Remote sensing imagery can be an invaluable resource to quantify land change in coastal wetlands. Obtaining an accurate measure of land change can, however, be complicated by differences in fluvial and tidal inundation experienced when the imagery is captured. This study classified Landsat imagery from two wetland areas in coastal Louisiana from 1983 to 2010 into categories of land and water. Tide height, river level, and date were used as independent variables in a multiple regression model to predict land area in the Wax Lake Delta (WLD) and compare those estimates with an adjacent marsh area lacking direct fluvial inputs. Coefficients of determination from regressions using both measures of water level along with date as predictor variables of land extent in the WLD, were higher than those obtained using the current methodology which only uses date to predict land change. Land change trend estimates were also improved when the data were divided by time period. Water level corrected land gain in the WLD from 1983 to 2010 was 1 km2 year−1, while rates in the adjacent marsh remained roughly constant. This approach of isolating environmental variability due to changing water levels improves estimates of actual land change in a dynamic system, so that other processes that may control delta development such as hurricanes, floods, and sediment delivery, may be further investigated.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-011-9437-z","issn":"15592723","usgsCitation":"Allen, Y., Couvillion, B., and Barras, J., 2012, Using multitemporal remote sensing imagery and inundation measures to improve land change estimates in coastal wetlands: Estuaries and Coasts, v. 35, no. 1, p. 190-200, https://doi.org/10.1007/s12237-011-9437-z.","productDescription":"11 p.","startPage":"190","endPage":"200","costCenters":[],"links":[{"id":243907,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Lousianna","otherGeospatial":"Atchafalaya Deltas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.6314697265625,\n 29.703560887190708\n ],\n [\n -91.65481567382812,\n 29.543593066460595\n ],\n [\n -91.51199340820312,\n 29.30077105450428\n ],\n [\n -91.30462646484375,\n 29.31154884819602\n ],\n [\n -91.14257812499999,\n 29.433617570990965\n ],\n [\n -91.6314697265625,\n 29.703560887190708\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-09-02","publicationStatus":"PW","scienceBaseUri":"505bc019e4b08c986b329f1d","contributors":{"authors":[{"text":"Allen, Y.C.","contributorId":63761,"corporation":false,"usgs":true,"family":"Allen","given":"Y.C.","email":"","affiliations":[],"preferred":false,"id":451066,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Couvillion, B.R. 0000-0001-5323-1687","orcid":"https://orcid.org/0000-0001-5323-1687","contributorId":26540,"corporation":false,"usgs":true,"family":"Couvillion","given":"B.R.","affiliations":[],"preferred":false,"id":451064,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barras, J.A.","contributorId":44260,"corporation":false,"usgs":true,"family":"Barras","given":"J.A.","email":"","affiliations":[],"preferred":false,"id":451065,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70046366,"text":"70046366 - 2012 - Upper Klamath Basin Landsat Image for November 8, 2004: Path 45 Rows 30 and 31","interactions":[],"lastModifiedDate":"2013-06-10T13:41:00","indexId":"70046366","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"title":"Upper Klamath Basin Landsat Image for November 8, 2004: Path 45 Rows 30 and 31","docAbstract":"This image is a mosaic of Landsat-5 images of the upper Klamath Basin. The original images were obtained from the U.S. Geological Survey Earth Resources Observation and Science Center (EROS). EROS is responsible for archive management and distribution of Landsat data products. The Landsat-5 satellite is part of an ongoing mission to provide quality remote sensing data in support of research and applications activities. The launch of Landsat-5 on March 1, 1984 marks the addition of the fifth satellite to the Landsat series. The Landsat-5 satellite carries the Thematic Mapper (TM) sensor. More information on the Landsat program can be found online at http://landsat.usgs.gov/.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/70046366","usgsCitation":"Snyder, D.T., 2012, Upper Klamath Basin Landsat Image for November 8, 2004: Path 45 Rows 30 and 31, Dataset, https://doi.org/10.3133/70046366.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":273550,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":273549,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/erosl1t_11082004_p45r30_l5_kl_NAD83.xml"}],"country":"United States","state":"Oregon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -123.382600,41.991760 ], [ -123.382600,43.492919 ], [ -120.601579,43.492919 ], [ -120.601579,41.991760 ], [ -123.382600,41.991760 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51b6f56fe4b0097a7158e62b","contributors":{"authors":[{"text":"Snyder, Daniel T. dtsnyder@usgs.gov","contributorId":820,"corporation":false,"usgs":true,"family":"Snyder","given":"Daniel","email":"dtsnyder@usgs.gov","middleInitial":"T.","affiliations":[],"preferred":true,"id":479558,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70193004,"text":"70193004 - 2012 - Design and implementation of the next generation Landsat satellite communications system","interactions":[],"lastModifiedDate":"2017-12-20T10:53:10","indexId":"70193004","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Design and implementation of the next generation Landsat satellite communications system","docAbstract":"The next generation Landsat satellite, Landsat 8 (L8), also known as the Landsat Data Continuity Mission (LDCM), uses a highly spectrally efficient modulation and data formatting approach to provide large amounts of downlink (D/L) bandwidth in a limited X-Band spectrum allocation. In addition to purely data throughput and bandwidth considerations, there were a number of additional constraints based on operational considerations for prevention of interference with the NASA Deep-Space Network (DSN) band just above the L8 D/L band, minimization of jitter contributions to prevent impacts to instrument performance, and the need to provide an interface to the Landsat International Cooperator (IC) community. A series of trade studies were conducted to consider either X- or Ka-Band, modulation type, and antenna coverage type, prior to the release of the request for proposal (RFP) for the spacecraft. Through use of the spectrally efficient rate-7/8 Low-Density Parity-Check error-correction coding and novel filtering, an XBand frequency plan was developed that balances all the constraints and considerations, while providing world-class link performance, fitting 384 Mbits/sec of data into the 375 MHz X-Band allocation with bit-error rates better than 10-12 using an earth-coverage antenna.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings from the International Telemetering Conference ","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"International Foundation for Telemetering","usgsCitation":"Mah, G.R., O’Brien, M., Garon, H., Mott, C., Ames, A., and Dearth, K., 2012, Design and implementation of the next generation Landsat satellite communications system, in Proceedings from the International Telemetering Conference , 14 p.","productDescription":"14 p.","ipdsId":"IP-038940","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":350124,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":347674,"type":{"id":15,"text":"Index Page"},"url":"https://arizona.openrepository.com/arizona/handle/10150/581626"}],"publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a6105a0e4b06e28e9c2557f","contributors":{"authors":[{"text":"Mah, Grant R. 0000-0002-2584-3915 mah@usgs.gov","orcid":"https://orcid.org/0000-0002-2584-3915","contributorId":4087,"corporation":false,"usgs":true,"family":"Mah","given":"Grant","email":"mah@usgs.gov","middleInitial":"R.