The Landsat Data Continuity Mission (LDCM) is the follow-on mission to Landsat 7 and will be the eighth mission in the Landsat series. The mission is in development via an interagency partnership between the National Aeronautics and Space Administration (NASA) and the Department of Interior (DOI) / United States Geological Survey (USGS). The LDCM satellite will carry two earth-observing sensors, the Operational Land Imager (OLI) to collect image data for nine spectral bands in the reflective portion of the spectrum and the Thermal Infrared Sensor (TIRS) to collect coincident image data for two thermal spectral bands. The LDCM ground segment will control the satellite and will receive, process, archive, and distribute the science data collected by the OLI and TIRS instruments. The USGS Earth Resources Observation & Science Center (EROS) will distribute LDCM data products at no cost to requestors. The mission objective is to continues the Landsat program's collection, archive, and distribution of multispectral imagery affording global, synoptic, and repetitive coverage of the Earth's land surfaces at a scale where natural and human-induced changes can be detected, differentiated, characterized, and monitored over time. The LDCM launch readiness date is currently December, 2012.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of SPIE 7695, algorithms and technologies for multispectral, hyperspectral, and ultraspectral imagery XVI","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SPIE 7695","conferenceDate":"April 5-9, 2010","conferenceLocation":"Orlando, Florida, United States","language":"English","publisher":"Society of Photo-Optical Instrumentation Engineers","doi":"10.1117/12.850416","usgsCitation":"Irons, J.R., and Dwyer, J.L., 2010, An overview of the Landsat Data Continuity Mission, in Proceedings of SPIE 7695, algorithms and technologies for multispectral, hyperspectral, and ultraspectral imagery XVI, v. 7695, Orlando, Florida, United States, April 5-9, 2010, 769508, 7 p., https://doi.org/10.1117/12.850416.","productDescription":"769508, 7 p.","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":475723,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/2060/20100031706","text":"External Repository"},{"id":394905,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7695","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Shen, Sylvia S.","contributorId":272229,"corporation":false,"usgs":false,"family":"Shen","given":"Sylvia S.","affiliations":[],"preferred":false,"id":831812,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Lewis, Paul E.","contributorId":149198,"corporation":false,"usgs":false,"family":"Lewis","given":"Paul","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":831813,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Irons, James R","contributorId":117742,"corporation":false,"usgs":true,"family":"Irons","given":"James","email":"","middleInitial":"R","affiliations":[],"preferred":false,"id":831810,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dwyer, John L. 0000-0002-8281-0896 dwyer@usgs.gov","orcid":"https://orcid.org/0000-0002-8281-0896","contributorId":3481,"corporation":false,"usgs":true,"family":"Dwyer","given":"John","email":"dwyer@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":831811,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":98323,"text":"ofr20101060 - 2010 - U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center-Fiscal Year 2009 Annual Report","interactions":[],"lastModifiedDate":"2012-02-02T00:14:42","indexId":"ofr20101060","displayToPublicDate":"2010-04-14T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-1060","title":"U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center-Fiscal Year 2009 Annual Report","docAbstract":"The Earth Resources Observation and Science (EROS) Center is a U.S. Geological Survey (USGS) facility focused on providing science and imagery to better understand our Earth. As part of the USGS Geography Discipline, EROS contributes to the Land Remote Sensing (LRS) Program, the Geographic Analysis and Monitoring (GAM) Program, and the National Geospatial Program (NGP), as well as our Federal partners and cooperators. The work of the Center is shaped by the Earth sciences, the missions of our stakeholders, and implemented through strong program and project management and application of state-of-the-art information technologies. Fundamentally, EROS contributes to the understanding of a changing Earth through 'research to operations' activities that include developing, implementing, and operating remote sensing based terrestrial monitoring capabilities needed to address interdisciplinary science and applications objectives at all levels-both nationally and internationally.\r\n\r\nThe Center's programs and projects continually strive to meet and/or exceed the changing needs of the USGS, the Department of the Interior, our Nation, and international constituents. The Center's multidisciplinary staff uses their unique expertise in remote sensing science and technologies to conduct basic and applied research, data acquisition, systems engineering, information access and management, and archive preservation to address the Nation's most critical needs. Of particular note is the role of EROS as the primary provider of Landsat data, the longest comprehensive global land Earth observation record ever collected.\r\n\r\nThis report is intended to provide an overview of the scientific and engineering achievements and illustrate the range and scope of the activities and accomplishments at EROS throughout fiscal year (FY) 2009. Additional information concerning the scientific, engineering, and operational achievements can be obtained from the scientific papers and other documents published by EROS staff.\r\n\r\nWe welcome comments and follow-up questions on any aspect of this Annual Report and invite any of our customers or partners to contact us at their convenience. To communicate with us, or for more information about EROS, contact: Communications and Outreach, USGS EROS Center, 47914 252nd Street, Sioux Falls, South Dakota 57198, jsnelson@usgs.gov, http://eros.usgs.gov/.\r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20101060","usgsCitation":"Nelson, J.S., 2010, U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center-Fiscal Year 2009 Annual Report: U.S. Geological Survey Open-File Report 2010-1060, xv, 83 p. , https://doi.org/10.3133/ofr20101060.","productDescription":"xv, 83 p. ","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":125890,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2010_1060.jpg"},{"id":13572,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2010/1060/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4afbe4b07f02db69624a","contributors":{"authors":[{"text":"Nelson, Janice S. jsnelson@usgs.gov","contributorId":113,"corporation":false,"usgs":true,"family":"Nelson","given":"Janice","email":"jsnelson@usgs.gov","middleInitial":"S.","affiliations":[],"preferred":true,"id":304993,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":98298,"text":"ofr20101055 - 2010 - eMODIS: A User-Friendly Data Source","interactions":[],"lastModifiedDate":"2012-02-02T00:15:02","indexId":"ofr20101055","displayToPublicDate":"2010-03-27T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-1055","title":"eMODIS: A User-Friendly Data Source","docAbstract":"The U.S. Geological Survey's (USGS) Earth Resources Observation and Science (EROS) Center is generating a suite of products called 'eMODIS' based on Moderate Resolution Imaging Spectroradiometer (MODIS) data acquired by the National Aeronautics and Space Administration's (NASA) Earth Observing System (EOS). With a more frequent repeat cycle than Landsat and higher spatial resolutions than the Advanced Very High Resolution Spectroradiometer (AVHRR), MODIS is well suited for vegetation studies. For operational monitoring, however, the benefits of MODIS are counteracted by usability issues with the standard map projection, file format, composite interval, high-latitude 'bow-tie' effects, and production latency. eMODIS responds to a community-specific need for alternatively packaged MODIS data, addressing each of these factors for real-time monitoring and historical trend analysis.\r\n\r\neMODIS processes calibrated radiance data (level-1B) acquired by the MODIS sensors on the EOS Terra and Aqua satellites by combining MODIS Land Science Collection 5 Atmospherically Corrected Surface Reflectance production code and USGS EROS MODIS Direct Broadcast System (DBS) software to create surface reflectance and Normalized Difference Vegetation Index (NDVI) products. eMODIS is produced over the continental United States and over Alaska extending into Canada to cover the Yukon River Basin. The 250-meter (m), 500-m, and 1,000-m products are delivered in Geostationary Earth Orbit Tagged Image File Format (Geo- TIFF) and composited in 7-day intervals. eMODIS composites are projected to non-Sinusoidal mapping grids that best suit the geography in their areas of application (see eMODIS Product Description below).\r\n\r\nFor eMODIS products generated over the continental United States (eMODIS CONUS), the Terra (from 2000) and Aqua (from 2002) records are available and continue through present time. eMODIS CONUS also is generated in an expedited process that delivers a 7-day rolling composite, created daily with the most recent 7 days of acquisition, to users monitoring real-time vegetation conditions. eMODIS Alaska is not part of expedited processing, but does cover the Terra mission life (2000-present). A simple file transfer protocol (FTP) distribution site currently is enabled on the Internet for direct download of eMODIS products (ftp://emodisftp.cr.usgs.gov/eMODIS), with plans to expand into an interactive portal environment.