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At least 937 records · Page 52Linked to original sources
USGS2012

Spatial aspects of building and population exposure data and their implications for global earthquake exposure modeling

This paper discusses spatial aspects of the global exposure dataset and mapping needs for earthquake risk assessment. We discuss this in the context of development of a Global Exposure Database for the Global Earthquake Model (GED4GEM), which requires compilation of a multi-scale inventory of assets at risk, for example, buildings, populations, and economic exposure. After defining the relevant spatial and geographic scales of interest, different procedures are proposed to disaggregate coarse-resolution data, to map them, and if necessary to infer missing data by using proxies. We discuss the advantages and limitations of these methodologies and detail the potentials of utilizing remote-sensing data. The latter is used especially to homogenize an existing coarser dataset and, where possible, replace it with detailed information extracted from remote sensing using the built-up indicators for different environments. Present research shows that the spatial aspects of earthquake risk computation are tightly connected with the availability of datasets of the resolution necessary for producing sufficiently detailed exposure. The global exposure database designed by the GED4GEM project is able to manage datasets and queries of multiple spatial scales.

Natural Hazards↗
USGS2024

Earthquake-triggered ground-failure inventory associated with the M7.1 2018 Southcentral Alaska earthquake

The 30 November 2018, magnitude (Mw) 7.1 earthquake in Southcentral Alaska triggered substantial landslides, liquefaction, and ground cracking throughout the region, resulting in widespread geotechnical damage to buildings and infrastructure. Despite a challenging reconnaissance and remote-sensing environment, we constructed a detailed digital inventory of ground failure associated with the event from several sources. Sources included information derived from remotely sensed data, and data compiled from literature, social media postings, and earthquake damage information compiled by local, state, and federal agencies. Each instance of ground failure within the inventory contains information on the location and type of observed ground failure, and the methods and data used to document the occurrence. Where high-quality data, such as LIDAR or satellite imagery, were available and showed the ground-failure instance clearly, the extent is mapped as a polygon or polyline. All other locations are mapped as points. There are a total of 886 ground-failure instances documented within the inventory (400 landslides, 286 liquefaction features, and 200 features unattributed to specific processes). A semi-quantitative confidence scheme is used to describe mapping certainty associated with each ground-failure feature. This inventory represents a relatively moderate ground-failure-triggering event that occurred in a subarctic environment. This data paper describes the content within the inventory, the inventory data collection procedures, and limitations of the data. Events of this type are not often documented in detail; thus, adding the inventory data to the US Geological Survey Open Repository of Earthquake-Triggered Ground-Failure Inventories further diversifies the datasets available to the scientific community to be used to better understand and model earthquake-triggered ground failure.

Alaska↗
USGS2023

Integrated science strategy for assessing and monitoring water availability and migratory birds for terminal lakes across the Great Basin, United States

