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At least 343 records · Page 19Linked to original sources

USGS2013

Controls on recent Alaskan lake changes identified from water isotopes and remote sensing

High-latitude lakes are important for terrestrial carbon dynamics and waterfowl habitat driving a need to better understand controls on lake area changes. To identify the existence and cause of recent lake area changes in the Yukon Flats, a region of discontinuous permafrost in north central Alaska, we evaluate remotely sensed imagery with lake water isotope compositions and hydroclimatic parameters. Isotope compositions indicate that mixtures of precipitation, river water, and groundwater source ~95% of the studied lakes. The remaining minority are more dominantly sourced by snowmelt and/or permafrost thaw. Isotope-based water balance estimates indicate 58% of lakes lose more than half of inflow by evaporation. For 26% of the lakes studied, evaporative losses exceeded supply. Surface area trend analysis indicates that most lakes were near their maximum extent in the early 1980s during a relatively cool and wet period. Subsequent reductions can be explained by moisture deficits and greater evaporation.

Alaska↗

USGS2011

Vegetation index-based crop coefficients to estimate evapotranspiration by remote sensing in agricultural and natural ecosystems

Crop coefficients were developed to determine crop water needs based on the evapotranspiration (ET) of a reference crop under a given set of meteorological conditions. Starting in the 1980s, crop coefficients developed through lysimeter studies or set by expert opinion began to be supplemented by remotely sensed vegetation indices (VI) that measured the actual status of the crop on a field-by-field basis. VIs measure the density of green foliage based on the reflectance of visible and near infrared (NIR) light from the canopy, and are highly correlated with plant physiological processes that depend on light absorption by a canopy such as ET and photosynthesis. Reflectance-based crop coefficients have now been developed for numerous individual crops, including corn, wheat, alfalfa, cotton, potato, sugar beet, vegetables, grapes and orchard crops. Other research has shown that VIs can be used to predict ET over fields of mixed crops, allowing them to be used to monitor ET over entire irrigation districts. VI-based crop coefficients can help reduce agricultural water use by matching irrigation rates to the actual water needs of a crop as it grows instead of to a modeled crop growing under optimal conditions. Recently, the concept has been applied to natural ecosystems at the local, regional and continental scales of measurement, using time-series satellite data from the MODIS sensors on the Terra satellite. VIs or other visible-NIR band algorithms are combined with meteorological data to predict ET in numerous biome types, from deserts, to arctic tundra, to tropical rainforests. These methods often closely match ET measured on the ground at the global FluxNet array of eddy covariance moisture and carbon flux towers. The primary advantage of VI methods for estimating ET is that transpiration is closely related to radiation absorbed by the plant canopy, which is closely related to VIs. The primary disadvantage is that they cannot capture stress effects or soil evaporation. Copyright ?? 2011 John Wiley & Sons, Ltd.

Hydrological Processes↗

USGS2015

An assessment of two methods for identifying undocumented levees using remotely sensed data

Many undocumented and commonly unmaintained levees exist in the landscape complicating flood forecasting, risk management, and emergency response. This report describes a pilot study completed by the U.S. Geological Survey in cooperation with the U.S. Army Corps of Engineers to assess two methods to identify undocumented levees by using remotely sensed, high-resolution topographic data. For the first method, the U.S. Army Corps of Engineers examined hillshades computed from a digital elevation model that was derived from light detection and ranging (lidar) to visually identify potential levees and then used detailed site visits to assess the validity of the identifications. For the second method, the U.S. Geological Survey applied a wavelet transform to a lidar-derived digital elevation model to identify potential levees. The hillshade method was applied to Delano, Minnesota, and the wavelet-transform method was applied to Delano and Springfield, Minnesota. Both methods were successful in identifying levees but also identified other features that required interpretation to differentiate from levees such as constructed barriers, high banks, and bluffs. Both methods are complementary to each other, and a potential conjunctive method for testing in the future includes (1) use of the wavelet-transform method to rapidly identify slope-break features in high-resolution topographic data, (2) further examination of topographic data using hillshades and aerial photographs to classify features and map potential levees, and (3) a verification check of each identified potential levee with local officials and field visits.

