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At least 991 records · Page 55Linked to original sources
USGS2010

Channel change and bed-material transport in the Lower Chetco River, Oregon

The lower Chetco River is a wandering gravel-bed river flanked by abundant and large gravel bars formed of coarse bed-material sediment. Since the early twentieth century, the large gravel bars have been a source of commercial aggregate for which ongoing permitting and aquatic habitat concerns have motivated this assessment of historical channel change and sediment transport rates. Analysis of historical channel change and bed-material transport rates for the lower 18 kilometers shows that the upper reaches of the study area are primarily transport zones, with bar positions fixed by valley geometry and active bars mainly providing transient storage of bed material. Downstream reaches, especially near the confluence of the North Fork Chetco River, are zones of active sedimentation and channel migration. Multiple analyses, supported by direct measurements of bedload during winter 2008–09, indicate that since 1970 the mean annual flux of bed material into the study reach has been about 40,000–100,000 cubic meters per year. Downstream tributary input of bed-material sediment, probably averaging 5–30 percent of the influx coming into the study reach from upstream, is approximately balanced by bed-material attrition by abrasion. Probably little bed material leaves the lower river under natural conditions, with most net influx historically accumulating in wider and more dynamic reaches, especially near the North Fork Chetco River confluence, 8 kilometers upstream from the Pacific Ocean. The year-to-year flux, however, varies tremendously. Some years may have less than 3,000 cubic meters of bed material entering the study area; by contrast, some high-flow years, such as 1982 and 1997, likely have more than 150,000 cubic meters entering the reach. For comparison, the estimated annual volume of gravel extracted from the lower Chetco River for commercial aggregate during 2000–2008 has ranged from 32,000 to 90,000 cubic meters and averaged about 59,000 cubic meters per year. Mined volumes probably exceeded 140,000 cubic meters per year for several years in the late 1970s. Repeat surveys and map analyses indicate a reduction in bar area and sinuosity between 1939 and 2008, chiefly in the period 1965–95. Repeat topographic and bathymetric surveys show channel incision for substantial portions of the study reach, with local areas of bed lowering by as much as 2 meters. A specific gage analysis at the upstream end of the study reach indicates that incision and narrowing followed aggradation culminating in the late 1970s. These observations are all consistent with a reduction of sediment supply relative to transport capacity since channel surveys in the late 1970s, probably owing to a combination of (1) bed sediment removal and (2) transient river adjustments to large sediment volumes brought by floods such as those in 1964 and, to a lesser extent, 1996.

Oregon↗
USGS2022

Delineating the Pierre Shale from geophysical surveys east and southeast of Ellsworth Air Force Base, South Dakota, 2021

The U.S. Geological Survey, in cooperation with the U.S. Air Force Civil Engineer Center, used surface-geophysical methods to delineate the top of Cretaceous Pierre Shale along survey transects in selected areas east and southeast of Ellsworth Air Force Base, South Dakota, from April to September 2021. Two complementary geophysical methods—electrical resistivity and passive seismic—were used along 21 colocated transect surveys east and southeast of Ellsworth Air Force Base for a total of 24.7 line-kilometers. Electrical resistivity results were analyzed using EarthImager2D electrical resistivity tomography processing and inversion software. Two-dimensional earth models showing the electrical properties of the subsurface were evaluated by directly comparing the high and low subsurface resistivity values to a surficial-geologic map and nearby wells with drillers logs. Passive seismic data were analyzed using the horizontal-to-vertical spectral ratio method to determine the depth to the Cretaceous Pierre Shale at each survey point. The depth to the Pierre Shale along the transects ranged from 0.0 to about 19.8 meters, and the mean and median depths were about 6.1 and 5.6 meters, respectively. The elevation of the Pierre Shale and thickness of unconsolidated deposits generally increased with land-surface elevation from south to north; however, some transects displayed topographically high and low areas that did not correlate with land-surface topography.

South Dakota↗
USGS2012

Mapping river bathymetry with a small footprint green LiDAR: Applications and challenges

Airborne bathymetric Light Detection And Ranging (LiDAR) systems designed for coastal and marine surveys are increasingly sought after for high-resolution mapping of fluvial systems. To evaluate the potential utility of bathymetric LiDAR for applications of this kind, we compared detailed surveys collected using wading and sonar techniques with measurements from the United States Geological Survey’s hybrid topographic⁄ bathymetric Experimental Advanced Airborne Research LiDAR (EAARL). These comparisons, based upon data collected from the Trinity and Klamath Rivers, California, and the Colorado River, Colorado, demonstrated that environmental conditions and postprocessing algorithms can influence the accuracy and utility of these surveys and must be given consideration. These factors can lead to mapping errors that can have a direct bearing on derivative analyses such as hydraulic modeling and habitat assessment. We discuss the water and substrate characteristics of the sites, compare the conventional and remotely sensed river-bed topographies, and investigate the laser waveforms reflected from submerged targets to provide an evaluation as to the suitability and accuracy of the EAARL system and associated processing algorithms for riverine mapping applications.

