This U.S. Geological Survey (USGS), Hawaiian Volcano Observatory (HVO) summary presents seismic data gathered during January–March 2009. The seismic summary offers earthquake hypocenters without interpretation as a source of preliminary data and is complete in that most data for events of M≥1.5 are included. All latitude and longitude references in this report are stated in Old Hawaiian Datum.
\nThe HVO summaries have been published in various forms since 1956. Summaries prior to 1974 were issued quarterly, but cost, convenience of preparation and distribution, and the large quantities of data necessitated an annual publication, beginning with Summary 74 for the year 1974. Since 2004, summaries have been identified simply by year, rather than by summary number.
\nSummaries originally issued as administrative reports were republished in 2007 as Open-File Reports. All the summaries since 1956 are available athttp://pubs.usgs.gov/of/2007/1316-1345/ (last accessed 02/24/2010). In January 1986, HVO adopted CUSP (California Institute of Technology USGS SeismicProcessing). Summary 86, available athttp://pubs.er.usgs.gov/usgspubs/ofr/ofr92301 (last accessed 02/24/2010), includes a description of the seismic instrumentation, calibration, and processing used in recent years. The present summary includes background information about the seismic network to provide the end user with an understanding of the processing parameters and how the data were gathered.
\nEarthworm software, documentation available at http://folkworm.ceri.memphis.edu/ew-doc/ (last accessed 02/24/2010), was first installed at HVO in 1999 as part of an upgrade to tsunami warning capabilities in the Pacific region. This improved and expanded data exchange with the Pacific Tsunami Warning Center in Ewa Beach, Oahu, that included not only seismic waveforms, but also parametric earthquake data. Although Earthworm does included modules for earthquake triggering and earthquake location, this software was never used to generate catalog hypocenter locations at HVO.
\nDuring 2009, HVO migrated from CUSP to seismic processing software developed by the California Integrated SeismicNetwork or CISN. This software is now referred to as AQMS, for Advanced National Seismic System Quake ManagementSystem. Summary data for this year will be presented in two reports; the first report includes earthquakes processed on the CUSP platform for January–March; earthquakes for the last three quarters, processed on the AQMS platform, will be published in a separate summary with a description of AQMS production parameters.
\nA report by Klein and Koyanagi (USGS Open-File Report 80-302, 1980) tabulates instrumentation, calibration, and recording history of each seismic station in the network. It is designed as a reference for users of seismograms and phase data and includes and augments the information in the station table in this summary.
\nFigures 11–14 are maps showing computer-located hypocenters. The maps were generated using the Generic Mapping Tools (GMT), found at http://gmt.soest.hawaii.edu/ (last accessed 01/22/2010), in place of traditional QPLOT maps.
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The elevated volcanic plateau of Lakshmi Planum, which represents a very specific and unique class of highlands on Venus, dominates the northern half of the quadrangle. The surface of the planum stands 3-4 km above mean planetary radius and the plateau is surrounded by the highest Venusian mountain ranges, 7-10 km high. \r\n\r\nBefore the Magellan mission, the geology of the Lakshmi Planum quadrangle was known on the basis of topographic data acquired by the Pioneer-Venus and Venera-15/16 altimeter and radar images received by the Arecibo telescope and Venera-15/16 spacecraft. These data showed unique topographic and morphologic structures of the mountain belts, which have no counterparts elsewhere on Venus, and the interior volcanic plateau with two large and low volcanic centers and large blocks of tessera-like terrain. From the outside, Lakshmi Planum is outlined by a zone of complexly deformed terrains that occur on the regional outer slope of Lakshmi. Vast low-lying plains surround this zone. After acquisition of the Venera-15/16 data, two classes of hypotheses were formulated to explain the unique structure of Lakshmi Planum and its surrounding. The first proposed that the western portion of Ishtar Terra, dominated by Lakshmi Planum, was a site of large-scale upwelling while the alternative hypothesis considered this region as a site of large-scale downwelling and underthrusting. \r\n\r\nEarly Magellan results showed important details of the general geology of this area displayed in the Venera-15/16 images. Swarms of extensional structures and massifs of tesserae populate the southern slope of Lakshmi. The zone of fractures and grabens form a giant arc thousands of kilometers long and hundreds of kilometers wide around the southern flank of Lakshmi Planum. From the north, the deformational zones consist mostly of contractional structures such as ridges. Corona and corona-like structures are not typical features of this zone but occur within separate branches of extensional structures oriented radial to the edge of Lakshmi. The southeastern edge of Lakshmi appears to be the source of large volcanic flows that extend to the south toward the lowland areas of Sedna Planitia. Colette and Sacajawea Paterae in the interior of Lakshmi are low volcanic centers with very deep central depressions. Lava flows sourced by Colette and Sacajawea form distinctive radial patterns around these volcanoes. Magellan gravity data show that the northern and northeastern portions of the quadrangle, which correspond to Lakshmi Planum, represent a significant geoid anomaly with the peak value of about 90 m over Maxwell Montes at the eastern edge of the map area. Maxwell is characterized also by very high vertical gravity acceleration values (as much as 268 mGal). The lowland of Sedna Planitia to the south of Lakshmi has mostly negative geoid values (down to -40 m). \r\n\r\nThe key geological structure of the quadrangle is Lakshmi Planum, the mode of formation of which is still a major unresolved problem. The topographic configuration, gravity signature, and pattern of deformation inside Lakshmi and along its boundaries make this feature unique on Venus. Thus, geological mapping of this region allows addressing several important questions that should help to put some constraints on the existing models of Lakshmi formation. What is the sequence of events in the formation and evolution of such a unique morphologic and topographic feature? What are the characteristics of the marginal areas of Lakshmi: the compact mountain belts and broad zones of deformation in the transition zone between Lakshmi and surrounding lowlands? How do the units in Lakshmi Planum quadrangle compare with the units mapped in neighboring and distant regions of Venus and what information do they provide concerning models for Venus","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sim3116","collaboration":"Prepared for the National Aeronautics and Space Administration\r\n","usgsCitation":"Ivanov, M.A., and Head, J.W., 2010, Geologic map of the Lakshmi Planum quadrangle (V-7), Venus: U.S. Geological Survey Scientific Investigations Map 3116, HTML, https://doi.org/10.3133/sim3116.","productDescription":"HTML","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":13909,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3116/","linkFileType":{"id":5,"text":"html"}},{"id":118496,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3116.jpg"}],"scale":"5000000","projection":"Lambert","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4afce4b07f02db69660f","contributors":{"authors":[{"text":"Ivanov, Mikhail A.","contributorId":25245,"corporation":false,"usgs":true,"family":"Ivanov","given":"Mikhail","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":305617,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Head, James W. III","contributorId":102954,"corporation":false,"usgs":true,"family":"Head","given":"James","suffix":"III","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":305618,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":98518,"text":"tm11C4 - 2010 - Land-Use Portfolio Modeler, Version 