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At least 451 records · Page 25Linked to original sources
USGS2022

Surface parameters and bedrock properties covary across a mountainous watershed: Insights from machine learning and geophysics

Bedrock property quantification is critical for predicting the hydrological response of watersheds to climate disturbances. Estimating bedrock hydraulic properties over watershed scales is inherently difficult, particularly in fracture-dominated regions. Our analysis tests the covariability of above- and belowground features on a watershed scale, by linking borehole geophysical data, near-surface geophysics, and remote sensing data. We use machine learning to quantify the relationships between bedrock geophysical/hydrological properties and geomorphological/vegetation indices and show that machine learning relationships can estimate most of their covariability. Although we can predict the electrical resistivity variation across the watershed, regions of lower variability in the input parameters are shown to provide better estimates, indicating a limitation of commonly applied geomorphological models. Our results emphasize that such an integrated approach can be used to derive detailed bedrock characteristics, allowing for identification of small-scale variations across an entire watershed that may be critical to assess the impact of disturbances on hydrological systems.

Colorado↗
USGS1983

Norwegian remote sensing experiment in a marginal ice zone

The Norwegian Remote Sensing Experiment in the marginal ice zone north of Svalbard took place in fall 1979. Coordinated passive and active microwave measurements were obtained from shipborne, airborne, and satellite instruments together with in situ observations. The obtained spectra of emissivity (frequency range, 5 to 100 gigahertz) should improve identification of ice types and estimates of ice concentration. Mesoscale features along the ice edge were revealed by a 1.215-gigahertz synthetic aperture radar. Ice edge location by the Nimbus 7 scanning multichannel microwave radiometer was shown to be accurate to within 10 kilometers.

Svalbard↗
USGS1987

Remote sensing of the Fram Strait marginal ice zone

Sequential remote sensing images of the Fram Strait marginal ice zone played a key role in elucidating the complex interactions of the atmosphere, ocean, and sea ice. Analysis of a subset of these images covering a 1-week period provided quantitative data on the mesoscale ice morphology, including ice edge positions, ice concentrations, floe size distribution, and ice kinematics. The analysis showed that, under light to moderate wind conditions, the morphology of the marginal ice zone reflects the underlying ocean circulation. High-resolution radar observations showed the location and size of ocean eddies near the ice edge. Ice kinematics from sequential radar images revealed an ocean eddy beneath the interior pack ice that was verified by in situ oceanographic measurements.

Science↗
USGS2021

Evaluation of remote mapping techniques for earthquake-triggered landslide inventories in an urban subarctic environment: A case study of the 2018 Anchorage, Alaska Earthquake

Earthquake-induced landslide inventories can be generated using field observations but doing so can be challenging if the affected landscape is large or inaccessible after an earthquake. Remote sensing data can be used to help overcome these limitations. The effectiveness of remotely sensed data to produce landslide inventories, however, is dependent on a variety of factors, such as the extent of coverage, timing, and data quality, as well as environmental factors such as atmospheric interference (e.g., clouds, water vapor) or snow and vegetation cover. With these challenges in mind, we use a combination of field observations and remote sensing data from multispectral, light detection and ranging (lidar), and synthetic aperture radar (SAR) sensors to produce a ground failure inventory for the urban areas affected by the 2018 magnitude (M w ) 7.1 Anchorage, Alaska earthquake. The earthquake occurred during late November at high latitude (∼61°N), and the lack of sunlight, persistent cloud cover, and snow cover that occurred after the earthquake made remote mapping challenging for this event. Despite these challenges, 43 landslides were manually mapped and classified using a combination of the datasets mentioned previously. Using this manually compiled inventory, we investigate the individual performance and reliability of three remote sensing techniques in this environment not typically hospitable to remotely sensed mapping. We found that differencing pre- and post-event normalized difference vegetation index maps and lidar worked best for identifying soil slumps and rapid soil flows, but not as well for small soil slides, soil block slides and rock falls. The SAR-based methods did not work well for identifying any landslide types because of high noise levels likely related to snow. Some landslides, especially those that resulted in minor surface displacement, were identifiable only from the field observations. This work highlights the importance of the rapid collection of field observations and provides guidance for future mappers on which techniques, or combination of techniques, will be most effective at remotely mapping landslides in a subarctic and urban environment.

