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","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr81768","usgsCitation":"Le Compte, J.R., 1981, Preliminary maps showing interpretation of Landsat imagery of the Healy quadrangle, Alaska: U.S. Geological Survey Open-File Report 81-768, 2 Plates: 35.92 × 28.53 inches and 38.60 × 27.74 inches, https://doi.org/10.3133/ofr81768.","productDescription":"2 Plates: 35.92 × 28.53 inches and 38.60 × 27.74 inches","costCenters":[],"links":[{"id":175541,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":80880,"rank":401,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/1981/0768/plate-2.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":80879,"rank":400,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/1981/0768/plate-1.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":108175,"rank":700,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_12157.htm","linkFileType":{"id":5,"text":"html"},"description":"12157"}],"country":"United States","state":"Alaska","otherGeospatial":"Healy quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -150,\n 63\n ],\n [\n -147,\n 63\n ],\n [\n -147,\n 64\n ],\n [\n -150,\n 64\n ],\n [\n -150,\n 63\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4afce4b07f02db696936","contributors":{"authors":[{"text":"Le Compte, James R.","contributorId":23913,"corporation":false,"usgs":true,"family":"Le Compte","given":"James","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":227649,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":22752,"text":"ofr8126 - 1981 - Mapsat conceptual design; system overview","interactions":[],"lastModifiedDate":"2024-04-04T22:42:25.789613","indexId":"ofr8126","displayToPublicDate":"1994-01-01T00:00:00","publicationYear":"1981","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":"81-26","title":"Mapsat conceptual design; system overview","docAbstract":"After more than 10 years of study and applications of Earth imaging satellite systems, the U. S. Geological Survey has conceptually defined a candidate Operational Land Remote Sensing Satellite. A conceptual design study of this system, known as MAPSAT, has been completed by Itek Optical Systems, a division of Itek Corporation, and the TRW Defense Systems and Space Group. The concept of MAPSAT is based on LANDSAT mission, sensing, and data communication characteristics, but reflects the evolution of technological and application responsiveness.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr8126","usgsCitation":"Colvocoresses, A.P., 1981, Mapsat conceptual design; system overview: U.S. Geological Survey Open-File Report 81-26, 26 p., https://doi.org/10.3133/ofr8126.","productDescription":"26 p.","costCenters":[],"links":[{"id":155616,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/1981/0026/report-thumb.jpg"},{"id":427471,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/1981/0026/report.pdf","linkFileType":{"id":1,"text":"pdf"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a1ae4b07f02db6063ff","contributors":{"authors":[{"text":"Colvocoresses, Alden P.","contributorId":72779,"corporation":false,"usgs":true,"family":"Colvocoresses","given":"Alden","email":"","middleInitial":"P.","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":188817,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":46217,"text":"ofr81728L - 1981 - Maps showing interpretation of Landsat imagery of the Bradfield Canal quadrangle, southeastern Alaska","interactions":[],"lastModifiedDate":"2012-02-02T00:10:42","indexId":"ofr81728L","displayToPublicDate":"1994-01-01T00:00:00","publicationYear":"1981","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":"81-728","chapter":"L","title":"Maps showing interpretation of Landsat imagery of the Bradfield Canal quadrangle, southeastern Alaska","language":"ENGLISH","doi":"10.3133/ofr81728L","usgsCitation":"Le Compte, J., 1981, Maps showing interpretation of Landsat imagery of the Bradfield Canal quadrangle, southeastern Alaska: U.S. Geological Survey Open-File Report 81-728, 2 maps ;44 x 50 cm., https://doi.org/10.3133/ofr81728L.","productDescription":"2 maps ;44 x 50 cm.","costCenters":[],"links":[{"id":170845,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":83192,"rank":400,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/1981/0728l/plate-1.