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At least 1,711 records · Page 95Linked to original sources

USGS1993

Compositing multitemporal remote sensing data sets

To eliminate cloud and atmosphere-affected pixels, the compositing of multi temporal remote sensing data sets is done by selecting the maximum vale of the normalized different vegetation index (NDVI) within a compositing period. The NDVI classifier, however, is strongly affected by surface type and anisotropic properties, sensor viewing geometries, and atmospheric conditions. Consequently, the composited, multi temporal, remote sensing data contain substantial noise from these external conditions. Consequently, the composited, multi temporal, remote sensing data contain substantial noise from these external effects. To improve the accuracy of compositing products, two key approaches can be taken: one is to refine the compositing classifier (NDVI) and the other is to improve existing compositing algorithms. In this project, an alternative classifier was developed and an alternative pixel selection criterion was proposed for compositing. The new classifier and the alternative compositing algorithm were applied to an advanced very high resolution radiometer data set of different biome types in the United States. The results were compared with the maximum value compositing and the best index slope extraction algorithms. The new approaches greatly reduced the high frequency noises related to the external factors and repainted more reliable data. The results suggest that the geometric-optical canopy properties of specific biomes may be needed in compositing. Limitations of the new approaches include the dependency of pixel selection on the length of the composite period and data discontinuity.

Pecora 12 Symposium↗

USGS1993

Raster profile development for the spatial data transfer standard

The Spatial Data Transfer Standard (SDTS), recently approved as Federal Information Processing Standard (FIPS) Publication 173, is designed to transfer various types of spatial data. Implementing all of the standard's options at one time is impractical. Profiles, or limited subsets of the SDTS, are the mechanisms by which the standards will be implemented. The development of a raster profile is being coordinated by the U.S. Geological Survey's (USGS) SDTS Task Force. This raster profile is intended to accommodate digital georeferenced image data and regularly spaces, georeferenced gridded data. The USGS's digital elevation models (DEMs) and digital orthophoto quadrangles (DOQs), National Oceanic and Atmospheric Administration's (NOAA) advanced very huh resolution radiometer (AVHRR) and Landsat data, and National Aeronautics and Space Administration's (NASA) Earth observing system (EOS) data are among the candidate data sets for this profile. Other raster profiles, designed to support nongeoreferenced and other types of "raw" sensor data will be consider in the future. As with the Topological Vector Profile (TVP) for the SDTS, development of the raster profile includes designing a prototype profile, testing the prototype profile using sample data sets, and finally, requesting and receiving FIPS approval.

Pecora 12 Symposium↗

USGS1993

Contrast enhancing and adjusting advanced very high resolution radiometer scenes for solar illumination

The AVHRR (Advanced Very High Resolution Radiometer) satellite sensors provide daily coverage of the entire Earth. As a result, individual scenes cover broad geographic areas (roughly 3000 km by 5000 km) and can contain varying levels of solar illumination. Mosaics of AVHRR scenes can be created for large (continental and global) study areas. As the north-south extent of such mosaics increases, the lightness variability within the mosaic increases. AVHRR channels one and two of multiple daytime scenes were histogrammed to find a relationship between solar zenith and scene lightness as described by brightness value distribution. This relationship was used to determine look-up tables (luts) which removed effects of varying solar illumination. These luts were combined with a contrast enhancing lut and stored online. For individual scenes, one precomputed composite lut was applied to the entire scene based on the solar zenith at scene center. For mosaicked scenes, each pixel was adjusted based on the solar zenith at that pixel location. These procedures reduce lightness variability within and between scenes and enhance scene contrast to provide visually pleasing imagery.

Pecora 12 Symposium↗

USGS2004

The LISST-SL streamlined isokinetic suspended-sediment profiler

The new manually deployed Laser In Situ Scattering Transmissometer-StreamLined profiler (LISST-SL) represents a major technological advance for suspended-sediment measurements in rivers. The LISST-SL is being designed to provide real-time data on sediment concentrations and particle-size distributions. A pressure sensor and current meter provide real-time depth and ambient velocity data, respectively. The velocity data are also used to control pumpage across an internal laser so that the intake velocity is constantly adjusted to match the ambient stream velocity. Such isokinetic withdrawal is necessary for obtaining representative sedimentary measurements in streamflow, and ensures compliance with established practices. The velocity and sediment-concentration data are used to compute fluxes for up to 32 particle-size classes at points, verticals, or in the entire stream cross section. All data are stored internally, as well as transmitted via a 2-wire conductor to the operator using a specially developed communication protocol. The LISST-SL's performance will be measured and compared to published sedimentological accuracy criteria, and a performance summary will be placed on-line.

