Results for “Sensors” — Page 71

USGS2021

Intelligent monitoring system for real-time geologic storage, optimization, and reservoir management

The objective of the subtask was to develop a near-real-time monitoring system for seismic data at the Decatur, IL, geologic carbon sequestration (GCS) site and specifically include fiber-optic cable derived distributed acoustic signal (DAS) data in the process. Owing to the large volumes of data, we opted to utilize existing deep borehole conventional seismic sensors for detection and pull DAS and shallow borehole seismic data once a detection has been made. Unfortunately, the horizontal fiber-optic cables did not yield microseismic signals for use in locating events near the GCS site. Various stacking and filtering approaches were tested without any coherent detection becoming apparent. We attribute the insensitivity to local microseismic events to a lack of coupling in downhole, vertical cable and the non-ideal alignment of the horizontal fiber-optic cable to the vertically polarized seismic energy. Despite the inability to detect and utilize the DAS data from the fiber-optic cables, we developed a general processing framework that enables easy adaptation for future deployment of fiber-optic cables with better suited alignment at Decatur or elsewhere.

Technical Report↗

USGS2019

Problems of Large Spatial Databases

Large spatial databases often labeled as geospatial big data exceed the capacity of commonly used computing systems as a result of data volume, variety, velocity, and veracity. Additional problems also labeled with V’s are cited, but the four primary ones are the most problematic and focus of this chapter (Li et al., 2016, Panimalar et al., 2017). Sources include satellites, aircraft and drone platforms, vehicles, geosocial networking services, mobile devices, and cameras. The problems in processing these data to extract useful information include query, analysis, and visualization. Data mining techniques and machine learning algorithms, such as deep convolutional neural networks, often are used with geospatial big data. The obvious problem is handling the large data volumes, particularly for input and output operations, requiring parallel read and write of the data, as well as high speed computers, disk services, and network transfer speeds. Additional problems of large spatial databases include the variety and heterogeneity of data requiring advanced algorithms to handle different data types and characteristics, and integration with other data. The velocity at which the data are acquired is a challenge, especially using today’s advanced sensors and the Internet of Things that includes millions of devices creating data on short temporal scales of micro seconds to minutes. Finally, the veracity, or truthfulness of large spatial databases is difficult to establish and validate, particularly for all data elements in the database.

Book chapter↗

USGS1976

Monitoring arctic habitat and goose production by satellite imagery

Spacecraft imagery, especially from the National Atmospheric and Oceanic Administration's Improved TIROS (Television Infra-Red Observational Satellite) Operational Satellites, permits timely evaluations of snow and ice conditions encountered by arctic nesting geese. Imagery from the TIROS satellite for 5 wide]y scattered locations in arctic North America was obtained for three 3-day intervals in June 1973 and 1974. These pictures were used to expand fragmentary habitat data available from ground observations. Late disappearance of snow and ice may prevent or retard nesting effort and reproductive success. Our immediate aim is to recognize years of catastrophic or very good production; however, supporting information from ground studies, LANDSAT imagery, analyses of banding data, and studies of age ratios in popu]ations and harvests eventua]]y may permit assessment of relative reproductive success. Satellite images from both Multi-Spectral Scanner and Very High Resolution Radiomder sensors were first used as management tools for consideration in setting the U.S. and Canadian regulations for the 1975-76 goose hunting season. Preliminary age ratio data from field observations and harvests substantiated the prediction of good production during the 1975 breeding season.