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":83193,"rank":401,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/1981/0728l/plate-2.pdf","linkFileType":{"id":1,"text":"pdf"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a19e4b07f02db605ae9","contributors":{"authors":[{"text":"Le Compte, J. R.","contributorId":41816,"corporation":false,"usgs":true,"family":"Le Compte","given":"J. R.","affiliations":[],"preferred":false,"id":232853,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70231494,"text":"70231494 - 1981 - Image enhancement through film recorder response contouring","interactions":[],"lastModifiedDate":"2022-05-11T16:13:31.090409","indexId":"70231494","displayToPublicDate":"1981-11-06T11:05:43","publicationYear":"1981","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Image enhancement through film recorder response contouring","docAbstract":"In contrast to the traditional recording from high-altitude aircraft of Earth images directly onto film in their inherently continuous analog form, a Landsat Earth resources satellite samples the ground image brightness and records it on a digital, electronic medium. Although digitization incurs several extra steps in the reproduction of the imagery, it permits manipulation or enhancement of the data for special uses. For instance, image data enhancement techniques can be applied to partially restore contrast lost because of atmospheric luminance and scatter. More significantly, the digital-to-analog transfer function of the film recorder can be modified to simulate certain characteristics of other film types. Manipulation of a film's apparent gamma, relative speed, and linear-response region is easily accomplished by mapping the input data to a new distribution in real time using a hardware-implemented lookup table. To accomplish the desired photographic results, however, full cooperation and communication between photographic, electronic, and computer technologists is essential.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings Volume 0278, Electro-Optical Instrumentation for Resources Evaluation","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"1981 Technical Symposium East","conferenceDate":"November 6, 1981","conferenceLocation":"Washington, D. C., United States","language":"English","publisher":"Society of Photo-Optical Instrumentation Engineers","doi":"10.1117/12.931938","usgsCitation":"Boyd, J.E., 1981, Image enhancement through film recorder response contouring, in Proceedings Volume 0278, Electro-Optical Instrumentation for Resources Evaluation, v. 278, Washington, D. C., United States, November 6, 1981, p. 157-166, https://doi.org/10.1117/12.931938.","productDescription":"10 p.","startPage":"157","endPage":"166","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":400512,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"278","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Boyd, John E.","contributorId":138984,"corporation":false,"usgs":true,"family":"Boyd","given":"John","email":"","middleInitial":"E.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":842782,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70113227,"text":"70113227 - 1981 - A comparative study of linear and nonlinear edge finding techniques for Landsat multispectral data","interactions":[],"lastModifiedDate":"2014-06-19T09:25:17","indexId":"70113227","displayToPublicDate":"1981-10-18T09:20:00","publicationYear":"1981","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3021,"text":"Pecora VII Symposium","active":true,"publicationSubtype":{"id":10}},"title":"A comparative study of linear and nonlinear edge finding techniques for Landsat multispectral data","docAbstract":"Several numerical methods were computerize in order to evaluate edge finding techniques for accuracy, versatility and computer time and cost. The study was preformed primarily to select edge detection operators which will be used to do spatial correlation between images for image registration of Landsat Multispectral Scanner (MSS) scenes. These method are also used to enhance and discriminate certain types of boundaries; such boundaries or edges are related to geologic structure, topographic relief, albedo and color changes. Application of these techniques has an aid in geologic and geographic remote sensing is evaluated. Landsat scenes of Washington, D.C. and Death Valley were chosen to test the applicability of techniques both in arid desert and vegetation--water--urban cases.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Pecora VII Symposium","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Society of Photogrammetry","publisherLocation":"Falls Church, VA","usgsCitation":"Shaw, R., Sowers, L., and Sanchez, E., 1981, A comparative study of linear and nonlinear edge finding techniques for Landsat multispectral data: Pecora VII Symposium, p. 529-542.","productDescription":"14 p.","startPage":"529","endPage":"542","numberOfPages":"14","costCenters":[{"id":195,"text":"Computer Center Division","active":false,"usgs":true}],"links":[{"id":288882,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae7610e4b0abf75cf2be69","contributors":{"authors":[{"text":"Shaw, Robert","contributorId":50020,"corporation":false,"usgs":true,"family":"Shaw","given":"Robert","email":"","affiliations":[],"preferred":false,"id":495001,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sowers, Lynda","contributorId":6298,"corporation":false,"usgs":true,"family":"Sowers","given":"Lynda","email":"","affiliations":[],"preferred":false,"id":495000,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sanchez, Ellen","contributorId":60058,"corporation":false,"usgs":true,"family":"Sanchez","given":"Ellen","email":"","affiliations":[],"preferred":false,"id":495002,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70113223,"text":"70113223 - 1981 - The role of remotely sensed and other spatial data for predictive modeling: the Umatilla, Oregon example","interactions":[],"lastModifiedDate":"2017-01-18T14:58:01","indexId":"70113223","displayToPublicDate":"1981-10-18T08:58:00","publicationYear":"1981","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3021,"text":"Pecora VII Symposium","active":true,"publicationSubtype":{"id":10}},"title":"The role of remotely sensed and other spatial data for predictive modeling: the Umatilla, Oregon example","docAbstract":"The U. S. Geological Survey's Earth Resources Observations Systems Data Center, in cooperation with the U.S. Army Corps of Engineers, Portland District, developed and tested techniques that used remotely sensed and other spatial data in predictive models to evaluate irrigation agriculture in the Umatilla River Basin of north-central Oregon. Landsat data and 1:24,000-scale aerial photographs were initially used to map he expansion of irrigate from 1973 to 1979 and to identify crops under irrigation in 1979. The crop data were then used with historical water requirement figures and digital topographic and hydrographic data to estimate water and power use for the 1979 irrigation season. The final project task involved production of a composite map of land suitability for irrigation development based on land cover (from Landsat), land-ownership, soil irrigability, slope gradient, and potential energy costs.
\nThe methods and data used in the study demonstrated the flexibility of remotely sensed and other spatial data as input for predictive models. When combined, they provided useful answers to complex questions facing resource managers.
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Methodologies for the processing and analysis of Landsat MSS and digital terrain data for the mapping of U.S. Forest Service fuel types were developed and demonstrated. Key elements in the mapping process were the development of a fuels terrain distribution model which provided a statistical description of the topographic distribution patterns of fuels within spectral classes, and secondly, the application of a layered classifier which incorporated the spectral and terrain data in a two-stage maximum likelihood classification framework for the mapping of fuels.
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B.","contributorId":292125,"corporation":false,"usgs":false,"family":"Webster","given":"K.","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":843858,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lucas, J. R.","contributorId":292126,"corporation":false,"usgs":false,"family":"Lucas","given":"J.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":843859,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Musgrove, R. J.","contributorId":292127,"corporation":false,"usgs":false,"family":"Musgrove","given":"R.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":843860,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Higer, A.L.","contributorId":8501,"corporation":false,"usgs":true,"family":"Higer","given":"A.L.","affiliations":[],"preferred":false,"id":843861,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70012022,"text":"70012022 - 1981 - Discrimination of a chestnut-oak forest unit for geologic mapping by means of a principal component enhancement of Landsat multispectral scanner data","interactions":[],"lastModifiedDate":"2024-02-15T01:09:32.738559","indexId":"70012022","displayToPublicDate":"1981-01-01T00:00:00","publicationYear":"1981","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Discrimination of a chestnut-oak forest unit for geologic mapping by means of a principal component enhancement of Landsat multispectral scanner data","docAbstract":"A principal component image enhancement has been effective in applying Landsat data to geologic mapping in a heavily forested area of eastern Virginia. A chestnut-oak forest unit, which occurs on metavolcanic rocks and some metaclastic rocks in the western Piedmont and on highly weathered upland gravel deposits in the eastern Piedmont, can be discerned on a digitally enhanced Landsat winter image. The image enhancement procedure consists of a principal component transformation, a histogram normalization, and the inverse principal component transformation. The enhancement preserves the independence of the principal components, yet produces a more readily interpretable image than does a single principal component transformation.
