Land cover is a critical component of the Earth system, infl uencing land-atmosphere interactions, greenhouse gas fl uxes, ecosystem health, and availability of food, fi ber, and energy for human populations. The recent Integrated Global Observations of Land (IGOL) report calls for the generation of maps documenting global land cover at resolutions between 10m and 30m at least every fi ve years (Townshend et al., in press). Moreover, despite 35 years of Landsat observations, there has not been a unifi ed global analysis of land-cover trends nor has there been a global assessment of land-cover change at Landsat-like resolution. Since the 1990s, the National Aeronautics and Space Administration (NASA) and the U.S. Geological Survey (USGS) have supported development of data sets based on global Landsat observations (Tucker et al., 2004). These land survey data sets, usually referred to as GeoCover ™, provide global, orthorectifi ed, typically cloud-free Landsat imagery centered on the years 1975, 1990, and 2000, with a preference for leaf-on conditions. Collectively, these data sets provided a consistent set of observations to assess land-cover changes at a decadal scale. These data are freely available via the Internet from the USGS Center for Earth Resources Observation and Science (EROS) (see http://earthexplorer.usgs.gov or http://glovis.usgs.gov). This has resulted in unprecedented downloads of data, which are widely used in scientifi c studies of land-cover change (e.g., Boone et al., 2007; Harris et al., 2005; Hilbert, 2006; Huang et al. 2007; Jantz et al., 2005, Kim et al., 2007; Leimgruber, 2005; Masek et al., 2006). NASA and USGS are continuing to support land-cover change research through the development of GLS2005 - an additional global Landsat assessment circa 20051 . Going beyond the earlier initiatives, this data set will establish a baseline for monitoring changes on a 5-year interval and will pave the way toward continuous global land-cover monitoring at Landsat-like resolution in the next decade.
","language":"English","publisher":"American Society of Photogrammetry","publisherLocation":"Falls Church, VA","usgsCitation":"Gutman, G., Byrnes, R.A., Masek, J., Covington, S., Justice, C., Franks, S., and Headley, R., 2008, Towards monitoring land-cover and land-use changes at a global scale: the global land survey 2005: Photogrammetric Engineering and Remote Sensing, v. 74, no. 1, p. 6-10.","productDescription":"5 p.","startPage":"6","endPage":"10","numberOfPages":"5","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":307121,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"74","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57fe8811e4b0824b2d149db7","contributors":{"authors":[{"text":"Gutman, G.","contributorId":146850,"corporation":false,"usgs":false,"family":"Gutman","given":"G.","email":"","affiliations":[],"preferred":false,"id":569142,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Byrnes, Raymond A. rbyrnes@usgs.gov","contributorId":4779,"corporation":false,"usgs":true,"family":"Byrnes","given":"Raymond","email":"rbyrnes@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":569143,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Masek, J.","contributorId":88563,"corporation":false,"usgs":true,"family":"Masek","given":"J.","affiliations":[],"preferred":false,"id":569144,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Covington, S.","contributorId":13111,"corporation":false,"usgs":true,"family":"Covington","given":"S.","email":"","affiliations":[],"preferred":false,"id":569145,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Justice, C.","contributorId":146851,"corporation":false,"usgs":false,"family":"Justice","given":"C.","email":"","affiliations":[],"preferred":false,"id":569146,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Franks, S.","contributorId":40803,"corporation":false,"usgs":true,"family":"Franks","given":"S.","email":"","affiliations":[],"preferred":false,"id":569147,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Headley, Rachel rheadley@usgs.gov","contributorId":1744,"corporation":false,"usgs":true,"family":"Headley","given":"Rachel","email":"rheadley@usgs.gov","affiliations":[],"preferred":true,"id":569148,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70204145,"text":"70204145 - 2008 - Detecting changes in riparian habitat conditions based on patterns of greenness change: A case study from the Upper San Pedro River Basin, USA","interactions":[],"lastModifiedDate":"2019-07-09T10:43:23","indexId":"70204145","displayToPublicDate":"2008-01-01T10:29:48","publicationYear":"2008","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Detecting changes in riparian habitat conditions based on patterns of greenness change: A case study from the Upper San Pedro River Basin, USA","docAbstract":"Healthy riparian ecosystems in arid and semi-arid regions exhibit shifting patterns of vegetation in response to periodic flooding. Their conditions also depend upon the amount of grazing and other human uses. Taking advantage of these system properties, we developed and tested an approach that utilizes historical Landsat data to track changes in the patterns of greenness (Normalized Difference Vegetation Index) within riparian zones. We tested the approach in the Upper San Pedro River of southeastern Arizona of the US, an unimpounded river system that flows north into the US from northern Mexico. We evaluated changes in the pattern of greenness in the San Pedro River National Conservation Area (SPRNCA), an area protected from grazing and development since 1988, and in a relatively unprotected area north of the SPRNCA (NA). The SPRNCA exhibited greater positive changes in greenness than did the NA. The SPRNCA also exhibited larger, more continuous patches of positive change than did the NA. These pattern differences may reflect greater pressures from grazing and urban sprawl in the NA than in the SPRNCA, as well as differences in floodplain width, depth to ground water, and base geology. The SPRNCA has greater amounts of ground and surface water available to support a riparian gallery forest than does the NA, and this may have influenced changes during the study period.
Estimates of the direction of greenness change (positive or negative) from satellite imagery were similar to estimates derived from aerial photography, except in areas where changes were from one type of shrub community to another, and in areas with agriculture. Change estimates in these areas may be more difficult because of relatively low greenness values, and because of differences in soil moisture, sun-angle, and crop rotations among the dates of data collection. The potential for applying a satellite-based, greenness change approach to evaluate riparian ecosystem condition over broad geographic areas is also discussed.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2007.01.001","usgsCitation":"Jones, K.B., Edmonds, C.M., Slonecker, E.T., Wickham, J., Neale, A., Wade, T., Riitters, K.H., and Kepner, W., 2008, Detecting changes in riparian habitat conditions based on patterns of greenness change: A case study from the Upper San Pedro River Basin, USA: Ecological Indicators, v. 8, no. 1, p. 89-99, https://doi.org/10.1016/j.ecolind.2007.01.001.","productDescription":"11 p.","startPage":"89","endPage":"99","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":365378,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Upper San Pedro River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.59,\n 31.335\n ],\n [\n -110.59,\n 31.8\n ],\n [\n -109.86328125,\n 31.8\n ],\n [\n -109.86328125,\n 31.335\n ],\n [\n -110.59,\n 31.335\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, K. Bruce","contributorId":66105,"corporation":false,"usgs":true,"family":"Jones","given":"K.","email":"","middleInitial":"Bruce","affiliations":[],"preferred":false,"id":765729,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edmonds, Curtis M.","contributorId":206574,"corporation":false,"usgs":false,"family":"Edmonds","given":"Curtis","email":"","middleInitial":"M.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":765730,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Slonecker, E. Terrence 0000-0002-5793-0503 tslonecker@usgs.gov","orcid":"https://orcid.org/0000-0002-5793-0503","contributorId":168591,"corporation":false,"usgs":true,"family":"Slonecker","given":"E.","email":"tslonecker@usgs.gov","middleInitial":"Terrence","affiliations":[{"id":36171,"text":"National Civil Applications Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":765731,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wickham, James","contributorId":140259,"corporation":false,"usgs":false,"family":"Wickham","given":"James","affiliations":[{"id":12657,"text":"EPA NEIC","active":true,"usgs":false}],"preferred":false,"id":765732,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Neale, Anne","contributorId":43275,"corporation":false,"usgs":true,"family":"Neale","given":"Anne","email":"","affiliations":[],"preferred":false,"id":765733,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wade, Timothy G.","contributorId":48845,"corporation":false,"usgs":true,"family":"Wade","given":"Timothy G.","affiliations":[],"preferred":false,"id":765734,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Riitters, Kurt H. 0000-0003-3901-4453","orcid":"https://orcid.org/0000-0003-3901-4453","contributorId":139788,"corporation":false,"usgs":false,"family":"Riitters","given":"Kurt","email":"","middleInitial":"H.","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":765735,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kepner, William","contributorId":9214,"corporation":false,"usgs":true,"family":"Kepner","given":"William","affiliations":[],"preferred":false,"id":765736,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70031748,"text":"70031748 - 2008 - Mangrove forest distributions and dynamics in Madagascar (1975-2005)","interactions":[],"lastModifiedDate":"2017-04-03T14:04:27","indexId":"70031748","displayToPublicDate":"2008-01-01T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3380,"text":"Sensors","active":true,"publicationSubtype":{"id":10}},"title":"Mangrove forest distributions and dynamics in Madagascar (1975-2005)","docAbstract":"Mangrove forests of Madagascar are declining, albeit at a much slower rate than the global average. The forests are declining due to conversion to other land uses and forest degradation. However, accurate and reliable information on their present distribution and their rates, causes, and consequences of change have not been available. Earlier studies used remotely sensed data to map and, in some cases, to monitor mangrove forests at a local scale. Nonetheless, a comprehensive national assessment and synthesis was lacking. We interpreted time-series satellite data of 1975, 1990, 2000, and 2005 using a hybrid supervised and unsupervised classification approach. Landsat data were geometrically corrected to an accuracy of ?? one-half pixel, an accuracy necessary for change analysis. We used a postclassification change detection approach. Our results showed that Madagascar lost 7% of mangrove forests from 1975 to 2005, to a present extent of ???2,797 km2. Deforestation rates and causes varied both spatially and temporally. The forests increased by 5.6% (212 km2) from 1975 to 1990, decreased by 14.3% (455 km 2) from 1990 to 2000, and decreased by 2.6% (73 km2) from 2000 to 2005. Similarly, major changes occurred in Bombekota Bay, Mahajamba Bay, the coast of Ambanja, the Tsiribihina River, and Cap St Vincent. The main factors responsible for mangrove deforestation include conversion to agriculture (35%), logging (16%), conversion to aquaculture (3%), and urban development (1%). ?? 2008 by MDPI.
