Results for “Scanning” — Page 8

USGS2018

Effectiveness of ultrasonic imaging for evaluating presence and maturity of eggs in fishes in remote field locations

Ultrasonic imaging is an effective, nonlethal method used to determine sex and maturity in a variety of fishes. However, many previous studies of this technique have been performed in laboratory environments. Using Common Carp Cyprinus carpio , we developed a standardized method for ultrasonically scanning cyprinids, and we accurately sexed 78% ( N = 58) of those individuals. We then applied this method to endangered Humpback Chub Gila cypha and obtained 751 scans of Humpback Chub in remote field locations within the Grand Canyon, Arizona. Ultrasonic scanning took less than 1 min per fish to perform, and we identified females containing eggs based on two jpeg images and one 10-s video clip. Using ImageJ software to evaluate ultrasonic scans of ovulatory, captive Humpback Chub, we determined that female fish were potentially ovulatory when scanned eggs exhibited an ImageJ brightness value within the range of 32–44. Although we could successfully evaluate egg maturity, we were unable to estimate egg mass. Fisheries managers can use this noninvasive scanning method or a similar technique in remote field locations to collect ultrasonic scans from cyprinids to determine their reproductive status.

North American Journal of Fisheries Management↗

USGS1992

Map showing sediment isopachs in the deep-sea basins of the Pacific continental margin, Point Conception to Point Loma

The U.S. Geological Survey conducted a series of cruises, EEZSCAN 84 (EEZ-SCAN 84 Scientific Staff, 1986), to collect reconnaissance data on the newly proclaimed Exclusive Economic Zone (EEZ), the area out to 200 nautical miles from the coastline of the United States. The cruises systematically surveyed the entire conterminous United States west coast EEZ using the Geological Long-Range Inclined Asdic (GLORIA) side-scan sonar, a 160-in 3 airgun seismic-reflection profiler, a 3.5-kHz high-resolution seismic-reflection profiler, a 10-kHz echo sounder, and a proton-precession magnetometer. The nominal trackline spacing throughout the survey was 30 km. Derivative maps of sediment thickness (I-2089-A, I-2090-A, I-2091-A) and depth to basement (I-2089-B, I-2090-B, I-2091-B) in the basins of the west coast EEZ were compiled from both the sonar-image dala and the deep-penetration seismic data obtained on these cruises. Only EEZ-SCAN 84 data were used for the map compilations because available data from other cruises in this region are sparsely located, have poor navigational control, or were obtained with seismic systems that were not powerful enough to resolve oceanic basement. For this map series, sediment thickness and depth to basement were determined only in the deep-ocean basin regions because the seismic system used on the EEZ-SCAN 84 cruises could not resolve oceanic basement beneath the thick sediments of the continental slope. All the data used to compile the maps are presented in the "Atlas of the Exclusive Economic Zone, Western Conterminous United States" (EEZ-SCAN 84 Scientific Staff, 1986). Basement Outcrops GLORIA imagery was used to locate areas of basement outcrop throughout the region. Where possible, sediment thickness on and immediately adjacent to basement outcrops was measured from seismic data. Where there was no bathymetric or seismic control, a seamount peak was assumed to have no sediment cover. A pattern is used on the map to indicate all basement outcrops. Data Reduction Acoustic basement in the basins, invariably oceanic Layer 2, was observed on all of the seismic records. One-way traveltime was measured from the sea floor to acoustic basement. Because the trackline spacing of about 30 km is relatively large compared to the data density along track, we chose to measure the sediment thickness every 0.5 hour or at an interval of approximately 7.5 km. Water depth was measured with a 10-kHz profiler. Depth to basement was calculated using the sea surface as the zero datum and adding the corrected water depth (Carter, 1980) to the sediment thickness. Acoustic travel times were converted to depths by first calculating a regression equation from the interval velocity versus depth data of Connard and others (1984). Their data base comprises a compilation of all available Deep Sea Drilling Project data plus wide-angle refraction data, which were collected in Cascadia Basin west of Oregon and represents the best data set available for the United States west coast EEZ. The regression equation was integrated to determine sediment thickness as a function of one-way traveltime . The resulting equation is z = 1400t + 0 .5t 2 where z is sediment thickness in meters, and t is one-way traveltime in seconds. Sediment thicknesses calculated using this equation were compared to values calculated from the general equation of Carlson and others (1986). Values for sediment thickness calculated by the two equations differed by no greater than 10 percent throughout the range of travel times. Bathymetry The bathymetry is from Chase and others (1981). The bathymetric data were compiled from a variety of sources, and data quality is inconsistent. Because of differences in navigational precision and density of coverage, the bathymetric contours of a feature may be at a different location than the corresponding isopleths derived from the EEZ-SCAN 84 data, or a feature may not be indicated on the bathymetry at all. These situations occur because either the feature is poorly located in the bathymetric data set or, especially in the outer EEZ, the bathymetric data are too sparse to have defined the existence of a feature. Acknowledgments Topographic digital data bases were corrected and verified by Christina Lief. Gerald Evenden developed the computer software system MAPGEN, used to compose this map. Reviews, suggestions, and technical contributions from Edward C. Escowitz and Florence Wong and advice about cartographic design from Will Stettner substantially improved the quality of this map. References Cited Carlson, R.L., Gangi, A.F., and Snow, K.R., 1986, Empirical reflection-traveltime/ depth and velocity/depth functions for the deep-sea sediment column: Journal of Geophysical Research, v. 91, no. B8, p. 8249-8266. Carter, D.J.T., 1980, Echo-sounding correction tables: Taunton, United Kingdom, Hydrographic Department, Ministry of Defence, 150 p. Chase, T.E., Wilde, Pat, Normark, W.R, Miller, C.P., Seekins, B.A., and Young, J.D., 1981, Offshore topography of the Western United States between 32° and 49° North latitudes: U.S. Geological Survey Open-File Report 81-443, scale 1:864,518 at 38° latitude, 2 sheets. Connard, G., Couch, R., Keeling , K., Roy, J., and Troseth, S., 1984, Abyssal plain and continental net-objective sedimentary thicknesses, in Kulm, L.D., and others, eds., Western North America continental margin and adjacent ocean floor off Oregon and Washington, Atlas 1 of Regional Atlas Series, Ocean Margin Drilling Program: Woods Hole, Mass., Marine Science International, sheet 7. EEZ-SCAN 84 Scientific Staff, 1986, Atlas of the Exclusive Economic Zone, Western Conterminous United States: U.S. Geological Survey Miscellaneous Investigations Series I-1792, scale 1:500,000, 152 p. index map for I-2089-A See Also "U.S. Pacific West Coast Field Activities" (Paskevich and others, 2011; http://pubs.usgs.gov/of/2010/1332/htmldocs/pc/pc_overview.html). Paskevich, V.F., Wong, F.L., O?Malley, J.J., Stevenson, A.J., and Gutmacher, C.E., 2011, GLORIA sidescan-sonar imagery for parts of the U.S. Exclusive Economic Zone and adjacent areas: U.S. Geological Survey Open-File Report 2010?1332, available at http://pubs.usgs.gov/of/2010/1332/.

