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We refute this hypothesis by showing that (1) due to its limited area, the Laguna Salada could have evaporated less than 10% of the flood flows that have occurred since 1989; (2) low flow volumes preferentially flow to the Gulf rather than Laguna Salada; (3) All’s method for detecting water surface area in the Laguna Salada appears to be flawed because Landsat Thematic Mapper images of the lakebed show it to be dry when All’s analyses said it was flooded; (4) direct measurements of salinity at the mouth of the river and in the Upper Gulf of California during flood flows in 1993 and 1998 confirm that flood waters reach the sea; and (5) stable oxygen isotope signatures in clam shells and fish otoliths recorded the dilution of seawater with fresh water during the 1993 and 1998 flows. Furthermore, All’s conclusion that freshwater flows do not benefit the ecology of the marine zone is incorrect because the peer-reviewed literature shows that postlarval larval shrimp populations increase during floods, and the subsequent year’s shrimp harvest increases. Furthermore, freshwater flows increase the nursery area for Gulf corvina (</span><i>Cynoscion othonopterus</i><span>), an important commercial fish that requires estuarine habitats with salinities in the range of 26–38‰ during its natal stages. Although flood flows are now much diminished compared to the pre-dam era, they are still important to the remnant wetland and riparian habitats of the Colorado River delta and to organisms in the intertidal and marine zone. Only a small fraction of the flood flows are evaporated in Laguna Salada.</span></p>","language":"English","publisher":"Springer","doi":"https://doi.org/10.1007/s00267-006-0070-8","usgsCitation":"Glenn, E., Flessa, K.W., Cohen, M., Nagler, P.L., Rowell, K., and Zamora-Arroyo, F., 2007, Just Add Water and the Colorado River Still Reaches the Sea: Environmental Management, v. 40, p. 1-6, https://doi.org/https://doi.org/10.1007/s00267-006-0070-8.","productDescription":"6 p.","startPage":"1","endPage":"6","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":497776,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","otherGeospatial":"Colorado River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -114.11365952795234,\n              33.03715093217198\n            ],\n            [\n              -115.4481499779273,\n              33.03715093217198\n            ],\n            [\n              -115.4481499779273,\n              31.27719649797926\n            ],\n            [\n              -114.11365952795234,\n              31.27719649797926\n            ],\n            [\n              -114.11365952795234,\n              33.03715093217198\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"40","noUsgsAuthors":false,"publicationDate":"2007-05-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Glenn, Edward P.","contributorId":56542,"corporation":false,"usgs":false,"family":"Glenn","given":"Edward P.","affiliations":[{"id":13060,"text":"Department of Soil, Water and Environmental Science, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":952732,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flessa, Karl W.","contributorId":175308,"corporation":false,"usgs":false,"family":"Flessa","given":"Karl","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":952733,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cohen, Michael","contributorId":178320,"corporation":false,"usgs":false,"family":"Cohen","given":"Michael","email":"","affiliations":[],"preferred":false,"id":952734,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":952735,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rowell, Kirsten","contributorId":364480,"corporation":false,"usgs":false,"family":"Rowell","given":"Kirsten","affiliations":[],"preferred":false,"id":952736,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zamora-Arroyo, Francisco","contributorId":75834,"corporation":false,"usgs":true,"family":"Zamora-Arroyo","given":"Francisco","email":"","affiliations":[],"preferred":false,"id":952737,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70156750,"text":"70156750 - 2007 - Scan line correction : enabling broader use of Landsat Enhanced Thematic Mapper Plus (ETM+) data","interactions":[],"lastModifiedDate":"2015-08-27T11:51:13","indexId":"70156750","displayToPublicDate":"2007-05-01T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1420,"text":"Earth Imaging Journal","active":true,"publicationSubtype":{"id":10}},"title":"Scan line correction : enabling broader use of Landsat Enhanced Thematic Mapper Plus (ETM+) data","docAbstract":"<p>No abstract available.</p>","language":"English","publisher":"V1 Media","usgsCitation":"Kurtz, R., 2007, Scan line correction : enabling broader use of Landsat Enhanced Thematic Mapper Plus (ETM+) data: Earth Imaging Journal, v. 4, no. 5, p. 32-36.","productDescription":"5 p.","startPage":"32","endPage":"36","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":307620,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55e034c2e4b0f42e3d040e42","contributors":{"authors":[{"text":"Kurtz, R.M.","contributorId":51958,"corporation":false,"usgs":true,"family":"Kurtz","given":"R.M.","email":"","affiliations":[],"preferred":false,"id":570364,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":79835,"text":"sim2948 - 2007 - Color shaded-relief and surface-classification maps of the Fish Creek Area, Harrison Bay Quadrangle, Northern Alaska","interactions":[],"lastModifiedDate":"2018-11-05T11:17:29","indexId":"sim2948","displayToPublicDate":"2007-04-24T00:00:00","publicationYear":"2007","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":"2948","title":"Color shaded-relief and surface-classification maps of the Fish Creek Area, Harrison Bay Quadrangle, Northern Alaska","docAbstract":"<p>The northeastern part of the National Petroleum Reserve in Alaska (NPRA) has become an area of active petroleum exploration during the past five years. Recent leasing and exploration drilling in the NPRA requires the U.S. Bureau of Land Management (BLM) to manage and monitor a variety of surface activities that include seismic surveying, exploration drilling, oil-field development drilling, construction of oil-production facilities, and construction of pipelines and access roads. BLM evaluates a variety of permit applications, environmental impact studies, and other documents that require rapid compilation and analysis of data pertaining to surface and subsurface geology, hydrology, and biology. In addition, BLM must monitor these activities and assess their impacts on the natural environment. Timely and accurate completion of these land-management tasks requires elevation, hydrologic, geologic, petroleum-activity, and cadastral data, all integrated in digital formats at a higher resolution than is currently available in nondigital (paper) formats.</p><p>To support these land-management tasks, a series of maps was generated from remotely sensed data in an area of high petroleum-industry activity (fig. 1). The maps cover an area from approximately latitude 70°00' N. to 70°30' N. and from longitude 151°00' W. to 153°10' W. The area includes the Alpine oil field in the east, the Husky Inigok exploration well (site of a landing strip) in the west, many of the exploration wells drilled in NPRA since 2000, and the route of a proposed pipeline to carry oil from discovery wells in NPRA to the Alpine oil field. This map area is referred to as the \"Fish Creek area\" after a creek that flows through the region.</p><p>The map series includes (1) a color shaded-relief map based on 5-m-resolution data (sheet 1), (2) a surface-classification map based on 30-m-resolution data (sheet 2), and (3) a 5-m-resolution shaded relief-surface classification map that combines the shaded-relief and surface-classification data (sheet 3). Remote sensing datasets that were used to compile the maps include Landsat 7 Enhanced Thematic Mapper+ (ETM+), and interferometric synthetic aperture radar (IFSAR) data. In addition, a 1:250,000-scale geologic map of the Harrison Bay quadrangle, Alaska (Carter and Galloway, 1985, 2005) was used in conjunction with ETM+ and IFSAR data.</p>","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sim2948","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Mars, J.L., Garrity, C.P., Houseknecht, D.W., Amoroso, L., and Meares, D.C., 2007, Color shaded-relief and surface-classification maps of the Fish Creek Area, Harrison Bay Quadrangle, Northern Alaska: U.S. Geological Survey Scientific Investigations Map 2948, Explanatory Text (iv, 15 p.); Maps: 3 Sheets (each 58 x 41 inches), https://doi.org/10.3133/sim2948.","productDescription":"Explanatory Text (iv, 15 p.); Maps: 3 Sheets (each 58 x 41 inches)","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":192849,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":9529,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/2007/2948/","linkFileType":{"id":5,"text":"html"}},{"id":110726,"rank":700,"type":{"id":15,"text":"Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_81198.htm","linkFileType":{"id":5,"text":"html"},"description":"81198"}],"scale":"63360","country":"United States","state":"Alaska","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b24e4b07f02db6ae97b","contributors":{"authors":[{"text":"Mars, John L. jmars@usgs.gov","contributorId":3428,"corporation":false,"usgs":true,"family":"Mars","given":"John","email":"jmars@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":false,"id":290961,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garrity, Christopher P. 0000-0002-5565-1818 cgarrity@usgs.gov","orcid":"https://orcid.org/0000-0002-5565-1818","contributorId":644,"corporation":false,"usgs":true,"family":"Garrity","given":"Christopher","email":"cgarrity@usgs.gov","middleInitial":"P.","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":290958,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Houseknecht, David W. 0000-0002-9633-6910 dhouse@usgs.gov","orcid":"https://orcid.org/0000-0002-9633-6910","contributorId":645,"corporation":false,"usgs":true,"family":"Houseknecht","given":"David","email":"dhouse@usgs.gov","middleInitial":"W.