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At least 523 records · Page 29Linked to original sources
USGS2006

Remote sensing studies of the Dionysius region of the Moon

The Dionysius region is located near the western edge of Mare Tranquillitatis and is centered on Dionysius crater, which exhibits a well-developed dark ray system. Proposed origins for these dark rays included impact melt deposits and dark primary ejecta. The region also contains extensive deposits of Cayley-type light plains. Clementine multispectral images and a variety of spacecraft photography were utilized to investigate the composition and origin of geologic units in the Dionysius region. The portions of the dark rays for which spectral and chemical data were obtained are composed of mare debris contaminated with minor amounts of highland material. Both five-point spectra and values of the optical maturity (OMAT) parameter indicate that the dark rays are dominated by mare basalts, not glassy impact melts. The high-albedo rays associated with Dionysius exhibit FeO and TiO2 values that are lower than those of the adjacent dark ray surfaces and OMAT values that indicate that bright ray surfaces are not fully mature. The high-albedo rays are bright largely because of the contrast in albedo between ray material containing highlands-rich ejecta and the adjacent mare-rich surfaces. The mafic debris ejected by Dionysius was derived from a dark, iron-rich unit exposed high on the inner wall of the crater. This layer probably represents a mare deposit that was present at the surface of the preimpact target site. With one possible exception, there is no evidence for buried mare basalts associated with Cayley plains in the region.

Journal of Geophysical Research E: Planets↗
USGS2019

Thermal, deformation, and degassing remote sensing time-series (A.D. 2000-2017) at the 47 most active volcanoes in Latin America: Implications for volcanic systems

Volcanoes are hazardous to local and global populations, but only a fraction are continuously monitored by ground-based sensors. For example, in Latin America, more than 60% of Holocene volcanoes are unmonitored, meaning long-term multi-parameter datasets of volcanic activity are rare and sparse. We use satellite observations of degassing, thermal anomalies, and surface deformation spanning 17 years at 47 of the most active volcanoes in Latin America, and compare these datasets to ground-based observations archived by the Global Volcanism Program (GVP). This first comparison of multi-satellite time-series on a regional scale provides information regarding volcanic behavior during, non-, pre-, syn- and post-eruptive periods. For example, at Copahue volcano, deviations from background activity in all three types of satellite measurements were manifested months to years in advance of renewed eruptive activity in 2012. By quantifying the amount of degassing, thermal output, and deformation measured at each of these volcanoes, we test the classification of these volcanoes as open or closed volcanic systems. We find that ~28% of the volcanoes do not fall into either classification and the rest show elements of both, demonstrating a dynamic range of behavior that can change over time. Finally, we recommend how volcano monitoring could be improved through better coordination of available satellite-based capabilities and new instruments.

Journal of Geophysical Research↗
USGS2024

Remote sensing large-wood storage downstream of reservoirs during and after dam removal: Elwha River, Washington, USA

Large wood is an integral part of many rivers, often defining river-corridor morphology and habitat, but its occurrence, magnitude, and evolution in a river system are much less well understood than the sedimentary and hydraulic components, and due to methodological limitations, have seldom previously been mapped in substantial detail. We present a new method for this, representing a substantial advance in automated deep-learning-based image segmentation. From these maps, we measured large wood and sediment deposits from high-resolution orthoimages to explore the dynamics of large wood in two reaches of the Elwha River, Washington, USA, between 2012 and 2017 as it adjusted to upstream dam removals. The data set consists of a time series of orthoimages (12.5-cm resolution) constructed using Structure-from-Motion photogrammetry on imagery from 14 aerial surveys. Model training was optimized to yield maximum accuracy for estimated wood areas, compared to manually digitized wood, therefore model development and intended application were coupled. These fully reproducible methods and model resulted in a maximum of 15% error between observed and estimated total wood areas and wood deposit size-distributions over the full spatio-temporal extent of the data. Areal extent of wood in the channel margin approximately doubled in the years following dam removal, with greatest increases in large wood in wider, lower-gradient sections. Large-wood deposition increased between the start of dam removal (2011) and winter 2013, then plateaued. Sediment bars continued to grow up until 2016/17, assisted by a partially static wood framework deposited predominantly during the period up to winter 2013.