IMAP↗

USGS1992

Map showing depth to basement in the deep-sea basins of the Pacific continental margin, Point Conception to Point Loma

The U.S. Geological Survey conducted a series of cruises, EEZSCAN 84 (EEZ-SCAN 84 Scientific Staff, 1986), to collect reconnaissance data on the newly proclaimed Exclusive Economic Zone (EEZ), the area out to 200 nautical miles from the coastline of the United States. The cruises systematically surveyed the entire conterminous United States west coast EEZ using the Geological Long-Range Inclined Asdic (GLORIA) side-scan sonar, a 160-in 3 airgun seismic-reflection profiler, a 3.5-kHz high-resolution seismic-reflection profiler, a 10-kHz echo sounder, and a proton-precession magnetometer. The nominal trackline spacing throughout the survey was 30 km. Derivative maps of sediment thickness (I-2089-A, I-2090-A, I-2091-A) and depth to basement (I-2089-B, I-2090-B, I-2091-B) in the basins of the west coast EEZ were compiled from both the sonar-image dala and the deep-penetration seismic data obtained on these cruises. Only EEZ-SCAN 84 data were used for the map compilations because available data from other cruises in this region are sparsely located, have poor navigational control, or were obtained with seismic systems that were not powerful enough to resolve oceanic basement. For this map series, sediment thickness and depth to basement were determined only in the deep-ocean basin regions because the seismic system used on the EEZ-SCAN 84 cruises could not resolve oceanic basement beneath the thick sediments of the continental slope. All the data used to compile the maps are presented in the "Atlas of the Exclusive Economic Zone, Western Conterminous United States" (EEZ-SCAN 84 Scientific Staff, 1986). Basement Outcrops GLORIA imagery was used to locate areas of basement outcrop throughout the region. Where possible, sediment thickness on and immediately adjacent to basement outcrops was measured from seismic data. Where there was no bathymetric or seismic control, a seamount peak was assumed to have no sediment cover. A pattern is used on the map to indicate all basement outcrops. Data Reduction Acoustic basement in the basins, invariably oceanic Layer 2, was observed on all of the seismic records. One-way traveltime was measured from the sea floor to acoustic basement. Because the trackline spacing of about 30 km is relatively large compared to the data density along track, we chose to measure the sediment thickness every 0.5 hour or at an interval of approximately 7.5 km. Water depth was measured with a 10-kHz profiler. Depth to basement was calculated using the sea surface as the zero datum and adding the corrected water depth (Carter, 1980) to the sediment thickness. Acoustic travel times were converted to depths by first calculating a regression equation from the interval velocity versus depth data of Connard and others (1984). Their data base comprises a compilation of all available Deep Sea Drilling Project data plus wide-angle refraction data, which were collected in Cascadia Basin west of Oregon and represents the best data set available for the United States west coast EEZ. The regression equation was integrated to determine sediment thickness as a function of one-way traveltime . The resulting equation is z = 1400t + 0 .5t 2 where z is sediment thickness in meters, and t is one-way traveltime in seconds. Sediment thicknesses calculated using this equation were compared to values calculated from the general equation of Carlson and others (1986). Values for sediment thickness calculated by the two equations differed by no greater than 10 percent throughout the range of travel times. Bathymetry The bathymetry is from Chase and others (1981). The bathymetric data were compiled from a variety of sources, and data quality is inconsistent. Because of differences in navigational precision and density of coverage, the bathymetric contours of a feature may be at a different location than the corresponding isopleths derived from the EEZ-SCAN 84 data, or a feature may not be indicated on the bathymetry at all. These situations occur because either the feature is poorly located in the bathymetric data set or, especially in the outer EEZ, the bathymetric data are too sparse to have defined the existence of a feature. Acknowledgments Topographic digital data bases were corrected and verified by Christina Lief. Gerald Evenden developed the computer software system MAPGEN, used to compose this map. Reviews, suggestions, and technical contributions from Edward C. Escowitz and Florence Wong and advice about cartographic design from Will Stettner substantially improved the quality of this map. References Cited Carlson, R.L., Gangi, A.F., and Snow, K.R., 1986, Empirical reflection-traveltime/ depth and velocity/depth functions for the deep-sea sediment column: Journal of Geophysical Research, v. 91, no. B8, p. 8249-8266. Carter, D.J.T., 1980, Echo-sounding correction tables: Taunton, United Kingdom, Hydrographic Department, Ministry of Defence, 150 p. Chase, T.E., Wilde, Pat, Normark, W.R, Miller, C.P., Seekins, B.A., and Young, J.D., 1981, Offshore topography of the Western United States between 32° and 49° North latitudes: U.S. Geological Survey Open-File Report 81-443, scale 1:864,518 at 38° latitude, 2 sheets. Connard, G., Couch, R., Keeling , K., Roy, J., and Troseth, S., 1984, Abyssal plain and continental net-objective sedimentary thicknesses, in Kulm, L.D., and others, eds., Western North America continental margin and adjacent ocean floor off Oregon and Washington, Atlas 1 of Regional Atlas Series, Ocean Margin Drilling Program: Woods Hole, Mass., Marine Science International, sheet 7. EEZ-SCAN 84 Scientific Staff, 1986, Atlas of the Exclusive Economic Zone, Western Conterminous United States: U.S. Geological Survey Miscellaneous Investigations Series I-1792, scale 1:500,000, 152 p. index map for I-2089-A See Also "U.S. Pacific West Coast Field Activities" (Paskevich and others, 2011; http://pubs.usgs.gov/of/2010/1332/htmldocs/pc/pc_overview.html). Paskevich, V.F., Wong, F.L., O?Malley, J.J., Stevenson, A.J., and Gutmacher, C.E., 2011, GLORIA sidescan-sonar imagery for parts of the U.S. Exclusive Economic Zone and adjacent areas: U.S. Geological Survey Open-File Report 2010?1332, available at http://pubs.usgs.gov/of/2010/1332/.

IMAP↗

USGS1993

Map showing sediment isopachs in the deep-sea basins of the Pacific continental margin, Cape Mendocino to Point Conception

