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At least 739 records · Page 41Linked to original sources
USGS1962

Elastic constants of calcite

The recent measurements of the elastic constants of calcite by Reddy and Subrahmanyam (1960) disagree with the values obtained independently by Voigt (1910) and Bhimasenachar (1945). The present authors, using an ultrasonic pulse technique at 3 Mc and 25°C, determined the elastic constants of calcite using the exact equations governing the wave velocities in the single crystal. The results are C 11 =13.7, C 33 =8.11, C 44 =3.50, C 12 =4.82, C 13 =5.68, and C 14 =−2.00, in units of 10 11 dyn/cm 2 . Independent checks of several of the elastic constants were made employing other directions and polarizations of the wave velocities. With the exception of C 13 , these values substantially agree with the data of Voigt and Bhimasenachar.

Journal of Applied Physics↗
USGS2001

Toward a national fuels mapping strategy: Lessons from selected mapping programs

The establishment of a robust national fuels mapping program must be based on pertinent lessons from relevant national mapping programs. Many large-area mapping programs are under way in numerous Federal agencies. Each of these programs follows unique strategies to achieve mapping goals and objectives. Implementation approaches range from highly centralized programs that use tightly integrated standards and dedicated staff, to dispersed programs that permit considerable flexibility. One model facilitates national consistency, while the other allows accommodation of locally relevant conditions and issues. An examination of the programmatic strategies of four national vegetation and land cover mapping initiatives can identify the unique approaches, accomplishments, and lessons of each that should be considered in the design of a national fuel mapping program. The first three programs are the U.S. Geological Survey Gap Analysis Program, the U.S. Geological Survey National Land Cover Characterization Program, and the U.S. Fish and Wildlife Survey National Wetlands Inventory. A fourth program, the interagency Multiresolution Land Characterization Program, offers insights in the use of partnerships to accomplish mapping goals. Collectively, the programs provide lessons, guiding principles, and other basic concepts that can be used to design a successful national fuels mapping initiative.

International Journal of Wildland Fire↗
USGS2012

The effect of leaf beetle herbivory on the fire behaviour of tamarisk (Tamarix ramosissima Lebed.)

The non-native tree, Tamarix spp. has invaded desert riparian ecosystems in the south-western United States. Fire hazard has increased, as typically fire-resistant native vegetation is replaced by Tamarix. The tamarisk leaf beetle, Diorhabda carinulata Desbrochers, introduced for biological control, may affect fire behaviour by converting hydrated live Tamarix leaves and twigs into desiccated and dead fuels. This potentially increases fire hazard in the short term before native vegetation can be re-established. This study investigates how fire behaviour is altered in Tamarix fuels desiccated by Diorhabda herbivory at a Great Basin site, and by herbivory simulated by foliar herbicide at a Mojave Desert site. It also evaluates the influence of litter depth on fire intensity. Fire behaviour was measured with a fire intensity index that integrates temperature and duration (degree-minutes above 70°C), and with maximum temperature, duration, flame lengths, rates of spread and vegetation removal. Maximum temperature, flame length and rate of spread were enhanced by foliar desiccation of Tamarix at both sites. At only the Mojave site, there was a trend for desiccated trees to burn with greater fire intensity. At both sites, fire behaviour parameters were influenced to a greater degree by litter depth, vegetation density and drier and windier conditions than by foliar desiccation.

International Journal of Wildland Fire↗
USGS2013

Estimating wildfire risk on a Mojave Desert landscape using remote sensing and field sampling

Predicting wildfires that affect broad landscapes is important for allocating suppression resources and guiding land management. Wildfire prediction in the south-western United States is of specific concern because of the increasing prevalence and severe effects of fire on desert shrublands and the current lack of accurate fire prediction tools. We developed a fire risk model to predict fire occurrence in a north-eastern Mojave Desert landscape. First we developed a spatial model using remote sensing data to predict fuel loads based on field estimates of fuels. We then modelled fire risk (interactions of fuel characteristics and environmental conditions conducive to wildfire) using satellite imagery, our model of fuel loads, and spatial data on ignition potential (lightning strikes and distance to roads), topography (elevation and aspect) and climate (maximum and minimum temperatures). The risk model was developed during a fire year at our study landscape and validated at a nearby landscape; model performance was accurate and similar at both sites. This study demonstrates that remote sensing techniques used in combination with field surveys can accurately predict wildfire risk in the Mojave Desert and may be applicable to other arid and semiarid lands where wildfires are prevalent.