Journal of Wildlife Management↗

USGS1996

Reproductive success, growth and survival of black-crowned night-heron ( Nycticorax nycticorax ) and snowy egret ( Egretta thula ) chicks in coastal Virginia

We studied reproductive success, growth, and survival of Black-crowned Night-Heron ( Nycticorax nycticorax ) and Snowy Egret ( Egretta thula ) chicks in two mixed-species heronries on marsh islands in Chincoteague Bay, Accomack County, Virginia in 1992 and 1993. We attached radio transmitters with mortality sensors to the oldest chicks (A-chicks) in 11 to 22 nests of both species to monitor survival during the mid- to late nestling period and into the postnesting dispersal period. For both species, we found significant differences between 1992 and 1993 in growth rates and survival. Mass growth rates of chicks were higher in 1993 than in 1992 for both species. Culmen-length growth rates varied significantly due to year-colony effects for night-herons, but only for hatching order for egrets. Differences in survival rates due to hatching order were found for the egrets in both years, but were found only in 1992 for night-herons. As with mass growth rates, survival of chicks was higher in 1993 than 1992. Survival of radio-marked A-chicks did not differ between species or years for the period from hatching to fledging or from fledging through the end of the study (ca. two months postfledging). Survival ranged from 0.80 to 1.00 from the time radio transmitters were attached (ca. two weeks of age) until dispersal age (53-55 days for egrets; 55-60 days for night-herons). After birds left the colony, survival rates were lower during the next 40 to 55 days, ranging from 0.25 to 0.60. These results suggest that, at least for Snowy Egrets, A-chicks may be buffered from annual variations in food conditions, but that growth and survival of other brood members may provide a barometer of local conditions. Despite problems of variability in measurement, some of these parameters show promise as bioindicators of estuarine conditions. We recommend that a cost-efficient wading-bird monitoring program would include: (1) estimating numbers of nesting birds of selected species (e.g. Snowy Egrets) at particular estuaries, and (2) monitoring "initial brood sizes" and survival of young to at least two weeks of age in a sample of nests for each focal species. However, additional biomonitoring (e.g. marsh forage fish, contaminant loads) is necessary to evaluate how well top trophic-level organisms such as fish-eating birds respond to changes in estuarine production or quality.

The Auk↗

USGS2023

Biophysical warming patterns of an open-top chamber and its short-term influence on a Phragmites wetland ecosystem in China

Passive-warming, open-top chambers (OTCs) are widely applied for studying the effects of future climate warming on coastal wetlands. In this study, a set of six OTCs were established at a Phragmites wetland located in the Yellow River Delta of Dongying City, China. With data collected through online transmission and in-situ sensors, the attributes and patterns of realized OTCs warming are demonstrated. The authors also quantified the preliminary influence of experimental chamber warming on plant traits. OTCs produced an elevated average air temperature of 0.8°C (relative to controls) during the growing season (June to October) of 2018, and soil temperatures actually decreased by 0.54°C at a depth of 5 cm and 0.46°C at a depth of 30 cm in the OTCs. Variations in diel patterns of warming depend greatly on the heat sources of incoming radiation in the daytime versus soil heat flux at night. Warming effects were often larger during instantaneous analyses and influenced OTCs air temperatures from −2.5°C to 8.3°C dependent on various meteorological conditions at any given time, ranging from cooling influences from vertical heat exchange and vegetation to radiation-associated warming. Night-time temperature depressions in the OTCs were due to the low turbulence inside OTCs and changes in surface soil-atmosphere heat transfer. Plant shoot density, basal diameter, and biomass of Phragmites decreased by 23.2%, 6.3%, and 34.0%, respectively, under experimental warming versus controls, and plant height increased by 4.3%, reflecting less carbon allocation to stem structures as plants in the OTCs experienced simultaneous wind buffering. While these passive-warming OTCs created the desired warming effects both to the atmosphere and soils, pest damages on the plant leaves and lodging within the OTCs were extensive and serious, creating the need to consider control options for these chambers and the replicated OTCs studies underway in other Chinese Phragmites marshes (Panjin and Yancheng).

Shandong Province↗

USGS1973

Autographic theme extraction

Remote-sensor images, including aerial and space photographs, are generally recorded on film, where the differences in density create the image of the scene. With panchromatic and multiband systems the density differences are recorded in shades of gray. On color or color infrared film, with the emulsion containing dyes sensitive to different wavelengths, a color image is created by a combination of color densities. The colors, however, can be separated by filtering or other techniques, and the color image reduced to monochromatic images in which each of the separated bands is recorded as a function of the gray scale.