","language":"English","publisher":"MDPI","doi":"10.3390/s8042104","issn":"14248220","usgsCitation":"Giri, S., and Muhlhausen, J., 2008, Mangrove forest distributions and dynamics in Madagascar (1975-2005): Sensors, v. 8, no. 4, p. 2104-2117, https://doi.org/10.3390/s8042104.","productDescription":"14 p.","startPage":"2104","endPage":"2117","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":476661,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/s8042104","text":"Publisher Index Page"},{"id":239808,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"4","noUsgsAuthors":false,"publicationDate":"2008-03-27","publicationStatus":"PW","scienceBaseUri":"505a4cc7e4b0c8380cd69ea3","contributors":{"authors":[{"text":"Giri, S.","contributorId":102621,"corporation":false,"usgs":true,"family":"Giri","given":"S.","email":"","affiliations":[],"preferred":false,"id":432954,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Muhlhausen, J.","contributorId":78936,"corporation":false,"usgs":true,"family":"Muhlhausen","given":"J.","email":"","affiliations":[],"preferred":false,"id":432953,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70031849,"text":"70031849 - 2008 - Landsat continuity: Issues and opportunities for land cover monitoring","interactions":[],"lastModifiedDate":"2017-04-03T14:02:00","indexId":"70031849","displayToPublicDate":"2008-01-01T00:00:00","publicationYear":"2008","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":"Landsat continuity: Issues and opportunities for land cover monitoring","docAbstract":"Initiated in 1972, the Landsat program has provided a continuous record of earth observation for 35 years. The assemblage of Landsat spatial, spectral, and temporal resolutions, over a reasonably sized image extent, results in imagery that can be processed to represent land cover over large areas with an amount of spatial detail that is absolutely unique and indispensable for monitoring, management, and scientific activities. Recent technical problems with the two existing Landsat satellites, and delays in the development and launch of a successor, increase the likelihood that a gap in Landsat continuity may occur. In this communication, we identify the key features of the Landsat program that have resulted in the extensive use of Landsat data for large area land cover mapping and monitoring. We then augment this list of key features by examining the data needs of existing large area land cover monitoring programs. Subsequently, we use this list as a basis for reviewing the current constellation of earth observation satellites to identify potential alternative data sources for large area land cover applications. Notions of a virtual constellation of satellites to meet large area land cover mapping and monitoring needs are also presented. Finally, research priorities that would facilitate the integration of these alternative data sources into existing large area land cover monitoring programs are identified. Continuity of the Landsat program and the measurements provided are critical for scientific, environmental, economic, and social purposes. It is difficult to overstate the importance of Landsat; there are no other systems in orbit, or planned for launch in the short-term, that can duplicate or approach replication, of the measurements and information conferred by Landsat. While technical and political options are being pursued, there is no satellite image data stream poised to enter the National Satellite Land Remote Sensing Data Archive should system failures occur to Landsat-5 and -7.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2007.07.004","issn":"00344257","usgsCitation":"Wulder, M., White, J.C., Goward, S., Masek, J.G., Irons, J.R., Herold, M., Cohen, W., Loveland, T., and Woodcock, C.E., 2008, Landsat continuity: Issues and opportunities for land cover monitoring: Remote Sensing of Environment, v. 112, no. 3, p. 955-969, https://doi.org/10.1016/j.rse.2007.07.004.","productDescription":"15 p.","startPage":"955","endPage":"969","numberOfPages":"15","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":242487,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214737,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2007.07.004"}],"volume":"112","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a43d5e4b0c8380cd66654","contributors":{"authors":[{"text":"Wulder, M.A.","contributorId":36287,"corporation":false,"usgs":true,"family":"Wulder","given":"M.A.","email":"","affiliations":[],"preferred":false,"id":433427,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Joanne C.","contributorId":63362,"corporation":false,"usgs":true,"family":"White","given":"Joanne","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":433428,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goward, S.N.","contributorId":94514,"corporation":false,"usgs":true,"family":"Goward","given":"S.N.","affiliations":[],"preferred":false,"id":433432,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Masek, J. G.","contributorId":105883,"corporation":false,"usgs":true,"family":"Masek","given":"J.","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":433433,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Irons, J. R.","contributorId":67694,"corporation":false,"usgs":true,"family":"Irons","given":"J.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":433430,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Herold, M.","contributorId":26533,"corporation":false,"usgs":true,"family":"Herold","given":"M.","email":"","affiliations":[],"preferred":false,"id":433426,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cohen, W.B.","contributorId":64046,"corporation":false,"usgs":true,"family":"Cohen","given":"W.B.","email":"","affiliations":[],"preferred":false,"id":433429,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Loveland, Thomas R. 0000-0003-3114-6646","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":106125,"corporation":false,"usgs":true,"family":"Loveland","given":"Thomas R.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":false,"id":433434,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Woodcock, C. E.","contributorId":93696,"corporation":false,"usgs":false,"family":"Woodcock","given":"C.","email":"","middleInitial":"E.","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":433431,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70032007,"text":"70032007 - 2008 - Detection rates of the MODIS active fire product in the United States","interactions":[],"lastModifiedDate":"2017-04-03T12:31:34","indexId":"70032007","displayToPublicDate":"2008-01-01T00:00:00","publicationYear":"2008","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":"Detection rates of the MODIS active fire product in the United States","docAbstract":"MODIS active fire data offer new information about global fire patterns. However, uncertainties in detection rates can render satellite-derived fire statistics difficult to interpret. We evaluated the MODIS 1??km daily active fire product to quantify detection rates for both Terra and Aqua MODIS sensors, examined how cloud cover and fire size affected detection rates, and estimated how detection rates varied across the United States. MODIS active fire detections were compared to 361 reference fires (??? 18??ha) that had been delineated using pre- and post-fire Landsat imagery. Reference fires were considered detected if at least one MODIS active fire pixel occurred within 1??km of the edge of the fire. When active fire data from both Aqua and Terra were combined, 82% of all reference fires were found, but detection rates were less for Aqua and Terra individually (73% and 66% respectively). Fires not detected generally had more cloudy days, but not when the Aqua data were considered exclusively. MODIS detection rates decreased with fire size, and the size at which 50% of all fires were detected was 105??ha when combining Aqua and Terra (195??ha for Aqua and 334??ha for Terra alone). Across the United States, detection rates were greatest in the West, lower in the Great Plains, and lowest in the East. The MODIS active fire product captures large fires in the U.S. well, but may under-represent fires in areas with frequent cloud cover or rapidly burning, small, and low-intensity fires. We recommend that users of the MODIS active fire data perform individual validations to ensure that all relevant fires are included. ?? 2008 Elsevier Inc. All rights reserved.","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2007.12.008","issn":"00344257","usgsCitation":"Hawbaker, T., Radeloff, V.C., Syphard, A., Zhu, Z., and Stewart, S.I., 2008, Detection rates of the MODIS active fire product in the United States: Remote Sensing of Environment, v. 112, no. 5, p. 2656-2664, https://doi.org/10.1016/j.rse.2007.12.008.","productDescription":"9 p.","startPage":"2656","endPage":"2664","numberOfPages":"9","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":242824,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":215055,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2007.12.008"}],"volume":"112","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059ff7de4b0c8380cd4f20a","contributors":{"authors":[{"text":"Hawbaker, T. J.","contributorId":98118,"corporation":false,"usgs":true,"family":"Hawbaker","given":"T. J.","affiliations":[],"preferred":false,"id":434118,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Radeloff, V. C.","contributorId":58467,"corporation":false,"usgs":false,"family":"Radeloff","given":"V.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":434116,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Syphard, A.D.","contributorId":68950,"corporation":false,"usgs":true,"family":"Syphard","given":"A.D.","email":"","affiliations":[],"preferred":false,"id":434117,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhu, Z.","contributorId":10898,"corporation":false,"usgs":true,"family":"Zhu","given":"Z.","email":"","affiliations":[],"preferred":false,"id":434115,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stewart, S. I.","contributorId":99779,"corporation":false,"usgs":false,"family":"Stewart","given":"S.","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":434119,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70032134,"text":"70032134 - 2008 - Quantifying multi-temporal urban development characteristics in Las Vegas from Landsat and ASTER data","interactions":[],"lastModifiedDate":"2017-04-03T14:07:25","indexId":"70032134","displayToPublicDate":"2008-01-01T00:00:00","publicationYear":"2008","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":"Quantifying multi-temporal urban development characteristics in Las Vegas from Landsat and ASTER data","docAbstract":"Urban development has expanded rapidly in Las Vegas, Nevada of the United States, over the last fifty years. A major environmental change associated with this urbanization trend is the transformation of the landscape from natural cover types to increasingly anthropogenic impervious surface. This research utilizes remote sensing data from both the Landsat and Terra-Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instruments in conjunction with digital orthophotography to estimate urban extent and its temporal changes by determining sub-pixel impervious surfaces. Percent impervious surface area has shown encouraging agreement with urban land extent and development density. Results indicate that total urban land-use increases approximately 110 percent from 1984 to 2002. Most of the increases are associated with medium-to high-density urban development. Places having significant increases in impervious surfaces are in the northwestern and southeastern parts of Las Vegas. Most high-density urban development, however, appears in central Las Vegas. Impervious surface conditions for 2002 measured from Landsat and ASTER satellite data are compared in terms of their accuracy.