1.0","interactions":[],"lastModifiedDate":"2012-02-02T00:14:54","indexId":"tm11C4","displayToPublicDate":"2010-07-17T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"11-C4","title":"Land-Use Portfolio Modeler, Version 1.0","docAbstract":"Natural hazards pose significant threats to the public safety and economic health of many communities throughout the world. Community leaders and decision-makers continually face the challenges of planning and allocating limited resources to invest in protecting their communities against catastrophic losses from natural-hazard events. Public efforts to assess community vulnerability and encourage loss-reduction measures through mitigation often focused on either aggregating site-specific estimates or adopting standards based upon broad assumptions about regional risks. The site-specific method usually provided the most accurate estimates, but was prohibitively expensive, whereas regional risk assessments were often too general to be of practical use. Policy makers lacked a systematic and quantitative method for conducting a regional-scale risk assessment of natural hazards. In response, Bernknopf and others developed the portfolio model, an intermediate-scale approach to assessing natural-hazard risks and mitigation policy alternatives. \r\n\r\nThe basis for the portfolio-model approach was inspired by financial portfolio theory, which prescribes a method of optimizing return on investment while reducing risk by diversifying investments in different security types. In this context, a security type represents a unique combination of features and hazard-risk level, while financial return is defined as the reduction in losses resulting from an investment in mitigation of chosen securities. Features are selected for mitigation and are modeled like investment portfolios. Earth-science and economic data for the features are combined and processed in order to analyze each of the portfolios, which are then used to evaluate the benefits of mitigating the risk in selected locations. Ultimately, the decision maker seeks to choose a portfolio representing a mitigation policy that maximizes the expected return-on-investment, while minimizing the uncertainty associated with that return-on-investment. \r\n\r\nThe portfolio model, now known as the Land-Use Portfolio Model (LUPM), provided the framework for the development of the Land-Use Portfolio Modeler, Version 1.0 software (LUPM v1.0). The software provides a geographic information system (GIS)-based modeling tool for evaluating alternative risk-reduction mitigation strategies for specific natural-hazard events. The modeler uses information about a specific natural-hazard event and the features exposed to that event within the targeted study region to derive a measure of a given mitigation strategy`s effectiveness. Harnessing the spatial capabilities of a GIS enables the tool to provide a rich, interactive mapping environment in which users can create, analyze, visualize, and compare different\r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/tm11C4","usgsCitation":"Taketa, R., and Hong, M., 2010, Land-Use Portfolio Modeler, Version 1.0: U.S. Geological Survey Techniques and Methods 11-C4, vi, 44 p.; Appendices, https://doi.org/10.3133/tm11C4.","productDescription":"vi, 44 p.; Appendices","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":118495,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm_11_c4.gif"},{"id":13908,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/tm11c4/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b23e4b07f02db6adf28","contributors":{"authors":[{"text":"Taketa, Richard","contributorId":25250,"corporation":false,"usgs":true,"family":"Taketa","given":"Richard","affiliations":[],"preferred":false,"id":305615,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hong, Makiko","contributorId":31495,"corporation":false,"usgs":true,"family":"Hong","given":"Makiko","email":"","affiliations":[],"preferred":false,"id":305616,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":98526,"text":"ofr20101129 - 2010 - Digital tabulation of stratigraphic data from oil and gas wells in the Santa Maria Basin and surrounding areas, central California coast","interactions":[],"lastModifiedDate":"2012-02-10T00:11:53","indexId":"ofr20101129","displayToPublicDate":"2010-07-17T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-1129","title":"Digital tabulation of stratigraphic data from oil and gas wells in the Santa Maria Basin and surrounding areas, central California coast","docAbstract":"Stratigraphic information from 694 oil and gas exploration wells from the onshore Santa Maria basin and surrounding areas are herein compiled in digital form from reports that were released originally in paper form. The Santa Maria basin is located within the southwesternmost part of the Coast Ranges and north of the western Transverse Ranges on the central California coast. Knowledge of the location and elevation of stratigraphic tops of formations throughout the basin is a first step toward understanding depositional trends and the structural evolution of the basin through time.\r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20101129","usgsCitation":"Sweetkind, D., Tennyson, M., Langenheim, V., and Shumaker, L., 2010, Digital tabulation of stratigraphic data from oil and gas wells in the Santa Maria Basin and surrounding areas, central California coast: U.S. Geological Survey Open-File Report 2010-1129, iv, 11 p.; Downloads Directory, https://doi.org/10.3133/ofr20101129.","productDescription":"iv, 11 p.; Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":266,"text":"Environmental Resources Science Center","active":false,"usgs":true}],"links":[{"id":118489,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2010_1129.jpg"},{"id":13916,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2010/1129/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121,34.5 ], [ -121,35.333333333333336 ], [ -119.66666666666667,35.333333333333336 ], [ -119.66666666666667,34.5 ], [ -121,34.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a93e4b07f02db6581f0","contributors":{"authors":[{"text":"Sweetkind, Donald S.","contributorId":18732,"corporation":false,"usgs":true,"family":"Sweetkind","given":"Donald S.","affiliations":[],"preferred":false,"id":305638,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tennyson, Marilyn E. 0000-0002-5166-2421 tennyson@usgs.gov","orcid":"https://orcid.org/0000-0002-5166-2421","contributorId":1433,"corporation":false,"usgs":true,"family":"Tennyson","given":"Marilyn E.","email":"tennyson@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":305636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Langenheim, Victoria E. 0000-0003-2170-5213 zulanger@usgs.gov","orcid":"https://orcid.org/0000-0003-2170-5213","contributorId":1526,"corporation":false,"usgs":true,"family":"Langenheim","given":"Victoria E.","email":"zulanger@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":305637,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shumaker, Lauren E.","contributorId":99666,"corporation":false,"usgs":true,"family":"Shumaker","given":"Lauren E.","affiliations":[],"preferred":false,"id":305639,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":98524,"text":"ltrmp2008T002 - 2010 - Status and trends of selected resources in the Upper Mississippi River System","interactions":[],"lastModifiedDate":"2012-02-10T00:11:57","indexId":"ltrmp2008T002","displayToPublicDate":"2010-07-17T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":44,"text":"Long Term Resource Monitoring Program Technical Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"2008-T002","title":"Status and trends of selected resources in the Upper Mississippi River System","docAbstract":"Like other large rivers, the Upper Mississippi River System (UMRS) serves a diversity of roles. The UMRS provides commercial and recreational fishing, floodplain agriculture, drinking water for many communities, an important bird migration pathway, a variety of recreational activities, and a navigation system that transports much of the country's agricultural exports. These multiple roles present significant management challenges. Regular assessment of the condition of the river is needed to improve management plans and evaluate their effectiveness. This report provides a summary of the recent status (mean and range of conditions) and trends (change in direction over time) for 24 