The U.S. Geological Survey conducted a series of cruises, EEZSCAN 84 (EEZ-SCAN 84 Scientific Staff, 1986), to collect reconnaissance data on the newly proclaimed Exclusive Economic Zone (EEZ), the area out to 200 nautical miles from the coastline of the United States. The cruises systematically surveyed the entire conterminous United States west coast EEZ using the Geological Long-Range Inclined Asdic (GLORIA) side-scan sonar, a 160-in 3 airgun seismic-reflection profiler, a 3.5-kHz high-resolution seismic-reflection profiler, a 10-kHz echo sounder, and a proton-precession magnetometer. The nominal trackline spacing throughout the survey was 30 km. Derivative maps of sediment thickness (I-2089-A, I-2090-A, I-2091-A) and depth to basement (I-2089-B, I-2090-B, I-2091-B) in the basins of the west coast EEZ were compiled from both the sonar-image dala and the deep-penetration seismic data obtained on these cruises. Only EEZ-SCAN 84 data were used for the map compilations because available data from other cruises in this region are sparsely located, have poor navigational control, or were obtained with seismic systems that were not powerful enough to resolve oceanic basement. For this map series, sediment thickness and depth to basement were determined only in the deep-ocean basin regions because the seismic system used on the EEZ-SCAN 84 cruises could not resolve oceanic basement beneath the thick sediments of the continental slope. All the data used to compile the maps are presented in the "Atlas of the Exclusive Economic Zone, Western Conterminous United States" (EEZ-SCAN 84 Scientific Staff, 1986). Basement Outcrops GLORIA imagery was used to locate areas of basement outcrop throughout the region. Where possible, sediment thickness on and immediately adjacent to basement outcrops was measured from seismic data. Where there was no bathymetric or seismic control, a seamount peak was assumed to have no sediment cover. A pattern is used on the map to indicate all basement outcrops. Data Reduction Acoustic basement in the basins, invariably oceanic Layer 2, was observed on all of the seismic records. One-way traveltime was measured from the sea floor to acoustic basement. Because the trackline spacing of about 30 km is relatively large compared to the data density along track, we chose to measure the sediment thickness every 0.5 hour or at an interval of approximately 7.5 km. Water depth was measured with a 10-kHz profiler. Depth to basement was calculated using the sea surface as the zero datum and adding the corrected water depth (Carter, 1980) to the sediment thickness. Acoustic travel times were converted to depths by first calculating a regression equation from the interval velocity versus depth data of Connard and others (1984). Their data base comprises a compilation of all available Deep Sea Drilling Project data plus wide-angle refraction data, which were collected in Cascadia Basin west of Oregon and represents the best data set available for the United States west coast EEZ. The regression equation was integrated to determine sediment thickness as a function of one-way traveltime . The resulting equation is z = 1400t + 0 .5t 2 where z is sediment thickness in meters, and t is one-way traveltime in seconds. Sediment thicknesses calculated using this equation were compared to values calculated from the general equation of Carlson and others (1986). Values for sediment thickness calculated by the two equations differed by no greater than 10 percent throughout the range of travel times. Bathymetry The bathymetry is from Chase and others (1981). The bathymetric data were compiled from a variety of sources, and data quality is inconsistent. Because of differences in navigational precision and density of coverage, the bathymetric contours of a feature may be at a different location than the corresponding isopleths derived from the EEZ-SCAN 84 data, or a feature may not be indicated on the bathymetry at all. These situations occur because either the feature is poorly located in the bathymetric data set or, especially in the outer EEZ, the bathymetric data are too sparse to have defined the existence of a feature. Acknowledgments Topographic digital data bases were corrected and verified by Christina Lief. Gerald Evenden developed the computer software system MAPGEN, used to compose this map. Reviews, suggestions, and technical contributions from Edward C. Escowitz and Florence Wong and advice about cartographic design from Will Stettner substantially improved the quality of this map. References Cited Carlson, R.L., Gangi, A.F., and Snow, K.R., 1986, Empirical reflection-traveltime/ depth and velocity/depth functions for the deep-sea sediment column: Journal of Geophysical Research, v. 91, no. B8, p. 8249-8266. Carter, D.J.T., 1980, Echo-sounding correction tables: Taunton, United Kingdom, Hydrographic Department, Ministry of Defence, 150 p. Chase, T.E., Wilde, Pat, Normark, W.R, Miller, C.P., Seekins, B.A., and Young, J.D., 1981, Offshore topography of the Western United States between 32° and 49° North latitudes: U.S. Geological Survey Open-File Report 81-443, scale 1:864,518 at 38° latitude, 2 sheets. Connard, G., Couch, R., Keeling , K., Roy, J., and Troseth, S., 1984, Abyssal plain and continental net-objective sedimentary thicknesses, in Kulm, L.D., and others, eds., Western North America continental margin and adjacent ocean floor off Oregon and Washington, Atlas 1 of Regional Atlas Series, Ocean Margin Drilling Program: Woods Hole, Mass., Marine Science International, sheet 7. EEZ-SCAN 84 Scientific Staff, 1986, Atlas of the Exclusive Economic Zone, Western Conterminous United States: U.S. Geological Survey Miscellaneous Investigations Series I-1792, scale 1:500,000, 152 p. See Also "U.S. Pacific West Coast Field Activities" (Paskevich and others, 2011; http://pubs.usgs.gov/of/2010/1332/htmldocs/pc/pc_overview.html). Paskevich, V.F., Wong, F.L., O?Malley, J.J., Stevenson, A.J., and Gutmacher, C.E., 2011, GLORIA sidescan-sonar imagery for parts of the U.S. Exclusive Economic Zone and adjacent areas: U.S. Geological Survey Open-File Report 2010?1332, available at http://pubs.usgs.gov/of/2010/1332/.

IMAP↗

USGS1993

Map showing depth to basement in the deep-sea basins of the Pacific continental margin, Cape Mendocino to Point Conception