Conference Paper↗

USGS2014

Unmanned aircraft systems (UAS) activities at the Department of the Interior

The U.S. Department of the Interior (DOI) is responsible for protecting and managing the natural resources and heritage on almost 20% of the land in the United States. The DOI’s mission requires access to remotely sensed data over vast lands, including areas that are remote and potentially dangerous to access. Unmanned Aircraft Systems (UAS) technology has the potential to enable the DOI to be a better steward of the land by: (1) Improving natural hazard forecasting and the analysis of the impacts. (2) Improving the understanding of climate change to better plan for likely impacts. (3) Developing precipitation and evaporation forecasting to better manage water resources. (4) Monitoring Arctic ice change and its impacts on ecosystems, coasts, and transportation. (5) Increasing safety and effectiveness of wildland fire management. (6) Enhancing search and rescue capabilities. (7) Broadening the abilities to monitor environmental or landscape conditions and changes. (8) Better understanding and protecting the Nation’s ecosystems. The initial operational testing and evaluations performed by the DOI have proven that UAS technology can be used to support many of the Department’s activities. UAS technology provides scientists a way to look longer, closer and more frequently at some of Earth’s most remote areas—places that were previously too dangerous or expensive to monitor in detail. The flexibility of operations and relative low cost to purchase and operate Small Unmanned Aerial System (sUAS) enhances the ability to track long-term landscape and environmental change. The initial testing indicates the operational costs are approximately 10% of traditional manned aircraft. In addition, users can quickly assess landscape-altering events such as wildland fires, floods and volcanoes. UAS technology will allow the DOI to do more with less and in the process enhance the Department’s ability to provide unbiased scientific information to help stakeholders make informed decisions. It will also provide a digital baseline record that can be archived and used when monitoring future events or conditions. One possible future scenario has scientists carrying sUAS into the field allowing quick deployment and operation to observe the environment or for emergency response. This scenario could also include a persistent monitoring capability provided by a UAS that can stay airborne over a small geographic area for days or weeks, or possibly longer. While the DOI focus is on sUAS, the Department recognizes that larger UAS systems will also play a role in meeting its mission. The Department anticipates meeting long-duration or specialized acquisition commitments, such as state or national aerial photography, by collaboration with other agencies or through commercial contracts. Even though the DOI continues to evaluate UAS and sensor technology to meet the Department’s mission, some of its bureaus are already moving towards an operational capability. The authors fully anticipate that by 2020 UAS will emerge as one of the primary platforms for DOI remote sensing applications.

Photogrammetric Engineering and Remote Sensing↗

USGS2006

Guided to gather: toy plane upgraded with telemetry

GPS/INS and infrared optical sensors propel USGS's transformation of a remote-controlled one-quarter scale recreational aircraft into a low-cost unmanned aerial vehicle designed for environmental particulate collection.

GPS World↗

USGS2014

U.S. Geological Survey external quality-assurance project report for the National Atmospheric Deposition Program / National Trends Network and Mercury Deposition Network, 2011-2012

The U.S. Geological Survey operated six distinct programs to provide external quality-assurance monitoring for the National Atmospheric Deposition Program (NADP) / National Trends Network (NTN) and Mercury Deposition Network (MDN) during 2011–2012. The field-audit program assessed the effects of onsite exposure, sample handling, and shipping on the chemistry of NTN samples; a system-blank program assessed the same effects for MDN. Two interlaboratory-comparison programs assessed the bias and variability of the chemical analysis data from the Central Analytical Laboratory and Mercury Analytical Laboratory (HAL). A blind-audit program was implemented for the MDN during 2011 to evaluate analytical bias in HAL total mercury concentration data. The co-located–sampler program was used to identify and quantify potential shifts in NADP data resulting from the replacement of original network instrumentation with new electronic recording rain gages and precipitation collectors that use optical precipitation sensors. The results indicate that NADP data continue to be of sufficient quality for the analysis of spatial distributions and time trends of chemical constituents in wet deposition across the United States. Co-located rain gage results indicate -3.7 to +6.5 percent bias in NADP precipitation-depth measurements. Co-located collector results suggest that the retrofit of the NADP networks with the new precipitation collectors could cause +10 to +36 percent shifts in NADP annual deposition values for ammonium, nitrate, and sulfate; -7.5 to +41 percent shifts for hydrogen-ion deposition; and larger shifts (-51 to +52 percent) for calcium, magnesium, sodium, potassium, and chloride. The prototype N-CON Systems bucket collector typically catches more precipitation than the NADP-approved Aerochem Metrics Model 301 collector.