indicators of the ecological condition of the Upper Mississippi and Illinois Rivers using data collected through the Long Term Resource Monitoring Program (LTRMP). The 24 indicators were grouped into seven categories: hydrology, sedimentation, water quality, land cover, aquatic vegetation, invertebrates, and fish. Most of the data used in the report were collected between about 1993 and 2004, although some older data were also used to compare to recent conditions.Historical observations and current LTRMP data clearly indicate that the UMRS has been changed by human activity in ways that have diminished the ecological health of the river. The data indicate that status and trends differ among regions, and we expect that regional responses to various ecological rehabilitation techniques will differ as well. The continuing role of the LTRMP will be to provide the data needed to assess changes in river conditions and to determine how those changes relate to management actions, natural variation, and the overall ecological integrity of the river system.","language":"ENGLISH","publisher":"U.S. Geological Survey","collaboration":"A product of the Long Term Resource Monitoring Program in cooperation with the U.S. Army Corps of Engineers, Rock Island District","usgsCitation":"2010, Status and trends of selected resources in the Upper Mississippi River System: Long Term Resource Monitoring Program Technical Report 2008-T002, vi, 101 p.; Appendices.","productDescription":"vi, 101 p.; Appendices","additionalOnlineFiles":"N","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":116007,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ltrmp_2008_t002.jpg"},{"id":13914,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/mis/LTRMP2008-T002/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49d8e4b07f02db5df87e","contributors":{"editors":[{"text":"Johnson, Barry L. bljohnson@usgs.gov","contributorId":608,"corporation":false,"usgs":true,"family":"Johnson","given":"Barry","email":"bljohnson@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":505754,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Hagerty, Karen H.","contributorId":113500,"corporation":false,"usgs":true,"family":"Hagerty","given":"Karen","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":505755,"contributorType":{"id":2,"text":"Editors"},"rank":2}]}} ,{"id":98523,"text":"ofr20101123 - 2010 - Three-dimensional geologic model of the Arbuckle-Simpson aquifer, south-central Oklahoma","interactions":[],"lastModifiedDate":"2012-02-10T00:11:53","indexId":"ofr20101123","displayToPublicDate":"2010-07-17T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-1123","title":"Three-dimensional geologic model of the Arbuckle-Simpson aquifer, south-central Oklahoma","docAbstract":"The Arbuckle-Simpson aquifer of south-central Oklahoma encompasses more than 850 square kilometers and is the principal water resource for south-central Oklahoma. Rock units comprising the aquifer are characterized by limestone, dolomite, and sandstones assigned to two lower Paleozoic units: the Arbuckle and Simpson Groups. Also considered to be part of the aquifer is the underlying Cambrian-age Timbered Hills Group that contains limestone and sandstone. The highly faulted and fractured nature of the Arbuckle-Simpson units and the variable thickness (600 to 2,750 meters) increases the complexity in determining the subsurface geologic framework of this aquifer. \r\n\r\nA three-dimensional EarthVision (Trademark) geologic framework model was constructed to quantify the geometric relationships of the rock units of the Arbuckle-Simpson aquifer in the Hunton anticline area. This 3-D EarthVision (Trademark) geologic framework model incorporates 54 faults and four modeled units: basement, Arbuckle-Timbered Hills Group, Simpson Group, and post-Simpson. Primary data used to define the model's 54 faults and four modeled surfaces were obtained from geophysical logs, cores, and cuttings from 126 water and petroleum wells. The 3-D framework model both depicts the volumetric extent of the aquifer and provides the stratigraphic layer thickness and elevation data used to construct a MODFLOW version 2000 regional groundwater-flow model.\r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20101123","collaboration":"Prepared in cooperation with Oklahoma State University and the Oklahoma Water Resources Board","usgsCitation":"Faith, J.R., Blome, C.D., Pantea, M.P., Puckette, J.O., Halihan, T., Osborn, N., Christenson, S., and Pack, S., 2010, Three-dimensional geologic model of the Arbuckle-Simpson aquifer, south-central Oklahoma: U.S. Geological Survey Open-File Report 2010-1123, Report: iii, 26 p.; CD-ROM; Downloads Directory, https://doi.org/10.3133/ofr20101123.","productDescription":"Report: iii, 26 p.; CD-ROM; Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":263,"text":"Environmental Change Science Center","active":false,"usgs":true}],"links":[{"id":118487,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2010_1123.jpg"},{"id":13913,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2010/1123/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -97.33333333333333,34.166666666666664 ], [ -97.33333333333333,34.666666666666664 ], [ -96.33333333333333,34.666666666666664 ], [ -96.33333333333333,34.166666666666664 ], [ -97.33333333333333,34.166666666666664 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a08e4b07f02db5f9d2a","contributors":{"authors":[{"text":"Faith, Jason R.","contributorId":92758,"corporation":false,"usgs":true,"family":"Faith","given":"Jason","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":305630,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blome, Charles D. 0000-0002-3449-9378 cblome@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-9378","contributorId":1246,"corporation":false,"usgs":true,"family":"Blome","given":"Charles","email":"cblome@usgs.gov","middleInitial":"D.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":305624,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pantea, Michael P. mpantea@usgs.gov","contributorId":1549,"corporation":false,"usgs":true,"family":"Pantea","given":"Michael","email":"mpantea@usgs.gov","middleInitial":"P.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":305625,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Puckette, James O.","contributorId":60349,"corporation":false,"usgs":true,"family":"Puckette","given":"James","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":305628,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Halihan, Todd","contributorId":68856,"corporation":false,"usgs":true,"family":"Halihan","given":"Todd","affiliations":[],"preferred":false,"id":305629,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Osborn, Noel","contributorId":102975,"corporation":false,"usgs":true,"family":"Osborn","given":"Noel","affiliations":[],"preferred":false,"id":305631,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Christenson, Scott","contributorId":59128,"corporation":false,"usgs":true,"family":"Christenson","given":"Scott","affiliations":[],"preferred":false,"id":305627,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pack, Skip","contributorId":33809,"corporation":false,"usgs":true,"family":"Pack","given":"Skip","email":"","affiliations":[],"preferred":false,"id":305626,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":98516,"text":"ofr20101005 - 2010 - Surficial geology of the sea floor in Long Island Sound offshore of Plum Island, New York","interactions":[],"lastModifiedDate":"2012-02-10T00:11:52","indexId":"ofr20101005","displayToPublicDate":"2010-07-16T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-1005","title":"Surficial geology of the sea floor in Long Island Sound offshore of Plum Island, New York","docAbstract":"The U.S. Geological Survey (USGS), the Connecticut Department of Environmental Protection, and the National Oceanic and Atmospheric Administration (NOAA) have been working cooperatively to interpret surficial sea-floor geology along the coast of the Northeastern United States. NOAA survey H11445 in eastern Long Island Sound, offshore of Plum Island, New York, covers an area of about 12 square kilometers. Multibeam bathymetry and sidescan-sonar imagery from the survey, as well as sediment and photographic data from 13 stations occupied during a USGS verification cruise are used to delineate sea-floor features and characterize the environment. Bathymetry gradually deepens offshore to over 100 meters in a depression in the northwest part of the study area and reaches 60 meters in Plum Gut, a channel between Plum Island and Orient Point. Sand waves are present on a shoal north of Plum Island and in several smaller areas around the basin. Sand-wave asymmetry indicates that counter-clockwise net sediment transport maintains the shoal. Sand is prevalent where there is low backscatter in the sidescan-sonar imagery. Gravel and boulder areas are submerged lag deposits produced from the Harbor Hill-Orient Point-Fishers Island moraine segment and are found adjacent to the shorelines and just north of Plum Island, where high backscatter is present in the sidescan-sonar imagery.