Executive Summary In 2022, the U.S. Geological Survey (USGS) established the Saline Lake Ecosystems Integrated Water Availability Assessment (IWAAs) to monitor and assess the hydrology of terminal lakes in the Great Basin and the migratory birds and other wildlife dependent on those habitats. Scientists from across the USGS (with specialties in water quantity, water quality, limnology, avian biology, data science, landscape ecology, and science communication) formed the Saline Lake Ecosystems IWAAs Team. The team has developed this regional strategic science plan to guide data collection and assessment activities at terminal lakes in the Great Basin. The U.S. Congress requested the USGS to establish the Saline Lake Ecosystems IWAAs in response to historically low water levels at terminal lakes and associated wetlands across the Great Basin. Not all Great Basin terminal lakes have high salinity; however, all terminal lakes occur in endorheic, closed, basins with no surface-water outflow. Low lake levels across the Great Basin are the result of increased water use for agriculture and municipalities, drought conditions, and a warming climate. Great Basin terminal lake water extents have decreased by as much as 90 percent over the last 150 years, and terminal lake wetlands have decreased in area by as much as 47 percent since 1984. Lake elevations and wetland areas are primarily supported by freshwater inputs from snowmelt feeding upgradient rivers, streams, and springs. These freshwater inputs have been severely reduced because of continued and increased surface-water diversions and surface-water capture through groundwater pumping for agriculture, mining, and public supply as well as unprecedented drought conditions and warming temperatures related to climate change. Water quality, specifically salinity, is highly variable for terminal lakes of the Great Basin, and this variability is a result of the balance between freshwater inflow and evaporation. Variability of salinity at each of the terminal lakes can be affected by lake morphology, hydrogeologic features of the basin, annual variability in weather patterns, and changes in upgradient water use. Hypersaline terminal lakes provide abundant food resources such as brine shrimp and brine flies that support nesting and migrating birds. The density and composition of invertebrates are closely tied to lake salinity. Increased salinity can exceed the tolerance of invertebrates, severely limiting their biomass. In contrast, decreased salinity can lead to altered invertebrate community composition, reducing the abundance of optimal avian prey resources. Great Basin terminal lake ecosystems, including open-water and adjacent aquatic and terrestrial environments, provide resources necessary to sustain many animal populations throughout the year. Although a variety of taxa use terminal lakes, these ecosystems are of acute importance for the millions of migratory waterbirds (for example, shorebirds, wading birds, and waterfowl) dependent on the network of terminal lakes and their associated wetlands. Migratory birds transiting the Pacific and Central Flyways use Great Basin terminal lake ecosystems throughout the year to feed, nest, and transit between wintering and breeding ranges. As such, successful conservation of birds and their habitats requires coordinated management of water and habitats across the Great Basin network of terminal lakes and wetlands. The linkages between water availability and ecosystem vulnerability of terminal lakes in the Great Basin are not well understood. The vulnerability of terminal lakes is related to the factors driving change and adaptive capacity of the lake ecosystem. Saline lake ecosystems are vulnerable when changes in water quantity affect ecosystem function. Water quantity affects salinity, which affects food webs and habitat; these linkages can be investigated with water-quality and food web monitoring. Water quantity also affects inundated habitat, which can be quantified through remote sensing. It is necessary to quantify hydroclimatic and water use controls on water availability to terminal lakes to assess the response of the ecosystems. Remotely sensed data can provide a broad-scale and long-term synoptic view of terminal lake hydrologic characteristics, but ground observations are required to interpret changes in water quality and ecological functions. Some terminal lake basins have ongoing monitoring and modeling efforts within the Great Basin (for example, Great Salt Lake, Carson River Basin), yet most monitoring locations are hydrologically upgradient and too far away from lake inflows to provide an accurate assessment of hydrological trends for the lake ecosystems. Other terminal lakes have no long-term hydrological monitoring in their respective watersheds (for example, Lake Abert). Ecological data collection in the Great Basin is also insufficient to understand how many birds exist on the landscape, how birds use the mosaic of terminal-lake habitats as an interconnected system, and how Great Basin terminal lakes are linked to the larger continental system of the Pacific and Central Flyways. Across agencies and organizations, tracking bird movement, abundance, and diversity is inconsistent, with some lakes having once- or twice-a-year bird survey efforts and a few locations having more intensive ecological data-gathering efforts (for example, Great Salt Lake, Lake Abert). Bridging hydrological and ecological information gaps will improve understanding of the trends in water supply and water quality, habitat availability and usage, and impacts on vulnerable waterbird species, all of which would be used by managers in coordinated conservation of this unique network of terminal-lake habitats. The terminal lakes of the Great Basin are part of the Basin and Range physiographic province that extends from the Colorado Plateau on the east to the Sierra Nevada on the west, and from the Snake River Plain on the north to the Garlock fault and the Mojave block on the south. The Great Basin is larger than 650,000 square kilometers and encompasses most of the State of Nevada but also extends to western Utah, eastern California, southeastern Idaho, southwestern Wyoming, and southeastern Oregon. The climate is arid to semiarid with a hydrologic regime that is snowmelt dominated, providing as much as 75 percent of total annual runoff for the region. Terminal lakes of the Great Basin occupy the lowest areas of closed (endorheic) drainage basins, such that lake levels and water quality respond rapidly to surface-water inflow. Terminal lakes provide local and regional economic value to the States in the Great Basin, including mineral extraction, aquaculture, public works, and recreational uses. As an example, assessments of Great Salt Lake’s ecological health and economic impact find hemispheric importance for the former and regional importance for the latter. Great Salt Lake creates about 7,000 jobs and $2 billion of economic output per year, most of which would be lost with further declines in lake level. The objectives of this Science Strategy are threefold: (1) to identify how changing water availability affects the quality, diversity, and abundance of habitats supporting continental waterbird populations; (2) to highlight the scientific monitoring and assessment needs of Great Basin terminal lakes; and (3) to support coordinated management and conservation actions to benefit those ecosystems, migratory birds, and other wildlife. There are long-term hydrological, ecological, and societal challenges associated with terminal lakes ecosystems in the Great Basin. This Science Strategy benefits partners by providing a conceptual model, nested at different spatial extents, that identifies key scientific information needs to inform coordinated implementation of management and conservation plans within and among hydrologic basins to address these complex challenges.

