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At least 703 records · Page 39Linked to original sources
USGS2016

Perspectives on monitoring gradual change across the continuity of Landsat sensors using time-series data

There are many types of changes occurring over the Earth's landscapes that can be detected and monitored using Landsat data. Here we focus on monitoring “within-state,” gradual changes in vegetation in contrast with traditional monitoring of “abrupt” land-cover conversions. Gradual changes result from a variety of processes, such as vegetation growth and succession, damage from insects and disease, responses to shifts in climate, and other factors. Despite the prevalence of gradual changes across the landscape, they are largely ignored by the remote sensing community. Gradual changes are best characterized and monitored using time-series analysis, and with the successful launch of Landsat 8 we now have appreciable data continuity that extends the Landsat legacy across the previous 43 years. In this study, we conducted three related analyses: (1) comparison of spectral values acquired by Landsats 7 and 8, separated by eight days, to ensure compatibility for time-series evaluation; (2) tracking of multitemporal signatures for different change processes across Landsat 5, 7, and 8 sensors using anniversary-date imagery; and (3) tracking the same type of processes using all available acquisitions. In this investigation, we found that data representing natural vegetation from Landsats 5, 7, and 8 were comparable and did not indicate a need for major modification prior to use for long-term monitoring. Analyses using anniversary-date imagery can be very effective for assessing long term patterns and trends occurring across the landscape, and are especially good for providing insights regarding trends related to long-term and continuous trends of growth or decline. We found that use of all available data provided a much more comprehensive level of understanding of the trends occurring, providing information about rate, duration, and intra- and inter-annual variability that could not be readily gleaned from the anniversary date analyses. We observed that using all available clear Landsat 5–8 observations with the new Continuous Change Detection and Classification (CCDC) algorithm was very effective for illuminating vegetation trends. There are a number of potential challenges for assessing gradual changes, including atmospheric impacts, algorithm development and visualization of the changes. One of the biggest challenges for studying gradual change will be the lack of appropriate data for validating results and products.

Remote Sensing of Environment↗
USGS2021

A novel automatic phenology learning (APL) method of training sample selection using multiple datasets for time-series land cover mapping

The long record of Landsat imagery, which is the cornerstone of Earth observation, provides an opportunity to monitor land use and land cover (LULC) change and understand the interactions between the climate and earth system through time. A few change detection algorithms such as Continuous Change Detection and Classification (CCDC) have been developed to utilize all available Landsat images for change detection and characterization at local or global scales. However, the reliable, rapid, and reproducible collection of training samples have become a challenge for time series land cover classification at a large scale. To meet the challenge, we proposed an automatic phenology learning (APL) method with the assumption that the temporal profiles of samples within the same land cover type are the same or similar at a local scale to generate evenly distributed training samples automatically. We designed the method to build land cover patterns for each category based on consensus samples derived from multiple existing scientific datasets including LANDFIRE's (LF) Existing Vegetation Type (EVT), USGS National Land Cover Database (NLCD), National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL), and National Wetlands Inventory (NWI). Then we calculated the Time-Weighted Dynamic Time Warping (twDTW) distance between any undefined samples and land cover patterns in the same geographical region as prior knowledge. Finally, we selected the optimal land cover category for each undefined sample from the land cover products based on the designed criteria iteratively using the twDTW distance as an indicator. The method was applied in the footprint of 10 selected Landsat Analysis Ready Data (ARD) tiles in the eastern and western conterminous United States (CONUS) to produce annual land cover maps from 1985 to 2017. The accuracy assessment and visual comparison revealed that the APL method can generate reliable training samples without any manual interpretation, producing better land cover results especially for the grass/shrub and wetland land cover classes. Applying the APL method, the overall accuracy of the annual land cover maps was improved by 2% over the accuracy of Land Change Monitoring, Assessment, and Projection (LCMAP) Collection 1.0 Science Products in the research regions. Our results also indicate that the APL method provides an approach for best use of different land cover products and meets the requirement of intensive sampling for training data collection.