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":290959,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Amoroso, Lee lamoroso@usgs.gov","contributorId":3069,"corporation":false,"usgs":true,"family":"Amoroso","given":"Lee","email":"lamoroso@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":290960,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Meares, Donald C.","contributorId":94753,"corporation":false,"usgs":true,"family":"Meares","given":"Donald","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":290962,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":79829,"text":"fs20073016 - 2007 - Landsat Image Mosaic of Antarctica","interactions":[],"lastModifiedDate":"2012-02-02T00:14:12","indexId":"fs20073016","displayToPublicDate":"2007-04-20T00:00:00","publicationYear":"2007","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":"2007-3016","title":"Landsat Image Mosaic of Antarctica","docAbstract":"Description\r\n\r\nFact sheet introduces the Landsat Image Mosaic of Antarctica (LIMA) with images from a section of the mosaic over McMurdo Station, descriptions of the four versions of LIMA, where to access and download LIMA, and a brief explanation of the Antarctic Web portal.","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/fs20073016","collaboration":"Prepared in cooperation with the National Science Foundation (NSF)","usgsCitation":"Water Resources Division, U.S. Geological Survey, 2007, Landsat Image Mosaic of Antarctica: U.S. Geological Survey Fact Sheet 2007-3016, 2 p., https://doi.org/10.3133/fs20073016.","productDescription":"2 p.","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":121005,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2007/3016/report-thumb.jpg"},{"id":91218,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2007/3016/report.pdf","linkFileType":{"id":1,"text":"pdf"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b20e4b07f02db6abf03","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":534859,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":79648,"text":"sir20075011 - 2007 - Land-Cover Trends of the Sierra Nevada Ecoregion, 1973-2000","interactions":[],"lastModifiedDate":"2012-02-10T00:11:44","indexId":"sir20075011","displayToPublicDate":"2007-02-24T00:00:00","publicationYear":"2007","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":"2007-5011","title":"Land-Cover Trends of the Sierra Nevada Ecoregion, 1973-2000","docAbstract":"The U.S. Geological Survey has developed and is implementing the Land Cover Trends project to estimate and describe the temporal and spatial distribution and variability of contemporary land-use and land-cover change in the United States. As part of the Land Cover Trends project, the purpose of this study was to assess land-use/land-cover change in the Sierra Nevada ecoregion for the period 1973 to 2000 using a probability sampling technique and satellite imagery. We randomly selected 36 100-km2 sample blocks to derive thematic images of land-use/land-cover for five dates of Landsat imagery (1973, 1980, 1986, 1992, 2000). We visually interpreted as many as 11 land-use/land-cover classes using a 60-meter minimum mapping unit from the five dates of imagery yielding four periods for analysis. Change-detection results from post-classification comparison of our mapped data showed that landscape disturbance from fire was the dominant change from 1973-2000. The second most-common change was forest disturbance resulting from harvest of timber resources by way of clear-cutting. The rates of forest regeneration from temporary fire and harvest disturbances coincided with the rates of disturbance from the previous period. Relatively minor landscape changes were caused by new development and reservoir drawdown. Multiple linear regression analysis suggests that land ownership and the proportion of forest and developed cover types were significant determinants of the likelihood of direct human-induced change occurring in sampling units. Driving forces of change include land ownership, land management such as fire suppression policy, and demand for natural resources. \r\n\r\n","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/sir20075011","usgsCitation":"Raumann, C.G., and Soulard, C.E., 2007, Land-Cover Trends of the Sierra Nevada Ecoregion, 1973-2000: U.S. Geological Survey Scientific Investigations Report 2007-5011, v, 29 p., https://doi.org/10.3133/sir20075011.","productDescription":"v, 29 p.","numberOfPages":"34","temporalStart":"1973-01-01","temporalEnd":"2000-12-31","costCenters":[{"id":293,"text":"Geographic Analysis and Monitoring Program","active":false,"usgs":true},{"id":296,"text":"Geography Program","active":false,"usgs":true}],"links":[{"id":194446,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":9286,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2007/5011/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122,34.5 ], [ -122,40.5 ], [ -117.5,40.5 ], [ -117.5,34.5 ], [ -122,34.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b23e4b07f02db6adf5f","contributors":{"authors":[{"text":"Raumann, Christian G.","contributorId":65893,"corporation":false,"usgs":true,"family":"Raumann","given":"Christian","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":290474,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":290473,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":79638,"text":"ofr20071006 - 2007 - Mapping Phyllic and Argillic-Altered Rocks in Southeastern Afghanistan using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Data","interactions":[],"lastModifiedDate":"2018-11-05T11:16:10","indexId":"ofr20071006","displayToPublicDate":"2007-02-22T00:00:00","publicationYear":"2007","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":"2007-1006","title":"Mapping Phyllic and Argillic-Altered Rocks in Southeastern Afghanistan using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Data","docAbstract":"Introduction: ASTER data and logical operators were successfully used to map phyllic and argillic-altered rocks in the southeastern part of Afghanistan. Hyperion data were used to correct ASTER band 5 and ASTER data were georegistered to orthorectified Landsat TM data. Logical operator algorithms produced argillic and phyllic byte ASTER images that were converted to vector data and overlain on ASTER and Landsat TM images.\r\n\r\nAlteration and fault patterns indicated that two areas, the Argandab igneous complex, and the Katawaz basin may contain potential polymetallic vein and porphyry copper deposits. ASTER alteration mapping in the Chagai Hills indicates less extensive phyllic and argillic-altered rocks than mapped in the Argandab igneous complex and the Katawaz basin and patterns of alteration are inconclusive to predict potential deposit types.\r\n","language":"ENGLISH","doi":"10.3133/ofr20071006","collaboration":"Prepared in Cooperation with the United States Agency for International Development; USGS Afghanistan Project Product No. 110","usgsCitation":"Mars, J.L., and Rowan, L.C., 2007, Mapping Phyllic and Argillic-Altered Rocks in Southeastern Afghanistan using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Data: U.S. Geological Survey Open-File Report 2007-1006, map, 36 by 72 inches, https://doi.org/10.3133/ofr20071006.","productDescription":"map, 36 by 72 inches","onlineOnly":"Y","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":194650,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":9270,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2007/1006/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b0be4b07f02db69df61","contributors":{"authors":[{"text":"Mars, John L. jmars@usgs.gov","contributorId":3428,"corporation":false,"usgs":true,"family":"Mars","given":"John","email":"jmars@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":false,"id":290449,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rowan, Lawrence C.","contributorId":58629,"corporation":false,"usgs":true,"family":"Rowan","given":"Lawrence","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":290450,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":79618,"text":"ofr20071029 - 2007 - Landsat ETM+ False-Color Image Mosaics of Afghanistan","interactions":[],"lastModifiedDate":"2012-02-02T00:14:19","indexId":"ofr20071029","displayToPublicDate":"2007-02-08T00:00:00","publicationYear":"2007","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":"2007-1029","title":"Landsat ETM+ False-Color Image Mosaics of Afghanistan","docAbstract":"In 2005, the U.S. Agency for International Development and the U.S. Trade and Development Agency contracted with the U.S. Geological Survey to perform assessments of the natural resources within Afghanistan. The assessments concentrate on the resources that are related to the economic development of that country. Therefore, assessments were initiated in oil and gas, coal, mineral resources, water resources, and earthquake hazards. All of these assessments require geologic, structural, and topographic information throughout the country at a finer scale and better accuracy than that provided by the existing maps, which were published in the 1970's by the Russians and Germans. The very rugged terrain in Afghanistan, the large scale of these assessments, and the terrorist threat in Afghanistan indicated that the best approach to provide the preliminary assessments was to use remotely sensed, satellite image data, although this may also apply to subsequent phases of the assessments. Therefore, the first step in the assessment process was to produce satellite image mosaics of Afghanistan that would be useful for these assessments. This report discusses the production of the Landsat false-color image database produced for these assessments, which was produced from the calibrated Landsat ETM+ image mosaics described by Davis (2006).","language":"ENGLISH","doi":"10.3133/ofr20071029","usgsCitation":"Davis, P.A., 2007, Landsat ETM+ False-Color Image Mosaics of Afghanistan (Version 1.0): U.S. Geological Survey Open-File Report 2007-1029, 22 p., https://doi.org/10.3133/ofr20071029.","productDescription":"22 p.","numberOfPages":"22","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":194640,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":9243,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2007/1029/","linkFileType":{"id":5,"text":"html"}}],"edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b23e4b07f02db6adee4","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":290390,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70033016,"text":"70033016 - 2007 - Shorebird abundance and distribution on the coastal plain of the Arctic National Wildlife Refuge","interactions":[],"lastModifiedDate":"2017-11-15T10:08:19","indexId":"70033016","displayToPublicDate":"2007-01-01T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1318,"text":"Condor","active":true,"publicationSubtype":{"id":10}},"title":"Shorebird abundance and distribution on the coastal plain of the Arctic National Wildlife Refuge","docAbstract":"The coastal plain of the Arctic National Wildlife Refuge hosts seven species of migratory shorebirds listed as highly imperiled or high priority by the U.S. Shorebird Conservation Plan and five species listed as Birds of Conservation Concern by the U.S. Fish and Wildlife Service. During the first comprehensive shorebird survey of the 674 000 ha \"1002 Area\" on the coastal plain, we recorded 14 species of breeding shorebirds at 197 rapidly surveyed plots during June 2002 and 2004. We also estimated detection ratios with a double counting technique, using data collected at 37 intensively studied plots located on the North Slope of Alaska and northern Canada. We stratified the study area by major habitat types, including wetlands, moist areas, uplands, and riparian areas, using previously classified Landsat imagery. We developed population estimates with confidence limits by species, and estimated the total number of shorebirds in the study area to be 230 000 (95% CI: 104 000-363 000), which exceeds the biological criterion for classification as both a Western Hemisphere Shorebird Reserve Network Site of International Importance (100 000 birds) and a Ramsar Wetland of International Importance (20 000 birds), even when conservatively estimated. Species richness and the density of many species were highest in wetland or riparian habitats, which are clustered along the coast. ?? The Cooper Ornithological Society 2007.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Condor","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1650/0010-5422(2007)109[1:SAADOT]2.0.CO;2","issn":"00105422","usgsCitation":"Brown, S., Bart, J., Lanctot, R., Johnson, J.A., Kendall, S., Payer, D., and Johnson, J., 2007, Shorebird abundance and distribution on the coastal plain of the Arctic National Wildlife Refuge: Condor, v. 109, no. 1, p. 1-14, https://doi.org/10.1650/0010-5422(2007)109[1:SAADOT]2.0.CO;2.","startPage":"1","endPage":"14","numberOfPages":"14","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":477020,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1650/0010-5422(2007)109[1:saadot]2.0.co;2","text":"Publisher Index Page"},{"id":240745,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213149,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1650/0010-5422(2007)109[1:SAADOT]2.0.CO;2"}],"volume":"109","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b8e84e4b08c986b3189b6","contributors":{"authors":[{"text":"Brown, S.","contributorId":80620,"corporation":false,"usgs":true,"family":"Brown","given":"S.","affiliations":[],"preferred":false,"id":438989,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bart, J.","contributorId":76272,"corporation":false,"usgs":true,"family":"Bart","given":"J.","affiliations":[],"preferred":false,"id":438987,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lanctot, Richard B.","contributorId":77879,"corporation":false,"usgs":false,"family":"Lanctot","given":"Richard B.