Long-term exposure to elevated nitrate levels in community drinking water supplies has been associated with an elevated risk of several cancers including non-Hodgkin's lymphoma, colon cancer, and bladder cancer. To estimate human exposure to nitrate, specific crop type information is needed as fertilizer application rates vary widely by crop type. Corn requires the highest application of nitrogen fertilizer of crops grown in the Midwest US. We developed a method to refine the US Geological Survey National Land Cover Dataset (NLCD) (including map and original Landsat images) to distinguish corn from other crops. Overall average agreement between the resulting corn and other row crops class and ground reference data was 0.79 kappa coefficient with individual Landsat images ranging from 0.46 to 0.93 kappa. The highest accuracies occurred in Regions where corn was the single dominant crop (greater than 80.0%) and the crop vegetation conditions at the time of image acquisition were optimum for separation of corn from all other crops. Factors that resulted in lower accuracies included the accuracy of the NLCD map, accuracy of corn areal estimates, crop mixture, crop condition at the time of Landsat overpass, and Landsat scene anomalies.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.compag.2005.11.003","issn":"01681699","usgsCitation":"Maxwell, S., Nuckols, J., and Ward, M., 2006, A method for mapping corn using the US Geological Survey 1992 National Land Cover Dataset: Computers and Electronics in Agriculture, v. 51, no. 1-2, p. 54-65, https://doi.org/10.1016/j.compag.2005.11.003.","productDescription":"12 p.","startPage":"54","endPage":"65","numberOfPages":"12","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":239100,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":211750,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.compag.2005.11.003"}],"volume":"51","issue":"1-2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059e455e4b0c8380cd465b4","contributors":{"authors":[{"text":"Maxwell, S.K.","contributorId":36665,"corporation":false,"usgs":true,"family":"Maxwell","given":"S.K.","email":"","affiliations":[],"preferred":false,"id":427166,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nuckols, J.R.","contributorId":85385,"corporation":false,"usgs":true,"family":"Nuckols","given":"J.R.","affiliations":[],"preferred":false,"id":427167,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ward, M.H.","contributorId":35939,"corporation":false,"usgs":true,"family":"Ward","given":"M.H.","email":"","affiliations":[],"preferred":false,"id":427165,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70028607,"text":"70028607 - 2006 - Cross-calibration of the Landsat-7 ETM+ and Landsat-5 TM with the ResourceSat-1 (IRS-P6) AWiFS and LISS-III sensors","interactions":[],"lastModifiedDate":"2024-09-17T15:03:45.047276","indexId":"70028607","displayToPublicDate":"2006-01-01T00:00:00","publicationYear":"2006","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Cross-calibration of the Landsat-7 ETM+ and Landsat-5 TM with the ResourceSat-1 (IRS-P6) AWiFS and LISS-III sensors","docAbstract":"Increasingly, data from multiple sensors are used to gain a more complete understanding of land surface processes at a variety of scales. The Landsat suite of satellites has collected the longest continuous archive of multispectral data. The ResourceSat-1 Satellite (also called as IRS-P6) was launched into the polar sunsynchronous orbit on Oct 17, 2003. It carries three remote sensing sensors: the High Resolution Linear Imaging Self-Scanner (LISS-IV), Medium Resolution Linear Imaging Self-Scanner (LISS-III), and the Advanced Wide Field Sensor (AWiFS). These three sensors are used together to provide images with different resolution and coverage. To understand the absolute radiometric calibration accuracy of IRS-P6 AWiFS and LISS-III sensors, image pairs from these sensors were compared to the Landsat-5 TM and Landsat-7 ETM+ sensors. The approach involved the calibration of nearly simultaneous surface observations based on image statistics from areas observed simultaneously by the two sensors.","conferenceTitle":"GEOSS and Next-Generation Sensors and Missions","conferenceDate":"November 13-14, 2006","conferenceLocation":"Goa, India","language":"English","publisher":"SPIE","doi":"10.1117/12.693742","issn":"0277786X","usgsCitation":"Chander, G., and Scaramuzza, P., 2006, Cross-calibration of the Landsat-7 ETM+ and Landsat-5 TM with the ResourceSat-1 (IRS-P6) AWiFS and LISS-III sensors, GEOSS and Next-Generation Sensors and Missions, v. 6407, Goa, India, November 13-14, 2006, 64070E, 12 p., https://doi.org/10.1117/12.693742.","productDescription":"64070E, 12 p.","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":236571,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6407","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059fcc1e4b0c8380cd4e3fd","contributors":{"authors":[{"text":"Chander, Gyanesh gchander@usgs.gov","contributorId":3013,"corporation":false,"usgs":true,"family":"Chander","given":"Gyanesh","email":"gchander@usgs.gov","affiliations":[],"preferred":true,"id":418806,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scaramuzza, Pat 0000-0002-2616-8456 pscar@usgs.gov","orcid":"https://orcid.org/0000-0002-2616-8456","contributorId":3970,"corporation":false,"usgs":true,"family":"Scaramuzza","given":"Pat","email":"pscar@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":418807,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70028107,"text":"70028107 - 2006 - An analysis of urban thermal characteristics and associated land cover in Tampa Bay and Las Vegas using Landsat satellite data","interactions":[],"lastModifiedDate":"2017-04-11T09:59:40","indexId":"70028107","displayToPublicDate":"2006-01-01T00:00:00","publicationYear":"2006","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":"An analysis of urban thermal characteristics and associated land cover in Tampa Bay and Las Vegas using Landsat satellite data","docAbstract":"Remote sensing data from both Landsat 5 and Landsat 7 systems were utilized to assess urban area thermal characteristics in Tampa Bay watershed of west-central Florida, and the Las Vegas valley of southern Nevada. To quantitatively determine urban land use extents and development densities, sub-pixel impervious surface areas were mapped for both areas. The urban–rural boundaries and urban development densities were defined by selecting certain imperviousness threshold values and Landsat thermal bands were used to investigate urban surface thermal patterns. Analysis results suggest that urban surface thermal characteristics and patterns can be identified through qualitatively based urban land use and development density data. Results show the urban area of the Tampa Bay watershed has a daytime heating effect (heat-source), whereas the urban surface in Las Vegas has a daytime cooling effect (heat-sink). These thermal effects strongly correlated with urban development densities where higher percent imperviousness is usually associated with higher surface temperature. Using vegetation canopy coverage information, the spatial and temporal distributions of urban impervious surface and associated thermal characteristics are demonstrated to be very useful sources in quantifying urban land use, development intensity, and urban thermal patterns.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2005.09.023","issn":"00344257","usgsCitation":"Xian, G., and Crane, M., 2006, An analysis of urban thermal characteristics and associated land cover in Tampa Bay and Las Vegas using Landsat satellite data: Remote Sensing of Environment, v. 104, no. 2, p. 147-156, https://doi.org/10.1016/j.rse.2005.09.023.","productDescription":"10 p.","startPage":"147","endPage":"156","numberOfPages":"10","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":210392,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2005.09.023"},{"id":237297,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"104","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059e9f7e4b0c8380cd48561","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":416559,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crane, Mike","contributorId":99824,"corporation":false,"usgs":true,"family":"Crane","given":"Mike","email":"","affiliations":[],"preferred":false,"id":416560,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70028089,"text":"70028089 - 2006 - Canopy reflectance related to marsh dieback onset and progression in Coastal Louisiana","interactions":[],"lastModifiedDate":"2019-10-08T18:20:02","indexId":"70028089","displayToPublicDate":"2006-01-01T00:00:00","publicationYear":"2006","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3052,"text":"Photogrammetric Engineering and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Canopy reflectance related to marsh dieback onset and progression in Coastal Louisiana","docAbstract":"In this study, we extended previous work linking leaf spectral changes, dieback onset, and progression of Spartina alterniflora marshes to changes in site-specific canopy reflectance spectra. First, we obtained canopy reflectance spectra (approximately 20 m ground resolution) from the marsh sites occupied during the leaf spectral analyses and from additional sites exhibiting visual signs of dieback. Subsequently, the canopy spectra were analyzed at two spectral scales: the first scale corresponded to whole-spectra sensors, such as the NASA Earth Observing-1 (EO-1) Hyperion, and the second scale corresponded to broadband spectral sensors, such as the EO-1 Advanced Land Imager and the Landsat Enhanced Thematic Mapper. In the whole-spectra analysis, spectral indicators were generated from the whole canopy spectra (about 400 nm to 1,000 nm) by extracting typical dead and healthy marsh spectra, and subsequently using them to determine the percent composition of all canopy reflectance spectra. Percent compositions were then used to classify canopy spectra at each field site into groups exhibiting similar levels of dieback progression ranging from relatively healthy to completely dead. In the broadband reflectance analysis, blue, green, red, red-edge, and near infrared (NIR) spectral bands and NIR/green and NIR/red transforms were extracted from the canopy spectra. Spectral band and band transform indicators of marsh dieback and progression were generated by relating them to marsh status indicators derived from classifications of the 35 mm slides collected at the same time as the canopy reflectance recordings. The whole spectra and broadband spectral indicators were both able to distinguish (a) healthy marsh, (b) live marsh impacted by dieback, and (c) dead marsh, and they both provided some discrimination of dieback progression. Whole-spectra resolution sensors like the EO-1 Hyperion, however, offered an enhanced ability to categorize dieback progression.