Journal of the American Water Resources Associatio↗
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↗
USGS2016

Integrating local pastoral knowledge, participatory mapping, and species distribution modeling for risk assessment of invasive rubber vine ( Cryptostegia grandiflora ) in Ethiopia’s Afar region

The threats posed by invasive plants span ecosystems and economies worldwide. Local knowledge of biological invasions has proven beneficial for invasive species research, but to date no work has integrated this knowledge with species distribution modeling for invasion risk assessments. In this study, we integrated pastoral knowledge with Maxent modeling to assess the suitable habitat and potential impacts of invasive Cryptostegia grandiflora Robx. Ex R.Br. (rubber vine) in Ethiopia’s Afar region. We conducted focus groups with seven villages across the Amibara and Awash-Fentale districts. Pastoral knowledge revealed the growing threat of rubber vine, which to date has received limited attention in Ethiopia, and whose presence in Afar was previously unknown to our team. Rubber vine occurrence points were collected in the field with pastoralists and processed in Maxent with MODIS-derived vegetation indices, topographic data, and anthropogenic variables. We tested model fit using a jackknife procedure and validated the final model with an independent occurrence data set collected through participatory mapping activities with pastoralists. A Multivariate Environmental Similarity Surface analysis revealed areas with novel environmental conditions for future targeted surveys. Model performance was evaluated using area under the receiver-operating characteristic curve (AUC) and showed good fit across the jackknife models (average AUC = 0.80) and the final model (test AUC = 0.96). Our results reveal the growing threat rubber vine poses to Afar, with suitable habitat extending downstream of its current known location in the middle Awash River basin. Local pastoral knowledge provided important context for its rapid expansion due to acute changes in seasonality and habitat alteration, in addition to threats posed to numerous endemic tree species that provide critical provisioning ecosystem services. This work demonstrates the utility of integrating local ecological knowledge with species distribution modeling for early detection and targeted surveying of recently established invasive species.

Ecology and Society↗
USGS2007

Predicting the potential distribution of invasive exotic species using GIS and information-theoretic approaches: A case of ragweed (Ambrosia artemisiifolia L.) distribution in China

Invasive exotic species pose a growing threat to the economy, public health, and ecological integrity of nations worldwide. Explaining and predicting the spatial distribution of invasive exotic species is of great importance to prevention and early warning efforts. We are investigating the potential distribution of invasive exotic species, the environmental factors that influence these distributions, and the ability to predict them using statistical and information-theoretic approaches. For some species, detailed presence/absence occurrence data are available, allowing the use of a variety of standard statistical techniques. However, for most species, absence data are not available. Presented with the challenge of developing a model based on presence-only information, we developed an improved logistic regression approach using Information Theory and Frequency Statistics to produce a relative suitability map. This paper generated a variety of distributions of ragweed (Ambrosia artemisiifolia L.) from logistic regression models applied to herbarium specimen location data and a suite of GIS layers including climatic, topographic, and land cover information. Our logistic regression model was based on Akaike's Information Criterion (AIC) from a suite of ecologically reasonable predictor variables. Based on the results we provided a new Frequency Statistical method to compartmentalize habitat-suitability in the native range. Finally, we used the model and the compartmentalized criterion developed in native ranges to "project" a potential distribution onto the exotic ranges to build habitat-suitability maps. ?? Science in China Press 2007.

Chinese Science Bulletin↗
USGS2020

Mapping croplands of Europe, Middle East, Russia, and Central Asia using Landsat 30-m data, machine learning algorithms and Google Earth Engine