Remote Sensing of Environment↗
USGS2026

Advances in volcano monitoring driven by the first decade of Sentinel-1 observations

Sentinel-1 has transformed how satellite radar data (SAR and InSAR) are used in volcanology. The systematic, long-term archive and open-access policy means that volcano observatories and research organisations have invested in integrating Sentinel-1 datasets into their monitoring systems. We identify 233 high priority volcanoes and estimate that Sentinel-1 data has been used in peer-reviewed publications for 90 of them. We examine a global archive of 3.3 million automatically processed Sentinel-1 interferograms of volcanoes and use machine learning methods to identify eruptions and periods of unrest. We then review the ways in which InSAR data are being used in different contexts. At frequently erupting basaltic systems in Iceland, Hawaiʻi, the Galápagos , and Piton de la Fournaise, InSAR has become an effective monitoring tool and is integrated with other datasets and models to forecast magma pathways. For large explosive eruptions, deformation measurements often remain challenging, but SAR backscatter is increasingly used to map damaging flows and measure the changing shape of ocean islands. Sentinel-1's long archive provides critical baseline measurements that are vital for measuring slow deformation, capturing new periods of unrest and providing fresh insights into subsurface dynamics. Understanding the drivers of deformation remains challenging and typically relies on integration with external datasets. Future European Space Agency missions have the potential to improve both resolution and coverage providing an even richer dataset to further enhance global volcano monitoring

Erta Ale volcano↗
USGS2017

Improved accuracy in quantitative laser-induced breakdown spectroscopy using sub-models

Accurate quantitative analysis of diverse geologic materials is one of the primary challenges faced by the Laser-Induced Breakdown Spectroscopy (LIBS)-based ChemCam instrument on the Mars Science Laboratory (MSL) rover. The SuperCam instrument on the Mars 2020 rover, as well as other LIBS instruments developed for geochemical analysis on Earth or other planets, will face the same challenge. Consequently, part of the ChemCam science team has focused on the development of improved multivariate analysis calibrations methods. Developing a single regression model capable of accurately determining the composition of very different target materials is difficult because the response of an element’s emission lines in LIBS spectra can vary with the concentration of other elements. We demonstrate a conceptually simple “sub-model” method for improving the accuracy of quantitative LIBS analysis of diverse target materials. The method is based on training several regression models on sets of targets with limited composition ranges and then “blending” these “sub-models” into a single final result. Tests of the sub-model method show improvement in test set root mean squared error of prediction (RMSEP) for almost all cases. The sub-model method, using partial least squares regression (PLS), is being used as part of the current ChemCam quantitative calibration, but the sub-model method is applicable to any multivariate regression method and may yield similar improvements.

Spectrochimica Acta Part B: Atomic Spectroscopy↗
USGS2015

Emerging technologies to conserve biodiversity

Technologies to identify individual animals, follow their movements, identify and locate animal and plant species, and assess the status of their habitats remotely have become better, faster, and cheaper as threats to the survival of species are increasing. New technologies alone do not save species, and new data create new problems. For example, improving technologies alone cannot prevent poaching: solutions require providing appropriate tools to the right people. Habitat loss is another driver: the challenge here is to connect existing sophisticated remote sensing with species occurrence data to predict where species remain. Other challenges include assembling a wider public to crowdsource data, managing the massive quantities of data generated, and developing solutions to rapidly emerging threats.

Trends in Ecology and Evolution↗
USGS2024

The emerging invasive species and climate change lexicon

The rapid diversification of terminology associated with invasion ecology is a known barrier to effective communication and management. These challenges are magnified by the addition of terms and concepts related to climate-induced range-shifting taxa and/or changes to impacts. Further, institutional policies and terminologies for invasive species introduce new ambiguities when considering climate change. To alleviate communication and application challenges, we introduce a conceptual framework that organizes climate-related invasion terms, revealing ambiguities and gaps. Additionally, we illustrate how these ambiguities can affect management with four case studies and consider situations where resolution can improve policy and management outcomes. The framework can help users avoid inconsistent use of terminology, and prioritize when to address management and policy consequences related to associated terminological ambiguity.