","language":"English","publisher":"American Society for Photogrammetry and Remote Sensing","doi":"10.14358/PERS.74.4.473","issn":"00991112","usgsCitation":"Xian, G., Crane, M., and McMahon, C., 2008, Quantifying multi-temporal urban development characteristics in Las Vegas from Landsat and ASTER data: Photogrammetric Engineering and Remote Sensing, v. 74, no. 4, p. 473-481, https://doi.org/10.14358/PERS.74.4.473.","productDescription":"9 p.","startPage":"473","endPage":"481","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":476789,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.14358/pers.74.4.473","text":"Publisher Index Page"},{"id":242666,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"74","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a91d3e4b0c8380cd804a9","contributors":{"authors":[{"text":"Xian, G. 0000-0001-5674-2204","orcid":"https://orcid.org/0000-0001-5674-2204","contributorId":65656,"corporation":false,"usgs":true,"family":"Xian","given":"G.","affiliations":[],"preferred":false,"id":434668,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crane, M.","contributorId":86957,"corporation":false,"usgs":true,"family":"Crane","given":"M.","email":"","affiliations":[],"preferred":false,"id":434669,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McMahon, C.","contributorId":59308,"corporation":false,"usgs":true,"family":"McMahon","given":"C.","email":"","affiliations":[],"preferred":false,"id":434667,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70032142,"text":"70032142 - 2008 - Mangrove forest distributions and dynamics (1975–2005) of the tsunami-affected region of Asia","interactions":[],"lastModifiedDate":"2017-04-03T14:03:20","indexId":"70032142","displayToPublicDate":"2008-01-01T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2193,"text":"Journal of Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Mangrove forest distributions and dynamics (1975–2005) of the tsunami-affected region of Asia","docAbstract":"Aim We aimed to estimate the present extent of tsunami-affected mangrove forests and determine the rates and causes of deforestation from 1975 to 2005.
Location Our study region covers the tsunami-affected coastal areas of Indonesia, Malaysia, Thailand, Burma (Myanmar), Bangladesh, India and Sri Lanka in Asia.
Methods We interpreted time-series Landsat data using a hybrid supervised and unsupervised classification approach. Landsat data were geometrically corrected to an accuracy of plus-or-minus half a pixel, an accuracy necessary for change analysis. Each image was normalized for solar irradiance by converting digital number values to the top-of-the atmosphere reflectance. Ground truth data and existing maps and data bases were used to select training samples and also for iterative labelling. We used a post-classification change detection approach. Results were validated with the help of local experts and/or high-resolution commercial satellite data.
Results The region lost 12% of its mangrove forests from 1975 to 2005, to a present extent of c. 1,670,000 ha. Rates and causes of deforestation varied both spatially and temporally. Annual deforestation was highest in Burma (c. 1%) and lowest in Sri Lanka (0.1%). In contrast, mangrove forests in India and Bangladesh remained unchanged or gained a small percentage. Net deforestation peaked at 137,000 ha during 1990–2000, increasing from 97,000 ha during 1975–90, and declining to 14,000 ha during 2000–05. The major causes of deforestation were agricultural expansion (81%), aquaculture (12%) and urban development (2%).
Main conclusions We assessed and monitored mangrove forests in the tsunami-affected region of Asia using the historical archive of Landsat data. We also measured the rates of change and determined possible causes. The results of our study can be used to better understand the role of mangrove forests in saving lives and property from natural disasters such as the Indian Ocean tsunami, and to identify possible areas for conservation, restoration and rehabilitation.
","language":"English","publisher":"Wiley","doi":"10.1111/j.1365-2699.2007.01806.x","issn":"03050270","usgsCitation":"Giri, S., Zhu, Z., Tieszen, L., Singh, A., Gillette, S., and Kelmelis, J., 2008, Mangrove forest distributions and dynamics (1975–2005) of the tsunami-affected region of Asia: Journal of Biogeography, v. 35, no. 3, p. 519-528, https://doi.org/10.1111/j.1365-2699.2007.01806.x.","productDescription":"10 p.","startPage":"519","endPage":"528","numberOfPages":"10","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":476783,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.1365-2699.2007.01806.x","text":"Publisher Index Page"},{"id":242799,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":215032,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1365-2699.2007.01806.x"}],"volume":"35","issue":"3","noUsgsAuthors":false,"publicationDate":"2007-10-25","publicationStatus":"PW","scienceBaseUri":"505a4cc6e4b0c8380cd69e9d","contributors":{"authors":[{"text":"Giri, S.","contributorId":102621,"corporation":false,"usgs":true,"family":"Giri","given":"S.","email":"","affiliations":[],"preferred":false,"id":434711,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhu, Z.","contributorId":10898,"corporation":false,"usgs":true,"family":"Zhu","given":"Z.","email":"","affiliations":[],"preferred":false,"id":434707,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tieszen, L.L.","contributorId":24046,"corporation":false,"usgs":true,"family":"Tieszen","given":"L.L.","email":"","affiliations":[],"preferred":false,"id":434709,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Singh, A.","contributorId":61211,"corporation":false,"usgs":true,"family":"Singh","given":"A.","affiliations":[],"preferred":false,"id":434710,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gillette, S.","contributorId":107518,"corporation":false,"usgs":true,"family":"Gillette","given":"S.","email":"","affiliations":[],"preferred":false,"id":434712,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kelmelis, J.A.","contributorId":14171,"corporation":false,"usgs":true,"family":"Kelmelis","given":"J.A.","email":"","affiliations":[],"preferred":false,"id":434708,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70032804,"text":"70032804 - 2008 - Modeling mechanisms of vegetation change due to fire in a semi-arid ecosystem","interactions":[],"lastModifiedDate":"2012-03-12T17:21:24","indexId":"70032804","displayToPublicDate":"2008-01-01T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Modeling mechanisms of vegetation change due to fire in a semi-arid ecosystem","docAbstract":"Vegetation growth and community composition in semi-arid environments is determined by water availability and carbon assimilation mechanisms specific to different plant types. Disturbance also impacts vegetation productivity and composition dependent on area affected, intensity, and frequency factors. In this study, a new spatially explicit ecosystem model is presented for the purpose of simulating vegetation cover type changes associated with fire disturbance in the northern Chihuahuan Desert region. The model is called the Landscape and Fire Simulator (LAFS) and represents physiological activity of six functional plant types incorporating site climate, fire, and seed dispersal routines for individual grid cells. We applied this model for Big Bend National Park, Texas, by assessing the impact of wildfire on the trajectory of vegetation communities over time. The model was initialized and calibrated based on landcover maps derived from Landsat-5 Thematic Mapper data acquired in 1986 and 1999 coupled with plant biomass measurements collected in the field during 2000. Initial vegetation cover change analysis from satellite data showed shrub encroachment during this time period that was captured in the simulated results. A synthetic 50-year climate record was derived from historical meteorological data to assess system response based on initial landcover conditions. This simulation showed that shrublands increased to the detriment of grass and yucca-ocotillo vegetation cover types indicating an ecosystem-level trajectory for shrub encroachment. Our analysis of simulated fires also showed that fires significantly reduced site biomass components including leaf area, stem, and seed biomass in this semi-arid ecosystem. In contrast to other landscape simulation models, this new model incorporates detailed physiological responses of functional plant types that will allow us to simulated the impact of increased atmospheric CO2 occurring with climate change coupled with fire disturbance. Simulations generated from this model are expected to be the subject of subsequent studies on landscape dynamics with specific regard to prediction of wildlife distributions associated with fire management and climate change.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecological Modelling","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1016/j.ecolmodel.2008.02.032","issn":"03043800","usgsCitation":"White, J., Gutzwiller, K., Barrow, W., Randall, L., and Swint, P., 2008, Modeling mechanisms of vegetation change due to fire in a semi-arid ecosystem: Ecological Modelling, v. 214, no. 2-4, p. 181-200, https://doi.org/10.1016/j.ecolmodel.2008.02.032.","startPage":"181","endPage":"200","numberOfPages":"20","costCenters":[],"links":[{"id":213900,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ecolmodel.2008.02.032"},{"id":241570,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"214","issue":"2-4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a5c09e4b0c8380cd6f9b0","contributors":{"authors":[{"text":"White, J.D.","contributorId":42923,"corporation":false,"usgs":true,"family":"White","given":"J.D.","email":"","affiliations":[],"preferred":false,"id":437986,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gutzwiller, K.J.","contributorId":78124,"corporation":false,"usgs":true,"family":"Gutzwiller","given":"K.J.","affiliations":[],"preferred":false,"id":437988,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barrow, W.C. 0000-0003-4671-2823","orcid":"https://orcid.org/0000-0003-4671-2823","contributorId":17322,"corporation":false,"usgs":true,"family":"Barrow","given":"W.C.","affiliations":[],"preferred":false,"id":437984,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Randall, L.J.","contributorId":57669,"corporation":false,"usgs":true,"family":"Randall","given":"L.J.","email":"","affiliations":[],"preferred":false,"id":437987,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Swint, P.","contributorId":37968,"corporation":false,"usgs":true,"family":"Swint","given":"P.","affiliations":[],"preferred":false,"id":437985,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70032843,"text":"70032843 - 2008 - Characterizing the marsh dieback spectral response at the plant and canopy level with hyperspectral and temporal remote sensing data","interactions":[],"lastModifiedDate":"2012-03-12T17:21:23","indexId":"70032843","displayToPublicDate":"2008-01-01T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Characterizing the marsh dieback spectral response at the plant and canopy level with hyperspectral and temporal remote sensing data","docAbstract":"We describe newly developed remote sensing tools to map the localized occurrences and regional distribution of the marsh dieback in coastal Louisiana (Fig. 1). As a final goal of our research and development, we identified what spectral features accompanied the onset of dieback and could be directly linked to the optical signal measured at the satellite. In order to accomplish our research goal, we carried out two interlinked objectives. First, we determined the spectral features within the hyperspectral spectra of the impacted plant that could be linked to the spectral return. This was accomplished by measuring the differences in leaf optical properties of impacted and non impacted marsh plants in such a way that the measured differences could be linked to the dieback onset and progression. The spectral analyses were constrained to selected wavelengths (bands of reflectance data) historically associated with changes in leaf composition and structure caused by changes in the plant biophysical environment. Second, we determined what changes in the canopy reflectance (canopy signal sensed at the satellite) could be linked to dieback onset and progression. Third, we transformed a suite of six Landsat Thematic Mapper images collected before, during, and in the final stages of dieback to maps of dieback occurrences. ??2008 IEEE.","largerWorkTitle":"US/EU-Baltic International Symposium: Ocean Observations, Ecosystem-Based Management and Forecasting - Provisional Symposium Proceed","conferenceTitle":"US/EU-Baltic International Symposium: Ocean Observations, Ecosystem-Based Management and Forecasting, BALTIC","conferenceDate":"27 May 2008 through 29 May 2008","conferenceLocation":"Tallinn","language":"English","doi":"10.1109/BALTIC.2008.4625515","isbn":"9781424422685","usgsCitation":"Ramsey, E., and Rangoonwala, A., 2008, Characterizing the marsh dieback spectral response at the plant and canopy level with hyperspectral and temporal remote sensing data, in US/EU-Baltic International Symposium: Ocean Observations, Ecosystem-Based Management and Forecasting - Provisional Symposium Proceed, Tallinn, 27 May 2008 through 29 May 2008, https://doi.org/10.1109/BALTIC.2008.4625515.","costCenters":[],"links":[{"id":213989,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1109/BALTIC.2008.4625515"},{"id":241671,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059f501e4b0c8380cd4c034","contributors":{"authors":[{"text":"Ramsey, E. 0000-0002-4518-5796","orcid":"https://orcid.org/0000-0002-4518-5796","contributorId":91310,"corporation":false,"usgs":true,"family":"Ramsey","given":"E.