Accurate and timely information on croplands is important for environmental, food security, and policy studies. Spatially explicit cropland datasets are also required to derive information on crop type, crop yield, cropping intensity, as well as irrigated areas. Large area defined as continental to global cropland mapping is challenging due to differential manifestation of croplands, wide range of cultivation practices and limited reference data availability. This study presents the results of a cropland extent mapping of 64 Countriescovering large parts of Europe, Middle East, Russia and Central Asia. To cover such a vast area, roughly 160,000 Landsat scenes from 3,351 footprints between 2014 and 2016 were processed within the Google Earth Engine (GEE) cloud-platform. We used the pixel-based supervised Random Forest (RF) machine learning algorithm with a set of satellite data inputs capturing diverse spectral, temporal and topographical characteristics across twelve agroecological zones (AEZs). The reference data to train the classification model were collected from very high spatial resolution imagery (VHRI) and ancillary datasets. The result is a binary map showing cultivated/non-cultivated areas ca. 2015. The map produced an overall accuracy of 94 percent with roughly 14 percent omission and commission errors for the cropland class based on a large set of independent validation samples. The map suggests the entire study area has a total 546 million hectares (Mha) of croplands occupying 18 percent of the land area. Comparison between national cropland area estimates from United Nations Food and Agricultural Organizations (FAO) and those derived from this work also showed an R-square value of 0.95. For the entire Landsat-derived 30-m product the overall accuracy was 93.8% with cropland class providing producers accuracy of 86.5% (errors of omissions = 13.5%) and users accuracy of 85.7% (errors of commissions = 14.3%). This Landsat-derived 30-m cropland product (GFSAD30) provided 10-30% greater cropland areas compared to UN FAO in the 64 Countries. Finally, the map-to-map comparison between GFSAD30 with several other cropland products revealed that the best similarity matrix was with the 30m global land cover (GLC30) product providing an overall accuracy of 88.8 percent (Kappa 0.7) with producers cropland similarity of 89.2 percent (errors of omissions = 10.8%) and users cropland similarity of 81.8 percent (errors of commissions = 8.1%). GFSAD30 captured the missing croplands in GLC30 product around significantly irrigated agricultural areas in Germany and Belgium and rainfed agriculture in Italy. This study also established that the real strength of GFSAD30 product, compared to other products, were in: 1. Identifying precise location of croplands, and 2. Capturing fragmented croplands. The cropland extent map dataset is available through NASAs Land Processes Distributed Active Archive Center (LP DAAC) at https://doi.org/10.5067/MEaSUREs/GFSAD/GFSAD30EUCEARUMECE.001, while the training and reference data as well as visualization are available at the Global Croplands website.

ISPRS Journal of Photogrammetry and Remote Sensing↗
USGS2017

Similarity of plant functional traits and aggregation pattern in a subtropical forest

The distribution of species and communities in relation to environmental heterogeneity is a central focus in ecology. Co-occurrence of species with similar functional traits is an indication that communities are determined in part by environmental filters. However, few studies have been designed to test how functional traits are selectively filtered by environmental conditions at local scales. Exploring the relationship between soil characteristics and plant traits is a step toward understanding the filtering hypothesis in determining plant distribution at local scale. Toward this end, we mapped all individual trees (diameter >1 cm) in a one-ha subtropical forest of China in 2007 and 2015. We measured topographic and detailed soil properties within the field site, as well as plant leaf functional traits and demographic rates of the seven most common tree species. A second one-ha study plot was established in 2015, to test and validate the general patterns that were drawn from first plot. We found that variation in species distribution at local scale can be explained by soil heterogeneity and plant functional traits. (From first plot). (1) Species dominant in habitats with high soil ammonium nitrogen and total phosphorus tended to have high specific leaf area (SLA) and relative growth rate (RGR). (2) Species dominant in low-fertility habitats tended to have high leaf dry matter content (LDMC), ratio of chlorophyll a and b (ratioab), and leaf thickness (LT). The hypothesis that functional traits are selected in part by environmental filters and determine plant distribution at local scale was confirmed by the data of the first plot and a second regional site showed similar species distribution patterns.

Zhejiang Province↗
USGS2008

Anatomy and dynamics of a floodplain, Powder River, Montana, U.S.A.

Centimeter-scale measurements on several Powder River floodplains provide insights into the nature of overbank depositional processes that created the floodplains; during a 20-year period after a major flood in 1978. Rising stages initially entered across a sill at the downriver end of the floodplains. Later, as stages continued to rise, water entered the floodplains through distinct low saddles along natural levees. The annual maximum depth of water over the levee crest averaged 0.19 in from 1983 through 1996, and the estimated flow velocities were approximately 0.15 m s-1. Water ponded in the floodplain trough, a topographic low between the natural levee and the pre-flood riverbank, and mud settled as thin layers of nearly constant thickness. Mud layers alternated with sand layers, which were relatively thick near the channel. Together, these beds created a distinctive natural levee. In some locations, individual flood deposits began as a thin mud layer that gradually coarsened upwards to medium-grained sand. Coarsening-upwards sequences form initially as mud because only the uppermost layers of water in the channel supply the first overbank flows, which are rich in mud but starved of sand. At successively higher stages, fine sands and then medium sands increase in concentration in the floodwater and are deposited as fine- and medium-sand layers overlying the initial mud layer. Theoretical predictions from mathematical models of sediment transport by advection and diffusion indicate that these processes acting alone are unlikely to create the observed sand layers of nearly uniform thickness that extend across much of the floodplain. We infer that other transport processes, notably bedload transport, must be important along Powder River. Even with the centimeter-scale measurements of floodplain deposits, daily hydraulic data, and precise annual surface topographic surveys, we were unable to determine any clear correspondence between the gauged flow record of overbank floods and the depositional layers mapped in the floodplain. These results provide a detailed example of floodplain deposits and depositional processes that should prove useful for interpreting natural levee deposits in a variety of geologic settings. Copyright ?? 2008, SEPM (Society for Sedimentary Geology).

