Sample records for significant results landsat

  1. Users, uses, and value of Landsat satellite imagery: results from the 2012 survey of users (United States)

    Miller, Holly M.; Richardson, Leslie A.; Koontz, Stephen R.; Loomis, John; Koontz, Lynne


    Landsat satellites have been operating since 1972, providing a continuous global record of the Earth’s land surface. The imagery is currently available at no cost through the U.S. Geological Survey (USGS). Social scientists at the USGS Fort Collins Science Center conducted an extensive survey in early 2012 to explore who uses Landsat imagery, how they use the imagery, and what the value of the imagery is to them. The survey was sent to all users registered with USGS who had accessed Landsat imagery in the year prior to the survey and over 11,000 current Landsat imagery users responded. The results of the survey revealed that respondents from many sectors use Landsat imagery in myriad project locations and scales, as well as application areas. The value of Landsat imagery to these users was demonstrated by the high importance of and dependence on the imagery, the numerous environmental and societal benefits observed from projects using Landsat imagery, the potential negative impacts on users’ work if Landsat imagery was no longer available, and the substantial aggregated annual economic benefit from the imagery. These results represent only the value of Landsat to users registered with USGS; further research would help to determine what the value of the imagery is to a greater segment of the population, such as downstream users of the imagery and imagery-derived products.

  2. Significance of operator variation and the angle of illumination in lineament analysis on synoptic images. [LANDSAT geological investigations (United States)

    Siegal, B. S.; Short, N. M.


    The significance of operator variation and the angle of illumination in acquired imagery is analyzed for lineament analysis. Five operators analyzed a LANDSAT image and four photographs of a plastic relief map illuminated at a low angle from varying directions of the Prescott, Arizona region. Significant differences were found in both number and length of the lineaments recognized by the different investigators for the images. The actual coincidence of lineaments recognized by the investigators for the same image is exceptionally low. Even the directional data on lineament orientation is significantly different from operator to operator and from image to image. Cluster analysis of the orientation data displays a clustering by operators rather than by images. It is recommended that extreme caution be taken before attempting to compare different investigators' results in lineament analysis.

  3. Assessing the value of Landsat imagery: Results from a 2012 comprehensive user survey (United States)

    Miller, H. M.; Richardson, L.; Loomis, J.; Koontz, S.; Koontz, L.


    Landsat satellite imagery has long been recognized as unique among remotely sensed data due to the combination of its extensive archive, global coverage, and relatively high spatial and temporal resolution. Since the imagery became available at no cost in 2008, the number of users registered with the U.S. Geological Survey (USGS) has increased tenfold while the number of scenes downloaded annually has increased a hundredfold. It is clear that the imagery is being used extensively, and understanding the benefits provided by this imagery can help inform decisions involving its provision. However, the value of Landsat imagery is difficult to measure for a variety of reasons, one of which stems from the fact that the imagery has characteristics of a public good and does not have a direct market price to reflect its value to society. Further, there is not a clear understanding of the full range of users of the imagery, as well as how these users are distributed across the many different end uses this data is applied to. To assess the value of Landsat imagery, we conducted a survey of users registered with USGS in early 2012. Over 11,000 current users of Landsat imagery responded to the survey. The value of the imagery was measured both qualitatively and quantitatively. To explore the qualitative value of the imagery, users were asked about the importance of the imagery to their work, their dependence on the imagery, and the impacts on their work if there was no Landsat imagery. The majority of users deemed Landsat imagery important to their work and stated they were dependent on Landsat imagery to do their work. Additionally, if Landsat imagery was no longer available, over half of the users would have to discontinue some of their work. On average, these users would discontinue half of their current work if the imagery was no longer available. The focus of this presentation will be the quantitative results of a double-bounded contingent valuation analysis which reveals

  4. Continuous fields of land cover for the conterminous United States using Landsat data: First results from the Web-Enabled Landsat Data (WELD) project (United States)

    Hansen, M.C.; Egorov, Alexey; Roy, David P.; Potapov, P.; Ju, J.; Turubanova, S.; Kommareddy, I.; Loveland, Thomas R.