Trends in Ecology and Evolution↗
USGS2018

Broad-spectrum antiviral JL122 blocks infection and inhibits transmission of aquatic rhabdoviruses

The aquaculture industry is growing rapidly to meet the needs for global protein consumption. Viral diseases in aquaculture are quite challenging due to lack of treatment options as well as limited injection-delivery vaccines, which are costly. Thus, water-immersion antiviral treatments are highly desirable. This study focused on broad-spectrum, light-activated antivirals that target the viral membrane (envelope) of viruses to prevent viral-cell membrane fusion, ultimately blocking viral entry into cells. Of the tested small-molecules, JL122, a new broad-spectrum antiviral previously unexplored against aquatic viruses, blocked infection of three aquatic rhabdoviruses (IHNV, VHSV and SVCV) in cell culture and in two live fish challenge models. Importantly, JL122 inhibited transmission of IHNV from infected to uninfected rainbow trout. Further, the effective antiviral concentrations were not toxic to cells or susceptible fish. These results show promise for JL122 to become an immersion treatment option for outbreaks of aquatic enveloped viral infections.

Virology↗
USGS2012

Analysis of host genetic diversity and viral entry as sources of between-host variation in viral load

Little is known about the factors that drive the high levels of between-host variation in pathogen burden that are frequently observed in viral infections. Here, two factors thought to impact viral load variability, host genetic diversity and stochastic processes linked with viral entry into the host, were examined. This work was conducted with the aquatic vertebrate virus, Infectious hematopoietic necrosis virus (IHNV), in its natural host, rainbow trout. It was found that in controlled in vivo infections of IHNV, a suggestive trend of reduced between-fish viral load variation was observed in a clonal population of isogenic trout compared to a genetically diverse population of out-bred trout. However, this trend was not statistically significant for any of the four viral genotypes examined, and high levels of fish-to-fish variation persisted even in the isogenic trout population. A decrease in fish-to-fish viral load variation was also observed in virus injection challenges that bypassed the host entry step, compared to fish exposed to the virus through the natural water-borne immersion route of infection. This trend was significant for three of the four virus genotypes examined and suggests host entry may play a role in viral load variability. However, high levels of viral load variation also remained in the injection challenges. Together, these results indicate that although host genetic diversity and viral entry may play some role in between-fish viral load variation, they are not major factors. Other biological and non-biological parameters that may influence viral load variation are discussed.