Minnesota↗

USGS2009

Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006

Shifts in the timing of spring phenology are a central feature of global change research. Long-term observations of plant phenology have been used to track vegetation responses to climate variability but are often limited to particular species and locations and may not represent synoptic patterns. Satellite remote sensing is instead used for continental to global monitoring. Although numerous methods exist to extract phenological timing, in particular start-of-spring (SOS), from time series of reflectance data, a comprehensive intercomparison and interpretation of SOS methods has not been conducted. Here, we assess 10 SOS methods for North America between 1982 and 2006. The techniques include consistent inputs from the 8 km Global Inventory Modeling and Mapping Studies Advanced Very High Resolution Radiometer NDVIg dataset, independent data for snow cover, soil thaw, lake ice dynamics, spring streamflow timing, over 16 000 individual measurements of ground-based phenology, and two temperature-driven models of spring phenology. Compared with an ensemble of the 10 SOS methods, we found that individual methods differed in average day-of-year estimates by ±60 days and in standard deviation by ±20 days. The ability of the satellite methods to retrieve SOS estimates was highest in northern latitudes and lowest in arid, tropical, and Mediterranean ecoregions. The ordinal rank of SOS methods varied geographically, as did the relationships between SOS estimates and the cryospheric/hydrologic metrics. Compared with ground observations, SOS estimates were more related to the first leaf and first flowers expanding phenological stages. We found no evidence for time trends in spring arrival from ground- or model-based data; using an ensemble estimate from two methods that were more closely related to ground observations than other methods, SOS trends could be detected for only 12% of North America and were divided between trends towards both earlier and later spring.

Global Change Biology↗

USGS2018

Use of remote sensing to detect and predict aquatic nuisance vegetation growth in coastal Louisiana: Summary of findings

On an annual basis, federal and state agencies are responsible for mapping and removing large expanses of aquatic nuisance vegetation from navigable waterways. This study set out to achieve four primary objectives: (1) utilize recent advancements in remote sensing techniques to classify the extent and distribution of aquatic vegetation in coastal ecosystems using satellite imagery, (2) assess primary aquatic vegetation growth and management efforts in coastal Louisiana, (3) statistically identify the ecological drivers that promote growth and infestation of aquatic nuisance vegetation, and (4) develop numerical models and a spatial tool to predict the probability of occurrence and growth of aquatic vegetation given ecological drivers. Moderate spatial resolution multispectral satellite imagery were used in conjunction with environmental variables from available data streams to generate regression models that predict aquatic vegetation occurrence in the eastern coastal region of south Louisiana. Geospatial tools were developed to execute the model logic using recent environmental conditions, thereby predicting aquatic vegetation occurrence and producing classified maps for end users. These products provide more efficient and enhanced capabilities for management of aquatic nuisance vegetation.

Louisiana↗

USGS2009

Research Implementation and Quality Assurance Project Plan: An Evaluation of Hyperspectral Remote Sensing Technologies for the Detection of Fugitive Contamination at Selected Superfund Hazardous Waste Sites

This project is a research collaboration between the U.S. Environmental Protection Agency (EPA) Office of Inspector General (OIG) and the U.S. Geological Survey (USGS) Eastern Geographic Science Center (EGSC), for the purpose of evaluating the utility of hyperspectral remote sensing technology for post-closure monitoring of residual contamination at delisted and closed hazardous waste sites as defined under the Comprehensive Environmental Response Compensation and Liability Act [CERCLA (also known as 'Superfund')] of 1980 and the Superfund Amendments and Reauthorization Act (SARA) of 1986.

Open-File Report↗

USGS2007

Optimizing remote sensing and GIS tools for mapping and managing the distribution of an invasive mangrove (Rhizophora mangle) on South Molokai, Hawaii

In 1902, the Florida red mangrove, Rhizophora mangle L., was introduced to the island of Molokai, Hawaii, and has since colonized nearly 25% of the south coast shoreline. By classifying three kinds of remote sensing imagery, we compared abilities to detect invasive mangrove distributions and to discriminate mangroves from surrounding terrestrial vegetation. Using three analytical techniques, we compared mangrove mapping accuracy for various sensor-technique combinations. ANOVA of accuracy assessments demonstrated significant differences among techniques, but no significant differences among the three sensors. We summarize advantages and disadvantages of each sensor and technique for mapping mangrove distributions in tropical coastal environments.