Report↗

USGS2015

Estimating concentrations of fine-grained and total suspended sediment from close-range remote sensing imagery

Fluvial sediment, a vital surface water resource, is hazardous in excess. Suspended sediment, the most prevalent source of impairment of river systems, can adversely affect flood control, navigation, fisheries and aquatic ecosystems, recreation, and water supply (e.g., Rasmussen et al., 2009; Qu, 2014). Monitoring programs typically focus on suspended-sediment concentration (SSC) and discharge (SSQ). These time-series data are used to study changes to basin hydrology, geomorphology, and ecology caused by disturbances. The U.S. Geological Survey (USGS) has traditionally used physical sediment sample-based methods (Edwards and Glysson, 1999; Nolan et al., 2005; Gray et al., 2008) to compute SSC and SSQ from continuous streamflow data using a sediment transport-curve (e.g., Walling, 1977) or hydrologic interpretation (Porterfield, 1972). Accuracy of these data is typically constrained by the resources required to collect and analyze intermittent physical samples. Quantifying SSC using continuous instream turbidity is rapidly becoming common practice among sediment monitoring programs. Estimations of SSC and SSQ are modeled from linear regression analysis of concurrent turbidity and physical samples. Sediment-surrogate technologies such as turbidity promise near real-time information, increased accuracy, and reduced cost compared to traditional physical sample-based methods (Walling, 1977; Uhrich and Bragg, 2003; Gray and Gartner, 2009; Rasmussen et al., 2009; Landers et al., 2012; Landers and Sturm, 2013; Uhrich et al., 2014). Statistical comparisons among SSQ computation methods show that turbidity-SSC regression models can have much less uncertainty than streamflow-based sediment transport-curves or hydrologic interpretation (Walling, 1977; Lewis, 1996; Glysson et al., 2001; Lee et al., 2008). However, computation of SSC and SSQ records from continuous instream turbidity data is not without challenges; some of these include environmental fouling, calibration, and data range among sensors. Of greatest interest to many programs is a hysteresis in the relationship between turbidity and SSC, attributed to temporal variation of particle size distribution (Landers and Sturm, 2013; Uhrich et al., 2014). This phenomenon causes increased uncertainty in regression-estimated values of SSC, due to changes in nephelometric reflectance off the varying grain sizes in suspension (Uhrich et al., 2014). Here, we assess the feasibility and application of close-range remote sensing to quantify SSC and particle size distribution of a disturbed, and highly-turbid, river system. We use a consumer-grade digital camera to acquire imagery of the river surface and a depth-integrating sampler to collect concurrent suspended-sediment samples. We then develop two empirical linear regression models to relate image spectral information to concentrations of fine sediment (clay to silt) and total suspended sediment. Before presenting our regression model development, we briefly summarize each data-acquisition method.

Conference Paper↗

USGS1989

Investigations of SPOT cartographic applications in the U.S. Geological Survey

The US Geological Survey has a longstanding commitment to the advancement of the technology and applications of remotely sensed data from civilian satellite systems. In the past, research based on satellite data was primarily directed toward natural resource and land use applications rather than cartographic applications. The availability of high-resolution, steroscopic data from the sensors on SPOT provides new opportunities for cartographic applications. The potential applications include production of satellite image and topographic maps, and generation of digital elevation data.