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":438201,"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":438202,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70033005,"text":"70033005 - 2008 - The Landsat Image Mosaic of Antarctica","interactions":[],"lastModifiedDate":"2018-02-21T12:52:10","indexId":"70033005","displayToPublicDate":"2008-01-01T00:00:00","publicationYear":"2008","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":"The Landsat Image Mosaic of Antarctica","docAbstract":"The Landsat Image Mosaic of Antarctica (LIMA) is the first true-color, high-spatial-resolution image of the seventh continent. It is constructed from nearly 1100 individually selected Landsat-7 ETM+ scenes. Each image was orthorectified and adjusted for geometric, sensor and illumination variations to a standardized, almost seamless surface reflectance product. Mosaicing to avoid clouds produced a high quality, nearly cloud-free benchmark data set of Antarctica for the International Polar Year from images collected primarily during 1999-2003. Multiple color composites and enhancements were generated to illustrate additional characteristics of the multispectral data including: the true appearance of the surface; discrimination between snow and bare ice; reflectance variations within bright snow; recovered reflectance values in regions of sensor saturation; and subtle topographic variations associated with ice flow. LIMA is viewable and individual scenes or user defined portions of the mosaic are downloadable at http://lima.usgs.gov. Educational materials associated with LIMA are available at http://lima.nasa.gov.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2008.07.006","issn":"00344","usgsCitation":"Bindschadler, R., Vornberger, P., Fleming, A., Fox, A., Mullins, J., Binnie, D., Paulsen, S., Granneman, B.J., and Gorodetzky, D., 2008, The Landsat Image Mosaic of Antarctica: Remote Sensing of Environment, v. 112, no. 12, p. 4214-4226, https://doi.org/10.1016/j.rse.2008.07.006.","startPage":"4214","endPage":"4226","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":241080,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213454,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2008.07.006"}],"otherGeospatial":"Antarctica","volume":"112","issue":"12","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505ba7a8e4b08c986b3216f4","contributors":{"authors":[{"text":"Bindschadler, Robert","contributorId":11112,"corporation":false,"usgs":true,"family":"Bindschadler","given":"Robert","email":"","affiliations":[],"preferred":false,"id":438936,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vornberger, P.","contributorId":29648,"corporation":false,"usgs":true,"family":"Vornberger","given":"P.","email":"","affiliations":[],"preferred":false,"id":438928,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fleming, A.","contributorId":103879,"corporation":false,"usgs":true,"family":"Fleming","given":"A.","email":"","affiliations":[],"preferred":false,"id":438935,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fox, A.","contributorId":52405,"corporation":false,"usgs":true,"family":"Fox","given":"A.","email":"","affiliations":[],"preferred":false,"id":438932,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mullins, J.","contributorId":74585,"corporation":false,"usgs":true,"family":"Mullins","given":"J.","email":"","affiliations":[],"preferred":false,"id":438933,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Binnie, D.","contributorId":49187,"corporation":false,"usgs":true,"family":"Binnie","given":"D.","email":"","affiliations":[],"preferred":false,"id":438931,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Paulsen, S.J.","contributorId":84986,"corporation":false,"usgs":true,"family":"Paulsen","given":"S.J.","email":"","affiliations":[],"preferred":false,"id":438934,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Granneman, Brian J. 0000-0002-1910-0955 grann@usgs.gov","orcid":"https://orcid.org/0000-0002-1910-0955","contributorId":4209,"corporation":false,"usgs":true,"family":"Granneman","given":"Brian","email":"grann@usgs.gov","middleInitial":"J.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":438929,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gorodetzky, D.","contributorId":37159,"corporation":false,"usgs":true,"family":"Gorodetzky","given":"D.","email":"","affiliations":[],"preferred":false,"id":438930,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70033067,"text":"70033067 - 2008 - Limited change in dune mobility in response to a large decrease in wind power in semi-arid northern China since the 1970s","interactions":[],"lastModifiedDate":"2012-03-12T17:21:37","indexId":"70033067","displayToPublicDate":"2008-01-01T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Limited change in dune mobility in response to a large decrease in wind power in semi-arid northern China since the 1970s","docAbstract":"The climatic controls on dune mobility, especially the relative importance of wind strength, remain incompletely understood. This is a key research problem in semi-arid northern China, both for interpreting past dune activity as evidence of paleoclimate and for predicting future environmental change. Potential eolian sand transport, which is approximately proportional to wind power above the threshold for sand entrainment, has decreased across much of northern China since the 1970s. Over the same period, effective moisture (ratio of precipitation to potential evapotranspiration) has not changed significantly. This \"natural experiment\" provides insight on the relative importance of wind power as a control on dune mobility in three dunefields of northern China (Mu Us, Otindag, and Horqin), although poorly understood and potentially large effects of human land use complicate interpretation. Dune forms in these three regions are consistent with sand transport vectors inferred from weather station data, suggesting that wind directions have remained stable and the stations adequately represent winds that shaped the dunes. The predicted effect of weaker winds since the 1970s would be dune stabilization, with lower sand transport rates allowing vegetation cover to expand. Large portions of all three dunefields remained stabilized by vegetation in the 1970s despite high wind power. Since the 1970s, trends in remotely sensed vegetation greenness and change in mobile dune area inferred from sequential Landsat images do indicate widespread dune stabilization in the eastern Mu Us region. On the other hand, expansion of active dunes took place farther west in the Mu Us dunefield and especially in the central Otindag dunefield, with little overall change in two parts of the Horqin dunes. Better ground truth is needed to validate the remote sensing analyses, but results presented here place limits on the relative importance of wind strength as a control on dune mobility in the study areas. High wind power alone does not completely destabilize these dunes. A large decrease in wind power either has little short-term effect on the dunes, or more likely its effect is sufficiently small that it is obscured by human impacts on dune stability in many parts of the study areas. ?? 2008 Elsevier B.V. All rights reserved.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geomorphology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1016/j.geomorph.2008.04.004","issn":"01695","usgsCitation":"Mason, J., Swinehart, J.B., Lu, H., Miao, X., Cha, P., and Zhou, Y., 2008, Limited change in dune mobility in response to a large decrease in wind power in semi-arid northern China since the 1970s: Geomorphology, v. 102, no. 3-4, p. 351-363, https://doi.org/10.1016/j.geomorph.2008.04.004.","startPage":"351","endPage":"363","numberOfPages":"13","costCenters":[],"links":[{"id":213421,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.geomorph.2008.04.004"},{"id":241045,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"102","issue":"3-4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a478de4b0c8380cd678c5","contributors":{"authors":[{"text":"Mason, J.A.","contributorId":31507,"corporation":false,"usgs":true,"family":"Mason","given":"J.A.","email":"","affiliations":[],"preferred":false,"id":439238,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swinehart, J. B.","contributorId":25244,"corporation":false,"usgs":true,"family":"Swinehart","given":"J.","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":439237,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lu, H.","contributorId":49936,"corporation":false,"usgs":true,"family":"Lu","given":"H.","email":"","affiliations":[],"preferred":false,"id":439239,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miao, X.","contributorId":60753,"corporation":false,"usgs":true,"family":"Miao","given":"X.","email":"","affiliations":[],"preferred":false,"id":439240,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cha, P.","contributorId":103090,"corporation":false,"usgs":true,"family":"Cha","given":"P.","email":"","affiliations":[],"preferred":false,"id":439242,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zhou, Y.","contributorId":70526,"corporation":false,"usgs":true,"family":"Zhou","given":"Y.","email":"","affiliations":[],"preferred":false,"id":439241,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70033296,"text":"70033296 - 2008 - Comparison of remote sensing image processing techniques to identify tornado damage areas from Landsat TM data","interactions":[],"lastModifiedDate":"2015-08-27T13:20:31","indexId":"70033296","displayToPublicDate":"2008-01-01T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3380,"text":"Sensors","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of remote sensing image processing techniques to identify tornado damage areas from Landsat TM data","docAbstract":"Remote sensing techniques have been shown effective for large-scale damage surveys after a hazardous event in both near real-time or post-event analyses. The paper aims to compare accuracy of common imaging processing techniques to detect tornado damage tracks from Landsat TM data. We employed the direct change detection approach using two sets of images acquired before and after the tornado event to produce a principal component composite images and a set of image difference bands. Techniques in the comparison include supervised classification, unsupervised classification, and objectoriented classification approach with a nearest neighbor classifier. Accuracy assessment is based on Kappa coefficient calculated from error matrices which cross tabulate correctly identified cells on the TM image and commission and omission errors in the result. Overall, the Object-oriented Approach exhibits the highest degree of accuracy in tornado damage detection. PCA and Image Differencing methods show comparable outcomes. While selected PCs can improve detection accuracy 5 to 10%, the Object-oriented Approach performs significantly better with 15-20% higher accuracy than the other two techniques. ?? 2008 by MDPI.
