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At least 343 records · Page 19Linked to original sources
USGS2023

Operational aspects of Landsat 8 and 9 geometry

Landsat 9 (L9) was launched on 27 September 2021. This spacecraft contained two instruments, the Operational Land Imager-2 (OLI-2) and Thermal Infrared Sensor-2 (TIRS-2), that allow for a continuation of the Landsat program and the mission to acquire multi-spectral observations of the globe on a moderate scale. Following a period of commissioning, during which time the spacecraft and instruments were initialized and set up for operations, with the initial calibration performed, the mission moved to an operational mode This operational mode involved the same cadence and methods that were performed for the Landsat 8 (L8) spacecraft and the two instruments onboard, the Operational Land Imager-1 (OLI-1) and Thermal Infrared Sensor-1 (TIRS-1), with respect to calibration, characterization, and validation. This paper discusses the geometric operational aspects of the L9 instruments during the first year of the mission and post-commissioning, and compares these same geometric activities performed for L8 during the same time frame. During this time, optical axes of the two sensors, OLI-1 and OLI-2, were adjusted to stay aligned with the spacecraft’s Attitude Control System (ACS), and the TIRS-1 and TIRS-2 instruments were adjusted to stay aligned with the OLI-1 and OLI-2 instruments, respectively. In this paper, the L9 operational adjustments are compared to the same operational aspects of L8 during this same time frame. The comparisons shown in this paper will demonstrate that both instruments aboard L8 and L9 performed very similar geometric qualities while fully meeting the expected requirements. This paper describes the geometric differences between the L9 imagery that was made available to the public prior to the reprocessing campaign that was performed using the new calibration updates to the sensor and to ACS and TIRS-to-OLI alignment parameters. This reprocessing campaign of L9 products involved data acquired from the launch of the spacecraft up to early 2023.

Remote Sensing↗
USGS2026

A comparison of non-contact methods for measuring turbidity in the Colorado River

Monitoring suspended-sediment concentration (SSC) is essential to better understand how sediment transport could adversely affect water availability for human communities and ecosystems. Aquatic remote sensing methods are increasingly utilized to estimate SSC and turbidity in rivers; however, an evaluation of their quantitative performance is limited. This study evaluates the performance of three multispectral sensors, which vary in resolution and ease of deployment, to estimate turbidity in the Colorado River: the Multispectral Instrument (MSI) on board the European Space Agency’s Sentinel-2 satellite, an industrial-grade 10-band dual camera system mounted on a cable car, and a consumer-grade 6-band dual camera system positioned on the riverbank. We use multivariate linear regression to compare in situ turbidity measurements with concurrent spectral reflectance data from each sensor. Models for all three sensors selected similar spectral information and resulted in mean errors <35% in predicting turbidity. A cross-sensor comparison showed that little accuracy is lost when applying models developed for satellite-based systems to ground-based systems, and vice versa. Transferability of satellite-based models to ground-based systems could support continuous water-quality monitoring between satellite overpasses and avoid issues associated with cloud interference. Conversely, continuously operating ground-based systems could be used to rapidly establish datasets and models for application in satellite imagery, thus accelerating remote sensing applications. The encouraging performance of the consumer-grade system indicates that SSC could be monitored for low cost.

Colorado↗
USGS2005

Volcano surveillance by ACR silver fox

Recent growth in the business of unmanned air vehicles (UAVs) both in the US and abroad has improved their overall capability, resulting in a reduction in cost, greater reliability and adoption into areas where they had previously not been considered. Uses in coastal and border patrol, forestry and agriculture have recently been evaluated in an effort to expand the observed area and reduce surveillance and reconnaissance costs for information gathering. The scientific community has both contributed and benefited greatly in this development. A larger suite of light-weight miniaturized sensors now exists for a range of applications which in turn has led to an increase in the gathering of information from these autonomous vehicles. In October 2004 the first eruption of Mount St Helens since 1986 caused tremendous interest amoUg people worldwide. Volcanologists at the U.S. Geological Survey rapidly ramped up the level of monitoring using a variety of ground-based sensors deployed in the crater and on the flanks of the volcano using manned helicopters. In order to develop additional unmanned sensing methods that can be used in potentially hazardous and low visibility conditions, a UAV experiment was conducted during the ongoing eruption early in November. The Silver Fox UAV was flown over and inside the crater to perform routine observation and data gathering, thereby demonstrating a technology that could reduce physical risk to scientists and other field operatives. It was demonstrated that UAVs can be flown autonomously at an active volcano and can deliver real time data to a remote location. Although still relatively limited in extent, these initial flights provided information on volcanic activity and thermal conditions within the crater and at the new (2004) lava dome. The flights demonstrated that readily available visual and infrared video sensors mounted in a small and relatively low-cost aerial platform can provide useful data on volcanic phenomena. This was made possible by utilizing GPS and computer-controlled flight direction and stabilization to acquire and track target areas within the Mount St. Helens crater. It was also determined that additional light-weight sensor development will be needed to enable autonomous measurements of volcanic gasses and imaging in poor-weather conditions. Copyright ?? 2005 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