The U.S. Geological Survey conducted a series of cruises, EEZSCAN 84 (EEZ-SCAN 84 Scientific Staff, 1986), to collect reconnaissance data on the newly proclaimed Exclusive Economic Zone (EEZ), the area out to 200 nautical miles from the coastline of the United States. The cruises systematically surveyed the entire conterminous United States west coast EEZ using the Geological Long-Range Inclined Asdic (GLORIA) side-scan sonar, a 160-in 3 airgun seismic-reflection profiler, a 3.5-kHz high-resolution seismic-reflection profiler, a 10-kHz echo sounder, and a proton-precession magnetometer. The nominal trackline spacing throughout the survey was 30 km. Derivative maps of sediment thickness (I-2089-A, I-2090-A, I-2091-A) and depth to basement (I-2089-B, I-2090-B, I-2091-B) in the basins of the west coast EEZ were compiled from both the sonar-image dala and the deep-penetration seismic data obtained on these cruises. Only EEZ-SCAN 84 data were used for the map compilations because available data from other cruises in this region are sparsely located, have poor navigational control, or were obtained with seismic systems that were not powerful enough to resolve oceanic basement. For this map series, sediment thickness and depth to basement were determined only in the deep-ocean basin regions because the seismic system used on the EEZ-SCAN 84 cruises could not resolve oceanic basement beneath the thick sediments of the continental slope. All the data used to compile the maps are presented in the "Atlas of the Exclusive Economic Zone, Western Conterminous United States" (EEZ-SCAN 84 Scientific Staff, 1986). Basement Outcrops GLORIA imagery was used to locate areas of basement outcrop throughout the region. Where possible, sediment thickness on and immediately adjacent to basement outcrops was measured from seismic data. Where there was no bathymetric or seismic control, a seamount peak was assumed to have no sediment cover. A pattern is used on the map to indicate all basement outcrops. Data Reduction Acoustic basement in the basins, invariably oceanic Layer 2, was observed on all of the seismic records. One-way traveltime was measured from the sea floor to acoustic basement. Because the trackline spacing of about 30 km is relatively large compared to the data density along track, we chose to measure the sediment thickness every 0.5 hour or at an interval of approximately 7.5 km. Water depth was measured with a 10-kHz profiler. Depth to basement was calculated using the sea surface as the zero datum and adding the corrected water depth (Carter, 1980) to the sediment thickness. Acoustic travel times were converted to depths by first calculating a regression equation from the interval velocity versus depth data of Connard and others (1984). Their data base comprises a compilation of all available Deep Sea Drilling Project data plus wide-angle refraction data, which were collected in Cascadia Basin west of Oregon and represents the best data set available for the United States west coast EEZ. The regression equation was integrated to determine sediment thickness as a function of one-way traveltime . The resulting equation is z = 1400t + 0 .5t 2 where z is sediment thickness in meters, and t is one-way traveltime in seconds. Sediment thicknesses calculated using this equation were compared to values calculated from the general equation of Carlson and others (1986). Values for sediment thickness calculated by the two equations differed by no greater than 10 percent throughout the range of travel times. Bathymetry The bathymetry is from Chase and others (1981). The bathymetric data were compiled from a variety of sources, and data quality is inconsistent. Because of differences in navigational precision and density of coverage, the bathymetric contours of a feature may be at a different location than the corresponding isopleths derived from the EEZ-SCAN 84 data, or a feature may not be indicated on the bathymetry at all. These situations occur because either the feature is poorly located in the bathymetric data set or, especially in the outer EEZ, the bathymetric data are too sparse to have defined the existence of a feature. Acknowledgments Topographic digital data bases were corrected and verified by Christina Lief. Gerald Evenden developed the computer software system MAPGEN, used to compose this map. Reviews, suggestions, and technical contributions from Edward C. Escowitz and Florence Wong and advice about cartographic design from Will Stettner substantially improved the quality of this map. References Cited Carlson, R.L., Gangi, A.F., and Snow, K.R., 1986, Empirical reflection-traveltime/ depth and velocity/depth functions for the deep-sea sediment column: Journal of Geophysical Research, v. 91, no. B8, p. 8249-8266. Carter, D.J.T., 1980, Echo-sounding correction tables: Taunton, United Kingdom, Hydrographic Department, Ministry of Defence, 150 p. Chase, T.E., Wilde, Pat, Normark, W.R, Miller, C.P., Seekins, B.A., and Young, J.D., 1981, Offshore topography of the Western United States between 32° and 49° North latitudes: U.S. Geological Survey Open-File Report 81-443, scale 1:864,518 at 38° latitude, 2 sheets. Connard, G., Couch, R., Keeling , K., Roy, J., and Troseth, S., 1984, Abyssal plain and continental net-objective sedimentary thicknesses, in Kulm, L.D., and others, eds., Western North America continental margin and adjacent ocean floor off Oregon and Washington, Atlas 1 of Regional Atlas Series, Ocean Margin Drilling Program: Woods Hole, Mass., Marine Science International, sheet 7. EEZ-SCAN 84 Scientific Staff, 1986, Atlas of the Exclusive Economic Zone, Western Conterminous United States: U.S. Geological Survey Miscellaneous Investigations Series I-1792, scale 1:500,000, 152 p. See Also "U.S. Pacific West Coast Field Activities" (Paskevich and others, 2011; http://pubs.usgs.gov/of/2010/1332/htmldocs/pc/pc_overview.html). Paskevich, V.F., Wong, F.L., O?Malley, J.J., Stevenson, A.J., and Gutmacher, C.E., 2011, GLORIA sidescan-sonar imagery for parts of the U.S. Exclusive Economic Zone and adjacent areas: U.S. Geological Survey Open-File Report 2010?1332, available at http://pubs.usgs.gov/of/2010/1332/.

IMAP↗

USGS1993

Map showing sediment isopachs in the deep-sea basins of the Pacific Continental Margin, Strait of Juan de Fuca to Cape Mendocino

The U.S. Geological Survey conducted a series of cruises, EEZSCAN 84 (EEZ-SCAN 84 Scientific Staff, 1986), to collect reconnaissance data on the newly proclaimed Exclusive Economic Zone (EEZ), the area out to 200 nautical miles from the coastline of the United States. The cruises systematically surveyed the entire conterminous United States west coast EEZ using the Geological Long-Range Inclined Asdic (GLORIA) side-scan sonar, a 160-in 3 airgun seismic-reflection profiler, a 3.5-kHz high-resolution seismic-reflection profiler, a 10-kHz echo sounder, and a proton-precession magnetometer. The nominal trackline spacing throughout the survey was 30 km. Derivative maps of sediment thickness (I-2089-A, I-2090-A, I-2091-A) and depth to basement (I-2089-B, I-2090-B, I-2091-B) in the basins of the west coast EEZ were compiled from both the sonar-image dala and the deep-penetration seismic data obtained on these cruises. Only EEZ-SCAN 84 data were used for the map compilations because available data from other cruises in this region are sparsely located, have poor navigational control, or were obtained with seismic systems that were not powerful enough to resolve oceanic basement. For this map series, sediment thickness and depth to basement were determined only in the deep-ocean basin regions because the seismic system used on the EEZ-SCAN 84 cruises could not resolve oceanic basement beneath the thick sediments of the continental slope. All the data used to compile the maps are presented in the "Atlas of the Exclusive Economic Zone, Western Conterminous United States" (EEZ-SCAN 84 Scientific Staff, 1986). Basement Outcrops GLORIA imagery was used to locate areas of basement outcrop throughout the region. Where possible, sediment thickness on and immediately adjacent to basement outcrops was measured from seismic data. Where there was no bathymetric or seismic control, a seamount peak was assumed to have no sediment cover. A pattern is used on the map to indicate all basement outcrops. Data Reduction Acoustic basement in the basins, invariably oceanic Layer 2, was observed on all of the seismic records. One-way traveltime was measured from the sea floor to acoustic basement. Because the trackline spacing of about 30 km is relatively large compared to the data density along track, we chose to measure the sediment thickness every 0.5 hour or at an interval of approximately 7.5 km. Water depth was measured with a 10-kHz profiler. Depth to basement was calculated using the sea surface as the zero datum and adding the corrected water depth (Carter, 1980) to the sediment thickness. Acoustic travel times were converted to depths by first calculating a regression equation from the interval velocity versus depth data of Connard and others (1984). Their data base comprises a compilation of all available Deep Sea Drilling Project data plus wide-angle refraction data, which were collected in Cascadia Basin west of Oregon and represents the best data set available for the United States west coast EEZ. The regression equation was integrated to determine sediment thickness as a function of one-way traveltime . The resulting equation is z = 1400t + 0 .5t 2 where z is sediment thickness in meters, and t is one-way traveltime in seconds. Sediment thicknesses calculated using this equation were compared to values calculated from the general equation of Carlson and others (1986). Values for sediment thickness calculated by the two equations differed by no greater than 10 percent throughout the range of travel times. Bathymetry The bathymetry is from Chase and others (1981). The bathymetric data were compiled from a variety of sources, and data quality is inconsistent. Because of differences in navigational precision and density of coverage, the bathymetric contours of a feature may be at a different location than the corresponding isopleths derived from the EEZ-SCAN 84 data, or a feature may not be indicated on the bathymetry at all. These situations occur because either the feature is poorly located in the bathymetric data set or, especially in the outer EEZ, the bathymetric data are too sparse to have defined the existence of a feature. Acknowledgments Topographic digital data bases were corrected and verified by Christina Lief. Gerald Evenden developed the computer software system MAPGEN, used to compose this map. Reviews, suggestions, and technical contributions from Edward C. Escowitz and Florence Wong and advice about cartographic design from Will Stettner substantially improved the quality of this map. References Cited Carlson, R.L., Gangi, A.F., and Snow, K.R., 1986, Empirical reflection-traveltime/ depth and velocity/depth functions for the deep-sea sediment column: Journal of Geophysical Research, v. 91, no. B8, p. 8249-8266. Carter, D.J.T., 1980, Echo-sounding correction tables: Taunton, United Kingdom, Hydrographic Department, Ministry of Defence, 150 p. Chase, T.E., Wilde, Pat, Normark, W.R, Miller, C.P., Seekins, B.A., and Young, J.D., 1981, Offshore topography of the Western United States between 32° and 49° North latitudes: U.S. Geological Survey Open-File Report 81-443, scale 1:864,518 at 38° latitude, 2 sheets. Connard, G., Couch, R., Keeling , K., Roy, J., and Troseth, S., 1984, Abyssal plain and continental net-objective sedimentary thicknesses, in Kulm, L.D., and others, eds., Western North America continental margin and adjacent ocean floor off Oregon and Washington, Atlas 1 of Regional Atlas Series, Ocean Margin Drilling Program: Woods Hole, Mass., Marine Science International, sheet 7. EEZ-SCAN 84 Scientific Staff, 1986, Atlas of the Exclusive Economic Zone, Western Conterminous United States: U.S. Geological Survey Miscellaneous Investigations Series I-1792, scale 1:500,000, 152 p. See Also "U.S. Pacific West Coast Field Activities" (Paskevich and others, 2011; http://pubs.usgs.gov/of/2010/1332/htmldocs/pc/pc_overview.html). Paskevich, V.F., Wong, F.L., O?Malley, J.J., Stevenson, A.J., and Gutmacher, C.E., 2011, GLORIA sidescan-sonar imagery for parts of the U.S. Exclusive Economic Zone and adjacent areas: U.S. Geological Survey Open-File Report 2010?1332, available at http://pubs.usgs.gov/of/2010/1332/.