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":438988,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, J. A.","contributorId":88375,"corporation":false,"usgs":true,"family":"Johnson","given":"J.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":438990,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kendall, S.","contributorId":48393,"corporation":false,"usgs":true,"family":"Kendall","given":"S.","affiliations":[],"preferred":false,"id":438986,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Payer, D.","contributorId":13443,"corporation":false,"usgs":true,"family":"Payer","given":"D.","affiliations":[],"preferred":false,"id":438984,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Johnson, J.","contributorId":31719,"corporation":false,"usgs":true,"family":"Johnson","given":"J.","email":"","affiliations":[],"preferred":false,"id":438985,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70156000,"text":"70156000 - 2007 - A project for monitoring trends in burn severity","interactions":[],"lastModifiedDate":"2017-04-14T13:22:30","indexId":"70156000","displayToPublicDate":"2007-01-01T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1636,"text":"Fire Ecology","active":true,"publicationSubtype":{"id":10}},"title":"A project for monitoring trends in burn severity","docAbstract":"<p><span>Jeff Eidenshink, Brian Schwind, Ken Brewer, Zhi-Liang Zhu, Brad Quayle, and Elected officials and leaders of environmental agencies need information about the effects of large wildfires in order to set policy and make management decisions. Recently, the Wildland Fire Leadership Council (WFLC), which implements and coordinates the National Fire Plan (NFP) and Federal Wildland Fire Management Policies (National Fire Plan 2004), adopted a strategy to monitor the effectiveness of the National Fire Plan and the Healthy Forests Restoration Act (HFRA). One component of this strategy is to assess the environmental impacts of large wildland fires and identify the trends of burn severity on all lands across the United States. To that end, WFLC has sponsored a six-year project, Monitoring Trends in Burn Severity (MTBS), which requires the U.S. Department of Agriculture Forest Service (USDA-FS) and the U.S. Geological Survey (USGS) to map and assess the burn severity for all large current and historical fires. Using Landsat data and the differenced Normalized Burn Ratio (dNBR) algorithm, the USGS Center for Earth Resources Observation and Science (EROS) and USDA-FS Remote Sensing Applications Center will map burn severity of all fires since 1984 greater than 202 ha (500ac) in the east, and 404 ha (1,000 ac) in the west. The number of historical fires from this period combined with current fires occurring during the course of the project will exceed 9,000. The MTBS project will generate burn severity data, maps, and reports, which will be available for use at local, state, and national levels to evaluate trends in burn severity and help develop and assess the effectiveness of land management decisions. Additionally, the information developed will provide a baseline from which to monitor the recovery and health of fire-affected landscapes over time. Spatial and tabular data quantifying burn severity will augment existing information used to estimate risk associated with a range of current and future resource threats. The annual report of 2004 fires has been completed. All data and results will be distributed to the public on a Web site. A Project for Monitoring Trends in Burn Severity</span></p>","language":"English","publisher":"Association for Fire Ecology","doi":"10.4996/fireecology.0301003","usgsCitation":"Eidenshink, J.C., Schwind, B., Brewer, K., Zhu, Z., Quayle, B., and Howard, S.M., 2007, A project for monitoring trends in burn severity: Fire Ecology, v. 3, no. 1, p. 3-21, https://doi.org/10.4996/fireecology.0301003.","productDescription":"19 p.","startPage":"3","endPage":"21","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":477044,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4996/fireecology.0301003","text":"Publisher Index Page"},{"id":306532,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","issue":"1","noUsgsAuthors":false,"publicationDate":"2007-06-01","publicationStatus":"PW","scienceBaseUri":"55c9cb2fe4b08400b1fdb6e9","contributors":{"authors":[{"text":"Eidenshink, Jeffery C. eidenshink@usgs.gov","contributorId":1352,"corporation":false,"usgs":true,"family":"Eidenshink","given":"Jeffery","email":"eidenshink@usgs.gov","middleInitial":"C.","affiliations":[],"preferred":true,"id":567606,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schwind, Brian","contributorId":146378,"corporation":false,"usgs":false,"family":"Schwind","given":"Brian","email":"","affiliations":[],"preferred":false,"id":567607,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brewer, Ken","contributorId":146379,"corporation":false,"usgs":false,"family":"Brewer","given":"Ken","email":"","affiliations":[],"preferred":false,"id":567608,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhu, Zhu-Liang","contributorId":146380,"corporation":false,"usgs":false,"family":"Zhu","given":"Zhu-Liang","email":"","affiliations":[],"preferred":false,"id":567609,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Quayle, Brad","contributorId":146381,"corporation":false,"usgs":false,"family":"Quayle","given":"Brad","email":"","affiliations":[],"preferred":false,"id":567610,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Howard, Stephen M. 0000-0001-5255-5882 smhoward@usgs.gov","orcid":"https://orcid.org/0000-0001-5255-5882","contributorId":3483,"corporation":false,"usgs":true,"family":"Howard","given":"Stephen","email":"smhoward@usgs.gov","middleInitial":"M.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":567611,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70029742,"text":"70029742 - 2007 - Quantitative remote sensing study indicates doubling of coastal erosion rate in past 50 yr along a segment of the Arctic coast of Alaska","interactions":[],"lastModifiedDate":"2012-03-12T17:21:06","indexId":"70029742","displayToPublicDate":"2007-01-01T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Quantitative remote sensing study indicates doubling of coastal erosion rate in past 50 yr along a segment of the Arctic coast of Alaska","docAbstract":"A new quantitative coastal land gained-and-lost method uses image analysis of topographic maps and Landsat thematic mapper short-wave infrared data to document accelerated coastal land loss and thermokarst lake expansion and drainage. The data span 1955-2005 along the Beaufort Sea coast north of Teshekpuk Lake in the National Petroleum Reserve in Alaska. Some areas have undergone as much as 0.9 km of coastal erosion in the past 50 yr. Land loss attributed to coastal erosion more than doubled, from 0.48 km2 yr-1 during 1955-1985 to 1.08 km2 yr-1 during 1985-2005. Coastal erosion has breached thermokarst lakes, causing initial draining of the lakes followed by marine floodng. Although inland thermokarst lakes show some uniform expansion, lakes breached by coastal erosion display lake expansion several orders of magnitude greater than inland lakes. ?? 2007 The Geological Society of America.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1130/G23672A.1","issn":"00917613","usgsCitation":"Mars, J., and Houseknecht, D., 2007, Quantitative remote sensing study indicates doubling of coastal erosion rate in past 50 yr along a segment of the Arctic coast of Alaska: Geology, v. 35, no. 7, p. 583-586, https://doi.org/10.1130/G23672A.1.","startPage":"583","endPage":"586","numberOfPages":"4","costCenters":[],"links":[{"id":212917,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1130/G23672A.1"},{"id":240482,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a922fe4b0c8380cd806f4","contributors":{"authors":[{"text":"Mars, J.C.","contributorId":74833,"corporation":false,"usgs":true,"family":"Mars","given":"J.C.","affiliations":[],"preferred":false,"id":424090,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Houseknecht, D.W. 0000-0002-9633-6910","orcid":"https://orcid.org/0000-0002-9633-6910","contributorId":33695,"corporation":false,"usgs":true,"family":"Houseknecht","given":"D.W.","affiliations":[],"preferred":false,"id":424089,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70029784,"text":"70029784 - 2007 - Mapping moderate-scale land-cover over very large geographic areas within a collaborative framework: A case study of the Southwest Regional Gap Analysis Project (SWReGAP)","interactions":[],"lastModifiedDate":"2012-03-12T17:21:05","indexId":"70029784","displayToPublicDate":"2007-01-01T00:00:00","publicationYear":"2007","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":"Mapping moderate-scale land-cover over very large geographic areas within a collaborative framework: A case study of the Southwest Regional Gap Analysis Project (SWReGAP)","docAbstract":"Land-cover mapping efforts within the USGS Gap Analysis Program have traditionally been state-centered; each state having the responsibility of implementing a project design for the geographic area within their state boundaries. The Southwest Regional Gap Analysis Project (SWReGAP) was the first formal GAP project designed at a regional, multi-state scale. The project area comprises the southwestern states of Arizona, Colorado, Nevada, New Mexico, and Utah. The land-cover map/dataset was generated using regionally consistent geospatial data (Landsat ETM+ imagery (1999-2001) and DEM derivatives), similar field data collection protocols, a standardized land-cover legend, and a common modeling approach (decision tree classifier). Partitioning of mapping responsibilities amongst the five collaborating states was organized around ecoregion-based \"mapping zones\". Over the course of 21/2 field seasons approximately 93,000 reference samples were collected directly, or obtained from other contemporary projects, for the land-cover modeling effort. The final map was made public in 2004 and contains 125 land-cover classes. An internal validation of 85 of the classes, representing 91% of the land area was performed. Agreement between withheld samples and the validated dataset was 61% (KHAT = .60, n = 17,030). This paper presents an overview of the methodologies used to create the regional land-cover dataset and highlights issues associated with large-area mapping within a coordinated, multi-institutional management framework. ?? 2006 Elsevier Inc. All rights reserved.