Alaska↗
USGS2021

A new remote sensing-based Carbon Sequestration Potential Index (CSPI): A tool to support land carbon management

Integrating remote sensing into assessments of carbon stocks and fluxes has advanced our understanding of how global change affects landscapes and our capacity to support decision making about forest management. However, there remains a lack of detailed and actionable analyses conducted across widely ranging environmental conditions that are appropriate for tactical planning. We used airborne laser scanning data and multi-source satellite imagery to estimate forest aboveground carbon density and gross primary production, and to map forest cover across the main Hawaiian Islands. We used these measures to develop the Carbon Sequestration Potential Index (CSPI), which identifies where the potential for carbon sequestration following afforestation would be highest within a complex landscape of 304 management units. Variation in CSPI was high across islands and between ecosystems, with low values for cool, dry and largely intact forest systems and high values for warm, wet and largely non-forested systems. The CSPI provided a rapid, spatially-explicit and actionable assessment of Hawaiian forest reserves, which can help stewardship agencies contribute to state carbon neutrality goals through climate-smart and science-driven prescriptions that encompass conservation to restoration.

Hawaii↗
USGS2023

Large increases in methane emissions expected from North America’s largest wetland complex

Natural methane (CH 4 ) emissions from aquatic ecosystems may rise because of human-induced climate warming, although the magnitude of increase is highly uncertain. Using an exceptionally large CH 4 flux dataset (~19,000 chamber measurements) and remotely sensed information, we modeled plot- and landscape-scale wetland CH 4 emissions from the Prairie Pothole Region (PPR), North America’s largest wetland complex. Plot-scale CH 4 emissions were driven by hydrology, temperature, vegetation, and wetland size. Historically, landscape-scale PPR wetland CH 4 emissions were largely dependent on total wetland extent. However, regardless of future wetland extent, PPR CH 4 emissions are predicted to increase by two- or threefold by 2100 under moderate or severe warming scenarios, respectively. Our findings suggest that international efforts to decrease atmospheric CH 4 concentrations should jointly account for anthropogenic and natural emissions to maintain climate mitigation targets to the end of the century.

North Dakota↗
USGS1987

Bedform alignment in directionally varying flows

Many kinds of sediment bedforms are presumed to trend either normal or parallel to the direction of sediment transport. For this reason, the trend of bedforms observed by remote sensing or by field observations is commonly used as an indicator of the direction of sediment transport. Such presumptions regarding bedform trend were tested experimentally in bidirectional flows by rotating a sand-covered board in steady winds. Transverse, oblique, and longitudinal bedforms were created by changing only two parameters: the angle between the two winds and the proportions of sand transported in the two directions. Regardless of whether the experimental bedforms were transverse, oblique, or longitudinal (as defined by the bedform trend relative to the resultant transport direction), they all had trends that yielded the maximum gross transport across the bedforms. The fact that many of the experimental bedforms were neither transverse nor parallel to the resultant transport direction suggests that transport directions cannot be accurately determined by presuming such alignment.

Science↗
USGS2018

Short-term forecasting and detection of explosions during the 2016–2017 eruption of Bogoslof volcano, Alaska

