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USGS2011

The geochemistry and petrogenesis of the Paleoproterozoic Green Mountain arc: A composite(?), bimodal, oceanic, fringing arc

The inferred subduction affinity of the ∼1780-Ma Green Mountain arc, a dominantly bimodal igneous terrane (together with immature marine and volcaniclastic sedimentary rocks) accreted to the southern margin of the Wyoming province, is integral to arc-accretion models of the Paleoproterozoic growth of southern Laurentia. Conversely, the dominantly bimodal nature of many putative arc-related igneous suites throughout southern Laurentia, including the Green Mountain arc, has also been used to support models of growth by extension of pre-existing crust. We report new geochemical and isotopic data from ∼1780-Ma gabbroic and granodioritic to tonalitic rocks of the Big Creek Gneiss, interpreted as consanguineous with previously studied metavolcanic rocks of the Green Mountain Formation. The ∼1780-Ma Big Creek Gneiss mafic rocks show clear geochemical signatures of a subduction origin and provide no supporting evidence for extensional tectonism. The ∼1780-Ma Big Creek Gneiss felsic rocks are attributed to partial melting of mafic and/or mixed lower-crustal material. The bimodal nature of the suite results from the combination of arc basalts and felsic crustal melts. The lack of andesite is consistent with the observed tholeiitic differentiation trend of the mafic magmas. The lower ɛ Nd (1780 Ma) values for the felsic rocks vs. the mafic rocks suggest that the unexposed lower crust of the arc may be older than the arc and that Trans-Hudson- or Penokean-aged rocks possibly form the substratum of the arc. Our results reinforce previous interpretations that arc-related magmatism played a key role in the Paleoproterozoic crustal growth of southern Laurentia, but also support the possibility of unexposed older crust as basement to the arcs.

Wyoming, Colorado↗

USGS2011

A working environment for digital planetary data processing and mapping using ISIS and GRASS GIS

Since the beginning of planetary exploration, mapping has been fundamental to summarize observations returned by scientific missions. Sensor-based mapping has been used to highlight specific features from the planetary surfaces by means of processing. Interpretative mapping makes use of instrumental observations to produce thematic maps that summarize observations of actual data into a specific theme. Geologic maps, for example, are thematic interpretative maps that focus on the representation of materials and processes and their relative timing. The advancements in technology of the last 30 years have allowed us to develop specialized systems where the mapping process can be made entirely in the digital domain. The spread of networked computers on a global scale allowed the rapid propagation of software and digital data such that every researcher can now access digital mapping facilities on his desktop. The efforts to maintain planetary missions data accessible to the scientific community have led to the creation of standardized digital archives that facilitate the access to different datasets by software capable of processing these data from the raw level to the map projected one. Geographic Information Systems (GIS) have been developed to optimize the storage, the analysis, and the retrieval of spatially referenced Earth based environmental geodata; since the last decade these computer programs have become popular among the planetary science community, and recent mission data start to be distributed in formats compatible with these systems. Among all the systems developed for the analysis of planetary and spatially referenced data, we have created a working environment combining two software suites that have similar characteristics in their modular design, their development history, their policy of distribution and their support system. The first, the Integrated Software for Imagers and Spectrometers (ISIS) developed by the United States Geological Survey, represents the state of the art for processing planetary remote sensing data, from the raw unprocessed state to the map projected product. The second, the Geographic Resources Analysis Support System (GRASS) is a Geographic Information System developed by an international team of developers, and one of the core projects promoted by the Open Source Geospatial Foundation (OSGeo). We have worked on enabling the combined use of these software systems throughout the set-up of a common user interface, the unification of the cartographic reference system nomenclature and the minimization of data conversion. Both software packages are distributed with free open source licenses, as well as the source code, scripts and configuration files hereafter presented. In this paper we describe our work done to merge these working environments into a common one, where the user benefits from functionalities of both systems without the need to switch or transfer data from one software suite to the other one. Thereafter we provide an example of its usage in the handling of planetary data and the crafting of a digital geologic map. ?? 2010 Elsevier Ltd. All rights reserved.