Mojave Desert↗
USGS2016

Synthesising empirical results to improve predictions of post-wildfire runoff and erosion response

Advances in research into wildfire impacts on runoff and erosion have demonstrated increasing complexity of controlling factors and responses, which, combined with changing fire frequency, present challenges for modellers. We convened a conference attended by experts and practitioners in post-wildfire impacts, meteorology and related research, including modelling, to focus on priority research issues. The aim was to improve our understanding of controls and responses and the predictive capabilities of models. This conference led to the eight selected papers in this special issue. They address aspects of the distinctiveness in the controls and responses among wildfire regions, spatiotemporal rainfall variability, infiltration, runoff connectivity, debris flow formation and modelling applications. Here we summarise key findings from these papers and evaluate their contribution to improving understanding and prediction of post-wildfire runoff and erosion under changes in climate, human intervention and population pressure on wildfire-prone areas.

International Journal of Wildland Fire↗
USGS2019

Evaluating the mid-infrared bi-spectral index for improved assessment of low-severity fire effects in a conifer forest

Remote sensing products provide a vital understanding of wildfire effects across a landscape, but detection and delineation of low- and mixed-severity fire remains difficult. While data provided by the Monitoring Trends in Burn Severity project (MTBS) are frequently used to assess severity in the United States, alternative indices can offer improvement to the measurement of low-severity fire effects and should be considered for future product development and adoption. This research note evaluated one such alternative, the mid-infrared bi-spectral index (MIRBI), which was developed in savannah ecosystems to isolate spectral changes caused by burning and reduce noise from other factors. MIRBI, differenced MIRBI (dMIRBI) and burn severity indices used by MTBS were assessed for spectral optimality at distinguishing severity and the ability to separate unburned and burned canopy in a conifer forest. The MIRBI indices were better at isolating changes caused by burning and demonstrated higher spectral separability, particularly at low severity. These findings suggest that MIRBI indices can provide an enhanced alternative or compliment to current MTBS products in high canopy cover forests for applications such as discernment of fire perimeters and unburned islands, as well as identification of low-severity fire effects.

International Journal of Wildland Fire↗
USGS2010

The use of multi-temporal Landsat Normalized Difference Vegetation Index (NDVI) data for mapping fuels in Yosemite National Park, USA

The objective of this study was to test the applicability of using Normalized Difference Vegetation Index (NDVI) values derived from a temporal sequence of six Landsat Thematic Mapper (TM) scenes to map fuel models for Yosemite National Park, USA. An unsupervised classification algorithm was used to define 30 unique spectral-temporal classes of NDVI values. A combination of graphical, statistical and visual techniques was used to characterize the 30 classes and identify those that responded similarly and could be combined into fuel models. The final classification of fuel models included six different types: short annual and perennial grasses, tall perennial grasses, medium brush and evergreen hardwoods, short-needled conifers with no heavy fuels, long-needled conifers and deciduous hardwoods, and short-needled conifers with a component of heavy fuels. The NDVI, when analysed over a season of phenologically distinct periods along with ancillary data, can elicit information necessary to distinguish fuel model types. Fuels information derived from remote sensors has proven to be useful for initial classification of fuels and has been applied to fire management situations on the ground.

International Journal of Remote Sensing↗
USGS2011

An evaluation of sampling strategies to improve precision of estimates of gross change in land use and land cover

Statistical sampling offers a cost-effective, practical alternative to complete-coverage mapping for the objective of estimating gross change in land cover over large areas. Because land cover change is typically rare, the sampling strategy must take advantage of design and analysis tools that enhance precision. Using two populations of land cover change in the eastern United States, we demonstrate that the choice of sampling unit size and use of a survey sampling regression estimator can significantly improve precision with only a minor increase in cost.