IMAP↗

USGS1993

Map showing depth to basement in the deep-sea basins of the Pacific continental margin, Strait of Juan de Fuca to Cape Mendocino

The U.S. Geological Survey conducted a series of cruises, EEZSCAN 84 (EEZ-SCAN 84 Scientific Staff, 1986), to collect reconnaissance data on the newly proclaimed Exclusive Economic Zone (EEZ), the area out to 200 nautical miles from the coastline of the United States. The cruises systematically surveyed the entire conterminous United States west coast EEZ using the Geological Long-Range Inclined Asdic (GLORIA) side-scan sonar, a 160-in 3 airgun seismic-reflection profiler, a 3.5-kHz high-resolution seismic-reflection profiler, a 10-kHz echo sounder, and a proton-precession magnetometer. The nominal trackline spacing throughout the survey was 30 km. Derivative maps of sediment thickness (I-2089-A, I-2090-A, I-2091-A) and depth to basement (I-2089-B, I-2090-B, I-2091-B) in the basins of the west coast EEZ were compiled from both the sonar-image dala and the deep-penetration seismic data obtained on these cruises. Only EEZ-SCAN 84 data were used for the map compilations because available data from other cruises in this region are sparsely located, have poor navigational control, or were obtained with seismic systems that were not powerful enough to resolve oceanic basement. For this map series, sediment thickness and depth to basement were determined only in the deep-ocean basin regions because the seismic system used on the EEZ-SCAN 84 cruises could not resolve oceanic basement beneath the thick sediments of the continental slope. All the data used to compile the maps are presented in the "Atlas of the Exclusive Economic Zone, Western Conterminous United States" (EEZ-SCAN 84 Scientific Staff, 1986). Basement Outcrops GLORIA imagery was used to locate areas of basement outcrop throughout the region. Where possible, sediment thickness on and immediately adjacent to basement outcrops was measured from seismic data. Where there was no bathymetric or seismic control, a seamount peak was assumed to have no sediment cover. A pattern is used on the map to indicate all basement outcrops. Data Reduction Acoustic basement in the basins, invariably oceanic Layer 2, was observed on all of the seismic records. One-way traveltime was measured from the sea floor to acoustic basement. Because the trackline spacing of about 30 km is relatively large compared to the data density along track, we chose to measure the sediment thickness every 0.5 hour or at an interval of approximately 7.5 km. Water depth was measured with a 10-kHz profiler. Depth to basement was calculated using the sea surface as the zero datum and adding the corrected water depth (Carter, 1980) to the sediment thickness. Acoustic travel times were converted to depths by first calculating a regression equation from the interval velocity versus depth data of Connard and others (1984). Their data base comprises a compilation of all available Deep Sea Drilling Project data plus wide-angle refraction data, which were collected in Cascadia Basin west of Oregon and represents the best data set available for the United States west coast EEZ. The regression equation was integrated to determine sediment thickness as a function of one-way traveltime . The resulting equation is z = 1400t + 0 .5t 2 where z is sediment thickness in meters, and t is one-way traveltime in seconds. Sediment thicknesses calculated using this equation were compared to values calculated from the general equation of Carlson and others (1986). Values for sediment thickness calculated by the two equations differed by no greater than 10 percent throughout the range of travel times. Bathymetry The bathymetry is from Chase and others (1981). The bathymetric data were compiled from a variety of sources, and data quality is inconsistent. Because of differences in navigational precision and density of coverage, the bathymetric contours of a feature may be at a different location than the corresponding isopleths derived from the EEZ-SCAN 84 data, or a feature may not be indicated on the bathymetry at all. These situations occur because either the feature is poorly located in the bathymetric data set or, especially in the outer EEZ, the bathymetric data are too sparse to have defined the existence of a feature. Acknowledgments Topographic digital data bases were corrected and verified by Christina Lief. Gerald Evenden developed the computer software system MAPGEN, used to compose this map. Reviews, suggestions, and technical contributions from Edward C. Escowitz and Florence Wong and advice about cartographic design from Will Stettner substantially improved the quality of this map. References Cited Carlson, R.L., Gangi, A.F., and Snow, K.R., 1986, Empirical reflection-traveltime/ depth and velocity/depth functions for the deep-sea sediment column: Journal of Geophysical Research, v. 91, no. B8, p. 8249-8266. Carter, D.J.T., 1980, Echo-sounding correction tables: Taunton, United Kingdom, Hydrographic Department, Ministry of Defence, 150 p. Chase, T.E., Wilde, Pat, Normark, W.R, Miller, C.P., Seekins, B.A., and Young, J.D., 1981, Offshore topography of the Western United States between 32° and 49° North latitudes: U.S. Geological Survey Open-File Report 81-443, scale 1:864,518 at 38° latitude, 2 sheets. Connard, G., Couch, R., Keeling , K., Roy, J., and Troseth, S., 1984, Abyssal plain and continental net-objective sedimentary thicknesses, in Kulm, L.D., and others, eds., Western North America continental margin and adjacent ocean floor off Oregon and Washington, Atlas 1 of Regional Atlas Series, Ocean Margin Drilling Program: Woods Hole, Mass., Marine Science International, sheet 7. EEZ-SCAN 84 Scientific Staff, 1986, Atlas of the Exclusive Economic Zone, Western Conterminous United States: U.S. Geological Survey Miscellaneous Investigations Series I-1792, scale 1:500,000, 152 p. See Also "U.S. Pacific West Coast Field Activities" (Paskevich and others, 2011; http://pubs.usgs.gov/of/2010/1332/htmldocs/pc/pc_overview.html). Paskevich, V.F., Wong, F.L., O?Malley, J.J., Stevenson, A.J., and Gutmacher, C.E., 2011, GLORIA sidescan-sonar imagery for parts of the U.S. Exclusive Economic Zone and adjacent areas: U.S. Geological Survey Open-File Report 2010?1332, available at http://pubs.usgs.gov/of/2010/1332/.