To determine how the chestnut-oak forest unit was being enhanced, average Landsat multispectral scanner (MSS) values were extracted for four sample forest types and were calculated through the inverted principal component transformation. Slope and intercept values for the linear histogram normalization were chosen to keep the scale between the raw MSS bands and the inverted principal component (PC) bands constant. Plots of the inverted principal component data show that the most separation between forest types is in inverted PC band 5. The chestnut-oak forest unit is characterized by a high value for inverted PC band 5 as opposed to a low value for inverted PC band 4. In contrast, raw MSS band 4 is greater than MSS band 5 for the four forest types sampled in the winter image. Such observations cannot be readily deduced from analysis of only the principal component rotation matrix. They may ultimately provide a means to map the distribution of chestnut-oak forest from Landsat.
Many diverse features can be discerned on the Landsat image of Volgograd and vicinity. Some of these features have resulted directly from man's alteration of the land surface in accordance with Stalin's and Khrushchev's plans for control of climate and for development in Volgograd and the surrounding area. Landsat images such as the one in this example provide the opportunity to inventory and assess man's imprint upon the land on a regional basis from a unique perspective.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00221348108980691","usgsCitation":"Dando, W.A., and Johnson, G., 1981, Volgograd and vicinity: a Landsat view: Journal of Geography, v. 80, no. 6, p. 235-237, https://doi.org/10.1080/00221348108980691.","productDescription":"3 p.","startPage":"235","endPage":"237","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":297842,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia","city":"Volgograd","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 41.15478515624999,\n 47.39834920035926\n ],\n [\n 41.15478515624999,\n 51.41291212935532\n ],\n [\n 47.35107421875,\n 51.41291212935532\n ],\n [\n 47.35107421875,\n 47.39834920035926\n ],\n [\n 41.15478515624999,\n 47.39834920035926\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"80","issue":"6","noUsgsAuthors":false,"publicationDate":"2007-09-25","publicationStatus":"PW","scienceBaseUri":"54dd2c88e4b08de9379b385c","contributors":{"authors":[{"text":"Dando, William A.","contributorId":139116,"corporation":false,"usgs":false,"family":"Dando","given":"William","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":540089,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Gary E.","contributorId":65007,"corporation":false,"usgs":true,"family":"Johnson","given":"Gary E.","affiliations":[],"preferred":false,"id":540090,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70011886,"text":"70011886 - 1981 - Arid land monitoring using Landsat albedo difference images","interactions":[],"lastModifiedDate":"2017-01-18T15:01:30","indexId":"70011886","displayToPublicDate":"1981-01-01T00:00:00","publicationYear":"1981","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":"Arid land monitoring using Landsat albedo difference images","docAbstract":"The Landsat albedo, or percentage of incoming radiation reflected from the ground in the wavelength range of 0.5 [mu]m to 1.1 [mu]m, is calculated from an equation using the Landsat digital brightness values and solar irradiance values, and correcting for atmospheric scattering, multispectral scanner calibration, and sun angle. The albedo calculated for each pixel is used to create an albedo image, whose grey scale is proportional to the albedo. Differencing sequential registered images and mapping selected values of the difference is used to create quantitative maps of increased or decreased albedo values of the terrain. All maps and other output products are in black and white rather than color, thus making the method quite economical. Decreases of albedo in arid regions may indicate improvement of land quality; increases may indicate degradation. Tests of the albedo difference mapping method in the Desert Experimental Range in southwestern Utah (a cold desert with little long-term terrain change) for a four-year period show that mapped changes can be correlated with erosion from flash floods, increased or decreased soil moisture, and increases or decreases in the density of desert vegetation, both perennial shrubs and annual plants. All terrain changes identified in this test were related to variations in precipitation. Although further tests of this method in hot deserts showing severe \"desertification\" are needed, the method is nevertheless recommended for experimental use in monitoring terrain change in other arid and semiarid regions of the world.