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At least 1,045 records · Page 58Linked to original sources
USGS2005

Streamflow properties from time series of surface velocity and stage

Time series of surface velocity and stage have been collected simultaneously. Surface velocity was measured using an array of newly developed continuous-wave microwave sensors. Stage was obtained from the standard U.S. Geological Survey (USGS) measurements. The depth of the river was measured several times during our experiments using sounding weights. The data clearly showed that the point of zero flow was not the bottom at the measurement site, indicating that a downstream control exists. Fathometer measurements confirmed this finding. A model of the surface velocity expected at a site having a downstream control was developed. The model showed that the standard form for the friction velocity does not apply to sites where a downstream control exists. This model fit our measured surface velocity versus stage plots very well with reasonable values of the parameters. Discharges computed using the surface velocities and measured depths matched the USGS rating curve for the site. Values of depth-weighted mean velocities derived from our data did not agree with those expected from Manning's equation due to the downstream control. These results suggest that if real-time surface velocities were available at a gauging station, unstable stream beds could be monitored. Journal of Hydraulic Engineering ?? ASCE.

Journal of Hydraulic Engineering↗
USGS1991

Torsional response of unique building

Acceleration response records obtained during the October 1, 1987 Whittier‐Narrows earthquake ( M s = 5.6 ) "> ( M s = 5.6 ) from the 32‐story, vertically irregular 1100 Wilshire Finance Building, of which the cross section changes from a nominally rectangular shape to a triangular one, are analyzed. The building was instrumented with 21 channels of synchronized sensors, consisting of 12 uniaxial accelerometers deployed throughout the superstructure and connected to a central recording system and three triaxial strong‐motion accelerographs in the basement. At each of the four levels of the superstructure, three uniaxial accelerometers were deployed, two parallel and at a distance apart, and the third one orthogonal to the parallel pair. The records permit the identification of the predominantly coupled torsional‐translational response of the building and the associated frequency at approximately 0.7–0.8 Hz from the difference between accelerations recorded by the parallel pairs of accelerometers at different levels. This mode corresponds to the second torsional mode. A translational mode at 0.3 Hz is also identified from the records. The center of rigidity of any instrumented level is identified by minimizing the coherence between the relative accelerations and the translational acceleration. Employing system identification techniques provides the modal damping percentage for the second torsional mode as 6–7%.

California↗
USGS1991

Seismic response of transamerical building. I. Data and preliminary analysis

The objective of this paper is to present preliminary analyses of a set of acceleration response records obtained during the October 17, 1989 Loma Prieta earthquake (Ms = 7.1) from the 60-story vertically tapered, pyramid-shaped Trans-america Building-a landmark of San Francisco. The building was instrumented in 1985 with 22 channels of synchronized sensors consisting of 13 uniaxial accelerometers deployed throughout the structure and connected to a central recording system and three triaxial strong-motion accelerographs at three different levels of the structure. No free-field accelerographs are at the site. The acceleration records permit the study of the behavior of this unique structure. The predominant translational response of the building and the associated frequency at approximately 0.28 Hz are identified from the records and their Fourier amplitude spectra. The records do not indicate any significant torsional motion. However, there is rocking type soil-structure interaction, and an associated frequency of approximately 2.0 Hz is identified from the Fourier amplitude spectra of the differential motions between the ground level and that at the basement. In addition, the response spectra for the basement motions indicate significant resonance in both directions at a period of approximately 0.5 seconds.