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":717588,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Brien, Michael mobrien@usgs.gov","contributorId":4333,"corporation":false,"usgs":true,"family":"O’Brien","given":"Michael","email":"mobrien@usgs.gov","affiliations":[],"preferred":true,"id":717589,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Garon, Howard","contributorId":198902,"corporation":false,"usgs":false,"family":"Garon","given":"Howard","email":"","affiliations":[],"preferred":false,"id":717592,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mott, Claire","contributorId":198901,"corporation":false,"usgs":false,"family":"Mott","given":"Claire","email":"","affiliations":[],"preferred":false,"id":717591,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ames, Alan","contributorId":198900,"corporation":false,"usgs":false,"family":"Ames","given":"Alan","email":"","affiliations":[],"preferred":false,"id":717590,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dearth, Ken","contributorId":198903,"corporation":false,"usgs":false,"family":"Dearth","given":"Ken","email":"","affiliations":[],"preferred":false,"id":717593,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70032574,"text":"70032574 - 2012 - Regional scale impacts of Tamarix leaf beetles (Diorhabda carinulata) on the water availability of western U.S. rivers as determined by multi-scale remote sensing methods","interactions":[],"lastModifiedDate":"2017-11-25T14:17:42","indexId":"70032574","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","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":"Regional scale impacts of Tamarix leaf beetles (Diorhabda carinulata) on the water availability of western U.S. rivers as determined by multi-scale remote sensing methods","docAbstract":"Tamarix leaf beetles (Diorhabda carinulata) have been widely released on western U.S. rivers to control introduced shrubs in the genus Tamarix. Part of the motivation to control Tamarix is to salvage water for human use. Information is needed on the impact of beetles on Tamarix seasonal leaf production and subsequent water use overwide areas andmultiple cycles of annual defoliation.Herewe combine ground data with high resolution phenocam imagery and moderate resolution (Landsat) and coarser resolution (MODIS) satellite imagery to test the effects of beetles on Tamarix evapotranspiration (ET) and leaf phenology at sites on six western rivers. Satellite imagery covered the period 2000 to 2010 which encompassed years before and after beetle release at each study site. Phenocam images showed that beetles reduced green leaf cover of individual canopies by about 30% during a 6-8 week period in summer, but plants produced new leaves after beetles became dormant in August, and over three years no net reduction in peak summer leaf production was noted. ETwas estimated by vegetation index methods, and both Landsat and MODIS analyses showed that beetles reduced ET markedly in the first year of defoliation, but ET recovered in subsequent years. Over all six sites, ET decreased by 14% to 15% by Landsat and MODIS estimates, respectively. However, resultswere variable among sites, ranging fromno apparent effect on ET to substantial reduction in ET. Baseline ET rates before defoliation were low, 394 mmyr-1 by Landsat and 314 mm yr-1 by MODIS estimates (20-25% of potential ET), further constraining the amount of water that could be salvaged. Beetle-Tamarix interactions are in their early stage of development on this continent and it is too soon to predict the eventual extent towhich Tamarix populationswill be reduced. The utility of remote sensing methods for monitoring defoliation was constrained by the small area covered by each phenocamimage, the low temporal resolution of Landsat, and the lowspatial resolution ofMODIS imagery. Even combined image sets did not adequately reveal the details of the defoliation process, and remote sensing data should be combined with ground observations to develop operational monitoring protocols.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Remote Sensing of Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.rse.2011.11.011","issn":"00344257","usgsCitation":"Nagler, P.L., Brown, T., Hultine, K.R., van Riper, C., Bean, D., Dennison, P.E., Murray, R.S., and Glenn, E.P., 2012, Regional scale impacts of Tamarix leaf beetles (Diorhabda carinulata) on the water availability of western U.S. rivers as determined by multi-scale remote sensing methods: Remote Sensing of Environment, v. 118, p. 227-240, https://doi.org/10.1016/j.rse.2011.11.011.","productDescription":"14 p.","startPage":"227","endPage":"240","numberOfPages":"14","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":241759,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214071,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2011.11.011"}],"country":"United States","state":"Colorado;Nevada;Utah;Wyoming","otherGeospatial":"Big Horn River;Humbolt River;Lower Delores River;Middle-upper Delores River;Upper Colorado River;Walker River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120.0800,37.0000 ], [ -120.0800,45.0000 ], [ -106.3000,45.0000 ], [ -106.3000,37.0000 ], [ -120.0800,37.0000 ] ] ] } } ] }","volume":"118","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50788eb2e4b0cfc2d59f5b0d","contributors":{"authors":[{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":436882,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Tim","contributorId":17841,"corporation":false,"usgs":true,"family":"Brown","given":"Tim","affiliations":[],"preferred":false,"id":436884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hultine, Kevin R. 0000-0001-9747-6037","orcid":"https://orcid.org/0000-0001-9747-6037","contributorId":23772,"corporation":false,"usgs":true,"family":"Hultine","given":"Kevin","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":436886,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van Riper, Charles III 0000-0003-1084-5843 charles_van_riper@usgs.gov","orcid":"https://orcid.org/0000-0003-1084-5843","contributorId":169488,"corporation":false,"usgs":true,"family":"van Riper","given":"Charles","suffix":"III","email":"charles_van_riper@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":436888,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bean, Daniel W.","contributorId":11016,"corporation":false,"usgs":false,"family":"Bean","given":"Daniel W.","affiliations":[{"id":16124,"text":"Colorado Department of Agriculture, Biological Pest Control","active":true,"usgs":false}],"preferred":false,"id":436883,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dennison, Philip E.","contributorId":105132,"corporation":false,"usgs":true,"family":"Dennison","given":"Philip","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":436889,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Murray, R. Scott","contributorId":64468,"corporation":false,"usgs":true,"family":"Murray","given":"R.","email":"","middleInitial":"Scott","affiliations":[],"preferred":false,"id":436887,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Glenn, Edward P.","contributorId":19289,"corporation":false,"usgs":true,"family":"Glenn","given":"Edward","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":436885,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70036375,"text":"70036375 - 2012 - Sensitivity analysis of the GEMS soil organic carbon model to land cover land use classification uncertainties under different climate scenarios in Senegal","interactions":[],"lastModifiedDate":"2017-04-06T14:20:32","indexId":"70036375","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1011,"text":"Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Sensitivity analysis of the GEMS soil organic carbon model to land cover land use classification uncertainties under different climate scenarios in Senegal","docAbstract":"Spatially explicit land cover land use (LCLU) change information is needed to drive biogeochemical models that simulate soil organic carbon (SOC) dynamics. Such information is increasingly being mapped using remotely sensed satellite data with classification schemes and uncertainties constrained by the sensing system, classification algorithms and land cover schemes. In this study, automated LCLU classification of multi-temporal Landsat satellite data were used to assess the sensitivity of SOC modeled by the Global Ensemble Biogeochemical Modeling System (GEMS). The GEMS was run for an area of 1560 km2 in Senegal under three climate change scenarios with LCLU maps generated using different Landsat classification approaches. This research provides a method to estimate the variability of SOC, specifically the SOC uncertainty due to satellite classification errors, which we show is dependent not only on the LCLU classification errors but also on where the LCLU classes occur relative to the other GEMS model inputs.