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Remote Sensing of Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/0034-4257(81)90014-6","issn":"00344257","usgsCitation":"Robinove, C.J., Chavez, P.S., Gehring, D.G., and Holmgren, R., 1981, Arid land monitoring using Landsat albedo difference images: Remote Sensing of Environment, v. 11, p. 133-156, https://doi.org/10.1016/0034-4257(81)90014-6.","productDescription":"24 p.","startPage":"133","endPage":"156","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":221260,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Desert Experimental Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.08203125,\n 37.055177106660814\n ],\n [\n -114.08203125,\n 41.96765920367816\n ],\n [\n -108.984375,\n 41.96765920367816\n ],\n [\n -108.984375,\n 37.055177106660814\n ],\n [\n -114.08203125,\n 37.055177106660814\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059ed77e4b0c8380cd49817","contributors":{"authors":[{"text":"Robinove, Charles J.","contributorId":16983,"corporation":false,"usgs":true,"family":"Robinove","given":"Charles","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":362211,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chavez, Pat S. Jr.","contributorId":39870,"corporation":false,"usgs":true,"family":"Chavez","given":"Pat","suffix":"Jr.","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":362212,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gehring, Dale G.","contributorId":51750,"corporation":false,"usgs":true,"family":"Gehring","given":"Dale","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":362209,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holmgren, Ralph","contributorId":66417,"corporation":false,"usgs":true,"family":"Holmgren","given":"Ralph","email":"","affiliations":[],"preferred":false,"id":362210,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70010322,"text":"70010322 - 1981 - Significant results from using earth observation satellites for mineral and energy resource exploration","interactions":[],"lastModifiedDate":"2017-01-18T15:02:50","indexId":"70010322","displayToPublicDate":"1981-01-01T00:00:00","publicationYear":"1981","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":661,"text":"Advances in Space Research","active":true,"publicationSubtype":{"id":10}},"title":"Significant results from using earth observation satellites for mineral and energy resource exploration","docAbstract":"A large number of Earth-observation satellites orbit our world several times each day, providing new information about the land and sea surfaces and the overlying thin layer of atmosphere that makes our planet unique. Meteorological satellites have had the longest history of experimental use and most are now considered operational. The geologic information collected by the Landsat, Polar Orbiting Geophysical Observatory (POGO), Magsat, Heat Capacity Mapping Mission (HCMM) and Seasat land and ocean observation systems is being thoroughly tested, and some of these systems are now approaching operational use.
\nLandsat multispectral images provide views of large areas of the Earth under uniform lighting conditions and can be obtained at a variety of scales and formats. Not only do the Landsat data provide highly useful images showing surficial materials and structures such as folds and faults, but also measurements and computer-derived ratios of the brightness of different rock types, alteration zones, and mineral associations. These data have led to the finding of a variety of new ore deposits. In addition, the combination of Landsat digital data and aeromagnetic data has extended the use of Landsat as an exploration tool which can be used to readily relate surface features to subsurface anomalies.
\nMagsat data, now being collected, are helping refine information on major crustal anomalies that were first recognized during the analysis of POGO data. The more nearly circular orbit, lower altitude, and increased sophistication of its vector magnetometer enable Magsat to provide more precise information than POGO. Information of this type is required to develop crustal models. Although Magsat is designed to operate for only 4–8 months, the number of orbits that it should be able to make will be sufficient to accomplish its mission and to record a major magnetic storm expected in 1980.
\nHCMM is a two-band visible to near-IR (0.55–1.1 μm) and thermal infrared (10.2–12.5 μm) system designed to measure reflected solar energy, determine the heat capacity of rocks and to monitor soil moisture, thermal effluents, plant canopy temperatures and snow cover. Launched in April 1978, it is in sun-synchronous, circular orbit at an altitude of 620 km. It is a relatively low-resolution system with an instantaneous field of view (IFOV) of 500–600 m and a swath width of 716 km. However, the system is designed to detect objects in the range of 260°–340° K with a sensitivity (NEδT) of 0.4°K at 280°. Recording the thermal radiation of urban heat islands and high thermal inertia of quartzite strata in the Appalachian region are two examples of its land applications.
