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At least 37 records · Page 2Linked to original sources
USGS2019

Monitoring, forecasting collapse events, and mapping pyroclastic deposits at Sinabung volcano with satellite imagery

During the ongoing (2013–present) eruption of Sinabung volcano, north Sumatra, we have routinely used a variety of satellite remote sensing data to observe and forecast lava dome and lava flow collapse events, to map the resulting pyroclastic deposits, and to estimate effusion rates. In this paper, we focus on the first two years of the current eruption (September 2013–December 2015), and we summarize major events in 2016. We divide the eruption into 5 major phases: 1) phreatomagmatic (July 2013–18 December 2013), 2) first dome growth and collapse (18 December 2013–10 January 2014), 3) lava-flow (10 January 2014–mid-September 2014), 4) second lava dome and collapse (mid-September 2014–July 2015), 5) lava dome collapse and ash explosion phase (August 2015–present). Throughout the eruption, remotely sensed information has been instrumental in assessing the stability of the lava dome and flow and to forecast collapse events that produce pyroclastic density currents (PDCs: block-and-ash flows, co-ignimbrite surges, and blasts). Forecasts based on remote sensing data in combination with seismic, geodetic and gas-monitoring data have also helped inform decisions related to alert levels and evacuations. Relatively unusual aspects of the Sinabung eruption include the transition from dome to flow morphology (phase 2 to phase 3 transition) and the frequent occurrence during phase 3 of collapses from the lava flow-front and flow-margins—collapses that produced extensive pyroclastic density currents. By analogy to the well-known “Merapi type” collapses and pyroclastic deposits, we propose that lava flow-front and flow-margin collapses with associated PDCs be known as “Sinabung type.” Although detailed study of deposits has not been possible due to continuing hazards, our observations suggest that the transition from lava dome to lava flow and the occurrence of flow-front and flow-margin collapses reflect a particular combination of lava viscosity and steepness of slope. Our observations also show clear evidence of at least one slope-parallel high-velocity and dilute PDC (a “blast”) that emanated from a lava-margin collapse site 500 m downslope from the vent. This 1 February 2014 blast downed and singed a forest out to at least 3.9 km from the collapse site and killed 16 people. We also use a combination of field and remotely sensed data to map the distribution of Sinabung deposits. We estimate eruptive volumes and extrusion rates by combining sequential measurements of lava surface and pyroclastic flow areas with thickness estimates derived from simple geometric assumptions, oblique photographs and Digital Elevation Models (DEMs) derived from remotely sensed data. Our estimates of short-term effusion rates vary widely on a daily to weekly basis, from <1 to >20 m 3 s −1 . In a few cases, periods of increased extrusion precede lava flow-front collapses by a few days to a week, suggesting delays in transmittance of effusion pulses as lava moves from vent to flow front. We find that, as of 1 January 2016, the total area of deposits is 10 7 m 2 , and their approximate deposit volume is about 0.3 km 3 , equivalent to 0.2 km 3 Dense Rock Equivalent (DRE). We anticipate that our deposit maps will be valuable in the future as a framework for the study of the magmatic and textural evolution of eruptive products through time.

Sinabung volcano↗
USGS2003

Assessment of forest fragmentation in southern New England using remote sensing and geographic information systems technology

Spatial patterns and rates of forest fragmentation were assessed using digital remote sensing data for a region in southern New England that included 157 townships in southern New Hampshire and northeastern Massachusetts. The study area has undergone marked population increases over the last several decades. Following classification of 1973 and 1988 Landsat Multispectral Scanner data into forest and nonforest classes, data were incorporated into a geographic information system. The natural logarithms of forest area to perimeter ratios, referred to as the forest continuity index, were used to assess patterns and trends of forest fragmentation across the region Forest continuity index values were extracted from each township for both data sets and compared with population data. Forest continuity index values were found to decrease with increasing population density until about 200 persons per square kilometer, after which the relationship stabilized. With slight population increases at low densities forest continuity index values declined sharply, implying abrupt increases in forest fragmentation. Results from the study indicated good negative correlations (r 2 values of 0.81 and 0.77) between the Multispectral Scanner-derived forest continuity index and natural logs of township population density. Socioeconomic indicators such as affluence and commuting patterns did not appear to correlate well with forest fragmentation estimates. Decreases in forest continuity index values occurred throughout much of the study region between 1973 and 1988, suggesting that forest fragmentation is occurring over large regions within the eastern United States. It is technologically feasible to assess patterns and rates of forest fragmentation across much larger areas than analyzed in this study; such analyses would provide useful overviews enabling objective assessment of the magnitude of forest fragmentation.