","language":"English","doi":"10.3390/s8021128","issn":"14243210","usgsCitation":"Myint, S., Yuan, M., Cerveny, R., and Giri, C., 2008, Comparison of remote sensing image processing techniques to identify tornado damage areas from Landsat TM data: Sensors, v. 8, no. 2, p. 1128-1156, https://doi.org/10.3390/s8021128.","startPage":"1128","endPage":"1156","numberOfPages":"29","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":476740,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/s8021128","text":"Publisher Index Page"},{"id":240827,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"2","noUsgsAuthors":false,"publicationDate":"2008-02-21","publicationStatus":"PW","scienceBaseUri":"5059f888e4b0c8380cd4d17d","contributors":{"authors":[{"text":"Myint, S.W.","contributorId":18103,"corporation":false,"usgs":true,"family":"Myint","given":"S.W.","affiliations":[],"preferred":false,"id":440208,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yuan, M.","contributorId":20889,"corporation":false,"usgs":true,"family":"Yuan","given":"M.","email":"","affiliations":[],"preferred":false,"id":440210,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cerveny, R.S.","contributorId":18899,"corporation":false,"usgs":true,"family":"Cerveny","given":"R.S.","email":"","affiliations":[],"preferred":false,"id":440209,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Giri, C.P.","contributorId":29647,"corporation":false,"usgs":true,"family":"Giri","given":"C.P.","email":"","affiliations":[],"preferred":false,"id":440211,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70033360,"text":"70033360 - 2008 - Evaluation and comparison of the IRS-P6 and the landsat sensors","interactions":[],"lastModifiedDate":"2017-04-03T12:39:55","indexId":"70033360","displayToPublicDate":"2008-01-01T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1944,"text":"IEEE Transactions on Geoscience and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation and comparison of the IRS-P6 and the landsat sensors","docAbstract":"The Indian Remote Sensing Satellite (IRS-P6), also called ResourceSat-1, was launched in a polar sun-synchronous orbit on October 17, 2003. It carries three sensors: the highresolution Linear Imaging Self-Scanner (LISS-IV), the mediumresolution Linear Imaging Self-Scanner (LISS-III), and the Advanced Wide-Field Sensor (AWiFS). These three sensors provide images of different resolutions 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 images from the Landsat-5 Thematic Mapper (TM) and Landsat-7 Enhanced TM Plus (ETM+) sensors. The approach involves calibration of surface observations based on image statistics from areas observed nearly simultaneously by the two sensors. This paper also evaluated the viability of data from these nextgeneration imagers for use in creating three National Land Cover Dataset (NLCD) products: land cover, percent tree canopy, and percent impervious surface. Individual products were consistent with previous studies but had slightly lower overall accuracies as compared to data from the Landsat sensors.","language":"English","publisher":"IEEE","doi":"10.1109/TGRS.2007.907426","issn":"01962892","usgsCitation":"Chander, G., Coan, M., and Scaramuzza, P.L., 2008, Evaluation and comparison of the IRS-P6 and the landsat sensors: IEEE Transactions on Geoscience and Remote Sensing, v. 46, no. 1, p. 209-221, https://doi.org/10.1109/TGRS.2007.907426.","productDescription":"13 p.","startPage":"209","endPage":"221","numberOfPages":"13","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":241031,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213407,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1109/TGRS.2007.907426"}],"volume":"46","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0c06e4b0c8380cd529da","contributors":{"authors":[{"text":"Chander, G.","contributorId":51449,"corporation":false,"usgs":true,"family":"Chander","given":"G.","affiliations":[],"preferred":false,"id":440498,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coan, M.J.","contributorId":47884,"corporation":false,"usgs":true,"family":"Coan","given":"M.J.","email":"","affiliations":[],"preferred":false,"id":440497,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scaramuzza, P. L. 0000-0002-2616-8456","orcid":"https://orcid.org/0000-0002-2616-8456","contributorId":107504,"corporation":false,"usgs":true,"family":"Scaramuzza","given":"P.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":440499,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70033412,"text":"70033412 - 2008 - Updated radiometric calibration for the Landsat-5 thematic mapper reflective bands","interactions":[],"lastModifiedDate":"2017-05-31T16:22:26","indexId":"70033412","displayToPublicDate":"2008-01-01T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Updated radiometric calibration for the Landsat-5 thematic mapper reflective bands","docAbstract":"The Landsat-5 Thematic Mapper (TM) has been the workhorse of the Landsat system. Launched in 1984, it continues collecting data through the time frame of this paper. Thus, it provides an invaluable link to the past history of the land features of the Earth's surface, and it becomes imperative to provide an accurate radiometric calibration of the reflective bands to the user community. Previous calibration has been based on information obtained from prelaunch, the onboard calibrator, vicarious calibration attempts, and cross-calibration with Landsat-7. Currently, additional data sources are available to improve this calibration. Specifically, improvements in vicarious calibration methods and development of the use of pseudoinvariant sites for trending provide two additional independent calibration sources. The use of these additional estimates has resulted in a consistent calibration approach that ties together all of the available calibration data sources. Results from this analysis indicate a simple exponential, or a constant model may be used for all bands throughout the lifetime of Landsat-5 TM. Where previously time constants for the exponential models were approximately one year, the updated model has significantly longer time constants in bands 1-3. In contrast, bands 4, 5, and 7 are shown to be best modeled by a constant. The models proposed in this paper indicate calibration knowledge of 5% or better early in life, decreasing to nearly 2% later in life. These models have been implemented at the U.S. Geological Survey Earth Resources Observation and Science (EROS) and are the default calibration used for all Landsat TM data now distributed through EROS. ?? 2008 IEEE.","language":"English","publisher":"IEEE","doi":"10.1109/TGRS.2008.920966","issn":"01962","usgsCitation":"Helder, D., Markham, B.L., Thome, K.J., Barsi, J., Chander, G., and Malla, R., 2008, Updated radiometric calibration for the Landsat-5 thematic mapper reflective bands, v. 46, no. 10, p. 3309-3325, https://doi.org/10.1109/TGRS.2008.920966.","productDescription":"17 p.","startPage":"3309","endPage":"3325","numberOfPages":"17","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":240833,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213228,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1109/TGRS.2008.920966"}],"volume":"46","issue":"10","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bbd1be4b08c986b328ecb","contributors":{"authors":[{"text":"Helder, D. L. 0000-0002-7379-4679","orcid":"https://orcid.org/0000-0002-7379-4679","contributorId":51496,"corporation":false,"usgs":true,"family":"Helder","given":"D. L.","affiliations":[],"preferred":false,"id":440768,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Markham, B. L.","contributorId":88872,"corporation":false,"usgs":true,"family":"Markham","given":"B.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":440770,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thome, K. J.","contributorId":88099,"corporation":false,"usgs":true,"family":"Thome","given":"K.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":440769,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barsi, J. A.","contributorId":24085,"corporation":false,"usgs":true,"family":"Barsi","given":"J. A.","affiliations":[],"preferred":false,"id":440766,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chander, G.","contributorId":51449,"corporation":false,"usgs":true,"family":"Chander","given":"G.","affiliations":[],"preferred":false,"id":440767,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Malla, R.","contributorId":9866,"corporation":false,"usgs":true,"family":"Malla","given":"R.","email":"","affiliations":[],"preferred":false,"id":440765,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70033424,"text":"70033424 - 2008 - Satellite remotely-sensed land surface parameters and their climatic effects for three metropolitan regions","interactions":[],"lastModifiedDate":"2017-04-03T14:13:30","indexId":"70033424","displayToPublicDate":"2008-01-01T00:00:00","publicationYear":"2008","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":"Satellite remotely-sensed land surface parameters and their climatic effects for three metropolitan regions","docAbstract":"By using both high-resolution orthoimagery and medium-resolution Landsat satellite imagery with other geospatial information, several land surface parameters including impervious surfaces and land surface temperatures for three geographically distinct urban areas in the United States – Seattle, Washington, Tampa Bay, Florida, and Las Vegas, Nevada, are obtained. Percent impervious surface is used to quantitatively define the spatial extent and development density of urban land use. Land surface temperatures were retrieved by using a single band algorithm that processes both thermal infrared satellite data and total atmospheric water vapor content. Land surface temperatures were analyzed for different land use and land cover categories in the three regions. The heterogeneity of urban land surface and associated spatial extents were shown to influence surface thermal conditions because of the removal of vegetative cover, the introduction of non-transpiring surfaces, and the reduction in evaporation over urban impervious surfaces. Fifty years of in situ climate data were integrated to assess regional climatic conditions. The spatial structure of surface heating influenced by landscape characteristics has a profound influence on regional climate conditions, especially through urban heat island effects.