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Remote Sensing of Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1016/j.rse.2006.11.008","issn":"00344257","usgsCitation":"Lowry, J., Ramsey, R., Thomas, K., Schrupp, D., Sajwaj, T., Kirby, J., Waller, E., Schrader, S., Falzarano, S., Langs, L., Manis, G., Wallace, C., Schulz, K., Comer, P., Pohs, K., Rieth, W., Velasquez, C., Wolk, B., Kepner, W., Boykin, K., O’Brien, L., Bradford, D., Thompson, B., and Prior-Magee, J., 2007, Mapping moderate-scale land-cover over very large geographic areas within a collaborative framework: A case study of the Southwest Regional Gap Analysis Project (SWReGAP): Remote Sensing of Environment, v. 108, no. 1, p. 59-73, https://doi.org/10.1016/j.rse.2006.11.008.","startPage":"59","endPage":"73","numberOfPages":"15","costCenters":[],"links":[{"id":213000,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2006.11.008"},{"id":240579,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"108","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a5060e4b0c8380cd6b664","contributors":{"authors":[{"text":"Lowry, J.","contributorId":82925,"corporation":false,"usgs":true,"family":"Lowry","given":"J.","email":"","affiliations":[],"preferred":false,"id":424324,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ramsey, R.D.","contributorId":46768,"corporation":false,"usgs":true,"family":"Ramsey","given":"R.D.","email":"","affiliations":[],"preferred":false,"id":424317,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thomas, K.","contributorId":37962,"corporation":false,"usgs":true,"family":"Thomas","given":"K.","email":"","affiliations":[],"preferred":false,"id":424313,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schrupp, D.","contributorId":92494,"corporation":false,"usgs":true,"family":"Schrupp","given":"D.","email":"","affiliations":[],"preferred":false,"id":424326,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sajwaj, T.","contributorId":51986,"corporation":false,"usgs":true,"family":"Sajwaj","given":"T.","email":"","affiliations":[],"preferred":false,"id":424319,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kirby, J.","contributorId":45522,"corporation":false,"usgs":true,"family":"Kirby","given":"J.","affiliations":[],"preferred":false,"id":424316,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Waller, E.","contributorId":54389,"corporation":false,"usgs":true,"family":"Waller","given":"E.","email":"","affiliations":[],"preferred":false,"id":424320,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schrader, S.","contributorId":10625,"corporation":false,"usgs":true,"family":"Schrader","given":"S.","email":"","affiliations":[],"preferred":false,"id":424307,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Falzarano, S.","contributorId":35954,"corporation":false,"usgs":true,"family":"Falzarano","given":"S.","email":"","affiliations":[],"preferred":false,"id":424312,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Langs, L.","contributorId":73015,"corporation":false,"usgs":true,"family":"Langs","given":"L.","email":"","affiliations":[],"preferred":false,"id":424322,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Manis, G.","contributorId":86977,"corporation":false,"usgs":true,"family":"Manis","given":"G.","email":"","affiliations":[],"preferred":false,"id":424325,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wallace, C.","contributorId":26885,"corporation":false,"usgs":true,"family":"Wallace","given":"C.","affiliations":[],"preferred":false,"id":424310,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Schulz, K.","contributorId":98544,"corporation":false,"usgs":true,"family":"Schulz","given":"K.","affiliations":[],"preferred":false,"id":424328,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Comer, P.","contributorId":67281,"corporation":false,"usgs":true,"family":"Comer","given":"P.","email":"","affiliations":[],"preferred":false,"id":424321,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Pohs, K.","contributorId":100615,"corporation":false,"usgs":true,"family":"Pohs","given":"K.","email":"","affiliations":[],"preferred":false,"id":424329,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Rieth, W.","contributorId":92495,"corporation":false,"usgs":true,"family":"Rieth","given":"W.","email":"","affiliations":[],"preferred":false,"id":424327,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Velasquez, C.","contributorId":48392,"corporation":false,"usgs":true,"family":"Velasquez","given":"C.","email":"","affiliations":[],"preferred":false,"id":424318,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Wolk, B.","contributorId":37963,"corporation":false,"usgs":true,"family":"Wolk","given":"B.","email":"","affiliations":[],"preferred":false,"id":424314,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Kepner, W.","contributorId":20498,"corporation":false,"usgs":true,"family":"Kepner","given":"W.","affiliations":[],"preferred":false,"id":424309,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Boykin, K.","contributorId":10226,"corporation":false,"usgs":true,"family":"Boykin","given":"K.","email":"","affiliations":[],"preferred":false,"id":424306,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"O’Brien, L.","contributorId":43574,"corporation":false,"usgs":true,"family":"O’Brien","given":"L.","email":"","affiliations":[],"preferred":false,"id":424315,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Bradford, D.","contributorId":35265,"corporation":false,"usgs":true,"family":"Bradford","given":"D.","email":"","affiliations":[],"preferred":false,"id":424311,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Thompson, B.","contributorId":13810,"corporation":false,"usgs":true,"family":"Thompson","given":"B.","affiliations":[],"preferred":false,"id":424308,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Prior-Magee, J.","contributorId":79711,"corporation":false,"usgs":true,"family":"Prior-Magee","given":"J.","affiliations":[],"preferred":false,"id":424323,"contributorType":{"id":1,"text":"Authors"},"rank":24}]}}
,{"id":70029807,"text":"70029807 - 2007 - Postfire soil burn severity mapping with hyperspectral image unmixing","interactions":[],"lastModifiedDate":"2012-03-12T17:21:07","indexId":"70029807","displayToPublicDate":"2007-01-01T00:00:00","publicationYear":"2007","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":"Postfire soil burn severity mapping with hyperspectral image unmixing","docAbstract":"Burn severity is mapped after wildfires to evaluate immediate and long-term fire effects on the landscape. Remotely sensed hyperspectral imagery has the potential to provide important information about fine-scale ground cover components that are indicative of burn severity after large wildland fires. Airborne hyperspectral imagery and ground data were collected after the 2002 Hayman Fire in Colorado to assess the application of high resolution imagery for burn severity mapping and to compare it to standard burn severity mapping methods. Mixture Tuned Matched Filtering (MTMF), a partial spectral unmixing algorithm, was used to identify the spectral abundance of ash, soil, and scorched and green vegetation in the burned area. The overall performance of the MTMF for predicting the ground cover components was satisfactory (r2 = 0.21 to 0.48) based on a comparison to fractional ash, soil, and vegetation cover measured on ground validation plots. The relationship between Landsat-derived differenced Normalized Burn Ratio (dNBR) values and the ground data was also evaluated (r2 = 0.20 to 0.58) and found to be comparable to the MTMF. However, the quantitative information provided by the fine-scale hyperspectral imagery makes it possible to more accurately assess the effects of the fire on the soil surface by identifying discrete ground cover characteristics. These surface effects, especially soil and ash cover and the lack of any remaining vegetative cover, directly relate to potential postfire watershed response processes. ?? 2006 Elsevier Inc. All rights reserved.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Remote Sensing of Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1016/j.rse.2006.11.027","issn":"00344257","usgsCitation":"Robichaud, P., Lewis, S., Laes, D., Hudak, A., Kokaly, R., and Zamudio, J., 2007, Postfire soil burn severity mapping with hyperspectral image unmixing: Remote Sensing of Environment, v. 108, no. 4, p. 467-480, https://doi.org/10.1016/j.rse.2006.11.027.","startPage":"467","endPage":"480","numberOfPages":"14","costCenters":[],"links":[{"id":212836,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2006.11.027"},{"id":240385,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"108","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a7e81e4b0c8380cd7a5a7","contributors":{"authors":[{"text":"Robichaud, P.R.","contributorId":102691,"corporation":false,"usgs":true,"family":"Robichaud","given":"P.R.","email":"","affiliations":[],"preferred":false,"id":424412,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lewis, S.A.","contributorId":82132,"corporation":false,"usgs":true,"family":"Lewis","given":"S.A.","email":"","affiliations":[],"preferred":false,"id":424411,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Laes, D.Y.M.","contributorId":48760,"corporation":false,"usgs":true,"family":"Laes","given":"D.Y.M.","email":"","affiliations":[],"preferred":false,"id":424409,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hudak, A.T.","contributorId":60023,"corporation":false,"usgs":true,"family":"Hudak","given":"A.T.","email":"","affiliations":[],"preferred":false,"id":424410,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kokaly, R.F. 0000-0003-0276-7101","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":42381,"corporation":false,"usgs":true,"family":"Kokaly","given":"R.F.","affiliations":[],"preferred":false,"id":424408,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zamudio, J.A.","contributorId":29436,"corporation":false,"usgs":true,"family":"Zamudio","given":"J.A.","email":"","affiliations":[],"preferred":false,"id":424407,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70029933,"text":"70029933 - 2007 - Spatial patterns of large natural fires in Sierra Nevada wilderness areas","interactions":[],"lastModifiedDate":"2012-03-12T17:21:09","indexId":"70029933","displayToPublicDate":"2007-01-01T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Spatial patterns of large natural fires in Sierra Nevada wilderness areas","docAbstract":"The effects of fire on vegetation vary based on the properties and amount of existing biomass (or fuel) in a forest stand, weather conditions, and topography. Identifying controls over the spatial patterning of fire-induced vegetation change, or fire severity, is critical in understanding fire as a landscape scale process. We use gridded estimates of fire severity, derived from Landsat ETM+ imagery, to identify the biotic and abiotic factors contributing to the observed spatial patterns of fire severity in two large natural fires. Regression tree analysis indicates the importance of weather, topography, and vegetation variables in explaining fire severity patterns between the two fires. Relative humidity explained the highest proportion of total sum of squares throughout the Hoover fire (Yosemite National Park, 2001). The lowest fire severity corresponded with increased relative humidity. For the Williams fire (Sequoia/Kings Canyon National Parks, 2003) dominant vegetation type explains the highest proportion of sum of squares. Dominant vegetation was also important in determining fire severity throughout the Hoover fire. In both fires, forest stands that were dominated by lodgepole pine (Pinus contorta) burned at highest severity, while red fir (Abies magnifica) stands corresponded with the lowest fire severities. There was evidence in both fires that lower wind speed corresponded with higher fire severity, although the highest fire severity in the Williams fire occurred during increased wind speed. Additionally, in the vegetation types that were associated with lower severity, burn severity was lowest when the time since last fire was fewer than 11 and 17 years for the Williams and Hoover fires, respectively. Based on the factors and patterns identified, managers can anticipate the effects of management ignited and naturally ignited fires at the forest stand and the landscape levels. ?? 2007 Springer Science+Business Media, Inc.