CISM Journal ACSGC↗

USGS1988

Differences in visible and near-IR responses, and derived vegetation indices, for the NOAA-9 and NOAA-10 AVHRRs: a case study

This study evaluates the differences in the visible and near-IR responses of the Advanced Very High Resolution Radiometers (AVHRR) of the National Oceanic and Atmospheric Administration (NOAA)-9 and -10 satellites for coincident sample locations. The study also evaluates the differences in vegetation indices computed from those data. Data were acquired of the southeast portion of the United States for the 6 December 1986 daylight orbits of NOAA-9 and NOAA-10 satellites. The results suggest that, with appropriate gain and offset, the vegetation indices of the two sensor systems may be interchangeable for assessment of land surfaces.

Photogrammetric Engineering and Remote Sensing↗

USGS2015

Landsat Science Team meeting: Winter 2015

The summer meeting of the joint U.S. Geological Survey (USGS)–NASA Landsat Science Team (LST) was held at the USGS’s Earth Resources Observation and Science (EROS) Center July 7-9, 2015, in Sioux Falls, SD. The LST co-chairs, Tom Loveland [EROS—Senior Scientist] and Jim Irons [NASA’s Goddard Space Flight Center (GSFC)—Landsat 8 Project Scientist], opened the three-day meeting on an upbeat note following the recent successful launch of the European Space Agency’s Sentinel-2 mission on June 23, 2015 (see image on page 14), and the news that work on Landsat 9 has begun, with a projected launch date of 2023. With over 60 participants in attendance, this was the largest LST meeting ever held. Meeting topics on the first day included Sustainable Land Imaging and Landsat 9 development, Landsat 7 and 8 operations and data archiving, the Landsat 8 Thermal Infrared Sensor (TIRS) stray-light issue, and the successful Sentinel-2 launch. In addition, on days two and three the LST members presented updates on their Landsat science and applications research. All presentations are available at landsat.usgs.gov/science_LST_Team_ Meetings.php.

The Earth Observer↗

USGS2015

In situ densimetric measurements as a surrogate for suspended-sediment concentrations in the Rio Puerco, New Mexico

Surrogate measurements of suspended-sediment concentration (SSC) are increasingly used to provide continuous, high-resolution, and demonstrably accurate data at a reasonable cost. Densimetric data, calculated from the difference between two in situ pressure measurements, exploit variations in real-time streamflow densities to infer SSCs. Unlike other suspendedsediment surrogate technologies based on bulk or digital optics, laser, or hydroacoustics, the accuracy of SSC data estimated using the pressure-difference (also referred to as densimetric) surrogate technology theoretically improves with increasing SCCs. Coupled with streamflow data, continuous suspended-sediment discharges can be calculated using SSC data estimated in real-time using the densimetric technology. The densimetric technology was evaluated at the Rio Puerco in New Mexico, a stream where SSC values regularly range from 10,000-200,000 milligrams per liter (mg/L) and have exceeded 500,000 mg/L. The constant-flow dual-orifice bubbler measures pressure using two precision pressure-transducer sensors at vertically aligned fixed locations in a water column. Water density is calculated from the temperature-compensated differential pressure and SSCs are inferred from the density data. A linear regression model comparing density values to field-measured SSC values yielded an R² of 0.74. Although the application of the densimetric surrogate is likely limited to fluvial systems with SSCs larger than about 10,000 mg/L, based on this and previous studies, the densimetric technology fills a void for monitoring streams with high SSCs.

New Mexico↗

USGS2015

Suspended-sediment transport and storage: A demonstration of acoustic methods in the evaluation of reservoir management strategies for a small water-supply reservoir in western Colorado

The U.S. Bureau of Reclamation (USBR) and local stakeholder groups are evaluating reservoir-management strategies within Paonia Reservoir. This small reservoir fills to capacity each spring and requires approximately half of the snowmelt-runoff volume from its sediment-laden source waters, Muddy Creek. The U.S. Geological Survey is currently conducting high-resolution (15-minute data-recording interval) sediment monitoring to characterize incoming and outgoing sediment flux during reservoir operations at two sites on Muddy Creek. The high-resolution monitoring is being used to establish current rates of reservoir sedimentation, support USBR sediment transport and storage models, and assess the viability of water-storage recovery in Paonia Reservoir. These sites are equipped with in situ, single-frequency, side-looking acoustic Doppler current meters in conjunction with turbidity sensors to monitor sediment flux. This project serves as a demonstration of the capability of using surrogate techniques to predict suspended-sediment concentrations in small streams (less than 20 meters in width and 2 meters in depth). These two sites provide the ability to report near real-time suspended-sediment concentrations through the U.S. Geological Survey National Water Information System (NWIS) web interface and National Real-Time Water Quality websites (NRTWQ) to aid in reservoir operations and assessments.