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.asr.2007.11.004","issn":"02731177","usgsCitation":"Xian, G., 2008, Satellite remotely-sensed land surface parameters and their climatic effects for three metropolitan regions: Advances in Space Research, v. 41, no. 11, p. 1861-1869, https://doi.org/10.1016/j.asr.2007.11.004.","productDescription":"9 p.","startPage":"1861","endPage":"1869","numberOfPages":"9","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":240803,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213200,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.asr.2007.11.004"}],"volume":"41","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b86e6e4b08c986b3161bf","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":440818,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70033535,"text":"70033535 - 2008 - Identifying mangrove species and their surrounding land use and land cover classes using object-oriented approach with a lacunarity spatial measure","interactions":[],"lastModifiedDate":"2017-04-03T12:54:02","indexId":"70033535","displayToPublicDate":"2008-01-01T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1722,"text":"GIScience and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Identifying mangrove species and their surrounding land use and land cover classes using object-oriented approach with a lacunarity spatial measure","docAbstract":"Accurate and reliable information on the spatial distribution of mangrove species is needed for a wide variety of applications, including sustainable management of mangrove forests, conservation and reserve planning, ecological and biogeographical studies, and invasive species management. Remotely sensed data have been used for such purposes with mixed results. Our study employed an object-oriented approach with the use of a lacunarity technique to identify different mangrove species and their surrounding land use and land cover classes in a tsunami-affected area of Thailand using Landsat satellite data. Our results showed that the object-oriented approach with lacunarity-transformed bands is more accurate (over-all accuracy 94.2%; kappa coefficient = 0.91) than traditional per-pixel classifiers (overall accuracy 62.8%; and kappa coefficient = 0.57). Copyright ?? 2008 by Bellwether Publishing, Ltd. All rights reserved.","language":"English","publisher":"Taylor & Francis","usgsCitation":"Myint, S., Giri, C., Wang, L., Zhu, Z., and Gillete, S., 2008, Identifying mangrove species and their surrounding land use and land cover classes using object-oriented approach with a lacunarity spatial measure: GIScience and Remote Sensing, v. 45, no. 2, p. 188-208.","productDescription":"21 p.","startPage":"188","endPage":"208","numberOfPages":"21","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":241982,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214277,"rank":9999,"type":{"id":15,"text":"Index Page"},"url":"https://www.tandfonline.com/doi/abs/10.2747/1548-1603.45.2.188"}],"volume":"45","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a384fe4b0c8380cd61510","contributors":{"authors":[{"text":"Myint, S.W.","contributorId":18103,"corporation":false,"usgs":true,"family":"Myint","given":"S.W.","affiliations":[],"preferred":false,"id":441345,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Giri, C.P.","contributorId":29647,"corporation":false,"usgs":true,"family":"Giri","given":"C.P.","email":"","affiliations":[],"preferred":false,"id":441346,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, L.","contributorId":76904,"corporation":false,"usgs":true,"family":"Wang","given":"L.","email":"","affiliations":[],"preferred":false,"id":441348,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhu, Z.","contributorId":10898,"corporation":false,"usgs":true,"family":"Zhu","given":"Z.","email":"","affiliations":[],"preferred":false,"id":441344,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gillete, S.C.","contributorId":51553,"corporation":false,"usgs":true,"family":"Gillete","given":"S.C.","email":"","affiliations":[],"preferred":false,"id":441347,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70033652,"text":"70033652 - 2008 - Reconstructed historical land cover and biophysical parameters for studies of land-atmosphere interactions within the eastern United States","interactions":[],"lastModifiedDate":"2017-04-03T14:10:55","indexId":"70033652","displayToPublicDate":"2008-01-01T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2316,"text":"Journal of Geophysical Research D: Atmospheres","active":true,"publicationSubtype":{"id":10}},"title":"Reconstructed historical land cover and biophysical parameters for studies of land-atmosphere interactions within the eastern United States","docAbstract":"Over the past 350 years, the eastern half of the United States experienced extensive land cover changes. These began with land clearing in the 1600s, continued with widespread deforestation, wetland drainage, and intensive land use by 1920, and then evolved to the present-day landscape of forest regrowth, intensive agriculture, urban expansion, and landscape fragmentation. Such changes alter biophysical properties that are key determinants of land-atmosphere interactions (water, energy, and carbon exchanges). To understand the potential implications of these land use transformations, we developed and analyzed 20-km land cover and biophysical parameter data sets for the eastern United States at 1650, 1850, 1920, and 1992 time slices. Our approach combined potential vegetation, county-level census data, soils data, resource statistics, a Landsat-derived land cover classification, and published historical information on land cover and land use. We reconstructed land use intensity maps for each time slice and characterized the land cover condition. We combined these land use data with a mutually consistent set of biophysical parameter classes, to characterize the historical diversity and distribution of land surface properties. Time series maps of land surface albedo, leaf area index, a deciduousness index, canopy height, surface roughness, and potential saturated soils in 1650, 1850, 1920, and 1992 illustrate the profound effects of land use change on biophysical properties of the land surface. Although much of the eastern forest has returned, the average biophysical parameters for recent landscapes remain markedly different from those of earlier periods. Understanding the consequences of these historical changes will require land-atmosphere interactions modeling experiments.","language":"English","publisher":"AGU Publications","doi":"10.1029/2006JD008277","issn":"01480227","usgsCitation":"Steyaert, L.T., and Knox, R., 2008, Reconstructed historical land cover and biophysical parameters for studies of land-atmosphere interactions within the eastern United States: Journal of Geophysical Research D: Atmospheres, v. 113, no. 2, p. 1-27, https://doi.org/10.1029/2006JD008277.","productDescription":"D02101; 27 p.","startPage":"1","endPage":"27","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":476704,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2006jd008277","text":"Publisher Index Page"},{"id":242290,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214555,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1029/2006JD008277"}],"volume":"113","issue":"2","noUsgsAuthors":false,"publicationDate":"2008-01-16","publicationStatus":"PW","scienceBaseUri":"50e4a24ae4b0e8fec6cdb555","contributors":{"authors":[{"text":"Steyaert, Louis T.","contributorId":24689,"corporation":false,"usgs":true,"family":"Steyaert","given":"Louis","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":441838,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knox, R.G.","contributorId":95690,"corporation":false,"usgs":true,"family":"Knox","given":"R.G.","email":"","affiliations":[],"preferred":false,"id":441839,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70033738,"text":"70033738 - 2008 - Land cover and forest formation distributions for St. Kitts, Nevis, St. Eustatius, Grenada and Barbados from decision tree classification of cloud-cleared satellite imagery","interactions":[],"lastModifiedDate":"2015-08-24T12:50:35","indexId":"70033738","displayToPublicDate":"2008-01-01T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1185,"text":"Caribbean Journal of Science","active":true,"publicationSubtype":{"id":10}},"title":"Land cover and forest formation distributions for St. Kitts, Nevis, St. Eustatius, Grenada and Barbados from decision tree classification of cloud-cleared satellite imagery","docAbstract":"Satellite image-based mapping of tropical forests is vital to conservation planning. Standard methods for automated image classification, however, limit classification detail in complex tropical landscapes. In this study, we test an approach to Landsat image interpretation on four islands of the Lesser Antilles, including Grenada and St. Kitts, Nevis and St. Eustatius, testing a more detailed classification than earlier work in the latter three islands. Secondly, we estimate the extents of land cover and protected forest by formation for five islands and ask how land cover has changed over the second half of the 20th century. The image interpretation approach combines image mosaics and ancillary geographic data, classifying the resulting set of raster data with decision tree software. Cloud-free image mosaics for one or two seasons were created by applying regression tree normalization to scene dates that could fill cloudy areas in a base scene. Such mosaics are also known as cloud-filled, cloud-minimized or cloud-cleared imagery, mosaics, or composites. The approach accurately distinguished several classes that more standard methods would confuse; the seamless mosaics aided reference data collection; and the multiseason imagery allowed us to separate drought deciduous forests and woodlands from semi-deciduous ones. Cultivated land areas declined 60 to 100 percent from about 1945 to 2000 on several islands. Meanwhile, forest cover has increased 50 to 950%. This trend will likely continue where sugar cane cultivation has dominated. Like the island of Puerto Rico, most higher-elevation forest formations are protected in formal or informal reserves. Also similarly, lowland forests, which are drier forest types on these islands, are not well represented in reserves. Former cultivated lands in lowland areas could provide lands for new reserves of drier forest types. The land-use history of these islands may provide insight for planners in countries currently considering lowland forest clearing for agriculture. Copyright 2008 College of Arts and Sciences.