    Vegetation Continuous Field (VCF) layers of 30 m percent tree cover, bare ground, other vegetation and probability of water were derived for the conterminous United States (CONUS) using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data sets from the Web-Enabled Landsat Data (WELD) project. Turnkey approaches to land cover characterization were enabled due to the systematic WELD Landsat processing, including conversion of digital numbers to calibrated top of atmosphere reflectance and brightness temperature, cloud masking, reprojection into a continental map projection and temporal compositing. Annual, seasonal and monthly WELD composites for 2008 were used as spectral inputs to a bagged regression and classification tree procedure using a large training data set derived from very high spatial resolution imagery and available ancillary data. The results illustrate the ability to perform Landsat land cover characterizations at continental scales that are internally consistent while retaining local spatial and thematic detail.

  5. The Landsat Phenology Study (LaPS): Preliminary CONUS Results for 2008 (United States)

    Henebry, Geoffrey M.; Roy, David P.; Ju, Junchang; Kovalskyy, Valeriy


    Most studies of land surface phenology (LSP) have used time series derived from moderate spatial resolution satellite sensor data (e.g., AVHRR, MODIS, VEGETATION) because these data are freely available and because they provide an acceptable trade-off between higher, near daily, temporal frequency of observation needed to reduce cloud contamination against lower (500m-5km) spatial resolution. The recent opening of the USGS Landsat archive to web-enabled access presents the opportunity to explore how well Landsat time series can portray LSPs at high spatial resolution. The NASA Web-enabled Landsat data (WELD) project ( has produced 30m composited mosaics for all the conterminous US (CONUS) from Landsat 7 ETM+ data. The composited mosaics are generated on monthly, seasonal, and annual basis and include spectral reflectance, normalized difference vegetation index (NDVI), and the acquisition date of each composited pixel. The WELD compositing approach is designed to select valid land surface observations with minimal cloud, snow, and atmospheric contamination. We extracted 30m pixel time series from the twelve monthly WELD composited mosaics for 2008 at 320 locations across the CONUS where we have ground phenological observations that are heterogeneous with respect to the types of plants observed, the phenophases recorded (predominantly spring green-up) and the ground sampling protocols used. The ground data came from several sources, including the cloned lilac/honeysuckle network, the Phenocam network, five LTER sites (H.J. Andrews, Harvard Forest, Jornada, Konza Prairie, and Sevilleta), and a private woodlot in Maine. Temporal profiles of the 30m WELD Landsat NDVI, the green NDVI (GNDVI), the normalized difference infrared index (NDII) derived from the composited reflectances, are compared to the ground observations. Results show that (i) inclusion of the Landsat acquisition date for each pixel improves the characterization of the LSP

  6. Results of agriclimatological studies using multiple satellite sensors like NOAA AVHRR; GMS IR and LANDSAT MSS and TM

    International Nuclear Information System (INIS)

    Choudhury, A.M.


    Bangladesh Space Research and Remote Sensing Organization (SPARRSO) routinely receives NOAA and GMS imagery and uses them in agrometeorological monitoring, it also uses LANDSAT MSS and TM data for this purpose. Analysis of multiple satellite sensor data shows advantages for high resolution sensors. However, in the ease of crop monitoring, a good correlation has been obtained between results obtained with NOAA AVHRR and LANDSAT MSS for vegetation index. Crop estimation has been made using all kinds of sensors and it has been found that higher resolution data always give more accurate results. (author). 3 refs

  7. Development of computer software to analyze entire LANDSAT scenes and to summarize classification results of variable-size polygons (United States)

    Turner, B. J. (Principal Investigator); Baumer, G. M.; Myers, W. L.; Sykes, S. G.