Journal of Structural Engineering↗
USGS2023

The new Self Anchored Suspension (SAS) Bridge of the San Francisco Bay Bridge System: A preliminary study of its response and behavior during a small earthquake

Seismic behavior and performance of the new Self- Anchored Suspension (SAS) Bridge of the San Francisco Bay Bridge System is studied using response data recorded during the October 14, 2019, 𝑀𝑤⁢4.6 Pleasant Hill earthquake. The new bridge went into service within the last decade as a replacement for the older truss bridge that spanned between Yerba Buena Island and East Bay. During the October 19, 1989, M6.9 Loma Prieta earthquake, which occurred ∼100 km away from the Bay Bridge, a section of the upper deck of the old truss bridge fell onto the lower deck—thus closing this important lifeline between San Francisco and East Bay. The new SAS Bridge (as well as the rest of the Bay Bridge) is instrumented by the California Strong Motion Instrumentation Program (CSMIP). The unique SAS Bridge is suspended by a single tower that is pivotal in trafficking the cable and hanger system to support the eastbound (E) and westbound (W) decks. At both the west and east ends of the SAS, there is a hinge system that connects the W and E decks to the skyways leading to highways. For the west side, the SAS is led to a tunnel at Yerba Buena Island. The response data analyses highlight the complex and yet identifiable coupled response of the deck, tower, and cable system. Using system identification methods including spectral analyses of both acceleration and displacement time history data, the fundamental frequencies (periods) and critical damping percentages are extracted for the main components (tower, deck, and cables) of the bridge where the sensors are deployed. Frequencies (periods) are then compared with the values computed during the design and analysis process of the bridge. The analyses in this paper showed that there is strong evidence of a beating effect attributed to low critical damping percentages and coupled modes. A possible correlation of fundamental periods of such suspension bridges with their span lengths is discussed. The beating effect and period versus span length can be significant topics for further research.

California↗
USGS1971

Mapping from space

Remote sensing of the earth promises to become an operational tool of the engineer and the scientist within the next few years. There are no real technical limits on the uses of data from space sensors. However, it is not practical to fly special missions, particularly in space, for each specific use. General-purpose, earth-sensing missions aimed at meeting a wide variety of requirements must be defined. Engineers must help define earth-sensing missions, based on the concepts of repetitive coverage, multispectral response, and spatial correlation.

Journal of the Surveying and Mapping Division↗
USGS2000

Follow-ons to the KidSAT/EarthKAM student remote sensing program

The KidSAT/EarthKAM program is a NASA educational initiative that allows students to develop and operate a remote sensing space program. The first phase of the program consisted of a student developed camera that is flown on Space Shuttle missions in the nadir window. A network of students develop a series of image acquisition requests, based on approved science proposals, that are combined into a set of instrument commands that are uplinked to the space shuttle. Acquired images are downlinked and archived for student access in completing their research. The International Space Station provides a unique platform for the next generation of KidSAT/EarthKAM instruments, which will allow more students to participate in the program and enable development of more sophisticated instruments. Follow-on instruments consist of Earth-looking multispectral digital sensors mounted in the optical window and on the express pallet, and radar instruments located on the express pallet. Use of the International Space Station will allow routine data acquisition and enable the instrument to be part of regular science curricula unconstrained by the Space Shuttle launch schedule.

Conference Paper↗
USGS2008

Seismic monitoring to assess performance of structures In near‐real time: Recent progress

Earlier papers have described how observed data from classical accelerometers deployed in structures or from differential GPS with high sampling ratios deployed at roofs of tall buildings can be configured to establish seismic health monitoring of structures. In these configurations, drift ratios 1 are the main parametric indicator of damage condition of a structure or component of a structure. Real‐time measurement of displacements are acquired either by double integration of accelerometer time‐series data, or by directly using GPS. Recorded sensor data is then related to the performance level of a building. Performance‐based design method stipulates that for a building the amplitude of relative displacement of the roof of a building (with respect to its base) indicates its performance. Usually, drift ratio is computed using relative displacement between two consecutive floors. When accelerometers are used, a specific software is used to compute displacements and drift ratios in realtime by double integration of accelerometer data from several floors. However, GPS‐measured relative displacements are limited to being acquired only at the roof with respect to its reference base. Thus, computed drift ratio is the average drift ratio for the whole building. Until recently, the validity of measurements using GPS was limited to long‐period structures ( T >1  s ) "> ( T >1 s ) because GPS systems readily available were limited to 10–20 samples per seconds (sps) capability. However, presently, up to 50 sps differential GPS systems are available on the market and have been successfully used to monitor drift ratios [1,2]—thus enabling future usefulness of GPS to all types of structures. Several levels of threshold drift ratios can be postulated in order to make decisions for inspections and/or occupancy. Experience with data acquired from both accelerometers and GPS deployments indicates that they are reliable and provide pragmatic alternatives to alert the owners and other authorized parties to make informed decisions and select choices for pre‐defined actions following significant events.