\r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20101055","usgsCitation":"Jenkerson, C.B., Maiersperger, T., and Schmidt, G., 2010, eMODIS: A User-Friendly Data Source: U.S. Geological Survey Open-File Report 2010-1055, viii, 10 p. , https://doi.org/10.3133/ofr20101055.","productDescription":"viii, 10 p. ","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":125442,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2010_1055.jpg"},{"id":13551,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2010/1055/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e477be4b07f02db47fd8f","contributors":{"authors":[{"text":"Jenkerson, Calli B. 0000-0002-3780-9175 jenkerson@usgs.gov","orcid":"https://orcid.org/0000-0002-3780-9175","contributorId":469,"corporation":false,"usgs":true,"family":"Jenkerson","given":"Calli","email":"jenkerson@usgs.gov","middleInitial":"B.","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":304937,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maiersperger, Thomas 0000-0003-3132-6997","orcid":"https://orcid.org/0000-0003-3132-6997","contributorId":16538,"corporation":false,"usgs":true,"family":"Maiersperger","given":"Thomas","affiliations":[],"preferred":false,"id":304938,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmidt, Gail 0000-0002-9684-8158","orcid":"https://orcid.org/0000-0002-9684-8158","contributorId":29086,"corporation":false,"usgs":true,"family":"Schmidt","given":"Gail","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":304939,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":98231,"text":"ofr20101027 - 2010 - Multitemporal L- and C-Band synthetic aperture radar to highlight differences in water status among boreal forest and wetland systems in the Yukon Flats, Interior Alaska","interactions":[],"lastModifiedDate":"2019-06-05T08:06:10","indexId":"ofr20101027","displayToPublicDate":"2010-03-06T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-1027","title":"Multitemporal L- and C-Band synthetic aperture radar to highlight differences in water status among boreal forest and wetland systems in the Yukon Flats, Interior Alaska","docAbstract":"Tracking landscape-scale water status in high-latitude boreal systems is indispensable to understanding the fate of stored and sequestered carbon in a climate change scenario. Spaceborne synthetic aperture radar (SAR) imagery provides critical information for water and moisture status in Alaskan boreal environments at the landscape scale. When combined with results from optical sensor analyses, a complementary picture of vegetation, biomass, and water status emerges. Whereas L-band SAR showed better inherent capacity to map water status, C-band had much more temporal coverage in this study. Analysis through the use of L- and C-band SARs combined with Landsat Enhanced Thematic Mapper Plus (ETM+) enables landscape stratification by vegetation and by seasonal and interannual hydrology. Resultant classifications are highly relevant to biogeochemistry at the landscape scale. These results enhance our understanding of ecosystem processes relevant to carbon balance and may be scaled up to inform regional carbon flux estimates and better parameterize general circulation models (GCMs).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20101027","usgsCitation":"Balser, A.W., and Wylie, B.K., 2010, Multitemporal L- and C-Band synthetic aperture radar to highlight differences in water status among boreal forest and wetland systems in the Yukon Flats, Interior Alaska: U.S. Geological Survey Open-File Report 2010-1027, iv, 21 p. , https://doi.org/10.3133/ofr20101027.","productDescription":"iv, 21 p. ","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":126472,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2010_1027.jpg"},{"id":13492,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2010/1027/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -146.43333333333334,66.18333333333334 ], [ -146.43333333333334,66.38333333333334 ], [ -145.88333333333333,66.38333333333334 ], [ -145.88333333333333,66.18333333333334 ], [ -146.43333333333334,66.18333333333334 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b32e4b07f02db6b48d4","contributors":{"authors":[{"text":"Balser, Andrew W.","contributorId":100965,"corporation":false,"usgs":true,"family":"Balser","given":"Andrew","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":304733,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","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":304732,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70208550,"text":"70208550 - 2010 - Accessing free Landsat data via the Internet: Africa's challenge","interactions":[],"lastModifiedDate":"2020-02-20T10:05:24","indexId":"70208550","displayToPublicDate":"2010-02-23T13:37:50","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3251,"text":"Remote Sensing Letters","active":true,"publicationSubtype":{"id":10}},"title":"Accessing free Landsat data via the Internet: Africa's challenge","docAbstract":"Since January 2008, the US Department of Interior/US Geological Survey has been providing terrain-corrected Landsat data over the Internet for free. This letter reports the size and proportion of the US Landsat archive that is over Africa by each Landsat sensor, discusses the implications of missing data and highlights the current bandwidth constraints on users accessing free Landsat data over the Internet from Africa.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/01431160903486693","usgsCitation":"Roy, D.P., Ju, J., Mbow, Frost, P., and Loveland, T., 2010, Accessing free Landsat data via the Internet: Africa's challenge: Remote Sensing Letters, v. 1, no. 2, p. 111-117, https://doi.org/10.1080/01431160903486693.","productDescription":"7 p.","startPage":"111","endPage":"117","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":475751,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/01431160903486693","text":"Publisher Index Page"},{"id":372363,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Africa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 34.95849609375,\n 29.49698759653577\n ],\n [\n 34.21142578125,\n 31.372399104880525\n ],\n [\n 30.563964843750004,\n 31.970803930433096\n ],\n [\n 21.68701171875,\n 33.37641235124676\n ],\n [\n 11.2939453125,\n 34.07086232376631\n ],\n [\n 11.7333984375,\n 35.94243575255426\n ],\n [\n 11.00830078125,\n 37.47485808497102\n ],\n [\n 8.54736328125,\n 37.42252593456307\n ],\n [\n 3.427734375,\n 37.31775185163688\n ],\n [\n 0.41748046875,\n 36.518465989675875\n ],\n [\n -3.0322265625,\n 35.54116627999815\n ],\n [\n -4.4384765625,\n 35.36665566526249\n ],\n [\n -5.3118896484375,\n 35.951329861522666\n ],\n [\n -6.0150146484375,\n 35.831174956246535\n ],\n [\n -6.448974609375,\n 34.92197103616377\n ],\n [\n -19.335937499999996,\n 32.91648534731439\n ],\n [\n -19.1162109375,\n 28.536274512989916\n ],\n [\n -18.3251953125,\n 20.282808691330054\n ],\n [\n -26.015625,\n 17.18277905643184\n ],\n [\n -24.873046874999996,\n 14.030014548014327\n ],\n [\n -16.5673828125,\n 10.531020008464989\n ],\n [\n -7.5146484375,\n 2.767477951092084\n ],\n [\n 3.8891601562499996,\n 5.200364681183489\n ],\n [\n 6.30615234375,\n -1.537901237431487\n ],\n [\n 12.15087890625,\n -8.18974234438369\n ],\n [\n 12.7001953125,\n -10.984335146101955\n ],\n [\n 10.0634765625,\n -17.35063837604883\n ],\n [\n 13.403320312499998,\n -22.228090416784486\n ],\n [\n 14.589843749999998,\n -27.80020993741824\n ],\n [\n 17.578125,\n -32.36140331527542\n ],\n [\n 17.885742187499996,\n -34.488447837809304\n ],\n [\n 19.86328125,\n -35.31736632923786\n ],\n [\n 26.9384765625,\n -34.27083595164999\n ],\n [\n 33.662109375,\n -28.110748760633534\n ],\n [\n 54.5361328125,\n -24.287026865376422\n ],\n [\n 59.67773437500001,\n -19.973348786110602\n ],\n [\n 57.216796875,\n -2.5479878714713835\n ],\n [\n 51.2841796875,\n 8.146242825034385\n ],\n [\n 51.8994140625,\n 12.425847783029134\n ],\n [\n 44.0771484375,\n 11.781325296112277\n ],\n [\n 40.2099609375,\n 18.312810846425442\n ],\n [\n 34.365234375,\n 28.34306490482549\n ],\n [\n 34.95849609375,\n 29.49698759653577\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"1","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Roy, David P.","contributorId":71083,"corporation":false,"usgs":true,"family":"Roy","given":"David","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":782397,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ju, Junchang","contributorId":222521,"corporation":false,"usgs":false,"family":"Ju","given":"Junchang","email":"","affiliations":[],"preferred":false,"id":782398,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mbow","contributorId":198826,"corporation":false,"usgs":false,"family":"Mbow","email":"","affiliations":[],"preferred":false,"id":782399,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frost, Philip","contributorId":222523,"corporation":false,"usgs":false,"family":"Frost","given":"Philip","email":"","affiliations":[],"preferred":false,"id":782400,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loveland, Thomas 0000-0003-3114-6646 loveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":140611,"corporation":false,"usgs":true,"family":"Loveland","given":"Thomas","email":"loveland@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":782401,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70118898,"text":"70118898 - 2010 - Modeling the human invader in the United States","interactions":[],"lastModifiedDate":"2017-04-06T12:02:16","indexId":"70118898","displayToPublicDate":"2010-02-08T08:53:54","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2172,"text":"Journal of Applied Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the human invader in the United States","docAbstract":"Modern biogeographers recognize that humans are seen as constituents of ecosystems, drivers of significant change, and perhaps, the most invasive species on earth. We found it instructive to model humans as invasive organisms with the same environmental factors. We present a preliminary model of the spread of modern humans in the conterminous United States between 1992 and 2001 based on a subset of National Land Cover Data (NLCD), a time series LANDSAT product. We relied on the commonly used Maxent model, a species-environmental matching model, to map urbanization. Results: Urban areas represented 5.1% of the lower 48 states in 2001, an increase of 7.5% (18,112 km2) in the nine year period. At this rate, an area the size of Massachusetts is converted to urban land use every ten years. We used accepted models commonly used for mapping plant and animal distributions and found that climatic and environmental factors can strongly predict our spread (i.e., the conversion of forests, shrub/grass, and wetland areas into urban areas), with a 92.5% success rate (Area Under the Curve). Adding a roads layer in the model improved predictions to a 95.5% success rate. 8.8% of the 1-km2> cells in the conterminous U.S. now have a major road in them. In 2001, 0.8% of 1-km2 > cells in the U.S. had an urbanness value of > 800, (>89% of a 1-km2> cell is urban), while we predict that 24.5% of 1-km2> cells in the conterminous U.S. will be > 800 eventually. Main conclusion: Humans have a highly predictable pattern of urbanization based on climatic and topographic variables. Conservation strategies may benefit from that predictability.","language":"English","publisher":"Society of Photo-optical Instrumentation Engineers","publisherLocation":"Bellingham, WA","doi":"10.1117/1.3357386","usgsCitation":"Stohlgren, T.J., Jarnevich, C.S., and Giri, C.P., 2010, Modeling the human invader in the United States: Journal of Applied Remote Sensing, v. 4, no. 1, Article 043509, https://doi.org/10.1117/1.3357386.","productDescription":"Article 043509","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":291443,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":291442,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1117/1.3357386"}],"volume":"4","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53db5846e4b0fba533fa358f","contributors":{"authors":[{"text":"Stohlgren, Thomas J. 0000-0001-9696-4450 stohlgrent@usgs.gov","orcid":"https://orcid.org/0000-0001-9696-4450","contributorId":2902,"corporation":false,"usgs":true,"family":"Stohlgren","given":"Thomas","email":"stohlgrent@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":497361,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":497362,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Giri, Chandra P.","contributorId":57379,"corporation":false,"usgs":true,"family":"Giri","given":"Chandra","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":497363,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":98153,"text":"sim3101 - 2010 - Landsat Thematic Mapper Image Mosaic of Colorado","interactions":[],"lastModifiedDate":"2012-02-10T00:11:51","indexId":"sim3101","displayToPublicDate":"2010-01-27T00:00:00","publicationYear":"2010","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":"3101","title":"Landsat Thematic Mapper Image Mosaic of Colorado","docAbstract":"The U.S. Geological Survey (USGS) Rocky Mountain Geographic Science Center (RMGSC) produced a seamless, cloud-minimized remotely-sensed image spanning the State of Colorado. Multiple orthorectified Landsat 5 Thematic Mapper (TM) scenes collected during 2006-2008 were spectrally normalized via reflectance transformation and linear regression based upon pseudo-invariant features (PIFS) following the removal of clouds. Individual Landsat scenes were then mosaicked to form a six-band image composite spanning the visible to shortwave infrared spectrum. This image mosaic, presented here, will also be used to create a conifer health classification for Colorado in Scientific Investigations Map 3103. \r\n\r\nAn archive of past and current Landsat imagery exists and is available to the scientific community (http://glovis.usgs.gov/), but significant pre-processing was required to produce a statewide mosaic from this information. Much of the data contained perennial cloud cover that complicated analysis and classification efforts. Existing Landsat mosaic products, typically three band image composites, did not include the full suite of multispectral information necessary to produce this assessment, and were derived using data collected in 2001 or earlier.\r\n\r\nA six-band image mosaic covering Colorado was produced. This mosaic includes blue (band 1), green (band 2), red (band 3), near infrared (band 4), and shortwave infrared information (bands 5 and 7). The image composite shown here displays three of the Landsat bands (7, 4, and 2), which are sensitive to the shortwave infrared, near infrared, and green ranges of the electromagnetic spectrum. Vegetation appears green in this image, while water looks black, and unforested areas appear pink. \r\n\r\nThe lines that may be visible in the on-screen version of the PDF are an artifact of the export methods used to create this file. The file should be viewed at 150 percent zoom or greater for optimum viewing.\r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sim3101","isbn":"978 1 4113 2635 4","usgsCitation":"Cole, C.J., Noble, S.M., Blauer, S.L., Friesen, B.A., and Bauer, M., 2010, Landsat Thematic Mapper Image Mosaic of Colorado: U.S. Geological Survey Scientific Investigations Map 3101, 1 map (46 x 36 inches); downloads directory, https://doi.org/10.3133/sim3101.","productDescription":"1 map (46 x 36 inches); downloads directory","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2006-01-01","temporalEnd":"2008-12-31","costCenters":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"links":[{"id":125811,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3101.jpg"},{"id":13396,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3101/","linkFileType":{"id":5,"text":"html"}}],"scale":"1","projection":"Albers Conical Equal Area Projection","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109,37 ], [ -109,41 ], [ -102,41 ], [ -102,37 ], [ -109,37 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b20e4b07f02db6abbd6","contributors":{"authors":[{"text":"Cole, Christopher J. cjcole@usgs.gov","contributorId":2163,"corporation":false,"usgs":true,"family":"Cole","given":"Christopher","email":"cjcole@usgs.gov","middleInitial":"J.","affiliations":[{"id":573,"text":"Special Applications Science Center","active":true,"usgs":true}],"preferred":true,"id":304466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noble, Suzanne M. smnoble@usgs.gov","contributorId":3400,"corporation":false,"usgs":true,"family":"Noble","given":"Suzanne","email":"smnoble@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":304468,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blauer, Steven L.","contributorId":23644,"corporation":false,"usgs":true,"family":"Blauer","given":"Steven","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":304469,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Friesen, Beverly A. bafriesen@usgs.gov","contributorId":3216,"corporation":false,"usgs":true,"family":"Friesen","given":"Beverly","email":"bafriesen@usgs.gov","middleInitial":"A.","affiliations":[{"id":573,"text":"Special Applications Science Center","active":true,"usgs":true}],"preferred":true,"id":304467,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bauer, Mark A. mabauer@usgs.gov","contributorId":1409,"corporation":false,"usgs":true,"family":"Bauer","given":"Mark A.","email":"mabauer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":304465,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":98117,"text":"sim3104 - 2010 - Mineral and Vegetation Maps of the Bodie Hills, Sweetwater Mountains, and Wassuk Range, California/Nevada, Generated from ASTER Satellite Data","interactions":[],"lastModifiedDate":"2012-02-10T00:11:53","indexId":"sim3104","displayToPublicDate":"2010-01-16T00:00:00","publicationYear":"2010","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":"3104","title":"Mineral and Vegetation Maps of the Bodie Hills, Sweetwater Mountains, and Wassuk Range, California/Nevada, Generated from ASTER Satellite Data","docAbstract":"Multispectral remote sensing data acquired by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were analyzed to identify and map minerals, vegetation groups, and volatiles (water and snow) in support of geologic studies of the Bodie Hills, Sweetwater Mountains, and Wassuk Range, California/Nevada. Digital mineral and vegetation mapping results are presented in both portable document format (PDF) and ERDAS Imagine format (.img). The ERDAS-format files are suitable for integration with other geospatial data in Geographic Information Systems (GIS) such as ArcGIS. The ERDAS files showing occurrence of 1) iron-bearing minerals, vegetation, and water, and 2) clay, sulfate, mica, carbonate, Mg-OH, and hydrous quartz minerals have been attributed according to identified material, so that the material detected in a pixel can be queried with the interactive attribute identification tools of GIS and image processing software packages (for example, the Identify Tool of ArcMap and the Inquire Cursor Tool of ERDAS Imagine). \r\n\r\nAll raster data have been orthorectified to the Universal Transverse Mercator (UTM) projection using a projective transform with ground-control points selected from orthorectified Landsat Thematic Mapper data and a digital elevation model from the U.S. Geological Survey (USGS) National Elevation Dataset (1/3 arc second, 10 m resolution).