    The Forest Pest Management Division (FPMD) of the Pennsylvania Bureau of Forestry has the responsibility for conducting annual surveys of the State's forest lands to accurately detect, map, and appraise forest insect infestations. A standardized, timely, and cost-effective method of accurately surveying forests and their condition should enhance the probability of suppressing infestations. The repetitive and synoptic coverage provided by LANDSAT (formerly ERTS) makes such satellite-derived data potentially attractive as a survey medium for monitoring forest insect damage over large areas. Forest Pest Management Division personnel have expressed keen interest in LANDSAT data and have informally cooperated with NASA/Goddard Space Flight Center (GSFC) since 1976 in the development of techniques to facilitate their use. The results of this work indicate that it may be feasible to use LANDSAT digital data to conduct annual surveys of insect defoliation of hardwood forests.

  8. The impact of landsat satellite monitoring on conservation biology. (United States)

    Leimgruber, Peter; Christen, Catherine A; Laborderie, Alison


    Landsat 7's recent malfunctioning will result in significant gaps in long-term satellite monitoring of Earth, affecting not only the research of the Earth science community but also conservation users of these data. To determine whether or how important Landsat monitoring is for conservation and natural resource management, we reviewed the Landsat program's history with special emphasis on the development of user groups. We also conducted a bibliographic search to determine the extent to which conservation research has been based on Landsat data. Conservation biologists were not an early user group of Landsat data because a) biologists lacked technical capacity--computers and software--to analyze these data; b) Landsat's 1980s commercialization rendered images too costly for biologists' budgets; and c) the broad-scale disciplines of conservation biology and landscape ecology did not develop until the mid-to-late 1980s. All these conditions had changed by the 1990s and Landsat imagery became an important tool for conservation biology. Satellite monitoring and Landsat continuity are mandated by the Land Remote Sensing Act of 1992. This legislation leaves open commercial options. However, past experiments with commercial operations were neither viable nor economical, and severely reduced the quality of monitoring, archiving and data access for academia and the public. Future satellite monitoring programs are essential for conservation and natural resource management, must provide continuity with Landsat, and should be government operated.

  9. Landsat Program (United States)

    Markham, Brian L.; Arvidson, Terry; Barsi, Julia A.; Choate, Michael; Kaita, Edward; Levy, Raviv; Lubke, Mark; Masek, Jeffrey G.


    Landsat initiated the revolution in moderate resolution Earth remote sensing in the 1970s. With seven successful missions over 40+ years, Landsat has documented - and continues to document - the global Earth land surface and its evolution. The Landsat missions and sensors have evolved along with the technology from a demonstration project in the analog world of visual interpretation to an operational mission in the digital world, with incremental improvements along the way in terms of spectral, spatial, radiometric and geometric performance as well as acquisition strategy, data availability, and products.

  10. Transformations of Mangrove Forests in Bahia Magdalena, Baja California Sur, Mexico: Two Decade Results Based on Landsat Imageries (United States)

    Suresh Babu, S.; Abdul Rahaman, S.; Muthushankar, G.; Jonathan, M. P.


    Mangrove forests which thrive along the tropical and subtropical regions are the most productive ecosystems in the world with a wide range of ecological and economical services to mankind. With the rapid urbanization across the globe, these forests tend to be destroying at an alarming rate. The area of concern for this study, Bahia Magdalena is very important for the economy of the state as nearly 50% of the artisan fisheries are established in the mangrove zone. Henceforth this study is an attempt for a regional assessment and to accurately quantify the mangroves using LANDSAT imageries for over two decades in Bahia Magdalena, Baja California. Satellite imageries from the year 1986 through 2014 were analysed to assess the prolonged changes taking place in and around the mangrove reserve. Using the estimates of land use/cover for all the years, the spatio - temporal data was validated using ArcGIS software. The results revealed that the spatial extent of mangroves are decreasing until 2005 due to the developmental plans such as tourism, shrimp farming and establishment of industries in this part of the country. During the past 10 years (~ after 2005) there is no much change in the area extent of mangrove reserves due to afforestation and conservation efforts. Thus the unbiased dataset generated may be widely used for an improved understanding of the role of mangrove forests in the socio economic aspects, protection from natural disasters, identify possible areas for conservation, restoration and rehabilitation; and improve estimates of the amount of carbon stored in mangrove vegetation and the associated marine environment. Keywords: Mangroves, LANDSAT, Bahia Magdalena, México.