Conference Paper↗
USGS2021

Expanding freshwater biologger studies to view fish as environmental sensing platforms

While recording fish habitat use by electronic sensors, biologgers can also be viewed as autonomous environmental monitoring systems with the organism as a vehicle. This dual perspective has provided novel results from marine ecosystems, but has not been applied to freshwater ecosystems. To understand limitations in fresh water, we evaluated miniature depth and temperature recorders as aquatic monitoring systems in a Laurentian Great Lake: Erie. As part of an acoustic telemetry study, biologgers were opportunistically implanted in a subsample of walleye Sander vitreus . Biologgers recorded temperature and depth at half-hour intervals for up to 1 year. Recaptures provided six biologgers for analysis of seasonal temperature patterns and lake stratification, key variables for understanding dimictic lakes. Depth-resolved temperature patterns showed close correspondence with independent weather buoy measurements. Because the buoy was deployed late in the season, biologger data provided improved estimates of the start of stratification, which had important implications for understanding development of hypoxia in the hypolimnion. Drawbacks to biologger data included imprecise knowledge of fish location and reliance on tag recoveries from the fishery. Optimistically, our results show how biologgers could be part of a monitoring approach that integrates limnological surveys with fisheries science.

Marine and Freshwater Research↗
USGS2014

Carnivore distributions across chaparral habitats exposed to wildfire and rural housing in southern California

Chaparral and coastal sage scrub habitats in southern California support biologically diverse plant and animal communities. However, native plant and animal species within these shrubland systems are increasingly exposed to human-caused wildfires and an expansion of the human–wildland interface. Few data exist to evaluate the effects of fire and anthropogenic pressures on plant and animal communities found in these environments. This is particularly true for carnivore communities. To address this knowledge gap, we collected detection–non-detection data with motion-sensor cameras and track plots to measure carnivore occupancy patterns following a large, human-caused wildfire (1134 km 2 ) in eastern San Diego County, California, USA, in 2003. Our focal species set included coyote ( Canis latrans ), gray fox ( Urocyon cinereoargenteus ), bobcat ( Lynx rufus ) and striped skunk ( Mephitis mephitis ). We evaluated the influence on species occupancies of the burned environment (burn edge, burn interior and unburned areas), proximity of rural homes, distance to riparian area and elevation. Gray fox occupancies were the highest overall, followed by striped skunk, coyote and bobcat. The three species considered as habitat and foraging generalists (gray fox, coyote, striped skunk) were common in all conditions. Occupancy patterns were consistent through time for all species except coyote, whose occupancies increased through time. In addition, environmental and anthropogenic variables had weak effects on all four species, and these responses were species-specific. Our results helped to describe a carnivore community exposed to frequent fire and rural human residences, and provide baseline data to inform fire management policy and wildlife management strategies in similar fire-prone ecosystems.

California↗
USGS2018

Time series of high-resolution images enhances efforts to monitor post-fire condition and recovery, Waldo Canyon fire, Colorado, USA

Interpretations of post-fire condition and rates of vegetation recovery can influence management priorities, actions and perception of latent risks from landslides and floods. In this study, we used the Waldo Canyon fire (2012, Colorado Springs, Colorado, USA) as a case study to explore how a time series (2011–2016) of high-resolution images can be used to delineate burn extent and severity, as well as quantify post-fire vegetation recovery. We applied an object-based approach to map burn severity and vegetation recovery using Worldview-2, Worldview-3 and QuickBird-2 imagery. The burned area was classified as 51% high, 20% moderate and 29% low burn-severity. Across the burn extent, the shrub cover class showed a rapid recovery, resprouting vigorously within 1 year, whereas 4 years post-fire, areas previously dominated by conifers were divided approximately equally between being classified as dominated by quaking aspen saplings with herbaceous species in the understorey or minimally recovered. Relative to using a pixel-based Normalised Difference Vegetation Index (NDVI), our object-based approach showed higher rates of revegetation. High-resolution imagery can provide an effective means to monitor post-fire site conditions and complement more prevalent efforts with moderate- and coarse-resolution sensors.