Conference Paper↗

USGS2007

Recent results on the spatiotemporal modelling and comparative analysis of Black Death and bubonic plague epidemics

Background: This work demonstrates the importance of spatiotemporal stochastic modelling in constructing maps of major epidemics from fragmentary information, assessing population impacts, searching for possible etiologies, and performing comparative analysis of epidemics. Methods: Based on the theory previously published by the authors and incorporating new knowledge bases, informative maps of the composite space-time distributions were generated for important characteristics of two major epidemics: Black Death (14th century Western Europe) and bubonic plague (19th-20th century Indian subcontinent). Results: The comparative spatiotemporal analysis of the epidemics led to a number of interesting findings: (1) the two epidemics exhibited certain differences in their spatiotemporal characteristics (correlation structures, trends, occurrence patterns and propagation speeds) that need to be explained by means of an interdisciplinary effort; (2) geographical epidemic indicators confirmed in a rigorous quantitative manner the partial findings of isolated reports and time series that Black Death mortality was two orders of magnitude higher than that of bubonic plague; (3) modern bubonic plague is a rural disease hitting harder the small villages in the countryside whereas Black Death was a devastating epidemic that indiscriminately attacked large urban centres and the countryside, and while the epidemic in India lasted uninterruptedly for five decades, in Western Europe it lasted three and a half years; (4) the epidemics had reverse areal extension features in response to annual seasonal variations. Temperature increase at the end of winter led to an expansion of infected geographical area for Black Death and a reduction for bubonic plague, reaching a climax at the end of spring when the infected area in Western Europe was always larger than in India. Conversely, without exception, the infected area during winter was larger for the Indian bubonic plague; (5) during the Indian epidemic, the disease disappeared and reappeared several times at most locations; in Western Europe, once the disease entered a place, it lasted a time proportional to the population and then disappeared for several years (this on-and-off situation lasted more than three centuries); and (6) on average, Black Death moved much faster than bubonic plague to reach virgin territories, despite the fact that India is only slightly larger in area than Western Europe and had a railroad network almost instantly moving infected rats, fleas, and people from one end of the subcontinent to the other. Conclusions: These findings throw new light on the spatiotemporal characteristics of the epidemics and need to be taken into consideration in the scientific discussion concerning the two devastating diseases and the lessons learned from them. ?? 2007 The Royal Institute of Public Health.

Public Health↗

USGS2015

High-resolution paleoclimatology of the Santa Barbara Basin during the Medieval Climate Anomaly and early Little Ice Age based on diatom and silicoflagellate assemblages in Kasten core SPR0901-02KC

Diatom and silicoflagellate assemblages documented in a high-resolution time series spanning 800 to 1600 AD in varved sediment recovered in Kasten core SPR0901-02KC (34°16.845’ N, 120°02.332’ W, water depth 588 m) from the Santa Barbara Basin (SBB) reveal that SBB surface water conditions during the Medieval Climate Anomaly (MCA) and the early part of the Little Ice Age (LIA) were not extreme by modern standards, mostly falling within one standard deviation of mean conditions during the pre anthropogenic interval of 1748 to 1900. No clear differences between the character of MCA and the early LIA conditions are apparent. During intervals of extreme droughts identified by terrigenous proxy scanning XRF analyses, diatom and silicoflagellate proxies for coastal upwelling typically exceed one standard deviation above mean values for 1748-1900, supporting the hypothesis that droughts in southern California are associated with cooler (or La Niña-like) sea surface temperatures (SSTs). Increased percentages of diatoms transported downslope generally coincide with intervals of increased siliciclastic flux to the SBB identified by scanning XRF analyses. Diatom assemblages suggest only two intervals of the MCA (at ~897 to 922 and ~1151 to 1167) when proxy SSTs exceeded one standard deviation above mean values for 1748 to 1900. Conversely, silicoflagellates imply extreme warm water events only at ~830 to 860 (early MCA) and ~1360 to 1370 (early LIA) that are not supported by the diatom data. Silicoflagellates appear to be more suitable for characterizing average climate during the 5 to 11 year-long sample intervals studied in the SPR0901-02KC core than diatoms, probably because diatom relative abundances may be dominated by seasonal blooms of a particular year.