  11. Are studies reporting significant results more likely to be published? (United States)

    Koletsi, Despina; Karagianni, Anthi; Pandis, Nikolaos; Makou, Margarita; Polychronopoulou, Argy; Eliades, Theodore


    Our objective was to assess the hypothesis that there are variations of the proportion of articles reporting a significant effect, with a higher percentage of those articles published in journals with impact factors. The contents of 5 orthodontic journals (American Journal of Orthodontics and Dentofacial Orthopedics, Angle Orthodontist, European Journal of Orthodontics, Journal of Orthodontics, and Orthodontics and Craniofacial Research), published between 2004 and 2008, were hand-searched. Articles with statistical analysis of data were included in the study and classified into 4 categories: behavior and psychology, biomaterials and biomechanics, diagnostic procedures and treatment, and craniofacial growth, morphology, and genetics. In total, 2622 articles were examined, with 1785 included in the analysis. Univariate and multivariate logistic regression analyses were applied with statistical significance as the dependent variable, and whether the journal had an impact factor, the subject, and the year were the independent predictors. A higher percentage of articles showed significant results relative to those without significant associations (on average, 88% vs 12%) for those journals. Overall, these journals published significantly more studies with significant results, ranging from 75% to 90% (P = 0.02). Multivariate modeling showed that journals with impact factors had a 100% increased probability of publishing a statistically significant result compared with journals with no impact factor (odds ratio [OR], 1.99; 95% CI, 1.19-3.31). Compared with articles on biomaterials and biomechanics, all other subject categories showed lower probabilities of significant results. Nonsignificant findings in behavior and psychology and diagnosis and treatment were 1.8 (OR, 1.75; 95% CI, 1.51-2.67) and 3.5 (OR, 3.50; 95% CI, 2.27-5.37) times more likely to be published, respectively. Journals seem to prefer reporting significant results; this might be because of authors

  12. Continuity of Landsat observations: Short term considerations (United States)

    Wulder, Michael A.; White, Joanne C.; Masek, Jeffery G.; Dwyer, John L.; Roy, David P.


    As of writing in mid-2010, both Landsat-5 and -7 continue to function, with sufficient fuel to enable data collection until the launch of the Landsat Data Continuity Mission (LDCM) scheduled for December of 2012. Failure of one or both of Landsat-5 or -7 may result in a lack of Landsat data for a period of time until the 2012 launch. Although the potential risk of a component failure increases the longer the sensor's design life is exceeded, the possible gap in Landsat data acquisition is reduced with each passing day and the risk of Landsat imagery being unavailable diminishes for all except a handful of applications that are particularly data demanding. Advances in Landsat data compositing and fusion are providing opportunities to address issues associated with Landsat-7 SLC-off imagery and to mitigate a potential acquisition gap through the integration of imagery from different sensors. The latter will likely also provide short-term, regional solutions to application-specific needs for the continuity of Landsat-like observations. Our goal in this communication is not to minimize the community's concerns regarding a gap in Landsat observations, but rather to clarify how the current situation has evolved and provide an up-to-date understanding of the circumstances, implications, and mitigation options related to a potential gap in the Landsat data record.

  13. Summary of the most significant results reported in this session

    CERN Document Server

    Sens, J C


    D1e most interesting although speculative result is the observation of a 4 standard deviation effect at 5. 3 GeV in the l)JK 0TI - and lj!K- 'ff+ mass plots (SPS Exp. WJ\\11) with a crosssection of 180 nb (assuming 1 % branching ratio). This is a cancliclatc bare b-state. + Tiw next most significant experimental result is the observation of Ac at the CERN Intersecting Storage Rings (ISR). TI1is state was discovered at BNL by Samios et al. and has since been seen in several neutrino experiments. It was seen at the ISR by Lockman ct al. about a year ago (reported at Budapest) but not in a convincing way. The analysis has now been improved, and the result shows a peak which is most clearly present in the stnnmed A(31T)+ and K-p1T+ mass spectra. 'TI1e signal has furthennore been seen in Exp. R606 (reported - + by F. Muller in this parallel session) in both A3TI and pK TI . 111e most convincing signal comes from the Spli t-Ficlcl Magnet (SFM) in K-pn + 'TI1e three observations together, all at the ISR, make this an...