Colorado↗

USGS2008

Deciphering landslide behavior using large-scale flume experiments

Landslides can be triggered by a variety of hydrologic events and they can exhibit a wide range of movement dynamics. Effective prediction requires understanding these diverse behaviors. Precise evaluation in the field is difficult; as an alternative we performed a series of landslide initiation experiments in the large-scale, USGS debris-flow flume. We systematically investigated the effects of three different hydrologic triggering mechanisms, including groundwater exfiltration from bedrock, prolonged rainfall infiltration, and intense bursts of rain. We also examined the effects of initial soil porosity (loose or dense) relative to the soil’s critical-state porosity. Results show that all three hydrologic mechanisms can instigate landsliding, but water pathways, sensor response patterns, and times to failure differ. Initial soil porosity has a profound influence on landslide movement behavior. Experiments using loose soil show rapid soil contraction during failure, with elevated pore pressures liquefying the sediment and creating fast-moving debris flows. In contrast, dense soil dilated upon shearing, resulting in slow, gradual, and episodic motion. These results have fundamental implications for forecasting landslide behavior and developing effective warning systems.

Conference Paper↗

USGS2012

Design and implementation of a structural health monitoring and alerting system for hospital buildings in the United States

This paper describes the current progress in the development of a structural health monitoring and alerting system to meet the needs of the U.S. Department of Veterans Affairs to monitor hospital buildings instrumented in high and very high seismic hazard regions in the U.S. The system, using the measured vibration data, is primarily designed for post-earthquake condition assessment of the buildings. It has two essential components – sensing and analysis. The sensing component includes all necessary firmware and sensors to measure the response of the building; while the analysis component consists of several data processing modules integrated into an open source software package which compresses a large amount of measured data into useful information to assess the building’s condition before and after an event. The information can be used for a rapid building safety assessment, and to support decisions for necessary repairs, replacements, and other maintenance and rehabilitation measures.

Conference Paper↗

USGS2015

A hidden view of wildlife conservation: How camera traps aid science, research and management

Florida panthers are among the world’s most endangered — and elusive — animals. For approximately four decades, scientists have been researching this small population of panthers that inhabit the dense forests and swamps of south Florida. Because of their wide habitat range along with an absence of clear visual features, these animals are difficult to detect and identify. In 2013, however, researchers released a study that used camera trap images collected between 2005 and 2007 to generate the first statistically reliable density estimates for the remaining population of this subspecies. Camera traps — remotely activated cameras with infrared sensors — first gained measurable popularity in wildlife conservation in the early 1990s. Today, they’re used for a variety of activities, from species-specific research to broad-scale inventory or monitoring programs that, in some cases, attempt to detect biodiversity across vast landscapes. As this modern tool continues to evolve, it’s worth examining its uses and benefits for wildlife management and conservation.

The Wildlife Professional↗

USGS2009

Use of multi-temporal Landsat images to monitor forest disturbance (1987-2007) in the Black Hills of South Dakota

Monitoring forest disturbance is important for studying carbon pools and fluxes. The goal of this study is to observe forest disturbance of different burn severity levels using multi-temporal Landsat images. The Jasper Fire occurred in the Black Hills National Forest, South Dakota, during August and September of 2000. The fire disturbance to ecosystem characteristics has a widespread and long-term impact. We used 18 Landsat images acquired from 1987 to 2007 to monitor the land cover changes due to the fire disturbance. The Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Normalized Burn Ratio (NBR), and Integrated Forest Index (IFI) were calculated from the Landsat at-sensor-reflectance data. Based on IFI in 2000 and Composite Burn Index data collected in May 2002, nine field plots were selected and monitored. The results showed that all four spectral indices were capable of detecting and monitoring the forest disturbance caused by thinning and fire. IFI and NBR are more suitable for long-term monitoring while NDVI and EVI are more sensitive to rapid changes within a one-year period.

South Dakota↗

USGS2015

Landsat science team meeting: Summer 2015

The Earth Observer↗