We evaluated competing models explaining the occurrence of five stream fishes in an urbanizing watershed to determine the relative importance of (a) impervious surface and other indicators of current land use, (b) historic land use (e.g., agriculture, impoundments), and (c) hydrogeomorphic characteristics (e.g., stream size, elevation, geology). For four of five species, the best-supported models were those that included both current effective impervious cover and historic land use predictor variables, although models with only effective impervious cover were equally well supported for two of those species. For the best-supported models for three species, occurrence probability was predicted to approach zero at levels of development equivalent to about 2%–4% effective impervious cover in the surrounding region. Data were drawn from 357 fish collections made in the Etowah River basin, Georgia, USA, between 1998 and 2003 and analyzed using hierarchical logistic regression accounting for imperfect species detection. This is the first study we know of to examine the response of individual fish species to both increasing impervious cover and historic land use. Such individual species assessments will be increasingly necessary to guide policies for managing urban effects and preventing extirpations of sensitive species.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/F08-046","usgsCitation":"Wenger, S.J., Peterson, J., Freeman, M.C., Freeman, B.J., and Homans, D.D., 2008, Stream fish occurrence in response to impervious cover, historic land use, and hydrogeomorphic factors: Canadian Journal of Fisheries and Aquatic Sciences, v. 65, no. 7, p. 1250-1264, https://doi.org/10.1139/F08-046.","productDescription":"15 p.","startPage":"1250","endPage":"1264","numberOfPages":"15","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":202082,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"65","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4adbe4b07f02db685a4b","contributors":{"authors":[{"text":"Wenger, Seth J.","contributorId":64786,"corporation":false,"usgs":true,"family":"Wenger","given":"Seth","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":342986,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterson, James T. 0000-0002-7709-8590 james_peterson@usgs.gov","orcid":"https://orcid.org/0000-0002-7709-8590","contributorId":2111,"corporation":false,"usgs":true,"family":"Peterson","given":"James","email":"james_peterson@usgs.gov","middleInitial":"T.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":342985,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Freeman, Mary C. 0000-0001-7615-6923","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":99659,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":342987,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Freeman, Byron J.","contributorId":49782,"corporation":false,"usgs":false,"family":"Freeman","given":"Byron","email":"","middleInitial":"J.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":342984,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Homans, D. David","contributorId":107833,"corporation":false,"usgs":true,"family":"Homans","given":"D.","email":"","middleInitial":"David","affiliations":[],"preferred":false,"id":342988,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":5224859,"text":"5224859 - 2008 - Estimation and correction of visibility bias in aerial surveys of wintering ducks","interactions":[],"lastModifiedDate":"2012-02-02T00:15:32","indexId":"5224859","displayToPublicDate":"2010-06-16T12:18:33","publicationYear":"2008","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Estimation and correction of visibility bias in aerial surveys of wintering ducks","docAbstract":"Incomplete detection of all individuals leading to negative bias in abundance estimates is a pervasive source of error in aerial surveys of wildlife, and correcting that bias is a critical step in improving surveys. We conducted experiments using duck decoys as surrogates for live ducks to estimate bias associated with surveys of wintering ducks in Mississippi, USA. We found detection of decoy groups was related to wetland cover type (open vs. forested), group size (1?100 decoys), and interaction of these variables. Observers who detected decoy groups reported counts that averaged 78% of the decoys actually present, and this counting bias was not influenced by either covariate cited above. We integrated this sightability model into estimation procedures for our sample surveys with weight adjustments derived from probabilities of group detection (estimated by logistic regression) and count bias. To estimate variances of abundance estimates, we used bootstrap resampling of transects included in aerial surveys and data from the bias-correction experiment. When we implemented bias correction procedures on data from a field survey conducted in January 2004, we found bias-corrected estimates of abundance increased 36?42%, and associated standard errors increased 38?55%, depending on species or group estimated. We deemed our method successful for integrating correction of visibility bias in an existing sample survey design for wintering ducks in Mississippi, and we believe this procedure could be implemented in a variety of sampling problems for other locations and species.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Wildlife Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","collaboration":"6915_Pearse.pdf","usgsCitation":"Pearse, A., Gerard, P., Dinsmore, S., Kaminski, R., and Reinecke, K.J., 2008, Estimation and correction of visibility bias in aerial surveys of wintering ducks: Journal of Wildlife Management, v. 72, no. 3, p. 808-813.","productDescription":"808-813","startPage":"808","endPage":"813","numberOfPages":"6","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":16901,"rank":200,"type":{"id":11,"text":"Document"},"url":"https://www.bioone.org/perlserv/?request=get-abstract&doi=10.2193%2F2007-274","linkFileType":{"id":5,"text":"html"}},{"id":201793,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"72","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a0be4b07f02db5fbe31","contributors":{"authors":[{"text":"Pearse, A.T.","contributorId":56333,"corporation":false,"usgs":true,"family":"Pearse","given":"A.T.","email":"","affiliations":[],"preferred":false,"id":342928,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gerard, P.D.","contributorId":16368,"corporation":false,"usgs":true,"family":"Gerard","given":"P.D.","email":"","affiliations":[],"preferred":false,"id":342925,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dinsmore, S.J.","contributorId":85114,"corporation":false,"usgs":true,"family":"Dinsmore","given":"S.J.","email":"","affiliations":[],"preferred":false,"id":342929,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kaminski, R.M.","contributorId":53330,"corporation":false,"usgs":true,"family":"Kaminski","given":"R.M.","email":"","affiliations":[],"preferred":false,"id":342926,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reinecke, K. J.","contributorId":54537,"corporation":false,"usgs":true,"family":"Reinecke","given":"K.