\r\n\r\nMetadata compliant with Federal Geographic Data Committee (FGDC) standards for all ERDAS-format files have been included, and contain important information regarding geographic coordinate systems, attributes, and cross-references. Documentation regarding spectral analysis methodologies employed to make the maps is included in these cross-references.\r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sim3104","usgsCitation":"Rockwell, B.W., 2010, Mineral and Vegetation Maps of the Bodie Hills, Sweetwater Mountains, and Wassuk Range, California/Nevada, Generated from ASTER Satellite Data (Version 1.0): U.S. Geological Survey Scientific Investigations Map 3104, Pamphlet: iii, 5 p.; 4 Sheets (each 48 x 36 inches); Downloads Directory, https://doi.org/10.3133/sim3104.","productDescription":"Pamphlet: iii, 5 p.; 4 Sheets (each 48 x 36 inches); Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2000-08-12","temporalEnd":"2004-06-20","costCenters":[{"id":177,"text":"Central Region Mineral Resources Science Center","active":false,"usgs":true}],"links":[{"id":125625,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3104.jpg"},{"id":13357,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3104/","linkFileType":{"id":5,"text":"html"}}],"scale":"62000","projection":"Universal Transverse Mercator","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.41666666666667,38.083333333333336 ], [ -119.41666666666667,38.5 ], [ -118.5,38.5 ], [ -118.5,38.083333333333336 ], [ -119.41666666666667,38.083333333333336 ] ] ] } } ] }","edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a61e4b07f02db6357f3","contributors":{"authors":[{"text":"Rockwell, Barnaby W. 0000-0002-9549-0617 barnabyr@usgs.gov","orcid":"https://orcid.org/0000-0002-9549-0617","contributorId":2195,"corporation":false,"usgs":true,"family":"Rockwell","given":"Barnaby","email":"barnabyr@usgs.gov","middleInitial":"W.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":304220,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70256009,"text":"70256009 - 2010 - Establishing a nationwide baseline of historical burn-severity data to support monitoring of trends in wildfire effects and national fire policies","interactions":[],"lastModifiedDate":"2024-07-12T15:07:23.549738","indexId":"70256009","displayToPublicDate":"2010-01-01T10:05:16","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":32,"text":"General Technical Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"PNW-GTR-802","title":"Establishing a nationwide baseline of historical burn-severity data to support monitoring of trends in wildfire effects and national fire policies","docAbstract":"There is a need to provide agency leaders, elected officials, and the general public with summary information regarding the effects of large wildfires. Recently, the Wildland Fire Leadership Council (WFLC), which implements and coordinates National Fire Plan (NFP) and Federal Wildland Fire Management Policies adopted a strategy to monitor the effectiveness and effects of the National Fire Plan and the Healthy Forests Restoration Act. 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 6-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/EROS Data Center and USDA-FS/ Remote Sensing Applications Center will map burn severity of all fires occurring from 1984 to 2010. Only fires that are greater than 500 ac in the East, and 1,000 ac in the West will be included. We anticipate mapping a total of more than 9,000 historical fires and fires that occur during the course of the study. 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. For example, fire severity data along with associated biophysical characteristics provide an analytical basis for assessing risk from invasive species as well as native insects and pathogens. All data and results will be distributed to the public via a Web interface.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Advances in threat assessment and their application to forest and rangeland management","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","publisher":"U.S. Department of Agriculture, Forest Service","usgsCitation":"Schwind, B., Quayle, B., and Eidenshink, J.C., 2010, Establishing a nationwide baseline of historical burn-severity data to support monitoring of trends in wildfire effects and national fire policies: General Technical Report PNW-GTR-802, 16 p.","productDescription":"16 p.","startPage":"381","endPage":"396","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":431011,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":431010,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://research.fs.usda.gov/treesearch/37081","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schwind, Brian","contributorId":146378,"corporation":false,"usgs":false,"family":"Schwind","given":"Brian","email":"","affiliations":[],"preferred":false,"id":906364,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quayle, Brad","contributorId":146381,"corporation":false,"usgs":false,"family":"Quayle","given":"Brad","email":"","affiliations":[],"preferred":false,"id":906365,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":906366,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70046634,"text":"ds587D - 2010 - National Land Cover Database 2001 (NLCD01) Imperviousness Layer Tile 4, Southeast United States: IMPV01_4","interactions":[],"lastModifiedDate":"2013-06-17T15:53:12","indexId":"ds587D","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"587","chapter":"D","title":"National Land Cover Database 2001 (NLCD01) Imperviousness Layer Tile 4, Southeast United States: IMPV01_4","docAbstract":"This 30-meter resolution data set represents the imperviousness layer for the conterminous United States for the 2001 time period. The data have been arranged into four tiles to facilitate timely display and manipulation within a Geographic Information System, browse graphic: nlcd01-partition. The National Land Cover Data Set for 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of Federal agencies (www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (USEPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM), and the USDA Natural Resources Conservation Service (NRCS). One of the primary goals of the project is to generate a current, consistent, seamless, and accurate National Land Cover Database (NLCD) circa 2001 for the United States at medium spatial resolution. For a detailed definition and discussion on MRLC and the NLCD 2001 products, refer to Homer and others (2004) and http://www.mrlc.gov/mrlc2k.asp.. The NLCD 2001 was created by partitioning the United States into mapping-zones. A total of 68 mapping-zones browse graphic: nlcd01-mappingzones.jpg were delineated within the conterminous United States based on ecoregion and geographical characteristics, edge-matching features, and the size requirement of Landsat mosaics. Mapping-zones encompass the whole or parts of several states. Questions about the NLCD mapping zones can be directed to the NLCD 2001 Land Cover Mapping Team at the USGS/EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds587D","usgsCitation":"Wieczorek, M., and LaMotte, A.E., 2010, National Land Cover Database 2001 (NLCD01) Imperviousness Layer Tile 4, Southeast United States: IMPV01_4 (Version 1): U.S. Geological Survey Data Series 587, Dataset, https://doi.org/10.3133/ds587D.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":273863,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":273861,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/impv01_4.xml"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -98.182478,22.983872 ], [ -98.182478,39.892971 ], [ -69.947056,39.892971 ], [ -69.947056,22.983872 ], [ -98.182478,22.983872 ] ] ] } } ] }","edition":"Version 1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51c02ff3e4b0ee1529ed3d2c","contributors":{"authors":[{"text":"Wieczorek, Michael mewieczo@usgs.gov","contributorId":2309,"corporation":false,"usgs":true,"family":"Wieczorek","given":"Michael","email":"mewieczo@usgs.gov","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":false,"id":479910,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LaMotte, Andrew E. 0000-0002-1434-6518 alamotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1434-6518","contributorId":2842,"corporation":false,"usgs":true,"family":"LaMotte","given":"Andrew","email":"alamotte@usgs.gov","middleInitial":"E.