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Caribbean Journal of Science","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","issn":"00086","usgsCitation":"Helmer, E., Kennaway, T., Pedreros, D., Clark, M.L., Marcano-Vega, H., Tieszen, L., Ruzycki, T., Schill, S., and Carrington, C., 2008, Land cover and forest formation distributions for St. Kitts, Nevis, St. Eustatius, Grenada and Barbados from decision tree classification of cloud-cleared satellite imagery: Caribbean Journal of Science, v. 44, no. 2, p. 175-198.","startPage":"175","endPage":"198","numberOfPages":"24","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":242031,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":307240,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.caribjsci.org/index.html"}],"volume":"44","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a41a2e4b0c8380cd65690","contributors":{"authors":[{"text":"Helmer, E.H.","contributorId":22213,"corporation":false,"usgs":true,"family":"Helmer","given":"E.H.","email":"","affiliations":[],"preferred":false,"id":442219,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennaway, T.A.","contributorId":68181,"corporation":false,"usgs":true,"family":"Kennaway","given":"T.A.","email":"","affiliations":[],"preferred":false,"id":442224,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pedreros, D.H. 0000-0001-9943-7373","orcid":"https://orcid.org/0000-0001-9943-7373","contributorId":44051,"corporation":false,"usgs":true,"family":"Pedreros","given":"D.H.","affiliations":[],"preferred":false,"id":442223,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clark, M. L.","contributorId":19595,"corporation":false,"usgs":true,"family":"Clark","given":"M.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":442218,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Marcano-Vega, H.","contributorId":101529,"corporation":false,"usgs":true,"family":"Marcano-Vega","given":"H.","email":"","affiliations":[],"preferred":false,"id":442225,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tieszen, L.L.","contributorId":24046,"corporation":false,"usgs":true,"family":"Tieszen","given":"L.L.","email":"","affiliations":[],"preferred":false,"id":442220,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ruzycki, T.R.","contributorId":37217,"corporation":false,"usgs":true,"family":"Ruzycki","given":"T.R.","email":"","affiliations":[],"preferred":false,"id":442222,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schill, S.R.","contributorId":36023,"corporation":false,"usgs":true,"family":"Schill","given":"S.R.","email":"","affiliations":[],"preferred":false,"id":442221,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Carrington, C.M.S.","contributorId":11480,"corporation":false,"usgs":true,"family":"Carrington","given":"C.M.S.","email":"","affiliations":[],"preferred":false,"id":442217,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70010039,"text":"70010039 - 2008 - Evaluation of Landsat-7 SLC-off image products for forest change detection","interactions":[],"lastModifiedDate":"2015-09-11T10:01:10","indexId":"70010039","displayToPublicDate":"2008-01-01T00:00:00","publicationYear":"2008","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":"Evaluation of Landsat-7 SLC-off image products for forest change detection","docAbstract":"Since July 2003, Landsat-7 ETM+ has been operating without the scan line corrector (SLC), which compensates for the forward motion of the satellite in the imagery acquired. Data collected in SLC-off mode have gaps in a systematic wedge-shaped pattern outside of the central 22 km swath of the imagery; however, the spatial and spectral quality of the remaining portions of the imagery are not diminished. To explore the continued use of Landsat-7 ETM+ SLC-off imagery to characterize change in forested environments, we compare the change detection results generated from a reference image pair (a 1999 Landsat-7 ETM+ image and a 2003 Landsat-5 TM image) with change detection results generated from the same 1999 Landsat-7 ETM+ image coupled with three different 2003 Landsat-7 SLC-off products: unremediated SLC-off (i.e., with gaps); histogram-based gap-filled; and segment-based gap-filled. The results are compared on both a pixel and polygon basis; on a pixel basis, the unremediated SLC-off product missed 35% of the change identified by the reference data, and the histogram- and segment-based gap-filled products missed 23% and 21% of the change, respectively. When using forest inventory polygons as a context for change (to reduce commission error), the amount of change missed was 31%, 14%, and 12% for the each of the unremediated, histogram-based gap-filled, and segment-based gap-filled products, respectively. Our results indicate that over the time period considered, and given the types and spatial distribution of change events within our study area, the gap-filled products can provide a useful data source for change detection in forested environments. The selection of which product to use is, however, very dependent on the nature of the application and the spatial configuration of change events. ?? 2008 Government of Canada.
","language":"English","publisher":"Canadian Aeronautics and Space Institute","doi":"10.5589/m08-020","issn":"07038992","usgsCitation":"Wulder, M.A., Ortlepp, S.M., White, J.C., and Maxwell, S., 2008, Evaluation of Landsat-7 SLC-off image products for forest change detection: Canadian Journal of Remote Sensing, v. 34, no. 1-2, p. 93-99, https://doi.org/10.5589/m08-020.","productDescription":"7 p.","startPage":"93","endPage":"99","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":219736,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"34","issue":"1-2","noUsgsAuthors":false,"publicationDate":"2014-06-02","publicationStatus":"PW","scienceBaseUri":"505a0c16e4b0c8380cd52a21","contributors":{"authors":[{"text":"Wulder, Michael A.","contributorId":103584,"corporation":false,"usgs":true,"family":"Wulder","given":"Michael","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":357752,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ortlepp, Stephanie M.","contributorId":28740,"corporation":false,"usgs":true,"family":"Ortlepp","given":"Stephanie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":357750,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"White, Joanne C.","contributorId":63362,"corporation":false,"usgs":true,"family":"White","given":"Joanne","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":357753,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maxwell, Susan","contributorId":30354,"corporation":false,"usgs":true,"family":"Maxwell","given":"Susan","affiliations":[],"preferred":false,"id":357751,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70010009,"text":"70010009 - 2008 - L5 TM radiometric recalibration procedure using the internal calibration trends from the NLAPS trending database","interactions":[],"lastModifiedDate":"2022-05-18T15:31:19.719614","indexId":"70010009","displayToPublicDate":"2008-01-01T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"L5 TM radiometric recalibration procedure using the internal calibration trends from the NLAPS trending database","docAbstract":"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. The multispectral data from the Landsat 5 (L5) Thematic Mapper (TM) sensor provide the backbone for this extensive archive. Historically, the radiometric calibration procedure for this imagery used the instrument's response to the Internal Calibrator (IC) on a scene-by-scene basis to determine the gain and offset for each detector. The IC system degraded with time causing radiometric calibration errors up to 20 percent. In May 2003 the National Landsat Archive Production System (NLAPS) was updated to use a gain model rather than the scene acquisition specific IC gains to calibrate TM data processed in the United States. Further modification of the gain model was performed in 2007. L5 TM data that were processed using IC prior to the calibration update do not benefit from the recent calibration revisions. A procedure has been developed to give users the ability to recalibrate their existing Level-1 products. The best recalibration results are obtained if the work order report that was originally included in the standard data product delivery is available. However, many users may not have the original work order report. In such cases, the IC gain look-up table that was generated using the radiometric gain trends recorded in the NLAPS database can be used for recalibration. This paper discusses the procedure to recalibrate L5 TM data when the work order report originally used in processing is not available. A companion paper discusses the generation of the NLAPS IC gain and bias look-up tables required to perform the recalibration.","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 XIII","conferenceDate":"Aug 11-13, 2008","conferenceLocation":"San Diego, CA","language":"English","publisher":"SPIE","doi":"10.1117/12.795652","usgsCitation":"Chander, G., Haque, M., Micijevic, E., and Barsi, J., 2008, L5 TM radiometric recalibration procedure using the internal calibration trends from the NLAPS trending database, in Proceedings of SPIE - The International Society for Optical Engineering, v. 7081, San Diego, CA, Aug 11-13, 2008, 708114, https://doi.org/10.1117/12.795652.","productDescription":"708114","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":219047,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7081","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a40d3e4b0c8380cd65088","contributors":{"authors":[{"text":"Chander, G.","contributorId":51449,"corporation":false,"usgs":true,"family":"Chander","given":"G.","affiliations":[],"preferred":false,"id":357664,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haque, Md. O. 0000-0002-0914-1446","orcid":"https://orcid.org/0000-0002-0914-1446","contributorId":94784,"corporation":false,"usgs":true,"family":"Haque","given":"Md. O.","affiliations":[],"preferred":false,"id":357666,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":357665,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barsi, J. A.","contributorId":24085,"corporation":false,"usgs":true,"family":"Barsi","given":"J. A.","affiliations":[],"preferred":false,"id":357663,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70010008,"text":"70010008 - 2008 - Development of landsat-5 thematic mapper internal calibrator gain and offset table","interactions":[],"lastModifiedDate":"2012-03-12T17:18:20","indexId":"70010008","displayToPublicDate":"2008-01-01T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Development of landsat-5 thematic mapper internal calibrator gain and offset table","docAbstract":"The National Landsat Archive Production System (NLAPS) has been the primary processing system for Landsat data since U.S. Geological Survey (USGS) Earth Resources Observation and Science Center (EROS) started archiving Landsat data. NLAPS converts raw satellite data into radiometrically and geometrically calibrated products. NLAPS has historically used the Internal Calibrator (IC) to calibrate the reflective bands of the Landsat-5 Thematic Mapper (TM), even though the