Massachusetts, New Hampshire↗
USGS2010

Surface energy balance estimates at local and regional scales using optical remote sensing from an aircraft platform and atmospheric data collected over semiarid rangelands

Remotely sensed data in the visible, near-infrared, and thermal-infrared wave bands were collected from a low-flying aircraft during the Monsoon '90 field experiment. Monsoon '90 was a multidisciplinary experiment conducted in a semiarid watershed. It had as one of its objectives the quantification of hydrometeorological fluxes during the “monsoon” or wet season. The remote sensing observations along with micrometeprological and atmospheric boundary layer (ABL) data were used to compute the surface energy balance over a range of spatial scales. The procedure involved averaging multiple pixels along transects flown over the meteorological and flux (METFLUX) stations. Average values of the spectral reflectance and thermal-infrared temperatures were computed for pixels of order 10 −1 to 10 1 km in length and were used with atmospheric data for evaluating net radiation ( R n ), soil heat flux ( G ), and sensible ( H ) and latent ( LE ) heat fluxes at these same length scales. The model employs a single-layer resistance approach for estimating H that requires wind speed and air temperature in the ABL and a remotely sensed surface temperature. The values of R n and G are estimated from remote sensing information together with near-surface observations of air temperature, relative humidity, and solar radiation. Finally, LE is solved as the residual term in the surface energy balance equation. Model calculations were compared to measurements from the METFLUX network for three days having different environmental conditions. Average percent differences for the three days between model and the METFLUX estimates of the local fluxes were about 5% for R n , 20% for G and H , and 15% for LE . Larger differences occurred during partly cloudy conditions because of errors in interpreting the remote sensing data and the higher spatial and temporal variation in the energy fluxes. Minor variations in modeled energy fluxes were observed when the pixel size representing the remote sensing inputs changed from 0.2 to 2 km. Regional scale estimates of the surface energy balance using bulk ABL properties for the model parameters and input variables and the 10-km pixel data differed from the METFLUX network averages by about 4% for R n , 10% for G and H , and 15% for LE . Model sensitivity in calculating the turbulent fluxes H and LE to possible variations in key model parameters (i.e., the roughness lengths for heat and momentum) was found to be fairly significant. Therefore the reliability of the methods for estimating key model parameters and potential errors needs further testing over different ecosystems and environmental conditions.

Water Resources Research↗
USGS2019

Performances of WorldView-3, Sentinel-2, and Landsat-8 data in mapping impervious surface

Many efforts have been made to map developed impervious surface from remotely sensed information in the last two decades. The U.S. Geological Survey (USGS) developed the National Land Cover Database (NLCD) to provide consistent land cover and change products for the Nation since 2001. Percent impervious surface area (ISA), one of the products in NLCD as a continuous field and estimated with Landsat imagery, represents the fraction of human-made impervious area in a 30 m resolution grid. ISA is used to map urban land cover types and extents for the United States. However, it is still a challenge to quantify highly heterogeneous features in many urban areas using remotely sensed data with spatial and spectral resolutions similar to Landsat and to determine the impacts of remotely sensed data characteristics on ISA mapping.

California, Texas↗
USGS1977

The Aristarchus-Harbinger region of the moon: Surface geology and history from recent remote-sensing observations

The region including the Aristarchus Plateau and Montes Harbinger is probably the most diverse, geologically, of any area of comparble size on the Moon. This part of the northwest quadrant of the lunar near side includes unique dark mantling material; both the densest concentration and the largest of the sinuous rilles; apparent volcanic vents, sinks, and domes; mare materials of various ages and colors; one of the freshest large craters (Aristarchus) with ejecta having unique colors and albedos; and three other large craters in different states of flooding and degradation (krieger, Herodotus, and Prinz). The three best-authenticated lunar transient phenomena were also observed here. This study is based principally on photographic and remote sensing observations made from Earth and Apollo orbiting space craft. Results include (1) delineation of geologic map units and their stratigraphic relationships; (2) discussion of the complex interrelationships between materials of volcanic and impact origin, including the effects of excavation, redistribution and mixing of previously deposited materials by younger impact craters; (3) deduction of physical and chemical properties of certain of the geologic units, based on both the remote-sensing information and on extrapolation of Apollo data to this area; and (4) development of a detailed geologic history of the region, outlining the probable sequence of events that resulted in its present appearance. A primary concern of the investigation has been anomalous red dark mantle on the Plateau. Based on an integration of Earth- and lunar orbit-based data, this layer seems to consist of fine-grained, block-free material containing a relatively large fraction of orange glass. It is probably of pyroclastic origin, laid down at some time during the Imbrian period of mare flooding. ?? 1977 D. Reidel Publishing Company.