IMAP↗

USGS2023

Identifying invasive species threats, pathways, and impacts to improve biosecurity

Managing invasive species with prevention and early-detection strategies can avert severe ecological and economic impacts. Horizon scanning, an evidence-based process combining risk screening and consensus building to identify threats, has become a valuable tool for prioritizing invasive species management and prevention. We assembled a working group of experts from academic, government, and nonprofit agencies and organizations, and conducted a multi-taxa horizon scan for Florida, USA, the first of its kind in North America. Our primary objectives were to identify high-risk species and their introduction pathways, to detail the magnitude and mechanism of potential impacts, and, more broadly, to demonstrate the utility of horizon scanning. As a means to facilitate future horizon scans, we document the process used to generate the list of taxa for screening. We evaluated 460 taxa for their potential to arrive, establish, and cause negative ecological and socioeconomic impacts, and identified 40 potential invaders, including alewife, zebra mussel, crab-eating macaque, and red swamp crayfish. Vertebrates and aquatic invertebrates posed the greatest invasion threat, over half of the high-risk taxa were omnivores, and there was high confidence in the scoring of high-risk taxa. Common arrival pathways were ballast water, biofouling of vessels, and escape from the pet/aquarium/horticulture trade. Competition, predation, and damage to agriculture/forestry/aquaculture were common impact mechanisms. We recommend full risk analysis for the high-risk taxa; increased surveillance at Florida's ports, state borders, and high-risk pathways; and periodic review and revision of the list. Few horizon scans detail the comprehensive methodology (including list-building), certainty estimates for all scoring categories and the final score, detailed pathways, and the magnitude and mechanism of impact. Providing this information can further inform prevention efforts and can be efficiently replicated in other regions. Moreover, harmonizing methodology can facilitate data sharing and enhance interpretation of results for stakeholders and the general public.

Ecosphere↗

USGS2012

Modelling rating curves using remotely sensed LiDAR data

Accurate stream discharge measurements are important for many hydrological studies. In remote locations, however, it is often difficult to obtain stream flow information because of the difficulty in making the discharge measurements necessary to define stage-discharge relationships (rating curves). This study investigates the feasibility of defining rating curves by using a fluid mechanics-based model constrained with topographic data from an airborne LiDAR scanning. The study was carried out for an 8m-wide channel in the boreal landscape of northern Sweden. LiDAR data were used to define channel geometry above a low flow water surface along the 90-m surveyed reach. The channel topography below the water surface was estimated using the simple assumption of a flat streambed. The roughness for the modelled reach was back calculated from a single measurment of discharge. The topographic and roughness information was then used to model a rating curve. To isolate the potential influence of the flat bed assumption, a 'hybrid model' rating curve was developed on the basis of data combined from the LiDAR scan and a detailed ground survey. Whereas this hybrid model rating curve was in agreement with the direct measurements of discharge, the LiDAR model rating curve was equally in agreement with the medium and high flow measurements based on confidence intervals calculated from the direct measurements. The discrepancy between the LiDAR model rating curve and the low flow measurements was likely due to reduced roughness associated with unresolved submerged bed topography. Scanning during periods of low flow can help minimize this deficiency. These results suggest that combined ground surveys and LiDAR scans or multifrequency LiDAR scans that see 'below' the water surface (bathymetric LiDAR) could be useful in generating data needed to run such a fluid mechanics-based model. This opens a realm of possibility to remotely sense and monitor stream flows in channels in remote locations.

Hydrological Processes↗

USGS2011

A simple and effective method for filling gaps in Landsat ETM+ SLC-off images

The scan-line corrector (SLC) of the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor failed in 2003, resulting in about 22% of the pixels per scene not being scanned. The SLC failure has seriously limited the scientific applications of ETM+ data. While there have been a number of methods developed to fill in the data gaps, each method has shortcomings, especially for heterogeneous landscapes. Based on the assumption that the same-class neighboring pixels around the un-scanned pixels have similar spectral characteristics, and that these neighboring and un-scanned pixels exhibit similar patterns of spectral differences between dates, we developed a simple and effective method to interpolate the values of the pixels within the gaps. We refer to this method as the Neighborhood Similar Pixel Interpolator (NSPI). Simulated and actual SLC-off ETM+ images were used to assess the performance of the NSPI. Results indicate that NSPI can restore the value of un-scanned pixels very accurately, and that it works especially well in heterogeneous regions. In addition, it can work well even if there is a relatively long time interval or significant spectral changes between the input and target image. The filled images appear reasonably spatially continuous without obvious striping patterns. Supervised classification using the maximum likelihood algorithm was done on both gap-filled simulated SLC-off data and the original "gap free" data set, and it was found that classification results, including accuracies, were very comparable. This indicates that gap-filled products generated by NSPI will have relevance to the user community for various land cover applications. In addition, the simple principle and high computational efficiency of NSPI will enable processing large volumes of SLC-off ETM+ data.

Remote Sensing of Environment↗

USGS2007

A multi-scale segmentation approach to filling gaps in Landsat ETM+ SLC-off images

On 31 May 2003, the Landsat Enhanced Thematic Plus (ETM+) Scan Line Corrector (SLC) failed, causing the scanning pattern to exhibit wedge-shaped scan-to-scan gaps. We developed a method that uses coincident spectral data to fill the image gaps. This method uses a multi-scale segment model, derived from a previous Landsat SLC-on image (image acquired prior to the SLC failure), to guide the spectral interpolation across the gaps in SLC-off images (images acquired after the SLC failure). This paper describes the process used to generate the segment model, provides details of the gap-fill algorithm used in deriving the segment-based gap-fill product, and presents the results of the gap-fill process applied to grassland, cropland, and forest landscapes. Our results indicate this product will be useful for a wide variety of applications, including regional-scale studies, general land cover mapping (e.g. forest, urban, and grass), crop-specific mapping and monitoring, and visual assessments. Applications that need to be cautious when using pixels in the gap areas include any applications that require per-pixel accuracy, such as urban characterization or impervious surface mapping, applications that use texture to characterize landscape features, and applications that require accurate measurements of small or narrow landscape features such as roads, farmsteads, and riparian areas.