Conference Paper↗
USGS2010

Comparison of turbidity to multi-frequency sideways-looking acoustic-Doppler data and suspended-sediment data in the Colorado River in Grand Canyon

Water clarity is important to biologists when studying fish and other fluvial fauna and flora. Turbidity is an indicator of the cloudiness of water, or reduced water clarity, and is commonly measured using nephelometric sensors that record the scattering and absorption of light by particles in the water. Unfortunately, nephelometric sensors only operate over a narrow range of the conditions typically encountered in rivers dominated by suspended-sediment transport. For example, sediment inputs into the Colorado River in Grand Canyon caused by tributary floods often result in turbidity levels that exceed the maximum recording level of nephelometric turbidity sensors. The limited range of these sensors is one reason why acoustic Doppler profiler instrument data, not turbidity, has been used as a surrogate for suspended sediment concentration and load of the Colorado River in Grand Canyon. However, in addition to being an important water-quality parameter to biologists, turbidity of the Colorado River in Grand Canyon has been used to strengthen the suspended-sediment record through the process of turbidity-threshold sampling; high turbidity values trigger a pump sampler to collect samples of the river at critical times for gathering suspended-sediment data. Turbidity depends on several characteristics of suspended sediment including concentration, particle size, particle shape, color, and the refractive index of particles. In this paper, turbidity is compared with other parameters coupled to suspended sediment, namely suspended-silt and clay concentration and multifrequency acoustic attenuation. These data have been collected since 2005 at four stations with different sediment-supply characteristics on the Colorado River in Grand Canyon. These comparisons reveal that acoustic attenuation is a particularly useful parameter, because it is strongly related to turbidity and it can be measured by instruments that experience minimal fouling and record over the entire range of turbidity encountered in the Colorado River in Grand Canyon. Relating turbidity to acoustic attenuation and suspended-silt and clay concentration provides an additional benefit in that data outliers are revealed that likely identify inflow events from anomalous sources with unusual sediment characteristics.

Arizona↗
USGS2022

River Metabolism Estimation Tools (RiverMET) with demo in the Illinois River Basin

Ecosystem metabolism quantifies the rate of production, maintenance, and decay of organic matter in terrestrial and aquatic systems. It is a fundamental measure of energy flow associated with biomass production by photosynthesizing organisms and biomass oxidation by respiring plants, animals, algae, and bacteria (Bernhardt et al., 2022) . Ecosystem metabolism also provides an understanding of energy flow to higher trophic levels that supports secondary and tertiary productivity, as well as helping to explain when aquatic ecosystems undergo out-of-balance behaviors such as harmful algal blooms and hypoxia. Recent advances in sensor technology and modeling capabilities have enabled estimation of aquatic system metabolism and gas exchange over long time periods in rivers, streams, ponds, and wetlands where oxygen sensors have been deployed. Here we present RiverMET, a framework for estimation of river metabolism, with workflows to streamline data preparation, run a stream metabolism model, assess the model performance, and flag and censor final output data. The workflows are specifically tailored to use streamMetabolizer, a model for one-station calculations of stream metabolism that calculates gross primary productivity (GPP), ecosystem respiration (ER) and the air-water gas exchange rate constant (K600). We advise potential users of RiverMET to review core publications for the streamMetabolizer model (Appling et al., 2018 a, b, c) to ensure best practices that produce the most useful results. We encourage feedback about our workflows, although issues regarding the streamMetabolizer model itself should be referred to the model authors. We tested RiverMET by calculating GPP, ER, and K600 across 17 river sites in the Illinois River basin (ILRB). Each river had between one and nine years of sensor data appropriate for modeling metabolism. In total, metabolism was modeled on 15,176 days between 2005 and 2020. Overall confidence in the results was rated as high at nine river sites, medium at six river sites, and poor at two river sites. Twenty-nine percent of the total modeled days had performance metrics that triggered flags. Metrics used for daily flagging are provided with the final output, with an option to only retain the censored daily outputs with high confidence (representing 72 %, i.e., 10,938 days, of the total days modeled). This work was completed as part of the U.S. Geological Survey Proxies Project, an effort supported by the Water Mission Area (WMA) Water Quality Processes program to develop estimation methods for harmful algal blooms (HABs), per- and polyfluoroalkyl substances (PFAS), and metals, at multiple spatial and temporal scales.