California, Idaho, Nevada, Oregon, Utah, Wyoming↗
USGS2014

Modeling vegetation heights from high resolution stereo aerial photography: an application for broad-scale rangeland monitoring

Vertical vegetation structure in rangeland ecosystems can be a valuable indicator for assessing rangeland health and monitoring riparian areas, post-fire recovery, available forage for livestock, and wildlife habitat. Federal land management agencies are directed to monitor and manage rangelands at landscapes scales, but traditional field methods for measuring vegetation heights are often too costly and time consuming to apply at these broad scales. Most emerging remote sensing techniques capable of measuring surface and vegetation height (e.g., LiDAR or synthetic aperture radar) are often too expensive, and require specialized sensors. An alternative remote sensing approach that is potentially more practical for managers is to measure vegetation heights from digital stereo aerial photographs. As aerial photography is already commonly used for rangeland monitoring, acquiring it in stereo enables three-dimensional modeling and estimation of vegetation height. The purpose of this study was to test the feasibility and accuracy of estimating shrub heights from high-resolution (HR, 3-cm ground sampling distance) digital stereo-pair aerial images. Overlapping HR imagery was taken in March 2009 near Lake Mead, Nevada and 5-cm resolution digital surface models (DSMs) were created by photogrammetric methods (aerial triangulation, digital image matching) for twenty-six test plots. We compared the heights of individual shrubs and plot averages derived from the DSMs to field measurements. We found strong positive correlations between field and image measurements for several metrics. Individual shrub heights tended to be underestimated in the imagery, however, accuracy was higher for dense, compact shrubs compared with shrubs with thin branches. Plot averages of shrub height from DSMs were also strongly correlated to field measurements but consistently underestimated. Grasses and forbs were generally too small to be detected with the resolution of the DSMs. Estimates of vertical structure will be more accurate in plots having low herbaceous cover and high amounts of dense shrubs. Through the use of statistically derived correction factors or choosing field methods that better correlate with the imagery, vegetation heights from HR DSMs could be a valuable technique for broad-scale rangeland monitoring needs.

California;Nevada↗
USGS2020

Development and validation of the CHIRTS-daily quasi-global high-resolution daily temperature data set

We present a high-resolution daily temperature data set, CHIRTS-daily, which is derived by merging the monthly Climate Hazards center InfraRed Temperature with Stations climate record with daily temperatures from version 5 of the European Centre for Medium-Range Weather Forecasts Re-Analysis. We demonstrate that remotely sensed temperature estimates may more closely represent true conditions than those that rely on interpolation, especially in regions with sparse in situ data. By leveraging remotely sensed infrared temperature observations, CHIRTS-daily provides estimates of 2-meter air temperature for 1983–2016 with a footprint covering 60°S-70°N. We describe this data set and perform a series of validations using station observations from two prominent climate data sources. The validations indicate high levels of accuracy, with CHIRTS-daily correlations with observations ranging from 0.7 to 0.9, and very good representation of heat wave trends.