","language":"English","publisher":"American Society for Photogrammetry and Remote Sensing","doi":"10.14358/PERS.72.6.641","issn":"00991112","usgsCitation":"Ramsey, E., and Rangoonwala, A., 2006, Canopy reflectance related to marsh dieback onset and progression in Coastal Louisiana: Photogrammetric Engineering and Remote Sensing, v. 72, no. 6, p. 641-652, https://doi.org/10.14358/PERS.72.6.641.","productDescription":"12 p.","startPage":"641","endPage":"652","numberOfPages":"12","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":477527,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.14358/pers.72.6.641","text":"Publisher Index Page"},{"id":237014,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"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 -92.17529296875,\n 29.391747742992806\n ],\n [\n -90.63720703125,\n 29.391747742992806\n ],\n [\n -90.63720703125,\n 30.817346256492073\n ],\n [\n -92.17529296875,\n 30.817346256492073\n ],\n [\n -92.17529296875,\n 29.391747742992806\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"72","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059f345e4b0c8380cd4b6dc","contributors":{"authors":[{"text":"Ramsey, Elijah W. III 0000-0002-4518-5796","orcid":"https://orcid.org/0000-0002-4518-5796","contributorId":72769,"corporation":false,"usgs":true,"family":"Ramsey","given":"Elijah W.","suffix":"III","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":416491,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rangoonwala, A. 0000-0002-0556-0598","orcid":"https://orcid.org/0000-0002-0556-0598","contributorId":95248,"corporation":false,"usgs":true,"family":"Rangoonwala","given":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":416492,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70028831,"text":"70028831 - 2006 - Absolute calibration accuracy of L4 TM and L5 TM sensor image pairs","interactions":[],"lastModifiedDate":"2022-05-17T15:11:33.806895","indexId":"70028831","displayToPublicDate":"2006-01-01T00:00:00","publicationYear":"2006","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Absolute calibration accuracy of L4 TM and L5 TM sensor image pairs","docAbstract":"The Landsat suite of satellites has collected the longest continuous archive of multispectral data of any land-observing space program. From the Landsat program's inception in 1972 to the present, the Earth science user community has benefited from a historical record of remotely sensed data. However, little attention has been paid to ensuring that the data are calibrated and comparable from mission to mission, Launched in 1982 and 1984 respectively, the Landsat 4 (L4) and Landsat 5 (L5) Thematic Mappers (TM) are the backbone of an extensive archive of moderate resolution Earth imagery. To evaluate the \"current\" absolute accuracy of these two sensors, image pairs from the L5 TM and L4 TM sensors were compared. The approach involves comparing image statistics derived from large common areas observed eight days apart by the two sensors. The average percent differences in reflectance estimates obtained from the L4 TM agree with those from the L5 TM to within 15 percent. Additional work to characterize the absolute differences between the two sensors over the entire mission is in progress.","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 XI","conferenceDate":"Aug 14-16, 2006","conferenceLocation":"San Diego, CA","language":"English","publisher":"SPIE","doi":"10.1117/12.683240","usgsCitation":"Chander, G., and Micijevic, E., 2006, Absolute calibration accuracy of L4 TM and L5 TM sensor image pairs, in Proceedings of SPIE - The International Society for Optical Engineering, v. 6296, San Diego, CA, Aug 14-16, 2006, 62960D, https://doi.org/10.1117/12.683240.","productDescription":"62960D","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":236651,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6296","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059e64ae4b0c8380cd47305","contributors":{"authors":[{"text":"Chander, G.","contributorId":51449,"corporation":false,"usgs":true,"family":"Chander","given":"G.","affiliations":[],"preferred":false,"id":419915,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":419916,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70028838,"text":"70028838 - 2006 - Cross-calibration of MODIS with ETM+ and ALI sensors for long-term monitoring of land surface processes","interactions":[],"lastModifiedDate":"2022-05-17T15:53:59.766539","indexId":"70028838","displayToPublicDate":"2006-01-01T00:00:00","publicationYear":"2006","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Cross-calibration of MODIS with ETM+ and ALI sensors for long-term monitoring of land surface processes","docAbstract":"Increasingly, data from multiple sensors are used to gain a more complete understanding of land surface processes at a variety of scales. Although higher-level products (e.g., vegetation cover, albedo, surface temperature) derived from different sensors can be validated independently, the degree to which these sensors and their products can be compared to one another is vastly improved if their relative spectroradiometric responses are known. Most often, sensors are directly calibrated to diffuse solar irradiation or vicariously to ground targets. However, space-based targets are not traceable to metrological standards, and vicarious calibrations are expensive and provide a poor sampling of a sensor's full dynamic range. Crosscalibration of two sensors can augment these methods if certain conditions can be met: (1) the spectral responses are similar, (2) the observations are reasonably concurrent (similar atmospheric & solar illumination conditions), (3) errors due to misregistrations of inhomogeneous surfaces can be minimized (including scale differences), and (4) the viewing geometry is similar (or, some reasonable knowledge of surface bi-directional reflectance distribution functions is available). This study explores the impacts of cross-calibrating sensors when such conditions are met to some degree but not perfectly. In order to constrain the range of conditions at some level, the analysis is limited to sensors where cross-calibration studies have been conducted (Enhanced Thematic Mapper Plus (ETM+) on Landsat-7 (L7), Advance Land Imager (ALI) and Hyperion on Earth Observer-1 (EO-1)) and including systems having somewhat dissimilar geometry, spatial resolution & spectral response characteristics but are still part of the so-called \"A.M. constellation\" (Moderate Resolution Imaging Spectrometer (MODIS) aboard the Terra platform). Measures for spectral response differences and methods for cross calibrating such sensors are provided in this study. These instruments are cross calibrated using the Railroad Valley playa in Nevada. Best fit linear coefficients (slope and offset) are provided for ALI-to-MODIS and ETM+-to-MODIS cross calibrations, and root-mean-squared errors (RMSEs) and correlation coefficients are provided to quantify the uncertainty in these relationships. In theory, the linear fits and uncertainties can be used to compare radiance and reflectance products derived from each instrument.","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 XI","conferenceDate":"Aug 14-16, 2006","conferenceLocation":"San Diego, CA","language":"English","publisher":"SPIE","doi":"10.1117/12.683567","usgsCitation":"Meyer, D., and Chander, G., 2006, Cross-calibration of MODIS with ETM+ and ALI sensors for long-term monitoring of land surface processes, in Proceedings of SPIE - The International Society for Optical Engineering, v. 6296, San Diego, CA, Aug 14-16, 2006, 62960H, https://doi.org/10.1117/12.683567.","productDescription":"62960H","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":236759,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6296","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059fcc1e4b0c8380cd4e3fa","contributors":{"authors":[{"text":"Meyer, D.","contributorId":31131,"corporation":false,"usgs":true,"family":"Meyer","given":"D.","affiliations":[],"preferred":false,"id":419938,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chander, G.","contributorId":51449,"corporation":false,"usgs":true,"family":"Chander","given":"G.","affiliations":[],"preferred":false,"id":419939,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":77491,"text":"i2600A - 2006 - Coastal-change and glaciological map of the Trinity Peninsula area and south Shetland Islands, Antarctica: 1843-2001: Chapter A in Coastal-change and glaciological maps of Antarctica","interactions":[],"lastModifiedDate":"2018-03-23T14:52:55","indexId":"i2600A","displayToPublicDate":"1994-01-01T00:00:00","publicationYear":"2006","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":320,"text":"IMAP","code":"I","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"2600","chapter":"A","title":"Coastal-change and glaciological map of the Trinity Peninsula area and south Shetland Islands, Antarctica: 1843-2001: Chapter A in Coastal-change and glaciological maps of Antarctica","docAbstract":"Changes in the area and volume of polar ice sheets are intricately linked to changes in global climate, and the resulting changes in sea level could severely impact the densely populated coastal regions on Earth. Melting of the West Antarctic part alone of the Antarctic ice sheet would cause a sea-level rise of approximately 6 meters (m). The potential sea-level rise after melting of the entire Antarctic ice sheet is estimated to be 65 m (Lythe and others, 2001) to 73 m (Williams and Hall, 1993). In addition to its importance, the mass balance (the net volumetric gain or loss) of the Antarctic ice sheet is highly complex, responding differently to different conditions in each region (Vaughan, 2005). In a review paper, Rignot and Thomas (2002) concluded that the West Antarctic ice sheet is probably becoming thinner overall; although it is thickening in the west, it is thinning in the north. Thomas and others (2004), on the basis of aircraft and satellite laser altimetry surveys, believe the thinning may be accelerating. Joughin and Tulaczyk (2002), on the basis of analysis of ice-flow velocities derived from synthetic aperture radar, concluded that most of the Ross ice streams (ice streams on the east side of the Ross Ice Shelf) have a positive mass balance, whereas Rignot and others (2004) infer even larger negative mass balance for glaciers flowing northward into the Amundsen Sea, a trend suggested by Swithinbank and others (2003a,b, 2004). The mass balance of the East Antarctic ice sheet is thought by Davis and others (2005) to be strongly positive on the basis of the change in satellite altimetry measurements made between 1992 and 2003.