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Landscape Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1007/s10980-006-9047-5","issn":"09212973","usgsCitation":"Collins, B., Kelly, M., van Wagtendonk, J., and Stephens, S., 2007, Spatial patterns of large natural fires in Sierra Nevada wilderness areas: Landscape Ecology, v. 22, no. 4, p. 545-557, https://doi.org/10.1007/s10980-006-9047-5.","startPage":"545","endPage":"557","numberOfPages":"13","costCenters":[],"links":[{"id":240215,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":212690,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10980-006-9047-5"}],"volume":"22","issue":"4","noUsgsAuthors":false,"publicationDate":"2006-10-19","publicationStatus":"PW","scienceBaseUri":"505b949de4b08c986b31abad","contributors":{"authors":[{"text":"Collins, B.M.","contributorId":33925,"corporation":false,"usgs":true,"family":"Collins","given":"B.M.","email":"","affiliations":[],"preferred":false,"id":424956,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kelly, M.","contributorId":39585,"corporation":false,"usgs":true,"family":"Kelly","given":"M.","affiliations":[],"preferred":false,"id":424957,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Wagtendonk, J. W.","contributorId":85111,"corporation":false,"usgs":true,"family":"van Wagtendonk","given":"J. W.","affiliations":[],"preferred":false,"id":424958,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stephens, S.L.","contributorId":85694,"corporation":false,"usgs":true,"family":"Stephens","given":"S.L.","email":"","affiliations":[],"preferred":false,"id":424959,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70030037,"text":"70030037 - 2007 - The landsat image mosaic of the Antarctica Web Portal","interactions":[],"lastModifiedDate":"2017-04-12T16:19:18","indexId":"70030037","displayToPublicDate":"2007-01-01T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1368,"text":"Data Science Journal","active":true,"publicationSubtype":{"id":10}},"title":"The landsat image mosaic of the Antarctica Web Portal","docAbstract":"<p><span>People believe what they can see. The Poles exist as a frozen dream to most people. The International Polar Year wants to break the ice (so to speak), open up the Poles to the general public, support current polar research, and encourage new research projects.&nbsp;</span><br><span>The IPY officially begins in March, 2007. As part of this effort, the U.S. Geological Survey (USGS) and the British Antarctic Survey (BAS), with funding from the National Science Foundation (NSF), are developing three Landsat mosaics of Antarctica and an Antarctic Web Portal with a Community site and an online map viewer. When scientists are able to view the entire scope of polar research, they will be better able to collaborate and locate the resources they need. When the general public more readily sees what is happening in the polar environments, they will understand how changes to the polar areas affect everyone.</span></p>","language":"English","publisher":"Ubiquity Press","doi":"10.2481/dsj.6.S333","issn":"16831470","usgsCitation":"Rusanowski, C., 2007, The landsat image mosaic of the Antarctica Web Portal: Data Science Journal, v. 6, no. S, p. S333-S352, https://doi.org/10.2481/dsj.6.S333.","productDescription":"20 p.","startPage":"S333","endPage":"S352","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":477287,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2481/dsj.6.s333","text":"Publisher Index Page"},{"id":240291,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":212755,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2481/dsj.6.S333"}],"volume":"6","issue":"S","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bad7be4b08c986b323c3d","contributors":{"authors":[{"text":"Rusanowski, C.J. 0000-0001-6215-4003","orcid":"https://orcid.org/0000-0001-6215-4003","contributorId":82131,"corporation":false,"usgs":true,"family":"Rusanowski","given":"C.J.","email":"","affiliations":[],"preferred":false,"id":425418,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70030100,"text":"70030100 - 2007 - Improved wetland remote sensing in Yellowstone National Park using classification trees to combine TM imagery and ancillary environmental data","interactions":[],"lastModifiedDate":"2018-02-21T11:28:14","indexId":"70030100","displayToPublicDate":"2007-01-01T00:00:00","publicationYear":"2007","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":"Improved wetland remote sensing in Yellowstone National Park using classification trees to combine TM imagery and ancillary environmental data","docAbstract":"<p><span>The U.S. Fish and Wildlife Service uses the term palustrine wetland to describe vegetated wetlands traditionally identified as marsh, bog, fen, swamp, or wet meadow. Landsat TM imagery was combined with image texture and ancillary environmental data to model probabilities of palustrine wetland occurrence in Yellowstone National Park using classification trees. Model training and test locations were identified from National Wetlands Inventory maps, and classification trees were built for seven years spanning a range of annual precipitation. At a coarse level, palustrine wetland was separated from upland. At a finer level, five palustrine wetland types were discriminated: aquatic bed (PAB), emergent (PEM), forested (PFO), scrub–shrub (PSS), and unconsolidated shore (PUS). TM-derived variables alone were relatively accurate at separating wetland from upland, but model error rates dropped incrementally as image texture, DEM-derived terrain variables, and other ancillary GIS layers were added. For classification trees making use of all available predictors, average overall test error rates were 7.8% for palustrine wetland/upland models and 17.0% for palustrine wetland type models, with consistent accuracies across years. However, models were prone to wetland over-prediction. While the predominant PEM class was classified with omission and commission error rates less than 14%, we had difficulty identifying the PAB and PSS classes. Ancillary vegetation information greatly improved PSS classification and moderately improved PFO discrimination. Association with geothermal areas distinguished PUS wetlands. Wetland over-prediction was exacerbated by class imbalance in likely combination with spatial and spectral limitations of the TM sensor. Wetland probability surfaces may be more informative than hard classification, and appear to respond to climate-driven wetland variability. The developed method is portable, relatively easy to implement, and should be applicable in other settings and over larger extents.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2006.10.019","issn":"00344257","usgsCitation":"Wright, C., and Gallant, A.L., 2007, Improved wetland remote sensing in Yellowstone National Park using classification trees to combine TM imagery and ancillary environmental data: Remote Sensing of Environment, v. 107, no. 4, p. 582-605, https://doi.org/10.1016/j.rse.2006.10.019.","productDescription":"24 p.","startPage":"582","endPage":"605","numberOfPages":"24","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":240226,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":212700,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2006.10.019"}],"volume":"107","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a3968e4b0c8380cd618f2","contributors":{"authors":[{"text":"Wright, C.","contributorId":69589,"corporation":false,"usgs":true,"family":"Wright","given":"C.","affiliations":[],"preferred":false,"id":425715,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gallant, Alisa L. 0000-0002-3029-6637 gallant@usgs.gov","orcid":"https://orcid.org/0000-0002-3029-6637","contributorId":2940,"corporation":false,"usgs":true,"family":"Gallant","given":"Alisa","email":"gallant@usgs.gov","middleInitial":"L.","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":425716,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70030150,"text":"70030150 - 2007 - Comparison of outgassing models for the Landsat thematic mapper sensors","interactions":[],"lastModifiedDate":"2022-05-18T15:26:18.828641","indexId":"70030150","displayToPublicDate":"2007-01-01T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Comparison of outgassing models for the Landsat thematic mapper sensors","docAbstract":"<p>The Thematic Mapper (TM) is a multi-spectral electro-optical sensor featured onboard both the Landsat 4 (L4) and Landsat 5 (L5) satellites. TM sensors have seven spectral bands with center wavelengths of approximately 0.49, 0.56, 0.66, 0.83, 1.65, 11.5 and 2.21 μm, respectively. The visible near-infrared (VNIR) bands are located on the primary focal plane (PFP), and two short-wave infrared (SWIR) bands and the thermal infrared (TIR) band are located on the cold focal plane (CFP). The CFP bands are maintained at cryogenic temperatures of about 91 K, to reduce thermal noise effects. Due to the cold temperature, an ice film accumulates on the CFP dewar window, which introduces oscillations in SWIR and an exponential decay in TIR band responses. This process is usually monitored and characterized by the detector responses to the internal calibrator (IC) lamps and the blackbody. The ice contamination on the dewar window is an effect of the sensor outgassing in a vacuum of the space environment. Outgassing models have been developed, which are based on the thin-film optical interference phenomenon. They provide the coefficients for correction for outgassing effects for the entire mission's lifetime. While the L4 TM ceased imaging in August 1993, the L5 TM continues to operate even after more than 23 years in orbit. The process of outgassing in L5 TM is still occurring, though at a much lower rate than during early years of mission. Although the L4 and L5 TM sensors are essentially identical, they exhibit slightly different responses to the outgassing effects. The work presented in the paper summarizes the results of modeling outgassing effects in each of the sensors and provides a detailed analysis of differences among the estimated modeling parameters. For both sensors, water ice was confirmed as a reasonable candidate for contaminant material, the contaminant growth rate was found to be gradually decreasing with the time since launch, and the indications exist that some film may remain after the CFP warm-up procedures, which are periodically initiated to remove accumulated contamination. The observed difference between the models could be contributed to differences in the operational history for the sensors, the content and amount of contaminant impurities, the sensor spectral filter responses, and the internal calibrator systems.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of SPIE - The International Society for Optical Engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Earth Observing Systems XII","conferenceDate":"Aug 26-28, 2007","conferenceLocation":"San Diego, CA","language":"English","publisher":"SPIE","doi":"10.1117/12.735405","usgsCitation":"Micijevic, E., and Chander, G., 2007, Comparison of outgassing models for the Landsat thematic mapper sensors, <i>in</i> Proceedings of SPIE - The International Society for Optical Engineering, v. 6677, San Diego, CA, Aug 26-28, 2007, 66770G, https://doi.org/10.1117/12.735405.","productDescription":"66770G","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":240507,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6677","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059f87de4b0c8380cd4d133","contributors":{"authors":[{"text":"Micijevic, E. 0000-0002-3828-9239","orcid":"https://orcid.org/0000-0002-3828-9239","contributorId":59939,"corporation":false,"usgs":true,"family":"Micijevic","given":"E.","affiliations":[],"preferred":false,"id":425910,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chander, G.","contributorId":51449,"corporation":false,"usgs":true,"family":"Chander","given":"G.","affiliations":[],"preferred":false,"id":425909,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70030162,"text":"70030162 - 2007 - A land-cover map for South and Southeast Asia derived from SPOT-VEGETATION data","interactions":[],"lastModifiedDate":"2017-04-12T16:17:47","indexId":"70030162","displayToPublicDate":"2007-01-01T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2193,"text":"Journal of Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"A land-cover map for South and Southeast Asia derived from SPOT-VEGETATION data","docAbstract":"<p><strong>Aim </strong> Our aim was to produce a uniform ‘regional’ land-cover map of South and Southeast Asia based on ‘sub-regional’ mapping results generated in the context of the Global Land Cover 2000 project.