General Interest Publication↗

USGS1975

Interpretation, compilation and field verification procedures in the CARETS project

The production of the CARETS map data base involved the development of a series of procedures for interpreting, compiling, and verifying data obtained from remote sensor sources. Level II land use mapping from high-altitude aircraft photography at a scale of 1:100,000 required production of a photomosaic mapping base for each of the 48, 50 x 50 km sheets, and the interpretation and coding of land use polygons on drafting film overlays. CARETS researchers also produced a series of 1970 to 1972 land use change overlays, using the 1970 land use maps and 1972 high-altitude aircraft photography. To enhance the value of the land use sheets, researchers compiled series of overlays showing cultural features, county boundaries and census tracts, surface geology, and drainage basins. In producing Level I land use maps from Landsat imagery, at a scale of 1:250,000, interpreters overlaid drafting film directly on Landsat color composite transparencies and interpreted on the film. They found that such interpretation involves pattern and spectral signature recognition. In studies using Landsat imagery, interpreters identified numerous areas of change but also identified extensive areas of "false change," where Landsat spectral signatures but not land use had changed.

Delaware;Maryl;New Jersey;North Carolina;Pennsylva↗

USGS2012

Upper Klamath Basin Landsat Image for April 7, 2004: Path 44 Row 31

This subset of a Landsat-5 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Oregon↗

USGS2012

Upper Klamath Basin Landsat Image for April 29, 2006: Path 44 Row 31

This subset of a Landsat-5 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Oregon↗

USGS2012

Upper Klamath Basin Landsat Image for April 30, 2004: Path 45 Rows 30 and 31

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Oregon↗

USGS2012

Upper Klamath Basin Landsat Image for May 25, 2004: Path 44 Row 31

This subset of a Landsat-5 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Oregon↗

USGS2012

Upper Klamath Basin Landsat Image for June 1, 2004: Path 45 Rows 30 and 31

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Oregon↗

USGS2012

Upper Klamath Basin Landsat Image for June 16, 2006: Path 44 Row 31

This subset of a Landsat-5 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Oregon↗

USGS2012

Upper Klamath Basin Landsat Image for June 17, 2004: Path 45 Rows 30 and 31

This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Oregon↗

USGS2012

Upper Klamath Basin Landsat Image for June 24, 2006: Path 44 Row 31

This subset of a Landsat-7 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-7 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-7 on April 15, 1999 marks the addition of the latest satellite to the Landsat series. The Landsat-7 satellite carries the Enhanced Thematic Mapper Plus (ETM+) sensor. A mechanical failure of the ETM+ Scan Line Corrector (SLC) occurred on May 31, 2003, with the result that all Landsat 7 scenes acquired from July 14, 2003 to present have been collected in 'SLC-off' mode. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Oregon↗

USGS2012

Upper Klamath Basin Landsat Image for June 26, 2004: Path 44 Row 31

This subset of a Landsat-5 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Oregon↗

USGS2012

Upper Klamath Basin Landsat Image for July 2, 2006: Path 44 Row 31

This subset of a Landsat-5 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Oregon↗

USGS2012

Upper Klamath Basin Landsat Image for July 10, 2006: Path 44 Row 31

This subset of a Landsat-7 image shows part of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-7 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-7 on April 15, 1999 marks the addition of the latest satellite to the Landsat series. The Landsat-7 satellite carries the Enhanced Thematic Mapper Plus (ETM+) sensor. A mechanical failure of the ETM+ Scan Line Corrector (SLC) occurred on May 31, 2003, with the result that all Landsat 7 scenes acquired from July 14, 2003 to present have been collected in 'SLC-off' mode. More information on the Landsat program can be found online at http://landsat.usgs.gov/.

Oregon↗