\nMeasurement of changes in area and mass balance of the Antarctic ice sheet was given a very high priority in recommendations by the Polar Research Board of the National Research Council (1986), in subsequent recommendations by the Scientific Committee on Antarctic Research (SCAR) (1989, 1993), and by the National Science Foundation's (1990) Division of Polar Programs. On the basis of these recommendations, the U.S. Geological Survey (USGS) decided that the archive of early 1970s Landsat 1, 2, and 3 Multispectral Scanner (MSS) images of Antarctica and the subsequent repeat coverage made possible with Landsat and other satellite images provided an excellent means of documenting changes in the coastline of Antarctica (Ferrigno and Gould, 1987). The availability of this information provided the impetus for carrying out a comprehensive analysis of the glaciological features of the coastal regions and changes in ice fronts of Antarctica (Swithinbank, 1988; Williams and Ferrigno, 1988). The project was later modified to include Landsat 4 and 5 MSS and Thematic Mapper (TM) [and in some areas Landsat 7 Enhanced Thematic Mapper Plus (ETM+)], RADARSAT images, and other data where available, to compare changes that occurred during a 20- to 25- or 30-year time interval (or longer where data were available, as in the Antarctic Peninsula). The results of the analysis are being used to produce a digital database and a series of USGS Geologic Investigations Series Maps (I–2600) consisting of 23 maps at 1:1,000,000 scale and 1 map at 1:5,000,000 scale, in both paper and digital format (Williams and others, 1995; Williams and Ferrigno, 1998; Ferrigno and others, 2002).
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Coastal-change and glaciological maps of Antarctica","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/i2600A","isbn":"0607964421","collaboration":"This report is Chapter A in Coastal-change and glaciological maps of Antarctica. For more information, see: IMAP 2600. Prepared in cooperation with the British Antarctic Survey, Scott Polar Research Institute, and Bundesamt für Kartographie und Geodäsie","usgsCitation":"Ferrigno, J.G., Cook, A.J., Foley, K.M., Williams, R., Swithinbank, C., Fox, A.J., Thomson, J.W., and Sievers, J., 2006, Coastal-change and glaciological map of the Trinity Peninsula area and south Shetland Islands, Antarctica: 1843-2001: Chapter A in Coastal-change and glaciological maps of Antarctica: U.S. Geological Survey IMAP 2600, 1 Plate: 45.00 x 28.00 inches; Pamphlet: iv, 32 p., https://doi.org/10.3133/i2600A.","productDescription":"1 Plate: 45.00 x 28.00 inches; Pamphlet: iv, 32 p.","numberOfPages":"36","temporalStart":"1842-12-31","temporalEnd":"2001-12-31","costCenters":[{"id":181,"text":"Coastal Change and Glaciological Maps of Antarctica","active":false,"usgs":true}],"links":[{"id":191198,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":9417,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/imap/2600/A/","linkFileType":{"id":5,"text":"html"}},{"id":295719,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/imap/2600/A/pdf/TrinityCoast.pdf"},{"id":295720,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/imap/2600/A/pdf/I2600-A-pamphlet.pdf"}],"scale":"1000000","projection":"Polar stereographic projection","otherGeospatial":"Antarctica, South Shetland Islands, Trinity Peninsula","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -67,-65 ], [ -67,-60 ], [ -52,-60 ], [ -52,-65 ], [ -67,-65 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b24e4b07f02db6aea19","contributors":{"authors":[{"text":"Ferrigno, Jane G. jferrign@usgs.gov","contributorId":39825,"corporation":false,"usgs":true,"family":"Ferrigno","given":"Jane","email":"jferrign@usgs.gov","middleInitial":"G.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":288586,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cook, Alison J.","contributorId":42665,"corporation":false,"usgs":true,"family":"Cook","given":"Alison","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":288587,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Foley, Kevin M. 0000-0003-1013-462X kfoley@usgs.gov","orcid":"https://orcid.org/0000-0003-1013-462X","contributorId":2543,"corporation":false,"usgs":true,"family":"Foley","given":"Kevin","email":"kfoley@usgs.gov","middleInitial":"M.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":288583,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Richard S. Jr.","contributorId":90679,"corporation":false,"usgs":true,"family":"Williams","given":"Richard S.","suffix":"Jr.","affiliations":[],"preferred":false,"id":288589,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Swithinbank, Charles","contributorId":26368,"corporation":false,"usgs":true,"family":"Swithinbank","given":"Charles","email":"","affiliations":[],"preferred":false,"id":288584,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fox, Adrian J.","contributorId":68413,"corporation":false,"usgs":true,"family":"Fox","given":"Adrian","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":288588,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thomson, Janet W.","contributorId":32212,"corporation":false,"usgs":true,"family":"Thomson","given":"Janet","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":288585,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sievers, Jorn","contributorId":101753,"corporation":false,"usgs":true,"family":"Sievers","given":"Jorn","email":"","affiliations":[],"preferred":false,"id":288590,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70121225,"text":"70121225 - No Year - Constraining rates and trends of historical wetland loss, Mississippi River Delta Plain, south-central Louisiana","interactions":[],"lastModifiedDate":"2019-06-03T15:01:17","indexId":"70121225","displayToPublicDate":"2006-01-01T10:11:00","publicationYear":"2006","noYear":true,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Constraining rates and trends of historical wetland loss, Mississippi River Delta Plain, south-central Louisiana","docAbstract":"The timing, magnitude, and rate of wetland loss were described for five wetland-loss \nhotspots in the Terrebonne Basin of the Mississippi River delta plain. Land and water areas \nwere mapped for 34 dates between 1956 and 2004 from historical National Wetlands \nInventory (NWI) datasets, aerial photographs, and Landsat Thematic Mapper (TM) satellite \nimages. Since 1956, the emergent land area at the five study areas in south-central Louisiana \nhas decreased by about 50%. Comparison of the water-area curve derived from the 29 TM \nimages with water-level records from the nearby Grand Isle, Louisiana tide gauge (NOS \n#8761724) clearly shows that changes in land and water areas fluctuate in response to \nvariations in regional water levels. The magnitude of water-area fluctuations decreased from \nthe 1980s to the 1990s as former areas of wet marsh within and immediately adjacent to the \nwetland-loss hotspots became permanently submerged. The most rapid wetland loss \noccurred during the late 1960s and 1970s. Peak wetland-loss rates during this period were \ntwo to four times greater than both the pre-1970s background rates and the most recent \nwetland-loss rates. These results provide constraints on predicting future delta-plain wetland \nlosses and identify Landsat TM imagery as an important source for analyzing land- and \nwater-area changes across the entire delta plain.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Coastal environment and water quality: proceedings of the AIH 25th Anniversary Meeting & International Conference \"Challenges in Coastal Hyrology and Water Quality\"","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Water Resource Publications","publisherLocation":"Highlands Ranch, CO","usgsCitation":"Bernier, J., Morton, R., and Barras, J., 2006, Constraining rates and trends of historical wetland loss, Mississippi River Delta Plain, south-central Louisiana, in Coastal environment and water quality: proceedings of the AIH 25th Anniversary Meeting & International Conference \"Challenges in Coastal Hyrology and Water Quality\", p. 371-382.","productDescription":"12 p.","startPage":"371","endPage":"382","numberOfPages":"12","costCenters":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"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":292614,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":292613,"type":{"id":15,"text":"Index Page"},"url":"https://coastal.er.usgs.gov/gc-subsidence/historical-wetland-loss.html"}],"country":"United States","state":"Louisiana","otherGeospatial":"Mississippi River Delta Plain","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -91.25,29.0 ], [ -91.25,29.5 ], [ -89.75,29.5 ], [ -89.75,29.0 ], [ -91.25,29.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53f5b64ce4b09d12e0e8e673","contributors":{"authors":[{"text":"Bernier, Julie 0000-0002-9918-5353 jbernier@usgs.gov","orcid":"https://orcid.org/0000-0002-9918-5353","contributorId":3549,"corporation":false,"usgs":true,"family":"Bernier","given":"Julie","email":"jbernier@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":498825,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morton, Robert A.","contributorId":88333,"corporation":false,"usgs":true,"family":"Morton","given":"Robert A.","affiliations":[],"preferred":false,"id":498826,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":498824,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70037974,"text":"70037974 - 2005 - Elevations and Distances","interactions":[],"lastModifiedDate":"2014-05-05T09:41:54","indexId":"70037974","displayToPublicDate":"2012-04-06T00:00:00","publicationYear":"2005","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"seriesTitle":{"id":362,"text":"General Information Product","active":false,"publicationSubtype":{"id":6}},"title":"Elevations and Distances","docAbstract":"Photographs and other images of the Earth taken from the air and from space show a great deal about the planet's landforms, vegetation, and resources. Aerial and satellite images, known as remotely sensed images, permit accurate mapping of land cover and make landscape features understandable on regional, continental, and even global scales. Transient phenomena, such as seasonal vegetation vigor and contaminant discharges, can be studied by comparing images acquired at different times. The U.S. Geological Survey (USGS), which began using aerial photographs for mapping in the 1930's, archives photographs from its mapping projects and from those of some other Federal agencies. In addition, many images from such space programs as Landsat, begun in 1972, are held by the USGS. Most satellite scenes can be obtained only in digital form for use in computer-based image processing and geographic information systems, but in some cases are also available as photographic products.