Marine Geodesy↗

USGS1995

Microwave radiometers and their application in field and aircraft campaigns for remote sensing of land and water surfaces

The paper presents an overview of the scientific investigations and practical applications of a group of specialists working in the Institute of Radioengineering and Electronics of the Russian Academy of Sciences (IRE RAS) with their partners in Russia and the USA in the area of passive microwave remote sensing as applied to the study of soil, vegetation and water bodies. Applications that are described include problems related to agriculture, land reclamation, water management, wetlands, and highways.

Conference Paper↗

USGS2020

Landslide monitoring and runout hazard assessment by integrating multi-source remote sensing and numerical models: An application to the Gold Basin landslide complex, northern Washington

The landslide complex at Gold Basin, Washington, has been drawing considerable attention after a catastrophic runout of the nearby landslide at Oso, Washington, in 2014. To evaluate potential threats of the Gold Basin landslide to the campground down the slope, remote sensing and numerical modeling were integrated to monitor recent landslide activity and simulate hypothetical runout scenarios. Bare-earth LiDAR DEM (digital elevation model) differencing, InSAR (Interferometric Synthetic Aperture Radar), and offset tracking of SAR images reveal that localized collapses at the headscarps have been the primary type of landslide activity at Gold Basin from 2005 to 2019, and currently no signs indicative of movement of a large centralized block or a deep-seated main body were detected. The maximum horizontal deformation rate is 5 m/year occurring primarily from headscarp recession of the middle lobe, and the annual landsliding volume of the whole landslide complex averages 1.03 × 10 5 m 3 . From three-dimensional limit equilibrium analysis of generalized terrace structures, the maximum landslide volume is estimated as 2.0 × 10 6 m 3 . Simulations of hypothetical runout scenarios were carried out using the depth-averaged two-phase model D-claw with above-obtained landslide geometry constraints. The simulation results demonstrate that debris flows with volume less than 10 5 m 3 only pose limited threats to the campground, while volumes over 10 6 m 3 could cause severe damages. Consequently, the estimated maximum landslide volume of 2.0 × 10 6 m 3 suggests a potential risk to the campground nearby. Adaption of our methodology could prove useful for evaluating other similar landslides globally for hazards prevention and mitigation.

Washington↗

USGS2002

Remotely sensed geology from lander-based to orbital perspectives: Results of FIDO rover May 2000 field tests

Blind field tests of the Field Integration Design and Operations (FIDO) prototype Mars rover were carried out 7-16 May 2000. A Core Operations Team (COT), sequestered at the Jet Propulsion Laboratory without knowledge of test site location, prepared command sequences and interpreted data acquired by the rover. Instrument sensors included a stereo panoramic camera, navigational and hazard-avoidance cameras, a color microscopic imager, an infrared point spectrometer, and a rock coring drill. The COT designed command sequences, which were relayed by satellite uplink to the rover, and evaluated instrument data. Using aerial photos and Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) data, and information from the rover sensors, the COT inferred the geology of the landing site during the 18 sol mission, including lithologic diversity, stratigraphic relationships, environments of deposition, and weathering characteristics. Prominent lithologic units were interpreted to be dolomite-bearing rocks, kaolinite-bearing altered felsic volcanic materials, and basalt. The color panoramic camera revealed sedimentary layering and rock textures, and geologic relationships seen in rock exposures. The infrared point spectrometer permitted identification of prominent carbonate and kaolinite spectral features and permitted correlations to outcrops that could not be reached by the rover. The color microscopic imager revealed fine-scale rock textures, soil components, and results of coring experiments. Test results show that close-up interrogation of rocks is essential to investigations of geologic environments and that observations must include scales ranging from individual boulders and outcrops (microscopic, macroscopic) to orbital remote sensing, with sufficient intermediate steps (descent images) to connect in situ and remote observations.

Journal of Geophysical Research E: Planets↗

USGS2011

Hyperspectral remote sensing of wetland vegetation

Wetlands proportionally exert a higher influence on biogeochemical fluxes among the land, the atmosphere, and hydrologic systems than their 1% worldwide occurrence suggests [1]. Although their frequency of occurrence is low and their importance is high, wetlands continue to face high detrimental pressures from natural and human-induced forces [2]. Remote sensing offers the single best source of timely, synoptic wetland status and trends information at a variety of spatial and temporal scales [3].