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":479911,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70046633,"text":"ds587C - 2010 - National Land Cover Database 2001 (NLCD01) Imperviousness Layer Tile 3, Southwest United States: IMPV01_3","interactions":[],"lastModifiedDate":"2013-06-17T15:45:18","indexId":"ds587C","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"587","chapter":"C","title":"National Land Cover Database 2001 (NLCD01) Imperviousness Layer Tile 3, Southwest United States: IMPV01_3","docAbstract":"This 30-meter resolution data set represents the imperviousness layer for the conterminous United States for the 2001 time period. The data have been arranged into four tiles to facilitate timely display and manipulation within a Geographic Information System, browse graphic: nlcd01-partition. The National Land Cover Data Set for 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of Federal agencies (www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (USEPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM), and the USDA Natural Resources Conservation Service (NRCS). One of the primary goals of the project is to generate a current, consistent, seamless, and accurate National Land Cover Database (NLCD) circa 2001 for the United States at medium spatial resolution. For a detailed definition and discussion on MRLC and the NLCD 2001 products, refer to Homer and others (2004) and http://www.mrlc.gov/mrlc2k.asp.. The NLCD 2001 was created by partitioning the United States into mapping-zones. A total of 68 mapping-zones browse graphic: nlcd01-mappingzones.jpg were delineated within the conterminous United States based on ecoregion and geographical characteristics, edge-matching features, and the size requirement of Landsat mosaics. Mapping-zones encompass the whole or parts of several states. 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The data have been arranged into four tiles to facilitate timely display and manipulation within a Geographic Information System, browse graphic: nlcd01-partition.jpg. The National Land Cover Data Set for 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of Federal agencies (www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (USEPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM), and the USDA Natural Resources Conservation Service (NRCS). One of the primary goals of the project is to generate a current, consistent, seamless, and accurate National Land Cover Database (NLCD) circa 2001 for the United States at medium spatial resolution. For a detailed definition and discussion on MRLC and the NLCD 2001 products, refer to Homer and others (2004) and http://www.mrlc.gov/mrlc2k.asp. The NLCD 2001 was created by partitioning the United States into mapping-zones. A total of 68 mapping-zones browse graphic: nlcd01-mappingzones.jpg were delineated within the conterminous United States based on ecoregion and geographical characteristics, edge-matching features, and the size requirement of Landsat mosaics. Mapping-zones encompass the whole or parts of several states. Questions about the NLCD mapping zones can be directed to the NLCD 2001 Land Cover Mapping Team at the USGS/EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/70046118","usgsCitation":"LaMotte, A.E., and Wieczorek, M., 2010, National Land Cover Database 2001 (NLCD01) Tree Canopy Layer Tile 1, Northwest United States: CNPY01_1, Dataset, https://doi.org/10.3133/70046118.","productDescription":"Dataset","costCenters":[],"links":[{"id":272848,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":272847,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/cnpy01_1.xml"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -128.307900,36.820901 ], [ -128.307900,51.834455 ], [ -98.182478,51.834455 ], [ -98.182478,36.820901 ], [ -128.307900,36.820901 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a5d1ece4b0605bc571efe4","contributors":{"authors":[{"text":"LaMotte, Andrew E. 0000-0002-1434-6518 alamotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1434-6518","contributorId":2842,"corporation":false,"usgs":true,"family":"LaMotte","given":"Andrew","email":"alamotte@usgs.gov","middleInitial":"E.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478959,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wieczorek, Michael mewieczo@usgs.gov","contributorId":2309,"corporation":false,"usgs":true,"family":"Wieczorek","given":"Michael","email":"mewieczo@usgs.gov","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":false,"id":478958,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70043220,"text":"70043220 - 2010 - Using the Sonoran and Libyan Desert test sites to monitor the temporal stability of reflective solar bands for Landsat 7 enhanced thematic mapper plus and Terra moderate resolution imaging spectroradiometer sensors","interactions":[],"lastModifiedDate":"2013-05-15T12:29:32","indexId":"70043220","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2172,"text":"Journal of Applied Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Using the Sonoran and Libyan Desert test sites to monitor the temporal stability of reflective solar bands for Landsat 7 enhanced thematic mapper plus and Terra moderate resolution imaging spectroradiometer sensors","docAbstract":"Remote sensing imagery is effective for monitoring environmental and climatic changes because of the extent of the global coverage and long time scale of the observations. Radiometric calibration of remote sensing sensors is essential for quantitative & qualitative science and applications. Pseudo-invariant ground targets have been extensively used to monitor the long-term radiometric calibration stability of remote sensing sensors. This paper focuses on the use of the Sonoran Desert site to monitor the radiometric stability of the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. The results are compared with the widely used Libya 4 Desert site in an attempt to evaluate the suitability of the Sonoran Desert site for sensor inter-comparison and calibration stability monitoring. Since the overpass times of ETM+ and MODIS differ by about 30 minutes, the impacts due to different view geometries or test site Bi-directional Reflectance Distribution Function (BRDF) are also presented. In general, the long-term drifts in the visible bands are relatively large compared to the drift in the near-infrared bands of both sensors. The lifetime Top-of-Atmosphere (TOA) reflectance trends from both sensors over 10 years are extremely stable, changing by no more than 0.1% per year (except ETM+ Band 1 and MODIS Band 3) over the two sites used for the study. The use of a semi-empirical BRDF model can reduce the impacts due to view geometries, thus enabling a better estimate of sensor temporal drifts.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Applied Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"SPIE Digital Library","doi":"10.1117/1.3424910","usgsCitation":"Angal, A., Xiong, X., Choi, T., Chander, G., and Wu, A., 2010, Using the Sonoran and Libyan Desert test sites to monitor the temporal stability of reflective solar bands for Landsat 7 enhanced thematic mapper plus and Terra moderate resolution imaging spectroradiometer sensors: Journal of Applied Remote Sensing, v. 4, no. 1, 043525, https://doi.org/10.1117/1.3424910.","productDescription":"043525","ipdsId":"IP-016646","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":272293,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272292,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1117/1.3424910"}],"country":"United States","volume":"4","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51955850e4b0a933d82c4ccf","contributors":{"authors":[{"text":"Angal, Amit","contributorId":67394,"corporation":false,"usgs":true,"family":"Angal","given":"Amit","email":"","affiliations":[],"preferred":false,"id":473192,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Xiong, Xiaoxiong","contributorId":15088,"corporation":false,"usgs":true,"family":"Xiong","given":"Xiaoxiong","email":"","affiliations":[],"preferred":false,"id":473190,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Choi, Tae-young","contributorId":89036,"corporation":false,"usgs":true,"family":"Choi","given":"Tae-young","affiliations":[],"preferred":false,"id":473193,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chander, Gyanesh gchander@usgs.gov","contributorId":3013,"corporation":false,"usgs":true,"family":"Chander","given":"Gyanesh","email":"gchander@usgs.gov","affiliations":[],"preferred":true,"id":473189,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wu, Aisheng","contributorId":65362,"corporation":false,"usgs":true,"family":"Wu","given":"Aisheng","email":"","affiliations":[],"preferred":false,"id":473191,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70037546,"text":"70037546 - 2010 - Radiometric, geometric, and image quality assessment of ALOS AVNIR-2 and PRISM sensors","interactions":[],"lastModifiedDate":"2017-04-06T11:58:50","indexId":"70037546","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1944,"text":"IEEE Transactions on Geoscience and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Radiometric, geometric, and image quality assessment of ALOS AVNIR-2 and PRISM sensors","docAbstract":"The Advanced Land Observing Satellite (ALOS) was launched on January 24, 2006, by a Japan Aerospace Exploration Agency (JAXA) H-IIA launcher. It carries three remote-sensing sensors: 1) the Advanced Visible and Near-Infrared Radiometer type 2 (AVNIR-2); 2) the Panchromatic Remote-Sensing Instrument for Stereo Mapping (PRISM); and 3) the Phased-Array type L-band Synthetic Aperture Radar (PALSAR). Within the framework of ALOS Data European Node, as part of the European Space Agency (ESA), the European Space Research Institute worked alongside JAXA to provide contributions to the ALOS commissioning phase plan. This paper summarizes the strategy that was adopted by ESA to define and implement a data verification plan for missions operated by external agencies; these missions are classified by the ESA as third-party missions. The ESA was supported in the design and execution of this plan by GAEL Consultant. The verification of ALOS optical data from PRISM and AVNIR-2 sensors was initiated 4 months after satellite launch, and a team of principal investigators assembled to provide technical expertise. This paper includes a description of the verification plan and summarizes the methodologies that were used for radiometric, geometric, and image quality assessment. The successful completion of the commissioning phase has led to the sensors being declared fit for operations. The consolidated measurements indicate that the radiometric calibration of the AVNIR-2 sensor is stable and agrees with the Landsat-7 Enhanced Thematic Mapper Plus and the Envisat MEdium-Resolution Imaging Spectrometer calibration. The geometrical accuracy of PRISM and AVNIR-2 products improved significantly and remains under control. The PRISM modulation transfer function is monitored for improved characterization.