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/70037974","collaboration":"Archived Publication--Most of the information contained in this publication is no longer current and is not expected to be updated.","usgsCitation":"Water Resources Division, U.S. Geological Survey, 2005, Elevations and Distances: General Information Product, HTML Document, https://doi.org/10.3133/70037974.","productDescription":"HTML Document","additionalOnlineFiles":"Y","costCenters":[],"links":[{"id":254451,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/70037974.gif"},{"id":254445,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/gip/Elevations-Distances/","linkFileType":{"id":5,"text":"html"}},{"id":286857,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/Elevations-Distances/elvadist.html"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a08cfe4b0c8380cd51ca8","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":535174,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":80125,"text":"fs20053118 - 2005 - Global Visualization (GloVis) Viewer","interactions":[],"lastModifiedDate":"2012-02-02T00:14:06","indexId":"fs20053118","displayToPublicDate":"2007-07-24T00:00:00","publicationYear":"2005","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":"2005-3118","title":"Global Visualization (GloVis) Viewer","docAbstract":"GloVis (http://glovis.usgs.gov) is a browse image-based search and order tool that can be used to quickly review the land remote sensing data inventories held at the U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS). GloVis was funded by the AmericaView project to reduce the difficulty of identifying and acquiring data for user-defined study areas.\r\n\r\nUpdated daily with the most recent satellite acquisitions, GloVis displays data in a mosaic, allowing users to select any area of interest worldwide and immediately view all available browse images for the following Landsat data sets: Multispectral Scanner (MSS), Multi-Resolution Land Characteristics (MRLC), Orthorectified, Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and ETM+ Scan Line Corrector-off (SLC-off). Other data sets include Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Moderate Resolution Imaging Spectroradiometer (MODIS), Aqua MODIS, and the Earth Observing-1 (EO-1) Advanced Land Imager (ALI) and Hyperion data.","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/fs20053118","usgsCitation":"Water Resources Division, U.S. Geological Survey, 2005, Global Visualization (GloVis) Viewer: U.S. Geological Survey Fact Sheet 2005-3118, 1 p., https://doi.org/10.3133/fs20053118.","productDescription":"1 p.","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":126487,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2005/3118/report-thumb.jpg"},{"id":91226,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2005/3118/report.pdf","linkFileType":{"id":1,"text":"pdf"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4abee4b07f02db674c36","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":534871,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":80129,"text":"fs20053075 - 2005 - USGS Releases Landsat Orthorectified State Mosaics","interactions":[],"lastModifiedDate":"2012-02-02T00:14:22","indexId":"fs20053075","displayToPublicDate":"2007-07-24T00:00:00","publicationYear":"2005","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":"2005-3075","title":"USGS Releases Landsat Orthorectified State Mosaics","docAbstract":"The U.S. Geological Survey (USGS) National Remote Sensing Data Archive, located at the USGS Center for Earth Resources Observation and Science (EROS) in Sioux Falls, South Dakota, maintains the Landsat orthorectified data archive. Within the archive are Landsat Enhanced Thematic Mapper Plus (ETM+) data that have been pansharpened and orthorectified by the Earth Satellite Corporation. This imagery has acquisition dates ranging from 1999 to 2001 and was created to provide users with access to quality-screened, high-resolution satellite images with global coverage over the Earth's landmasses.","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/fs20053075","usgsCitation":"Water Resources Division, U.S. Geological Survey, 2005, USGS Releases Landsat Orthorectified State Mosaics: U.S. Geological Survey Fact Sheet 2005-3075, 2 p., https://doi.org/10.3133/fs20053075.","productDescription":"2 p.","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":122412,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2005/3075/report-thumb.jpg"},{"id":91230,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2005/3075/report.pdf","linkFileType":{"id":1,"text":"pdf"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a28e4b07f02db6114f0","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":534872,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":80120,"text":"fs20053105 - 2005 - The AmericaView Project - Putting the Earth into Your Hands","interactions":[],"lastModifiedDate":"2012-02-02T00:14:14","indexId":"fs20053105","displayToPublicDate":"2007-07-24T00:00:00","publicationYear":"2005","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":"2005-3105","title":"The AmericaView Project - Putting the Earth into Your Hands","docAbstract":"The U.S. Geological Survey (USGS) is a leader in collecting, archiving, and distributing geospatial data and information about the Earth. Providing quick, reliable access to remotely sensed images and geospatial data is the driving principle behind the AmericaView Project.\r\n\r\nA national not-for-profit organization, AmericaView, Inc. was established and is supported by the USGS to coordinate the activities of a national network of university-led consortia with the primary objective of the advancement of the science of remote sensing. Individual consortia members include academic institutions, as well as state, local, and tribal government agencies. AmericaView's focus is to expand the understanding and use of remote sensing through education and outreach efforts and to provide affordable, integrated remote sensing information access and delivery to the American public.\r\n\r\nUSGS's Landsat and NASA's Earth Observing System (EOS) satellite data are downlinked from satellites or transferred from other facilities to the USGS Center for Earth Resources Observation and Science (EROS) ground receiving station in Sioux Falls, South Dakota. The data can then be transferred over high-speed networks to consortium members, where it is archived and made available for public use.","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/fs20053105","usgsCitation":"Water Resources Division, U.S. Geological Survey, 2005, The AmericaView Project - Putting the Earth into Your Hands: U.S. Geological Survey Fact Sheet 2005-3105, 1 p., https://doi.org/10.3133/fs20053105.","productDescription":"1 p.","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":122404,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2005/3105/report-thumb.jpg"},{"id":91222,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2005/3105/report.pdf","linkFileType":{"id":1,"text":"pdf"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ad5e4b07f02db683410","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":534867,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":75993,"text":"fs20053130 - 2005 - Landsat: A global land-observing program","interactions":[{"subject":{"id":75993,"text":"fs20053130 - 2005 - Landsat: A global land-observing program","indexId":"fs20053130","publicationYear":"2005","noYear":false,"title":"Landsat: A global land-observing program"},"predicate":"SUPERSEDED_BY","object":{"id":98375,"text":"fs20103026 - 2010 - Landsat: A Global Land-Imaging Project","indexId":"fs20103026","publicationYear":"2010","noYear":false,"title":"Landsat: A Global Land-Imaging Project"},"id":1}],"supersededBy":{"id":98375,"text":"fs20103026 - 2010 - Landsat: A Global Land-Imaging Project","indexId":"fs20103026","publicationYear":"2010","noYear":false,"title":"Landsat: A Global Land-Imaging Project"},"lastModifiedDate":"2017-03-27T15:36:50","indexId":"fs20053130","displayToPublicDate":"2006-03-30T00:00:00","publicationYear":"2005","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":"2005-3130","title":"Landsat: A global land-observing program","docAbstract":"Landsat represents the world’s longest continuously acquired collection of space-based land remote sensing data. The Landsat Project is a joint initiative of the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA) designed to gather Earth resource data from space. NASA developed and launched the spacecrafts, while the USGS handles the operations, maintenance, and management of all ground data reception, processing, archiving, product generation, and distribution.