Scientific Data↗
USGS2005

Trend analysis of time-series phenology derived from satellite data

Remote sensing information has been used in studies of the seasonal dynamics (phenology) of the land surface for the past 15 years. While our understanding of remote sensing phenology is still in development, it is regarded as a key to understanding land surface processes over large areas. Repeat observations from satellite-borne multispectral sensors provide a mechanism to move from plant-specific to regional scale studies of phenology. In addition, we now have sufficient time-series (since 1982 at 8-km resolution covering the globe and since 1989 at 1-km resolution over the conterminous US) to study seasonal and interannual trends from satellite data. Phenology metrics including start of season, end of season, duration of season, and seasonally integrated greenness were derived from 8 km AVHRR data over North America spanning the years 1982-2003. Trend analysis was performed on the annual summaries of the metrics to determine areas with increasing or decreasing trends for the time period under study. Results show only small areas of changing start of season, but the end of season is coming later over well defined areas of New England and SE Canada, principally as a result of land use changes. The total greenness metric is most striking at the shrub/tundra boundary of North America, indicating increasing vegetation vigor or possible vegetation conversion as a result of warming. ?? 2005 IEEE.

Conference Paper↗
USGS2008

Characterization of errors in a coupled snow hydrology-microwave emission model

Traditional approaches to the direct estimation of snow properties from passive microwave remote sensing have been plagued by limitations such as the tendency of estimates to saturate for moderately deep snowpacks and the effects of mixed land cover within remotely sensed pixels. An alternative approach is to assimilate satellite microwave emission observations directly, which requires embedding an accurate microwave emissions model into a hydrologic prediction scheme, as well as quantitative information of model and observation errors. In this study a coupled snow hydrology [Variable Infiltration Capacity (VIC)] and microwave emission [Dense Media Radiative Transfer (DMRT)] model are evaluated using multiscale brightness temperature (TB) measurements from the Cold Land Processes Experiment (CLPX). The ability of VIC to reproduce snowpack properties is shown with the use of snow pit measurements, while TB model predictions are evaluated through comparison with Ground-Based Microwave Radiometer (GBMR), air-craft [Polarimetric Scanning Radiometer (PSR)], and satellite [Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E)] TB measurements. Limitations of the model at the point scale were not as evident when comparing areal estimates. The coupled model was able to reproduce the TB spatial patterns observed by PSR in two of three sites. However, this was mostly due to the presence of relatively dense forest cover. An interesting result occurs when examining the spatial scaling behavior of the higher-resolution errors; the satellite-scale error is well approximated by the mode of the (spatial) histogram of errors at the smaller scale. In addition, TB prediction errors were almost invariant when aggregated to the satellite scale, while forest-cover fractions greater than 30% had a significant effect on TB predictions. ?? 2008 American Meteorological Society.

Journal of Hydrometeorology↗
USGS2026

Invasion resistance varies by fuel break type in sagebrush ecosystems

Background Wildfire is an increasingly important driver of changes within sagebrush (Artemisia spp. L.) ecosystems of the western USA, often resulting in increased spread of exotic annual grasses, such as cheatgrass (Bromus tectorum L.), and subsequent losses of native vegetation and wildlife habitat. Fuel breaks— areas of land treated to reduce or redistribute fuel loads — are widely implemented to help prevent the spread of wildfires and provide areas to facilitate firefighting efforts. However, localized installation and maintenance of fuel breaks directly reduce or remove vegetation and may propagate the spread of exotic annual grasses into fuel break boundaries and surrounding areas, inadvertently weakening ecological resilience to disturbance. To investigate if exotic annual grass cover was associated with mowed or green strip fuel breaks across the sagebrush biome, we combined multiple data sources and methodologies. We used targeted field surveys and land-management agency monitoring data within a space-for-time substitution framework coupled with a progressive-change before-after control-impact (PC BACI) study design using historical remotely sensed vegetation cover data which allowed us to account for potential confounding effects of roads on annual grass cover. Results Models using both field collected and remotely sensed vegetation indices estimated increases in exotic annual grass cover over time following mowed fuel break installation, and higher exotic annual grass cover closer to mowed fuel breaks. These increases in exotic annual grass occurred within, at 500 m and at 1000 m from mowed fuel breaks. However, we found variable patterns of exotic annual grass after green strip fuel break installation depending on the data source. No increase in exotic annual grass were indicated by either analysis at distances greater than 500 m from green strip fuel breaks. However, our and field data analyses disagreed on the direction of the association of exotic annual grass cover and green strip fuel breaks. Conclusions Although fuel breaks are an important tool in managing wildland fire, our analysis underscores the importance of planting fire-resistant vegetation, rather than mowing alone, to reduce invasion by annual grasses within and around fuel breaks in sagebrush ecosystems. In addition, site characteristics that hinder the proliferation of exotic annual grasses could be evaluated when installing fuel breaks to minimize unintended effects of exotic annual grass on surrounding sagebrush habitat.