International Journal of Remote Sensing↗

USGS2022

Alaska Volcano Observatory archive of seismic drum records of eruptions of Augustine Volcano (1986), Redoubt Volcano (1989–90), Mount Spurr (1992), and Pavlof Volcano (1996), and the 1996 earthquake swarm at Akutan Peak

The advent of continuous digital recording of seismograph stations in Alaska did not occur until the fall of 2002. Continuous records of seismic waveforms prior to 2002 were recorded only in analog form. The Alaska Volcano Observatory (AVO) has a substantial archive of continuous analog records made on helicorders in a collection maintained by the University of Alaska Fairbanks Geophysical Institute. As part of the response to the 2006 Augustine Volcano eruption, the AVO scanned analog drum records of the 1986 Augustine eruption to aid in comparing the progression of volcanic seismicity in 2006 with the seismic record of the 1986 eruption. The scanned records proved useful, prompting subsequent efforts to preserve records from other notable episodes of volcanic unrest as readily available scanned images. The data archive accompanying this report contains scanned images of select drum records for the eruptions at Augustine Volcano (1986), Redoubt Volcano (1989–90), Mount Spurr (1992), and Pavlof Volcano (1996), as well as for the 1996 earthquake swarm at Akutan Peak.

Alaska↗

USGS2012

Bathymetry and acoustic backscatter data collected in 2010 from Cat Island, Mississippi

Scientists from the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center (SPCMSC), in collaboration with the U.S. Army Corps of Engineers (USACE), conducted geophysical and sedimentological surveys around Cat Island, the westernmost island in the Mississippi-Alabama barrier island chain (fig. 1). The objectives of the study were to understand the geologic evolution of Cat Island relative to other barrier islands in the northern Gulf of Mexico and to identify relationships between the geologic history, present day morphology, and sediment distribution. This report contains data from the bathymetry and side-scan sonar portion of the study collected during two geophysical cruises. Interferometric swath bathymetry and side-scan sonar data were collected aboard the RV G.K. Gilbert September 7-15, 2010. Single-beam bathymetry was collected in shallow water around the island (< 2 meter (m)) from the RV Streeterville from September 28 to October 2, 2010, to cover the data gap between the landward limit of the previous cruise and the shoreline. This report serves as an archive of processed interferometric swath and single-beam bathymetry and side scan sonar data. GIS data products include a 50-m cell size interpolated gridded bathymetry surface, trackline maps, and an acoustic side-scan sonar image. Additional files include error analysis maps, Field Activity Collection System (FACS) logs, and formal Federal Geographic Data Committee (FDGC) metadata.

Alabama;Mississippi↗

USGS2003

Geologic map of the Mount Trumbull 30' X 60' quadrangle, Mohave and Coconino Counties, northwestern Arizona

The geologic map of the Mount Trumbull 30' x 60' quadrangle is a cooperative product of the U.S. Geological Survey, the National Park Service, and the Bureau of Land Management that provides geologic map coverage and regional geologic information for visitor services and resource management of Grand Canyon National Park, Lake Mead Recreational Area, and Grand Canyon Parashant National Monument, Arizona. This map is a compilation of previous and new geologic mapping that encompasses the Mount Trumbull 30' x 60' quadrangle of Arizona. This digital database, a compilation of previous and new geologic mapping, contains geologic data used to produce the 100,000-scale Geologic Map of the Mount Trumbull 30' x 60' Quadrangle, Mohave and Coconino Counties, Northwestern Arizona. The geologic features that were mapped as part of this project include: geologic contacts and faults, bedrock and surficial geologic units, structural data, fold axes, karst features, mines, and volcanic features. This map was produced using 1:24,000-scale 1976 infrared aerial photographs followed by extensive field checking. Volcanic rocks were mapped as separate units when identified on aerial photographs as mappable and distinctly separate units associated with one or more pyroclastic cones and flows. Many of the Quaternary alluvial deposits that have similar lithology but different geomorphic characteristics were mapped almost entirely by photogeologic methods. Stratigraphic position and amount of erosional degradation were used to determine relative ages of alluvial deposits having similar lithologies. Each map unit and structure was investigated in detail in the field to ensure accuracy of description. Punch-registered mylar sheets were scanned at the Flagstaff Field Center using an Optronics 5040 raster scanner at a resolution of 50 microns (508 dpi). The scans were output in .rle format, converted to .rlc, and then converted to ARC/INFO grids. A tic file was created in geographic coordinates and projected into the base map projection (Polyconic) using a central meridian of -113.500. The tic file was used to transform the grid into Universal Transverse Mercator projection. The linework was vectorized using gridline. Scanned lines were edited interactively in ArcEdit. Polygons were attributed in ArcEdit and all artifacts and scanning errors visible at 1:100,000 were removed. Point data were digitized onscreen. Due to the discovery of digital and geologic errors on the original files, the ARC/INFO coverages were converted to a personal geodatabase and corrected in ArcMap. The feature classes which define the geologic units, lines and polygons, are topologically related and maintained in the geodatabase by a set of validation rules. The internal database structure and feature attributes were then modified to match other geologic map databases being created for the Grand Canyon region. Faults were edited with the downthrown block, if known, on the 'right side' of the line. The 'right' and 'left' sides of a line are determined from 'starting' at the line's 'from node' and moving to the line's end or 'to node'.

Arizona↗

USGS1983

Assessment of gray whale feeding grounds and sea floor interaction in the northeastern Bering Sea

A dense ampeliscid amphipod community in Chirikov Basin and around St. Lawrence Island in the northeastern Bering Sea has been outlined by summarizing biological studies, analyzing bioturbation in sediment samples, and examining sea floor photos and videotapes. The amphipod population is associated with a homogeneous, relict fine-grained sand body 0.10-1.5 m thick that is deposited during the marine transgression over the Bering land bridge 8,000-10,000 yr B.P. Modern current and water mass movements and perhaps whale feeding activity prevent modern deposition in this area. The distribution of the transgressive sand sheet, associated amphipod community and feeding gray whales mapped by aerial survey correlate closely with three types of sea-floor pits observed on high (500 kHz) and low (105 kHz) resolution side-scan sonar; they are attributed to gray whale feeding traces and their subsequent current scour modification. The fresh and modified feeding pits are present in 22,000 km2 of the basin and they cover a total of 2 to 18% of the sea floor in different areas of the feeding region. The smallest size class of pits approximates whale mouth gape size and is assumed to represent fresh whale feeding pits. Fresh feeding disturbance of the sea floor is estimated to average about 5.7% for a full feeding season. Combined with information that 34% of the measured benthic biomass is amphipod prey species, and calculating the number of gray whale feeding days in the Alaskan waters plus amount consumed per day, it can be estimated that Chirikov Basin, 2% of the feeding area, supplies a minimum of 5.3 to 7.1% of the gray whale's food resource in the Bering Sea and Arctic Ocean. If a maximum of 50% of the fresh feeding features are assumed to be missed because they parallel side-scan beam paths, then a maximum whale food resource of 14.2% is possible in northeastern Bering Sea. Because of side-scan techniques and possible higher amphipod biomass estimates, a reasonable minimum estimate of the total whale food resource in northeastern Bering Sea is 10%. These data show that side-scan sonar is a powerful new technique for analyzing marine mammal benthic feeding grounds. Sonographs reveal that the gray whales profoundly disturb the substrate and initiate substantial further erosion by bottom currents, all of which enhances productivity of the prey species and results in a 'farming of the sea floor'. In turn, because of the high concentration of whale prey species in a prime feeding ground that is vulnerable to the development of petroleum and mining for sand, great care is required in the exploitation of these resources in the Chirikov Basin.