Book chapter↗

USGS1978

A selected bibliography: Remote sensing applications for tropical and subtropical vegetation analysis

This bibliography contains 425 citations of selected technical reports, journal articles, and other publications covering the general subject of tropical and subtropical vegetation analysis. Functionally related topics that include vegetation analysis are included for completeness, and citations have been organized under the following subheadings for ease of reference: remote sensing application overviews, vegetation (general), forestry, grasslands/savannah/shrublands, agriculture, land use/thematic mapping, and integrated surveys/multiple resource analysis/land systems. The terms "tropics and subtropics" are used in the widest context to include applications related to a broad range of equatorial environments. The bibliography contains selected citations published between 1924 and 1978. Many foreign language and non U.S.- source items are included.

Report↗

USGS2006

Remotely sensed data available from the US Geological Survey EROS Data Center

The Center for Earth Resources Observation Systems (EROS) is a field center of the geography discipline within the US geological survey (USGS) of the Department of the Interior. The EROS Data Center (EDC) was established in the early 1970s as the nation’s principal archive of remotely sensed data. Initially the EDC was responsible for the archive, reproduction, and distribution of black-and-white and color-infrared aerial photography acquired under numerous mapping programs conducted by various Federal agencies including the USGS, Department of Agriculture, Environmental Protection Agency, and NASA. The EDC was also designated the central archive for data acquired by the first satellite sensor designed for broad-scale earth observations in support of civilian agency needs for earth resource information. A four-band multispectral scanner (MSS) and a return-beam vidicon (RBV) camera were initially flown on the Earth Resources Technology Satellite-1, subsequently designated Landsat-1. The synoptic coverage, moderate spatial resolution, and multi-spectral view provided by these data stimulated scientists with an unprecedented perspective from which to study the Earth’s surface and to understand the relationships between human activity and natural systems.

Book chapter↗

USGS2016

An intercomparison of remote sensing river discharge estimation algorithms from measurements of river height, width, and slope

The Surface Water and Ocean Topography (SWOT) satellite mission planned for launch in 2020 will map river elevations and inundated area globally for rivers >100 m wide. In advance of this launch, we here evaluated the possibility of estimating discharge in ungauged rivers using synthetic, daily ‘‘remote sensing’’ measurements derived from hydraulic models corrupted with minimal observational errors. Five discharge algorithms were evaluated, as well as the median of the five, for 19 rivers spanning a range of hydraulic and geomorphic conditions. Reliance upon a priori information, and thus applicability to truly ungauged reaches, varied among algorithms: one algorithm employed only global limits on velocity and depth, while the other algorithms relied on globally available prior estimates of discharge. We found at least one algorithm able to estimate instantaneous discharge to within 35% relative root-mean-squared error (RRMSE) on 14/16 nonbraided rivers despite out-of-bank flows, multichannel planforms, and backwater effects. Moreover, we found RRMSE was often dominated by bias; the median standard deviation of relative residuals across the 16 nonbraided rivers was only 12.5%. SWOT discharge algorithm progress is therefore encouraging, yet future efforts should consider incorporating ancillary data or multialgorithm synergy to improve results

Water Resources Research↗

USGS1994

A vegetation classification logic-based on remote-sensing for use in global biogeochemical models

A simple new classification logic for global vegetation is proposed. The critical features of this classification are that: it is based on simple, observable, unambiguous character- istics of vegetation structure that are important to ecosystem biogeochemistry and can be measured in the field for validation; the structural characteristics can be determined by remote sensing, so that repeatable and efficient global re-classifications of existing vegetation will be possible; and the defined vegetation classes directly translate into the biophysical parameters of interest by global climate and biogeochemical models. A first test of this logic for the continental United States is presented based on an existing 1 km Normalized Difference Vegetation Index database. Currently recognized global biome classes can easily be derived from this classification by adding climate descriptors and defining mixtures of these fundamental six vegetation classes.