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":342927,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":5224851,"text":"5224851 - 2008 - A hierarchical model for estimating change in American Woodcock populations","interactions":[],"lastModifiedDate":"2012-02-02T00:15:30","indexId":"5224851","displayToPublicDate":"2010-06-16T12:18:33","publicationYear":"2008","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"A hierarchical model for estimating change in American Woodcock populations","docAbstract":"The Singing-Ground Survey (SGS) is a primary source of information on population change for American woodcock (Scolopax minor). We analyzed the SGS using a hierarchical log-linear model and compared the estimates of change and annual indices of abundance to a route regression analysis of SGS data. We also grouped SGS routes into Bird Conservation Regions (BCRs) and estimated population change and annual indices using BCRs within states and provinces as strata. Based on the hierarchical model?based estimates, we concluded that woodcock populations were declining in North America between 1968 and 2006 (trend = -0.9%/yr, 95% credible interval: -1.2, -0.5). Singing-Ground Survey results are generally similar between analytical approaches, but the hierarchical model has several important advantages over the route regression. Hierarchical models better accommodate changes in survey efficiency over time and space by treating strata, years, and observers as random effects in the context of a log-linear model, providing trend estimates that are derived directly from the annual indices. We also conducted a hierarchical model analysis of woodcock data from the Christmas Bird Count and the North American Breeding Bird Survey. All surveys showed general consistency in patterns of population change, but the SGS had the shortest credible intervals. We suggest that population management and conservation planning for woodcock involving interpretation of the SGS use estimates provided by the hierarchical model.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Wildlife Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","collaboration":"6895_Sauer.pdf","usgsCitation":"Sauer, J., Link, W., Kendall, W., Kelley, J., and Niven, D., 2008, A hierarchical model for estimating change in American Woodcock populations: Journal of Wildlife Management, v. 72, no. 1, p. 204-214.","productDescription":"204-214","startPage":"204","endPage":"214","numberOfPages":"11","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":16897,"rank":200,"type":{"id":11,"text":"Document"},"url":"https://www.bioone.org/doi/abs/10.2193/2006-534","linkFileType":{"id":5,"text":"html"}},{"id":202168,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"72","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b24e4b07f02db6ae4a1","contributors":{"authors":[{"text":"Sauer, J.R. 0000-0002-4557-3019","orcid":"https://orcid.org/0000-0002-4557-3019","contributorId":66197,"corporation":false,"usgs":true,"family":"Sauer","given":"J.R.","affiliations":[],"preferred":false,"id":342903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Link, W.A. 0000-0002-9913-0256","orcid":"https://orcid.org/0000-0002-9913-0256","contributorId":8815,"corporation":false,"usgs":true,"family":"Link","given":"W.A.","affiliations":[],"preferred":false,"id":342900,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kendall, W. L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":32880,"corporation":false,"usgs":true,"family":"Kendall","given":"W. L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":342902,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kelley, J.R.","contributorId":98437,"corporation":false,"usgs":true,"family":"Kelley","given":"J.R.","email":"","affiliations":[],"preferred":false,"id":342904,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Niven, D.K.","contributorId":21247,"corporation":false,"usgs":true,"family":"Niven","given":"D.K.","email":"","affiliations":[],"preferred":false,"id":342901,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":5224862,"text":"5224862 - 2008 - Hierarchical Bayes estimation of species richness and occupancy in spatially replicated surveys","interactions":[],"lastModifiedDate":"2012-02-02T00:15:32","indexId":"5224862","displayToPublicDate":"2010-06-16T12:18:33","publicationYear":"2008","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Hierarchical Bayes estimation of species richness and occupancy in spatially replicated surveys","docAbstract":"1. Species richness is the most widely used biodiversity metric, but cannot be observed directly as, typically, some species are overlooked. Imperfect detectability must therefore be accounted for to obtain unbiased species-richness estimates. When richness is assessed at multiple sites, two approaches can be used to estimate species richness: either estimating for each site separately, or pooling all samples. The first approach produces imprecise estimates, while the second loses site-specific information. 2. In contrast, a hierarchical Bayes (HB) multispecies site-occupancy model benefits from the combination of information across sites without losing site-specific information and also yields occupancy estimates for each species. The heart of the model is an estimate of the incompletely observed presence-absence matrix, a centrepiece of biogeography and monitoring studies. We illustrate the model using Swiss breeding bird survey data, and compare its estimates with the widely used jackknife species-richness estimator and raw species counts. 3. Two independent observers each conducted three surveys in 26 1-km(2) quadrats, and detected 27-56 (total 103) species. The average estimated proportion of species detected after three surveys was 0.87 under the HB model. Jackknife estimates were less precise (less repeatable between observers) than raw counts, but HB estimates were as repeatable as raw counts. The combination of information in the HB model thus resulted in species-richness estimates presumably at least as unbiased as previous approaches that correct for detectability, but without costs in precision relative to uncorrected, biased species counts. 4. Total species richness in the entire region sampled was estimated at 113.1 (CI 106-123); species detectability ranged from 0.08 to 0.99, illustrating very heterogeneous species detectability; and species occupancy was 0.06-0.96. Even after six surveys, absolute bias in observed occupancy was estimated at up to 0.40. 5. Synthesis and applications. The HB model for species-richness estimation combines information across sites and enjoys more precise, and presumably less biased, estimates than previous approaches. It also yields estimates of several measures of community size and composition. Covariates for occupancy and detectability can be included. We believe it has considerable potential for monitoring programmes as well as in biogeography and community ecology.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Applied Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","collaboration":"6918_Kery.pdf","usgsCitation":"Kery, M., and Royle, J., 2008, Hierarchical Bayes estimation of species richness and occupancy in spatially replicated surveys: Journal of Applied Ecology, v. 45, no. 2, p. 589-598.","productDescription":"589-598","startPage":"589","endPage":"598","numberOfPages":"10","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":16902,"rank":200,"type":{"id":11,"text":"Document"},"url":"https://www3.interscience.wiley.com/journal/119392093/abstract","linkFileType":{"id":5,"text":"html"}},{"id":201551,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a61e4b07f02db635ad8","contributors":{"authors":[{"text":"Kery, M.","contributorId":46637,"corporation":false,"usgs":true,"family":"Kery","given":"M.","affiliations":[],"preferred":false,"id":342940,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":96221,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","affiliations":[],"preferred":false,"id":342941,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":5224863,"text":"5224863 - 2008 - Hierarchical modeling of cluster size in wildlife surveys","interactions":[],"lastModifiedDate":"2013-03-14T13:13:46","indexId":"5224863","displayToPublicDate":"2010-06-16T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2151,"text":"Journal of Agricultural, Biological, and Environmental Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Hierarchical modeling of cluster size in wildlife surveys","docAbstract":"Clusters or groups of individuals are the fundamental unit of observation in many wildlife sampling problems, including aerial surveys of waterfowl, marine mammals, and ungulates. Explicit accounting of cluster size in