California↗

USGS2016

Lesser prairie-chicken avoidance of trees in a grassland landscape

Grasslands are among the most imperiled ecosystems in North America. Reasons that grasslands are threatened include conversion to row-crop agriculture, fragmentation, and changes in fire regimes. The reduction of fire processes in remaining prairies has resulted in tree encroachment and establishment in grasslands, further reducing grassland quantity and quality. Grassland birds have been experiencing precipitous population declines in recent decades, commensurate with landscape changes to grasslands. The lesser prairie-chicken ( Tympanuchus pallidicinctus Ridgway) is a declining species of prairie grouse of conservation concern. We used second- and third-order habitat selection metrics to test if female lesser prairie-chickens avoid grasslands where trees were present. Our results indicated that female lesser prairie-chickens selected habitats avoiding the nearest trees by 283 m on average, nearly twice as far as would be expected at random. Lesser prairie-chickens were 40 times more likely to use habitats with tree densities of 0 trees ∙ ha − 1 than habitats with 5 trees ∙ ha − 1 . Probability of use indicated that lesser prairie-chickens were 19 times more likely to use habitats 1000 m from the nearest tree when compared with using habitats 0 m from the nearest tree. Nest survival was not affected at densities < 2 trees ∙ ha − 1 ; however, we could not test if nest survival was affected at greater tree densities as no nests were detected at densities > 2 trees ∙ ha − 1 . Avoidance of trees could be due to perceived increased predation risk, reduced habitat quality, or a combination of these potentially confounding factors. Preventing further establishment and expansion of trees in landscapes occupied by lesser prairie-chickens could contribute to the continued persistence of the species. Additionally, restoring grasslands through tree removal may facilitate conservation efforts for grassland species such as the lesser prairie-chicken by improving habitat quality and promoting expansion of occupied range.

Kansas↗

USGS2020

Departures of rangeland fractional component cover and land cover from landsat-based ecological potential in Wyoming USA

Monitoring rangelands by identifying the departure of contemporary conditions from long-term ecological potential allows for the disentanglement of natural biophysical gradients driving change from changes associated with land uses and other disturbance types. We developed maps of ecological potential (EP) for shrub, sagebrush ( Artemisia spp.), perennial herbaceous, litter, and bare ground fractional cover in Wyoming, USA. EP maps correspond to the potential natural vegetation cover expected by environmental conditions in the absence of anthropogenic and natural disturbance as represented by the greenest and least disturbed period of the Landsat archive. EP was predicted using regression tree models with inputs of soil maps and spectral data associated with the 75th percentile of the Normalized Difference Vegetation Index in the Landsat archive. We trained our EP models with 2015 component cover maps on ecologically intact sites with relatively lower bare ground than expected. We generated departure of vegetation cover by comparing the EP and 2015 fractional cover. The departures represent land cover change from potential land cover and/or within-state changes in 2015. Next, we converted EP and 2015 fractional cover maps into thematic land cover and evaluated departure to determine if it was great enough to result in land cover change. The 2015 conditions showed reduced shrub, sagebrush, litter, and perennial herbaceous cover and increased bare ground relative to EP. Known disturbances, such as energy development, fires, and vegetation treatments, are clearly visible on the departure maps, but not on EP component maps. The most frequent departure from EP land cover was shrubland conversion to grassland. Land cover departures can be explained only in small part by known disturbance, and instead are ostensibly related to climate and land management practices. These drivers result in land cover departures that broadened the ecotone between shrubland and grassland relative to EP.

Wyoming↗

USGS2020

Energy development and production in the Great Plains: Implications and restoration opportunities

Energy is an integral part of society. The major US energy sources of fossil fuels (coal, oil, natural gas); biofuels (ethanol); and wind are concentrated in grassland ecosystems of the Great Plains. As energy demand continues to increase, mounting pressures will be placed on North American grassland systems. In this review, we present the ecological effects of energy development and production on grassland systems. We then identify opportunities to mitigate these effects during the planning, construction, and production phases by using informed methodology and improved technology. Primary effects during energy development include small- and large-scale soil disturbance and vegetation removal as small patches of grasslands are used to host oil or gas wells, wind turbine pads, associated roadways, and pipelines or through the conversion of large grassland areas to biofuel croplands. Direct habitat loss or habitat fragmentation can affect wildlife directly through increased mortality or indirectly through reduction in habitat quantity and quality. During energy production, air and water quality can be affected through regular emissions or unplanned spills. Energy development can also affect the economy and health of local communities. During planning, energy development and production effects can be reduced by carefully considering effects on grasslands during siting and even by selecting different energy source types. During construction, effects on soil and plant systems can be minimized by eliminating weed populations before disturbance, salvaging and stockpiling topsoil for future revegetation, and harvesting native local seed for postsite restoration. During energy production operations, noise and road traffic reduction plans and atmospheric monitoring will enable more informed mitigation measures. Continued research on energy development effects and mitigation measures is necessary to establish best management practices beneficial to grassland health while providing needed energy for the United States.