Washington↗
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↗
USGS2025

Remote sensing of river discharge based on critical flow theory

Critical flow theory provides a physical foundation for inferring discharge from measurements of wavelength and channel width made from images. In rivers with hydraulically steep local slopes greater than ∼0.01, flow velocities are high and the Froude number F r (ratio of inertial to gravitational forces) can approach 1.0 (critical flow) or greater. Under these conditions, undular hydraulic jumps (UHJ's) can form as standing wave trains at slope transitions or constrictions. The presence of UHJ's indicates that mean F r ≈ 1, implying that the velocity and depth of the flow and the spacing of the waves are uniquely related to one another. Discharges estimated from 82 Google Earth images agreed closely with discharges recorded at gaging stations ( R 2 = 0.98), with a mean bias of 1% ± 11%. This approach could provide reliable discharge information in many fluvial environments where critical flow occurs, which tend to be underrepresented in gage networks

Geophysical Research Letters↗
USGS2012

Surface coating effects in remote sensing measurements

Measurements of the infrared spectra of a liquid-(water) coated quartz substrate and a solid-(pyrophyllite) coated quartzite are compared to theoretical values. Results demonstrate that in the case of the water-coated quartz, a loss in spectral contrast of the quartz emission occurs at the principal restrahlen wavelengths of 8.5, 9.0, and 12.5 µ but is most pronounced at 12.5 µ. In the case of pyrophyllite-coated quartzite, additional spectral features appear between 8.0 and 10.0 µ as the exposure of quartzite through the pyrophyllite coating is increased. Addition of the pure quartzite and pyrophyllite spectra, weighted by exposed area, is shown to satisfactorily describe the composite spectra.

Journal of Geophysical Research↗
USGS2001

A new global 1-km dataset of percentage tree cover derived from remote sensing

Accurate assessment of the spatial extent of forest cover is a crucial requirement for quantifying the sources and sinks of carbon from the terrestrial biosphere. In the more immediate context of the United Nations Framework Convention on Climate Change, implementation of the Kyoto Protocol calls for estimates of carbon stocks for a baseline year as well as for subsequent years. Data sources from country level statistics and other ground-based information are based on varying definitions of 'forest' and are consequently problematic for obtaining spatially and temporally consistent carbon stock estimates. By combining two datasets previously derived from the Advanced Very High Resolution Radiometer (AVHRR) at 1 km spatial resolution, we have generated a prototype global map depicting percentage tree cover and associated proportions of trees with different leaf longevity (evergreen and deciduous) and leaf type (broadleaf and needleleaf). The product is intended for use in terrestrial carbon cycle models, in conjunction with other spatial datasets such as climate and soil type, to obtain more consistent and reliable estimates of carbon stocks. The percentage tree cover dataset is available through the Global Land Cover Facility at the University of Maryland at http://glcf.umiacs.umd.edu.

Global Change Biology↗
USGS2012

Integrating field research, modeling and remote sensing to quantify morphodynamics in a high-energy coastal setting, ocean beach, San Francisco, California

Wave and coastal circulation modeling are combined with multibeam bathymetry, high-resolution beach surveys, cross-shore Personal Water Craft surveys, digital bed sediment camera surveys, and real-time video monitoring to quantify morphological change and nearshore processes at Ocean Beach, San Francisco. Initial SWAN (Simulating Waves Nearshore) wave modeling results show a focusing of wave energy at the location of an erosion hot spot on the southern end of Ocean Beach during prevailing northwest swell conditions. During El Nin??o winters, swell out of the west and southwest dominates the region, and although the wave energy is focused further to the north on Ocean Beach, the oblique wave approach sets up a strong northerly littoral drift, thereby starving the southern end of sediment, leaving it increasingly vulnerable to wave attack when the persistent northwest swell returns. An accurate assessment of the interaction between wave and tidal processes is crucial for evaluating coastal management options in an area that includes the annual dredging and disposal of ship channel sediment and an erosion hot spot that is posing a threat to local infrastructure. Copyright ASCE 2006.

Conference Paper↗
USGS2007

Analysis of Alaskan burn severity patterns using remotely sensed data

Wildland fire is the dominant large-scale disturbance mechanism in the Alaskan boreal forest, and it strongly influences forest structure and function. In this research, patterns of burn severity in the Alaskan boreal forest are characterised using 24 fires. First, the relationship between burn severity and area burned is quantified using a linear regression. Second, the spatial correlation of burn severity as a function of topography is modelled using a variogram analysis. Finally, the relationship between vegetation type and spatial patterns of burn severity is quantified using linear models where variograms account for spatial correlation. These results show that: 1) average burn severity increases with the natural logarithm of the area of the wildfire, 2) burn severity is more variable in topographically complex landscapes than in flat landscapes, and 3) there is a significant relationship between burn severity and vegetation type in flat landscapes but not in topographically complex landscapes. These results strengthen the argument that differential flammability of vegetation exists in some boreal landscapes of Alaska. Additionally, these results suggest that through feedbacks between vegetation and burn severity, the distribution of forest vegetation through time is likely more stable in flat terrain than it is in areas with more complex topography. ?? IAWF 2007.