We describe a multidisciplinary approach to forecast, rapidly detect, and characterize explosive events during the 2016–2017 eruption of Bogoslof volcano, a back-arc shallow submarine volcano in Alaska’s Aleutian arc. The eruptive sequence began in December 2016 and included about 70 discrete explosive events. Because the volcano has no local monitoring stations, we used distant stations on the nearest volcanoes, Okmok (54 km) and Makushin (72 km), combined with regional infrasound sensors and lightning detection from the Worldwide Lightning Location Network (WWLLN). Pre-eruptive seismicity was detected for 12 events during the first half of the eruption; for all other events co-eruptive signals allowed for detection only. Monitoring of activity used a combination of scheduled checks combined with automated alarms. Alarms triggered on real-time data included real-time seismic amplitude measurement (RSAM); infrasound from several arrays, the closest being on Okmok; and lightning strokes detected from WWLLN within a 20-km radius of the volcano. During periods of unrest, a multidisciplinary response team of four people fulfilled specific roles to evaluate geophysical and remote-sensing data, run event-specific ash-cloud dispersion models, ensure interagency coordination, and develop and distribute of formalized warning products. Using this approach, for events that produced ash clouds ≥7.5 km above sea level, Alaska Volcano Observatory (AVO) called emergency response partners 15 min, and issued written notices 30 min, after event onset (mean times). Factors that affect timeliness of written warnings include event size and number of data streams available; bigger events and more data both decrease uncertainty and allow for faster warnings. In remote areas where airborne ash is the primary hazard, the approach used at Bogoslof is an effective strategy for hazard mitigation.

Alaska↗
USGS2018

Connectivity of streams and wetlands to downstream waters: An integrated systems framework

Interest in connectivity has increased in the aquatic sciences, partly because of its relevance to the Clean Water Act. This paper has two objectives: (1) provide a framework to understand hydrological, chemical, and biological connectivity, focusing on how headwater streams and wetlands connect to and contribute to rivers; and (2) briefly review methods to quantify hydrological and chemical connectivity. Streams and wetlands affect river structure and function by altering material and biological fluxes to the river; this depends on two factors: (1) functions within streams and wetlands that affect material fluxes; and (2) connectivity (or isolation) from streams and wetlands to rivers that allows (or prevents) material transport between systems. Connectivity can be described in terms of frequency, magnitude, duration, timing, and rate of change. It results from physical characteristics of a system, e.g., climate, soils, geology, topography, and the spatial distribution of aquatic components. Biological connectivity is also affected by traits and behavior of the biota. Connectivity can be altered by human impacts, often in complex ways. Because of variability in these factors, connectivity is not constant but varies over time and space. Connectivity can be quantified with field‐based methods, modeling, and remote sensing. Further studies using these methods are needed to classify and quantify connectivity of aquatic ecosystems and to understand how impacts affect connectivity.

Journal of the American Water Resources Associatio↗
USGS2000

Orbital radar studies of paleodrainages in the central Namib Desert

Orbital radar images of the central Namib Desert show clearly the extent of relict fluvial deposits associated with former courses of the Tsondab and Kuiseb rivers. South of the Kuiseb River, radar data show the existence of a drainage network developed in calcrete-cemented late Tertiary fluvial deposits. The sand-filled paleovalleys are imaged as radar-dark tones in contrast to the radar-bright interfluves where the calcreted gravels occur. The drainage network developed as a result of local runoff from indurated gravels and channeled surface and subsurface flow to the sites of the many interdune lacustrine deposits found in the area. (C) Elsevier Science Inc., 2000.Orbital radar images of the central Namib Desert show clearly the extent of relict fluvial deposits associated with former courses of the Tsondab and Kuiseb rivers. South of the Kuiseb River, radar data show the existence of a drainage network developed in calcrete-cemented late Tertiary fluvial deposits. The sand-filled paleovalleys are imaged as radar-dark tones in contrast to the radar-bright interfluves where the calcreted gravels occur. The drainage network developed as a result of local runoff from indurated gravels and channeled surface and subsurface flow to the sites of the many interdune lacustrine deposits found in the area.