Colorado, Illinois, Indiana, Iowa, Kansas, Minneso↗

USGS2023

Future direction of fuels management in sagebrush rangelands

Sagebrush ecosystems in the United States have been declining since EuroAmerican settlement, largely due to agricultural and urban development, invasive species, and altered fire regimes, resulting in loss of biodiversity and wildlife habitat. To combat continued conversion to undesirable ecological states and loss of habitat to invasive species fueled by frequent fire, a variety of fuel treatments, including networks of fuel breaks, are being implemented or proposed in sagebrush ecosystems, particularly in and around the Great Basin. In this forum paper we briefly review current knowledge of common fuel treatment approaches, their intended benefits, potential risks, and limitations. We additionally discuss challenges for fuel treatment strategies in the context of changes in climate, invasive species, wildlife habitat, and human population, and we explore how advances in geospatial technologies, monitoring, and fire behavior modeling, as well as accounting for social context, can improve the efficacy of fuels management in sagebrush ecosystems. Finally, given continued potential for ecosystem transformation, we describe approaches to future fuels management by considering the applicability of the Resist-Accept-Direct (RAD) framework. The intent of the paper is to provide scientists and land managers with key information and a forward-thinking framework for fuels science and adaptive management that can respond to both expected and unexpected changes in sagebrush rangelands.

Rangeland Ecology and Management↗

USGS2025

Edge effects along roadside fuel treatments in sagebrush steppe

Increasing wildfire has motivated the construction of fuel breaks on many rangelands to improve prospects for wildfire suppression. However, the linear shape of fuel breaks greatly increases treatment perimeter: area and thus increased potential for edge effects, e.g., invasions by exotic plants. Potential for edge effects are further increased by the disturbances associated with fuel-break implementation. Fire risk in perennial-dominated and sagebrush-steppe rangelands are increased by exotic species, such as cheatgrass and other associated annuals, and therefore invasions after fuel-break implementation are problematic, yet have rarely been evaluated. Abundances of dominant invaders, cheatgrass and Russian thistle, were measured along treated and neighboring untreated edges in 40 paired plots along ∼61 km of 60-m wide fuel breaks. Fuel breaks were constructed using a variety of shrub-cutting and herbicide applications 1–4 yr before measurement. Generalized linear mixed effect models revealed that fractional cover significantly increased in treated compared with untreated areas by 0.02–0.12 for cheatgrass and 0–0.06 for Russian thistle within 9 m of treatment boundaries (on a scale of 0-1). We neither detected increased invasion in adjacent and untreated areas nor gradients of increasing invasion with proximity to treatment boundaries. Although these findings reveal invasions that were otherwise undetected across the entire 60 m width of fuel breaks, invasion levels did not surpass nominal management thresholds for fire behavior or risk of conversion to annual grasslands.

Rangeland Ecology and Management↗

USGS2004

Land cover mapping of North and Central America—Global Land Cover 2000

The Land Cover Map of North and Central America for the year 2000 (GLC 2000-NCA), prepared by NRCan/CCRS and USGS/EROS Data Centre (EDC) as a regional component of the Global Land Cover 2000 project, is the subject of this paper. A new mapping approach for transforming satellite observations acquired by the SPOT4/VGTETATION (VGT) sensor into land cover information is outlined. The procedure includes: (1) conversion of daily data into 10-day composite; (2) post-seasonal correction and refinement of apparent surface reflectance in 10-day composite images; and (3) extraction of land cover information from the composite images. The pre-processing and mosaicking techniques developed and used in this study proved to be very effective in removing cloud contamination, BRDF effects, and noise in Short Wave Infra-Red (SWIR). The GLC 2000-NCA land cover map is provided as a regional product with 28 land cover classes based on modified Federal Geographic Data Committee/Vegetation Classification Standard (FGDC NVCS) classification system, and as part of a global product with 22 land cover classes based on Land Cover Classification System (LCCS) of the Food and Agriculture Organisation. The map was compared on both areal and per-pixel bases over North and Central America to the International Geosphere–Biosphere Programme (IGBP) global land cover classification, the University of Maryland global land cover classification (UMd) and the Moderate Resolution Imaging Spectroradiometer (MODIS) Global land cover classification produced by Boston University (BU). There was good agreement (79%) on the spatial distribution and areal extent of forest between GLC 2000-NCA and the other maps, however, GLC 2000-NCA provides additional information on the spatial distribution of forest types. The GLC 2000-NCA map was produced at the continental level incorporating specific needs of the region.