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/bg-9-631-2012","issn":"18106277","usgsCitation":"Dieye, A., Roy, D.P., Hanan, N., Liu, S., Hansen, M., and Toure, A., 2012, Sensitivity analysis of the GEMS soil organic carbon model to land cover land use classification uncertainties under different climate scenarios in Senegal: Biogeosciences, v. 9, p. 631-648, https://doi.org/10.5194/bg-9-631-2012.","productDescription":"18 p.","startPage":"631","endPage":"648","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":474697,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-9-631-2012","text":"Publisher Index Page"},{"id":246158,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","noUsgsAuthors":false,"publicationDate":"2012-02-03","publicationStatus":"PW","scienceBaseUri":"505b8d24e4b08c986b318292","contributors":{"authors":[{"text":"Dieye, A.M.","contributorId":35988,"corporation":false,"usgs":true,"family":"Dieye","given":"A.M.","email":"","affiliations":[],"preferred":false,"id":455789,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roy, David P.","contributorId":54761,"corporation":false,"usgs":false,"family":"Roy","given":"David","email":"","middleInitial":"P.","affiliations":[{"id":26958,"text":"South Dakota State University, Brookings, SD","active":true,"usgs":false},{"id":33433,"text":"University of Maryland, College Park","active":true,"usgs":false},{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":455790,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hanan, N.P.","contributorId":82123,"corporation":false,"usgs":true,"family":"Hanan","given":"N.P.","affiliations":[],"preferred":false,"id":455791,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Liu, S.","contributorId":93170,"corporation":false,"usgs":true,"family":"Liu","given":"S.","affiliations":[],"preferred":false,"id":455792,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hansen, M.","contributorId":34670,"corporation":false,"usgs":true,"family":"Hansen","given":"M.","affiliations":[],"preferred":false,"id":455788,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Toure, A.","contributorId":98920,"corporation":false,"usgs":true,"family":"Toure","given":"A.","email":"","affiliations":[],"preferred":false,"id":455793,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70004360,"text":"70004360 - 2011 - Landsat Update: Volume 5 Issue 1","interactions":[],"lastModifiedDate":"2017-01-18T13:42:16","indexId":"70004360","displayToPublicDate":"2015-08-09T08:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Landsat Update: Volume 5 Issue 1","language":"English","publisher":"U.S. Geological Survey","usgsCitation":"U.S. Geological Survey, 2011, Landsat Update: Volume 5 Issue 1, v. 5, no. 1, 4 p.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-027769","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":311062,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":311061,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://landsat.usgs.gov/documents/2011_Landsat_Updates.pdf"}],"volume":"5","issue":"1","tableOfContents":"MSS Data Products now created with LPGS processing system
A Landsat Milestone: Four Million Scenes
Too Close for Comfort Meetings and Conferences Tips and Tricks - G-Verify Image
EROS Authors in Recent Publications
Landsat Image of Interest – Gulf of Carpentaria, Queensland, Australia
No abstract available.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/70004399","usgsCitation":"U.S. Geological Survey, 2011, Landsat Update: Volume 5 Issue 2: Landsat Update, v. 5, no. 2, 6 p, https://doi.org/10.3133/70004399.","productDescription":"6 p","startPage":"13","endPage":"18","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-029614","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":310736,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":310735,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://landsat.usgs.gov/documents/2011_Landsat_Updates.pdf"}],"country":"UNITED STATES","volume":"5","issue":"2","tableOfContents":"Call for Pecora 2011 Award Nominations
Landsat 4 Thermal Band Calibration Update
LandsatLook Images
Global Land Survey 2010 Available
Meetings - Landsat Science Team Meeting Held
Upcoming Meetings
Tips and Tricks – Landsat Download Video Demonstration
EROS Authors in Recent Publications
Landsat Image of Interest – Fires in Western Texas
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For the past several years, USGS has taken a multi-faceted approach to investigating the condition and trends in sagebrush steppe ecosystems. This recent effort builds upon decades of work in semi-arid ecosystems providing a specific, applied focus on the cumulative impacts of expanding human activities across these landscapes. Here, we discuss several on-going projects contributing to these efforts: (1) mapping and monitoring the distribution and condition of shrub steppe communities with local detail at a regional scale, (2) assessing the relationships between specific, land-use features (for example, roads, transmission lines, industrial pads) and invasive plants, including their potential (environmentally defined) distribution across the region, and (3) monitoring the effects of habitat treatments on the ecosystem, including wildlife use and invasive plant abundance. This research is focused on the northern sagebrush steppe, primarily in Wyoming, but also extending into Montana, Colorado, Utah and Idaho. The study area includes a range of sagebrush types (including, Artemisia tridentata ssp. tridentata, Artemisia tridentata ssp. wyomingensis, Artemisia tridentata ssp. vaseyana, Artemisia nova) and other semi-arid shrubland types (for example, Sarcobatus vermiculatus, Atriplex confertifolia, Atriplex gardneri), impacted by extensive interface between steppe ecosystems and industrial energy activities resulting in a revealing multiple-variable analysis. We use a combination of remote sensing (AWiFS (1 Any reference to platforms, data sources, equipment, software, patented or trade-marked methods is for information purposes only. It does not represent endorsement of the U.S.D.I., U.S.G.S. or the authors), Landsat and Quickbird platforms), Geographic Information System (GIS) design and data management, and field-based, replicated sampling to generate multiple scales of data representing the distribution of shrub communities for the habitat inventory. Invasive plant sampling focused on the interaction between human infrastructure and weedy plant distributions in southwestern Wyoming, while also capturing spatial variability associated with growing conditions and management across the region. In a separate but linked study, we also sampled native and invasive composition of recent and historic habitat treatments. Here, we summarize findings of this ongoing work, highlighting patterns and relationships between vegetation (native and invasive), land cover, landform, and land-use patterns in the sagebrush steppe.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Natural Resources and Environmental Issues","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Utah State University","publisherLocation":"Logan, UT","usgsCitation":"Manier, D., Aldridge, C.L., Anderson, P., Chong, G., Homer, C.G., O’Donnell, M.S., and Schell, S., 2011, Land use and habitat conditions across the southwestern Wyoming sagebrush steppe: development impacts, management effectiveness and the distribution of invasive plants: Natural Resources and Environmental Issues, v. 117, no. 1, 13 p.; Article 4.","productDescription":"13 p.; Article 4","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":257814,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":257805,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://digitalcommons.usu.edu/nrei/vol17/iss1/4","linkFileType":{"id":5,"text":"html"}}],"country":"United States","otherGeospatial":"Wyoming","volume":"117","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a43b8e4b0c8380cd66573","contributors":{"authors":[{"text":"Manier, Daniel J.","contributorId":77435,"corporation":false,"usgs":true,"family":"Manier","given":"Daniel J.","affiliations":[],"preferred":false,"id":348675,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":348669,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Patrick","contributorId":65347,"corporation":false,"usgs":true,"family":"Anderson","given":"Patrick","affiliations":[],"preferred":false,"id":348673,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chong, Geneva","contributorId":71454,"corporation":false,"usgs":true,"family":"Chong","given":"Geneva","affiliations":[],"preferred":false,"id":348674,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Homer, Collin G. 0000-0003-4755-8135 homer@usgs.gov","orcid":"https://orcid.org/0000-0003-4755-8135","contributorId":2262,"corporation":false,"usgs":true,"family":"Homer","given":"Collin","email":"homer@usgs.gov","middleInitial":"G.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":348670,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O’Donnell, Michael S. 0000-0002-3488-003X odonnellm@usgs.gov","orcid":"https://orcid.org/0000-0002-3488-003X","contributorId":3351,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Michael","email":"odonnellm@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":348671,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schell, Spencer 0000-0001-7732-1863 schells@usgs.gov","orcid":"https://orcid.org/0000-0001-7732-1863","contributorId":3357,"corporation":false,"usgs":true,"family":"Schell","given":"Spencer","email":"schells@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":348672,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70006259,"text":"fs20113153 - 2011 - LandsatLook images","interactions":[],"lastModifiedDate":"2020-01-27T10:00:39","indexId":"fs20113153","displayToPublicDate":"2011-12-16T00:00:00","publicationYear":"2011","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":"2011-3153","title":"LandsatLook images","docAbstract":"LandsatLook images are full resolution JPEG files derived from Landsat Level 1 data products. 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Landsat Thematic Mapper remote sensing data are used to map burn severity for 99 fires (cumulatively over 97 000 ha) that burned in Yosemite over a 20-year period. These maps are used to quantify the frequency distributions of fire severity by fire-regime type. A classification is created for the resultant distributions and they are discussed within the context of four vegetation zones: the foothill shrub and woodland zone; the lower montane forest zone; the upper montane forest zone and the subalpine forest zone. The severity distributions can form a building block from which to discuss current fire regimes across the Sierra Nevada in California. This work establishes a framework for comparing the effects of current fires on our landscapes with our notions of how fires historically burned, and how current fire severity distributions differ from our desired future conditions. As this process is refined, a new set of information will be available to researchers and land managers to help understand how fire regimes have changed from the past and how we might attempt to manage them in the future.