Remote Sensing of Environment↗
USGS2017

Optical and biochemical properties of a southwest Florida whiting event

“Whiting” in oceanography is a term used to describe a sharply defined patch of water that contains high levels of suspended, fine-grained calcium carbonate (CaCO 3 ). Whitings have been reported in many oceanic and lake environments, and recently have been reported in southwest Florida coastal waters. Here, field and laboratory measurements were used to study optical, biological, and chemical properties of whiting waters off southwest Florida. No significant difference was found in chlorophyll a concentrations between whiting and outside waters (non-whiting water), but average particle backscattering coefficients in whiting waters were double those in outside waters, and remote sensing reflectance in whiting waters was higher at all wavelengths (400–700 nm). While other potential causes cannot be completely ruled out, particle composition and biochemical differences between sampled whiting water, contiguous water, and outside water indicate a biologically precipitated mode of whiting formation. Taxonomic examination of marine phytoplankton samples collected during a whiting event revealed a community dominated by autotrophic picoplankton and a small (<10 μm), centric diatom species, identified as Thalassiosira sp. through the use of scanning electron microscopy. Amorphous to fully formed crystals of CaCO 3 were observed along the girdle bands of Thalassiosira sp. cells and autotrophic picoplankton cells. Although carbonate parameters differed from whiting and contiguous to outside water, more sampling is needed to determine if these results are statistically significant.

Florida↗
USGS2013

MODIS phenology image service ArcMap toolbox

Seasonal change is important to consider when managing conservation areas at landscape scales. The study of such patterns throughout the year is referred to as phenology. Recurring life-cycle events that are initiated and driven by environmental factors include animal migration and plant flowering. Phenological events capture public attention, such as fall color change in deciduous forests, the first flowering in spring, and for those with allergies, the start of the pollen season. These events can affect our daily lives, provide clues to help understand and manage ecosystems, and provide evidence of how climate variability can affect the natural cycle of plants and animals. Phenological observations can be gathered at a range of scales, from plots smaller than an acre to landscapes of hundreds to thousands of acres. Linking these observations to diverse disciplines such as evolutionary biology or climate sciences can help further research in species and ecosystem responses to climate change scenarios at appropriate scales. A cooperative study between the National Park Service (NPS), the U.S. Geological Survey (USGS), and the National Aeronautics and Space Administration (NASA) has been exploring how satellite information can be used to summarize phenological patterns observed at the park or landscape scale and how those summaries can be presented to both park managers and visitors. This study specifically addressed seasonal changes in plants, including the onset of growth, photosynthesis in the spring, and the senescence of deciduous vegetation in the fall. The primary objective of the work is to demonstrate that seasonality even in protected areas changes considerably across years. A major challenge is to decouple natural variability from possible trends—directional change that can lead to a permanent and radically different ecosystem state. Trends can be either a gradual degradation of the landscape (often from external influences) or steady improvement (by implementing long-term conservation plans). In either case, it is important to first grasp the magnitude of natural variation so that it is not confused with actual trends. This work used existing and freely available remote sensing data, specifically the NASA-funded 250-meter (m) spatial resolution land-surface phenology product for North America. This product is calculated from an annual record of vegetation health observed by NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. The land-surface phenology product is, in essence, a method to summarize all the observations throughout a year into a few key, ecologically relevant “metrics”.

Open-File Report↗
USGS2005

Initial results of rover localization and topographic mapping for the 2003 mars exploration rover mission

This paper presents the initial results of lander and rover localization and topographic mapping of the MER 2003 mission (by Sol 225 for Spirit and Sol 206 for Opportunity). The Spirit rover has traversed a distance of 3.2 km (actual distance traveled instead of odometry) and Opportunity at 1.2 km. We localized the landers in the Gusev Crater and on the Meridiani Planum using two-way Doppler radio positioning technology and cartographic triangulations through landmarks visible in both orbital and ground images. Additional high-resolution orbital images were taken to verify the determined lander positions. Visual odometry and bundle-adjustment technologies were applied to overcome wheel slippages, azimuthal angle drift and other navigation errors (as large as 21 percent). We generated timely topographic products including 68 orthophoto maps and 3D Digital Terrain Models, eight horizontal rover traverse maps, vertical traverse profiles up to Sol 214 for Spirit and Sol 62 for Opportunity, and five 3D crater models. A web-based landing-site Geographic Information System (GIS) has been set up at The Ohio State University to update and disseminate the daily localization and topographic information to support tactical and strategic operations of the mission. Also described in this paper are applications of the data for science operations planning, geological traverse survey, survey of wind-related features, and other science applications. The majority of the instruments onboard both rovers are healthy at this moment, and they will continue to explore the two landing sites on the Martian surface. We expect to report further localization and topographic mapping results to be achieved in the rest of the mission period and in post-mission data processing.