California, Idaho, Nevada, Oregon, Utah↗
USGS2018

Mapping wildfire burn severity in the Arctic Tundra from downsampled MODIS data

Wildfires are historically infrequent in the arctic tundra, but are projected to increase with climate warming. Fire effects on tundra ecosystems are poorly understood and difficult to quantify in a remote region where a short growing season severely limits ground data collection. Remote sensing has been widely utilized to characterize wildfire regimes, but primarily from the Landsat sensor, which has limited data acquisition in the Arctic. Here, coarse-resolution remotely sensed data are assessed as a means to quantify wildfire burn severity of the 2007 Anaktuvuk River Fire in Alaska, the largest tundra wildfire ever recorded on Alaska's North Slope. Data from Landsat Thematic Mapper (TM) and downsampled Moderate-resolution Imaging Spectroradiometer (MODIS) were processed to spectral indices and correlated to observed metrics of surface, subsurface, and comprehensive burn severity. Spectral indices were strongly correlated to surface severity (maximum R2 = 0.88) and slightly less strongly correlated to substrate severity. Downsampled MODIS data showed a decrease in severity one year post-fire, corroborating rapid vegetation regeneration observed on the burned site. These results indicate that widely-used spectral indices and downsampled coarse-resolution data provide a reasonable supplement to often-limited ground data collection for analysis and long-term monitoring of wildfire effects in arctic ecosystems.

Alaska↗
USGS2025

Department of the Interior: DOI

Remotely sensed data and derived information contribute substantially to mission-critical work across the Department of the Interior (DOI). 1 This DOI section highlights a sample of DOI remote sensing applications and illustrates a range of technology, platforms, and specialized sensors employed.

conterminous United States↗
USGS2013

Marsh collapse thresholds for coastal Louisiana estimated using elevation and vegetation index data

Forecasting marsh collapse in coastal Louisiana as a result of changes in sea-level rise, subsidence, and accretion deficits necessitates an understanding of thresholds beyond which inundation stress impedes marsh survival. The variability in thresholds at which different marsh types cease to occur (i.e., marsh collapse) is not well understood. We utilized remotely sensed imagery, field data, and elevation data to help gain insight into the relationships between vegetation health and inundation. A Normalized Difference Vegetation Index (NDVI) dataset was calculated using remotely sensed data at peak biomass (August) and used as a proxy for vegetation health and productivity. Statistics were calculated for NDVI values by marsh type for intermediate, brackish, and saline marsh in coastal Louisiana. Marsh-type specific NDVI values of 1.5 and 2 standard deviations below the mean were used as upper and lower limits to identify conditions indicative of collapse. As marshes seldom occur beyond these values, they are believed to represent a range within which marsh collapse is likely to occur. Inundation depth was selected as the primary candidate for evaluation of marsh collapse thresholds. Elevation relative to mean water level (MWL) was calculated by subtracting MWL from an elevation dataset compiled from multiple data types including light detection and ranging (lidar) and bathymetry. A polynomial cubic regression was used to examine a random subset of pixels to determine the relationship between elevation (relative to MWL) and NDVI. The marsh collapse uncertainty range values were found by locating the intercept of the regression line with the 1.5 and 2 standard deviations below the mean NDVI value for each marsh type. Results indicate marsh collapse uncertainty ranges of 30.7–35.8 cm below MWL for intermediate marsh, 20–25.6 cm below MWL for brackish marsh, and 16.9–23.5 cm below MWL for saline marsh. These values are thought to represent the ranges of inundation depths within which marsh collapse is probable.

Louisiana↗
USGS2002

Northern Everglades, Florida, satellite image map

These satellite image maps are one product of the USGS Land Characteristics from Remote Sensing project, funded through the USGS Place-Based Studies Program with support from the Everglades National Park. The objective of this project is to develop and apply innovative remote sensing and geographic information system techniques to map the distribution of vegetation, vegetation characteristics, and related hydrologic variables through space and over time. The mapping and description of vegetation characteristics and their variations are necessary to accurately simulate surface hydrology and other surface processes in South Florida and to monitor land surface changes. As part of this research, data from many airborne and satellite imaging systems have been georeferenced and processed to facilitate data fusion and analysis. These image maps were created using image fusion techniques developed as part of this project.