","language":"English","publisher":"IEEE","doi":"10.1109/TGRS.2010.2048714","issn":"01962892","usgsCitation":"Saunier, S., Goryl, P., Chander, G., Santer, R., Bouvet, M., Collet, B., Mambimba, A., and Kocaman, A.S., 2010, Radiometric, geometric, and image quality assessment of ALOS AVNIR-2 and PRISM sensors: IEEE Transactions on Geoscience and Remote Sensing, v. 48, no. 10, p. 3855-3866, https://doi.org/10.1109/TGRS.2010.2048714.","productDescription":"12 p.","startPage":"3855","endPage":"3866","numberOfPages":"12","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":246080,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":218098,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1109/TGRS.2010.2048714"}],"volume":"48","issue":"10","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a9418e4b0c8380cd811d8","contributors":{"authors":[{"text":"Saunier, S.","contributorId":96914,"corporation":false,"usgs":true,"family":"Saunier","given":"S.","email":"","affiliations":[],"preferred":false,"id":461550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goryl, P.","contributorId":58484,"corporation":false,"usgs":true,"family":"Goryl","given":"P.","email":"","affiliations":[],"preferred":false,"id":461547,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chander, G.","contributorId":51449,"corporation":false,"usgs":true,"family":"Chander","given":"G.","affiliations":[],"preferred":false,"id":461546,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Santer, R.","contributorId":9884,"corporation":false,"usgs":true,"family":"Santer","given":"R.","email":"","affiliations":[],"preferred":false,"id":461543,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bouvet, M.","contributorId":25375,"corporation":false,"usgs":true,"family":"Bouvet","given":"M.","email":"","affiliations":[],"preferred":false,"id":461544,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Collet, B.","contributorId":95731,"corporation":false,"usgs":true,"family":"Collet","given":"B.","email":"","affiliations":[],"preferred":false,"id":461549,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mambimba, A.","contributorId":26172,"corporation":false,"usgs":true,"family":"Mambimba","given":"A.","email":"","affiliations":[],"preferred":false,"id":461545,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kocaman, Aksakal S.","contributorId":89757,"corporation":false,"usgs":true,"family":"Kocaman","given":"Aksakal","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":461548,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70037467,"text":"70037467 - 2010 - A comparison of multi-spectral, multi-angular, and multi-temporal remote sensing datasets for fractional shrub canopy mapping in Arctic Alaska","interactions":[],"lastModifiedDate":"2012-03-12T17:22:10","indexId":"70037467","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"A comparison of multi-spectral, multi-angular, and multi-temporal remote sensing datasets for fractional shrub canopy mapping in Arctic Alaska","docAbstract":"Shrub cover appears to be increasing across many areas of the Arctic tundra biome, and increasing shrub cover in the Arctic has the potential to significantly impact global carbon budgets and the global climate system. For most of the Arctic, however, there is no existing baseline inventory of shrub canopy cover, as existing maps of Arctic vegetation provide little information about the density of shrub cover at a moderate spatial resolution across the region. Remotely-sensed fractional shrub canopy maps can provide this necessary baseline inventory of shrub cover. In this study, we compare the accuracy of fractional shrub canopy (> 0.5 m tall) maps derived from multi-spectral, multi-angular, and multi-temporal datasets from Landsat imagery at 30 m spatial resolution, Moderate Resolution Imaging SpectroRadiometer (MODIS) imagery at 250 m and 500 m spatial resolution, and MultiAngle Imaging Spectroradiometer (MISR) imagery at 275 m spatial resolution for a 1067 km2 study area in Arctic Alaska. The study area is centered at 69 ??N, ranges in elevation from 130 to 770 m, is composed primarily of rolling topography with gentle slopes less than 10??, and is free of glaciers and perennial snow cover. Shrubs > 0.5 m in height cover 2.9% of the study area and are primarily confined to patches associated with specific landscape features. Reference fractional shrub canopy is determined from in situ shrub canopy measurements and a high spatial resolution IKONOS image swath. Regression tree models are constructed to estimate fractional canopy cover at 250 m using different combinations of input data from Landsat, MODIS, and MISR. Results indicate that multi-spectral data provide substantially more accurate estimates of fractional shrub canopy cover than multi-angular or multi-temporal data. Higher spatial resolution datasets also provide more accurate estimates of fractional shrub canopy cover (aggregated to moderate spatial resolutions) than lower spatial resolution datasets, an expected result for a study area where most shrub cover is concentrated in narrow patches associated with rivers, drainages, and slopes. Including the middle infrared bands available from Landsat and MODIS in the regression tree models (in addition to the four standard visible and near-infrared spectral bands) typically results in a slight boost in accuracy. Including the multi-angular red band data available from MISR in the regression tree models, however, typically boosts accuracy more substantially, resulting in moderate resolution fractional shrub canopy estimates approaching the accuracy of estimates derived from the much higher spatial resolution Landsat sensor. Given the poor availability of snow and cloud-free Landsat scenes in many areas of the Arctic and the promising results demonstrated here by the MISR sensor, MISR may be the best choice for large area fractional shrub canopy mapping in the Alaskan Arctic for the period 2000-2009.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Remote Sensing of Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1016/j.rse.2010.01.012","issn":"00344257","usgsCitation":"Selkowitz, D., 2010, A comparison of multi-spectral, multi-angular, and multi-temporal remote sensing datasets for fractional shrub canopy mapping in Arctic Alaska: Remote Sensing of Environment, v. 114, no. 7, p. 1338-1352, https://doi.org/10.1016/j.rse.2010.01.012.","startPage":"1338","endPage":"1352","numberOfPages":"15","costCenters":[],"links":[{"id":217035,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2010.01.012"},{"id":244946,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"114","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059e36fe4b0c8380cd45ff9","contributors":{"authors":[{"text":"Selkowitz, D.J.","contributorId":82886,"corporation":false,"usgs":true,"family":"Selkowitz","given":"D.J.","affiliations":[],"preferred":false,"id":461205,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70037446,"text":"70037446 - 2010 - Use of land surface remotely sensed satellite and airborne data for environmental exposure assessment in cancer research","interactions":[],"lastModifiedDate":"2017-04-05T16:42:19","indexId":"70037446","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2282,"text":"Journal of Exposure Science and Environmental Epidemiology","active":true,"publicationSubtype":{"id":10}},"title":"Use of land surface remotely sensed satellite and airborne data for environmental exposure assessment in cancer research","docAbstract":"In recent years, geographic information systems (GIS) have increasingly been used for reconstructing individual-level exposures to environmental contaminants in epidemiological research. Remotely sensed data can be useful in creating space-time models of environmental measures. The primary advantage of using remotely sensed data is that it allows for study at the local scale (e.g., residential level) without requiring expensive, time-consuming monitoring campaigns. The purpose of our study was to identify how land surface remotely sensed data are currently being used to study the relationship between cancer and environmental contaminants, focusing primarily on agricultural chemical exposure assessment applications. We present the results of a comprehensive literature review of epidemiological research where remotely sensed imagery or land cover maps derived from remotely sensed imagery were applied. We also discuss the strengths and limitations of the most commonly used imagery data (aerial photographs and Landsat satellite imagery) and land cover maps.