Virus Research↗
USGS2021

Approach for quantifying rare Earth elements at low keV

The challenges of analyzing bastnaesite (REECO3F) and hydroxylbastnaesite (REECO3OH) include beam sensitivity, quantification of light elements in a heavy element matrix, the presence of elements that cannot be analyzed with EPMA (H), and the use of x-ray lines whose physical constants are not well known. To overcome some of these challenges, Ca, La, Ce, Pr, Nd, and Sm were analyzed at 15 keV accelerating voltage and the light elements (C, O, F) were analyzed at 7 keV accelerating voltage. This approach is ideal for samples that are homogeneous within the volume analyzed. However, for the bastnaesite of interest, this solution is unsatisfactory as backscattered electron imaging reveals chemical variations at scales of less than 1 m (fig. 1). Monte Carlo simulations and wavescans of the REE M family of x-rays were evaluated to determine the best analytical approach. Monte Carlo simulations using Casino v2.42 were ran on a substrate of CeCO3F with a density of 5.00 g/cm3 at 15 keV and 7 kCV accelerating voltage. Depth distribution curves, φ(ρz), reveal x-ray generation at 15 keV for the Ce L shell x-rays approaches 1.0 m whereas the depth of Ce M shell x-ray generation at 7 keV is less than 0.4 m. Similarly, the K shell x-ray generation depth for C, O, and F at 7 keV is also less than 0.4 m. These simulations demonstrate an accelerating voltage of 7 keV or less and use of the REE M x-rays is necessary to acquire chemical information from the same volume of material for the light and heavy elements. Bastnaesite contains all REE and therefore one must consider the energy of the highest x-ray line of interest, namely the Lu M at 1.83 kV, to achieve an overvoltage (Eo/Ec) of over 2. Bastnaesite is also an insulator and requires a conductive coating, therefore 7 keV was used to avoid contributions of the coating material to the analysis given the above constraints. The USNM REE phosphate standards, Edinburgh REE glasses, CeO2, LaB6, and the metals of Sm, Dy, Gd, Er, and Yb were selected to evaluate the peak overlaps of the M family x-ray lines. The materials were coated with ~ 5nm iridium with a Leica ACE600 prior to analysis. Full spectrometer wavescans were collected at 7 keV accelerating voltage, 50 nA beam current, and 20 um beam diameter on a JEOL 8530F Plus using TAP and TAPL crystals. The step size was 0.109 mm along the length of the spectrometer with a dwell of 3 seconds at each step. M and M lines are broad and not individually resolved for the light REE but become more separated and sharper with increasing atomic number. M and M lines for each REE are also present across the spectrometer range further complicating peak interference corrections. The peak positions and overall shape for the Ce M and M lines vary with the coordination of the element. Significant shifts in position and shape were not observed when comparing the Ce M peaks of CeO2 and CePO4. Similar results were seen when comparing the available REE metal to the phosphate (Sm, Dy, Gd, Er, Yb). These wavescans suggest the use of the M or M lines if matrix matched standards are not available.

Microscopy and Microanalysis↗
USGS2026

Ten new insights in climate science 2025

Interdisciplinary understanding is vital for delivering sound climate policy advice. However, navigating the ever-growing and increasingly diverse scholarly literature on climate change is challenging for any individual researcher. This annual synthesis highlights and explains recent advances across a variety of fields of climate change research. This year, the 10 insights focus on: (1) the record-warmth of 2023/2024 and the elevated Earth energy imbalance; (2) acceleration of ocean warming and intensifying marine heatwaves; (3) northern land carbon sinks under strain; (4) reinforcing feedback between biodiversity loss and climate change; (5) accelerated depletion of groundwater; (6) global dengue incidence; (7) global income losses and labour productivity declines; (8) strategic scaling of CDR; (9) integrity challenges in carbon credit markets and emerging responses; and (10) effective policy mixes for emissions reductions. The insights have been written to be accessible to researchers from different fields, serving as entry-points to specific topics, as well as providing an overview of the evolving landscape of climate change research. In the final section, the insights are used to develop overarching policy-relevant messages. This paper provides the basis for a science-policy report that was shared with all Party delegations ahead of COP30 in Belém, Brazil.

Global Sustainability↗
USGS2025

The US EPA’s National Nutrient Inventory: Critical shifts in US nutrient pollution sources from 1987 to 2017

Efforts to constrain the negative environmental impacts of excess nitrogen (N) and phosphorus (P) are costly and challenging, due in part to inconsistent reporting of nutrient sources at temporal and spatial scales relevant for local decision making. To meet this challenge, the U.S. Environmental Protection Agency’s National Nutrient Inventory provides estimates of major agricultural, urban, atmospheric, and natural nutrient fluxes for the contiguous United States at county and HUC12 scales annually from 1987 (from 1950 for agriculture) to 2017. Since the late 1980s, total N emissions and atmospheric N deposition have declined 22% and 15%, respectively, despite increased agricultural emissions. Over the same period, municipal wastewater N and P loads remained largely stable, despite population increases, through wastewater treatment upgrades and the phaseout of phosphorus-containing detergents. Improved agricultural efficiency allowed for dramatic increases in agricultural production and crop harvest since 1987 (∼25% for N and P), with little change in surplus nutrients left on fields. Overall, a combination of innovative technologies and management has stemmed or even decreased major sources of nutrient pollution to the environment over the last several decades, representing an important shift that, if continued, may contribute to improved air, land, and water quality and human health.