Florida↗
USGS2012

Mapping surface disturbance of energy-related infrastructure in southwest Wyoming--An assessment of methods

We evaluated how well three leading information-extraction software programs (eCognition, Feature Analyst, Feature Extraction) and manual hand digitization interpreted information from remotely sensed imagery of a visually complex gas field in Wyoming. Specifically, we compared how each mapped the area of and classified the disturbance features present on each of three remotely sensed images, including 30-meter-resolution Landsat, 10-meter-resolution SPOT (Satellite Pour l'Observation de la Terre), and 0.6-meter resolution pan-sharpened QuickBird scenes. Feature Extraction mapped the spatial area of disturbance features most accurately on the Landsat and QuickBird imagery, while hand digitization was most accurate on the SPOT imagery. Footprint non-overlap error was smallest on the Feature Analyst map of the Landsat imagery, the hand digitization map of the SPOT imagery, and the Feature Extraction map of the QuickBird imagery. When evaluating feature classification success against a set of ground-truthed control points, Feature Analyst, Feature Extraction, and hand digitization classified features with similar success on the QuickBird and SPOT imagery, while eCognition classified features poorly relative to the other methods. All maps derived from Landsat imagery classified disturbance features poorly. Using the hand digitized QuickBird data as a reference and making pixel-by-pixel comparisons, Feature Extraction classified features best overall on the QuickBird imagery, and Feature Analyst classified features best overall on the SPOT and Landsat imagery. Based on the entire suite of tasks we evaluated, Feature Extraction performed best overall on the Landsat and QuickBird imagery, while hand digitization performed best overall on the SPOT imagery, and eCognition performed worst overall on all three images. Error rates for both area measurements and feature classification were prohibitively high on Landsat imagery, while QuickBird was time and cost prohibitive for mapping large spatial extents. The SPOT imagery produced map products that were far more accurate than Landsat and did so at a far lower cost than QuickBird imagery. Consideration of degree of map accuracy required, costs associated with image acquisition, software, operator and computation time, and tradeoffs in the form of spatial extent versus resolution should all be considered when evaluating which combination of imagery and information-extraction method might best serve any given land use mapping project. When resources permit, attaining imagery that supports the highest classification and measurement accuracy possible is recommended.

Wyoming↗
USGS2013

Merapi 2010 eruption—Chronology and extrusion rates monitored with satellite radar and used in eruption forecasting

Despite dense cloud cover, satellite-borne commercial Synthetic Aperture Radar (SAR) enabled frequent monitoring of Merapi volcano's 2010 eruption. Near-real-time interpretation of images derived from the amplitude of the SAR signals and timely delivery of these interpretations to those responsible for warnings, allowed satellite remote sensing for the first time to play an equal role with in situ seismic, geodetic and gas monitoring in guiding life-saving decisions during a major volcanic crisis. Our remotely sensed data provide an observational chronology for the main phase of the 2010 eruption, which lasted 12 days (26 October–7 November, 2010). Unlike the prolonged low-rate and relatively low explosivity dome-forming and collapse eruptions of recent decades at Merapi, the eruption began with an explosive eruption that produced a new summit crater on 26 October and was accompanied by an ash column and pyroclastic flows that extended 8 km down the flanks. This initial explosive event was followed by smaller explosive eruptions on 29 October–1 November, then by a period of rapid dome growth on 1–4 November, which produced a summit lava dome with a volume of ~ 5 × 10 6 m 3 . A paroxysmal VEI 4 magmatic eruption (with ash column to 17 km altitude) destroyed this dome, greatly enlarged the new summit crater and produced extensive pyroclastic flows (to ~ 16 km radial distance in the Gendol drainage) and surges during the night of 4–5 November. The paroxysmal eruption was followed by a period of jetting of gas and tephra and by a second short period (12 h) of rapid dome growth on 6 November. The eruption ended with low-level ash and steam emissions that buried the 6 November dome with tephra and continued at low levels until seismicity decreased to background levels by about 23 November. Our near-real-time commercial SAR documented the explosive events on 26 October and 4–5 November and high rates of dome growth (> 25 m 3 s − 1 ). An event tree analysis for the previous 2006 Merapi eruption indicated that for lava dome extrusion rates > 1.2 m 3 s − 1 , the probability of a large (1872-scale) eruption was ~ 10%. Consequently, the order-of-magnitude greater rates in 2010, along with the explosive start of the eruption on 26 October, the large volume of lava accumulating at the summit by 4 November, and the rapid and large increases in seismic energy release, deformation and gas emissions were the basis for warnings of an unusually large eruption by the Indonesian Geological Agency's Center for Volcanology and Geologic Hazard Mitigation (CVGHM) and their Volcano Research and Technology Development Center (BPPTK) in Yogyakarta — warnings that saved thousands of lives.