","language":"English","publisher":"Nature","doi":"10.1038/jes.2009.7","issn":"15590631","usgsCitation":"Maxwell, S., Meliker, J., and Goovaerts, P., 2010, Use of land surface remotely sensed satellite and airborne data for environmental exposure assessment in cancer research: Journal of Exposure Science and Environmental Epidemiology, v. 20, no. 2, p. 176-185, https://doi.org/10.1038/jes.2009.7.","productDescription":"10 p.","startPage":"176","endPage":"185","numberOfPages":"10","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":475977,"rank":10000,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1038/jes.2009.7","text":"External Repository"},{"id":245328,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":217383,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1038/jes.2009.7"}],"volume":"20","issue":"2","noUsgsAuthors":false,"publicationDate":"2009-02-25","publicationStatus":"PW","scienceBaseUri":"505bbf35e4b08c986b329a0a","contributors":{"authors":[{"text":"Maxwell, S.K.","contributorId":36665,"corporation":false,"usgs":true,"family":"Maxwell","given":"S.K.","email":"","affiliations":[],"preferred":false,"id":461097,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meliker, J.R.","contributorId":56456,"corporation":false,"usgs":true,"family":"Meliker","given":"J.R.","email":"","affiliations":[],"preferred":false,"id":461098,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goovaerts, P.","contributorId":76973,"corporation":false,"usgs":true,"family":"Goovaerts","given":"P.","email":"","affiliations":[],"preferred":false,"id":461099,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70037231,"text":"70037231 - 2010 - Updating the 2001 National Land Cover Database Impervious Surface Products to 2006 using Landsat imagery change detection methods","interactions":[],"lastModifiedDate":"2018-03-08T13:02:07","indexId":"70037231","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Updating the 2001 National Land Cover Database Impervious Surface Products to 2006 using Landsat imagery change detection methods","docAbstract":"A prototype method was developed to update the U.S. Geological Survey (USGS) National Land Cover Database (NLCD) 2001 to a nominal date of 2006. NLCD 2001 is widely used as a baseline for national land cover and impervious cover conditions. To enable the updating of this database in an optimal manner, methods are designed to be accomplished by individual Landsat scene. Using conservative change thresholds based on land cover classes, areas of change and no-change were segregated from change vectors calculated from normalized Landsat scenes from 2001 and 2006. By sampling from NLCD 2001 impervious surface in unchanged areas, impervious surface predictions were estimated for changed areas within an urban extent defined by a companion land cover classification. Methods were developed and tested for national application across six study sites containing a variety of urban impervious surface. Results show the vast majority of impervious surface change associated with urban development was captured, with overall RMSE from 6.86 to 13.12% for these areas. Changes of urban development density were also evaluated by characterizing the categories of change by percentile for impervious surface. This prototype method provides a relatively low cost, flexible approach to generate updated impervious surface using NLCD 2001 as the baseline.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2010.02.018","issn":"00344257","usgsCitation":"Xian, G., and Homer, C.G., 2010, Updating the 2001 National Land Cover Database Impervious Surface Products to 2006 using Landsat imagery change detection methods: Remote Sensing of Environment, v. 114, no. 8, p. 1676-1686, https://doi.org/10.1016/j.rse.2010.02.018.","productDescription":"11 p.","startPage":"1676","endPage":"1686","numberOfPages":"11","ipdsId":"IP-016198","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":245347,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":217401,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2010.02.018"}],"volume":"114","issue":"8","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bbd1ee4b08c986b328ed4","contributors":{"authors":[{"text":"Xian, George 0000-0001-5674-2204","orcid":"https://orcid.org/0000-0001-5674-2204","contributorId":76589,"corporation":false,"usgs":true,"family":"Xian","given":"George","affiliations":[],"preferred":false,"id":459986,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Homer, Collin G. 0000-0003-4755-8135 homer@usgs.gov","orcid":"https://orcid.org/0000-0003-4755-8135","contributorId":2262,"corporation":false,"usgs":true,"family":"Homer","given":"Collin","email":"homer@usgs.gov","middleInitial":"G.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":459985,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70037029,"text":"70037029 - 2010 - Monitoring on-orbit calibration stability of the Terra MODIS and Landsat 7 ETM+ sensors using pseudo-invariant test sites","interactions":[],"lastModifiedDate":"2017-04-05T14:15:43","indexId":"70037029","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring on-orbit calibration stability of the Terra MODIS and Landsat 7 ETM+ sensors using pseudo-invariant test sites","docAbstract":"The ability to detect and quantify changes in the Earth's environment depends on sensors that can provide calibrated, consistent measurements of the Earth's surface features through time. A critical step in this process is to put image data from different sensors onto a common radiometric scale. This work focuses on monitoring the long-term on-orbit calibration stability of the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) sensors using the Committee on Earth Observation Satellites (CEOS) reference standard pseudo-invariant test sites (Libya 4, Mauritania 1/2, Algeria 3, Libya 1, and Algeria 5). These sites have been frequently used as radiometric targets because of their relatively stable surface conditions temporally. This study was performed using all cloud-free calibrated images from the Terra MODIS and the L7 ETM+ sensors, acquired from launch to December 2008. Homogeneous regions of interest (ROI) were selected in the calibrated images and the mean target statistics were derived from sensor measurements in terms of top-of-atmosphere (TOA) reflectance. For each band pair, a set of fitted coefficients (slope and offset) is provided to monitor the long-term stability over very stable pseudo-invariant test sites. The average percent differences in intercept from the long-term trends obtained from the ETM + TOA reflectance estimates relative to the MODIS for all the CEOS reference standard test sites range from 2.5% to 15%. This gives an estimate of the collective differences due to the Relative Spectral Response (RSR) characteristics of each sensor, bi-directional reflectance distribution function (BRDF), spectral signature of the ground target, and atmospheric composition. The lifetime TOA reflectance trends from both sensors over 10 years are extremely stable, changing by no more than 0.4% per year in its TOA reflectance over the CEOS reference standard test sites.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2009.12.003","issn":"00344257","usgsCitation":"Chander, G., Xiong, X., Choi, T., and Angal, A., 2010, Monitoring on-orbit calibration stability of the Terra MODIS and Landsat 7 ETM+ sensors using pseudo-invariant test sites: Remote Sensing of Environment, v. 114, no. 4, p. 925-939, https://doi.org/10.1016/j.rse.2009.12.003.","productDescription":"15 p.","startPage":"925","endPage":"939","numberOfPages":"15","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":245110,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":217188,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2009.12.003"}],"volume":"114","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a5dd0e4b0c8380cd705f6","contributors":{"authors":[{"text":"Chander, G.","contributorId":51449,"corporation":false,"usgs":true,"family":"Chander","given":"G.","affiliations":[],"preferred":false,"id":459044,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Xiong, X.","contributorId":54822,"corporation":false,"usgs":true,"family":"Xiong","given":"X.","email":"","affiliations":[],"preferred":false,"id":459046,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Choi, T.","contributorId":21794,"corporation":false,"usgs":true,"family":"Choi","given":"T.","email":"","affiliations":[],"preferred":false,"id":459043,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Angal, A.","contributorId":52716,"corporation":false,"usgs":true,"family":"Angal","given":"A.","affiliations":[],"preferred":false,"id":459045,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70036184,"text":"70036184 - 2010 - Establishing the Antarctic Dome C community reference standard site towards consistent measurements from Earth observation satellites","interactions":[],"lastModifiedDate":"2013-05-12T21:39:11","indexId":"70036184","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1175,"text":"Canadian Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Establishing the Antarctic Dome