","language":"English","publisher":"CSIRO Publishing","doi":"10.1071/WF09060","usgsCitation":"Thode, A., van Wagtendonk, J., Miller, D.J., and Quinn, J.F., 2011, Quantifying the fire regime distributions for severity in Yosemite National Park, California, USA: International Journal of Wildland Fire, v. 20, no. 2, p. 223-239, https://doi.org/10.1071/WF09060.","productDescription":"17 p.","startPage":"223","endPage":"239","numberOfPages":"17","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":204490,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Yosemite National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.06134033203125,\n 37.477037796698056\n ],\n [\n -119.11102294921875,\n 37.477037796698056\n ],\n [\n -119.11102294921875,\n 38.156156969924915\n ],\n [\n -120.06134033203125,\n 38.156156969924915\n ],\n [\n -120.06134033203125,\n 37.477037796698056\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4adce4b07f02db6862f8","contributors":{"authors":[{"text":"Thode, Andrea E.","contributorId":31896,"corporation":false,"usgs":false,"family":"Thode","given":"Andrea E.","affiliations":[],"preferred":false,"id":349427,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Wagtendonk, Jan W. 0000-0002-0788-2654","orcid":"https://orcid.org/0000-0002-0788-2654","contributorId":98269,"corporation":false,"usgs":true,"family":"van Wagtendonk","given":"Jan W.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":349429,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, D. 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The results also highlight several challenges to implementing this type of approach. The approach described here consistently yields accurate results in locations with persistent winter and spring snow cover where ten or more partially snow covered images are available to populate the image database, but is less successful in areas with shallower or more ephemeral snow covers or when fewer images are available to populate the image database. This work represents a first step towards developing an algorithm to combine Landsat and MODIS data to produce daily 30 m resolution binary SCA images. Further research should focus on testing the accuracy of this approach across a range of landscape types and snow cover regimes, developing methods to improve prediction accuracy when snow cover is nearly complete or nearly absent, and developing methods to compensate for the effects of canopy cover on SCA retrievals.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 79th Annual Western Snow Conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Western Snow Conference","usgsCitation":"Selkowitz, D.J., 2011, Exploring the potential for a fused Landsat-MODIS snow covered area product, in Proceedings of the 79th Annual Western Snow Conference, p. 31-36.","productDescription":"6 p.","startPage":"31","endPage":"36","ipdsId":"IP-033390","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":408742,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":408741,"rank":1,"type":{"id":39,"text":"HTML Document"},"url":"https://westernsnowconference.org/sites/westernsnowconference.org/PDFs/2011Selkowitz.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Selkowitz, David J. 0000-0003-0824-7051 dselkowitz@usgs.gov","orcid":"https://orcid.org/0000-0003-0824-7051","contributorId":3259,"corporation":false,"usgs":true,"family":"Selkowitz","given":"David","email":"dselkowitz@usgs.gov","middleInitial":"J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":855820,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70005584,"text":"gip133 - 2011 - Tracking change over time","interactions":[],"lastModifiedDate":"2017-03-28T11:13:35","indexId":"gip133","displayToPublicDate":"2011-09-29T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"133","title":"Tracking change over time","docAbstract":"Landsat satellites capture images of Earth from space-and have since 1972! These images provide a long-term record of natural and human-induced changes on the global landscape. Comparing images from multiple years reveals slow and subtle changes as well as rapid and devastating ones. Landsat images are available over the Internet at no charge. Using the free software MultiSpec, students can track changes to the landscape over time-just like remote sensing scientists do! The objective of the Tracking Change Over Time lesson plan is to get students excited about studying the changing Earth. Intended for students in grades 5-8, the lesson plan is flexible and may be used as a student self-guided tutorial or as a teacher-led class lesson. Enhance students' learning of geography, map reading, earth science, and problem solving by seeing landscape changes from space.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip133","usgsCitation":"Water Resources Division, U.S. Geological Survey, 2011, Tracking change over time (Originally posted September 28, 2011; Version 2.0: March 10, 2016): U.S. Geological Survey General Information Product 133, Teacher: 20 p.; Student: 4 p.; Remote Sensing Student: 4 p.; Urban Area Change-Phoenix, AZ Teacher: 4 p.; Urban Area Change-Phoenix, AZ Student: 2 p., https://doi.org/10.3133/gip133.","productDescription":"Teacher: 20 p.; Student: 4 p.; Remote Sensing Student: 4 p.; Urban Area Change-Phoenix, AZ Teacher: 4 p.; Urban Area Change-Phoenix, AZ Student: 2 p.","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":116529,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/gip133.PNG"},{"id":94231,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/gip/133/","linkFileType":{"id":5,"text":"html"}}],"edition":"Originally posted September 28, 2011; Version 2.0: March 10, 2016","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4afce4b07f02db696846","contributors":{"authors":[{"text":"Water Resources Division, U.S. Geological Survey","contributorId":128075,"corporation":true,"usgs":false,"organization":"Water Resources Division, U.S. Geological Survey","id":535131,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70005597,"text":"70005597 - 2011 - Landsat 8 on-orbit characterization and calibration system","interactions":[],"lastModifiedDate":"2017-01-18T13:44:16","indexId":"70005597","displayToPublicDate":"2011-09-13T03:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Landsat 8 on-orbit characterization and calibration system","docAbstract":"The Landsat Data Continuity Mission (LDCM) is planning to launch the Landsat 8 satellite in December 2012, which continues an uninterrupted record of consistently calibrated globally acquired multispectral images of the Earth started in 1972. The satellite will carry two imaging sensors: the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). The OLI will provide visible, near-infrared and short-wave infrared data in nine spectral bands while the TIRS will acquire thermal infrared data in two bands. Both sensors have a pushbroom design and consequently, each has a large number of detectors to be characterized. Image and calibration data downlinked from the satellite will be processed by the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center using the Landsat 8 Image Assessment System (IAS), a component of the Ground System. In addition to extracting statistics from all Earth images acquired, the IAS will process and trend results from analysis of special calibration acquisitions, such as solar diffuser, lunar, shutter, night, lamp and blackbody data, and preselected calibration sites. The trended data will be systematically processed and analyzed, and calibration and characterization parameters will be updated using both automatic and customized manual tools. This paper describes the analysis tools and the system developed to monitor and characterize on-orbit performance and calibrate the Landsat 8 sensors and image data products.