Merapi Volcano↗
USGS2014

Change detection using vegetation indices and multiplatform satellite imagery at multiple temporal and spatial scales

This chapter describes emerging methods for using satellite imagery across temporal and spatial scales using a case study approach to illustrate some of the opportunities now available for combining observations across scales. It explores the use of multiplatform sensor systems to characterize ecological change, as exemplified by efforts to scale the effects of a biocontrol insect (the leaf beetle Diorhabda carinulata ) on the phenology and water use of Tamarix shrubs (Tamarix ramosissima and related species and hybrids) targeted for removal on western U.S. rivers, from the level of individual leaves to the regional level of measurement. Finally, the chapter summarizes the lessons learned and emphasize the need for ground data to calibrate and validate remote sensing data and the types of errors inherent in scaling point data over wide areas, illustrated with research on evapotranspiration (ET) of Tamarix using a wide range of ground measurement and remote sensing methods.

Book chapter↗
USGS2014

Landscape selection by piping plovers has implications for measuring habitat and population size

How breeding birds distribute in relation to landscape-scale habitat features has important implications for conservation because those features may constrain habitat suitability. Furthermore, knowledge of these associations can help build models to improve area-wide demographic estimates or to develop a sampling stratification for research and monitoring. This is particularly important for rare species that have uneven distributions across vast areas, such as the federally listed piping plover (Charadrius melodus; hereafter plover). We examined how remotely-sensed landscape features influenced the distribution of breeding plover pairs among 2-km shoreline segments during 2006–2009 at Lake Sakakawea in North Dakota, USA. We found strong associations between remotely-sensed landscape features and plover abundance and distribution (R 2 = 0.65). Plovers were nearly absent from segments with bluffs (>25 m elevation increase within 250 m of shoreline). Relative plover density (pairs/ha) was markedly greater on islands (4.84 ± 1.22 SE) than on mainlands (0.85 ± 0.17 SE). Pair numbers increased with abundance of nesting habitat (unvegetated-flat areas β^=0.28±0.08SE ). On islands, pair numbers also increased with the relative proportion of the total area that was habitat ( β^=3.27±0.46SE ). Our model could be adapted to estimate the breeding population of plovers or to make predictions that provide a basis for stratification and design of future surveys. Knowledge of landscape features, such as bluffs, that exclude use by birds refines habitat suitability and facilitates more accurate estimates of habitat and population abundance, by decreasing the size of the sampling universe. Furthermore, techniques demonstrated here are applicable to other vast areas where birds breed in sparse or uneven densities.

North Dakota↗
USGS2008

Simplified Surface Energy Balance (SSEB) approach for estimating actual ET: An evaluation with lysimeter data

Evapotranspiration (ET) is an essential component of the water balance and a major consumptive use of irrigation water and precipitation on cropland. Numerous energy balance (EB) algorithms have been developed to make use of remote sensing data to estimate ET regionally. However, a review of different ET mapping algorithms shows that most EB models are complex to use and may not be suitable for operational ET remote sensing. Efforts are being made to simplify procedures to estimate regional ET mainly through the scaling of reference ET. The Simplified Surface Energy Balance (SSEB) is one such method. In this study, the SSEB approach was applied to six Landsat TM images covering a major portion of the Southern High Plains (parts of the Texas Panhandle and northeastern New Mexico) that were acquired during the 2007 cropping season. Performance of the SSEB was evaluated by comparing estimated ET with measured daily ET from four large monolithic lysimeters, with each lysimeter located in the center of a 210 by 225 m field at the USDA_ARS Conservation and Production Research Laboratory, Bushland, Tex. [350 11' N, 1020 06' W; 1,170 m elevation MSL]. Results indicated that the SSEB can provide ET estimates with reasonable accuracy for the Bushland location. However, more evaluation is needed for different agroclimatological conditions in the region.