International Journal of Wildland Fire↗
USGS1996

Remote sensing of forest fire severity and vegetation recovery

Burned forested areas have patterns of varying burn severity as a consequence of various topographic, vegetation, and meteorological factors. These patterns are detected and mapped using satellite data. Other ecological information can be abstracted from satellite data regarding rates of recovery of vegetation foliage and variation of burn severity on different vegetation types. Middle infrared wavelengths are useful for burn severity mapping because the land cover changes associated with burning increase reflectance in this part of the electromagnetic spectrum. Simple stratification of Landsat Thematic Mapper data define varying classes of burn severity because of changes in canopy cover, biomass removal, and soil chemical composition. Reasonable maps of burn severity are produced when the class limits of burn severity reflectance are applied to the entire satellite data. Changes in satellite reflectance over multiple years reveal the dynamics of vegetation and fire severity as low burn areas have lower changes in reflectance relative to high burn areas. This results as a consequence of how much the site was altered due to the burn and how much space is available for vegetation recovery. Analysis of change in reflectance across steppe, riparian, and forested vegetation types indicate that fires potentially increase biomass in steppe areas, while riparian and forested areas are slower to regrow to pre-fire conditions. This satellite-based technology is useful for mapping severely burned areas by exploring the ecological manifestations before and after fire.

International Journal of Wildland Fire↗
USGS2008

Humid tropical forest clearing from 2000 to 2005 quantified by using multitemporal and multiresolution remotely sensed data

Forest cover is an important input variable for assessing changes to carbon stocks, climate and hydrological systems, biodiversity richness, and other sustainability science disciplines. Despite incremental improvements in our ability to quantify rates of forest clearing, there is still no definitive understanding on global trends. Without timely and accurate forest monitoring methods, policy responses will be uninformed concerning the most basic facts of forest cover change. Results of a feasible and cost-effective monitoring strategy are presented that enable timely, precise, and internally consistent estimates of forest clearing within the humid tropics. A probability-based sampling approach that synergistically employs low and high spatial resolution satellite datasets was used to quantify humid tropical forest clearing from 2000 to 2005. Forest clearing is estimated to be 1.39% (SE 0.084%) of the total biome area. This translates to an estimated forest area cleared of 27.2 million hectares (SE 2.28 million hectares), and represents a 2.36% reduction in area of humid tropical forest. Fifty-five percent of total biome clearing occurs within only 6% of the biome area, emphasizing the presence of forest clearing “hotspots.” Forest loss in Brazil accounts for 47.8% of total biome clearing, nearly four times that of the next highest country, Indonesia, which accounts for 12.8%. Over three-fifths of clearing occurs in Latin America and over one-third in Asia. Africa contributes 5.4% to the estimated loss of humid tropical forest cover, reflecting the absence of current agro-industrial scale clearing in humid tropical Africa.

Proceedings of the National Academy of Sciences of↗
USGS2011

Using remote sensing and imagery exploitation to monitor the dynamics of East Timbalier Island, LA: 2000-2010

In 1999, the National Oceanic and Atmospheric Administration-National Marine Fisheries Service and the State of Louisiana jointly undertook the restoration of East Timbalier, a barrier island along a sediment-starved portion of the Gulf of Mexico coast of Louisiana. High-resolution overhead imagery was used to monitor the course of this restoration effort. This article describes the changes in area and movement of East Timbalier Island and compares these changes with the previous measurements. Between 2000 and 2010, East Timbalier Island lost 52–66% of its area and moved northwards 12–105 m/year. The area of East Timbalier Island is less today than at any time since 1887. Understanding of the physical processes in nature that control the size, shape and movement of the island, as well as the human impacts that have hastened its degradation, is critical for accomplishing any future restoration.

Louisiana↗
USGS1996

Grassland canopy parameters and their relationships to remotely sensed vegetation indices in the Nebraska Sand Hills

Relationships among spectral vegetation indices and grassland biophysical parameters including the effects of varying levels of standing dead vegetation, range sites, and range plant communities were examined. Range plant communities consisting of northern mixed grass prairie and a smooth brome field as well as range sites and management in a Sand Hills bluestem prairie were sampled with a ground radiometer and for LAI, biomass, chlorophy]] and nitrogen amounts. Live above ground (herbaceous and shrub leaf) biomass quadrat estimates in early June, 1994, ranged from a mean value of 35,9 g/m 2 in the burned area to 128.0 g/m 2 in the mixed grass prairie. Shrubs, when present, had a stronger effect on the ground radiometer NDVI and MSAVI relationships with live biomass than either standing dead vegetation or plant community composition. Predictive relationships for live biomass from ground radiometer spectral data allowed rapid nondestructive estimation of live biomass for eleven 30 m by 30 m plots. Strong (r 2 ‐ 0.81 to 0.87) predictive relationships for live biomass and SPOT vegetation indices at the 30 m by 30 m scale were developed and applied to estimate live biomass for entire site areas.