Colorado↗
USGS2010

The use of multi-temporal Landsat Normalized Difference Vegetation Index (NDVI) data for mapping fuels in Yosemite National Park, USA

The objective of this study was to test the applicability of using Normalized Difference Vegetation Index (NDVI) values derived from a temporal sequence of six Landsat Thematic Mapper (TM) scenes to map fuel models for Yosemite National Park, USA. An unsupervised classification algorithm was used to define 30 unique spectral-temporal classes of NDVI values. A combination of graphical, statistical and visual techniques was used to characterize the 30 classes and identify those that responded similarly and could be combined into fuel models. The final classification of fuel models included six different types: short annual and perennial grasses, tall perennial grasses, medium brush and evergreen hardwoods, short-needled conifers with no heavy fuels, long-needled conifers and deciduous hardwoods, and short-needled conifers with a component of heavy fuels. The NDVI, when analysed over a season of phenologically distinct periods along with ancillary data, can elicit information necessary to distinguish fuel model types. Fuels information derived from remote sensors has proven to be useful for initial classification of fuels and has been applied to fire management situations on the ground.

International Journal of Remote Sensing↗
USGS2010

A spatial regression procedure for evaluating the relationship between AVHRR-NDVI and climate in the northern Great Plains

The relationship between vegetation and climate in the grassland and cropland of the northern US Great Plains was investigated with Normalized Difference Vegetation Index (NDVI) (1989–1993) images derived from the Advanced Very High Resolution Radiometer (AVHRR), and climate data from automated weather stations. The relationship was quantified using a spatial regression technique that adjusts for spatial autocorrelation inherent in these data. Conventional regression techniques used frequently in previous studies are not adequate, because they are based on the assumption of independent observations. Six climate variables during the growing season; precipitation, potential evapotranspiration, daily maximum and minimum air temperature, soil temperature, solar irradiation were regressed on NDVI derived from a 10-km weather station buffer. The regression model identified precipitation and potential evapotranspiration as the most significant climatic variables, indicating that the water balance is the most important factor controlling vegetation condition at an annual timescale. The model indicates that 46% and 24% of variation in NDVI is accounted for by climate in grassland and cropland, respectively, indicating that grassland vegetation has a more pronounced response to climate variation than cropland. Other factors contributing to NDVI variation include environmental factors (soil, groundwater and terrain), human manipulation of crops, and sensor variation.

International Journal of Remote Sensing↗
USGS2010

Estimating suspended sediment concentrations in turbid coastal waters of the Santa Barbara Channel with SeaWiFS

A technique is presented for estimating suspended sediment concentrations of turbid coastal waters with remotely sensed multi-spectral data. The method improves upon many standard techniques, since it incorporates analyses of multiple wavelength bands (four for Sea-viewing Wide Field of view Sensor (SeaWiFS)) and a nonlinear calibration, which produce highly accurate results (expected errors are approximately ±10%). Further, potential errors produced by erroneous atmospheric calibration in excessively turbid waters and influences of dissolved organic materials, chlorophyll pigments and atmospheric aerosols are limited by a dark pixel subtraction and removal of the violet to blue wavelength bands. Results are presented for the Santa Barbara Channel, California where suspended sediment concentrations ranged from 0–200+ mg l −1 (±20 mg l −1 ) immediately after large river runoff events. The largest plumes were observed 10–30 km off the coast and occurred immediately following large El Niño winter floods.