\r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20101005","usgsCitation":"McMullen, K., Poppe, L., Danforth, W.W., Blackwood, D., Schaer, J., Ostapenko, A., Glomb, K., and Doran, E.F., 2010, Surficial geology of the sea floor in Long Island Sound offshore of Plum Island, New York: U.S. Geological Survey Open-File Report 2010-1005, CD-ROM, https://doi.org/10.3133/ofr20101005.","productDescription":"CD-ROM","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":125650,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2010_1005.jpg"},{"id":13907,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2010/1005/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{\"crs\": {\"type\": \"name\", \"properties\": {\"name\": \"urn:ogc:def:crs:OGC:1.3:CRS84\"}}, \"geometry\": {\"type\": \"Polygon\", \"coordinates\": [[[-72.23516836276917, 41.16768711887295], [-72.23111763184, 41.178340452371295], [-72.2360517072875, 41.17939894490813], [-72.23543283444947, 41.18637645094174], [-72.18772946511221, 41.19593661813189], [-72.18786170095235, 41.197126740692894], [-72.1458631423921, 41.20404987477649], [-72.14512136415755, 41.20286914163183], [-72.14549329541614, 41.19467101663821], [-72.14411287914203, 41.19070342294655], [-72.14523804837421, 41.18980328756077], [-72.14806625153051, 41.19078676881565], [-72.15453111277291, 41.18971438530048], [-72.16174930335535, 41.19144436509123], [-72.17497263820324, 41.18693171594866], [-72.19023254914104, 41.18943660847439], [-72.19399829360924, 41.18833906687864], [-72.19500457354043, 41.18604311553214], [-72.19838125512348, 41.18529380923495], [-72.2006772064701, 41.18248150899762], [-72.205425214642, 41.1820179958073], [-72.21176069544987, 41.17810094910606], [-72.21336978269075, 41.173821257369966], [-72.20736572582194, 41.171201086952465], [-72.20995333749335, 41.16880846314797], [-72.20905598030328, 41.167174884114665], [-72.21048433928217, 41.164957000709194], [-72.21282599177988, 41.16357989896312], [-72.22358032145434, 41.16168732247473], [-72.22862258377774, 41.16259257603377], [-72.23362561844692, 41.160492387776856], [-72.23488486512088, 41.161207319890934], [-72.23455126218204, 41.163722799534845], [-72.23654066971932, 41.16428833884997], [-72.2348157338622, 41.16522147238929], [-72.23516836276917, 41.16768711887295]]]}, \"properties\": {\"extentType\": \"Custom\", \"code\": \"\", \"name\": \"\", \"notes\": \"\", \"promotedForReuse\": false, \"abbreviation\": \"\", \"shortName\": \"\", \"description\": \"\"}, \"bbox\": [-72.23654066971932, 41.160492387776856, -72.14411287914203, 41.20404987477649], \"type\": \"Feature\", \"id\": \"3091913\"}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ae1e4b07f02db6888b4","contributors":{"authors":[{"text":"McMullen, K.Y.","contributorId":51857,"corporation":false,"usgs":true,"family":"McMullen","given":"K.Y.","email":"","affiliations":[],"preferred":false,"id":305610,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poppe, L.J.","contributorId":72782,"corporation":false,"usgs":true,"family":"Poppe","given":"L.J.","affiliations":[],"preferred":false,"id":305612,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Danforth, W. W.","contributorId":16386,"corporation":false,"usgs":true,"family":"Danforth","given":"W.","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":305607,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blackwood, D.S.","contributorId":98747,"corporation":false,"usgs":true,"family":"Blackwood","given":"D.S.","email":"","affiliations":[],"preferred":false,"id":305614,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schaer, J.D.","contributorId":31082,"corporation":false,"usgs":true,"family":"Schaer","given":"J.D.","affiliations":[],"preferred":false,"id":305609,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ostapenko, A.J.","contributorId":90009,"corporation":false,"usgs":true,"family":"Ostapenko","given":"A.J.","email":"","affiliations":[],"preferred":false,"id":305613,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Glomb, K.A.","contributorId":67996,"corporation":false,"usgs":true,"family":"Glomb","given":"K.A.","email":"","affiliations":[],"preferred":false,"id":305611,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Doran, E. F.","contributorId":31066,"corporation":false,"usgs":true,"family":"Doran","given":"E.","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":305608,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70047032,"text":"dds49009 - 2010 - Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: Level 3 Ecoregions","interactions":[],"lastModifiedDate":"2013-11-25T16:00:42","indexId":"dds49009","displayToPublicDate":"2010-07-15T14:01:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"490-09","title":"Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: Level 3 Ecoregions","docAbstract":"This data set represents the estimated area of level 3 ecological landscape regions (ecoregions), as defined by Omernik (1987), compiled for every catchment of NHDPlus for the conterminous United States. The source data set is Level III Ecoregions of the Continental United States (U.S. Environmental Protection Agency, 2003). The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as \"the New England Method.\" This technique involves \"burning in\" the 1:100,000-scale NHD and when available building \"walls\" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dds49009","usgsCitation":"Wieczorek, M., and LaMotte, A.E., 2010, Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: Level 3 Ecoregions: U.S. Geological Survey Data Series 490-09, Datatset, https://doi.org/10.3133/dds49009.","productDescription":"Datatset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":274994,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":274993,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/nhd_eco3.xml"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -127.910792,23.243486 ], [ -127.910792,51.657387 ], [ 65.327751,51.657387 ], [ 65.327751,23.243486 ], [ -127.910792,23.243486 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51e519e4e4b069f8d27cca8e","contributors":{"authors":[{"text":"Wieczorek, Michael mewieczo@usgs.gov","contributorId":2309,"corporation":false,"usgs":true,"family":"Wieczorek","given":"Michael","email":"mewieczo@usgs.gov","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":false,"id":480903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LaMotte, Andrew E. 0000-0002-1434-6518 alamotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1434-6518","contributorId":2842,"corporation":false,"usgs":true,"family":"LaMotte","given":"Andrew","email":"alamotte@usgs.gov","middleInitial":"E.