models for estimating abundance is necessary because detection of individuals within clusters is not independent and detectability of clusters is likely to increase with cluster size. This induces a cluster size bias in which the average cluster size in the sample is larger than in the population at large. Thus, failure to account for the relationship between delectability and cluster size will tend to yield a positive bias in estimates of abundance or density. I describe a hierarchical modeling framework for accounting for cluster-size bias in animal sampling. The hierarchical model consists of models for the observation process conditional on the cluster size distribution and the cluster size distribution conditional on the total number of clusters. Optionally, a spatial model can be specified that describes variation in the total number of clusters per sample unit. Parameter estimation, model selection, and criticism may be carried out using conventional likelihood-based methods. An extension of the model is described for the situation where measurable covariates at the level of the sample unit are available. Several candidate models within the proposed class are evaluated for aerial survey data on mallard ducks (Anas platyrhynchos).","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Agricultural, Biological, and Environmental Statistics","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","collaboration":"6919_Royle.pdf","usgsCitation":"Royle, J., 2008, Hierarchical modeling of cluster size in wildlife surveys: Journal of Agricultural, Biological, and Environmental Statistics, v. 13, no. 1, p. 23-36.","productDescription":"23-36","startPage":"23","endPage":"36","numberOfPages":"14","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":16903,"rank":200,"type":{"id":11,"text":"Document"},"url":"https://pubs.amstat.org/doi/abs/10.1198/108571108X273188","linkFileType":{"id":5,"text":"html"}},{"id":202266,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a18e4b07f02db60518e","contributors":{"authors":[{"text":"Royle, J. Andrew 0000-0003-3135-2167","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":96221,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","affiliations":[],"preferred":false,"id":342942,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":98197,"text":"sir20095226 - 2008 - Potentiometric Surfaces and Changes in Groundwater Levels in Selected Bedrock Aquifers in the Twin Cities Metropolitan Area, March-August 2008 and 1988-2008","interactions":[],"lastModifiedDate":"2012-03-08T17:16:30","indexId":"sir20095226","displayToPublicDate":"2010-02-13T00:00:00","publicationYear":"2008","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":"2009-5226","title":"Potentiometric Surfaces and Changes in Groundwater Levels in Selected Bedrock Aquifers in the Twin Cities Metropolitan Area, March-August 2008 and 1988-2008","docAbstract":"This report depicts potentiometric surfaces and groundwater- level changes in three aquifers that underlie the seven-county Twin Cities Metropolitan Area. Approximately 350 groundwater levels were measured in wells from the three aquifers-the Prairie du Chien-Jordan, the Franconia-Ironton-Galesville, and the Mount Simon-Hinckley aquifers-in March and August of 2008. The report presents maps, associated data tables, and 22 geographic information system datasets. The maps presented in this report show the potentiometric surfaces in March and August of 2008 for all three aquifers, groundwater-level changes from March to August 2008 for each aquifer, and revised potentiometric-surface contours for the winter of 1988-89 for the Prairie du Chien-Jordan and the Mount Simon-Hinckley aquifers, and the estimated long-term (winter of 1988-89 to March 2008) groundwater-level changes for the Prairie du Chien-Jordan and Mount Simon-Hinckley aquifers. This report documents the methods used to construct the maps and provides a context for the period of the measurements.\r\n\r\nAlthough withdrawal demand is increasing in the Twin Cities Metropolitan area, particularly in the Prairie du Chien-Jordan aquifer, year-to-year changes in withdrawals can be substantial, and the relation between potentiometric surfaces in the major aquifers and year-to-year withdrawals is not well established. The estimated long-term (19-year) groundwater-level changes for the Prairie du Chien-Jordan and Mount Simon-Hinckley aquifers have not been large based on data and maps produced during this study, despite the large seasonal fluctuations shown by the March and August 2008 synoptic measurements.\r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20095226","usgsCitation":"Sanocki, C.A., Langer, S.K., and Menard, J.C., 2008, Potentiometric Surfaces and Changes in Groundwater Levels in Selected Bedrock Aquifers in the Twin Cities Metropolitan Area, March-August 2008 and 1988-2008: U.S. Geological Survey Scientific Investigations Report 2009-5226, Report: iv, 67 p.; Downloads Directory , https://doi.org/10.3133/sir20095226.","productDescription":"Report: iv, 67 p.; Downloads Directory ","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":199351,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":13441,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2009/5226/","linkFileType":{"id":5,"text":"html"}}],"scale":"24000","projection":"Universal Transverse Mercator projection","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -94,44.5 ], [ -94,45.333333333333336 ], [ -92.75,45.333333333333336 ], [ -92.75,44.5 ], [ -94,44.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ac3e4b07f02db678773","contributors":{"authors":[{"text":"Sanocki, Christopher A.","contributorId":100432,"corporation":false,"usgs":true,"family":"Sanocki","given":"Christopher","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":304640,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Langer, Susan K. slanger@usgs.gov","contributorId":107824,"corporation":false,"usgs":true,"family":"Langer","given":"Susan","email":"slanger@usgs.gov","middleInitial":"K.","affiliations":[],"preferred":false,"id":304641,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Menard, Jason C.","contributorId":19661,"corporation":false,"usgs":true,"family":"Menard","given":"Jason","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":304639,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":97773,"text":"ofr20081385 - 2008 - Digital Mapping Techniques '07 - Workshop Proceedings","interactions":[],"lastModifiedDate":"2019-04-01T08:43:21","indexId":"ofr20081385","displayToPublicDate":"2009-08-19T00:00:00","publicationYear":"2008","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":"2008-1385","title":"Digital Mapping Techniques '07 - Workshop Proceedings","docAbstract":"The Digital Mapping Techniques '07 (DMT'07) workshop was attended by 85 technical experts from 49 agencies, universities, and private companies, including representatives from 27 state geological surveys. This year's meeting, the tenth in the annual series, was hosted by the South Carolina Geological Survey, from May 20-23, 2007, on the University of South Carolina campus in Columbia, South Carolina. Each DMT workshop has been coordinated by the U.S. Geological Survey's National Geologic Map Database Project and the Association of American State Geologists (AASG).\r\n\r\nAs in previous year's meetings, the objective was to foster informal discussion and exchange of technical information, principally in order to develop more efficient methods for digital mapping, cartography, GIS analysis, and information management. At this meeting, oral and poster presentations and special discussion sessions emphasized: 1) methods for creating and publishing map products (here, 'publishing' includes Web-based release); 2) field data capture software and techniques, including the use of LIDAR; 3) digital cartographic techniques; 4) migration of digital maps into ArcGIS Geodatabase format; 5) analytical GIS techniques; and 6) continued development of the National Geologic Map Database.