The Moon↗
USGS2000

Coastal erosion vs riverline sediment discharge in the Arctic shelfx seas

This article presents a comparison of sediment input by rivers and by coastal erosion into both the Laptev Sea and the Canadian Beaufort Sea (CBS). New data on coastal erosion in the Laptev Sea, which are based on field measurements and remote sensing information and existing data on coastal erosion in the CBS as well as riverine sediment discharge into both the Laptev Sea and the CBS are included. Strong regional differences in the percentages of coastal ero- sion and riverine sediment supply are observed. The CBS is dominated by the riverine sediment discharge (64.45x106 t a-1) mainly of the Mackenzie River. which is the largest single source of sediments in the Arctic. Riverine sediment discharge into the Laptev Sea amounts to 24.10x106 t a-1, more than 70% of which are related to the Lena River. In comparison with the CBS. the Laptev Sea coast on average delivers approximately twice as much sediment mass per kilometer, a result of higher erosion rates due to higher cliffs and seasonal ice melting. In the Laptev Sea sediment input by coastal erosion (58.4x106 t a-1) is therefore more important than in the CBS and the ratio between riverine and coastal sediment input amounts to 0.4. Coastal erosion supplying 5.6x106 t a-1 is less significant for the sediment budget of the CBS where riverine sediment discharge exceeds coastal sediment input by a factor of ca. 10.

International Journal of Earth Sciences↗
USGS2019

Assessing the feasibility of satellite-based thresholds for hydrologically driven landsliding

Elevated soil moisture and heavy precipitation contribute to landslides worldwide. These environmental variables are now being resolved with satellites at spatiotemporal scales that could offer new perspectives on the development of landslide warning systems. However, the application of these data to hydro-meteorological thresholds (which account for antecedent soil moisture and rainfall) first need to be evaluated with respect to proven, direct measurement-based thresholds that use rain gauges and in situ soil moisture sensors. Here, we compare ground-based hydrologic data to overlapping satellite-based data before, during, and after a recent season of widespread shallow landsliding in the San Francisco Bay Area (California, USA). We then explore how the remotely sensed information could be used to empirically define hypothetical thresholds for shallow landsliding. We find that the ground-based thresholds developed with a single monitoring station show superior performance because the in situ soil saturation data better reflect the gravity-dominated subsurface flow conditions that are characteristic of hillslopes during the rainy season. Although the satellite-based thresholds can identify most of the landslide days, they include a greater number of false alarms due to overestimates of soil moisture between major storm events. To avoid the type of false alarms that are characteristic of our satellite-based thresholds, further post-processing of the near-surface hydrologic response data to better reflect gravity-dominated drainage should be integrated into satellite-based model outputs. Our results encourage further deployment of ground stations in landslide-prone terrain and cautious exploration of satellite-based hydro-meteorological thresholds where in situ networks are nonexistent.

California↗
USGS2025

Biotic and abiotic drivers of ecosystem temporal stability in herbaceous wetlands in China

Maintaining the stability of ecosystems is critical for supporting essential ecosystem services over time. However, our understanding of the contribution of the diverse biotic and abiotic factors to this stability in wetlands remains limited. Here, we combined data from a field vegetation survey of 725 herbaceous wetland sites in China with remote sensing information from the Enhanced Vegetation Index (EVI) from 2010 to 2020 to explore the contribution of biotic and abiotic factors to the temporal stability of primary productivity. We found that plant species richness directly contributed to stability on a national scale, but that this contribution differed among climate zones, hydrological regimes, and vegetation types. In addition, many abiotic factors, including soil properties, geographical location, and climate also contributed to stability. Piecewise structural equation modeling identified that soil properties, including soil pH, total nitrogen, and soil organic carbon, emerged as primary factors modulating ecosystem stability, both directly and indirectly by affecting species richness and vegetation type. Higher species richness and soil organic carbon were related to higher ecosystem stability in peatlands but less so in coastal and inland marshes. These findings enhance our ability to forecast how wetland ecosystems may respond to future environmental changes and biodiversity loss and can inform policy decisions related to ecosystem stability.