  14. Estimation of the genetically significant dose resulting from diagnostic radiology

    International Nuclear Information System (INIS)

    Angerstein, W.


    Based on the average gonad dose received per examination or per film and on the frequency of x-ray examinations (36 million per annum), the mean annual gonad dose to individuals in the GDR has been determined to be 33 mR. Considering different age groups of patients and the fact that the gonad dose to children is often significantly reduced in comparison to adults, estimates of the genetically significant dose (GSD) range from 7 to 19 mR per annum. Examinations of women have accounted for about 66 per cent of the GSD. The highest contribution to the GSD result from examinations of the following organs: kidneys, colon, bile duct (only in women), lumbar spine, pelois, hips, and proximal femur. Despite their high frequency, examinations of the stomach account for only about 3 per cent of the GSD. All thorax examinations (nearly 10,000,000 per annum) contribute less than 0.5 per cent, and the most frequent x-ray examinations of the skeletal system, skull, cervical spine, and teeth account for less than 3 per cent. The GSD values obtained are comparable with those from countries such as India, Japan, Netherlands, USSR, and USA. (author)

  15. The global Landsat archive: Status, consolidation, and direction (United States)

    Wulder, Michael A.; White, Joanne C.; Loveland, Thomas; Woodcock, Curtis; Belward, Alan; Cohen, Warren B.; Fosnight, Eugene A.; Shaw, Jerad; Masek, Jeffery G.; Roy, David P.


    New and previously unimaginable Landsat applications have been fostered by a policy change in 2008 that made analysis-ready Landsat data free and open access. Since 1972, Landsat has been collecting images of the Earth, with the early years of the program constrained by onboard satellite and ground systems, as well as limitations across the range of required computing, networking, and storage capabilities. Rather than robust on-satellite storage for transmission via high bandwidth downlink to a centralized storage and distribution facility as with Landsat-8, a network of receiving stations, one operated by the U.S. government, the other operated by a community of International Cooperators (ICs), were utilized. ICs paid a fee for the right to receive and distribute Landsat data and over time, more Landsat data was held outside the archive of the United State Geological Survey (USGS) than was held inside, much of it unique. Recognizing the critical value of these data, the USGS began a Landsat Global Archive Consolidation (LGAC) initiative in 2010 to bring these data into a single, universally accessible, centralized global archive, housed at the Earth Resources Observation and Science (EROS) Center in Sioux Falls, South Dakota. The primary LGAC goals are to inventory the data held by ICs, acquire the data, and ingest and apply standard ground station processing to generate an L1T analysis-ready product. As of January 1, 2015 there were 5,532,454 images in the USGS archive. LGAC has contributed approximately 3.2 million of those images, more than doubling the original USGS archive holdings. Moreover, an additional 2.3 million images have been identified to date through the LGAC initiative and are in the process of being added to the archive. The impact of LGAC is significant and, in terms of images in the collection, analogous to that of having had twoadditional Landsat-5 missions. As a result of LGAC, there are regions of the globe that now have markedly improved


    Directory of Open Access Journals (Sweden)

    E. S. Vdovin


    Full Text Available Thestudy presents the results of an assessment of forest cover of the territories of the republics of Mordovia and Mari El on the color classification results of multispectral Landsat 8 in comparison with the data of the state register of forests. The study highlights the problem of transformation of the structure of land due to natural afforestation of agricultural land. Emphasized the importance of managing the recovery process "wildlife" in the regions of compact residence of the Finno-Ugric peoples using the methods of ecological planning of land for the purpose of solving the reconstruction of the ethnic environment of the Finno-Ugric peoples.