\nLaunched in June 1978, Seasat operated for only 100 days, but successfully acquired much information over both sea and land. The collection of synthetic aperture radar (SAR) imagery and radar altimetry was particularly important to geologists. Although there are difficulties in processing and distributing these data in a timely manner, initial evaluations indicate that the radar imagery supplements Landsat data by increasing the spectral range and offering a different look angle. The radar altimeter provides accurate profiles over narrow strips of land (1 km wide) and has demonstrated usefulness in measuring icecap surfaces (Greenland, Iceland, and Antarctica). The Salar of Uyuni in southern Bolivia served as a calibration site for the altimeter and has enabled investigators to develop a land-based smoothing algorithm that is believed to increase the accuracy of the system to 10 cm. Data from the altimeter are currently being used to measure subsidence resulting from ground water withdrawal in the Phoenix-Tucson area.
","language":"English","publisher":"Elsevier","doi":"10.1016/0273-1177(81)90402-6","issn":"02731177","usgsCitation":"Carter, W.D., 1981, Significant results from using earth observation satellites for mineral and energy resource exploration: Advances in Space Research, v. 1, no. 10, p. 261-269, https://doi.org/10.1016/0273-1177(81)90402-6.","productDescription":"9 p.","startPage":"261","endPage":"269","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":218640,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":266021,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/0273-1177(81)90402-6"}],"volume":"1","issue":"10","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b8f2de4b08c986b318d89","contributors":{"authors":[{"text":"Carter, William D.","contributorId":64567,"corporation":false,"usgs":true,"family":"Carter","given":"William","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":358640,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70011967,"text":"70011967 - 1981 - Effects of the atmosphere on the detection of surface changes from Landsat multispectral scanner data","interactions":[],"lastModifiedDate":"2017-01-18T15:01:08","indexId":"70011967","displayToPublicDate":"1981-01-01T00:00:00","publicationYear":"1981","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":"Effects of the atmosphere on the detection of surface changes from Landsat multispectral scanner data","docAbstract":"The atmospheric effects on radiometric data recorded in the Landsat multispectral scanner system (MSS) bands are compiled for cases of representative and ideal atmospheric conditions. The effects are expressed as a difference between the Earth's surface spectral reflectivity, a0, and the surface-atmosphere system spectral reflectivity, as, derived from the satellite data,
\nas−a0 = −a0[l+(l/μ0)](B+W) + 2a2 0B + g(μ0)B/2μ0
\nwhere μ0 is the cosine of the solar zenith angle, B and W are the backscattering and absorption optical thickness respectively, and the function g( μ0) is the anisotropy of backscattering to the zenith from the direct beam. This formula is accurate only for an atmosphere of low optical thickness. Also, the equation applies only to large areas having a uniform reflectivity, because adjacency effects due to reflection from the terrain surrounding the object pixel and subsequent scattering by the atmosphere are not considered.
\nIt is concluded that in the quantitative monitoring of surface changes from satellites, scattering effects predominate in some applications (for example, bathy-metric mapping of coastal waters), whereas absorption effects predominate in other applications (for example, monitoring desert fringe areas). Different measurements are more appropriate for assessing the scattering effects than for assessing the absorption effects.