C community reference standard site towards consistent measurements from Earth observation satellites","docAbstract":"Establishing satellite measurement consistency by using common desert sites has become increasingly more important not only for climate change detection but also for quantitative retrievals of geophysical variables in satellite applications. Using the Antarctic Dome C site (75°06′S, 123°21′E, elevation 3.2 km) for satellite radiometric calibration and validation (Cal/Val) is of great interest owing to its unique location and characteristics. The site surface is covered with uniformly distributed permanent snow, and the atmospheric effect is small and relatively constant. In this study, the long-term stability and spectral characteristics of this site are evaluated using well-calibrated satellite instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS). Preliminary results show that despite a few limitations, the site in general is stable in the long term, the bidirectional reflectance distribution function (BRDF) model works well, and the site is most suitable for the Cal/Val of reflective solar bands in the 0.4–1.0 µm range. It was found that for the past decade, the reflectivity change of the site is within 1.35% at 0.64 µm, and interannual variability is within 2%. The site is able to resolve calibration biases between instruments at a level of ~1%. The usefulness of the site is demonstrated by comparing observations from seven satellite instruments involving four space agencies, including OrbView-2–SeaWiFS, Terra–Aqua MODIS, Earth Observing 1 (EO-1) – Hyperion, Meteorological Operational satellite programme (MetOp) – Advanced Very High Resolution Radiometer (AVHRR), Envisat Medium Resolution Imaging Spectrometer (MERIS) – dvanced Along-Track Scanning Radiometer (AATSR), and Landsat 7 Enhanced Thematic Mapper Plus (ETM+). Dome C is a promising candidate site for climate quality calibration of satellite radiometers towards more consistent satellite measurements, as part of the framework for climate change detection and data quality assurance for the Global Earth Observation System of Systems (GEOSS).","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Canadian Journal of Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Canadian Remote Sensing Society","doi":"10.5589/m10-075","issn":"07038992","usgsCitation":"Cao, C., Uprety, S., Xiong, J., Wu, A., Jing, P., Smith, D., Chander, G., Fox, N., and Ungar, S., 2010, Establishing the Antarctic Dome C community reference standard site towards consistent measurements from Earth observation satellites: Canadian Journal of Remote Sensing, v. 36, no. 5, p. 498-513, https://doi.org/10.5589/m10-075.","productDescription":"16 p.","startPage":"498","endPage":"513","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":218572,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.5589/m10-075"},{"id":246595,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"5","noUsgsAuthors":false,"publicationDate":"2014-06-02","publicationStatus":"PW","scienceBaseUri":"505a0a64e4b0c8380cd52338","contributors":{"authors":[{"text":"Cao, C.","contributorId":37944,"corporation":false,"usgs":true,"family":"Cao","given":"C.","email":"","affiliations":[],"preferred":false,"id":454680,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Uprety, S.","contributorId":65345,"corporation":false,"usgs":true,"family":"Uprety","given":"S.","affiliations":[],"preferred":false,"id":454686,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Xiong, J.","contributorId":58472,"corporation":false,"usgs":true,"family":"Xiong","given":"J.","email":"","affiliations":[],"preferred":false,"id":454684,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wu, A.","contributorId":44019,"corporation":false,"usgs":true,"family":"Wu","given":"A.","email":"","affiliations":[],"preferred":false,"id":454682,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jing, P.","contributorId":38859,"corporation":false,"usgs":true,"family":"Jing","given":"P.","email":"","affiliations":[],"preferred":false,"id":454681,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, D.","contributorId":60978,"corporation":false,"usgs":true,"family":"Smith","given":"D.","affiliations":[],"preferred":false,"id":454685,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chander, G.","contributorId":51449,"corporation":false,"usgs":true,"family":"Chander","given":"G.","affiliations":[],"preferred":false,"id":454683,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fox, N.","contributorId":90905,"corporation":false,"usgs":true,"family":"Fox","given":"N.","email":"","affiliations":[],"preferred":false,"id":454687,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ungar, S.","contributorId":15413,"corporation":false,"usgs":true,"family":"Ungar","given":"S.","affiliations":[],"preferred":false,"id":454679,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70034551,"text":"70034551 - 2010 - Modeling fire severity in black spruce stands in the Alaskan boreal forest using spectral and non-spectral geospatial data","interactions":[],"lastModifiedDate":"2017-11-22T11:30:36","indexId":"70034551","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Modeling fire severity in black spruce stands in the Alaskan boreal forest using spectral and non-spectral geospatial data","docAbstract":"Biomass burning in the Alaskan interior is already a major disturbance and source of carbon emissions, and is likely to increase in response to the warming and drying predicted for the future climate. In addition to quantifying changes to the spatial and temporal patterns of burned areas, observing variations in severity is the key to studying the impact of changes to the fire regime on carbon cycling, energy budgets, and post-fire succession. Remote sensing indices of fire severity have not consistently been well-correlated with in situ observations of important severity characteristics in Alaskan black spruce stands, including depth of burning of the surface organic layer. The incorporation of ancillary data such as in situ observations and GIS layers with spectral data from Landsat TM/ETM+ greatly improved efforts to map the reduction of the organic layer in burned black spruce stands. Using a regression tree approach, the R2 of the organic layer depth reduction models was 0.60 and 0.55 (pb0.01) for relative and absolute depth reduction, respectively. All of the independent variables used by the regression tree to estimate burn depth can be obtained independently of field observations. Implementation of a gradient boosting algorithm improved the R2 to 0.80 and 0.79 (pb0.01) for absolute and relative organic layer depth reduction, respectively. Independent variables used in the regression tree model of burn depth included topographic position, remote sensing indices related to soil and vegetation characteristics, timing of the fire event, and meteorological data. Post-fire organic layer depth characteristics are determined for a large (N200,000 ha) fire to identify areas that are potentially vulnerable to a shift in post-fire succession. This application showed that 12% of this fire event experienced fire severe enough to support a change in post-fire succession. We conclude that non-parametric models and ancillary data are useful in the modeling of the surface organic layer fire depth. Because quantitative differences in post-fire surface characteristics do not directly influence spectral properties, these modeling techniques provide better information than the use of remote sensing data alone.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2010.02.001","issn":"00344257","usgsCitation":"Barrett, K.M., Kasischke, E., McGuire, A., Turetsky, M., and Kane, E., 2010, Modeling fire severity in black spruce stands in the Alaskan boreal forest using spectral and non-spectral geospatial data: Remote Sensing of Environment, v. 114, no. 7, p. 1494-1503, https://doi.org/10.1016/j.rse.2010.02.001.","productDescription":"10 p.","startPage":"1494","endPage":"1503","numberOfPages":"10","ipdsId":"IP-018226","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":243722,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":215887,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2010.02.001"}],"volume":"114","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a5bf8e4b0c8380cd6f937","contributors":{"authors":[{"text":"Barrett, Kirsten M. kbarrett@usgs.gov","contributorId":2979,"corporation":false,"usgs":true,"family":"Barrett","given":"Kirsten","email":"kbarrett@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":446347,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kasischke, E.S.","contributorId":61201,"corporation":false,"usgs":true,"family":"Kasischke","given":"E.S.","email":"","affiliations":[],"preferred":false,"id":446349,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGuire, A. D.","contributorId":16552,"corporation":false,"usgs":true,"family":"McGuire","given":"A. D.","affiliations":[],"preferred":false,"id":446346,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Turetsky, M.R.","contributorId":107470,"corporation":false,"usgs":true,"family":"Turetsky","given":"M.R.","email":"","affiliations":[],"preferred":false,"id":446350,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kane, E.S.","contributorId":42275,"corporation":false,"usgs":true,"family":"Kane","given":"E.S.","email":"","affiliations":[],"preferred":false,"id":446348,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}