Photogrammetric Engineering and Remote Sensing↗
USGS2013

A GIS and statistical approach to identify variables that control water quality in hydrothermally altered and mineralized watersheds, Silverton, Colorado, USA

Hydrothermally altered bedrock in the Silverton mining area, southwest Colorado, USA, contains sulfide minerals that weather to produce acidic and metal-rich leachate that is toxic to aquatic life. This study utilized a geographic information system (GIS) and statistical approach to identify watershed-scale geologic variables in the Silverton area that influence water quality. GIS analysis of mineral maps produced using remote sensing datasets including Landsat Thematic Mapper, advanced spaceborne thermal emission and reflection radiometer, and a hybrid airborne visible infrared imaging spectrometer and field-based product enabled areas of alteration to be quantified. Correlations between water quality signatures determined at watershed outlets, and alteration types intersecting both total watershed areas and GIS-buffered areas along streams were tested using linear regression analysis. Despite remote sensing datasets having varying watershed area coverage due to vegetation cover and differing mineral mapping capabilities, each dataset was useful for delineating acid-generating bedrock. Areas of quartz–sericite–pyrite mapped by AVIRIS have the highest correlations with acidic surface water and elevated iron and aluminum concentrations. Alkalinity was only correlated with area of acid neutralizing, propylitically altered bedrock containing calcite and chlorite mapped by AVIRIS. Total watershed area of acid-generating bedrock is more significantly correlated with acidic and metal-rich surface water when compared with acid-generating bedrock intersected by GIS-buffered areas along streams. This methodology could be useful in assessing the possible effects that alteration type area has in either generating or neutralizing acidity in unmined watersheds and in areas where new mining is planned.

Colorado↗
USGS2021

DLR Earth Sensing Imaging Spectrometer (DESIS) level 1 product evaluation using RadCalNet measurements

The DLR Earth Sensing Imaging Spectrometer (DESIS) is the first hyperspectral imaging spectrometer installed in the Multi-User System for Earth Sensing (MUSES) on the International Space Station (ISS) for acquiring routine science grade images from orbit. It was launched on 29 June 2018 and integrated into MUSES. DESIS measures energy in the spectral range of 400 to 1000 nm with high spatial and spectral resolution: 30 m and 2.55 nm, respectively. DESIS data should be sufficiently quantitative and accurate to use it for different applications and research. This work performs a radiometric evaluation of DESIS Level 1 product (Top of Atmosphere (TOA) reflectance) by comparing it with coincident Radiometric Calibration Network (RadCalNet) measurements at Railroad Valley Playa (RVUS), Gobabeb (GONA), and La Crau (LCFR). RVUS, GONA, and LCFR offer 4, 15, and 5 coincident datasets between DESIS and RadCalNet measurements, respectively. The results show an agreement between DESIS and RadCalNet TOA reflectance within ~5% for most spectral regions. However, there is an additional ~5% disagreement across the wavelengths affected by water vapor absorption and atmospheric scattering. Among the three RadCalNet sites, RVUS and GONA show a similar measurement disagreement with DESIS of ~5%, while LCFR differs by ~10%. Agreement between DESIS and RadCalNet measurements is variable across all three sites, likely due to surface type differences. DESIS and RadCalNet agreement show a precision of ~2.5%, 4%, and 7% at RVUS, GONA, and LCFR, respectively. RVUS and GONA, which have a similar surface type, sand, have a similar level of radiometric accuracy and precision, whereas LCFR, which consists of sparse vegetation, has lower accuracy and precision. The observed precision of DESIS Level 1 products from all the sites, especially LCFR, can be improved with a better Bidirectional Reflection Distribution Function (BRDF) characterization of the RadCalNet sites.