Remote Sensing of Environment↗

USGS2005

A simple and effective radiometric correction method to improve landscape change detection across sensors and across time

Satellite data offer unrivaled utility in monitoring and quantifying large scale land cover change over time. Radiometric consistency among collocated multi-temporal imagery is difficult to maintain, however, due to variations in sensor characteristics, atmospheric conditions, solar angle, and sensor view angle that can obscure surface change detection. To detect accurate landscape change using multi-temporal images, we developed a variation of the pseudoinvariant feature (PIF) normalization scheme: the temporally invariant cluster (TIC) method. Image data were acquired on June 9, 1990 (Landsat 4), June 20, 2000 (Landsat 7), and August 26, 2001 (Landsat 7) to analyze boreal forests near the Siberian city of Krasnoyarsk using the normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and reduced simple ratio (RSR). The temporally invariant cluster (TIC) centers were identified via a point density map of collocated pixel VIs from the base image and the target image, and a normalization regression line was created to intersect all TIC centers. Target image VI values were then recalculated using the regression function so that these two images could be compared using the resulting common radiometric scale. We found that EVI was very indicative of vegetation structure because of its sensitivity to shadowing effects and could thus be used to separate conifer forests from deciduous forests and grass/crop lands. Conversely, because NDVI reduced the radiometric influence of shadow, it did not allow for distinctions among these vegetation types. After normalization, correlations of NDVI and EVI with forest leaf area index (LAI) field measurements combined for 2000 and 2001 were significantly improved; the r 2 values in these regressions rose from 0.49 to 0.69 and from 0.46 to 0.61, respectively. An EVI "cancellation effect" where EVI was positively related to understory greenness but negatively related to forest canopy coverage was evident across a post fire chronosequence with normalized data. These findings indicate that the TIC method provides a simple, effective and repeatable method to create radiometrically comparable data sets for remote detection of landscape change. Compared to some previous relative radiometric normalization methods, this new method does not require high level programming and statistical skills, yet remains sensitive to landscape changes occurring over seasonal and inter-annual time scales. In addition, the TIC method maintains sensitivity to subtle changes in vegetation phenology and enables normalization even when invariant features are rare. While this normalization method allowed detection of a range of land use, land cover, and phenological/biophysical changes in the Siberian boreal forest region studied here, it is necessary to further examine images representing a wide variety of ecoregions to thoroughly evaluate the TIC method against other normalization schemes. ?? 2005 Elsevier Inc. All rights reserved.

Remote Sensing of Environment↗

USGS2009

Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors

This paper provides a summary of the current equations and rescaling factors for converting calibrated Digital Numbers (DNs) to absolute units of at-sensor spectral radiance, Top-Of-Atmosphere (TOA) reflectance, and at-sensor brightness temperature. It tabulates the necessary constants for the Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and Advanced Land Imager (ALI) sensors. These conversions provide a basis for standardized comparison of data in a single scene or between images acquired on different dates or by different sensors. This paper forms a needed guide for Landsat data users who now have access to the entire Landsat archive at no cost.