\nThese effects on the monitoring of surface changes by the use of Landsat MSS data are discussed in terms of departures of the actual atmosphere at the time of a satellite passage from a ‘minima’ atmosphere having no aerosols and characterized by gaseous absorption corresponding to minimal water vapour amounts.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/01431168108948369","issn":"01431161","usgsCitation":"Otterman, J., and Robinove, C.J., 1981, Effects of the atmosphere on the detection of surface changes from Landsat multispectral scanner data: International Journal of Remote Sensing, v. 2, no. 4, p. 351-360, https://doi.org/10.1080/01431168108948369.","productDescription":"10 p.","startPage":"351","endPage":"360","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":221485,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","issue":"4","noUsgsAuthors":false,"publicationDate":"2007-05-15","publicationStatus":"PW","scienceBaseUri":"505a07fee4b0c8380cd51915","contributors":{"authors":[{"text":"Otterman, Joseph","contributorId":75683,"corporation":false,"usgs":true,"family":"Otterman","given":"Joseph","email":"","affiliations":[],"preferred":false,"id":362406,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robinove, Charles J.","contributorId":16983,"corporation":false,"usgs":true,"family":"Robinove","given":"Charles","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":362405,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70140589,"text":"70140589 - 1981 - Evaluation of Landsat Multispectral Scanner data for mapping vegetated soil landscapes","interactions":[],"lastModifiedDate":"2019-12-10T14:47:26","indexId":"70140589","displayToPublicDate":"1981-01-01T00:00:00","publicationYear":"1981","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3420,"text":"Soil Science Society of America Journal","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of Landsat Multispectral Scanner data for mapping vegetated soil landscapes","docAbstract":"Landsat multispectral scanner data for Brazos County, Texas, were evaluated in terms of effectiveness for classifying soils on vegetated landscapes at three times during the year: a time of normally adequate soil water, a time of expected soil water deficit, and a time when soil water is normally being replenished. Six test sites were used to evaluate LARSYS supervised and unsupervised classification of vegetated soil landscapes. Open grassland soils were best separated in the fall during a period when soil moisture was being replenished after the summer period of soil water deficit. Woodland soils were separated by Landsat data in late spring when adequate moisture was available. However, a high degree of accuracy was not achieved using Landsat for separating soil map units. Accurate separation of soil mapping units on vegetated landscapes was not possible during late summer when soil water was deficient. Selected soil properties important to plant growth were separable on the test sites using June and October Landsat data. Particle size and soil moisture regime were separated at both dates. Soils with argillic horizons were separated from soils without argillic horizons.
","language":"English","publisher":"Soil Science Society of America","doi":"10.2136/sssaj1981.03615995004500010020x","usgsCitation":"Thompson, D.R., Haas, R.H., and Milford, M.H., 1981, Evaluation of Landsat Multispectral Scanner data for mapping vegetated soil landscapes: Soil Science Society of America Journal, v. 45, no. 1, p. 91-95, https://doi.org/10.2136/sssaj1981.03615995004500010020x.","productDescription":"5 p.","startPage":"91","endPage":"95","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":297874,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","county":"Brazos 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D. R.","contributorId":139146,"corporation":false,"usgs":false,"family":"Thompson","given":"D.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":540205,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haas, Robert H.","contributorId":93388,"corporation":false,"usgs":true,"family":"Haas","given":"Robert","email":"","middleInitial":"H.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":540206,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Milford, M. H.","contributorId":139147,"corporation":false,"usgs":false,"family":"Milford","given":"M.","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":540207,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70139922,"text":"70139922 - 1981 - Use of remote sensing for monitoring deforestation in tropical and subtropical latitudes","interactions":[],"lastModifiedDate":"2017-01-18T15:00:21","indexId":"70139922","displayToPublicDate":"1981-01-01T00:00:00","publicationYear":"1981","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3863,"text":"Ciencia Interamericana","active":true,"publicationSubtype":{"id":10}},"title":"Use of remote sensing for monitoring deforestation in tropical and subtropical latitudes","docAbstract":"Of the three types of remotely sensed data discussed here, Landsat data offers the greatest potential for monitoring broad changes in extensive tropical forest environments because of its low-cost, synoptic, repetitive coverage. Scientists from developing countries can choose from a variety of Landsat data classification techniques, thus enabling each country to satisfy limitations on available funding, trained personnel, and equipment.
\n\n
Factors limiting the application of Landsat data—including relatively low spatial resolution, persistent cloud cover in tropical regions, inadequate coverage of certain areas due to data-acquisition restraints and lack of local Landsat data receiving stations for real-time data recording—must be considered in any proposed study. Future improvements in Landsat capabilities might extend present applications beyond distinction of forest vs. non-forest cover, determination of gross vegetation or forest type, and generalized land use mapping.
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