Landsat satellites have been collecting images of the Earth’s surface for more than thirty years. Landsat’s Global Survey Mission is to repeatedly capture images of the Earth’s land mass, coastal boundaries, and coral reefs, and to ensure that sufficient data are acquired to support the observation of changes on the Earth’s land surface and surrounding environment. NASA launched the first Landsat satellite in 1972, and the most recent one, Landsat 7, in 1999. Landsats 5 and 7 continue to capture hundreds of additional images of the Earth’s surface each day. These images provide a valuable resource for people who work
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/fs20053130","usgsCitation":"Water Resources Division, U.S. Geological Survey, 2005, Landsat: A global land-observing program (Supersedes FS 023-03): U.S. Geological Survey Fact Sheet 2005-3130, 4 p., https://doi.org/10.3133/fs20053130.","productDescription":"4 p.","numberOfPages":"4","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":7090,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2005/3130/FS-2005-3130.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":121345,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2005_3130.jpg"},{"id":115897,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2005/3130/","linkFileType":{"id":5,"text":"html"}}],"edition":"Supersedes FS 023-03","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b20e4b07f02db6abb33","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":534773,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":75213,"text":"ofr20051445 - 2005 - Digital method for regional mapping of surficial basin deposits in arid regions, example from central Death Valley, Inyo County, California","interactions":[],"lastModifiedDate":"2022-11-22T22:25:37.934105","indexId":"ofr20051445","displayToPublicDate":"2006-03-07T00:00:00","publicationYear":"2005","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":"2005-1445","title":"Digital method for regional mapping of surficial basin deposits in arid regions, example from central Death Valley, Inyo County, California","docAbstract":"Derivative maps generated from DEM's and panchromatic remote sensing data (TM Landsat 7 or SPOT) can be used to characterize surficial basin deposits in arid regions dominated by basin and range topography. Results indicate the technique is useful for rapid digital mapping of surficial deposits where a first order, systematic subdivision of bedrock, alluvial fan units, and playas is unavailable at regional scales. Digital mapping can provide information about relative age and material properties of units that in part can be derived from the position of units within the basin. This automated mapping, implemented in a GIS system, involves an iterative process applied to a combination of digital elevation models (DEM) and satellite image data, such as SPOT or the high-resolution panchromatic Band 8 of Landsat 7 scenes.
The method first discriminates the region into first-order terrains consisting of bedrock mountain highlands, basin piedmonts, and playa-basin interiors based on user-defined slope cutoffs applied to DEM data. The basin areas are subsequently classified into surficial map units such as active channels, ground-water discharge zones, and multiple age alluvial-fan piedmont units based on reflective properties of the associated surfaces in the satellite imagery. The surficial units are differentiated through systematic classification based on specific user-defined ranges of spectral values for each unit. The spectral ranges used in the classification are largely dependent on the composite effects of surface characteristics and material properties, including depositional morphology and texture, pavement development, degree of surface clast varnishing, and (or) properties of exposed soils of the alluvial fan units. We have used the slope-curvature properties derived from the DEM data to discriminate the bajada areas that exhibit non-unique spectral characteristics. Slope curvature is particularly effective at differentiating young undissected surfaces from older dissected piedmont units.
Available geologic maps and field observations may be used both to iteratively calibrate the spectral classification scheme and to provide additional verification of the digital map output. Digital mapping combined with detailed field studies in selected areas provides useful regional maps of surficial units until time and funding is available for more field intensive studies. In addition, anomalous areas on the thematic maps indicate where more detailed field or air photo work is warranted. The technique successfully distinguishes between bedrock, alluvial fans (generally multiple fan units), active washes, playas, playa rimming marshes and seeps and other active and inactive discharge zones in arid basin and mountain regions. Limitations occur in the subdivision of some fan units where the dominant detrital clast lithologies are not susceptible to varnish development.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20051445","usgsCitation":"Jayko, A.S., Menges, C., and Thompson, R.A., 2005, Digital method for regional mapping of surficial basin deposits in arid regions, example from central Death Valley, Inyo County, California (Version 1.0): U.S. Geological Survey Open-File Report 2005-1445, 43 p., https://doi.org/10.3133/ofr20051445.","productDescription":"43 p.","numberOfPages":"43","costCenters":[],"links":[{"id":191393,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":409557,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_75055.htm","linkFileType":{"id":5,"text":"html"}},{"id":7633,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2005/1445/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","county":"Inyo County","otherGeospatial":"central Death Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117,\n 36.5\n ],\n [\n -117,\n 36\n ],\n [\n -116,\n 36\n ],\n [\n -116,\n 36.5\n ],\n [\n -117,\n 36.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a96e4b07f02db65aba0","contributors":{"authors":[{"text":"Jayko, A. S. 0000-0002-7378-0330","orcid":"https://orcid.org/0000-0002-7378-0330","contributorId":18011,"corporation":false,"usgs":true,"family":"Jayko","given":"A.","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":286828,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Menges, C.M.","contributorId":71200,"corporation":false,"usgs":false,"family":"Menges","given":"C.M.","affiliations":[],"preferred":false,"id":286829,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, R. A.","contributorId":100420,"corporation":false,"usgs":true,"family":"Thompson","given":"R.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":286830,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":74503,"text":"fs20053060 - 2005 - Earth Observing-1 Extended Mission","interactions":[{"subject":{"id":47840,"text":"fs03203 - 2003 - Earth Observing-1 Extended Mission","indexId":"fs03203","publicationYear":"2003","noYear":false,"title":"Earth Observing-1 Extended Mission"},"predicate":"SUPERSEDED_BY","object":{"id":74503,"text":"fs20053060 - 2005 - Earth Observing-1 Extended Mission","indexId":"fs20053060","publicationYear":"2005","noYear":false,"title":"Earth Observing-1 Extended Mission"},"id":1}],"lastModifiedDate":"2012-02-27T14:10:03","indexId":"fs20053060","displayToPublicDate":"2006-02-19T00:00:00","publicationYear":"2005","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":"2005-3060","title":"Earth Observing-1 Extended Mission","docAbstract":"Since November 2000, the National Aeronautics and Space Administration (NASA) Earth Observing-1 (EO-1) mission has demonstrated the capabilities of a dozen spacecraft sensor and communication innovations. Onboard the EO-1 spacecraft are two land remote sensing instruments. The Advanced Land Imager (ALI) acquires data in spectral bands and at resolutions similar to Landsat. The Hyperion instrument, which is the first civilian spaceborne hyperspectral imager, acquires data in 220 10-nanometer bands covering the visible, near, and shortwave-infrared bands. The initial one-year technology demonstration phase of the mission included a detailed comparison of ALI with the Landsat Enhanced Thematic Mapper Plus (ETM+) instrument. Specifications for the Operational Land Imager (OLI), the planned successor to ETM+, were formulated in part from performance characteristics of ALI.\n\nRecognizing the remarkable performance of the satellite's instruments and the exceptional value of the data, the U.S. Geological Survey (USGS) and NASA agreed in December 2001 to share responsibility for operating EO-1. The extended mission continues, on a cost-reimbursable basis, as long as customer sales fully recover flight and ground operations costs. As of May 2005, more than 17,800 scenes from each instrument have been acquired, indexed, archived, and made available to the public.","language":"ENGLISH","publisher":"Geological Survey (U.S.)","doi":"10.3133/fs20053060","usgsCitation":"Water Resources Division, U.S. Geological Survey, 2005, Earth Observing-1 Extended Mission: U.S. Geological Survey Fact Sheet 2005-3060, 2 p., https://doi.org/10.3133/fs20053060.","productDescription":"2 p.","numberOfPages":"2","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":124441,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2005_3060.jpg"},{"id":115894,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2005/3060/","linkFileType":{"id":5,"text":"html"}},{"id":7575,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2005/3060/fs2005-3060.pdf","linkFileType":{"id":1,"text":"pdf"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a52e4b07f02db62aa42","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":534768,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":72803,"text":"ofr20051371 - 2005 - Aerial gamma-ray, Landsat TM, and digital elevation data, Big Bend area, Texas","interactions":[],"lastModifiedDate":"2022-01-26T21:40:32.288849","indexId":"ofr20051371","displayToPublicDate":"2006-01-02T00:00:00","publicationYear":"2005","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":"2005-1371","title":"Aerial gamma-ray, Landsat TM, and digital elevation data, Big Bend area, Texas","docAbstract":"No abstract available.