</p><p><strong>Location </strong> The ‘region’ of tropical and sub-tropical South and Southeast Asia stretches from the Himalayas and the southern border of China in the north, to Sri Lanka and Indonesia in the south, and from Pakistan in the west to the islands of New Guinea in the far east.</p><p><strong>Methods </strong> The regional land-cover map is based on sub-regional digital mapping results derived from SPOT-VEGETATION satellite data for the years 1998–2000. Image processing, digital classification and thematic mapping were performed separately for the three sub-regions of South Asia, continental Southeast Asia, and insular Southeast Asia. Landsat TM images, field data and existing national maps served as references. We used the FAO (Food and Agriculture Organization) Land Cover Classification System (LCCS) for coding the sub-regional land-cover classes and for aggregating the latter to a uniform regional legend. A validation was performed based on a systematic grid of sample points, referring to visual interpretation from high-resolution Landsat imagery. Regional land-cover area estimates were obtained and compared with FAO statistics for the categories ‘forest’ and ‘cropland’.</p><p><strong>Results </strong> The regional map displays 26 land-cover classes. The LCCS coding provided a standardized class description, independent from local class names; it also allowed us to maintain the link to the detailed sub-regional land-cover classes. The validation of the map displayed a mapping accuracy of 72% for the dominant classes of ‘forest’ and ‘cropland’; regional area estimates for these classes correspond reasonably well to existing regional statistics.</p><p><strong>Main conclusions </strong> The land-cover map of South and Southeast Asia provides a synoptic view of the distribution of land cover of tropical and sub-tropical Asia, and it delivers reasonable thematic detail and quantitative estimates of the main land-cover proportions. The map may therefore serve for regional stratification or modelling of vegetation cover, but could also support the implementation of forest policies, watershed management or conservation strategies at regional scales.</p>","language":"English","publisher":"Wiley","doi":"10.1111/j.1365-2699.2006.01637.x","issn":"03050270","usgsCitation":"Stibig, H., Belward, A., Roy, P., Rosalina-Wasrin, U., Agrawal, S., Joshi, P., Hildanus, Beuchle, R., Fritz, S., Mubareka, S., and Giri, S., 2007, A land-cover map for South and Southeast Asia derived from SPOT-VEGETATION data: Journal of Biogeography, v. 34, no. 4, p. 625-637, https://doi.org/10.1111/j.1365-2699.2006.01637.x.","productDescription":"13 p.","startPage":"625","endPage":"637","numberOfPages":"13","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":240196,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":212673,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1365-2699.2006.01637.x"}],"volume":"34","issue":"4","noUsgsAuthors":false,"publicationDate":"2006-11-28","publicationStatus":"PW","scienceBaseUri":"5059e430e4b0c8380cd4649c","contributors":{"authors":[{"text":"Stibig, H.-J.","contributorId":14198,"corporation":false,"usgs":true,"family":"Stibig","given":"H.-J.","email":"","affiliations":[],"preferred":false,"id":425958,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belward, A.S.","contributorId":6197,"corporation":false,"usgs":true,"family":"Belward","given":"A.S.","email":"","affiliations":[],"preferred":false,"id":425956,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roy, P.S.","contributorId":87369,"corporation":false,"usgs":true,"family":"Roy","given":"P.S.","email":"","affiliations":[],"preferred":false,"id":425964,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rosalina-Wasrin, U.","contributorId":39199,"corporation":false,"usgs":true,"family":"Rosalina-Wasrin","given":"U.","email":"","affiliations":[],"preferred":false,"id":425960,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Agrawal, S.","contributorId":30448,"corporation":false,"usgs":true,"family":"Agrawal","given":"S.","email":"","affiliations":[],"preferred":false,"id":425959,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Joshi, P.K.","contributorId":78553,"corporation":false,"usgs":true,"family":"Joshi","given":"P.K.","email":"","affiliations":[],"preferred":false,"id":425963,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hildanus","contributorId":128026,"corporation":true,"usgs":false,"organization":"Hildanus","id":535157,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Beuchle, R.","contributorId":39584,"corporation":false,"usgs":true,"family":"Beuchle","given":"R.","email":"","affiliations":[],"preferred":false,"id":425961,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fritz, S.","contributorId":91221,"corporation":false,"usgs":true,"family":"Fritz","given":"S.","email":"","affiliations":[],"preferred":false,"id":425965,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mubareka, S.","contributorId":7912,"corporation":false,"usgs":true,"family":"Mubareka","given":"S.","email":"","affiliations":[],"preferred":false,"id":425957,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Giri, S.","contributorId":102621,"corporation":false,"usgs":true,"family":"Giri","given":"S.","email":"","affiliations":[],"preferred":false,"id":425966,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70042855,"text":"cir13065B - 2007 - Land area changes in coastal Louisiana after Hurricanes Katrina and Rita","interactions":[],"lastModifiedDate":"2019-06-18T11:50:24","indexId":"cir13065B","displayToPublicDate":"2007-01-01T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1306","chapter":"5B","title":"Land area changes in coastal Louisiana after Hurricanes Katrina and Rita","docAbstract":"Comparison of classified Landsat Thematic Mapper (TM) satellite imagery acquired before and after the landfalls of Hurricanes Katrina (August 29, 2005) and Rita (September 24, 2005) demonstrated that water area increased by 217 mi<sup>2</sup> (562 km<sup>2</sup>) in coastal Louisiana. Approximately 82 mi<sup>2</sup> (212 km<sup>2</sup>) of new water areas were in areas primarily impacted by Katrina (Mississippi River Delta basin, Breton Sound basin, Pontchartrain basin, Pearl River basin), whereas 117 mi<sup>2</sup> (303 km<sup>2</sup>) were in areas primarily impacted by Rita (Calcasieu/ Sabine basin, Mermentau basin, Teche/Vermilion basin, Atchafalaya basin, Terrebonne basin). Barataria basin contained new water areas caused by both hurricanes, resulting in some 18 mi<sup>2</sup> (46.6 km<sup>2</sup>) of new water areas. The fresh marsh and intermediate marsh communities' land areas decreased by 122 mi<sup>2</sup> (316 km<sup>2</sup>) and 90 mi<sup>2</sup> (233.1 km<sup>2</sup>), respectively. The brackish marsh and saline marsh communities' land areas decreased by 33 mi<sup>2</sup> (85.5 km<sup>2</sup>) and 28 mi<sup>2</sup> (72.5 km<sup>2</sup>), respectively. These new water areas identify permanent losses caused by direct removal of wetlands. They also indicate transitory water area changes caused by remnant flooding, removal of aquatic vegetation, scouring of marsh vegetation, and water-level variation attributed to normal tidal and meteorological variation between satellite images. Permanent losses cannot be estimated until several growing seasons have passed and the transitory impacts of the hurricanes are minimized. The purpose of this study was to provide preliminary information on water area changes in coastal Louisiana acquired shortly after both hurricanes' landfalls (detectable with Landsat TM imagery) and to serve as a regional baseline for monitoring posthurricane wetland recovery.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Science and the storms-the USGS response to the hurricanes of 2005 (Circular 1306)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir13065B","collaboration":"This report is Chapter 5B in <i>Science and the storms-the USGS response to the hurricanes of 2005</i>.  See <a href=\"http://pubs.er.usgs.gov/publication/cir1306\" target=\"_blank\">Circular 1306</a> for more information and other chapters.","usgsCitation":"Barras, J., 2007, Land area changes in coastal Louisiana after Hurricanes Katrina and Rita: U.S. Geological Survey Circular 1306, 16 p., https://doi.org/10.3133/cir13065B.","productDescription":"16 p.","startPage":"97","endPage":"112","numberOfPages":"16","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":266487,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/cir_1306_5b.jpg"},{"id":266484,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1306/pdf/c1306_ch5_b.pdf"},{"id":266485,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ofr20061274"},{"id":266483,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/circ/1306/"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -93.779296875,\n              28.844673680771795\n            ],\n            [\n              -88.6376953125,\n              28.844673680771795\n            ],\n            [\n              -88.6376953125,\n              30.50548389892728\n            ],\n            [\n              -93.779296875,\n              30.50548389892728\n            ],\n            [\n              -93.779296875,\n              28.844673680771795\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5103b78ae4b0ce88de640a20","contributors":{"authors":[{"text":"Barras, John A. jbarras@usgs.gov","contributorId":2425,"corporation":false,"usgs":true,"family":"Barras","given":"John A.","email":"jbarras@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":472393,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70042708,"text":"cir13063F - 2007 - Hurricane Katrina flooding and oil slicks mapped with satellite imagery","interactions":[],"lastModifiedDate":"2019-06-18T12:12:46","indexId":"cir13063F","displayToPublicDate":"2007-01-01T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1306","chapter":"3F","title":"Hurricane Katrina flooding and oil slicks mapped with satellite imagery","docAbstract":"A multiple-database approach that combined remotely sensed data from Radarsat-1 and Landsat Thematic Mapper Plus (ETM+) imagery was used to map Hurricane Katrinainduced flooding and to identify offshore oil slicks. Maps depicting the areal extent of flooding, oil slicks, and floating debris provide vital information to emergency managers for directing floodrelief efforts and the clean-up of polluted waters.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Science and the storms-the USGS response to the hurricanes of 2005 (Circular 1306)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir13063F","collaboration":"This report is Chapter 3F in <i>Science and the storms-the USGS response to the hurricanes of 2005</i>.  