Remote Sensing of Environment↗

USGS2009

Using LiDAR and quickbird data to model plant production and quantify uncertainties associated with wetland detection and land cover generalizations

Spatiotemporal data from satellite remote sensing and surface meteorology networks have made it possible to continuously monitor global plant production, and to identify global trends associated with land cover/use and climate change. Gross primary production (GPP) and net primary production (NPP) are routinely derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard satellites Terra and Aqua, and estimates generally agree with independent measurements at validation sites across the globe. However, the accuracy of GPP and NPP estimates in some regions may be limited by the quality of model input variables and heterogeneity at fine spatial scales. We developed new methods for deriving model inputs (i.e., land cover, leaf area, and photosynthetically active radiation absorbed by plant canopies) from airborne laser altimetry (LiDAR) and Quickbird multispectral data at resolutions ranging from about 30??m to 1??km. In addition, LiDAR-derived biomass was used as a means for computing carbon-use efficiency. Spatial variables were used with temporal data from ground-based monitoring stations to compute a six-year GPP and NPP time series for a 3600??ha study site in the Great Lakes region of North America. Model results compared favorably with independent observations from a 400??m flux tower and a process-based ecosystem model (BIOME-BGC), but only after removing vapor pressure deficit as a constraint on photosynthesis from the MODIS global algorithm. Fine-resolution inputs captured more of the spatial variability, but estimates were similar to coarse-resolution data when integrated across the entire landscape. Failure to account for wetlands had little impact on landscape-scale estimates, because vegetation structure, composition, and conversion efficiencies were similar to upland plant communities. Plant productivity estimates were noticeably improved using LiDAR-derived variables, while uncertainties associated with land cover generalizations and wetlands in this largely forested landscape were considered less important.

Remote Sensing of Environment↗

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↗

USGS2017

A land cover change detection and classification protocol for updating Alaska NLCD 2001 to 2011

Monitoring and mapping land cover changes are important ways to support evaluation of the status and transition of ecosystems. The Alaska National Land Cover Database (NLCD) 2001 was the first 30-m resolution baseline land cover product of the entire state derived from circa 2001 Landsat imagery and geospatial ancillary data. We developed a comprehensive approach named AKUP11 to update Alaska NLCD from 2001 to 2011 and provide a 10-year cyclical update of the state's land cover and land cover changes. Our method is designed to characterize the main land cover changes associated with different drivers, including the conversion of forests to shrub and grassland primarily as a result of wildland fire and forest harvest, the vegetation successional processes after disturbance, and changes of surface water extent and glacier ice/snow associated with weather and climate changes. For natural vegetated areas, a component named AKUP11-VEG was developed for updating the land cover that involves four major steps: 1) identify the disturbed and successional areas using Landsat images and ancillary datasets; 2) update the land cover status for these areas using a SKILL model (System of Knowledge-based Integrated-trajectory Land cover Labeling); 3) perform decision tree classification; and 4) develop a final land cover and land cover change product through the postprocessing modeling. For water and ice/snow areas, another component named AKUP11-WIS was developed for initial land cover change detection, removal of the terrain shadow effects, and exclusion of ephemeral snow changes using a 3-year MODIS snow extent dataset from 2010 to 2012. The overall approach was tested in three pilot study areas in Alaska, with each area consisting of four Landsat image footprints. The results from the pilot study show that the overall accuracy in detecting change and no-change is 90% and the overall accuracy of the updated land cover label for 2011 is 86%. The method provided a robust, consistent, and efficient means for capturing major disturbance events and updating land cover for Alaska. The method has subsequently been applied to generate the land cover and land cover change products for the entire state of Alaska.

Alaska↗

USGS2018

Analyzing floating and bedfast lake ice regimes across Arctic Alaska using 25 years of space-borne SAR imagery

Late-winter lake ice regimes are controlled by water depth relative to maximum ice thickness (MIT). When MIT exceeds maximum water depth, lakes freeze to the bottom with bedfast ice (BI) and when MIT is less than maximum water depth lakes have floating ice (FI). Both airborne radar and space-borne synthetic aperture radar (SAR) imagery (Ku-, X-, C-, and L-band) have been used previously to determine whether lakes have a BI or FI regime in a given year, across a number of years, or across large regions. In this study, we use a combination of ERS-1/2, RADARSAT-2, Envisat, and Sentinel-1 SAR imagery for seven lake-rich regions in Arctic Alaska to analyze lake ice regime extents and dynamics over a 25-year period (1992–2016). Our interactive threshold classification method determines a unique statistic-based intensity threshold for each SAR scene, allowing for the comparison of classification results from C-band SAR data acquired with different polarizations and incidence angles. Additionally, our novel method accommodates declining signal strength in aging extended-mission satellite SAR instruments. Comparison of SAR ice regime classifications with extensive field measurements from six years yielded a 93% accuracy. Significant declines in BI regimes were only observed in the Fish Creek area with 3% of lakes exhibiting transitional ice regimes—lakes that switch from BI to FI during this 25-year period. This analysis suggests that the potential conversion from BI to FI regimes is primarily a function of lake depth distributions in addition to regional differences in climate variability . Remote sensing of lake ice regimes with C-band SAR is a useful tool to monitor the associated thermal impacts on permafrost, since lake ice regimes can be used as a proxy for of sub-lake permafrost thaw, considered by the Global Climate Observing System as an Essential Climate Variable (ECV). Continued winter warming and variable snow conditions in the Arctic are expected and our long-term analysis provides a valuable baseline for predicting where potential future lake ice regimes shifts will be most pronounced.