Illinois River Basin↗
USGS2024

Dynamic water-quality responses to wildfire in Colorado

In 2020, Colorado experienced the most severe wildfire season in recorded history, with wildfires burning 625 357 acres across the state. Two of the largest fires burned parts of Rocky Mountain National Park (RMNP), and a study was initiated to address concerns about potential effects on drinking water quality from mobilization of ash and sediment. The study took advantage of a wealth of pre-fire data from adjacent burned and unburned basins in western RMNP. Pre- and post-fire data collection included discrete sample collection and high-frequency water-quality measurements using in-stream sensors. Kruskal–Wallis tests on discrete data indicated that specific conductance, base cations, sulphate, chloride, nitrate, and total dissolved nitrogen concentrations increased post-fire, whereas silica and dissolved organic carbon (DOC) did not ( p ≤ 0.05). In-stream sensors captured large spikes in concentrations of nutrients, turbidity, and DOC in the burned basin that were missed by discrete sampling. Sensor data indicated nitrate and turbidity increased by up to one and two orders of magnitude, respectively, from pre-event concentrations during storms, and DOC increased up to 3.5×. Empirical regression equations were developed using pre-fire data and applied to the post-fire period to estimate expected stream chemistry in the absence of fire (a ‘no-fire’ scenario). Overlays of actual post-fire chemistry showed the timing and magnitude of differences between observed and ‘estimated’ chemistry. For most solutes, observed post-fire concentrations were notably greater than expected under the ‘no-fire’ scenario, and differences were greatest during storm events. Comparison of data from the burned and unburned basins indicated DOC concentrations were affected by climate as well as fire. Results from this study demonstrate the importance of both pre-fire data and high-frequency data for characterizing dynamic hydrochemical responses in wildfire-affected areas.

Colorado↗
USGS2021

Field evaluation of a compact, polarizing topo‐bathymetric lidar across a range of river conditions

This paper summarizes field trials to evaluate the performance of a prototype compact topo‐bathymetric lidar sensor for surveying rivers. The sensor uses a novel polarization technique to distinguish between laser returns from the water surface and streambed and its size and weight permit deployment from a small unmanned aerial system (sUAS) or a boat. Field testing was designed to identify the range of operational conditions under which the sensor can provide accurate information on river depths. For accuracy assessment, conventional, field‐based depth measurements were collected by wading and sonar. Additionally, optical properties of the rivers were measured in situ. Wading and lidar bathymetry comparisons in relatively shallow channels yielded observed versus predicted (OP) regression R 2 values ranging from 0.60 to 0.97. A comparison between sonar and lidar bathymetry in a deeper river resulted in an OP R 2 of 0.72. Absorption and attenuation coefficients at the 532 nm wavelength of the lidar were recorded in the field and the highest values of these inherent optical properties were at sites with the highest turbidity and highest concentrations of colored dissolved organic matter, chlorophyll, and suspended sediment. At these sites, which included both sand and gravel/cobble beds, the point density of riverbed returns was not uniform, with areas of sparse coverage occurring primarily in deeper water. However, submerged objects and slopes could be resolved in the lidar point clouds.