See <a href=\"http://pubs.er.usgs.gov/publication/cir1306\" target=\"_blank\">Circular 1306</a> for more information and other chapters.","usgsCitation":"Rykhus, R.P., and Lu, Z., 2007, Hurricane Katrina flooding and oil slicks mapped with satellite imagery: U.S. Geological Survey Circular 1306, 4 p., https://doi.org/10.3133/cir13063F.","productDescription":"4 p.","startPage":"49","endPage":"52","numberOfPages":"4","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":265899,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/cir_1306_3f.jpg"},{"id":265897,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/circ/1306/"},{"id":265898,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1306/pdf/c1306_ch3_f.pdf"}],"country":"United States","otherGeospatial":"Gulf Of Mexico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -91.44,28.55 ], [ -91.44,30.4 ], [ -87.6,30.4 ], [ -87.6,28.55 ], [ -91.44,28.55 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50fa7d61e4b061045bf9ac7f","contributors":{"authors":[{"text":"Rykhus, Russell P.","contributorId":27337,"corporation":false,"usgs":true,"family":"Rykhus","given":"Russell","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":472095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lu, Zhong 0000-0001-9181-1818 lu@usgs.gov","orcid":"https://orcid.org/0000-0001-9181-1818","contributorId":901,"corporation":false,"usgs":true,"family":"Lu","given":"Zhong","email":"lu@usgs.gov","affiliations":[],"preferred":true,"id":472094,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70034543,"text":"70034543 - 2007 - Improved outgassing models for the Landsat-5 thematic mapper","interactions":[],"lastModifiedDate":"2022-05-18T15:07:28.918166","indexId":"70034543","displayToPublicDate":"2007-01-01T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Improved outgassing models for the Landsat-5 thematic mapper","docAbstract":"<p>The Landsat-5 (L5) Thematic Mapper (TM) detectors of the short wave infrared (SWIR) bands 5 and 7 are maintained on cryogenic temperatures to minimize thermal noise and allow adequate detection of scene energy. Over the instrument's lifetime, gain oscillations are observed in these bands that are caused by an ice-like contaminant that gradually builds up on the window of a dewar that houses these bands' detectors. This process of icing, an effect of material outgassing in space, is detected and characterized through observations of Internal Calibrator (IC) data. Analyses of IC data indicated three to five percent uncertainty in absolute gain estimates due to this icing phenomenon. The thin-film interference lifetime models implemented in the image product generation systems at the U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS) successfully remove up to 80 percent of the icing effects for the image acquisition period from the satellite's launch in 1984 until 2001; however, their correction ability was found to be much lower for the time thereafter. This study concentrates on improving the estimates of the contaminant film growth rate and the associated change in the period of gain oscillations. The goal is to provide model parameters with the potential to correct 70 to 80 percent of gain uncertainties caused by outgassing effects in L5 TM bands 5 and 7 over the instrument's entire lifetime.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"International Geoscience and Remote Sensing Symposium (IGARSS)","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"2007 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2007","conferenceDate":"June 23-28, 2007","conferenceLocation":"Barcelona, Spain","language":"English","publisher":"IEEE","doi":"10.1109/IGARSS.2007.4423440","usgsCitation":"Micijevic, E., Chander, G., and Hayes, R.W., 2007, Improved outgassing models for the Landsat-5 thematic mapper, <i>in</i> International Geoscience and Remote Sensing Symposium (IGARSS), Barcelona, Spain, June 23-28, 2007, p. 2860-2863, https://doi.org/10.1109/IGARSS.2007.4423440.","productDescription":"4 p.","startPage":"2860","endPage":"2863","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":243598,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a3961e4b0c8380cd618d7","contributors":{"authors":[{"text":"Micijevic, E. 0000-0002-3828-9239","orcid":"https://orcid.org/0000-0002-3828-9239","contributorId":59939,"corporation":false,"usgs":true,"family":"Micijevic","given":"E.","affiliations":[],"preferred":false,"id":446312,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chander, G.","contributorId":51449,"corporation":false,"usgs":true,"family":"Chander","given":"G.","affiliations":[],"preferred":false,"id":446311,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayes, R. W.","contributorId":105493,"corporation":false,"usgs":true,"family":"Hayes","given":"R.","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":446313,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70010312,"text":"70010312 - 2007 - Local search for optimal global map generation using mid-decadal landsat images","interactions":[],"lastModifiedDate":"2012-03-12T17:18:23","indexId":"70010312","displayToPublicDate":"2007-01-01T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Local search for optimal global map generation using mid-decadal landsat images","docAbstract":"NASA and the US Geological Survey (USGS) are seeking to generate a map of the entire globe using Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor data from the \"mid-decadal\" period of 2004 through 2006. The global map is comprised of thousands of scene locations and, for each location, tens of different images of varying quality to chose from. Furthermore, it is desirable for images of adjacent scenes be close together in time of acquisition, to avoid obvious discontinuities due to seasonal changes. These characteristics make it desirable to formulate an automated solution to the problem of generating the complete map. This paper formulates a Global Map Generator problem as a Constraint Optimization Problem (GMG-COP) and describes an approach to solving it using local search. Preliminary results of running the algorithm on image data sets are summarized. The results suggest a significant improvement in map quality using constraint-based solutions. Copyright ?? 2007, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.","largerWorkTitle":"AAAI Workshop - Technical Report","conferenceTitle":"2007 AAAI Workshop","conferenceDate":"22 July 2007 through 22 July 2007","conferenceLocation":"Vancouver, BC","language":"English","isbn":"9781577353379","usgsCitation":"Khatib, L., Gasch, J., Morris, R., and Covington, S., 2007, Local search for optimal global map generation using mid-decadal landsat images, <i>in</i> AAAI Workshop - Technical Report, v. WS-07-10, Vancouver, BC, 22 July 2007 through 22 July 2007, p. 66-70.","startPage":"66","endPage":"70","numberOfPages":"5","costCenters":[],"links":[{"id":219676,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"WS-07-10","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a48e4e4b0c8380cd681d9","contributors":{"authors":[{"text":"Khatib, L.","contributorId":87816,"corporation":false,"usgs":true,"family":"Khatib","given":"L.","email":"","affiliations":[],"preferred":false,"id":358605,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gasch, J.","contributorId":87388,"corporation":false,"usgs":true,"family":"Gasch","given":"J.","email":"","affiliations":[],"preferred":false,"id":358604,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morris, Robert","contributorId":70723,"corporation":false,"usgs":true,"family":"Morris","given":"Robert","affiliations":[],"preferred":false,"id":358603,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Covington, S.","contributorId":13111,"corporation":false,"usgs":true,"family":"Covington","given":"S.","email":"","affiliations":[],"preferred":false,"id":358602,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70031771,"text":"70031771 - 2007 - Characterization of post-fire surface cover, soils, and burn severity at the Cerro Grande Fire, New Mexico, using hyperspectral and multispectral remote sensing","interactions":[],"lastModifiedDate":"2012-03-12T17:21:14","indexId":"70031771","displayToPublicDate":"2007-01-01T00:00:00","publicationYear":"2007","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":"Characterization of post-fire surface cover, soils, and burn severity at the Cerro Grande Fire, New Mexico, using hyperspectral and multispectral remote sensing","docAbstract":"Forest fires leave behind a changed ecosystem with a patchwork of surface cover that includes ash, charred organic matter, soils and soil minerals, and dead, damaged, and living vegetation. The distributions of these materials affect post-fire processes of erosion, nutrient cycling, and vegetation regrowth. We analyzed high spatial resolution (2.4??m pixel size) Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) data collected over the Cerro Grande fire, to map post-fire surface cover into 10 classes, including ash, soil minerals, scorched conifer trees, and green vegetation. The Cerro Grande fire occurred near Los Alamos, New Mexico, in May 2000. The AVIRIS data were collected September 3, 2000. The surface cover map revealed complex patterns of ash, iron oxide minerals, and clay minerals in areas of complete combustion. Scorched conifer trees, which retained dry needles heated by the fire but not fully combusted by the flames, were found to cover much of the post-fire landscape. These scorched trees were found in narrow zones at the edges of completely burned areas. A surface cover map was also made using Landsat Enhanced Thematic Mapper plus (ETM+) data, collected September 5, 2000, and a maximum likelihood, supervised classification. When compared to AVIRIS, the Landsat classification grossly overestimated cover by dry conifer and ash classes and severely underestimated soil and green vegetation cover. In a comparison of AVIRIS surface cover to the Burned Area Emergency Rehabilitation (BAER) map of burn severity, the BAER high burn severity areas did not capture the variable patterns of post-fire surface cover by ash, soil, and scorched conifer trees seen in the AVIRIS map. The BAER map, derived from air photos, also did not capture the distribution of scorched trees that were observed in the AVIRIS map. Similarly, the moderate severity class of Landsat-derived burn severity maps generated from the differenced Normalized Burn Ratio (dNBR) calculation had low agreement with the AVIRIS classes of scorched conifer trees. Burn severity and surface cover images were found to contain complementary information, with the dNBR map presenting an image of degree of change caused by fire and the AVIRIS-derived map showing specific surface cover resulting from fire.