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480904,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70237833,"text":"70237833 - 2010 - A comparison of multi-spectral, multi-angular, and multi-temporal remote sensing datasets for fractional shrub canopy mapping in Arctic Alaska","interactions":[],"lastModifiedDate":"2022-10-26T11:47:36.243469","indexId":"70237833","displayToPublicDate":"2010-07-15T06:45:34","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"A comparison of multi-spectral, multi-angular, and multi-temporal remote sensing datasets for fractional shrub canopy mapping in Arctic Alaska","docAbstract":"Shrub cover appears to be increasing across many areas of the Arctic tundra biome, and increasing shrub cover in the Arctic has the potential to significantly impact global carbon budgets and the global climate system. For most of the Arctic, however, there is no existing baseline inventory of shrub canopy cover, as existing maps of Arctic vegetation provide little information about the density of shrub cover at a moderate spatial resolution across the region. Remotely-sensed fractional shrub canopy maps can provide this necessary baseline inventory of shrub cover. In this study, we compare the accuracy of fractional shrub canopy (> 0.5 m tall) maps derived from multi-spectral, multi-angular, and multi-temporal datasets from Landsat imagery at 30 m spatial resolution, Moderate Resolution Imaging SpectroRadiometer (MODIS) imagery at 250 m and 500 m spatial resolution, and MultiAngle Imaging Spectroradiometer (MISR) imagery at 275 m spatial resolution for a 1067 km2 study area in Arctic Alaska. The study area is centered at 69 °N, ranges in elevation from 130 to 770 m, is composed primarily of rolling topography with gentle slopes less than 10°, and is free of glaciers and perennial snow cover. Shrubs > 0.5 m in height cover 2.9% of the study area and are primarily confined to patches associated with specific landscape features. Reference fractional shrub canopy is determined from in situ shrub canopy measurements and a high spatial resolution IKONOS image swath. Regression tree models are constructed to estimate fractional canopy cover at 250 m using different combinations of input data from Landsat, MODIS, and MISR. Results indicate that multi-spectral data provide substantially more accurate estimates of fractional shrub canopy cover than multi-angular or multi-temporal data. Higher spatial resolution datasets also provide more accurate estimates of fractional shrub canopy cover (aggregated to moderate spatial resolutions) than lower spatial resolution datasets, an expected result for a study area where most shrub cover is concentrated in narrow patches associated with rivers, drainages, and slopes. Including the middle infrared bands available from Landsat and MODIS in the regression tree models (in addition to the four standard visible and near-infrared spectral bands) typically results in a slight boost in accuracy. Including the multi-angular red band data available from MISR in the regression tree models, however, typically boosts accuracy more substantially, resulting in moderate resolution fractional shrub canopy estimates approaching the accuracy of estimates derived from the much higher spatial resolution Landsat sensor. Given the poor availability of snow and cloud-free Landsat scenes in many areas of the Arctic and the promising results demonstrated here by the MISR sensor, MISR may be the best choice for large area fractional shrub canopy mapping in the Alaskan Arctic for the period 2000–2009.
After a major disaster, a satellite image or a collection of aerial photographs of the event is frequently the fastest, most effective way to determine its scope and severity. The U.S. Geological Survey (USGS) Emergency Operations Portal provides emergency first responders and support personnel with easy access to imagery and geospatial data, geospatial Web services, and a digital library focused on emergency operations. Imagery and geospatial data are accessed through the Hazards Data Distribution System (HDDS). HDDS historically provided data access and delivery services through nongraphical interfaces that allow emergency response personnel to select and obtain pre-event baseline data and (or) event/disaster response data. First responders are able to access full-resolution GeoTIFF images or JPEG images at medium- and low-quality compressions through ftp downloads. USGS HDDS home page: http://hdds.usgs.gov/hdds2/
","language":"ENGLISH","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20103053","usgsCitation":"Jones, B., and Lamb, R.M., 2010, The Hazards Data Distribution System update (2.0): U.S. Geological Survey Fact Sheet 2010-3053, 1 p., https://doi.org/10.3133/fs20103053.","productDescription":"1 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":116130,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2010_3053.jpg"},{"id":13896,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2010/3053/","linkFileType":{"id":5,"text":"html"}}],"edition":"2.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ac9e4b07f02db67c530","contributors":{"authors":[{"text":"Jones, Brenda K. 0000-0003-4941-5349","orcid":"https://orcid.org/0000-0003-4941-5349","contributorId":60739,"corporation":false,"usgs":true,"family":"Jones","given":"Brenda K.","affiliations":[],"preferred":false,"id":305575,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lamb, Rynn M. 0000-0001-6054-4139 lamb@usgs.gov","orcid":"https://orcid.org/0000-0001-6054-4139","contributorId":4038,"corporation":false,"usgs":true,"family":"Lamb","given":"Rynn","email":"lamb@usgs.gov","middleInitial":"M.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":305574,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":98508,"text":"fs20103055 - 2010 - The National Map: New Viewer, Services, and Data Download","interactions":[],"lastModifiedDate":"2012-02-02T00:14:44","indexId":"fs20103055","displayToPublicDate":"2010-07-10T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-3055","title":"The National Map: New Viewer, Services, and Data Download","docAbstract":"Managed by the U.S. Geological Survey's (USGS) National Geospatial Program, The National Map has transitioned data assets and viewer applications to a new visualization and product and service delivery environment, which includes an improved viewing platform, base map data and overlay services, and an integrated data download service. \r\n\r\nThis new viewing solution expands upon the National Geospatial Intelligence Agency (NGA) Palanterra X3 viewer, providing a solid technology foundation for navigation and basic Web mapping functionality. Building upon the NGA viewer allows The National Map to focus on improving data services, functions, and data download capabilities. Initially released to the public at the 125th anniversary of mapping in the USGS on December 3, 2009, the viewer and services are now the primary distribution point for The National Map data. \r\n\r\nThe National Map Viewer: http://viewer.nationalmap.gov\r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/fs20103055","usgsCitation":"Dollison, R.M., 2010, The National Map: New Viewer, Services, and Data Download: U.S. Geological Survey Fact Sheet 2010-3055, 2 p., https://doi.org/10.3133/fs20103055.","productDescription":"2 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":125932,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2010_3055.png"},{"id":13897,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2010/3055/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ac7e4b07f02db67b01c","contributors":{"authors":[{"text":"Dollison, Robert M. rdollison@usgs.gov","contributorId":3751,"corporation":false,"usgs":true,"family":"Dollison","given":"Robert","email":"rdollison@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":305576,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":98506,"text":"sir20105045 - 2010 - Alluvial Diamond Resource Potential and Production Capacity Assessment of Ghana","interactions":[],"lastModifiedDate":"2012-02-10T00:11:52","indexId":"sir20105045","displayToPublicDate":"2010-07-10T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-5045","title":"Alluvial Diamond Resource Potential and Production Capacity Assessment of Ghana","docAbstract":"In May of 2000, a meeting was convened in Kimberley, South Africa, and attended by representatives of the diamond industry and leaders of African governments to develop a certification process intended to assure that rough, exported diamonds were free of conflictual concerns. This meeting was supported later in 2000 by the United Nations in a resolution adopted by the General Assembly. By 2002, the Kimberley Process Certification Scheme (KPCS) was ratified and signed by both diamond-producing and diamond-importing countries. Over 70 countries were included as members at the end of 2007.