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20051371","usgsCitation":"Duval, J.S., 2005, Aerial gamma-ray, Landsat TM, and digital elevation data, Big Bend area, Texas: U.S. Geological Survey Open-File Report 2005-1371, HTML Document, https://doi.org/10.3133/ofr20051371.","productDescription":"HTML Document","costCenters":[],"links":[{"id":191717,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":394921,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_74492.htm"},{"id":7400,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2005/1371/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Texas","otherGeospatial":"Big Bend area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.74664306640625,\n 28.9913248161703\n ],\n [\n -102.89794921875,\n 28.9913248161703\n ],\n [\n -102.89794921875,\n 29.76914573606667\n ],\n [\n -103.74664306640625,\n 29.76914573606667\n ],\n [\n -103.74664306640625,\n 28.9913248161703\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b03e4b07f02db698e60","contributors":{"authors":[{"text":"Duval, Joseph S.","contributorId":22314,"corporation":false,"usgs":true,"family":"Duval","given":"Joseph","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":286132,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70259127,"text":"70259127 - 2005 - Landsat 7 scan line corrector-off gap-filled product development","interactions":[],"lastModifiedDate":"2024-09-27T16:23:06.366893","indexId":"70259127","displayToPublicDate":"2005-12-01T11:16:42","publicationYear":"2005","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Landsat 7 scan line corrector-off gap-filled product development","docAbstract":"The Landsat 7 Enhanced Thematic Mapper Plus (ETM+) scan line corrector (SLC) failed on May 31, 2003, causing the scanning pattern to exhibit wedge-shaped scan-to-scan gaps. The ETM+ has continued to acquire data with the SLC powered off, leading to images that are missing approximately 22 percent of the normal scene area. To improve the utility of the SLC-off data, the U.S. Geological Survey (USGS) developed new products that use the data from multiple ETM+ scenes to provide complete ground coverage. These gap-filled products were developed and deployed in two phases. The gaps in the Phase I products are filled with data from imagery collected previously with a functional SLC (SLC-on). A single SLC-on scene provides complete coverage of the scan gaps, making the gap-filling procedure straightforward. Several radiometric adjustment techniques for matching the SLC-on fill scene to the SLC-off primary scene were evaluated for performance, processing speed, and ease of implementation. A simple local histogram matching method was adopted as a result of this evaluation. The Phase II products use data from multiple SLC-off scenes to fill the scan gaps with more recent data. Because the locations of the scan gaps are different for each SLC-off scene, the gap-filling process must account for scan gap interactions. The Phase II product development included a more comprehensive study of candidate radiometric adjustment techniques. This study showed that the histogram matching method used in Phase I, with minor refinements, provided the best overall performance and was adopted for Phase II as well.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Global priorities in land remote sensing","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"William T. Pecora Memorial Symposium on Remote Sensing, 16th","conferenceDate":"October 23-27, 2005","conferenceLocation":"Sioux Falls, SD","language":"English","publisher":"ASPRS","usgsCitation":"Storey, J.C., Scaramuzza, P., Schmidt, G.L., and Barsi, J., 2005, Landsat 7 scan line corrector-off gap-filled product development, in Global priorities in land remote sensing, Sioux Falls, SD, October 23-27, 2005, 13 p.","productDescription":"13 p.","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":462345,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.asprs.org/Conference-Proceedings.html","linkFileType":{"id":5,"text":"html"}},{"id":462346,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Storey, James C. 0000-0002-6664-7232 storey@usgs.gov","orcid":"https://orcid.org/0000-0002-6664-7232","contributorId":5333,"corporation":false,"usgs":true,"family":"Storey","given":"James","email":"storey@usgs.gov","middleInitial":"C.","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":914265,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scaramuzza, Pasquale 0000-0002-2616-8456","orcid":"https://orcid.org/0000-0002-2616-8456","contributorId":344596,"corporation":false,"usgs":true,"family":"Scaramuzza","given":"Pasquale","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":914266,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmidt, Gail L. 0000-0002-9684-8158 gschmidt@usgs.gov","orcid":"https://orcid.org/0000-0002-9684-8158","contributorId":3475,"corporation":false,"usgs":true,"family":"Schmidt","given":"Gail","email":"gschmidt@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":914267,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barsi, Julia","contributorId":251781,"corporation":false,"usgs":false,"family":"Barsi","given":"Julia","email":"","affiliations":[{"id":50397,"text":"SSAI","active":true,"usgs":false}],"preferred":false,"id":914268,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70155970,"text":"70155970 - 2005 - Monitoring boreal forest leaf area index across a Siberian burn chronosequence: A MODIS validation study","interactions":[],"lastModifiedDate":"2021-02-09T12:47:39.093671","indexId":"70155970","displayToPublicDate":"2005-12-01T00:00:00","publicationYear":"2005","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring boreal forest leaf area index across a Siberian burn chronosequence: A MODIS validation study","docAbstract":"Landscapes containing differing amounts of ecological disturbance provide an excellent opportunity to validate and better understand the emerging Moderate Resolution Imaging Spectrometer (MODIS) vegetation products. Four sites, including 1‐year post‐fire coniferous, 13‐year post‐fire deciduous, 24‐year post‐fire deciduous, and >100 year old post‐fire coniferous forests, were selected to serve as a post‐fire chronosequence in the central Siberian region of Krasnoyarsk (57.3°N, 91.6°E) with which to study the MODIS leaf area index (LAI) and vegetation index (VI) products. The collection 4 MODIS LAI product correctly represented the summer site phenologies, but significantly underestimated the LAI value of the >100 year old coniferous forest during the November to April time period. Landsat 7‐derived enhanced vegetation index (EVI) performed better than normalized difference vegetation index (NDVI) to separate the deciduous and conifer forests, and both indices contained significant correlation with field‐derived LAI values at coniferous forest sites (r 2 = 0.61 and r 2 = 0.69, respectively). The reduced simple ratio (RSR) markedly improved LAI prediction from satellite measurements (r 2 = 0.89) relative to NDVI and EVI. LAI estimates derived from ETM+ images were scaled up to evaluate the 1 km resolution MODIS LAI product; from this analysis MODIS LAI overestimated values in the low LAI deciduous forests (where LAI<5) and underestimated values in the high LAI conifer forests (where LAI>6). Our results indicate that further research on the MODIS LAI product is warranted to better understand and improve remote LAI quantification in disturbed forest landscapes over the course of the year.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/01431160500285142","usgsCitation":"Chen, X., Vierling, L., Deering, D., and Conley, A., 2005, Monitoring boreal forest leaf area index across a Siberian burn chronosequence: A MODIS validation study: International Journal of Remote Sensing, v. 26, no. 24, p. 5433-5451, https://doi.org/10.1080/01431160500285142.","productDescription":"19 p.","startPage":"5433","endPage":"5451","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":306465,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia","otherGeospatial":"Krasnoyarsk Kray","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 92.61749267578125,\n 55.90457539720638\n ],\n [\n 92.61749267578125,\n 56.12259144921196\n ],\n [\n 93.1475830078125,\n 56.12259144921196\n ],\n [\n 93.1475830078125,\n 55.90457539720638\n ],\n [\n 92.61749267578125,\n 55.90457539720638\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"26","issue":"24","noUsgsAuthors":false,"publicationDate":"2007-02-22","publicationStatus":"PW","scienceBaseUri":"57fe90b7e4b0824b2d14bfc3","contributors":{"authors":[{"text":"Chen, X.","contributorId":76527,"corporation":false,"usgs":true,"family":"Chen","given":"X.","affiliations":[],"preferred":false,"id":567472,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vierling, Lee","contributorId":17022,"corporation":false,"usgs":true,"family":"Vierling","given":"Lee","affiliations":[],"preferred":false,"id":567473,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Deering, D.","contributorId":69352,"corporation":false,"usgs":true,"family":"Deering","given":"D.","email":"","affiliations":[],"preferred":false,"id":567474,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conley, A.","contributorId":146334,"corporation":false,"usgs":false,"family":"Conley","given":"A.","email":"","affiliations":[],"preferred":false,"id":567475,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":72640,"text":"i2600D - 2005 - Coastal-change and glaciological map of the Ronne Ice Shelf area, Antarctica, 1974-2002","interactions":[],"lastModifiedDate":"2012-02-10T00:11:37","indexId":"i2600D","displayToPublicDate":"2005-10-21T00:00:00","publicationYear":"2005","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":320,"text":"IMAP","code":"I","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"2600","chapter":"D","title":"Coastal-change and glaciological map of the Ronne Ice Shelf area, Antarctica, 1974-2002","docAbstract":"Changes in the area and volume of polar ice sheets are intricately linked to changes in global climate, and the resulting changes in sea level may severely impact the densely populated coastal regions on Earth. Melting of the West Antarctic part alone of the Antarctic ice sheet could cause a sea-level rise of approximately 6 meters (m). The potential sea-level rise after melting of the entire Antarctic ice sheet is estimated to be 65 m (Lythe and others, 2001) to 73 m (Williams and Hall, 1993). In spite of its importance, the mass balance (the net volumetric gain or loss) of the Antarctic ice sheet is poorly known; it is not known for certain whether the ice sheet is growing or shrinking. In a review paper, Rignot and Thomas (2002) concluded that the West Antarctic part of the Antarctic ice sheet is probably becoming thinner overall; although it is thickening in the west, it is thinning in the north. Joughin and Tulaczyk (2002), on the basis of analysis of ice-flow velocities derived from synthetic aperture radar, concluded that most of the Ross ice streams (ice streams on the east side of the Ross Ice Shelf) have a positive mass balance, whereas Rignot and others (in press) infer even larger negative mass balance for glaciers flowing northward into the Amundsen Sea, a trend suggested by Swithinbank and others (2003a,b, 2004). The mass balance of the East Antarctic part of the Antarctic ice sheet is unknown, but thought to be in near equilibrium.