International Journal of Remote Sensing↗
USGS2007

Mapping the invasive species, Chinese tallow, with EO1 satellite Hyperion hyperspectral image data and relating tallow occurrences to a classified Landsat Thematic Mapper land cover map

Our objective was to provide a realistic and accurate representation of the spatial distribution of Chinese tallow (Triadica sebifera) in the Earth Observing 1 (EO1) Hyperion hyperspectral image coverage by using methods designed and tested in previous studies. We transformed, corrected, and normalized Hyperion reflectance image data into composition images with a subpixel extraction model. Composition images were related to green vegetation, senescent foliage and senescing cypress-tupelo forest, senescing Chinese tallow with red leaves ('red tallow'), and a composition image that only corresponded slightly to yellowing vegetation. These statistical and visual comparisons confirmed a successful portrayal of landscape features at the time of the Hyperion image collection. These landscape features were amalgamated in the Landsat Thematic Mapper (TM) pixel, thereby preventing the detection of Chinese tallow occurrences in the Landsat TM classification. With the occurrence in percentage of red tallow (as a surrogate for Chinese tallow) per pixel mapped, we were able to link dominant land covers generated with Landsat TM image data to Chinese tallow occurrences as a first step toward determining the sensitivity and susceptibility of various land covers to tallow establishment. Results suggested that the highest occurrences and widest distribution of red tallow were (1) apparent in disturbed or more open canopy woody wetland deciduous forests (including cypress-tupelo forests), upland woody land evergreen forests (dominantly pines and seedling plantations), and upland woody land deciduous and mixed forests; (2) scattered throughout the fallow fields or located along fence rows separating active and non-active cultivated and grazing fields, (3) found along levees lining the ubiquitous canals within the marsh and on the cheniers near the coastline; and (4) present within the coastal marsh located on the numerous topographic highs. ?? 2005 US Government.

International Journal of Remote Sensing↗
USGS2009

Global irrigated area map (GIAM), derived from remote sensing, for the end of the last millennium

A Global Irrigated Area Map (GIAM) has been produced for the end of the last millennium using multiple satellite sensor, secondary, Google Earth and groundtruth data. The data included: (a) Advanced Very High Resolution Radiometer (AVHRR) 3-band and Normalized Difference Vegetation Index (NDVI) 10 km monthly time-series for 1997-1999, (b) Syste me pour l'Observation de la Terre Vegetation (SPOT VGT) NDVI 1 km monthly time series for 1999, (c) East Anglia University Climate Research Unit (CRU) rainfall 50km monthly time series for 1961-2000, (d) Global 30 Arc-Second Elevation Data Set (GTOPO30) 1 km digital elevation data of the World, (e) Japanese Earth Resources Satellite-1 Synthetic Aperture Radar (JERS-1 SAR) data for the rain forests during two seasons in 1996 and (f) University of Maryland Global Tree Cover 1 km data for 1992-1993. A single mega-file data-cube (MFDC) of the World with 159 layers, akin to hyperspectral data, was composed by re-sampling different data types into a common 1 km resolution. The MFDC was segmented based on elevation, temperature and precipitation zones. Classification was performed on the segments. Quantitative spectral matching techniques (SMTs) used in hyperspectral data analysis were adopted to group class spectra derived from unsupervised classification and match them with ideal or target spectra. A rigorous class identification and labelling process involved the use of: (a) space-time spiral curve (ST-SC) plots, (b) brightness-greenness-wetness (BGW) plots, (c) time series NDVI plots, (d) Google Earth very-high-resolution imagery (VHRI) 'zoom-in views' in over 11 000 locations, (e) groundtruth data broadly sourced from the degree confluence project (3 864 sample locations) and from the GIAM project (1 790 sample locations), (f) high-resolution Landsat-ETM+ Geocover 150m mosaic of the World and (g) secondary data (e.g. national and global land use and land cover data). Mixed classes were resolved based on decision tree algorithms and spatial modelling, and when that did not work, the problem class was used to mask and re-classify the MDFC, and the class identification and labelling protocol repeated. The sub-pixel area (SPA) calculations were performed by multiplying full-pixel areas (FPAs) with irrigated area fractions (IAFs) for every class. A 28 class GIAM was produced and the area statistics reported as: (a) annualized irrigated areas (AIAs), which consider intensity of irrigation (i.e. sum of irrigated areas from different seasons in a year plus continuous year-round irrigation or gross irrigated areas), and (b) total area available for irrigation (TAAI), which does not consider intensity of irrigation (i.e. irrigated areas at any given point of time plus the areas left fallow but 'equipped for irrigation' at the same point of time or net irrigated areas). The AIA of the World at the end of the last millennium was 467 million hectares (Mha), which is sum of the non-overlapping areas of: (a) 252 Mha from season one, (b) 174 Mha from season two and (c) 41 Mha from continuous year-round crops. The TAAI at the end of the last millennium was 399 Mha. The distribution of irrigated areas is highly skewed amongst continents and countries. Asia accounts for 79% (370 Mha) of all AIAs, followed by Europe (7%) and North America (7%). Three continents, South America (4%), Africa (2%) and Australia (1%), have a very low proportion of the global irrigation. The GIAM had an accuracy of 79-91%, with errors of omission not exceeding 21%, and the errors of commission not exceeding 23%. The GIAM statistics were also compared with: (a) the United Nations Food and Agricultural Organization (FAO) and University of Frankfurt (UF) derived irrigated areas and (b) national census data for India. The relationships and causes of differences are discussed in detail. The GIAM products are made available through a web portal (http://www.iwmigiam.org). ?? 2009 Taylor & Francis.