\r\n\r\nTo prevent trade in 'conflict' diamonds while protecting legitimate trade, the KPCS requires that each country set up an internal system of controls to prevent conflict diamonds from entering any imported or exported shipments of rough diamonds. Every diamond or diamond shipment must be accompanied by a Kimberley Process (KP) certificate and be contained in tamper-proof packaging. \r\n\r\nThe objective of this study was to assess the alluvial diamond resource endowment and current production capacity of the alluvial diamond-mining sector in Ghana. A modified volume and grade methodology was used to estimate the remaining diamond reserves within the Birim and Bonsa diamond fields. The production capacity of the sector was estimated using a formulaic expression of the number of workers reported in the sector, their productivity, and the average grade of deposits mined. This study estimates that there are approximately 91,600,000 carats of alluvial diamonds remaining in both the Birim and Bonsa diamond fields: 89,000,000 carats in the Birim and 2,600,000 carats in the Bonsa. \r\n\r\nProduction capacity is calculated to be 765,000 carats per year, based on the formula used and available data on the number of workers and worker productivity. Annual production is highly dependent on the international diamond market and prices, the numbers of seasonal workers actively mining in the sector, and environmental conditions, which influence seasonal farming. \r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20105045","collaboration":"Prepared in cooperation with the Geological Survey Department,\r\nMinerals Commission, \r\nand Precious Minerals Marketing Company of Ghana\r\nunder the auspices of the U.S. Department of State","usgsCitation":"Chirico, P., Malpeli, K., Anum, S., and Phillips, E.C., 2010, Alluvial Diamond Resource Potential and Production Capacity Assessment of Ghana: U.S. Geological Survey Scientific Investigations Report 2010-5045, iv, 25 p. , https://doi.org/10.3133/sir20105045.","productDescription":"iv, 25 p. ","costCenters":[{"id":410,"text":"National Center","active":false,"usgs":true}],"links":[{"id":125931,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2010_5045.jpg"},{"id":13895,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5045/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -20,5 ], [ -20,20 ], [ 13,20 ], [ 13,5 ], [ -20,5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4adee4b07f02db687526","contributors":{"authors":[{"text":"Chirico, Peter G.","contributorId":27086,"corporation":false,"usgs":true,"family":"Chirico","given":"Peter G.","affiliations":[],"preferred":false,"id":305570,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Malpeli, Katherine C.","contributorId":55106,"corporation":false,"usgs":true,"family":"Malpeli","given":"Katherine C.","affiliations":[],"preferred":false,"id":305571,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anum, Solomon","contributorId":91587,"corporation":false,"usgs":true,"family":"Anum","given":"Solomon","email":"","affiliations":[],"preferred":false,"id":305573,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Phillips, Emily C.","contributorId":65189,"corporation":false,"usgs":true,"family":"Phillips","given":"Emily","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":305572,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":98505,"text":"sir20105105 - 2010 - Simulated groundwater flow in the Ogallala and Arikaree aquifers, Rosebud Indian Reservation area, South Dakota – Revisions with data through water year 2008 and simulations of potential future scenarios","interactions":[],"lastModifiedDate":"2021-12-14T19:52:30.499727","indexId":"sir20105105","displayToPublicDate":"2010-07-09T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-5105","title":"Simulated groundwater flow in the Ogallala and Arikaree aquifers, Rosebud Indian Reservation area, South Dakota – Revisions with data through water year 2008 and simulations of potential future scenarios","docAbstract":"The Ogallala and Arikaree aquifers are important water resources in the Rosebud Indian Reservation area and are used extensively for irrigation, municipal, and domestic water supplies. Drought or increased withdrawals from the Ogallala and Arikaree aquifers in the Rosebud Indian Reservation area have the potential to affect water levels in these aquifers. This report documents revisions and recalibration of a previously published three-dimensional, numerical groundwater-flow model for this area. Data for a 30-year period (water years 1979 through 2008) were used in steady-state and transient numerical simulations of groundwater flow. In the revised model, revisions include (1) extension of the transient calibration period by 10 years, (2) the use of inverse modeling for steady-state calibration, (3) model calibration to base flow for an additional four surface-water drainage basins, (4) improved estimation of transient aquifer recharge, (5) improved delineation of vegetation types, and (6) reduced cell size near large capacity water-supply wells. In addition, potential future scenarios were simulated to assess the potential effects of drought and increased groundwater withdrawals.
The model comprised two layers: the upper layer represented the Ogallala aquifer and the lower layer represented the Arikaree aquifer. The model’s grid had 168 rows and 202 columns, most of which were 1,640 feet (500 meters) wide, with narrower rows and columns near large water-supply wells. Recharge to the Ogallala and Arikaree aquifers occurs from precipitation on the outcrop areas. The average recharge rates used for the steady-state simulation were 2.91 and 1.45 inches per year for the Ogallala aquifer and Arikaree aquifer, respectively, for a total rate of 255.4 cubic feet per second (ft3/s). Discharge from the aquifers occurs through evapotranspiration, discharge to streams as base flow and spring flow, and well withdrawals. Discharge rates for the steady-state simulation were 171.3 ft3/s for evapotranspiration, 74.4 ft3/s for net outflow to streams and springs, and 11.6 ft3/s for well withdrawals. Estimated horizontal hydraulic conductivity used for the numerical model ranged from 0.2 to 84.4 feet per day (ft/d) in the Ogallala aquifer and from 0.1 to 4.3 ft/d in the Arikaree aquifer. A uniform vertical hydraulic conductivity value of 4.2x10-4 ft/d was estimated for the Ogallala aquifer. Vertical hydraulic conductivity was estimated for five zones in the Arikaree aquifer and ranged from 8.8x10-5 to 3.7 ft/d. Average rates of recharge, maximum evapotranspiration, and well withdrawals were included in the steady-state simulation, whereas the time-varying rates were included in the transient simulation.
Inverse modeling techniques were used for steady-state model calibration. These methods were designed to estimate parameter values that are, statistically, the most likely set of values to result in the smallest differences between simulated and observed hydraulic heads and base-flow discharges. For the steady-state simulation, the root mean square error for simulated hydraulic heads for all 383 wells was 27.3 feet. Simulated hydraulic heads were within ±50 feet of observed values for 93 percent of the wells. The potentiometric surfaces of the two aquifers calculated by the steady-state simulation established initial conditions for the transient simulation. For the transient simulation, the difference between the simulated and observed means for hydrographs was within ±40 feet for 98 percent of 44 observation wells.
A sensitivity analysis was used to examine the response of the calibrated steady-state model to changes in model parameters including horizontal and vertical hydraulic conductivity, evapotranspiration, recharge, and riverbed conductance. The model was most sensitive to recharge and maximum evapotranspiration and least sensitive to riverbed and spring conductances.
To simulate a potential future drought scenario, a synthetic recharge record was created, the mean of which was equal to 64 percent of the average estimated recharge rate for the 30-year calibration period. This synthetic recharge record was used to simulate the last 20 years of the calibration period under drought conditions. Compared with results of the calibrated model, decreases in hydraulic-head values for the drought scenario at the end of the simulation period were as much as 39 feet for the Ogallala aquifer. To simulate the effects of potential increases in pumping, well withdrawal rates were increased by 50 percent from those estimated for the 30-year calibration period for the last 20 years of the calibration period. Compared with results of the calibrated model, decreases in hydraulic-head values for the scenario of increased pumping at the end of the simulation period were as much as 13 feet for the Ogallala aquifer.