Arizona, Colorado↗
USGS1992

A spatial length scale analysis of turbulent temperature and velocity fluctuations within and above an orchard canopy

Turbulent flow within and above an almond orchard was measured with three-dimensional wind sensors and fine-wire thermocouple sensors arranged in a horizontal array. The data showed organized turbulent structures as indicated by coherent asymmetric ramp patterns in the time series traces across the sensor array. Space-time correlation analysis indicated that velocity and temperature fluctuations were significantly correlated over a transverse distance more than 4m. Integral length scales of velocity and temperature fluctuations were substantially greater in unstable conditions than those in stable conditions. The coherence spectral analysis indicated that Davenport's geometric similarity hypothesis was satisfied in the lower frequency region. From the geometric similarity hypothesis, the spatial extents of large ramp structures were also estimated with the coherence functions.

Boundary-Layer Meteorology↗
USGS2019

Influence of land use and hydrologic variability on seasonal dissolved organic carbon and nitrate export: Insights from a multi-year regional analysis for the northeastern USA

Land use/land cover (LULC) change has significant impacts on nutrient loading to aquatic systems and has been linked to deteriorating water quality globally. While many relationships between LULC and nutrient loading have been identified, characterization of the interaction between LULC, climate (specifically variable hydrologic forcing) and solute export across seasonal and interannual time scales is needed to understand the processes that determine nutrient loading and responses to change. Recent advances in high-frequency water quality sensors provide opportunities to assess these interannual relationships with sufficiently high temporal resolution to capture the unpredictable, short-term storm events that likely drive important export mechanisms for dissolved organic carbon (DOC) and nitrate (NO 3 − –N). We deployed a network of in situ sensors in forested, agricultural, and urban watersheds across the northeastern United States. Using 2 years of high-frequency sensor data, we provide a regional assessment of how LULC and hydrologic variability affected the timing and magnitude of dissolved organic carbon and nitrate export, and the status of watershed fluxes as either supply or transport controlled. Analysis of annual export dynamics revealed systematic differences in the timing and magnitude of DOC and NO 3 − –N delivery among different LULC classes, with distinct regional similarities in the timing of DOC and NO 3 − –N fluxes from forested and urban watersheds. Conversely, export dynamics at agricultural sites appeared to be highly site-specific, likely driven by local agricultural practices and regulations. Furthermore, the magnitude of solute fluxes across watersheds responded strongly to interannual variability in rainfall, suggesting a high degree of hydrologic control over nutrient loading across the region. Thus, there is strong potential for climate-driven changes in regional hydrologic cycles to drive variation in the magnitude of downstream nutrient fluxes, particularly in watersheds where solute supply and/or transport has been modified.

Delaware, Rhode Island, Vermont↗
USGS2018

A novel high-frequency groundwater quality monitoring system

High-frequency, long-term monitoring of water quality has revolutionized the study of surface waters in recent years. However, application of these techniques to groundwater has been limited by the ability to remotely pump and analyze groundwater. This paper describes a novel autonomous groundwater quality monitoring system which samples multiple wells to evaluate temporal changes and identify trends in groundwater chemistry. The system, deployed near Fresno, California, USA, collects and transmits high-frequency data, including water temperature, specific conductance, pH, dissolved oxygen, and nitrate, from supply and monitoring wells, in real-time. The system consists of a water quality sonde and optical nitrate sensor, manifold, submersible three-phase pump, variable frequency drive, data collection platform, solar panels, and rechargeable battery bank. The manifold directs water from three wells to a single set of sensors, thereby reducing setup and operation costs associated with multi-sensor networks. Sampling multiple wells at high frequency for several years provided a means of monitoring the vertical distribution and transport of solutes in the aquifer. Initial results show short period variability of nitrate, specific conductivity, and dissolved oxygen in the shallow aquifer, while the deeper portion of the aquifer remains unchanged—observations that may be missed with traditional discrete sampling approaches. In this aquifer system, nitrate and specific conductance are increasing in the shallow aquifer, while invariant changes in deep groundwater chemistry likely reflect relatively slow groundwater flow. In contrast, systems with high groundwater velocity, such as karst aquifers, have been shown to exhibit higher-frequency groundwater chemistry changes. The stability of the deeper aquifer over the monitoring period was leveraged to develop estimates of measurement system uncertainty, which were typically lower than the manufacturer’s stated specifications, enabling the identification of subtle variability in water chemistry that may have otherwise been missed.