","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":"Proceeding of SPIE: Earth Observing Systems XV!","largerWorkSubtype":{"id":19,"text":"Conference Paper"},"conferenceTitle":"Earth Observing Systems XVI","conferenceDate":"August 23-25, 2011","conferenceLocation":"San Diego, CA","language":"English","publisher":"Society of Photo-Optical Instrumentation Engineers","doi":"10.1117/12.896177","usgsCitation":"Micijevic, E., Morfitt, R., and Choate, M., 2011, Landsat 8 on-orbit characterization and calibration system, in Proceeding of SPIE: Earth Observing Systems XV!, v. 8153, San Diego, CA, August 23-25, 2011, https://doi.org/10.1117/12.896177.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-031455","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":307715,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"8153","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"560bb6c2e4b058f706e53d1f","contributors":{"authors":[{"text":"Micijevic, Esad 0000-0002-3828-9239 emicijevic@usgs.gov","orcid":"https://orcid.org/0000-0002-3828-9239","contributorId":3075,"corporation":false,"usgs":true,"family":"Micijevic","given":"Esad","email":"emicijevic@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":570758,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morfitt, Ron 0000-0002-4777-4877 rmorfitt@usgs.gov","orcid":"https://orcid.org/0000-0002-4777-4877","contributorId":4097,"corporation":false,"usgs":true,"family":"Morfitt","given":"Ron","email":"rmorfitt@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":570759,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Choate, Mike 0000-0002-8101-4994 choate@usgs.gov","orcid":"https://orcid.org/0000-0002-8101-4994","contributorId":4618,"corporation":false,"usgs":true,"family":"Choate","given":"Mike","email":"choate@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":570760,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70004836,"text":"70004836 - 2011 - Estimation of late twentieth century land-cover change in California","interactions":[],"lastModifiedDate":"2017-04-06T13:41:53","indexId":"70004836","displayToPublicDate":"2011-08-31T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Estimation of late twentieth century land-cover change in California","docAbstract":"We present the first comprehensive multi-temporal analysis of land-cover change for California across its major ecological regions and primary land-cover types. Recently completed satellite-based estimates of land-cover and land-use change information for large portions of the United States allow for consistent measurement and comparison across heterogeneous landscapes. Landsat data were employed within a pure-panel stratified one-stage cluster sample to estimate and characterize land-cover change for 1973–2000. Results indicate anthropogenic and natural disturbances, such as forest cutting and fire, were the dominant changes, followed by large fluctuations between agriculture and rangelands. Contrary to common perception, agriculture remained relatively stable over the 27-year period with an estimated loss of 1.0% of agricultural land. The largest net declines occurred in the grasslands/shrubs class at 5,131 km2 and forest class at 4,722 km2. Developed lands increased by 37.6%, composing an estimated 4.2% of the state’s land cover by 2000.
","language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s10661-010-1385-8","usgsCitation":"Sleeter, B.M., Wilson, T.S., Soulard, C.E., and Liu, J., 2011, Estimation of late twentieth century land-cover change in California: Environmental Monitoring and Assessment, v. 173, no. 1-4, p. 251-266, https://doi.org/10.1007/s10661-010-1385-8.","productDescription":"16 p.","startPage":"251","endPage":"266","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":204146,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","volume":"173","issue":"1-4","noUsgsAuthors":false,"publicationDate":"2010-03-09","publicationStatus":"PW","scienceBaseUri":"4f4e4a0ae4b07f02db5fb2cb","contributors":{"authors":[{"text":"Sleeter, Benjamin M. 0000-0003-2371-9571 bsleeter@usgs.gov","orcid":"https://orcid.org/0000-0003-2371-9571","contributorId":3479,"corporation":false,"usgs":true,"family":"Sleeter","given":"Benjamin","email":"bsleeter@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":351453,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, Tamara S.","contributorId":36640,"corporation":false,"usgs":true,"family":"Wilson","given":"Tamara","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":351454,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Soulard, Christopher E. 0000-0002-5777-9516 csoulard@usgs.gov","orcid":"https://orcid.org/0000-0002-5777-9516","contributorId":2642,"corporation":false,"usgs":true,"family":"Soulard","given":"Christopher","email":"csoulard@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":351451,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Liu, Jinxun 0000-0003-0561-8988 jxliu@usgs.gov","orcid":"https://orcid.org/0000-0003-0561-8988","contributorId":3414,"corporation":false,"usgs":true,"family":"Liu","given":"Jinxun","email":"jxliu@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":351452,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70156612,"text":"70156612 - 2011 - Bias estimation for the Landsat 8 operational land imager","interactions":[],"lastModifiedDate":"2017-04-25T16:31:36","indexId":"70156612","displayToPublicDate":"2011-08-25T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Bias estimation for the Landsat 8 operational land imager","docAbstract":"The Operational Land Imager (OLI) is a pushbroom sensor that will be a part of the Landsat Data Continuity Mission (LDCM). This instrument is the latest in the line of Landsat imagers, and will continue to expand the archive of calibrated earth imagery. An important step in producing a calibrated image from instrument data is accurately accounting for the bias of the imaging detectors. Bias variability is one factor that contributes to error in bias estimation for OLI. Typically, the bias is simply estimated by averaging dark data on a per-detector basis. However, data acquired during OLI pre-launch testing exhibited bias variation that correlated well with the variation in concurrently collected data from a special set of detectors on the focal plane. These detectors are sensitive to certain electronic effects but not directly to incoming electromagnetic radiation. A method of using data from these special detectors to estimate the bias of the imaging detectors was developed, but found not to be beneficial at typical radiance levels as the detectors respond slightly when the focal plane is illuminated. In addition to bias variability, a systematic bias error is introduced by the truncation performed by the spacecraft of the 14-bit instrument data to 12-bit integers. This systematic error can be estimated and removed on average, but the per pixel quantization error remains. This paper describes the variability of the bias, the effectiveness of a new approach to estimate and compensate for it, as well as the errors due to truncation and how they are reduced.