  17. Landsat-D thematic mapper simulator (United States)

    Flanagan, G. F.; Tilton, E. L., III

    The design and testing program for the airborne Landsat-D thematic-mapper simulator (TMS) is summarized. The TMS is intended to provide data similar enough to those expected from Landsat-D to facilitate the development of data-processing software. The design process comprised mainly modifications on the existing MSS-simulator fiber optics, dichroics, and detectors to provide 7-channel coverage of the 0.45-12.3-micron range at 60-deg angle of view, corresponding to a 418-element, 13.8-km-wide ground swath. The TMS is carried on a Lear 23 aircraft operating at 750 km/h and 12-m altitude and equipped with a 15.2-cm aerial mapping camera and a ground-updated inertial navigational system. Agricultural, forestry, and geological trial applications are reviewed, and some sample results are given. The significant improvements predicted for the Landsat-D thematic mapper (relative to the Landsat MSS) are seen as confirmed, with the possible exception of the 120-m-resolution version of channel 7.

  18. Safety Significance of the Halden IFA-650 LOCA Test Results

    International Nuclear Information System (INIS)

    Fuketa, Toyoshi; Nagase, Fumihisa; Grandjean, Claude; Petit, Marc; Hozer, Zoltan; Kelppe, Seppo; Khvostov, Grigori; Hafidi, Biya; Therache, Benjamin; Heins, Lothar; Valach, Mojmir; Voglewede, John; Wiesenack, Wolfgang


    CSNI therefore posed the question to the Working Group on Fuel Safety (WGFS): How could the Halden LOCA tests affect regulation? The WGFS agreed that the main safety concern would be fuel dispersal (and hence the potential for loss of coolable geometry) occurring at relatively low temperature, i.e. 800 deg. C. In order to assess the applicability of the IFA-650.4 results to actual power plant situations and the possible impact on safety criteria, a number of aspects should be clarified before considering a safety significance of the Halden IFA-650 series results: - Representativeness for NPP cases - Gas flow - Relocation - Burnup effect - Repeatability - Power history These items will be discussed one by one in this CSNI report. On April 17, 2009, test 650.9 was carried out with 650.4 sibling fuel. The target cladding peak temperature was 1100 deg. C in this case, but otherwise the experimental conditions were very similar. In many respects, 650.9 repeated the 650.4 experiment, e.g. by showing clear signs of fuel relocation which was confirmed by gamma scanning later on. The WGFS therefore decided that 650.9 should be considered as well for this CSNI report. Mention is also made of IFA-650.3, which failed with a small crack in a weak spot induced by thermocouple welding, and IFA-650.5 which involved ballooning and fuel ejection under conditions of restricted gas flow

  19. Evaluating the trade-off between food and timber resulting from the conversion of Miombo forests to agricultural land in Angola using multi-temporal Landsat data. (United States)

    Schneibel, Anne; Stellmes, Marion; Röder, Achim; Finckh, Manfred; Revermann, Rasmus; Frantz, David; Hill, Joachim


    The repopulation of abandoned areas in Angola after 27years of civil war led to a fast and extensive expansion of agricultural fields to meet the rising food demand. Yet, the increase in crop production at the expense of natural resources carries an inherent potential for conflicts since the demand for timber and wood extraction are also supposed to rise. We use the concept of ecosystem services to evaluate the trade-off between food and woody biomass. Our study area is located in central Angola, in the highlands of the upper Okavango catchment. We used Landsat data (spatial resolution: 30×30m) with a bi-temporal and multi-seasonal change detection approach for five time steps between 1989 and 2013 to estimate the conversion area from woodland to agriculture. Overall accuracy is 95%, user's accuracy varies from 89-95% and producer's accuracy ranges between 92-99%. To quantify the trade-off between woody biomass and the amount of food, this information was combined with indicator values and we furthermore assessed biomass regrowth on fallows. Our results reveal a constant rise in agricultural expansion from 1989-2013 with the mean annual deforestation rate increasing from roughly 5300ha up to about 12,000ha. Overall, 5.6% of the forested areas were converted to agriculture, whereas the FAO states a national deforestation rate for Angola of 5% from 1990-2010 (FAO, 2010). In the last time step 961,000t per year of woodland were cleared to potentially produce 1240t per year of maize. Current global agro-economical projections forecast increasing pressure on tropical dry forests from large-scale agriculture schemes (Gasparri et al., 2015; Searchinger and Heimlich, 2015). Our study underlines the importance of considering subsistence-related change processes, which may contribute significantly to negative effects associated with deforestation and degradation of these forest ecosystems. Copyright © 2016 Elsevier B.V. All rights reserved.