Geocarto International↗
USGS2008

Integrating modelling and remote sensing to identify ecosystem performance anomalies in the boreal forest, Yukon River Basin, Alaska

High-latitude ecosystems are exposed to more pronounced warming effects than other parts of the globe. We develop a technique to monitor ecological changes in a way that distinguishes climate influences from disturbances. In this study, we account for climatic influences on Alaskan boreal forest performance with a data-driven model. We defined ecosystem performance anomalies (EPA) using the residuals of the model and made annual maps of EPA. Most areas (88%) did not have anomalous ecosystem performance for at least 6 of 8 years between 1996 and 2004. Areas with underperforming EPA (10%) often indicate areas associated with recent fires and areas of possible insect infestation or drying soil related to permafrost degradation. Overperforming areas (2%) occurred in older fire recovery areas where increased deciduous vegetation components are expected. The EPA measure was validated with composite burn index data and Landsat vegetation indices near and within burned areas.

International Journal of Digital Earth↗
USGS2018

A decade of remotely sensed observations highlight complex processes linked to coastal permafrost bluff erosion in the Arctic

Eroding permafrost coasts are indicators and integrators of changes in the Arctic System as they are susceptible to the combined effects of declining sea ice extent, increases in open water duration, more frequent and impactful storms, sea-level rise, and warming permafrost. However, few observation sites in the Arctic have yet to link decadal-scale erosion rates with changing environmental conditions due to temporal data gaps. This study increases the temporal fidelity of coastal permafrost bluff observations using near-annual high spatial resolution (<1 m) satellite imagery acquired between 2008 and 2017 for a 9-km segment of coastline at Drew Point, Beaufort Sea coast, Alaska. Our results show that mean annual erosion for the 2007 to 2016 decade was 17.2 m yr<sup>-1</sup>, which is 2.5 times faster than historic rates, indicating that bluff erosion at this site is likely responding to changes in the Arctic System. In spite of a sustained increase in decadal-scale mean annual erosion rates, mean open water season erosion varied from 6.7 m yr<sup>-1</sup> in 2010 to more than 22.0 m yr<sup>-1</sup> in 2007, 2012, and 2016. This variability provided a range of coastal responses through which we explored the different roles of potential environmental drivers. The lack of significant correlations between mean open water season erosion and the environmental variables compiled in this study indicates that we may not be adequately capturing the environmental forcing factors, that the system is conditioned by long-term transient effects or extreme weather events rather than annual variability, or that other not yet considered factors may be responsible for the increased erosion occurring at Drew Point. Our results highlight an increase in erosion at Drew Point in the 21st century as well as the complexities associated with unraveling the factors responsible for changing coastal permafrost bluffs in the Arctic.

Alaska↗
USGS2019

Investigating lake-area dynamics across a permafrost-thaw spectrum using airborne electromagnetic surveys and remote sensing time-series data in Yukon Flats, Alaska

Lakes in boreal lowlands cycle carbon and supply an important source of freshwater for wildlife and migratory waterfowl. The abundance and distribution of these lakes are supported, in part, by permafrost distribution, which is subject to change. Relationships between permafrost thaw and lake dynamics remain poorly known in most boreal regions. Here, new airborne electromagnetic (AEM) data collected during June 2010 and February 2016 were used to constrain deep permafrost distribution. AEM data were coupled with Landsat-derived lake surface-area data from 1979 through 2011 to inform temporal lake behavior changes in the 35 500- km 2 Yukon Flats ecoregion of Alaska. Together, over 1500 km of AEM data, and roughly 30 years of Landsat data were used to explore processes that drive lake dynamics across a variety of permafrost thaw states not possible in studies conducted with satellite imagery or field measurements alone. Clustered time-series data identified lakes with similar temporal dynamics. Clusters possessed similarities in lake permanence (i.e. ephemeral versus perennial), subsurface permafrost distribution, and proximity to rivers and streams. Of the clustered lakes, ~66% are inferred to have at least intermittent connectivity with other surface-water features, ~19% are inferred to have shallow subsurface connectivity to other surface water features that served as a low-pass filter for hydroclimatic fluctuations, and ~15% appear to be isolated by surrounding permafrost (i.e. no connectivity). Integrated analysis of AEM and Landsat data reveals a progression from relatively synchronous lake dynamics among disconnected lakes in the most spatially continuous, thick permafrost to quite high spatiotemporal heterogeneity in lake behavior among variably-connected lakes in regions with notably less continuous permafrost. Variability can be explained by the preferential development of thawed permeable gravel pathways for lateral water redistribution in this area. The general spatial progression in permafrost thaw state and lake area behavior may be extended to the temporal dimension. However, extensive permafrost thaw, beyond what is currently observed, is expected to promote ubiquitous subsurface connectivity, eventually evolving to a state of increased lake synchronicity.

Alaska↗