International Journal of Remote Sensing↗
USGS2011

On the terminology of the spectral vegetation index (NIR – SWIR)/(NIR + SWIR)

The spectral vegetation index (ρNIR – ρSWIR)/(ρNIR + ρSWIR), where ρNIR and ρSWIR are the near-infrared (NIR) and shortwave-infrared (SWIR) reflectances, respectively, has been widely used to indicate vegetation moisture condition. This index has multiple names in the literature, including infrared index (II), normalized difference infrared index (NDII), normalized difference water index (NDWI), normalized difference moisture index (NDMI), land surface water index (LSWI), and normalized burn ratio (NBR), etc. After reviewing each term’s definition, associated sensors, and channel specifications, we found that the index consists of three variants, differing only in the SWIR region (1.2–1.3 µm, 1.55–1.75 µm, or 2.05–2.45 µm). Thus, three terms are sufficient to represent these three SWIR variants; other names are redundant and therefore unnecessary. Considering the spectral representativeness, the term’s popularity, and the “rule of priority” in scientific nomenclature, NDWI, NDII, and NBR, each corresponding to the three SWIR regions, are more preferable terms.

International Journal of Remote Sensing↗
USGS2011

An approach to regional wetland digital elevation model development using a differential global positioning system and a custom-built helicopter-based surveying system

Accurate topographic data are critical to restoration science and planning for the Everglades region of South Florida, USA. They are needed to monitor and simulate water level, water depth and hydroperiod and are used in scientific research on hydrologic and biologic processes. Because large wetland environments and data acquisition challenge conventional ground-based and remotely sensed data collection methods, the United States Geological Survey (USGS) adapted a classical data collection instrument to global positioning system (GPS) and geographic information system (GIS) technologies. Data acquired with this instrument were processed using geostatistics to yield sub-water level elevation values with centimetre accuracy (±15 cm). The developed database framework, modelling philosophy and metadata protocol allow for continued, collaborative model revision and expansion, given additional elevation or other ancillary data.

Florida↗
USGS2016

Lidar-based mapping of flood control levees in south Louisiana

Flood protection in south Louisiana is largely dependent on earthen levees, and in the aftermath of Hurricane Katrina the state’s levee system has received intense scrutiny. Accurate elevation data along the levees are critical to local levee district managers responsible for monitoring and maintaining the extensive system of non-federal levees in coastal Louisiana. In 2012, high resolution airborne lidar data were acquired over levees in Lafourche Parish, Louisiana, and a mobile terrestrial lidar survey was conducted for selected levee segments using a terrestrial lidar scanner mounted on a truck. The mobile terrestrial lidar data were collected to test the feasibility of using this relatively new technology to map flood control levees and to compare the accuracy of the terrestrial and airborne lidar. Metrics assessing levee geometry derived from the two lidar surveys are also presented as an efficient, comprehensive method to quantify levee height and stability. The vertical root mean square error values of the terrestrial lidar and airborne lidar digital-derived digital terrain models were 0.038 m and 0.055 m, respectively. The comparison of levee metrics derived from the airborne and terrestrial lidar-based digital terrain models showed that both types of lidar yielded similar results, indicating that either or both surveying techniques could be used to monitor geomorphic change over time. Because airborne lidar is costly, many parts of the USA and other countries have never been mapped with airborne lidar, and repeat surveys are often not available for change detection studies. Terrestrial lidar provides a practical option for conducting repeat surveys of levees and other terrain features that cover a relatively small area, such as eroding cliffs or stream banks, and dunes.