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Digital Mapping Techniques '07 - Workshop Proceedings","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Digital Mapping techniques '07 - Workshop Proceedings","conferenceDate":"May 20-23, 2007","conferenceLocation":"Columbia, South Carolina","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20081385","collaboration":"Convened by the Association of American State Geologists and the United States Geological Survey; Hosted by the South Carolina Geological Survey","usgsCitation":"Soller, D.R., 2008, Digital Mapping Techniques '07 - Workshop Proceedings: U.S. Geological Survey Open-File Report 2008-1385, iv, 140 p., https://doi.org/10.3133/ofr20081385.","productDescription":"iv, 140 p.","additionalOnlineFiles":"Y","temporalStart":"2007-05-20","temporalEnd":"2007-05-23","costCenters":[{"id":420,"text":"National Geologic Map Database","active":false,"usgs":true}],"links":[{"id":118545,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2008_1385.jpg"},{"id":362520,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2008/1385/pdf/ofr2008-1385.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":12936,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2008/1385/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b32e4b07f02db6b45ee","contributors":{"authors":[{"text":"Soller, David R. 0000-0001-6177-8332 drsoller@usgs.gov","orcid":"https://orcid.org/0000-0001-6177-8332","contributorId":2700,"corporation":false,"usgs":true,"family":"Soller","given":"David","email":"drsoller@usgs.gov","middleInitial":"R.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":303107,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":5211433,"text":"5211433 - 2008 - Environmental contaminant hazards to wildlife at National Capital region and Mid-Atlantic National Park Service units","interactions":[],"lastModifiedDate":"2012-02-02T00:15:23","indexId":"5211433","displayToPublicDate":"2009-06-09T09:23:20","publicationYear":"2008","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Environmental contaminant hazards to wildlife at National Capital region and Mid-Atlantic National Park Service units","docAbstract":"Pollutant data for air, water, soil and biota were compiled from databases and internet sources and by staff interviews at 23 National Park Service (NPS) units in 2005. A metric was derived describing the quality and quantity of data for each park, and in combination with known contaminant threats, the need for ecotoxicological study was identified and ranked. Over half of NP units were near Toxic Release Inventory sites discharging persistent pollutants, and fish consumption advisories were in effect at or near 22 of the units. Pesticide and herbicide use was found to be minimal, with the exception of those units with agricultural leases. Only 70 reports were found that describe terrestrial vertebrate environmental contaminant data at or near the units. Of the >75,000 compounds in commerce, empirical exposure data were limited to merely 58 halogenated compounds, insecticides, rodenticides, metals, and some contemporary compounds. Further ecotoxicological monitoring and research is warranted at several units including Shenandoah National Park, Richmond National Battlefield Park, Chesapeake & Ohio Canal National Historical Park, Valley Forge National Historical Park, Hopewell Furnace National Historic Site, Monocacy National Battlefield, and Harpers Ferry National Historical Park. The types of investigations vary according to the wildlife species present and potential contaminant threats, but should focus on contemporary use pesticides and herbicides, polychlorinated biphenyls, mercury, lead, and perhaps antibiotics, flame retardants, pharmaceuticals, and surfactants. Other management recommendations include inclusion of screening level contaminant risk assessments into the NPS Vital Signs Program, development of protocols for toxicological analysis of seemingly affected wildlife, alternative methods and compounds for pest management, and use of non-toxic fishing tackle by visitors.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Rethinking Protected Areas in a Changing World: Proceedings of the 2007 George Wright Society Biennial Conference on parks, protected areas & cultural sites, April 16-20, 2007, St. Paul, Minnesota.","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"George Wright Society","publisherLocation":"Hancock, Michigan","collaboration":" PDF on file: 6953_Rattner.pdf","usgsCitation":"Rattner, B., and Ackerson, B., 2008, Environmental contaminant hazards to wildlife at National Capital region and Mid-Atlantic National Park Service units, chap. of Rethinking Protected Areas in a Changing World: Proceedings of the 2007 George Wright Society Biennial Conference on parks, protected areas & cultural sites, April 16-20, 2007, St. Paul, Minnesota., p. 307-311.","startPage":"307","endPage":"311","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":202513,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4aa7e4b07f02db667298","contributors":{"editors":[{"text":"Weber, S.","contributorId":102823,"corporation":false,"usgs":true,"family":"Weber","given":"S.","email":"","affiliations":[],"preferred":false,"id":508118,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Harmon, David","contributorId":111703,"corporation":false,"usgs":true,"family":"Harmon","given":"David","email":"","affiliations":[],"preferred":false,"id":508119,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Rattner, Barnett A. 0000-0003-3676-2843","orcid":"https://orcid.org/0000-0003-3676-2843","contributorId":95843,"corporation":false,"usgs":true,"family":"Rattner","given":"Barnett A.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":331024,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ackerson, B.K.","contributorId":20853,"corporation":false,"usgs":true,"family":"Ackerson","given":"B.K.","email":"","affiliations":[],"preferred":false,"id":331023,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":5211445,"text":"5211445 - 2008 - North American Bird Banding and quantitative population ecology","interactions":[],"lastModifiedDate":"2012-02-02T00:15:28","indexId":"5211445","displayToPublicDate":"2009-06-09T09:23:20","publicationYear":"2008","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"North American Bird Banding and quantitative population ecology","docAbstract":"Early bird-banding programs in North America were developed to provide descriptions of bird migration and movement patterns. This initial interest in description quickly evolved into more quantitative interests in two ways. There was (1) interest in quantifying migration and movement patterns, and (2) rapid recognition that re-observations of marked birds provided information about other parameters relevant to population dynamics. These included survival rate, recruitment rate, and population size. The evolution of methods for estimating population size, survival, recruitment, and movement is reviewed and we show it to be closely tied to bird-banding data. These estimation methods have been used with bird-banding data to draw important inferences about evolutionary ecology, population ecology, and population management. Illustrative examples of such inferences are provided.