Journal of Sedimentary Research↗
USGS1878

Annual Report upon the geographical surveys of the territory of the United States west of the 100th meridian, in the States and Territories of California, Colorado, Kansas, Nebraska, Nevada, Oregon, Texas, Arizona, Idaho, Montana, New Mexico, Utah, Washington, and Wyoming: Being Appendix NN of the Annual Report of the Chief of Engineers for 1878

I [George M. Wheeler] have the honor to submit the following report for the fiscal year ending June 30, 1878: At the close of the present field season parties of the survey will have been engaged in fourteen of the fifteen States and Territories, a part or all of which lie west of the 100th meridian of longitude; the remaining political division (Dakota) alone having been unvisited. The progress of the work since its commencement has been directed over connected areas, and in such manner that, at a minimum of time and expense, as large areas as practicable, pursuant to required methods, shall be topographically surveyed in detail, to the end that the War Department shall have, at as early a date as possible, a complete map of the entire region.

Arizona, California, Colorado, Idaho, Kansas, Mont↗
USGS2014

On the effects of scale for ecosystem services mapping

Ecosystems provide life-sustaining services upon which human civilization depends, but their degradation largely continues unabated. Spatially explicit information on ecosystem services (ES) provision is required to better guide decision making, particularly for mountain systems, which are characterized by vertical gradients and isolation with high topographic complexity, making them particularly sensitive to global change. But while spatially explicit ES quantification and valuation allows the identification of areas of abundant or limited supply of and demand for ES, the accuracy and usefulness of the information varies considerably depending on the scale and methods used. Using four case studies from mountainous regions in Europe and the U.S., we quantify information gains and losses when mapping five ES - carbon sequestration, flood regulation, agricultural production, timber harvest, and scenic beauty - at coarse and fine resolution (250 m vs. 25 m in Europe and 300 m vs. 30 m in the U.S.). We analyze the effects of scale on ES estimates and their spatial pattern and show how these effects are related to different ES, terrain structure and model properties. ES estimates differ substantially between the fine and coarse resolution analyses in all case studies and across all services. This scale effect is not equally strong for all ES. We show that spatially explicit information about non-clustered, isolated ES tends to be lost at coarse resolution and against expectation, mainly in less rugged terrain, which calls for finer resolution assessments in such contexts. The effect of terrain ruggedness is also related to model properties such as dependency on land use-land cover data. We close with recommendations for mapping ES to make the resulting maps more comparable, and suggest a four-step approach to address the issue of scale when mapping ES that can deliver information to support ES-based decision making with greater accuracy and reliability.

PLoS ONE↗
USGS2012

Recently Active Traces of the Berryessa Fault, California: A Digital Database

The purpose of this map is to show the location of and evidence for recent movement on active fault traces within the Berryessa section and parts of adjacent sections of the Green Valley Fault Zone, California. The location and recency of the mapped traces is primarily based on geomorphic expression of the fault as interpreted from large-scale 2010 aerial photography and from 2007 and 2011 0.5 and 1.0 meter bare-earth LiDAR imagery (that is, high-resolution topographic data). In a few places, evidence of fault creep and offset Holocene strata in trenches and natural exposures have confirmed the activity of some of these traces. This publication is formatted both as a digital database for use within a geographic information system (GIS) and for broader public access as map images that may be browsed on-line or download a summary map . The report text describes the types of scientific observations used to make the map, gives references pertaining to the fault and the evidence of faulting, and provides guidance for use of and limitations of the map.

California↗
USGS2018

Mapping and measuring aeolian sand dunes with photogrammetry and LiDAR from unmanned aerial vehicles (UAV) and multispectral satellite imagery on the Paria Plateau, AZ, USA

The Paria Plateau is a potentially important but relatively unstudied aeolian sand source area in the Grand Canyon region of Arizona, USA. This study used unmanned aerial vehicle(UAV) - based LiDAR and structure-from-motion (SfM) photogrammetry to produce high-resolution topographic models of aeolian dunes on the plateau. We combined the dune topography data with a high-resolution satellite image maximum likelihood classification (producer's accuracy = 87.2%) to quantify potential aeolian sand source areas across the 958 km 2 plateau. We mapped all the unvegetated active aeolian dunes on the plateau and estimate they contain 24 Tg of sand, and could, therefore, be a proportionately important regional sand source considering the annual sand loads of the downwind Paria River at its confluence with the Colorado River are generally <1 Tg. The results and data from this study could be useful for future investigations that wish to explicitly link aeolian sand on the Paria Plateau to downwind sediment dynamics in the region. The methodology for UAV and satellite remote sensing that we demonstrate could be applied to quantify sand at large geographic extents in other aeolian environments around the world.

Arizona↗