lamps in the IC were less stable than the TM detectors, as evidenced by vicarious calibration results. In 2003, a major effort was made to model the actual TM gain change and to update NLAPS to use this model rather than the unstable IC data for radiometric calibration. The model coefficients were revised in 2007 to reflect greater understanding of the changes in the TM responsivity. While the calibration updates are important to users with recently processed data, the processing system no longer calculates the original IC gain or offset. For specific applications, it is useful to have a record of the gain and offset actually applied to the older data. Thus, the NLAPS calibration database was used to generate estimated daily values for the radiometric gain and offset that might have been applied to TM data. This paper discusses the need for and generation of the NLAPSIC gain and offset tables. A companion paper covers the application of and errors associated with using these tables.","largerWorkTitle":"Proceedings of SPIE - The International Society for Optical Engineering","conferenceTitle":"Earth Observing Systems XIII","conferenceDate":"11 August 2008 through 13 August 2008","conferenceLocation":"San Diego, CA","language":"English","doi":"10.1117/12.795268","issn":"0277786X","isbn":"9780819473011","usgsCitation":"Barsi, J., Chander, G., Micijevic, E., Markham, B.L., and Haque, M., 2008, Development of landsat-5 thematic mapper internal calibrator gain and offset table, in Proceedings of SPIE - The International Society for Optical Engineering, v. 7081, San Diego, CA, 11 August 2008 through 13 August 2008, https://doi.org/10.1117/12.795268.","costCenters":[],"links":[{"id":204903,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1117/12.795268"},{"id":218988,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7081","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a005ae4b0c8380cd4f6fa","contributors":{"authors":[{"text":"Barsi, J. A.","contributorId":24085,"corporation":false,"usgs":true,"family":"Barsi","given":"J. A.","affiliations":[],"preferred":false,"id":357658,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chander, G.","contributorId":51449,"corporation":false,"usgs":true,"family":"Chander","given":"G.","affiliations":[],"preferred":false,"id":357659,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":357660,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Markham, B. L.","contributorId":88872,"corporation":false,"usgs":true,"family":"Markham","given":"B.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":357661,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haque, Md. O. 0000-0002-0914-1446","orcid":"https://orcid.org/0000-0002-0914-1446","contributorId":94784,"corporation":false,"usgs":true,"family":"Haque","given":"Md. O.","affiliations":[],"preferred":false,"id":357662,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70010007,"text":"70010007 - 2008 - Radiometric cross-calibration of the Terra MODIS and Landsat 7 ETM+ using an invariant desert site","interactions":[],"lastModifiedDate":"2022-05-19T11:10:31.983008","indexId":"70010007","displayToPublicDate":"2008-01-01T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Radiometric cross-calibration of the Terra MODIS and Landsat 7 ETM+ using an invariant desert site","docAbstract":"A methodology for long-term radiometric cross-calibration between the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) sensors was developed. The approach involves calibration of near-simultaneous surface observations between 2000 and 2007. Fifty-seven cloud-free image pairs were carefully selected over the Libyan desert for this study. The Libyan desert site (+28.55??, +23.39??), located in northern Africa, is a high reflectance site with high spatial, spectral, and temporal uniformity. Because the test site covers about 12 kmx13 km, accurate geometric preprocessing is required to match the footprint size between the two sensors to avoid uncertainties due to residual image misregistration. MODIS Level IB radiometrically corrected products were reprojected to the corresponding ETM+ image's Universal Transverse Mercator (UTM) grid projection. The 30 m pixels from the ETM+ images were aggregated to match the MODIS spatial resolution (250 m in Bands 1 and 2, or 500 m in Bands 3 to 7). The image data from both sensors were converted to absolute units of at-sensor radiance and top-ofatmosphere (TOA) reflectance for the spectrally matching band pairs. For each band pair, a set of fitted coefficients (slope and offset) is provided to quantify the relationships between the testing sensors. This work focuses on long-term stability and correlation of the Terra MODIS and L7 ETM+ sensors using absolute calibration results over the entire mission of the two sensors. Possible uncertainties are also discussed such as spectral differences in matching band pairs, solar zenith angle change during a collection, and differences in solar irradiance models.","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 XIII","conferenceDate":"August 11-13, 2008","conferenceLocation":"San Diego, CA","language":"English","publisher":"SPIE","doi":"10.1117/12.793829","usgsCitation":"Choi, T., Angal, A., Chander, G., and Xiong, X., 2008, Radiometric cross-calibration of the Terra MODIS and Landsat 7 ETM+ using an invariant desert site, in Proceedings of SPIE - The International Society for Optical Engineering, v. 7081, San Diego, CA, August 11-13, 2008, 708110, https://doi.org/10.1117/12.793829.","productDescription":"708110","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":218987,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7081","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a9410e4b0c8380cd811a2","contributors":{"authors":[{"text":"Choi, T.","contributorId":48698,"corporation":false,"usgs":true,"family":"Choi","given":"T.","affiliations":[],"preferred":false,"id":357655,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Angal, A.","contributorId":52716,"corporation":false,"usgs":true,"family":"Angal","given":"A.","affiliations":[],"preferred":false,"id":357657,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chander, G.","contributorId":51449,"corporation":false,"usgs":true,"family":"Chander","given":"G.","affiliations":[],"preferred":false,"id":357656,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Xiong, X.","contributorId":37885,"corporation":false,"usgs":true,"family":"Xiong","given":"X.","affiliations":[],"preferred":false,"id":357654,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70009743,"text":"70009743 - 2008 - Categorizing natural disaster damage assessment using satellite-based geospatial techniques","interactions":[],"lastModifiedDate":"2017-04-03T11:59:20","indexId":"70009743","displayToPublicDate":"2008-01-01T00:00:00","publicationYear":"2008","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2824,"text":"Natural Hazards and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Categorizing natural disaster damage assessment using satellite-based geospatial techniques","docAbstract":"Remote sensing of a natural disaster's damage offers an exciting backup and/or alternative to traditional means of on-site damage assessment. Although necessary for complete assessment of damage areas, ground-based damage surveys conducted in the aftermath of natural hazard passage can sometimes be potentially complicated due to on-site difficulties (e.g., interaction with various authorities and emergency services) and hazards (e.g., downed power lines, gas lines, etc.), the need for rapid mobilization (particularly for remote locations), and the increasing cost of rapid physical transportation of manpower and equipment. Satellite image analysis, because of its global ubiquity, its ability for repeated independent analysis, and, as we demonstrate here, its ability to verify on-site damage assessment provides an interesting new perspective and investigative aide to researchers. Using one of the strongest tornado events in US history, the 3 May 1999 Oklahoma City Tornado, as a case example, we digitized the tornado damage path and co-registered the damage path using pre- and post-Landsat Thematic Mapper image data to perform a damage assessment. We employed several geospatial approaches, specifically the Getis index, Geary's C, and two lacunarity approaches to categorize damage characteristics according to the original Fujita tornado damage scale (F-scale). Our results indicate strong relationships between spatial indices computed within a local window and tornado F-scale damage categories identified through the ground survey. Consequently, linear regression models, even incorporating just a single band, appear effective in identifying F-scale damage categories using satellite imagery. This study demonstrates that satellite-based geospatial techniques can effectively add spatial perspectives to natural disaster damages, and in particular for this case study, tornado damages.","language":"English","publisher":"European Geosciences Union","doi":"10.5194/nhess-8-707-2008","issn":"15618633","usgsCitation":"Myint, S., Yuan, M., Cerveny, R., and Giri, S., 2008, Categorizing natural disaster damage assessment using satellite-based geospatial techniques: Natural Hazards and Earth System Sciences, v. 8, no. 4, p. 707-719, https://doi.org/10.5194/nhess-8-707-2008.","productDescription":"13 p.","startPage":"707","endPage":"719","numberOfPages":"13","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":476767,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/nhess-8-707-2008","text":"Publisher Index Page"},{"id":218905,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":267913,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.5194/nhess-8-707-2008"}],"volume":"8","issue":"4","noUsgsAuthors":false,"publicationDate":"2008-07-17","publicationStatus":"PW","scienceBaseUri":"5059f3cee4b0c8380cd4b98b","contributors":{"authors":[{"text":"Myint, S.W.","contributorId":18103,"corporation":false,"usgs":true,"family":"Myint","given":"S.W.","affiliations":[],"preferred":false,"id":357033,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yuan, M.","contributorId":20889,"corporation":false,"usgs":true,"family":"Yuan","given":"M.","email":"","affiliations":[],"preferred":false,"id":357035,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cerveny, R.S.","contributorId":18899,"corporation":false,"usgs":true,"family":"Cerveny","given":"R.S.","email":"","affiliations":[],"preferred":false,"id":357034,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Giri, S.","contributorId":102621,"corporation":false,"usgs":true,"family":"Giri","given":"S.","email":"","affiliations":[],"preferred":false,"id":357036,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}