contiguous United States↗
USGS2011

Influence of dissolved organic matter on the environmental fate of metals, nanoparticles, and colloids

We have known for decades that dissolved organic matter (DOM) plays a critical role in the biogeochemical cycling of trace metals and the mobility of colloidal particles in aquatic environments. In recent years, concerns about the ecological and human health effects of metal-based engineered nanoparticles released into natural waters have increased efforts to better define the nature of DOM interactions with metals and surfaces. Nanomaterials exhibit unique properties and enhanced reactivities that are not apparent in larger materials of the same composition 1,2 or dissolved ions of metals that comprise the nanoparticles. These nanoparticle-specific properties generally result from the relatively large proportion of the atoms located at the surface, which leads to very high specific surface areas and a high proportion of crystal lattice imperfections relative to exposed surface area. Nanoscale colloids are ubiquitous in nature,2 and many engineered nanomaterials have analogs in the natural world. The properties of these materials, whether natural or manmade, are poorly understood, and new challenges have been presented in assessing their environmental fate. These challenges are particularly relevant in aquatic environments where interactions with DOM are key, albeit often overlooked, moderators of reactivity at the molecular and nanocolloidal scales.

Environmental Science & Technology↗
USGS2004

Granular avalanches across irregular three-dimensional terrain: 1. Theory and computation

To establish a theoretical basis for predicting and interpreting the behavior of rapid mass movements on Earth's surface, we develop and test a new computational model for gravity-driven motion of granular avalanches across irregular, three-dimensional (3-D) terrain. The principles embodied in the model are simple and few: continuum mass and momentum conservation and intergranular stress generation governed by Coulomb friction. However, significant challenges result from the necessity of satisfying these principles when deforming avalanches interact with steep and highly variable 3-D terrain. We address these challenges in four ways. (1) We formulate depth-averaged governing equations that are referenced to a rectangular Cartesian coordinate system (with z vertical) and that account explicitly for the effect of nonzero vertical accelerations on depth-averaged mass and momentum fluxes and stress states. (2) We compute fluxes of mass and momentum across vertical cell boundaries using a high-resolution finite volume method and Roe-type Riemann solver. Our algorithm incorporates flux difference splitting, an entropy correction for the flux, and eigenvector decomposition to embed the effects of driving and resisting forces in Riemann solutions. (3) We use a finite element method and avalanche displacements predicted by Riemann solutions to compute Coulomb stresses conjugate to the displacements in 3-D stress space. (4) We test the model output against analytical solutions, a sand cone conceptual experiment, and (in a companion paper) data from detailed laboratory experiments. Model results illustrate a complex interplay of basal traction and internal stress, and they successfully predict not only the gross behavior but also many details of avalanche motion from initiation to deposition.

Journal of Geophysical Research Earth Surface↗
USGS2003

Editorial

In our 3 years serving as editors, we have learned to our delight that Water Resources Research is truly the journal of the hydrologic community. Many individuals have expressed to us their sense of ownership of the journal and their passion for the sustained excellence of the journal. This is extremely healthy as it leads to productive discussions in which varying points of view are put forward, all for the purpose of making the journal better. The community decides the future of its journal. For WRR to be strong the community must be engaged, committed, and willing to discuss matters in a way that will enhance the journal. At this time, there are a number of challenges that face Water Resources Research . These are challenges for each member of the hydrologic community to consider.