This numerical model is suitable as a tool to help understand the flow system, to help confirm that previous estimates of aquifer properties were reasonable, and to estimate aquifer properties in areas without data. The model also is useful to help assess the effects of drought and increases in pumping by simulations of these scenarios, the results of which are not precise but may be considered when making water management decisions.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sir20105105","collaboration":"Prepared in cooperation with the Rosebud Sioux Tribe","usgsCitation":"Long, A.J., and Putnam, L.D., 2010, Simulated groundwater flow in the Ogallala and Arikaree aquifers, Rosebud Indian Reservation area, South Dakota – Revisions with data through water year 2008 and simulations of potential future scenarios: U.S. Geological Survey Scientific Investigations Report 2010-5105, viii, 54 p., https://doi.org/10.3133/sir20105105.","productDescription":"viii, 54 p.","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2007-10-01","temporalEnd":"2008-09-30","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":118481,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2010_5105.jpg"},{"id":392872,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_93504.htm"},{"id":13894,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5105/","linkFileType":{"id":5,"text":"html"}}],"scale":"1","projection":"Universal Transverse Mercator","country":"United States","state":"South Dakota","otherGeospatial":"Arikaree aquifer, Ogallala aquifer, Rosebud Indian Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.2881,\n 42.96\n ],\n [\n -100.1711,\n 42.96\n ],\n [\n -100.1711,\n 43.6456\n ],\n [\n -101.2881,\n 43.6456\n ],\n [\n -101.2881,\n 42.96\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4acce4b07f02db67e568","contributors":{"authors":[{"text":"Long, Andrew J. 0000-0001-7385-8081 ajlong@usgs.gov","orcid":"https://orcid.org/0000-0001-7385-8081","contributorId":989,"corporation":false,"usgs":true,"family":"Long","given":"Andrew","email":"ajlong@usgs.gov","middleInitial":"J.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":305568,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Putnam, Larry D. ldputnam@usgs.gov","contributorId":990,"corporation":false,"usgs":true,"family":"Putnam","given":"Larry","email":"ldputnam@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":305569,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":98502,"text":"ofr20101095 - 2010 - A Review of Aeromagnetic Anomalies in the Sawatch Range, Central Colorado","interactions":[],"lastModifiedDate":"2012-02-10T00:11:53","indexId":"ofr20101095","displayToPublicDate":"2010-07-09T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-1095","title":"A Review of Aeromagnetic Anomalies in the Sawatch Range, Central Colorado","docAbstract":"This report contains digital data and image files of aeromagnetic anomalies in the Sawatch Range of central Colorado. The primary product is a data layer of polygons with linked data records that summarize previous interpretations of aeromagnetic anomalies in this region. None of these data files and images are new; rather, they are presented in updated formats that are intended to be used as input to geographic information systems, standard graphics software, or map-plotting packages.\r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20101095","usgsCitation":"Bankey, V., 2010, A Review of Aeromagnetic Anomalies in the Sawatch Range, Central Colorado: U.S. Geological Survey Open-File Report 2010-1095, iii, 5 p.; Downloads Directory, https://doi.org/10.3133/ofr20101095.","productDescription":"iii, 5 p.; Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":266,"text":"Environmental Resources Science Center","active":false,"usgs":true}],"links":[{"id":118483,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2010_1095.jpg"},{"id":13890,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2010/1095/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -107,38 ], [ -107,39.75 ], [ -105.75,39.75 ], [ -105.75,38 ], [ -107,38 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd4966e4b0b290850ef21b","contributors":{"authors":[{"text":"Bankey, Viki viki@usgs.gov","contributorId":1238,"corporation":false,"usgs":true,"family":"Bankey","given":"Viki","email":"viki@usgs.gov","affiliations":[],"preferred":true,"id":305545,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":98503,"text":"ofr20101144 - 2010 - Public Review Draft: A Method for Assessing Carbon Stocks, Carbon Sequestration, and Greenhouse-Gas Fluxes in Ecosystems of the United States Under Present Conditions and Future Scenarios","interactions":[{"subject":{"id":98503,"text":"ofr20101144 - 2010 - Public Review Draft: A Method for Assessing Carbon Stocks, Carbon Sequestration, and Greenhouse-Gas Fluxes in Ecosystems of the United States Under Present Conditions and Future Scenarios","indexId":"ofr20101144","publicationYear":"2010","noYear":false,"title":"Public Review Draft: A Method for Assessing Carbon Stocks, Carbon Sequestration, and Greenhouse-Gas Fluxes in Ecosystems of the United States Under Present Conditions and Future Scenarios"},"predicate":"SUPERSEDED_BY","object":{"id":98900,"text":"sir20105233 - 2010 - A method for assessing carbon stocks, carbon sequestration, and greenhouse-gas fluxes in ecosystems of the United States under present conditions and future scenarios","indexId":"sir20105233","publicationYear":"2010","noYear":false,"title":"A method for assessing carbon stocks, carbon sequestration, and greenhouse-gas fluxes in ecosystems of the United States under present conditions and future scenarios"},"id":1}],"supersededBy":{"id":98900,"text":"sir20105233 - 2010 - A method for assessing carbon stocks, carbon sequestration, and greenhouse-gas fluxes in ecosystems of the United States under present conditions and future scenarios","indexId":"sir20105233","publicationYear":"2010","noYear":false,"title":"A method for assessing carbon stocks, carbon sequestration, and greenhouse-gas fluxes in ecosystems of the United States under present conditions and future scenarios"},"lastModifiedDate":"2012-02-02T00:15:01","indexId":"ofr20101144","displayToPublicDate":"2010-07-09T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-1144","title":"Public Review Draft: A Method for Assessing Carbon Stocks, Carbon Sequestration, and Greenhouse-Gas Fluxes in Ecosystems of the United States Under Present Conditions and Future Scenarios","docAbstract":"The Energy Independence and Security Act of 2007 (EISA), Section 712, authorizes the U.S. Department of the Interior to develop a methodology and conduct an assessment of the Nation's ecosystems focusing on carbon stocks, carbon sequestration, and emissions of three greenhouse gases (GHGs): carbon dioxide, methane, and nitrous oxide. The major requirements include (1) an assessment of all ecosystems (terrestrial systems, such as forests, croplands, wetlands, shrub and grasslands; and aquatic ecosystems, such as rivers, lakes, and estuaries), (2) an estimation of annual potential capacities of ecosystems to increase carbon sequestration and reduce net GHG emissions in the context of mitigation strategies (including management and restoration activities), and (3) an evaluation of the effects of controlling processes, such as climate change, land use and land cover, and wildlfires. The purpose of this draft methodology for public review is to propose a technical plan to conduct the assessment. \r\nWithin the methodology, the concepts of ecosystems, carbon pools, and GHG fluxes used for the assessment follow conventional definitions in use by major national and international assessment or inventory efforts. In order to estimate current ecosystem carbon stocks and GHG fluxes and to understand the potential capacity and effects of mitigation strategies, the method will use two time periods for the assessment: 2001 through 2010, which establishes a current ecosystem GHG baseline and will be used to validate the models; and 2011 through 2050, which will be used to assess future potential conditions based on a set of projected scenarios. The scenario framework is constructed using storylines of the Intergovernmental Panel on Climate Change (IPCC) Special Report Emission Scenarios (SRES), along with initial