Remote Sensing↗
USGS2011

Field Reconnaissance Geologic Mapping of the Columbia Hills, Mars: Results from MER Spirit and MRO HiRISE Observations

Chemical, mineralogic, and lithologic ground truth was acquired for the first time on Mars in terrain units mapped using orbital Mars Reconnaissance Orbiter's High Resolution Imaging Science Experiment (MRO HiRISE) image data. Examination of several dozen outcrops shows that Mars is geologically complex at meter length scales, the record of its geologic history is well exposed, stratigraphic units may be identified and correlated across significant areas on the ground, and outcrops and geologic relationships between materials may be analyzed with techniques commonly employed in terrestrial field geology. Despite their burial during the course of Martian geologic time by widespread epiclastic materials, mobile fines, and fall deposits, the selective exhumation of deep and well-preserved geologic units has exposed undisturbed outcrops, stratigraphic sections, and structural information much as they are preserved and exposed on Earth. A rich geologic record awaits skilled future field investigators on Mars. The correlation of ground observations and orbital images enables construction of a corresponding geologic reconnaissance map. Most of the outcrops visited are interpreted to be pyroclastic, impactite, and epiclastic deposits overlying an unexposed substrate, probably related to a modified Gusev crater central peak. Fluids have altered chemistry and mineralogy of these protoliths in degrees that vary substantially within the same map unit. Examination of the rocks exposed above and below the major unconformity between the plains lavas and the Columbia Hills directly confirms the general conclusion from remote sensing in previous studies over past years that the early history of Mars was a time of more intense deposition and modification of the surface. Although the availability of fluids and the chemical and mineral activity declined from this early period, significant later volcanism and fluid convection enabled additional, if localized, chemical activity.

Journal of Geophysical Research E: Planets↗
USGS2025

A method to obtain remotely sensed grain size distributions from nonplanar granular deposits

Constraining the grain size distribution of granular deposits with complex surfaces is difficult with existing approaches. Field and laboratory techniques are time consuming and limited by the maximum grain size that laboratories can accommodate. In this study, we present a new method to identify the coarse fraction of the grain size distribution at a debris-flow fan deposit surveyed with terrestrial laser scanning (TLS) in Glenwood Canyon, Colorado, USA. This method is a novel grain segmentation algorithm developed for application to point cloud data of deposits with complex surfaces and angular grains ranging in size from centimeters to a meter. This approach combines an existing random forest machine learning method with a novel iterative clustering algorithm. We compared the grain size distribution from our algorithm with a Wolman pebble count conducted in the field, and found a root mean squared error of less than 2 cm from the 5th to 95th percentile of the grain size distribution of grains ranging from cobble to boulder sized (6.3–78 cm in our application). Finally, we compared our new algorithm with an existing open-source grain segregation algorithm, and our method outperformed the selected alternative when applied to the debris-flow deposit point cloud.

Colorado↗
USGS2020

A novel approach for next generation water use mapping using Landsat and Sentinel-2 satellite data

Evapotranspiration (ET) is needed in a range of applications in hydrology, climatology, ecology, and agriculture. Remote sensing-based estimation is the only viable and economical method for ET estimation over large areas. The current Landsat satellites provide images every 16 days limiting the ability to capture biophysical changes affecting ET. Thus, we explored the potential integration of Landsat 8 and Sentinel-2 data for estimating ET using a surface energy balance model. The results indicate the proposed Landsat-Sentinel data fusion approach substantially reduced relative errors from 48% to 10% on area-wide and from 49% to 17% on pixel-wide compared to linear interpolation between two Landsat images. The proposed approach had a better agreement with expected actual ET maps across high-vegetation conditions than in low-vegetation conditions. The finer temporal resolution and better accuracy of ET maps based on Landsat-Sentinel integration is of great importance in managing limited water resources.

Arizona, California↗