Global Change Biology↗
USGS2007

Dry Stream Reaches in Carbonate Terranes: Surface Indicators of Ground-Water Reservoirs

In areas where dry stream reaches occur, subsurface drainage successfully competes with surface drainage, and sheet-like dissolution openings have developed parallel to bedding creating the ground-water reservoir. Union Hollow in south-central Tennessee is the setting for a case study that illustrates the application of the dry stream reach technique. In this technique, dry stream reach identification is based on two types of readily acquired information: remotely sensed black and white infrared aerial photography; and surface reconnaissance of stream channel characteristics. Test drilling in Union Hollow subsequent to identification of the dry reach proved that a localized ground-water reservoir was present.

Water Resources Bulletin↗
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↗
USGS1980

A survey of image processing developments in support of remote sensing

New algorithm developments for image processing (IP) will occur throughout the 1980's, resulting from evolution in computer hardware and sensors as well as continuing research. This report will describe the areas of algorithm development that are occurring in applications, research, and operational environments. Included is an overview of image processing activities at institutions which are generally regarded as leaders in IP algorithm development and implementation. Finally, this report addresses directions in IP algorithm development that are being proposed for the EROS Data Center (EDC). The major applications of IP at EDC are developed for use in the processing, analysis, and extraction of remote sensing information from Landsat and aircraft data (platforms).

Report↗
USGS2025

Evaluating the performance of multiple precipitation datasets over the transboundary Ili River Basin between China and Kazakhstan

The Ili River Basin is characterized by complex topography and diverse climatic zones with limited in situ observations. This study evaluates the performance of six widely used precipitation datasets, CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data), ERA5_Land (European Centre for Medium-Range Weather Forecasts—ECMWF Reanalysis 5_Land), GPCC (Global Precipitation Climatology Centre), IMERG (Integrated Multi-satellite Retrievals for GPM), PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks), and TerraClimate, against ground-based data from 2001 to 2023. The evaluation is conducted across multiple spatial scales and temporal resolutions. At the basin scale, most datasets exhibit strong correlations with in situ observations across all temporal scales (r > 0.7), except for PERSIANN, which demonstrates a relatively weaker performance during summer and winter (r < 0.6). All datasets except ERA5_ Land show low annual and monthly bias (<5%), although larger errors are observed during summer, particularly for IMERG and PERSIANN. Dataset performance generally declines with increasing elevation. Basin-wide gridded evaluations reveal distinct spatial variations across all elevation zones, with CHIRPS showing the strongest ability to capture orographic precipitation gradients throughout the basin. All datasets correctly identified 2008 as a drought year and 2016 as a wet year, even though the magnitude and spatial resolution of the anomalies varied among them. These findings highlight the importance of selecting precipitation datasets that are suited to the complex topographic and climatic characteristics of transboundary basins. Our study provides valuable insights for improving hydrological modeling and can be used for water sustainability and flood–drought mitigation support activities in the Ili River Basin.

Ili River Basin↗
USGS2005

The detection and mapping of oil on a marshy area by a remote luminescent sensor

Airborne remote sensing can be a cost-effective method for monitoring pollutants in large areas such as occur in oil spills. An opportunity to test a particular method arose when a well ruptured and for 23 days spewed a 90-meter fountain of oil into the air, dispersing the oil over a wide area. The method tested was an airborne luminescence detector with a Fraunhofer Line Discriminator (FLD) which was flown over the affected area 41 days after the well was capped to obtain a map or the deposition pattern. To calibrate the system, samples of Spartina (wire grass) and Phragmites (common reed) were collected from the contaminated area and the oil residues were eluted in cyclohexane and quantitatively analyzed in a fluorescence photometer. Good correlation was observed between the remote sensor (FLD) and the laboratory analysis. Isopleths defining the deposition pattern of oil were drawn from the remote sensing information. A discussion will be presented on the feasibility of using this instrument for similar contamination incidents for cleanup and damage assessment.