","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":"Proceedings of SPIE volume 8153","conferenceTitle":"Earth Observing Systems XVI","conferenceDate":"August 23-25, 2011","conferenceLocation":"San Diego, California","language":"English","publisher":"SPIE","doi":"10.1117/12.896221","usgsCitation":"Morfitt, R., and Vanderwerff, K., 2011, Bias estimation for the Landsat 8 operational land imager, in Proceedings of SPIE volume 8153, San Diego, California, August 23-25, 2011, 12 p., https://doi.org/10.1117/12.896221.","productDescription":"12 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-031998","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":307368,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55dd91aee4b0518e354dd12d","contributors":{"authors":[{"text":"Morfitt, Ron 0000-0002-4777-4877 rmorfitt@usgs.gov","orcid":"https://orcid.org/0000-0002-4777-4877","contributorId":4097,"corporation":false,"usgs":true,"family":"Morfitt","given":"Ron","email":"rmorfitt@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":569663,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vanderwerff, Kelly kvanderwerff@usgs.gov","contributorId":4617,"corporation":false,"usgs":true,"family":"Vanderwerff","given":"Kelly","email":"kvanderwerff@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":569664,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70157328,"text":"70157328 - 2011 - Timing constraints on remote sensing of wildland fire burned area in the southeastern US","interactions":[],"lastModifiedDate":"2017-04-25T16:35:32","indexId":"70157328","displayToPublicDate":"2011-08-15T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Timing constraints on remote sensing of wildland fire burned area in the southeastern US","docAbstract":"Remote sensing using Landsat Thematic Mapper (TM) satellite imagery is increasingly used for mapping wildland fire burned area and burn severity, owing to its frequency of collection, relatively high resolution, and availability free of charge. However, rapid response of vegetation following fire and frequent cloud cover pose challenges to this approach in the southeastern US. We assessed these timing constraints by using a series of Landsat TM images to determine how rapidly the remotely sensed burn scar signature fades following prescribed burns in wet flatwoods and depression swamp community types in the Apalachicola National Forest, Florida, USA during 2006. We used both the Normalized Burn Ratio (NBR) of reflectance bands sensitive to vegetation and exposed soil cover, as well as the change in NBR from before to after fire (dNBR), to estimate burned area. We also determined the average and maximum amount of time following fire required to obtain a cloud-free image for burns in each month of the year, as well as the predicted effect of this time lag on percent accuracy of burn scar estimates. Using both NBR and dNBR, the detectable area decreased linearly 9% per month on average over the first four months following fire. Our findings suggest that the NBR and dNBR methods for monitoring burned area in common southeastern US vegetation community types are limited to an average of 78–90% accuracy among months of the year, with individual burns having values as low as 38%, if restricted to use of Landsat 5 TM imagery. However, the majority of burns can still be mapped at accuracies similar to those in other regions of the US, and access to additional sources of satellite imagery would improve overall accuracy.
","language":"English","publisher":"MDPI","doi":"10.3390/rs3081680","usgsCitation":"Picotte, J.J., and Robertson, K., 2011, Timing constraints on remote sensing of wildland fire burned area in the southeastern US: Remote Sensing, v. 3, no. 8, p. 1680-1690, https://doi.org/10.3390/rs3081680.","productDescription":"11 p.","startPage":"1680","endPage":"1690","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-029374","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":474936,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs3081680","text":"Publisher Index Page"},{"id":308290,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","issue":"8","noUsgsAuthors":false,"publicationDate":"2011-08-15","publicationStatus":"PW","scienceBaseUri":"55fd35c1e4b05d6c4e502c85","contributors":{"authors":[{"text":"Picotte, Joshua J. 0000-0002-4021-4623 jpicotte@usgs.gov","orcid":"https://orcid.org/0000-0002-4021-4623","contributorId":4626,"corporation":false,"usgs":true,"family":"Picotte","given":"Joshua","email":"jpicotte@usgs.gov","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":572701,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robertson, Kevin","contributorId":147774,"corporation":false,"usgs":false,"family":"Robertson","given":"Kevin","affiliations":[{"id":16929,"text":"Brown University","active":true,"usgs":false}],"preferred":false,"id":572702,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70208565,"text":"70208565 - 2011 - Testing a high-resolution satellite interpretation technique for crop area monitoring in developing countries","interactions":[],"lastModifiedDate":"2020-02-20T09:58:46","indexId":"70208565","displayToPublicDate":"2011-08-09T10:02:58","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Testing a high-resolution satellite interpretation technique for crop area monitoring in developing countries","docAbstract":"District-level crop area (CA) is a highly uncertain term in food production equations, which are used to allocate food aid and implement appropriate food security initiatives. Remote sensing studies typically overestimate CA and production, as subsistence plots are exaggerated at coarser resolution, which leads to overoptimistic food reports. In this study, medium-resolution (MR) Landsat 7 Enhanced Thematic Mapper Plus (ETM+) images were manually classified for Niger and corrected using CA estimates derived from high-resolution (HR) sample image, topographic and socioeconomic data. A logistic model with smoothing splines was used to compute the block-average (0.1°) probability of an area being cropped. Livelihood zones and elevation explained 75% of the deviance in CA, while MR did not add explanatory power. The model overestimates CA when compared to the national inventory, possibly because of temporal changes in intercropping and the exclusion of some staple crops in the national inventory.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/01431161.2010.532168","usgsCitation":"Marshall, M.T., Husak, G., Michaelsen, J., Funk, C., Pedreros, D., and Adoum, A., 2011, Testing a high-resolution satellite interpretation technique for crop area monitoring in developing countries: International Journal of Remote Sensing, v. 32, no. 23, p. 7997-8012, https://doi.org/10.1080/01431161.2010.532168.","productDescription":"16 p.","startPage":"7997","endPage":"8012","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":372383,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Niger","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 0.0439453125,\n 11.824341483849048\n ],\n [\n 15.380859374999998,\n 11.824341483849048\n ],\n [\n 15.380859374999998,\n 16.088042220148818\n ],\n [\n 0.0439453125,\n 16.088042220148818\n ],\n [\n 0.0439453125,\n 11.824341483849048\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"32","issue":"23","noUsgsAuthors":false,"publicationDate":"2011-08-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Marshall, M. 