reference land-use and land-cover (LULC) and land-management scenarios. An additional three LULC and land-management mitigation scenarios will be constructed for each storyline to enhance carbon sequestration and reduce GHG fluxes in ecosystems. Input from regional experts and stakeholders will be solicited to construct realistic and meaningful scenarios. \r\nThe methods for mapping the current LULC and ecosystem disturbances will require the extensive use of both remote-sensing data and in-situ (for example, forest inventory data) to capture and characterize landscape-change events. For future potential LULC and ecosystem disturbances, key drivers such as socioeconomic, policy, and climate assumptions will be used in addition to biophysical data. The product of these analyses will be a series of maps for each future year for each scenario. These annual maps will form the basis for estimating carbon storage and GHG emissions. For terrestrial ecosystems, carbon storage, carbon-sequestration capacities, and GHG emissions under the current and projected future conditions will be assessed using the LULC and ecosystem-disturbance estimates in map format with a spatially explicit biogeochemical ensemble modeling system that incorporates properties of management activities (such as tillage or harvesting) and properties of individual ecosystems (such as elevation, vegetation characteristics, and soil attributes). For aquatic ecosystems, carbon burial in sediments and GHG fluxes are functions of the current and projected future stream flow and sediment transports, and therefore will be assessed using empirical modeling methods. Validation and uncertainty analysis methods described in the methodology will follow established guidelines to assess the quality of the assessment results. \r\nThe U.S. Environmental Protection Agency's Level II ecoregions map (which delineates 24 ecoregions for the Nation) will be the practical instrument for developing and delivering assessment results. Consequently, the ecoregion will be the reporting unit of the assessment because the mitigation scenarios, assessment results, validation, and uncertainty analysis will be","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20101144","usgsCitation":"Bergamaschi, B., Bernknopf, R., Clow, D., Dye, D., Faulkner, S., Forney, W., Gleason, R., Hawbaker, T., Liu, J., Liu, S., Prisley, S., Reed, B., Reeves, M., Rollins, M., Sleeter, B., Sohl, T., Stackpoole, S., Stehman, S., Striegl, R.G., Wein, A., and Zhu, Z., 2010, Public Review Draft: A Method for Assessing Carbon Stocks, Carbon Sequestration, and Greenhouse-Gas Fluxes in Ecosystems of the United States Under Present Conditions and Future Scenarios: U.S. Geological Survey Open-File Report 2010-1144, xviii, 196 p.; Appendices, https://doi.org/10.3133/ofr20101144.","productDescription":"xviii, 196 p.; 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Alaska","interactions":[],"lastModifiedDate":"2012-02-10T00:10:06","indexId":"ofr20101135","displayToPublicDate":"2010-07-08T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-1135","title":"Initial Results from a Study of Climatic Changes and the Effect on Wild Sheep Habitat in Selected Study Areas of Alaska","docAbstract":"Climate change theorists have projected striking changes in local weather on earth due to increases in temperature. These predicted changes may cause melting glaciers and ice caps, rising sea levels, increasing desertification and other environmental changes which seem likely to affect presumed indicator species as harbingers of more significant changes. Wild sheep, even though they are one of the more successful mammalian taxa since Pleistocene times, exhibit a suite of adaptations to glacier driven environments which may be presumed to render them sensitive to environmental changes. The authors began investigation with these assumptions by comparing changes, as determined by satellite imagery, in glacier extent in our study areas in Denali National Park, Alaska, during the last 30 years. Our findings showed the extent of glacial retreat in Alaska during this time period was approximately 40-50 percent as measured by ablation zone and retreat of terminal moraines. During the first half of this 30-year period, Dall sheep (Ovis dalli dalli) populations were stable at historically recorded highs. In the early to mid-1990s, Dall sheep populations in Alaska declined from an historical estimated high of 75,000 sheep to the presently estimated 40-50,000. The declines seemed to be weather related, on the basis of the presumption that lamb survival rates are primarily weather-mediated in Alaska. Changes in local weather appear, at this point, to be correlated with oscillation in the Pacific Current in the Northern Pacific ocean. Of course, changes in local weather affect forage abundance and quality seasonally. In investigating a possible linkage of weather to seasonal forage abundance and quality, we also investigated changes in snow and ice extent and distribution, as well as increased water runoff associated with permafrost and depleted glaciers. Databases were assembled from a wide variety of remotely sensed satellite data, ground-based observations, and historical data bases relating to Dall sheep habitats in selected study areas. Alaska's sheep habitats are typified by long, narrow bands of mountainous uplifts generally arrayed west-to-east, and perpendicular to prevailing south-to-north weather-front movements. Classic Dall sheep habitat occurs on snow-shadowed slopes within these narrow mountainous habitats. On the basis of these data, we offer an explanatory hypothesis relating Dall sheep welfare to weather and climate-influenced nutrition and a monitoring scheme, which should produce data sufficient to test the robustness of this hypothesis. If correlated with population changes, the methods used in our comparative observations may provide long-term monitoring tools for wildlife managers and be applicable in other widely-dispersed wild sheep habitats. If no significant correlations emerge from our modeling exercises, the notion that wild sheep are a sufficiently sensitive species to be seen as an indicator species will have to be reexamined. \r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20101135","usgsCitation":"Pfeifer, E., Ruhlman, J., Middleton, B., Dye, D., and Acosta, A., 2010, Initial Results from a Study of Climatic Changes and the Effect on Wild Sheep Habitat in Selected Study Areas of Alaska: U.S. Geological Survey Open-File Report 2010-1135, iv, 39 p.; Appendices, https://doi.org/10.3133/ofr20101135.","productDescription":"iv, 39 p.; Appendices","onlineOnly":"Y","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":125930,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2010_1135.jpg"},{"id":13886,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2010/1135/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -150.33333333333334,63.166666666666664 ], [ -150.33333333333334,63.666666666666664 ], [ -149,63.666666666666664 ], [ -149,63.166666666666664 ], [ -150.33333333333334,63.166666666666664 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4acce4b07f02db67e886","contributors":{"authors":[{"text":"Pfeifer, Edwin epfeifer@usgs.gov","contributorId":569,"corporation":false,"usgs":true,"family":"Pfeifer","given":"Edwin","email":"epfeifer@usgs.gov","affiliations":[],"preferred":true,"id":305534,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ruhlman, Jana","contributorId":93013,"corporation":false,"usgs":true,"family":"Ruhlman","given":"Jana","email":"","affiliations":[],"preferred":false,"id":305538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Middleton, Barry","contributorId":38119,"corporation":false,"usgs":true,"family":"Middleton","given":"Barry","affiliations":[],"preferred":false,"id":305535,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dye, Dennis","contributorId":54159,"corporation":false,"usgs":true,"family":"Dye","given":"Dennis","affiliations":[],"preferred":false,"id":305536,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Acosta, Alex aacosta@usgs.gov","contributorId":73557,"corporation":false,"usgs":true,"family":"Acosta","given":"Alex","email":"aacosta@usgs.gov","affiliations":[],"preferred":false,"id":305537,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}