Alaska↗

USGS2007

The distribution, occurrence and environmental effect of mercury in Chinese coals

Mercury (Hg) is a toxic, persistent, and globally distributed pollutant due to its characteristic properties such as low melting and boiling points, conversion between chemical forms and participation in biological cycles. During combustion mercury in coal is almost totally emitted to the atmosphere. With a huge amount of coal consumed, coal combustion is one of the main anthropogenic sources of this element in the environment. In this study, Hg data of 1699 coal samples of China has been compiled, and the concentration, distribution, modes of occurrence, and the impact of Hg emissions on the environment are investigated. Most Chinese coals have Hg content in the range of 0.1 to 0.3??ppm, with an average of 0.19??ppm, which is slightly higher than the average Hg content of world coals and is close to that of the U.S. coals. The Hg content in coals varies in different coal basins, geological ages and coal ranks. The most likely mode of occurrences of Hg in high-sulfur and high Hg content coals is as solid solution in pyrite. But in low-sulfur coals, modes of occurrence of Hg are variable, and the organic-bound and sulfide-bound Hg may dominate. Silicate-bound Hg may be the main form in some coals because of magmatic intrusion. Mercury emissions during coal combustion have resulted in serious environmental contamination in China, particularly in the northeastern and southwestern China, where a high Hg content in the atmosphere occurs. ?? 2007 Elsevier B.V. All rights reserved.

Science of the Total Environment↗

USGS2014

Mercury cycling in agricultural and managed wetlands: a synthesis of methylmercury production, hydrologic export, and bioaccumulation from an integrated field study

With seasonal wetting and drying, and high biological productivity, agricultural wetlands (rice paddies) may enhance the conversion of inorganic mercury (Hg(II)) to methylmercury (MeHg), the more toxic, organic form that biomagnifies through food webs. Yet, the net balance of MeHg sources and sinks in seasonal wetland environments is poorly understood because it requires an annual, integrated assessment across biota, sediment, and water components. We examined a suite of wetlands managed for rice crops or wildlife during 2007–2008 in California's Central Valley, in an area affected by Hg contamination from historic mining practices. Hydrologic management of agricultural wetlands for rice, wild rice, or fallowed — drying for field preparation and harvest, and flooding for crop growth and post-harvest rice straw decay — led to pronounced seasonality in sediment and aqueous MeHg concentrations that were up to 95-fold higher than those measured concurrently in adjacent, non-agricultural permanently-flooded and seasonally-flooded wetlands. Flooding promoted microbial MeHg production in surface sediment of all wetlands, but extended water residence time appeared to preferentially enhance MeHg degradation and storage. When incoming MeHg loads were elevated, individual fields often served as a MeHg sink, rather than a source. Slow, horizontal flow of shallow water in the agricultural wetlands led to increased importance of vertical hydrologic fluxes, including evapoconcentration of surface water MeHg and transpiration-driven advection into the root zone, promoting temporary soil storage of MeHg. Although this hydrology limited MeHg export from wetlands, it also increased MeHg exposure to resident fish via greater in situ aqueous MeHg concentrations. Our results suggest that the combined traits of agricultural wetlands — slow-moving shallow water, manipulated flooding and drying, abundant labile plant matter, and management for wildlife — may enhance microbial methylation of Hg(II) and MeHg exposure to local biota, as well as export to downstream habitats during uncontrolled winter-flow events.

California↗