California↗
USGS2007

Generation and validation of characteristic spectra from EO1 Hyperion image data for detecting the occurrence of the invasive species, Chinese tallow

Chinese tallow (Triadica sebifera) is an invasive tree that is spreading throughout the south-eastern United States and now into the west, and in many places causing extensive change to native habitat and associated wildlife. Detecting and mapping the relative distribution of this species is important to its control and eradication. To map the relative distribution of Chinese tallow within a southwestern Louisiana coastal wetland to upland environment, Earth Observing 1 (EO1) satellite Hyperion sensor hyperspectral image data were combined with a subpixel extraction method that modelled characteristic spectra from the image data without requiring a priori characteristic spectra. Because of the low percentage occurrences of Chinese tallow and high spectral covariation in the environment, unique validation and verification methods were implemented, relying on simultaneous collection of field canopy reflectance spectra and subsequent classification of canopy compositions. The subpixel extraction method produced five characteristic spectra, which we further refined to four that adequately represented the field spectra, as well as the Hyperion imaged canopy reflectance datasets. Characteristic spectra were designated as senescing foliage, cypress-tupelo trees, and trees without leaves; shadows and green vegetation; senescing Chinese tallow with yellow leaves and yellowing foliage; and senescing Chinese tallow with red leaves ('red tallow'). About 81% (n=34) of the field and 78% (n=33) of the Hyperion imaged characteristic spectra associated with 'red tallow' were explained by the compositions generated in the field slide classifications. ?? 2005 US Government.

International Journal of Remote Sensing↗
USGS2009

Global irrigated area map (GIAM), derived from remote sensing, for the end of the last millennium

A Global Irrigated Area Map (GIAM) has been produced for the end of the last millennium using multiple satellite sensor, secondary, Google Earth and groundtruth data. The data included: (a) Advanced Very High Resolution Radiometer (AVHRR) 3-band and Normalized Difference Vegetation Index (NDVI) 10 km monthly time-series for 1997-1999, (b) Syste me pour l'Observation de la Terre Vegetation (SPOT VGT) NDVI 1 km monthly time series for 1999, (c) East Anglia University Climate Research Unit (CRU) rainfall 50km monthly time series for 1961-2000, (d) Global 30 Arc-Second Elevation Data Set (GTOPO30) 1 km digital elevation data of the World, (e) Japanese Earth Resources Satellite-1 Synthetic Aperture Radar (JERS-1 SAR) data for the rain forests during two seasons in 1996 and (f) University of Maryland Global Tree Cover 1 km data for 1992-1993. A single mega-file data-cube (MFDC) of the World with 159 layers, akin to hyperspectral data, was composed by re-sampling different data types into a common 1 km resolution. The MFDC was segmented based on elevation, temperature and precipitation zones. Classification was performed on the segments. Quantitative spectral matching techniques (SMTs) used in hyperspectral data analysis were adopted to group class spectra derived from unsupervised classification and match them with ideal or target spectra. A rigorous class identification and labelling process involved the use of: (a) space-time spiral curve (ST-SC) plots, (b) brightness-greenness-wetness (BGW) plots, (c) time series NDVI plots, (d) Google Earth very-high-resolution imagery (VHRI) 'zoom-in views' in over 11 000 locations, (e) groundtruth data broadly sourced from the degree confluence project (3 864 sample locations) and from the GIAM project (1 790 sample locations), (f) high-resolution Landsat-ETM+ Geocover 150m mosaic of the World and (g) secondary data (e.g. national and global land use and land cover data). Mixed classes were resolved based on decision tree algorithms and spatial modelling, and when that did not work, the problem class was used to mask and re-classify the MDFC, and the class identification and labelling protocol repeated. The sub-pixel area (SPA) calculations were performed by multiplying full-pixel areas (FPAs) with irrigated area fractions (IAFs) for every class. A 28 class GIAM was produced and the area statistics reported as: (a) annualized irrigated areas (AIAs), which consider intensity of irrigation (i.e. sum of irrigated areas from different seasons in a year plus continuous year-round irrigation or gross irrigated areas), and (b) total area available for irrigation (TAAI), which does not consider intensity of irrigation (i.e. irrigated areas at any given point of time plus the areas left fallow but 'equipped for irrigation' at the same point of time or net irrigated areas). The AIA of the World at the end of the last millennium was 467 million hectares (Mha), which is sum of the non-overlapping areas of: (a) 252 Mha from season one, (b) 174 Mha from season two and (c) 41 Mha from continuous year-round crops. The TAAI at the end of the last millennium was 399 Mha. The distribution of irrigated areas is highly skewed amongst continents and countries. Asia accounts for 79% (370 Mha) of all AIAs, followed by Europe (7%) and North America (7%). Three continents, South America (4%), Africa (2%) and Australia (1%), have a very low proportion of the global irrigation. The GIAM had an accuracy of 79-91%, with errors of omission not exceeding 21%, and the errors of commission not exceeding 23%. The GIAM statistics were also compared with: (a) the United Nations Food and Agricultural Organization (FAO) and University of Frankfurt (UF) derived irrigated areas and (b) national census data for India. The relationships and causes of differences are discussed in detail. The GIAM products are made available through a web portal (http://www.iwmigiam.org). ?? 2009 Taylor & Francis.