Louisiana↗
USGS2019

The potential role of very high-resolution imagery to characterise lake, wetland and stream systems across the Prairie Pothole Region, United States

Aquatic features critical to watershed hydrology range widely in size from narrow, shallow streams to large, deep lakes. In this study we evaluated wetland, lake, and river systems across the Prairie Pothole Region to explore where pan-sharpened high-resolution (PSHR) imagery, relative to Landsat imagery, could provide additional data on surface water distribution and movement, missed by Landsat. We used the monthly Global Surface Water (GSW) Landsat product as well as surface water derived from Landsat imagery using a matched filtering algorithm (MF Landsat) to help consider how including partially inundated Landsat pixels as water influenced our findings. The PSHR outputs (and MF Landsat) were able to identify ~60–90% more surface water interactions between waterbodies, relative to the GSW Landsat product. However, regardless of Landsat source, by documenting many smaller (<0.2 ha), inundated wetlands, the PSHR outputs modified our interpretation of wetland size distribution across the Prairie Pothole Region.

Prairie Pothole Region↗
USGS2005

Geochemical controls on microbial nitrate-dependent U(IV) oxidation

After reductive immobilization of uranium, the element may be oxidized and remobilized in the presence of nitrate by the activity of dissimilatory nitrate-reducing bacteria. We examined controls on microbially mediated nitrate-dependent U(IV) oxidation in landfill leachate-impacted subsurface sediments. Nitrate-dependent U(IV)-oxidizing bacteria were at least two orders of magnitude less numerous in these sediments than glucose- or Fe(II)-oxidizing nitrate-reducing bacteria and grew more slowly than the latter organisms, suggesting that U(IV) is ultimately oxidized by Fe(III) produced by nitrate-dependent Fe(II)-oxidizing bacteria or by oxidation of Fe(II) by nitrite that accumulates during organotrophic dissimilatory nitrate reduction. We examined the effect of nitrate and reductant concentration on nitrate-dependent U(IV) oxidation in sediment incubations and used the initial reductive capacity (RDC = [reducing equivalents] - [oxidizing equivalents]) of the incubations as a unified measurement of the nitrate or reductant concentration. When we lowered the RDC with progressively higher nitrate concentrations, we observed a corresponding increase in the extent of U(IV) oxidation, but did not observe this relationship between RDC and U(IV) oxidation rate, especially when RDC > 0, suggesting that nitrate concentration strongly controls the extent, but not the rate of nitrate-dependent U(IV) oxidation. On the other hand, when we raised the RDC in sediment incubations with progressively higher reductant (acetate, sulfide, soluble Fe(II), or FeS) concentrations, we observed progressively lower extents and rates of nitrate-dependent U(IV) oxidation. Acetate was a relatively poor inhibitor of nitrate-dependent U(IV) oxidation, while Fe(II) was the most effective inhibitor. Based on these results, we propose that it may be possible to predict the stability of U(IV) in a bioremediated aquifer based on the geochemical characteristics of that aquifer.

Geomicrobiology Journal↗
USGS2011

Acetate availability and its influence on sustainable bioremediation of Uranium-contaminated groundwater