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The map was created as an environmental input to the Santa Cruz Watershed Ecosystem Portfolio Model (SCWEPM) that is being created by the U.S. Geological Survey for the watershed. The SCWEPM is a map-based multicriteria evaluation tool that allows stakeholders to explore tradeoffs between valued ecosystem services at multiple scales within a participatory decision-making process. Maps related to vegetation type and are needed for use in modeling wildlife habitat and other ecosystem services. Although detailed vegetation maps existed for the U.S. side of the border, there was a lack of consistent data for the Santa Cruz Watershed in Mexico. We produced a binational vegetation classification of the Santa Cruz River riparian habitat and watershed vegetation based on NatureServe Terrestrial Ecological Systems (TES) units using Classification And Regression Tree (CART) modeling. Environmental layers used as predictor data were derived from a seasonal set of Landsat Thematic Mapper (TM) images (spring, summer, and fall) and from a 30-meter digital-elevation-model (DEM) grid. Because both sources of environmental data are seamless across the international border, they are particularly suited to this binational modeling effort. Training data were compiled from existing field data for the riparian corridor and data collected by the NM-GAP (New Mexico Gap Analysis Project) team for the original Southwest Regional Gap Analysis Project (SWReGAP) modeling effort. Additional training data were collected from core areas of the SWReGAP classification itself, allowing the extrapolation of the SWReGAP mapping into the Mexican portion of the watershed without collecting additional training data.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111143","usgsCitation":"Wallace, C., Villarreal, M., and Norman, L.M., 2011, Development of a high-resolution binational vegetation map of the Santa Cruz River riparian corridor and surrounding watershed, southern Arizona and northern Sonora, Mexico: U.S. Geological Survey Open-File Report 2011-1143, iv, 22 p., https://doi.org/10.3133/ofr20111143.","productDescription":"iv, 22 p.","onlineOnly":"Y","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":116184,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1143.gif"},{"id":24440,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1143/","linkFileType":{"id":5,"text":"html"}}],"country":"United States;Mexico","state":"Arizona","otherGeospatial":"Santa Cruz Watershed","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.75,30.75 ], [ -111.75,32.75 ], [ -110,32.75 ], [ -110,30.75 ], [ -111.75,30.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a9ee4b07f02db6605e3","contributors":{"authors":[{"text":"Wallace, Cynthia S.A.","contributorId":70487,"corporation":false,"usgs":true,"family":"Wallace","given":"Cynthia S.A.","affiliations":[],"preferred":false,"id":351724,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Villarreal, Miguel L.","contributorId":107012,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel L.","affiliations":[],"preferred":false,"id":351725,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Norman, Laura M. 0000-0002-3696-8406 lnorman@usgs.gov","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":967,"corporation":false,"usgs":true,"family":"Norman","given":"Laura","email":"lnorman@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":351723,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70208567,"text":"70208567 - 2011 - Treatment of anchor pixels in the METRIC model for improved estimation of sensible and latent heat fluxes","interactions":[],"lastModifiedDate":"2020-02-20T10:00:34","indexId":"70208567","displayToPublicDate":"2011-07-12T10:23:50","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1927,"text":"Hydrological Sciences Journal","active":true,"publicationSubtype":{"id":10}},"title":"Treatment of anchor pixels in the METRIC model for improved estimation of sensible and latent heat fluxes","docAbstract":"Reliable estimation of sensible heat flux (H) is important in energy balance models for quantifying evapotranspiration (ET). This study was conducted to evaluate the value of adding the Priestley-Taylor (PT) equation to the METRIC (Mapping Evapotranspiration at high Resolution with Internalized Calibration) model. METRIC was used to estimate energy fluxes for 10 Landsat images from the 2005, 2006 and 2007 crop growing seasons in south-central Nebraska, USA, where each image owing to recent rainfall exhibited high residual moisture content even at the hot pixel. The METRIC model performed satisfactorily for net radiation (Rn ) and soil heat flux (G) estimation with a root mean square error (RMSE) of 52 and 24 W m-2, respectively. A RMSE of 122 W m-2 for H indicated the limitation of the METRIC model in estimating H for high residual moisture content of the hot pixel (Alfalfa reference ET fraction, ET r F > 0.15). The modified METRIC model (wet METRIC or wMETRIC) incorporating the PT equation was applied to calculate H at the anchor pixels (hot and cold) for high residual moisture content of the hot pixel. The α coefficient of the PT equation was locally calibrated using hourly meteorological data from an automatic weather station and Rn and G data from a Bowen ratio flux tower. The mean α coefficient value was 1.14. The wMETRIC model reduced the RMSE of H from 122 to 64 W m-2 and that of latent heat flux, LE, from 163 to 106 W m-2. The RMSE of daily ET decreased from 1.7 to 1.1 mm d-1 with wMETRIC. The results indicate that treatment of anchor pixels for high residual moisture content with the PT approach gives improved estimation of H, LE and daily ET. It is recommended that the wMETRIC model be used for estimating ET if the hot pixel has high residual moisture (i.e. reference ET fraction > 0.15).
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02626667.2011.587424","usgsCitation":"Singh, R.K., and Irmak, A., 2011, Treatment of anchor pixels in the METRIC model for improved estimation of sensible and latent heat fluxes: Hydrological Sciences Journal, v. 56, no. 5, p. 895-906, https://doi.org/10.1080/02626667.2011.587424.","productDescription":"12 p.","startPage":"895","endPage":"906","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":372386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"South Central Agricultural Laboratory","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.13434600830078,\n 40.53859061142965\n ],\n [\n -98.06156158447266,\n 40.53859061142965\n ],\n [\n -98.06156158447266,\n 40.57563021524945\n ],\n [\n -98.13434600830078,\n 40.57563021524945\n ],\n [\n -98.13434600830078,\n 40.53859061142965\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","issue":"5","noUsgsAuthors":false,"publicationDate":"2011-07-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Singh, Ramesh K. 0000-0002-8164-3483 rsingh@usgs.gov","orcid":"https://orcid.org/0000-0002-8164-3483","contributorId":3895,"corporation":false,"usgs":true,"family":"Singh","given":"Ramesh","email":"rsingh@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":782549,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Irmak, A.","contributorId":101473,"corporation":false,"usgs":true,"family":"Irmak","given":"A.","email":"","affiliations":[],"preferred":false,"id":782550,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70004670,"text":"ofr20111131 - 2011 - A multitemporal (1979-2009) land-use/land-cover dataset of the binational Santa Cruz Watershed","interactions":[],"lastModifiedDate":"2012-02-10T00:11:59","indexId":"ofr20111131","displayToPublicDate":"2011-06-17T16:50:04","publicationYear":"2011","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":"2011-1131","title":"A multitemporal (1979-2009) land-use/land-cover dataset of the binational Santa Cruz Watershed","docAbstract":"Trends derived from multitemporal land-cover data can be used to make informed land management decisions and to help managers model future change scenarios. We developed a multitemporal land-use/land-cover dataset for the binational Santa Cruz watershed of southern Arizona, United States, and northern Sonora, Mexico by creating a series of land-cover maps at decadal intervals (1979, 1989, 1999, and 2009) using Landsat Multispectral Scanner and Thematic Mapper data and a classification and regression tree classifier. The classification model exploited phenological changes of different land-cover spectral signatures through the use of biseasonal imagery collected during the (dry) early summer and (wet) late summer following rains from the North American monsoon. Landsat images were corrected to remove atmospheric influences, and the data were converted from raw digital numbers to surface reflectance values. The 14-class land-cover classification scheme is based on the 2001 National Land Cover Database with a focus on \"Developed\" land-use classes and riverine \"Forest\" and \"Wetlands\" cover classes required for specific watershed models. The classification procedure included the creation of several image-derived and topographic variables, including digital elevation model derivatives, image variance, and multitemporal Kauth-Thomas transformations. The accuracy of the land-cover maps was assessed using a random-stratified sampling design, reference aerial photography, and digital imagery. This showed high accuracy results, with kappa values (the statistical measure of agreement between map and reference data) ranging from 0.80 to 0.85.