Conference Paper↗
USGS2020

Evaluation of survey methods for colonial waterbirds at Chase Lake National Wildlife Refuge, North Dakota

Estimating the number of breeding pairs in a mixed-species waterbird colony is difficult because colonial waterbirds are vulnerable to human intrusion and their colonies are often in remote areas with limited access. We investigated methods to estimate the number of nests of waterbirds at a large, mixed-species colony at Chase Lake National Wildlife Refuge in south-central North Dakota. The primary goals of this study were to evaluate survey methods for shrub- and ground-nesting colonial waterbirds at Chase Lake National Wildlife Refuge and to develop protocols for estimating abundance of the different species. The specific objectives were (1) to assess visible-nest counts for ciconiiform species from the perimeter of nesting areas (hereafter, perimeter counts) and observational surveys from fixed points outside the colony to count flights of adult ciconiiforms in and out of the colony (hereafter, flightline surveys) as alternatives to within-colony counts of ciconiiform nests, and (2) to assess semiautomated, pixel-based image-analysis techniques to estimate abundance of American White Pelicans ( Pelecanus erythrorhynchos ) as an alternative to traditional manual counts from aerial photographs. For shrub-nesting ciconiiform species, observers counted 2,259 and 1,759 active ciconiiform nests in 2012 and 2013, respectively, during within-colony counts of ciconiiform nests. Results from within-colony counts of ciconiiform nests indicated a positive relation between the number of nests and the area of the shrub subcolony for the three most common ciconiiform species and all ciconiiform species combined. The perimeter nest counts of ciconiiform nests at Chase Lake represented only 18.8 percent of the total active ciconiiform nests counted in 11 subcolonies in 2012, which was well below the recommended target of 50 percent. Although we found a positive relationship between the number of nests counted during perimeter counts and the number of nests counted during within-colony counts for the three most common ciconiiform species and all ciconiiform species combined, perimeter counts at Chase Lake were hampered by disturbance to nesting birds. Thus, we discontinued the perimeter counts before they were completed. We did not develop predictive models from these perimeter counts in 2012 because these models could be misleading due to inconsistent application of the survey methods, which likely would have provided inaccurate perimeter counts. The extent of this issue is unknown. Flightline surveys at Chase Lake documented patterns of ciconiiform activity that were unknown for this region. For the common ciconiiform species, the number of flights to and from the South Island at Chase Lake were greatest in the morning (7:00−12:00 central daylight time [CDT]) and least in the afternoon (12:00−17:00), and least early in the breeding season (May 29–June 20, 2013) and greatest later in the breeding season (June 24–August 1, 2013). Flightline surveys are an index but lacked comparability with within-colony nest counts because the two methods provide measures of different things (that is, adult activity away from the colony as compared to the number of nests within the colony). The overall proportions of flights generally reflected the proportions of the within-colony nest counts for the four most common species: Black-crowned Night-Heron ( Nycticorax nycticorax ), Cattle Egret ( Bubulcus ibis ), Great Egret ( Ardea alba ), and Snowy Egret ( Egretta thula ). Flightline surveys at Chase Lake indicated apparent variation related to the time of day and season, as well as a variation in detection of inbound and outbound adult ciconiiforms. For ciconiiforms at Chase Lake, the most appropriate combination of survey approaches will depend on the need for annual estimates of nest abundance of ciconiiform species, balanced with the financial, personnel, and logistical constraints associated with the survey methods. For ground-nesting American White Pelicans, the results from this study indicated that digital-image processing using remote-sensing software provides an accurate estimate of the number of American White Pelican nests. Estimates of the number of pelican nests from digital-image processing, using two commercially available remote-sensing software packages, produced nest estimates that were comparable to those of traditional manual counts from aerial photographs.

North Dakota↗