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Bird Banding in North America: The First Hundred Years","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Nuttall Ornithological Club","publisherLocation":"Cambridge, Massachusetts","collaboration":"ISBN 1-877973-45-9 PDF on file: 7018_Nichols.pdf","usgsCitation":"Nichols, J., and Tautin, J., 2008, North American Bird Banding and quantitative population ecology, chap. of Bird Banding in North America: The First Hundred Years, p. 133-161.","productDescription":"ix, 280","startPage":"133","endPage":"161","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":202834,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4afde4b07f02db696dd7","contributors":{"editors":[{"text":"Davis, William E. Jr.","contributorId":113000,"corporation":false,"usgs":false,"family":"Davis","given":"William","suffix":"Jr.","email":"","middleInitial":"E.","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":508134,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Jackson, Jerome A.","contributorId":112944,"corporation":false,"usgs":true,"family":"Jackson","given":"Jerome","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":508133,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Tautin, John","contributorId":113586,"corporation":false,"usgs":true,"family":"Tautin","given":"John","email":"","affiliations":[],"preferred":false,"id":508135,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Nichols, J.D. 0000-0002-7631-2890","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":14332,"corporation":false,"usgs":true,"family":"Nichols","given":"J.D.","affiliations":[],"preferred":false,"id":331077,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tautin, J.","contributorId":95168,"corporation":false,"usgs":true,"family":"Tautin","given":"J.","affiliations":[],"preferred":false,"id":331078,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":5200344,"text":"5200344 - 2008 - Hierarchical modeling and inference in ecology: The analysis of data from populations, metapopulations and communities","interactions":[],"lastModifiedDate":"2015-12-10T10:46:10","indexId":"5200344","displayToPublicDate":"2009-06-08T16:49:39","publicationYear":"2008","noYear":false,"publicationType":{"id":4,"text":"Book"},"publicationSubtype":{"id":15,"text":"Monograph"},"title":"Hierarchical modeling and inference in ecology: The analysis of data from populations, metapopulations and communities","docAbstract":"A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods. This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures. The authors apply principles of hierarchical modeling to ecological problems, including * occurrence or occupancy models for estimating species distribution * abundance models based on many sampling protocols, including distance sampling * capture-recapture models with individual effects * spatial capture-recapture models based on camera trapping and related methods * population and metapopulation dynamic models * models of biodiversity, community structure and dynamics.
","language":"English","publisher":"Academic Press","publisherLocation":"San Diego, California","doi":"10.1016/B978-0-12-374097-7.50001-5","usgsCitation":"Royle, J., and Dorazio, R.M., 2008, Hierarchical modeling and inference in ecology: The analysis of data from populations, metapopulations and communities, xviii, 444, https://doi.org/10.1016/B978-0-12-374097-7.50001-5.","productDescription":"xviii, 444","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":201286,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a54e4b07f02db62bec0","contributors":{"authors":[{"text":"Royle, J. Andrew aroyle@usgs.gov","contributorId":138860,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":327564,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dorazio, Robert M. 0000-0003-2663-0468 bob_dorazio@usgs.gov","orcid":"https://orcid.org/0000-0003-2663-0468","contributorId":1668,"corporation":false,"usgs":true,"family":"Dorazio","given":"Robert","email":"bob_dorazio@usgs.gov","middleInitial":"M.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":327563,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":97529,"text":"ofr20081152 - 2008 - Fischer-assays of oil-shale drill cores and rotary cuttings from the greater Green River basin, southwestern Wyoming","interactions":[],"lastModifiedDate":"2022-06-28T19:44:44.014256","indexId":"ofr20081152","displayToPublicDate":"2009-05-20T00:00:00","publicationYear":"2008","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":"2008-1152","title":"Fischer-assays of oil-shale drill cores and rotary cuttings from the greater Green River basin, southwestern Wyoming","docAbstract":"Chapter 1 of this CD–ROM is a database of digitized Fischer (shale-oil) assays of cores and cuttings from boreholes drilled in the Eocene Green River oil shale deposits in southwestern Wyoming. Assays of samples from some surface sections are also included. Most of the Fischer assay analyses were made by the former U.S. Bureau of Mines (USBM) at its laboratory in Laramie, Wyoming. Other assays, made by institutional or private laboratories, were donated to the U.S. Geological Survey (USGS) and are included in this database as well as Adobe PDF-scanned images of some of the original laboratory assay reports and lithologic logs prepared by USBM geologists. The size of this database is 75.2 megabytes and includes information on 971 core holes and rotary-drilled boreholes and numerous surface sections. Most of these data were released previously by the USBM and the USGS through the National Technical Information Service but are no longer available from that agency. Fischer assays for boreholes in northeastern Utah and northwestern Colorado have been published by the USGS.
Additional data include geophysical logs, groundwater data, chemical and X-ray diffraction analyses, and other data. These materials are available for inspection in the office of the USGS Central Energy Resources Team in Lakewood, Colorado. The digitized assays were checked with the original laboratory reports, but some errors likely remain. Other information, such as locations and elevations of core holes and oil and gas tests, were not thoroughly checked. However, owing to the current interest in oil-shale development, it was considered in the public interest to make this preliminary database available at this time.
Chapter 2 of this CD–ROM presents oil-yield histograms of samples of cores and cuttings from exploration drill holes in the Eocene Green River Formation in the Great Divide, Green River, and Washakie Basins of southwestern Wyoming. A database was compiled that includes about 47,000 Fischer assays from 186 core holes and 240 rotary drill holes. Most of the oil yield data are from analyses performed by the former U.S. Bureau of Mines oil shale laboratory in Laramie, Wyoming, with some analyses made by private laboratories. Location data for 971 Wyoming oil-shale drill holes are listed in a spreadsheet that is included in the CD–ROM.
These Wyoming Fischer assays and histograms are part of a much larger collection of oil-shale information, including geophysical and lithologic logs, water data, chemical and X-ray diffraction analyses on the Green River oil-shale deposits in Colorado, Utah, and Wyoming held by the U.S. Geological Survey. Because of an increased interest in oil shale, this CD–ROM containing Fischer assay data and oil-yield histograms for the Green River oil-shale deposits in southwestern Wyoming is being released to the public.