California↗
USGS1986

An instrument system for monitoring and sampling suspended sediment in the benthic boundary layer

An instrument system has been constructed that can monitor and sample suspended sediment distributions in the benthic boundary layer. It consists of miniature nephelometers and suspended sediment samplers placed within one meter of the seabed. The system is capable of continuously monitoring suspended sediment profiles at eight levels between 14 and 100 cm above the seabed and collecting suspended sediment samples at four levels (20, 50, 70 and 100 cm) at three times during a deployment period. The suspended sediment system is designed to fit onto the instrumented tripod GEOPROBE which contains four electromagnetic current meters, pressure sensor, bottom stereo camera, two temperature sensors, transmissometer, and a Savonius rotor current meter. Sensor operation, data recording, and sediment sampling events are synchronized. Thus detailed measurements of the near-bottom flow conditions are made concurrently with suspended sediment measurements. The combined system has been used in sediment transporting environments within San Francisco Bay, California, and Puget Sound, Washington.

Marine Geology↗
USGS2020

Making ‘chemical cocktails’ – Evolution of urban geochemical processes across the periodic table of elements

Urbanization contributes to the formation of novel elemental combinations and signatures in terrestrial and aquatic watersheds, also known as ‘chemical cocktails.’ The composition of chemical cocktails evolves across space and time due to: (1) elevated concentrations from anthropogenic sources, (2) accelerated weathering and corrosion of the built environment, (3) increased drainage density and intensification of urban water conveyance systems, and (4) enhanced rates of geochemical transformations due to changes in temperature, ionic strength, pH, and redox potentials. Characterizing chemical cocktails and underlying geochemical processes is necessary for: (1) tracking pollution sources using complex chemical mixtures instead of individual elements or compounds; (2) developing new strategies for co-managing groups of contaminants; (3) identifying proxies for predicting transport of chemical mixtures using continuous sensor data; and (4) determining whether interactive effects of chemical cocktails produce ecosystem-scale impacts greater than the sum of individual chemical stressors. First, we discuss some unique urban geochemical processes which form chemical cocktails, such as urban soil formation, human-accelerated weathering, urban acidification-alkalinization, and Freshwater Salinization Syndrome. Second, we review and synthesize global patterns in concentrations of major ions, carbon and nutrients, and trace elements in urban streams across different world regions and make comparisons with reference conditions. In addition to our global analysis, we highlight examples from watersheds in the Baltimore-Washington DC area, USA, which show increased transport of major ions, trace metals, and nutrients across streams draining a well-defined land-use gradient. Urbanization increased the concentrations of multiple major and trace elements in streams draining human-dominated watersheds compared to reference conditions. Chemical cocktails of major and trace elements were formed over diurnal cycles coinciding with changes in streamflow, dissolved oxygen, pH, and other variables measured by high-frequency sensors. Some chemical cocktails of major and trace elements were also significantly related to specific conductance (p < 0.05), which can be measured by sensors. Concentrations of major and trace elements increased, peaked, or decreased longitudinally along streams as watershed urbanization increased, which is consistent with distinct shifts in chemical mixtures upstream and downstream of other major cities in the world. Our global analysis of urban streams shows that concentrations of multiple elements along the periodic table significantly increase when compared with reference conditions. Furthermore, similar biogeochemical patterns and processes can be grouped among distinct mixtures of elements of major ions, dissolved organic matter, nutrients, and trace elements as chemical cocktails. Chemical cocktails form in urban waters over diurnal cycles, decades, and throughout drainage basins. We conclude our global review and synthesis by proposing strategies for monitoring and managing chemical cocktails using source control, ecosystem restoration, and green infrastructure. We discuss future research directions applying the watershed chemical cocktail approach to diagnose and manage environmental problems. Ultimately, a chemical cocktail approach targeting sources, transport, and transformations of different and distinct elemental combinations is beneficial to more holistically monitor and manage the emerging impacts of chemical mixtures in the world's fresh waters.