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Remote Sensing of Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1016/j.rse.2006.08.006","issn":"00344257","usgsCitation":"Kokaly, R., Rockwell, B., Haire, S., and King, T.V., 2007, Characterization of post-fire surface cover, soils, and burn severity at the Cerro Grande Fire, New Mexico, using hyperspectral and multispectral remote sensing: Remote Sensing of Environment, v. 106, no. 3, p. 305-325, https://doi.org/10.1016/j.rse.2006.08.006.","startPage":"305","endPage":"325","numberOfPages":"21","costCenters":[],"links":[{"id":239678,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":212224,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2006.08.006"}],"volume":"106","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059f4d6e4b0c8380cd4bf5a","contributors":{"authors":[{"text":"Kokaly, R.F. 0000-0003-0276-7101","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":42381,"corporation":false,"usgs":true,"family":"Kokaly","given":"R.F.","affiliations":[],"preferred":false,"id":433047,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rockwell, B.W.","contributorId":73396,"corporation":false,"usgs":true,"family":"Rockwell","given":"B.W.","email":"","affiliations":[],"preferred":false,"id":433048,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haire, S.L.","contributorId":23503,"corporation":false,"usgs":true,"family":"Haire","given":"S.L.","email":"","affiliations":[],"preferred":false,"id":433046,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"King, T. V. V.","contributorId":6192,"corporation":false,"usgs":true,"family":"King","given":"T.","email":"","middleInitial":"V. V.","affiliations":[],"preferred":false,"id":433045,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70031630,"text":"70031630 - 2007 - Consistency of L4 TM absolute calibration with respect to the L5 TM sensor based on near-simultaneous image acquisition","interactions":[],"lastModifiedDate":"2022-05-17T16:27:34.255739","indexId":"70031630","displayToPublicDate":"2007-01-01T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Consistency of L4 TM absolute calibration with respect to the L5 TM sensor based on near-simultaneous image acquisition","docAbstract":"The Landsat archive provides more than 35 years of uninterrupted multispectral remotely sensed data of Earth observations. Since 1972, Landsat missions have carried different types of sensors, from the Return Beam Vidicon (RBV) camera to the Enhanced Thematic Mapper Plus (ETM+). However, the Thematic Mapper (TM) sensors on Landsat 4 (L4) and Landsat 5 (L5), launched in 1982 and 1984 respectively, are the backbone of an extensive archive. Effective April 2, 2007, the radiometric calibration of L5 TM data processed and distributed by the U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS) was updated to use an improved lifetime gain model, based on the instrument's detector response to pseudo-invariant desert site data and cross-calibration with the L7 ETM+. However, no modifications were ever made to the radiometric calibration procedure of the Landsat 4 (L4) TM data. The L4 TM radiometric calibration procedure has continued to use the Internal Calibrator (IC) based calibration algorithms and the post calibration dynamic ranges, as previously defined. To evaluate the \"current\" absolute accuracy of these two sensors, image pairs from the L5 TM and L4 TM sensors were compared. The number of coincident image pairs in the USGS EROS archive is limited, so the scene selection for the cross-calibration studies proved to be a challenge. Additionally, because of the lack of near-simultaneous images available over well-characterized and traditionally used calibration sites, alternate sites that have high reflectance, large dynamic range, high spatial uniformity, high sun elevation, and minimal cloud cover were investigated. The alternate sites were identified in Yuma, Iraq, Egypt, Libya, and Algeria. The cross-calibration approach involved comparing image statistics derived from large common areas observed eight days apart by the two sensors. This paper summarizes the average percent differences in reflectance estimates obtained between the two sensors. The work presented in this paper is a first step in understanding the current performance of L4 TM absolute calibration and potentially serves as a platform to revise and improve the radiometric calibration procedures implemented for the processing of L4 TM data.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of SPIE - The International Society for Optical Engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Earth Observing Systems XII","conferenceDate":"Aug 26-28, 2007","conferenceLocation":"San Diego, CA","language":"English","publisher":"SPIE","doi":"10.1117/12.734208","usgsCitation":"Chander, G., Helder, D., Malla, R., Micijevic, E., and Mettler, C.J., 2007, Consistency of L4 TM absolute calibration with respect to the L5 TM sensor based on near-simultaneous image acquisition, <i>in</i> Proceedings of SPIE - The International Society for Optical Engineering, v. 6677, San Diego, CA, Aug 26-28, 2007, 66770F, https://doi.org/10.1117/12.734208.","productDescription":"66770F","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":240076,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6677","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059fa00e4b0c8380cd4d87d","contributors":{"authors":[{"text":"Chander, G.","contributorId":51449,"corporation":false,"usgs":true,"family":"Chander","given":"G.","affiliations":[],"preferred":false,"id":432423,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Helder, D. L. 0000-0002-7379-4679","orcid":"https://orcid.org/0000-0002-7379-4679","contributorId":51496,"corporation":false,"usgs":true,"family":"Helder","given":"D. L.","affiliations":[],"preferred":false,"id":432424,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Malla, R.","contributorId":9866,"corporation":false,"usgs":true,"family":"Malla","given":"R.","email":"","affiliations":[],"preferred":false,"id":432422,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Micijevic, E. 0000-0002-3828-9239","orcid":"https://orcid.org/0000-0002-3828-9239","contributorId":59939,"corporation":false,"usgs":true,"family":"Micijevic","given":"E.","affiliations":[],"preferred":false,"id":432425,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mettler, C. J.","contributorId":65670,"corporation":false,"usgs":true,"family":"Mettler","given":"C.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":432426,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70031622,"text":"70031622 - 2007 - Regional dynamics of grassland change in the western Great Plains","interactions":[],"lastModifiedDate":"2012-03-12T17:21:11","indexId":"70031622","displayToPublicDate":"2007-01-01T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Regional dynamics of grassland change in the western Great Plains","docAbstract":"This paper examines the contemporary land-cover changes in two western Great Plains ecoregions between 1973 and 2000. Agriculture and other land uses can have a substantial effect on grassland cover that varies regionally depending on the primary driving forces of change. In order to better understand change, the rates, types, and causes of land conversion were examined for 1973, 1980, 1986, 1992, and 2000 using Landsat satellite data and a statistical sampling strategy. The overall estimated rate of land-cover change between 1973 and 2000 was 7.4% in the Northwestern Great Plains and 11.5% in the Western High Plains. Trends in both ecoregions have similarities, although the dynamics of change differ temporally depending on driving forces. Between 1973 and 1986, grassland cover declined when economic opportunity drove an expansion of agriculture. Between 1986 and 2000, grassland expanded as public policy and a combination of socioeconomic factors drove a conversion from agriculture to grassland. ?? 2007 Copyright by the Center for Great Plains Studies, University of Nebraska-Lincoln.","largerWorkTitle":"Great Plains Research","language":"English","issn":"10525165","usgsCitation":"Drummond, M., 2007, Regional dynamics of grassland change in the western Great Plains, <i>in</i> Great Plains Research, v. 17, no. 2, p. 133-144.","startPage":"133","endPage":"144","numberOfPages":"12","costCenters":[],"links":[{"id":239937,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e4a4c1e4b0e8fec6cdbc4b","contributors":{"authors":[{"text":"Drummond, M.A.","contributorId":53602,"corporation":false,"usgs":true,"family":"Drummond","given":"M.A.","email":"","affiliations":[],"preferred":false,"id":432395,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70031566,"text":"70031566 - 2007 - Radiometric calibration status of Landsat-7 and Landsat-5","interactions":[],"lastModifiedDate":"2012-03-12T17:21:09","indexId":"70031566","displayToPublicDate":"2007-01-01T00:00:00","publicationYear":"2007","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Radiometric calibration status of Landsat-7 and Landsat-5","docAbstract":"Launched in April 1999, Landsat-7 ETM+ continues to acquire data globally. The Scan Line Corrector in failure in 2003 has affected ground coverage and the recent switch to Bumper Mode operations in April 2007 has degraded the internal geometric accuracy of the data, but the radiometry has been unaffected. The best of the three on-board calibrators for the reflective bands, the Full Aperture Solar Calibrator, has indicated slow changes in the ETM+, but this is believed to be due to contamination on the panel rather then instrument degradation. The Internal Calibrator lamp 2, though it has not been used regularly throughout the whole mission, indicates smaller changes than the FASC since 2003. The changes indicated by lamp 2 are only statistically significant in band 1, circa 0.3% per year, and may be lamp as opposed to instrument degradations. Regular observations of desert targets in the Saharan and Arabian deserts indicate the no change in the ETM+ reflective band response, though the uncertainty is larger and does not preclude the small changes indicated by lamp 2. The thermal band continues to be stable and well-calibrated since an offset error was corrected in late-2000. Launched in 1984, Landsat-5 TM also continues to acquire global data; though without the benefit of an on-board recorder, data can only be acquired where a ground station is within range. Historically, the calibration of the TM reflective bands has used an onboard calibration system with multiple lamps. The calibration procedure for the TM reflective bands was updated in 2003 based on the best estimate at the time, using only one of the three lamps and a cross-calibration with Landsat-7 ETM+. Since then, the Saharan desert sites have been used to validate this calibration model. Problems were found with the lamp based model of up to 13% in band 1. Using the Saharan data, a new model was developed and implemented in the US processing system in April 2007. The TM thermal band was found to have a calibration offset error of 0.092 W/m 2 sr ??m (0.68K at 300K) based on vicarious calibration data between 1999 and 2006. The offset error was corrected in the US processing system on April 2007 for all data acquired since April 1999.","largerWorkTitle":"Proceedings of SPIE - The International Society for Optical Engineering","conferenceTitle":"Sensors, Systems, and Next-Generation Satellites XI","conferenceDate":"17 September 2007 through 20 September 2007","conferenceLocation":"Florence","language":"English","doi":"10.1117/12.738221","issn":"0277786X","isbn":"9780819469021","usgsCitation":"Barsi, J., Markham, B.L., Helder, D., and Chander, G., 2007, Radiometric calibration status of Landsat-7 and Landsat-5, <i>in</i> Proceedings of SPIE - The International Society for Optical Engineering, v. 6744, Florence, 17 September 2007 through 20 September 2007, https://doi.org/10.1117/12.738221.","costCenters":[],"links":[{"id":212629,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1117/12.738221"},{"id":240144,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6744","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a940fe4b0c8380cd8119c","contributors":{"authors":[{"text":"Barsi, J. A.","contributorId":24085,"corporation":false,"usgs":true,"family":"Barsi","given":"J. A.","affiliations":[],"preferred":false,"id":432149,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Markham, B. L.","contributorId":88872,"corporation":false,"usgs":true,"family":"Markham","given":"B.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":432152,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Helder, D. L. 0000-0002-7379-4679","orcid":"https://orcid.org/0000-0002-7379-4679","contributorId":51496,"corporation":false,"usgs":true,"family":"Helder","given":"D. L.","affiliations":[],"preferred":false,"id":432151,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chander, G.","contributorId":51449,"corporation":false,"usgs":true,"family":"Chander","given":"G.","affiliations":[],"preferred":false,"id":432150,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
]}