Ambio↗

USGS2022

High-resolution remote sensing and multistate occupancy estimation identify drivers of spawning site selection in fall chum salmon (Oncorhynchus keta) across a sub-Arctic riverscape

Groundwater upwellings provide warmer, stable overwinter temperatures for developing salmon embryos, which may be particularly important in cold, braided, gravel-bed sub-Arctic rivers. We used a three-year time series of aerial counts and remote sensing to estimate the distribution of low and high aggregations of spawning fall chum salmon ( Oncorhynchus keta ), classify approximately 0.5 km long river segments by geomorphic channel type, and map thermal variability along a 25.4 km stretch of the Teedriinjik River, Alaska. We used a dynamic multistate occupancy model to estimate detectability, occupancy, and the dynamics of spawning aggregations among river segments. Detectability was higher for large (>150) relative to smaller aggregations. Unoccupied segments were likely to remain so from year to year; low abundance spawning segments were dynamic and rarely remained in that state for multiple years, while ∼20%–35% of high abundance segments remained stable, indicating the presence of high-quality spawning habitat. Spawning habitat use was associated with warmer water temperatures likely caused by groundwater upwellings. We identified spawning habitat characteristics and trends in usage by fall chum salmon, which will inform land management decisions and assist in evaluating impacts of shifting climate conditions and resource management on Arctic salmon populations.

Alaska↗

USGS1993

The Conterminous United States Mineral Assessment Program; background information to accompany folio of geologic, geochemical, remote sensing, and mineral resources maps of the Butte 1 degree x 2 degrees Quadrangle, Montana

The Butte 1?x2 ? quadrangle in west-central Montana was investigated as part of the U.S. Geological Survey's Conterminous United States Mineral Assessment Program (CUSMAP). These investigations included geologic mapping, geochemical surveys, gravity and aeromagnetic surveys, examinations of mineral deposits, and specialized geochronologic and remote-sensing studies. The data collected during these studies were compiled, combined with available published and unpublished data, analyzed, and used in a mineral-resource assessment of the quadrangle. The results, including data, interpretations, and mineral-resource assessments for nine types of mineral deposits, are published separately as a folio of maps. These maps are accompanied by figures, tables, and explanatory text. This circular provides background information on the Butte quadrangle, summarizes the studies and published maps, and lists a selected bibliography of references pertinent to the geology, geochemistry, geophysics, and mineral resources of the quadrangle. The Butte quadrangle, which includes the world-famous Butte mining district, has a long history of mineral production. Many mining districts within the quadrangle have produced large quantities of many commodities; the most important in dollar value of production were copper, gold, silver, lead, zinc, manganese, molybdenum, and phosphate. At present, mines at several locations produce copper, molybdenum, gold, silver, lead, zinc, and phosphate. Exploration, mainly for gold, has indicated the presence of other mineral deposits that may be exploited in the future. The results of the investigations by the U.S. Geological Survey indicate that many areas of the quadrangle are highly favorable for the occurrence of additional undiscovered resources of gold, silver, copper, molybdenum, tungsten, and other metals in several deposit types.

Circular↗

USGS2012

Thermal infrared (2.5-13.5 μm) spectroscopic remote sensing of igneous rock types on particulate planetary surfaces

Fundamental molecular vibration bands are significantly diminished by scattering. Thus such bands in spectra of fine particulate regoliths (i.e., dominated by <5-μm particles), or regoliths displaying a similar scale of porosity, are difficult to use for mineralogical or rock type identification. Consequently, other spectral features have been sought that may be more useful in spectroscopic remote sensing of composition. We find that mineralogical information is retained in overtones and combination tones of the fundamental molecular vibrations in the 3.0- to 7.0-μm region, but that relatively few minerals have a sufficiently distinctive band structure to be unambiguously identified with currently available techniques. More significantly, identification of general rock type, as defined by the SCFM chemical index (SCFM = SiO 2 /SiO 2 + CaO + FeO + MgO), is possible using spectral features associated with the principal Christiansen frequency and with a region of relative transparency between the Si-O stretching and bending bands. However, environmental factors may affect the appearance and wavelengths of these features. Finally, prominent absorption bands may result from the presence of relatively small amounts of water, hydroxyl or carbonate, because absorption bands exhibited by these materials in the 2.7- to 4.0-μm region, where silicate spectra are otherwise featureless, increase strongly in spectral contrast with decreasing particle size. Such materials are thus detectable in very small amounts in a particulate regolith composed predominantly of silicate minerals.

Journal of Geophysical Research↗