than determined for the lysimeters at the sage lysimeter site. On the basis of lysimeter measurements from August 1990 to November 1994, cumulative evapotrans- piration ranged from about 97 to 103 percent of the annual precipitation each year. The evapotranspiration measurements made at the grass and sage lysimeter sites, which were based on weight changes in the lysimeters, showed that storage changes became nearly zero each year some time between August and November as average surface soil moisture decreased to about 2 percent and evapotranspiration rates decreased to less than 0.1 millimeter per day.

Water-Resources Investigations Report↗

USGS2021

Estimating actual evapotranspiration over croplands using vegetation index methods and dynamic harvested area

Advances in estimating actual evapotranspiration (ETa) with remote sensing (RS) have contributed to improving hydrological, agricultural, and climatological studies. In this study, we evaluated the applicability of Vegetation-Index (VI) -based ETa (ET-VI) for mapping and monitoring drought in arid agricultural systems in a region where a lack of ground data hampers ETa work. To map ETa (2000–2019), ET-VIs were translated and localized using Landsat-derived 3- and 2-band Enhanced Vegetation Indices (EVI and EVI2) over croplands in the Zayandehrud River Basin (ZRB) in Iran. Since EVI and EVI2 were optimized for the MODerate Imaging Spectroradiometer (MODIS), using these VIs with Landsat sensors required a cross-sensor transformation to allow for their use in the ET-VI algorithm. The before- and after- impact of applying these empirical translation methods on the ETa estimations was examined. We also compared the effect of cropping patterns’ interannual change on the annual ETa rate using the maximum Normalized Difference Vegetation Index (NDVI) time series. The performance of the different ET-VIs products was then evaluated. Our results show that ETa estimates agreed well with each other and are all suitable to monitor ETa in the ZRB. Compared to ETc values, ETa estimations from MODIS-based continuity corrected Landsat-EVI (EVI2) (EVI MccL and EVI2 MccL ) performed slightly better across croplands than those of Landsat-EVI (EVI2) without transformation. The analysis of harvested areas and ET-VIs anomalies revealed a decline in the extent of cultivated areas and a loss of corresponding water resources downstream. The findings show the importance of continuity correction across sensors when using empirical algorithms designed and optimized for specific sensors. Our comprehensive ETa estimation of agricultural water use at 30 m spatial resolution provides an inexpensive monitoring tool for cropping areas and their water consumption.

Remote Sensing↗

USGS2022

Landsat 9 geometric characteristics using underfly data

The Landsat program has a long history of providing remotely sensed data to the user community. This history is being extended with the addition of the Landsat 9 satellite, which closely mimics the Landsat 8 satellite and its instruments. These satellites contain two instruments, the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). OLI is a push-broom sensor that collects visible and near-infrared (VNIR) and short-wave infrared (SWIR) wavelengths at 30 m ground sample distance, along with a panchromatic 15 m band. The TIRS sensor contains two long-wave thermal spectral channels centered at 10.9 and 12 µm. The data from these two instruments, on both satellites, are combined into a single Landsat product. The Landsat 5–9 satellites follow a 16 day repeat cycle designated as the Worldwide Reference System (WRS-2), which provides a global notional gridded mapping for identifying individual Landsat scenes. The Landsat 8 and 9 satellites are flown such that their orbital tracks are separated by 8 days in this 16 day cycle. During the commissioning period of Landsat 9, and during its ascent to its operational WRS-2 orbit, the Landsat 9 satellite’s orbital track went under and crossed over the orbital track of the Landsat 8 satellite. This produced a unique situation where nearly time-coincident imagery could be obtained from the instruments of the two spacecrafts. From a radiometric standpoint, this allowed for near-time cross-calibration between the instruments to be performed. From a geometry perspective, calibration is achieved through high-resolution reference imagery over specific ground locations, thus ensuring calibration of the instruments and for the instruments to be well cross-calibrated geometrically. Although these underfly data do not provide calibration of the instruments between the platforms from a geometric perspective, they allow for the verification of the calibration steps involving the instruments and spacecraft. This paper discusses the co-registration of this unique set of data while also discussing other geometric aspects of these data by looking at and comparing the differences in sensor viewing and sun angles associated with the collections from the two platforms for imagery obtained over common geographic locations. The image-to-image comparisons between Landsat 8 and 9 coincident pairs, where both datasets are precision terrain products, are registered to within 2.2 m with respect to their root-mean-squared radial error (RMSEr). The 2.2 m represents less than 0.1 of a 30 m multispectral pixel in misregistration between the L9 and L8 underfly products that will be available to the user community. This unique dataset will provide well-registered, near-coincident image acquisitions between the two platforms that can be a key to any calibration or application comparisons. The paper also presents that, for images for which one of the image pairs failed precision corrections and became a terrain-corrected only product type, a range of 8–14 m RMSEr could be expected in co-registration, while, in cases where both image pairs failed the precision correction step and both images became a terrain-corrected only product type, a 14 m RMSEr could be expected for co-registration.

Remote Sensing↗