Microsoft Excel spreadsheets included with Chapter 2 contain the Fischer assay data from the 426 holes and data on the company name and drill-hole name, and location. Histograms of the oil yields obtained from the Fischer assays are presented in both Grapher and PDF format. Fischer assay text data files are also included in the CD–ROM.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20081152","isbn":"9781411321847","usgsCitation":"U.S. Geological Survey Oil Shale Assessment Team, 2008, Fischer-assays of oil-shale drill cores and rotary cuttings from the greater Green River basin, southwestern Wyoming (Version 1.0): U.S. Geological Survey Open-File Report 2008-1152, Chapter 1: ii, 16 p.; Chapter 2: ii, 10 p.; Downloads Directory, https://doi.org/10.3133/ofr20081152.","productDescription":"Chapter 1: ii, 16 p.; Chapter 2: ii, 10 p.; Downloads Directory","additionalOnlineFiles":"Y","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":121065,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2008_1152.jpg"},{"id":402632,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_93981.htm","linkFileType":{"id":5,"text":"html"}},{"id":14088,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2008/1152/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Wyoming","otherGeospatial":"Green River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.9619140625,\n 40.98819156349393\n ],\n [\n -106.171875,\n 40.98819156349393\n ],\n [\n -106.171875,\n 42.65012181368022\n ],\n [\n -110.9619140625,\n 42.65012181368022\n ],\n [\n -110.9619140625,\n 40.98819156349393\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49fbe4b07f02db5f46b0","contributors":{"authors":[{"text":"U.S. Geological Survey Oil Shale Assessment Team","contributorId":128035,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey Oil Shale Assessment Team","id":535011,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":97542,"text":"ds2184FO - 2008 - Evaluation of Well-Test Results and the Potential for Basin-Center Gas in the Colulmbia Basin, Central Washington","interactions":[],"lastModifiedDate":"2012-02-02T00:14:28","indexId":"ds2184FO","displayToPublicDate":"2009-05-20T00:00:00","publicationYear":"2008","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":"2184","chapter":"F-O","title":"Evaluation of Well-Test Results and the Potential for Basin-Center Gas in the Colulmbia Basin, Central Washington","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ds2184FO","usgsCitation":"Wilson, M., Dyman, T.S., and Condon, S.M., 2008, Evaluation of Well-Test Results and the Potential for Basin-Center Gas in the Colulmbia Basin, Central Washington: U.S. Geological Survey Data Series 2184, 12 p., https://doi.org/10.3133/ds2184FO.","productDescription":"12 p.","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":195120,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a09e4b07f02db5faf8d","contributors":{"authors":[{"text":"Wilson, Matthew","contributorId":27571,"corporation":false,"usgs":true,"family":"Wilson","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":302441,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dyman, Thaddeus S.","contributorId":83971,"corporation":false,"usgs":true,"family":"Dyman","given":"Thaddeus","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":302442,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Condon, Steven M.","contributorId":95464,"corporation":false,"usgs":true,"family":"Condon","given":"Steven","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":302443,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":97431,"text":"ds398 - 2008 - EAARL coastal topography– Northeast barrier islands 2007: Bare earth","interactions":[],"lastModifiedDate":"2022-04-29T21:07:14.055866","indexId":"ds398","displayToPublicDate":"2009-04-11T00:00:00","publicationYear":"2008","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":"398","title":"EAARL coastal topography– Northeast barrier islands 2007: Bare earth","docAbstract":"These remotely sensed, geographically referenced elevation measurements of Lidar-derived bare earth (BE) topography were produced collaboratively by the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA.\r\n\r\nThis project provides highly detailed and accurate datasets of the northeast coastal barrier islands in New York and New Jersey, acquired April 29-30 and May 15-16, 2007. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers and an integrated miniature digital inertial measurement unit, which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. \r\n\r\nElevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is routinely used to create maps that represent submerged or first surface topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds398","usgsCitation":"Nayegandhi, A., Brock, J., Sallenger, A., Wright, C.W., Yates, X., and Bonisteel, J.M., 2008, EAARL coastal topography– Northeast barrier islands 2007: Bare earth: U.S. Geological Survey Data Series 398, HTML Document; 1 DVD-ROM, https://doi.org/10.3133/ds398.","productDescription":"HTML Document; 1 DVD-ROM","onlineOnly":"N","additionalOnlineFiles":"Y","temporalStart":"2007-04-26","temporalEnd":"2007-05-16","costCenters":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"links":[{"id":195467,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":399954,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_86505.htm"},{"id":12568,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/398/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New York","otherGeospatial":"Long Island","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -74.08333333333333,40.25 ], [ -74.08333333333333,41.1175 ], [ -71.75,41.1175 ], [ -71.75,40.25 ], [ -74.08333333333333,40.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a58e4b07f02db62f462","contributors":{"authors":[{"text":"Nayegandhi, Amar","contributorId":37292,"corporation":false,"usgs":true,"family":"Nayegandhi","given":"Amar","affiliations":[],"preferred":false,"id":302100,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brock, John 0000-0002-5289-9332 jbrock@usgs.gov","orcid":"https://orcid.org/0000-0002-5289-9332","contributorId":2261,"corporation":false,"usgs":true,"family":"Brock","given":"John","email":"jbrock@usgs.gov","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":302098,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sallenger, A. 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This project provides highly detailed and accurate datasets of the northeast coastal barrier islands in New York and New Jersey, acquired April 29-30 and May 15-16, 2007. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is routinely used to create maps that represent submerged or first surface topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds397","usgsCitation":"Nayegandhi, A., Brock, J., Sallenger, A., Wright, C.W., Yates, X., and Bonisteel, J.M., 2008, EAARL coastal topography–Northeast Barrier Islands 2007: First surface: U.S. Geological Survey Data Series 397, DVD-ROM, https://doi.org/10.3133/ds397.","productDescription":"DVD-ROM","onlineOnly":"N","additionalOnlineFiles":"Y","temporalStart":"2007-04-29","temporalEnd":"2007-05-16","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":195383,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":388255,"rank":2,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_86504.htm"},{"id":12567,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/397/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New York","otherGeospatial":"Long Island","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -74.08333333333333,40.25 ], [ -74.08333333333333,41.1175 ], [ -71.75,41.1175 ], [ -71.75,40.25 ], [ -74.08333333333333,40.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a58e4b07f02db62f48a","contributors":{"authors":[{"text":"Nayegandhi, Amar","contributorId":37292,"corporation":false,"usgs":true,"family":"Nayegandhi","given":"Amar","affiliations":[],"preferred":false,"id":302094,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brock, John 0000-0002-5289-9332 jbrock@usgs.gov","orcid":"https://orcid.org/0000-0002-5289-9332","contributorId":2261,"corporation":false,"usgs":true,"family":"Brock","given":"John","email":"jbrock@usgs.gov","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":302092,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sallenger, A. H.","contributorId":78290,"corporation":false,"usgs":true,"family":"Sallenger","given":"A. H.","affiliations":[],"preferred":false,"id":302096,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wright, C. Wayne wwright@usgs.gov","contributorId":57422,"corporation":false,"usgs":true,"family":"Wright","given":"C.","email":"wwright@usgs.gov","middleInitial":"Wayne","affiliations":[],"preferred":false,"id":302095,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yates, Xan","contributorId":78291,"corporation":false,"usgs":true,"family":"Yates","given":"Xan","email":"","affiliations":[],"preferred":false,"id":302097,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bonisteel, Jamie