Conference Paper↗
USGS1993

Integration of environmental simulation models with satellite remote sensing and geographic information systems technologies: case studies

Environmental modelers are testing and evaluating a prototype land cover characteristics database for the conterminous United States developed by the EROS Data Center of the U.S. Geological Survey and the University of Nebraska Center for Advanced Land Management Information Technologies. This database was developed from multi temporal, 1-kilometer advanced very high resolution radiometer (AVHRR) data for 1990 and various ancillary data sets such as elevation, ecological regions, and selected climatic normals. Several case studies using this database were analyzed to illustrate the integration of satellite remote sensing and geographic information systems technologies with land-atmosphere interactions models at a variety of spatial and temporal scales. The case studies are representative of contemporary environmental simulation modeling at local to regional levels in global change research, land and water resource management, and environmental simulation modeling at local to regional levels in global change research, land and water resource management and environmental risk assessment. The case studies feature land surface parameterizations for atmospheric mesoscale and global climate models; biogenic-hydrocarbons emissions models; distributed parameter watershed and other hydrological models; and various ecological models such as ecosystem, dynamics, biogeochemical cycles, ecotone variability, and equilibrium vegetation models. The case studies demonstrate the important of multi temporal AVHRR data to develop to develop and maintain a flexible, near-realtime land cover characteristics database. Moreover, such a flexible database is needed to derive various vegetation classification schemes, to aggregate data for nested models, to develop remote sensing algorithms, and to provide data on dynamic landscape characteristics. The case studies illustrate how such a database supports research on spatial heterogeneity, land use, sensitivity analysis, and scaling issues involving regional extrapolations and parameterizations of dynamic land processes within simulation models.

Pecora 12 Symposium↗
USGS2005

Planning for bird conservation: a tale of two models

Planning for bird conservation has become increasingly reliant on remote sensing, geographical information systems, and, especially, models used to predict the occurrence of bird species as well as their density and demographics. We address the role of such tools by contrasting two models used in bird conservation. One, the Mallard ( Anas platyrhynchos) productivity model, is very detailed, mechanistic, and based on an enormous body of research. The Mallard model has been extensively used with success to guide management efforts for Mallards and certain other species of ducks. The other model, the concept of Bird Conservation Areas, is more simple, less mechanistic, and less well-grounded in research. This concept proposes that large patches of suitable habitat in a proper landscape will be adequate to maintain populations of birds. The Bird Conservation Area concept recently has been evaluated in the northern tallgrass prairie, where its fundamental assumptions have been found not to hold consistently. We argue that a more comprehensive understanding of the biology of individual species, and how they respond to habitat features, will be essential before we can use remotely sensed information and geographic information system products with confidence.

General Technical Report↗
USGS2021

Improving Landsat predictions of rangeland fractional cover with multitask learning and uncertainty

Operational satellite remote sensing products are transforming rangeland management and science. Advancements in computation, data storage and processing have removed barriers that previously blocked or hindered the development and use of remote sensing products. When combined with local data and knowledge, remote sensing products can inform decision‐making at multiple scales. We used temporal convolutional networks to produce a fractional cover product that spans western United States rangelands. We trained the model with 52,012 on‐the‐ground vegetation plots to simultaneously predict fractional cover for annual forbs and grasses, perennial forbs and grasses, shrubs, trees, litter and bare ground. To assist interpretation and to provide a measure of prediction confidence, we also produced spatiotemporal‐explicit, pixel‐level estimates of uncertainty. We evaluated the model with 5,780 on‐the‐ground vegetation plots removed from the training data. Model evaluation averaged 6.3% mean absolute error and 9.6% root mean squared error. Evaluation with additional datasets that were not part of the training dataset, and that varied in geographic range, method of collection, scope and size, revealed similar metrics. Model performance increased across all functional groups compared to the previously produced fractional product. The advancements achieved with the new rangeland fractional cover product expand the management toolbox with improved predictions of fractional cover and pixel‐level uncertainty. The new product is available on the Rangeland Analysis Platform (https://rangelands.app/), an interactive web application that tracks rangeland vegetation through time. This product is intended to be used alongside local on‐the‐ground data, expert knowledge, land use history, scientific literature and other sources of information when making interpretations. When being used to inform decision‐making, remotely sensed products should be evaluated and utilized according to the context of the decision and not be used in isolation.

Methods in Ecology and Evolution↗