Open-File Report↗

USGS2019

Erosion monitoring along selected bank locations of the Coosa River in Alabama using terrestrial light detection and ranging (T–lidar) technology, 2014–17

The Alabama Power Company operates a series of dams on the Coosa River in east central Alabama. Seven dams impound the river to form six reservoirs: Weiss Lake, H Neely Henry Lake, Logan Martin Lake, Lay Lake, Lake Mitchell, and Lake Jordan. Streamflow below these reservoirs is primarily controlled by power generation at the dams, and there is ongoing concern about the stability of selected stream banks downstream from the dams. During relicensing in the early 2000s, the Alabama Power Company and stakeholders identified particular areas of concern to monitor and document the extent of erosion. The U.S. Geological Survey, in cooperation with the Alabama Power Company, conducted a 3-year monitoring program, from 2014 to 2017, of the geomorphic conditions of six selected reaches along the Coosa River. The six reaches included two downstream from H Neely Henry Dam near Gadsden, two downstream from Logan Martin Dam near Vincent, and two downstream from Walter Bouldin Dam near Wetumpka, Alabama. The geomorphic monitoring was conducted using boat- and tripod-mounted terrestrial light detection and ranging technology. Site LM–108, an island in the Coosa River downstream from Logan Martin Dam, exhibited the greatest amount of normalized erosion, 2.05 cubic meters per square meter of area, likely because this site experiences head-on flow from the river. Bank retreat at the upstream end of the island (LM–108) was estimated at 2.9 meters for the study period. The remaining five reaches were exposed to shear flow from the river; the greatest amount of normalized erosion, 0.467 cubic meter per square meter of area, was exhibited by site WB–106 on the right bank downstream from Walter Bouldin Dam. Results of the comparisons of terrestrial light detection and ranging scans indicated that intervals between scans that exhibited the greatest amounts of erosion generally corresponded to periods of above-median flow, and that intervals between scans that exhibited the least amounts of erosion, or deposition, generally corresponded to periods of below-median flow. Relatively smaller surface areas could be surveyed at some sites because inundation or dense vegetation obscured parts of the banks, suggesting that, in future investigations, it may be preferable to conduct scans during periods of leaf-off and low flow to avoid bias introduced by parts of the banks of interest being inundated or obscured by vegetation.

Alabama↗

USGS2019

A bibliometric profile of the Remote Sensing Open Access Journal published by MDPI between 2009 and 2018

Remote Sensing Open Access Journal (RS OAJ) is an international leading journal in the field of remote sensing science and technology. It was first published in the year 2009 and is currently celebrating tenth year of publications. In this research, a bibliometric analysis of RS OAJ was conducted based on 5588 articles published during the 10-year (2009–2018) time-period. The bibliometric analysis includes a comprehensive set of indicators such as dynamics and trends of publications, journal impact factor, total cites, eigenfactor score, normalized eigenfactor, CiteScore, h-index, h-classic publications, most productive countries (or territories) and institutions, co-authorship collaboration about countries (territories), research themes, citation impact of co-occurrences keywords, intellectual structure, and knowledge commutation. We found that publications of RS OAJ presented an exponential growth in the past ten years. From 2010 to 2017 (for which complete years data were available), the h-index of RS OAJ is 67. From 2009–2018, RS OAJ includes publications from 129 countries (or territories) and 3826 institutions. The leading nations contributing articles, based on 2009–2018 data, and listed based on ranking were: China, United States, Germany, Italy, France, Spain, Canada, England, Australia, Netherlands, Japan, Switzerland and Austria. The leading institutions, also for the same period and listed based on ranking were: Chinese Academy of Sciences, Wuhan University, University of Chinese Academy of Sciences, Beijing Normal University, The university of Maryland, National Aeronautics and Space Administration, National Oceanic and Atmospheric Administration, China University of Geosciences, United States Geological Survey, German Aerospace Centre, University of Twente, and California Institute of Technology. For the year 2017, RS OAJ had an impressive journal impact factor of 3.4060, a CiteScore of 4.03, eigenfactor score of 0.0342, and normalized eigenfactor score of 3.99. In addition, based on 2009–2018, data co-word analysis determined that “remote sensing”, “MODIS”, “Landsat”, “LiDAR” and “NDVI” are the high-frequency of author keywords co-occurrence in RS OAJ. The main themes of RS OAJ are multi-spectral and hyperspectral remote sensing, LiDAR scanning and forestry remote sensing monitoring, MODIS and LAI data applications, Remote sensing applications and Synthetic Aperture Radar (SAR). Through author keywords citation impact analysis, we find the most influential keyword is Unmanned Aerial Vehicle (UAV), followed, forestry, Normalized Difference Vegetation Index (NDVI), terrestrial laser scanning, airborne laser scanning, forestry inventory, urban heat island, monitoring, agriculture, and laser scanning. By analyzing the intellectual structure of RS OAJ, we identify the main reference publications and find that the themes are about Random Forests, MODIS vegetation indices and image analysis, etc. RS OAJ ranks first in cited journals and third in citing, this indicates that RS OAJ has the internal knowledge flow. Our results will bring more benefits to scholars, researchers and graduate students, who hopes to get a quick overview of the RS OAJ. And this article will also be the starting point for communication between scholars and practitioners. Finally, this paper proposed a nuanced h-index (nh-index) to measure productivity and intellectual contribution of authors by considering h-index based on whether the one is first, second, third, or nth author. This nuanced approach to determining h-index of authors is powerful indicator of an academician’s productivity and intellectual contribution.

Remote Sensing↗

USGS2015

Evaluating habitat associations of a fish assemblage at multiple spatial scales in a minimally disturbed stream using low‐cost remote sensing

Habitat heterogeneity at multiple scales is a major factor affecting fish assemblage structure. However, assessments that examine these relationships at multiple scales concurrently are lacking. The lack of assessments at these scales is a critical gap in understanding as conservation and restoration efforts typically work at these levels. A combination of low‐cost side‐scan sonar surveys, aerial imagery using an unmanned aerial vehicle, and fish collections were used to evaluate the relationship between physicochemical and landscape variables at various spatial scales (e.g. micro‐mesohabitat, mesohabitat, channel unit, stream reach) and stream–fish assemblage structure and habitat associations in the South Llano River, a spring‐fed second‐order stream on the Edwards Plateau in central Texas during 2012–2013. Low‐cost side‐scan sonar surveys have not typically been used to generate data for riverscape assessments of assemblage structure, thus the secondary objective was to assess the efficacy of this approach. The finest spatial scale (micro‐mesohabitat) and the intermediate scale (channel unit) had the greatest explanatory power for variation in fish assemblage structure. Many of the fish endemic to the Edwards Plateau showed similar associations with physicochemical and landscape variables suggesting that conservation and restoration actions targeting a single endemic species may provide benefits to a large proportion of the endemic species in this system. Low‐cost side‐scan sonar proved to be a cost‐effective means of acquiring information on the habitat availability of the entire river length and allowed the assessment of how a full suite of riverscape‐level variables influenced local fish assemblage structure.

Texas↗