International Journal of Remote Sensing↗
USGS2010

Accessing free Landsat data via the Internet: Africa's challenge

Since January 2008, the US Department of Interior/US Geological Survey has been providing terrain-corrected Landsat data over the Internet for free. This letter reports the size and proportion of the US Landsat archive that is over Africa by each Landsat sensor, discusses the implications of missing data and highlights the current bandwidth constraints on users accessing free Landsat data over the Internet from Africa.

Remote Sensing Letters↗
USGS2011

On the terminology of the spectral vegetation index (NIR – SWIR)/(NIR + SWIR)

The spectral vegetation index (ρNIR – ρSWIR)/(ρNIR + ρSWIR), where ρNIR and ρSWIR are the near-infrared (NIR) and shortwave-infrared (SWIR) reflectances, respectively, has been widely used to indicate vegetation moisture condition. This index has multiple names in the literature, including infrared index (II), normalized difference infrared index (NDII), normalized difference water index (NDWI), normalized difference moisture index (NDMI), land surface water index (LSWI), and normalized burn ratio (NBR), etc. After reviewing each term’s definition, associated sensors, and channel specifications, we found that the index consists of three variants, differing only in the SWIR region (1.2–1.3 µm, 1.55–1.75 µm, or 2.05–2.45 µm). Thus, three terms are sufficient to represent these three SWIR variants; other names are redundant and therefore unnecessary. Considering the spectral representativeness, the term’s popularity, and the “rule of priority” in scientific nomenclature, NDWI, NDII, and NBR, each corresponding to the three SWIR regions, are more preferable terms.

International Journal of Remote Sensing↗
USGS2013

Field calibration and validation of remote-sensing surveys

The Optical Collection Suite (OCS) is a ground-truth sampling system designed to perform in situ measurements that help calibrate and validate optical remote-sensing and swath-sonar surveys for mapping and monitoring coastal ecosystems and ocean planning. The OCS system enables researchers to collect underwater imagery with real-time feedback, measure the spectral response, and quantify the water clarity with simple and relatively inexpensive instruments that can be hand-deployed from a small vessel. This article reviews the design and performance of the system, based on operational and logistical considerations, as well as the data requirements to support a number of coastal science and management projects. The OCS system has been operational since 2009 and has been used in several ground-truth missions that overlapped with airborne lidar bathymetry (ALB), hyperspectral imagery (HSI), and swath-sonar bathymetric surveys in the Gulf of Maine, southwest Alaska, and the US Virgin Islands (USVI). Research projects that have used the system include a comparison of backscatter intensity derived from acoustic (multibeam/interferometric sonars) versus active optical (ALB) sensors, ALB bottom detection, and seafloor characterization using HSI and ALB.

Alaska↗