Applied Geochemistry↗
USGS2019

Debris-flow monitoring and warning: Review and examples

Debris flows represent one of the most dangerous types of mass movements, because of their high velocities, large impact forces and long runout distances. This review describes the available debris-flow monitoring techniques and proposes recommendations to inform the design of future monitoring and warning/alarm systems. The selection and application of these techniques is highly dependent on site and hazard characterization, which is illustrated through detailed descriptions of nine monitoring sites: five in Europe, three in Asia and one in the USA. Most of these monitored catchments cover less than ∼10 km 2 and are topographically rugged with Melton Indices greater than 0.5. Hourly rainfall intensities between 5 and 15 mm/h are sufficient to trigger debris flows at many of the sites, and observed debris-flow volumes range from a few hundred up to almost one million cubic meters. The sensors found in these monitoring systems can be separated into two classes: a class measuring the initiation mechanisms, and another class measuring the flow dynamics. The first class principally includes rain gauges, but also contains of soil moisture and pore-water pressure sensors. The second class involves a large variety of sensors focusing on flow stage or ground vibrations and commonly includes video cameras to validate and aid in the data interpretation. Given the sporadic nature of debris flows, an essential characteristic of the monitoring systems is the differentiation between a continuous mode that samples at low frequency (“non-event mode”) and another mode that records the measurements at high frequency (“event mode”). The event detection algorithm, used to switch into the “event mode” depends on a threshold that is typically based on rainfall or ground vibration. Identifying the correct definition of these thresholds is a fundamental task not only for monitoring purposes, but also for the implementation of warning and alarm systems.

Earth-Science Reviews↗
USGS2006

The Short Wave Aerostat-Mounted Imager (SWAMI): A novel platform for acquiring remotely sensed data from a tethered balloon

We describe a new remote sensing system called the Short Wave Aerostat-Mounted Imager (SWAMI). The SWAMI is designed to acquire co-located video imagery and hyperspectral data to study basic remote sensing questions and to link landscape level trace gas fluxes with spatially and temporally appropriate spectral observations. The SWAMI can fly at altitudes up to 2 km above ground level to bridge the spatial gap between radiometric measurements collected near the surface and those acquired by other aircraft or satellites. The SWAMI platform consists of a dual channel hyperspectral spectroradiometer, video camera, GPS, thermal infrared sensor, and several meteorological and control sensors. All SWAMI functions (e.g. data acquisition and sensor pointing) can be controlled from the ground via wireless transmission. Sample data from the sampling platform are presented, along with several potential scientific applications of SWAMI data.

Remote Sensing of Environment↗
USGS2015

Prospective HyspIRI global observations of tidal wetlands

Tidal wetlands are highly productive and act as critical habitat for a wide variety of plants, fish, shellfish, and other wildlife. These ecotones between aquatic and terrestrial environments also provide protection from storm damage, run-off filtering, and recharge of aquifers. Many wetlands along coasts have been exposed to stress-inducing alterations globally, including dredge and fill operations, hydrologic modifications, pollutants, impoundments, fragmentation by roads/ditches, and sea level rise. For wetland protection and sensible coastal development, there is a need to monitor these ecosystems at global and regional scales. Recent advances in satellite sensor design and data analysis are providing practical methods for monitoring natural and man-made changes in wetlands. However, available satellite remote sensors have been limited to mapping primarily wetland location and extent. This paper describes how the HyspIRI hyperspectral and thermal infrared sensors can be used to study and map key ecological properties, such as species composition, biomass, hydrology, and evapotranspiration of tidal salt and brackish marshes and mangroves, and perhaps other major wetland types, including freshwater marshes and wooded/shrub wetlands.

Remote Sensing of Environment↗
USGS2016

Assessing the role of climate and resource management on groundwater dependent ecosystem changes in arid environments with the Landsat archive