Water Resources Research↗
USGS2009

Quantifying the spatial details of carbon sequestration potential and performance

Upscaling the spatial and temporal changes of carbon stocks and fluxes from sites to regions is challenging owing to the spatial and temporal variances and covariance of driving variables and the uncertainties in both the model and the input data. Although various modeling approaches have been developed to facilitate the upscaling process, few deal with error transfer from model input to output, and error propagation in time and space. The author has developed the General Ensemble Biogeochemical Modelling System (GEMS) for upscaling carbon stocks and fluxes from sites to regions with measures of uncertainty. This chapter describes the GEMS model, its application to regional- and larger-scale areas, and the new results that demonstrate the challenges of upscaling. GEMS relies on site-scale biogeochemical models to simulate carbon dynamics at the site scale. The spatial deployment of the site-scale model in GEMS is based on the spatial and temporal joint frequency distribution of major driving variables (e.g., land cover and land use change, climate, soils, disturbances, and management). At the site scale, GEMS uses stochastic ensemble simulations to incorporate input uncertainty to quantify uncertainty transfer from input to output, and to identify trends in both input data and simulation results. It permits one to simulate the range of possible permutations of input values and identify the trends and variance in both the input data and results. Using data assimilation techniques, GEMS simulations can be constrained by field and satellite observations, including estimates of net primary production (NPP) from the Moderate Resolution Imaging Spectroradiometer (MODIS), grain yield and cropping practices, and forest inventories. The modeling philosophy embedded in GEMS makes it ideal for assimilating information with various uncertainties to support estimating the spatial details of carbon sequestration potential as well as dynamic monitoring of the performance of carbon sequestration activities over large areas. As a case study, GEMS is applied to simulate the spatial and temporal details of carbon sources, sinks, and uncertainty in the Ridge and Valley ecoregion in the eastern United States

Book chapter↗
USGS2009

Interactions between soil thermal and hydrological dynamics in the response of Alaska ecosystems to fire disturbance

Soil temperature and moisture are important factors that control many ecosystem processes. However, interactions between soil thermal and hydrological processes are not adequately understood in cold regions, where the frozen soil, fire disturbance, and soil drainage play important roles in controlling interactions among these processes. These interactions were investigated with a new ecosystem model framework, the dynamic organic soil version of the Terrestrial Ecosystem Model, that incorporates an efficient and stable numerical scheme for simulating soil thermal and hydrological dynamics within soil profiles that contain a live moss horizon, fibrous and amorphous organic horizons, and mineral soil horizons. The performance of the model was evaluated for a tundra burn site that had both preburn and postburn measurements, two black spruce fire chronosequences (representing space-for-time substitutions in well and intermediately drained conditions), and a poorly drained black spruce site. Although space-for-time substitutions present challenges in model-data comparison, the model demonstrates substantial ability in simulating the dynamics of evapotranspiration, soil temperature, active layer depth, soil moisture, and water table depth in response to both climate variability and fire disturbance. Several differences between model simulations and field measurements identified key challenges for evaluating/improving model performance that include (1) proper representation of discrepancies between air temperature and ground surface temperature; (2) minimization of precipitation biases in the driving data sets; (3) improvement of the measurement accuracy of soil moisture in surface organic horizons; and (4) proper specification of organic horizon depth/properties, and soil thermal conductivity.

Alaska↗
USGS2009

An introduction to global carbon cycle management

Past and current human activities have fundamentally altered the global carbon cycle. Potential future efforts to control atmospheric CO 2 will also involve significant changes in the global carbon cycle. Carbon cycle scientists and engineers now face not only the difficulties of recording and understanding past and present changes but also the challenge of providing information and tools for new management strategies that are responsive to societal needs. The challenge is nothing less than managing the global carbon cycle.

Book chapter↗
USGS2011

Studying geodesy and earthquake hazard in and around the New Madrid Seismic Zone

Workshop on New Madrid Geodesy and the Challenges of Understanding Intraplate Earthquakes; Norwood, Massachusetts, 4 March 2011 Twenty-six researchers gathered for a workshop sponsored by the U.S. Geological Survey (USGS) and FM Global to discuss geodesy in and around the New Madrid seismic zone (NMSZ) and its relation to earthquake hazards. The group addressed the challenge of reconciling current geodetic measurements, which show low present-day surface strain rates, with paleoseismic evidence of recent, relatively frequent, major earthquakes in the region. The workshop presentations and conclusions will be available in a forthcoming USGS open-file report (http://pubs.usgs.gov).

Eos, Transactions, American Geophysical Union↗