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111131","usgsCitation":"U.S. Geological Survey, 2011, A multitemporal (1979-2009) land-use/land-cover dataset of the binational Santa Cruz Watershed: U.S. Geological Survey Open-File Report 2011-1131, iv, 25 p.; Appendix; Readme File; Metadata; ZIP Data, https://doi.org/10.3133/ofr20111131.","productDescription":"iv, 25 p.; Appendix; Readme File; Metadata; ZIP Data","startPage":"i","endPage":"26","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":116206,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1131.gif"},{"id":21901,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1131/","linkFileType":{"id":5,"text":"html"}}],"country":"United States;Mexico","state":"Arizona","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.16666666666667,30.216666666666665 ], [ -111.16666666666667,32.166666666666664 ], [ -110,32.166666666666664 ], [ -110,30.216666666666665 ], [ -111.16666666666667,30.216666666666665 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b23e4b07f02db6ade0e"} ,{"id":70004571,"text":"gip127 - 2011 - Ride the Rockies 2011, postcard","interactions":[],"lastModifiedDate":"2012-02-10T00:11:54","indexId":"gip127","displayToPublicDate":"2011-06-06T16:50:03","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"127","title":"Ride the Rockies 2011, postcard","docAbstract":"2011 Ride The Rockies route on shaded-relief mosaic of USGS Landsat 7 satellite images, north-central Colorado.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip127","usgsCitation":"Slate, J.L., 2011, Ride the Rockies 2011, postcard: U.S. Geological Survey General Information Product 127, 2 p., https://doi.org/10.3133/gip127.","productDescription":"2 p.","startPage":"1","endPage":"2","numberOfPages":"2","temporalStart":"2011-01-01","temporalEnd":"2011-12-31","costCenters":[],"links":[{"id":116212,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/gip_127.gif"},{"id":21846,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/gip/127/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Colorado","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109,37 ], [ -109,41 ], [ -102,41 ], [ -102,37 ], [ -109,37 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a14e4b07f02db6024f7","contributors":{"authors":[{"text":"Slate, Janet L. 0000-0002-2870-9068 jslate@usgs.gov","orcid":"https://orcid.org/0000-0002-2870-9068","contributorId":252,"corporation":false,"usgs":true,"family":"Slate","given":"Janet","email":"jslate@usgs.gov","middleInitial":"L.","affiliations":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"preferred":true,"id":350749,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70003699,"text":"70003699 - 2011 - A habitat overlap analysis derived from maxent for tamarisk and the south-western willow flycatcher","interactions":[],"lastModifiedDate":"2021-02-25T17:57:50.319955","indexId":"70003699","displayToPublicDate":"2011-06-01T13:01:04","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1706,"text":"Frontiers of Earth Science","active":true,"publicationSubtype":{"id":10}},"title":"A habitat overlap analysis derived from maxent for tamarisk and the south-western willow flycatcher","docAbstract":"Biologic control of the introduced and invasive, woody plant tamarisk (Tamarix spp, saltcedar) in south-western states is controversial because it affects habitat of the federally endangered South-western Willow Flycatcher (Empidonax traillii extimus). These songbirds sometimes nest in tamarisk where floodplain-level invasion replaces native habitats. Biologic control, with the saltcedar leaf beetle (Diorhabda elongate), began along the Virgin River, Utah, in 2006, enhancing the need for comprehensive understanding of the tamarisk-flycatcher relationship. We used maximum entropy (Maxent) modeling to separately quantify the current extent of dense tamarisk habitat (>50% cover) and the potential extent of habitat available for E. traillii extimus within the studied watersheds. We used transformations of 2008 Landsat Thematic Mapper images and a digital elevation model as environmental input variables. Maxent models performed well for the flycatcher and tamarisk with Area Under the ROC Curve (AUC) values of 0.960 and 0.982, respectively. Classification of thresholds and comparison of the two Maxent outputs indicated moderate spatial overlap between predicted suitable habitat for E. traillii extimus and predicted locations with dense tamarisk stands, where flycatcher habitat will potentially change flycatcher habitats. Dense tamarisk habitat comprised 500 km2 within the study area, of which 11.4% was also modeled as potential habitat for E. traillii extimus. Potential habitat modeled for the flycatcher constituted 190 km2, of which 30.7% also contained dense tamarisk habitat. Results showed that both native vegetation and dense tamarisk habitats exist in the study area and that most tamarisk infestations do not contain characteristics that satisfy the habitat requirements of E. traillii extimus. Based on this study, effective biologic control of Tamarix spp. may, in the short term, reduce suitable habitat available to E. traillii extimus, but also has the potential in the long term to increase suitable habitat if appropriate mixes of native woody vegetation replace tamarisk in biocontrol areas.
","language":"English","publisher":"Springer","doi":"10.1007/s11707-011-0154-5","usgsCitation":"York, P., Evangelista, P., Kumar, S., Graham, J., Flather, C., and Stohlgren, T., 2011, A habitat overlap analysis derived from maxent for tamarisk and the south-western willow flycatcher: Frontiers of Earth Science, v. 5, no. 2, p. 120-129, https://doi.org/10.1007/s11707-011-0154-5.","productDescription":"10 p.","startPage":"120","endPage":"129","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":203829,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"2","noUsgsAuthors":false,"publicationDate":"2011-03-24","publicationStatus":"PW","scienceBaseUri":"4f4e4b24e4b07f02db6ae4e4","contributors":{"authors":[{"text":"York, Patricia","contributorId":79767,"corporation":false,"usgs":true,"family":"York","given":"Patricia","email":"","affiliations":[],"preferred":false,"id":348402,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evangelista, Paul","contributorId":46371,"corporation":false,"usgs":true,"family":"Evangelista","given":"Paul","affiliations":[],"preferred":false,"id":348401,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kumar, Sunil","contributorId":84992,"corporation":false,"usgs":true,"family":"Kumar","given":"Sunil","affiliations":[],"preferred":false,"id":348404,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graham, James","contributorId":83398,"corporation":false,"usgs":true,"family":"Graham","given":"James","affiliations":[],"preferred":false,"id":348403,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Flather, Curtis","contributorId":104779,"corporation":false,"usgs":true,"family":"Flather","given":"Curtis","affiliations":[],"preferred":false,"id":348405,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stohlgren, Thomas","contributorId":22206,"corporation":false,"usgs":true,"family":"Stohlgren","given":"Thomas","affiliations":[],"preferred":false,"id":348400,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}