M.","contributorId":12005,"corporation":false,"usgs":true,"family":"Bonisteel","given":"Jamie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":302093,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":97377,"text":"sim3060 - 2008 - Field and Laboratory Data From an Earthquake History Study of Scarps in the Hanging Wall of the Tacoma Fault, Mason and Pierce Counties, Washington","interactions":[],"lastModifiedDate":"2012-02-10T00:11:46","indexId":"sim3060","displayToPublicDate":"2009-03-17T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3060","title":"Field and Laboratory Data From an Earthquake History Study of Scarps in the Hanging Wall of the Tacoma Fault, Mason and Pierce Counties, Washington","docAbstract":"As part of the effort to assess seismic hazard in the Puget Sound region, we map fault scarps on Airborne Laser Swath Mapping (ALSM, an application of LiDAR) imagery (with 2.5-m elevation contours on 1:4,000-scale maps) and show field and laboratory data from backhoe trenches across the scarps that are being used to develop a latest Pleistocene and Holocene history of large earthquakes on the Tacoma fault. We supplement previous Tacoma fault paleoseismic studies with data from five trenches on the hanging wall of the fault. In a new trench across the Catfish Lake scarp, broad folding of more tightly folded glacial sediment does not predate 4.3 ka because detrital charcoal of this age was found in stream-channel sand in the trench beneath the crest of the scarp. A post-4.3-ka age for scarp folding is consistent with previously identified uplift across the fault during AD 770-1160. In the trench across the younger of the two Stansberry Lake scarps, six maximum 14C ages on detrital charcoal in pre-faulting B and C soil horizons and three minimum ages on a tree root in post-faulting colluvium, limit a single oblique-slip (right-lateral) surface faulting event to AD 410-990. Stratigraphy and sedimentary structures in the trench across the older scarp at the same site show eroded glacial sediments, probably cut by a meltwater channel, with no evidence of post-glacial deformation. At the northeast end of the Sunset Beach scarps, charcoal ages in two trenches across graben-forming scarps give a close maximum age of 1.3 ka for graben formation. The ages that best limit the time of faulting and folding in each of the trenches are consistent with the time of the large regional earthquake in southern Puget Sound about AD 900-930. ","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sim3060","usgsCitation":"Nelson, A.R., Personius, S.F., Sherrod, B.L., Buck, J., Bradley, L., Henley, G., Liberty, L.M., Kelsey, H.M., Witter, R., Koehler, R., Schermer, E.R., Nemser, E.S., and Cladouhos, T.T., 2008, Field and Laboratory Data From an Earthquake History Study of Scarps in the Hanging Wall of the Tacoma Fault, Mason and Pierce Counties, Washington: U.S. Geological Survey Scientific Investigations Map 3060, 3 Sheets - Sheet 1: 38 x 36 inches; Sheet 2: 66.64 x 36 inches; Sheet 3: 45.9 x 35.76 inches; This publication is available at Maps-on-Demand, https://doi.org/10.3133/sim3060.","productDescription":"3 Sheets - Sheet 1: 38 x 36 inches; Sheet 2: 66.64 x 36 inches; Sheet 3: 45.9 x 35.76 inches; This publication is available at Maps-on-Demand","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":110813,"rank":700,"type":{"id":15,"text":"Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_86611.htm","linkFileType":{"id":5,"text":"html"},"description":"86611"},{"id":195762,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":12602,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3060/","linkFileType":{"id":5,"text":"html"}}],"scale":"4000","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.91666666666667,47.36666666666667 ], [ -122.91666666666667,52.766666666666666 ], [ -122.88333333333334,52.766666666666666 ], [ -122.88333333333334,47.36666666666667 ], [ -122.91666666666667,47.36666666666667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49fce4b07f02db5f5a79","contributors":{"authors":[{"text":"Nelson, Alan R. 0000-0001-7117-7098 anelson@usgs.gov","orcid":"https://orcid.org/0000-0001-7117-7098","contributorId":812,"corporation":false,"usgs":true,"family":"Nelson","given":"Alan","email":"anelson@usgs.gov","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":301901,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Personius, Stephen F. personius@usgs.gov","contributorId":1214,"corporation":false,"usgs":true,"family":"Personius","given":"Stephen","email":"personius@usgs.gov","middleInitial":"F.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":301903,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sherrod, Brian L.","contributorId":16874,"corporation":false,"usgs":true,"family":"Sherrod","given":"Brian","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":301905,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buck, Jason","contributorId":45008,"corporation":false,"usgs":true,"family":"Buck","given":"Jason","affiliations":[],"preferred":false,"id":301907,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bradley, Lee-Ann bradley@usgs.gov","contributorId":1141,"corporation":false,"usgs":true,"family":"Bradley","given":"Lee-Ann","email":"bradley@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":301902,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Henley, Gary II","contributorId":21654,"corporation":false,"usgs":true,"family":"Henley","given":"Gary","suffix":"II","email":"","affiliations":[],"preferred":false,"id":301906,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Liberty, Lee M.","contributorId":89631,"corporation":false,"usgs":true,"family":"Liberty","given":"Lee","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":301912,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kelsey, Harvey M.","contributorId":101713,"corporation":false,"usgs":true,"family":"Kelsey","given":"Harvey","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":301913,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":4528,"corporation":false,"usgs":true,"family":"Witter","given":"Robert C.","email":"rwitter@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":301904,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Koehler, R.D.","contributorId":55925,"corporation":false,"usgs":true,"family":"Koehler","given":"R.D.","email":"","affiliations":[],"preferred":false,"id":301908,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Schermer, Elizabeth R.","contributorId":64344,"corporation":false,"usgs":true,"family":"Schermer","given":"Elizabeth","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":301910,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Nemser, Eliza S.","contributorId":63114,"corporation":false,"usgs":true,"family":"Nemser","given":"Eliza","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":301909,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Cladouhos, Trenton T.","contributorId":66801,"corporation":false,"usgs":true,"family":"Cladouhos","given":"Trenton","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":301911,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":97360,"text":"ds390 - 2008 - EAARL topography - Vicksburg National Military Park 2008: Bare earth","interactions":[],"lastModifiedDate":"2022-08-02T19:23:53.189894","indexId":"ds390","displayToPublicDate":"2009-03-14T00:00:00","publicationYear":"2008","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":"390","title":"EAARL topography - Vicksburg National Military Park 2008: Bare earth","docAbstract":"These remotely sensed, geographically referenced elevation measurements of Lidar-derived bare earth (BE) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the National Park Service (NPS), Gulf Coast Network, Lafayette, LA; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA.\r\n\r\nThis project provides highly detailed and accurate datasets of the Vicksburg National Military Park in Mississippi, acquired on March 6, 2008. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. \r\n\r\nElevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first surface topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds390","usgsCitation":"Nayegandhi, A., Brock, J., Wright, C.W., Segura, M., and Yates, X., 2008, EAARL topography - Vicksburg National Military Park 2008: Bare earth: U.S. Geological Survey Data Series 390, HTML Document: DVD-ROM, https://doi.org/10.3133/ds390.","productDescription":"HTML Document: DVD-ROM","onlineOnly":"N","additionalOnlineFiles":"Y","temporalStart":"2008-01-01","temporalEnd":"2008-12-31","costCenters":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"links":[{"id":195208,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":404700,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_86439.htm","linkFileType":{"id":5,"text":"html"}},{"id":12419,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/390/","linkFileType":{"id":5,"text":"html"}}],"projection":"Universal Transverse Mercator","country":"United States","state":"Mississippi","otherGeospatial":"Vicksburg National Military Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.91014862060547,\n 32.29496874193891\n ],\n [\n -90.81470489501953,\n 32.29496874193891\n ],\n [\n -90.81470489501953,\n 32.38286083092867\n ],\n [\n -90.91014862060547,\n 32.38286083092867\n ],\n [\n -90.91014862060547,\n 32.29496874193891\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a55e4b07f02db62d03e","contributors":{"authors":[{"text":"Nayegandhi, Amar","contributorId":37292,"corporation":false,"usgs":true,"family":"Nayegandhi","given":"Amar","affiliations":[],"preferred":false,"id":301830,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brock, John 0000-0002-5289-9332 jbrock@usgs.gov","orcid":"https://orcid.org/0000-0002-5289-9332","contributorId":2261,"corporation":false,"usgs":true,"family":"Brock","given":"John","email":"jbrock@usgs.gov","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":301829,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wright, C. Wayne wwright@usgs.gov","contributorId":57422,"corporation":false,"usgs":true,"family":"Wright","given":"C.","email":"wwright@usgs.gov","middleInitial":"Wayne","affiliations":[],"preferred":false,"id":301831,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Segura, Martha","contributorId":77939,"corporation":false,"usgs":true,"family":"Segura","given":"Martha","email":"","affiliations":[],"preferred":false,"id":301832,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yates, Xan","contributorId":78291,"corporation":false,"usgs":true,"family":"Yates","given":"Xan","email":"","affiliations":[],"preferred":false,"id":301833,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":97363,"text":"ds395 - 2008 - EAARL submerged topography– U.S. Virgin Islands 2003","interactions":[],"lastModifiedDate":"2021-09-22T20:06:30.087093","indexId":"ds395","displayToPublicDate":"2009-03-14T00:00:00","publicationYear":"2008","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":"395","title":"EAARL submerged topography– U.S. Virgin Islands 2003","docAbstract":"These remotely sensed, geographically referenced elevation measurements of Lidar-derived submerged topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the National Park Service (NPS), South Florida-Caribbean Network, Miami, FL; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA.\r\n\r\nThis project provides highly detailed and accurate bathymetric datasets of a portion of the U.S. Virgin Islands, acquired on April 21, 23, and 30, May 2, and June 14 and 17, 2003. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. \r\n\r\nElevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first surface topography. 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Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is routinely used to create maps that represent submerged or first surface topography. 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One objective of this research is to create techniques to survey areas for the purposes of geomorphic change studies following major storm events. The USGS Coastal and Marine Geology Program's National Assessment of Coastal Change Hazards project is a multi-year undertaking to identify and quantify the vulnerability of U.S. shorelines to coastal change hazards such as effects of severe storms, sea-level rise, and shoreline erosion and retreat. Airborne Lidar surveys conducted during periods of calm weather are compared to surveys collected following extreme storms in order to quantify the resulting coastal change. Other applications of high-resolution topography include habitat mapping, ecological monitoring, volumetric change detection, and event assessment.\r\n\r\nThe purpose of this project is to provide highly detailed and accurate datasets of the northern Gulf of Mexico coastal areas, acquired on September 19, 2004, immediately following Hurricane Ivan. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Airborne Advanced Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532 nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking RGB (red-green-blue) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers and an integrated miniature digital inertial measurement unit which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys.\r\n\r\nElevation measurements were collected over the survey area using the EAARL system on September 19, 2004. The survey resulted in the acquisition of 3.2 gigabytes of data. The data were processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for pre-survey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is routinely used to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of 'last return' elevations.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds384","usgsCitation":"Nayegandhi, A., Brock, J., Sallenger, A., Wright, C.W., Travers, L.J., and Lebonitte, J., 2008, EAARL coastal topography - Northern Gulf of Mexico: U.S. Geological Survey Data Series 384, HTML Document; DVD-ROM, https://doi.org/10.3133/ds384.","productDescription":"HTML Document; DVD-ROM","onlineOnly":"N","additionalOnlineFiles":"Y","temporalStart":"2004-01-01","temporalEnd":"2004-12-31","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":195570,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":12416,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/384/","linkFileType":{"id":5,"text":"html"}},{"id":416630,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_86436.htm","linkFileType":{"id":5,"text":"html"}}],"projection":"Universal Transverse Mercator","country":"United States","state":"Alabama, Florida, Mississippi","otherGeospatial":"northern Gulf of Mexico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.61749999999999,29.3675 ], [ -88.61749999999999,30.6175 ], [ -84.25,30.6175 ], [ -84.25,29.3675 ], [ -88.61749999999999,29.3675 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a58e4b07f02db62f4a5","contributors":{"authors":[{"text":"Nayegandhi, Amar","contributorId":37292,"corporation":false,"usgs":true,"family":"Nayegandhi","given":"Amar","affiliations":[],"preferred":false,"id":301815,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brock, John 0000-0002-5289-9332 jbrock@usgs.gov","orcid":"https://orcid.org/0000-0002-5289-9332","contributorId":2261,"corporation":false,"usgs":true,"family":"Brock","given":"John","email":"jbrock@usgs.gov","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":301812,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sallenger, Abby","contributorId":9363,"corporation":false,"usgs":true,"family":"Sallenger","given":"Abby","email":"","affiliations":[],"preferred":false,"id":301814,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wright, C. 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