Field biostimulation experiments at the U.S. Department of Energy's Integrated Field Research Challenge (IFRC) site in Rifle, Colorado, have demonstrated that uranium concentrations in groundwater can be decreased to levels below the U.S. Environmental Protection Agency's (EPA) drinking water standard (0.126 μM). During successive summer experiments – referred to as “Winchester” (2007) and “Big Rusty” (2008) - acetate was added to the aquifer to stimulate the activity of indigenous dissimilatory metal-reducing bacteria capable of reductively immobilizing uranium. The two experiments differed in the length of injection (31 vs. 110 days), the maximum concentration of acetate (5 vs. 30 mM), and the extent to which iron reduction (“Winchester”) or sulfate reduction (“Big Rusty”) was the predominant metabolic process. In both cases, rapid removal of U(VI) from groundwater occurred at calcium concentrations (6 mM) and carbonate alkalinities (8 meq/L) where Ca-UO 2 -CO 3 ternary complexes constitute >90% of uranyl species in groundwater. Complete consumption of acetate and increased alkalinity (>30 meq/L) accompanying the onset of sulfate reduction corresponded to temporary increases in U(VI); however, by increasing acetate concentrations in excess of available sulfate (10 mM), low U(VI) concentrations (0.1–0.05 μM) were achieved for extended periods of time (>140 days). Uniform delivery of acetate during “Big Rusty” was impeded due to decreases in injection well permeability, likely resulting from biomass accumulation and carbonate and sulfide mineral precipitation. Such decreases were not observed during the short-duration “Winchester” experiment. Terminal restriction fragment length polymorphism (TRFLP) analysis of 16S rRNA genes demonstrated that Geobacter sp. and Geobacter -like strains dominated the groundwater community profile during iron reduction, with 13 C stable isotope probing (SIP) results confirming these strains were actively utilizing acetate to replicate their genome during the period of optimal U(VI) removal. Gene transcript levels during “Big Rusty” were quantified for Geobacter -specific citrate synthase ( gltA ), with ongoing transcription during sulfate reduction indicating that members of the Geobacteraceae were still active and likely contributing to U(VI) removal. The persistence of reducible Fe(III) in sediments recovered from an area of prolonged (110-day) sulfate reduction is consistent with this conclusion. These results indicate that acetate availability and its ability to sustain the activity of iron- and uranyl-respiring Geobacter strains during sulfate reduction exerts a primary control on optimized U(VI) removal from groundwater at the Rifle IFRC site over extended time scales (>50 days).

Geomicrobiology Journal↗
USGS1993

Evaluation of 55Fe as a tracer of Fe(III) reduction in aquatic sediments

The potential utility of 55 Fe as a tracer for Fe(III) reduction in aquatic sediments was evaluated using freshwater sediments from the Potomac River, Md, in which Fe(III) reduction was the predominant terminal electron accepting process. In laboratory incubations of sediments amended with poorly crystalline 55 Fe(III) oxide, the accumulation of 55 Fe in Fe(II) over time paralleled Fe(II) production. However, within 1 h of addition of 55 Fe(III) oxide, significant quantities of 55 Fe were recovered in extractable (1 M sodium acetate, pH 5) and soluble Fe(II) pools. There was proportionately more 55 Fe(II) activity in sediments with higher Fe(II) concentrations. These results suggest that there was rapid isotopic exchange between 55 Fe in poorly crystalline Fe(III) oxide and the Fe(II) pools. Because of this exchange, 55 Fe could not be used to trace Fe(III) reduction in sediments in the manner that 35 SO 4 2− is used to trace sulfate reduction. Although accumulation of 55 Fe in Fe(II) pools paralleled unla‐beled Fe(II) production, given the relative ease with which Fe(II) pools in sediments can be measured there is no apparent advantage to using 55 Fe to follow Fe(III) reduction.

Geomicrobiology Journal↗
USGS1992

Trace elements in lake sediment, macrozoobenthos, and fish near a coal ash disposal basin

Samples of lake sediment, macrozoobenthos, and fish were collected during 1983 and 1984 near a coal ash disposal basin situated on the western shoreline of Lake Erie. Neutron activation analysis was used to determine if potentially toxic trace elements were present in higher concentrations at stations near the basin than at reference stations a few kilometers away. Of the 29 trace elements examined, arsenic and cobalt were significantly ( p <0.05) more concentrated in sediment nearest the coal ash basin except in spring, when little or no difference was detected. Arsenic and bromine were significantly higher in oligochaetes, and selenium was significantly higher in both oligochaetes and chironomids taken from proximal stations than in those taken from reference stations. Selenium, bromine, cobalt, nickel, and chromium were higher in young-of-the-year brown bullheads taken nearer the disposal basin in fall 1983. Selenium was higher in adult spottail shiners taken at the proximal station in spring 1984, and bromine was higher in yearling white bass from the proximal station in fall 1983 and 1984. None of the trace elements was higher in adult yellow perch or adult brown bullheads at any time. Fewer spottail shiners and yearling white bass were caught close to the disposal basin than far away, which may indicate avoidance by these fish of increased concentrations of trace elements contained within the ash effluent.

Journal of Freshwater Ecology↗