\r\n\r\nMeasurement of changes in area and mass balance of the Antarctic ice sheet was given a very high priority in recommendations by the Polar Research Board of the National Research Council (1986), in subsequent recommendations by the Scientific Committee on Antarctic Research (SCAR) (1989, 1993), and by the National Science Foundation's (1990) Division of Polar Pro-grams. On the basis of these recommendations, the U.S. Geo-logical Survey (USGS) decided that the archive of early 1970s Landsat 1, 2, and 3 Multispectral Scanner (MSS) images of Ant-arctica and the subsequent repeat coverage made possible with Landsat and other satellite images provided an excellent means of documenting changes in the coastline of Antarctica (Ferrigno and Gould, 1987). The availability of this information provided the impetus for carrying out a comprehensive analysis of the glaciological features of the coastal regions and changes in ice fronts of Antarctica (Swithinbank, 1988; Williams and Ferrigno, 1988). The project was later modified to include Landsat 4 and 5 MSS and Thematic Mapper (TM) (and in some areas Landsat 7 Enhanced Thematic Mapper Plus (ETM+)), RADARSAT images, and other data where available, to compare changes during a 20- to 25- or 30-year time interval (or longer where data were available, as in the Antarctic Peninsula). The results of the analysis are being used to produce a digital database and a series of USGS Geologic Investigations Series Maps (I-2600) consisting of 23 maps at 1:1,000,000 scale and 1 map at 1:5,000,000 scale, in both paper and digital format (Williams and others, 1995; Williams and Ferrigno, 1998; Ferrigno and others, 2002) (available online at http://www.glaciers.er.usgs.gov).","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Coastal-change and glaciological maps of Antarctica","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"ENGLISH","doi":"10.3133/i2600D","isbn":"0607964413","usgsCitation":"Ferrigno, J.G., Foley, K., Swithinbank, C., Williams, R., and Dalide, L., 2005, Coastal-change and glaciological map of the Ronne Ice Shelf area, Antarctica, 1974-2002 (Version 1.0): U.S. Geological Survey IMAP 2600, 1 map : col. ; 48 x 56 in. 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A low-cost, aerial photomosaic of the 4200 ha, study area was constructed utilizing an automated digital camera system, supplemented with oblique photographs to aid in determining species composition and plant heights. Ground-truth plots showed high accuracy in distinguishing native cottonwood (Populus fremontii) and willow (Salix gooddingii) trees from other vegetation on aerial photos. Marsh vegetation (mainly cattails, Typha domengensis) was also easily identified. However, shrubby terrestrial vegetation, consisting of saltcedar (Tamarix ramosissima), arrowweed (Pluchea sericea), and mesquite trees (Prosopis spp.), could not be accurately distinguished from each other and were combined into a single shrub layer on the final vegetation map. The final map took the form of a base, shrub and marsh layer, which was displayed as a Normalized Difference Vegetation Index map from a Landsat Enhanced Thematic Mapper (ETM+) image to show vegetation intensity. Native willow and cottonwood trees were digitized manually on the photomosaic and overlain on the shrub layer in a GIS. By contrast to present, qualitative mapping systems used on the Lower Colorado River, this mapping system provides quantitative information that can be used for accurate change detection. However, better methods to distinguish between saltcedar, mesquite, and arrowweed are needed to map the shrub layer.
","language":"English","publisher":"Springer","doi":"10.1007/s10661-005-6285-y","usgsCitation":"Nagler, P., Glenn, E., Hursh, K., Curtin, C., and Huete, A., 2005, Vegetation mapping for change detection on an arid-zone river: Environmental Monitoring and Assessment, v. 109, p. 255-274, https://doi.org/10.1007/s10661-005-6285-y.","productDescription":"20 p.","startPage":"255","endPage":"274","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":497524,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"109","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Nagler, Pamela L. 0000-0003-0674-103X","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":363777,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","middleInitial":"L.","affiliations":[],"preferred":true,"id":952319,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":952320,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hursh, Kim","contributorId":364200,"corporation":false,"usgs":false,"family":"Hursh","given":"Kim","affiliations":[],"preferred":false,"id":952321,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Curtin, Charles","contributorId":167142,"corporation":false,"usgs":false,"family":"Curtin","given":"Charles","email":"","affiliations":[],"preferred":false,"id":952322,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huete, Alfredo","contributorId":211930,"corporation":false,"usgs":false,"family":"Huete","given":"Alfredo","affiliations":[{"id":38362,"text":"University of Technology, Sydney, Australia","active":true,"usgs":false}],"preferred":false,"id":952323,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70258651,"text":"70258651 - 2005 - Outgassing models for Landsat-4 thematic mapper short wave infrared bands","interactions":[],"lastModifiedDate":"2024-09-19T16:40:13.44745","indexId":"70258651","displayToPublicDate":"2005-08-22T11:35:38","publicationYear":"2005","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Outgassing models for Landsat-4 thematic mapper short wave infrared bands","docAbstract":"Detector responses to the Internal Calibrator (IC) pulses in the Landsat-4 Thematic Mapper (TM) have been observed to follow an oscillatory behavior. This phenomenon is present only in the Short Wave Infrared (SWIR) bands and has been observed throughout the lifetime of the instrument, which was launched in July 1982 and imaged the Earth's surface until late 1993. These periodic changes in amplitude, which can be as large as 7.5 percent, are known as outgassing effects and are believed to be due to optical interference caused by a gradual buildup of an ice-like material on the window of the cryogenically cooled dewar containing the SWIR detectors. Similar outgassing effects in the Landsat-5 TM have been characterized using an optical thin-film model that relates detector behavior to the ice film growth rate, which was found to gradually decrease with time. A similar approach, which takes into consideration the different operational history of the instrument, has been applied in this study to three closely sampled data sets acquired throughout the lifetime of the Landsat-4 TM. Although Landsat-4 and Landsat-5 Thematic Mappers are essentially identical instruments, data generated from analyses of outgassing effects indicate subtle, but important, differences between the two. The estimated lifetime model could improve radiometric accuracy by as much as five percent.
","conferenceTitle":"Optics and Photonics 2005: Earth Observing Systems X","conferenceDate":"July 31-August 4, 2005","conferenceLocation":"San Diego, CA","language":"English","publisher":"SPIE","doi":"10.1117/12.620160","usgsCitation":"Micijevic, E., and Helder, D., 2005, Outgassing models for Landsat-4 thematic mapper short wave infrared bands, Optics and Photonics 2005: Earth Observing Systems X, v. 5882, San Diego, CA, July 31-August 4, 2005, 588208, 11 p., https://doi.org/10.1117/12.620160.","productDescription":"588208, 11 p.","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":439157,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5882","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Micijevic, Esad 0000-0002-3828-9239 emicijevic@usgs.gov","orcid":"https://orcid.org/0000-0002-3828-9239","contributorId":3075,"corporation":false,"usgs":true,"family":"Micijevic","given":"Esad","email":"emicijevic@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":913557,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Helder, Dennis 0000-0002-7379-4679","orcid":"https://orcid.org/0000-0002-7379-4679","contributorId":213606,"corporation":false,"usgs":true,"family":"Helder","given":"Dennis","email":"","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":913558,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70258392,"text":"70258392 - 2005 - Landsat-4 and Landsat-5 thematic mapper band 6 historical performance and calibration","interactions":[],"lastModifiedDate":"2024-09-16T16:13:35.633671","indexId":"70258392","displayToPublicDate":"2005-08-22T11:04:28","publicationYear":"2005","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Landsat-4 and Landsat-5 thematic mapper band 6 historical performance and calibration","docAbstract":"Launched in 1982 and 1984 respectively, the Landsat-4 and -5 Thematic Mappers (TM) are the backbone of an extensive archive of moderate resolution Earth imagery. However, these sensors and their data products were not subjected to the type of intensive monitoring that has been part of the Landsat-7 system since its launch in 1999. With Landsat-4's 11 year and Landsat-5's 20+ year data record, there is a need to understand the historical behavior of the instruments in order to verify the scientific integrity of the archive and processed products. Performance indicators of the Landsat-4 and -5 thermal bands have recently been extracted from a processing system database allowing for a more complete study of thermal band characteristics and calibration than was previously possible. The database records responses to the internal calibration system, instrument temperatures and applied gains and offsets for each band for every scene processed through the National Landsat Archive Production System (NLAPS). Analysis of this database has allowed for greater understanding of the calibration and improvement in the processing system. This paper will cover the trends in the Landsat-4 and -5 thermal bands, the effect of the changes seen in the trends, and how these trends affect the use of the thermal data.