  20. Improving the mapping of crop types in the Midwestern U.S. by fusing Landsat and MODIS satellite data (United States)

    Zhu, Likai; Radeloff, Volker C.; Ives, Anthony R.


    Mapping crop types is of great importance for assessing agricultural production, land-use patterns, and the environmental effects of agriculture. Indeed, both radiometric and spatial resolution of Landsat's sensors images are optimized for cropland monitoring. However, accurate mapping of crop types requires frequent cloud-free images during the growing season, which are often not available, and this raises the question of whether Landsat data can be combined with data from other satellites. Here, our goal is to evaluate to what degree fusing Landsat with MODIS Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR) data can improve crop-type classification. Choosing either one or two images from all cloud-free Landsat observations available for the Arlington Agricultural Research Station area in Wisconsin from 2010 to 2014, we generated 87 combinations of images, and used each combination as input into the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) algorithm to predict Landsat-like images at the nominal dates of each 8-day MODIS NBAR product. Both the original Landsat and STARFM-predicted images were then classified with a support vector machine (SVM), and we compared the classification errors of three scenarios: 1) classifying the one or two original Landsat images of each combination only, 2) classifying the one or two original Landsat images plus all STARFM-predicted images, and 3) classifying the one or two original Landsat images together with STARFM-predicted images for key dates. Our results indicated that using two Landsat images as the input of STARFM did not significantly improve the STARFM predictions compared to using only one, and predictions using Landsat images between July and August as input were most accurate. Including all STARFM-predicted images together with the Landsat images significantly increased average classification error by 4% points (from 21% to 25%) compared to using only Landsat

  1. Mutagenicity in drug development: interpretation and significance of test results. (United States)

    Clive, D


    The use of mutagenicity data has been proposed and widely accepted as a relatively fast and inexpensive means of predicting long-term risk to man (i.e., cancer in somatic cells, heritable mutations in germ cells). This view is based on the universal nature of the genetic material, the somatic mutation model of carcinogenesis, and a number of studies showing correlations between mutagenicity and carcinogenicity. An uncritical acceptance of this approach by some regulatory and industrial concerns is over-conservative, naive, and scientifically unjustifiable on a number of grounds: Human cancers are largely life-style related (e.g., cigarettes, diet, tanning). Mutagens (both natural and man-made) are far more prevalent in the environment than was originally assumed (e.g., the natural bases and nucleosides, protein pyrolysates, fluorescent lights, typewriter ribbon, red wine, diesel fuel exhausts, viruses, our own leukocytes). "False-positive" (relative to carcinogenicity) and "false-negative" mutagenicity results occur, often with rational explanations (e.g., high threshold, inappropriate metabolism, inadequate genetic endpoint), and thereby confound any straightforward interpretation of mutagenicity test results. Test battery composition affects both the proper identification of mutagens and, in many instances, the ability to make preliminary risk assessments. In vitro mutagenicity assays ignore whole animal protective mechanisms, may provide unphysiological metabolism, and may be either too sensitive (e.g., testing at orders-of-magnitude higher doses than can be ingested) or not sensitive enough (e.g., short-term treatments inadequately model chronic exposure in bioassay). Bacterial systems, particularly the Ames assay, cannot in principle detect chromosomal events which are involved in both carcinogenesis and germ line mutations in man. Some compounds induce only chromosomal events and little or no detectable single-gene events (e.g., acyclovir, caffeine

  2. The use of Landsat-4 MSS digital data in temporal data sets and the evaluation of scene-to-scene registration accuracy (United States)

    Anderson, J. E.