Groundwater dependent ecosystems (GDEs) rely on near-surface groundwater. These systems are receiving more attention with rising air temperature, prolonged drought, and where groundwater pumping captures natural groundwater discharge for anthropogenic use. Phreatophyte shrublands, meadows, and riparian areas are GDEs that provide critical habitat for many sensitive species, especially in arid and semi-arid environments. While GDEs are vital for ecosystem services and function, their long-term (i.e. ~ 30 years) spatial and temporal variability is poorly understood with respect to local and regional scale climate, groundwater, and rangeland management. In this work, we compute time series of NDVI derived from sensors of the Landsat TM, ETM +, and OLI lineage for assessing GDEs in a variety of land and water management contexts. Changes in vegetation vigor based on climate, groundwater availability, and land management in arid landscapes are detectable with Landsat. However, the effective quantification of these ecosystem changes can be undermined if changes in spectral bandwidths between different Landsat sensors introduce biases in derived vegetation indices, and if climate, and land and water management histories are not well understood. The objective of this work is to 1) use the Landsat 8 under-fly dataset to quantify differences in spectral reflectance and NDVI between Landsat 7 ETM + and Landsat 8 OLI for a range of vegetation communities in arid and semiarid regions of the southwestern United States, and 2) demonstrate the value of 30-year historical vegetation index and climate datasets for assessing GDEs. Specific study areas were chosen to represent a range of GDEs and environmental conditions important for three scenarios: baseline monitoring of vegetation and climate, riparian restoration, and groundwater level changes. Google's Earth Engine cloud computing and environmental monitoring platform is used to rapidly access and analyze the Landsat archive along with downscaled North American Land Data Assimilation System gridded meteorological data, which are used for both atmospheric correction and correlation analysis. Results from the cross-sensor comparison indicate a benefit from the application of a consistent atmospheric correction method, and that NDVI derived from Landsat 7 and 8 are very similar within the study area. Results from continuous Landsat time series analysis clearly illustrate that there are strong correlations between changes in vegetation vigor, precipitation, evaporative demand, depth to groundwater, and riparian restoration. Trends in summer NDVI associated with riparian restoration and groundwater level changes were found to be statistically significant, and interannual summer NDVI was found to be moderately correlated to interannual water-year precipitation for baseline study sites. Results clearly highlight the complementary relationship between water-year PPT, NDVI, and evaporative demand, and are consistent with regional vegetation index and complementary relationship studies. This work is supporting land and water managers for evaluation of GDEs with respect to climate, groundwater, and resource management.

Remote Sensing of Environment↗
USGS2016

A note on the temporary misregistration of Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) imagery

The Landsat-8 and Sentinel-2 sensors provide multi-spectral image data with similar spectral and spatial characteristics that together provide improved temporal coverage globally. Both systems are designed to register Level 1 products to a reference image framework, however, the Landsat-8 framework, based upon the Global Land Survey images, contains residual geolocation errors leading to an expected sensor-to-sensor misregistration of 38 m (2σ). These misalignments vary geographically but should be stable for a given area. The Landsat framework will be readjusted for consistency with the Sentinel-2 Global Reference Image, with completion expected in 2018. In the interim, users can measure Landsat-to-Sentinel tie points to quantify the misalignment in their area of interest and if appropriate to reproject the data to better alignment.

Remote Sensing of Environment↗
USGS2023

Quantification of wetland vegetation communities features with airborne AVIRIS-NG, UAVSAR, and UAV LiDAR data in Peace-Athabasca Delta

Arctic-boreal wetlands, important ecosystems for biodiversity and ecological services, are experiencing hydrological changes including permafrost thaw, earlier snowmelt, and increased wildfire susceptibility. These changes are affecting wetland productivity, species diversity, and biogeochemical cycles. However, given the diverse forms and structures of wetland vegetation communities, traditional wetland maps generated from lower spatial and spectral resolution satellite imagery lack community-level vegetation classification and miss spatially complex patterns. In this study, we built a cloud-based workflow to map wetland vegetation community of the Peace-Athabasca Delta (PAD), Canada, by leveraging high-resolution (5-m) airborne multi-sensor datasets, namely NASA's Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) and Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR), and a historical LiDAR archive. Validation of our classifications using ground references indicates that classifications derived from AVIRIS-NG have higher accuracies (≥87.9%) than either UAVSAR (65.6%) or LiDAR (75.9%) for mapping wetland vegetation communities. We also show improved classification accuracy when combining information from multiple sensors. In particular, incorporating AVIRIS-NG and UAVSAR datasets substantially reduced omission errors of wet graminoid and wet shrub classes from 29.6% to 20.5% and from 10.8% to 7.5%, respectively. Combining AVIRIS-NG and LiDAR datasets further improves overall accuracy (+2.2%) for most classifications, especially emergent vegetation, wet graminoid, and wet shrub. The best performing model, using features derived from all three sensors, achieved an overall accuracy of 93.5%. The framework established here can be used to leverage extensive airborne AVIRIS-NG and UAVSAR datasets collected across Alaska and northwest Canada to understand the spatial distribution of Arctic-Boreal wetland vegetation communities.

Remote Sensing of Environment↗