","conferenceTitle":"Optic and Photonics 2005","conferenceDate":"July 31-Augest 2, 2005","conferenceLocation":"San Diego, CA","language":"English","publisher":"SPIE","doi":"10.1117/12.619992","usgsCitation":"Barsi, J.A., Chander, G., Markham, B.L., and Higgs, N., 2005, Landsat-4 and Landsat-5 thematic mapper band 6 historical performance and calibration, Optic and Photonics 2005, v. 5882, San Diego, CA, July 31-Augest 2, 2005, 588206, https://doi.org/10.1117/12.619992.","productDescription":"588206","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":434784,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5882","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Barsi, Julia A.","contributorId":71822,"corporation":false,"usgs":false,"family":"Barsi","given":"Julia","email":"","middleInitial":"A.","affiliations":[{"id":12721,"text":"NASA GSFC SSAI","active":true,"usgs":false}],"preferred":false,"id":913178,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chander, Gyanesh gchander@usgs.gov","contributorId":3013,"corporation":false,"usgs":true,"family":"Chander","given":"Gyanesh","email":"gchander@usgs.gov","affiliations":[],"preferred":true,"id":913179,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Markham, Brian L. 0000-0002-9612-8169","orcid":"https://orcid.org/0000-0002-9612-8169","contributorId":121488,"corporation":false,"usgs":true,"family":"Markham","given":"Brian","email":"","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":913180,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Higgs, Nicholas","contributorId":344206,"corporation":false,"usgs":false,"family":"Higgs","given":"Nicholas","email":"","affiliations":[],"preferred":false,"id":913181,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70156397,"text":"70156397 - 2005 - Land cover mapping of Greater Mesoamerica using MODIS data","interactions":[],"lastModifiedDate":"2015-08-20T15:06:53","indexId":"70156397","displayToPublicDate":"2005-08-01T00:00:00","publicationYear":"2005","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":"Land cover mapping of Greater Mesoamerica using MODIS data","docAbstract":"A new land cover database of Greater Mesoamerica has been prepared using moderate resolution imaging spectroradiometer (MODIS, 500 m resolution) satellite data. Daily surface reflectance MODIS data and a suite of ancillary data were used in preparing the database by employing a decision tree classification approach. The new land cover data are an improvement over traditional advanced very high resolution radiometer (AVHRR) based land cover data in terms of both spatial and thematic details. The dominant land cover type in Greater Mesoamerica is forest (39%), followed by shrubland (30%) and cropland (22%). Country analysis shows forest as the dominant land cover type in Belize (62%), Cost Rica (52%), Guatemala (53%), Honduras (56%), Nicaragua (53%), and Panama (48%), cropland as the dominant land cover type in El Salvador (60.5%), and shrubland as the dominant land cover type in Mexico (37%). A three-step approach was used to assess the quality of the classified land cover data: (i) qualitative assessment provided good insight in identifying and correcting gross errors; (ii) correlation analysis of MODIS- and Landsat-derived land cover data revealed strong positive association for forest (r2 = 0.88), shrubland (r2 = 0.75), and cropland (r2 = 0.97) but weak positive association for grassland (r2 = 0.26); and (iii) an error matrix generated using unseen training data provided an overall accuracy of 77.3% with a Kappa coefficient of 0.73608. Overall, MODIS 500 m data and the methodology used were found to be quite useful for broad-scale land cover mapping of Greater Mesoamerica.
","language":"English","publisher":"Canadian Aeronautics and Space Institute","doi":"10.5589/m05-014","usgsCitation":"Giri, C., and Jenkins, C.N., 2005, Land cover mapping of Greater Mesoamerica using MODIS data: Canadian Journal of Remote Sensing, v. 31, no. 4, p. 274-282, https://doi.org/10.5589/m05-014.","productDescription":"9 p.","startPage":"274","endPage":"282","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":307056,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"4","noUsgsAuthors":false,"publicationDate":"2014-06-02","publicationStatus":"PW","scienceBaseUri":"55d6fa34e4b0518e3546bc4f","contributors":{"authors":[{"text":"Giri, Chandra cgiri@usgs.gov","contributorId":2403,"corporation":false,"usgs":true,"family":"Giri","given":"Chandra","email":"cgiri@usgs.gov","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":569024,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jenkins, Clinton N.","contributorId":101437,"corporation":false,"usgs":true,"family":"Jenkins","given":"Clinton","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":569025,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70725,"text":"fs20053056 - 2005 - Satellite Image Atlas of Glaciers of the World","interactions":[{"subject":{"id":44701,"text":"fs13002 - 2002 - Satellite Image Atlas of Glaciers of the World","indexId":"fs13002","publicationYear":"2002","noYear":false,"title":"Satellite Image Atlas of Glaciers of the World"},"predicate":"SUPERSEDED_BY","object":{"id":70725,"text":"fs20053056 - 2005 - Satellite Image Atlas of Glaciers of the World","indexId":"fs20053056","publicationYear":"2005","noYear":false,"title":"Satellite Image Atlas of Glaciers of the World"},"id":1}],"lastModifiedDate":"2012-02-02T00:13:47","indexId":"fs20053056","displayToPublicDate":"2005-06-21T00:00:00","publicationYear":"2005","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":"2005-3056","title":"Satellite Image Atlas of Glaciers of the World","docAbstract":"In 1978, the USGS began the preparation of the 11-chapter USGS Professional Paper 1386, 'Satellite Image Atlas of Glaciers of the World'. Between 1979 and 1981, optimum satellite images were distributed to a team of 70 scientists, representing 25 nations and 45 institutions, who agreed to author sections of the Professional Paper concerning either a geographic area (chapters B-K) or a glaciological topic (included in Chapter A). The scientists used Landsat 1, 2, and 3 multispectral scanner (MSS) images and Landsat 2 and 3 return beam vidicon (RBV) images to inventory the areal occurrence of glacier ice on our planet within the boundaries of the spacecrafts' coverage (between about 82? north and south latitudes). Some later contributors also used Landsat 4 and 5 MSS and Thematic Mapper, Landsat 7 Enhanced Thematic Mapper-Plus (ETM+), and other satellite images. In addition to analyzing images of a specific geographic area, each author was asked to summarize up-to-date information about the glaciers within each area and compare their present-day areal distribution with reliable historical information (from published maps, reports, and photographs) about their past extent. Because of the limitations of Landsat images for delineating or monitoring small glaciers in some geographic areas (the result of inadequate spatial resolution, lack of suitable seasonal coverage, or absence of coverage), some information on the areal distribution of small glaciers was derived from ancillary sources, including other satellite images. Completion of the atlas will provide an accurate regional inventory of the areal extent of glaciers on our planet during a relatively narrow time interval (1972-1981).","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/fs20053056","usgsCitation":"Williams, R., and Ferrigno, J.G., 2005, Satellite Image Atlas of Glaciers of the World (Revised 2008, Supersedes Fact Sheets 130-02, 133-99 & 009-94): U.S. Geological Survey Fact Sheet 2005-3056, 2 p., https://doi.org/10.3133/fs20053056.","productDescription":"2 p.","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":121199,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2005_3056.jpg"},{"id":6707,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2005/3056/","linkFileType":{"id":5,"text":"html"}}],"edition":"Revised 2008, Supersedes Fact Sheets 130-02, 133-99 & 009-94","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a14e4b07f02db602ac0","contributors":{"authors":[{"text":"Williams, Richard S. 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