    The MSS sensor on Landsat 4 is, in certain performance aspects, diferent from those of Landsats 1 through 3. These differences created some concern in the NASA research community as to whether individual data sets can be registered accurately enough to produce acceptable data sets for multitemporal data analysis. The use of Landsat 4 MSS digital data in temporal data sets is examined and a method is presented for estimating temporal registration accuracy based on the use of an X-Y digitizer and grey tone electrostatic plots. Results indicate that the RMS temporal registration errors are not significantly different from the temporal data sets generated using Landsat 4 and Landsat 2 data (33.35 meters) and the temporal data set constructed from two Landsat 2 data sets (33.61 meters). A derivation of the model used to evaluate the temporal registration is included.

  3. Obtaining land cover changes information from multitemporal analysis of Landsat-TM images: results from a case study in West African dryland (United States)

    Nutini, F.; Boschetti, M.; Brivio, P. A.; Antoninetti, M.


    The Sahelian belt of West Africa is a semiarid region characterized by wide climate variations, which can in turn affect the livelihood of local populations particularly in rangeland areas, as happens during the dramatic food crisis in the 70-80s caused by rainfall scarcity. The monitoring of natural resources and rainfed agricultural activities, with the aim to provide information to support Sahelian food security action, needs the production of detailed thematic maps as emphasized by several scientific papers. In this framework, a study was conducted to develop a method to exploit time series of remote sensed satellite data to 1) provide reliable land cover (LC) map at local scale in a dry region and 2) obtain a LC change (LCC) map that contribute to identify the plausible causes of local environmental instability. Satellite images used for this work consist in a time series of Landsat Thematic Mapper (TM) (path row 195-50) acquired in the 2000 (6 scenes) and 2007 (9 scenes) from February (Dry season) to September (end of wet season). The study investigates the different contribution provided by spectra information of a single Landsat TM image and by time series of derived NDVI. Different tests have been conducted with different combination of data set (spectral and temporal)in order to identify the best approach to obtain a LC map in five classes of interest: Shrubland, Cultivated Land, Water body, Herbaceous vegetation and Bare soil. The best classification approach is exposed and applied on two years in the last decade. The comparison between this two LC results in land cover change map, that displays the changes of vegetation patterns that have been characterized the area. The discussed results show a largely stable dryland region, but locally characterized by hot-spot of decreasing in natural vegetation inside the rangelands and an increasing of cultivations along fossil valleys where human activities are slightly intense. The discussion shows that this hot

  4. An Improved Physics-Based Model for Topographic Correction of Landsat TM Images

    Directory of Open Access Journals (Sweden)

    Ainong Li


    Full Text Available Optical remotely sensed images in mountainous areas are subject to radiometric distortions induced by topographic effects, which need to be corrected before quantitative applications. Based on Li model and Sandmeier model, this paper proposed an improved physics-based model for the topographic correction of Landsat Thematic Mapper (TM images. The model employed Normalized Difference Vegetation Index (NDVI thresholds to approximately divide land targets into eleven groups, due to NDVI’s lower sensitivity to topography and its significant role in indicating land cover type. Within each group of terrestrial targets, corresponding MODIS BRDF (Bidirectional Reflectance Distribution Function products were used to account for land surface’s BRDF effect, and topographic effects are corrected without Lambertian assumption. The methodology was tested with two TM scenes of severely rugged mountain areas acquired under different sun elevation angles. Results demonstrated that reflectance of sun-averted slopes was evidently enhanced, and the overall quality of images was improved with topographic effect being effectively suppressed. Correlation coefficients between Near Infra-Red band reflectance and illumination condition reduced almost to zero, and coefficients of variance also showed some reduction. By comparison with the other two physics-based models (Sandmeier model and Li model, the proposed model showed favorable results on two tested Landsat scenes. With the almost half-century accumulation of Landsat data and the successive launch and operation of Landsat 8, the improved model in this paper can be potentially helpful for the topographic correction of Landsat and Landsat-like data.

  5. Comparison of Landsat-8 and Sentinel-2A reflectance and normalized difference vegetation index (United States)

    Zhang, H.; Roy, D. P.; Yan, L.; Li, Z.; Huang, H.


    The moderate spatial resolution satellite data from the polar-orbiting Landsat-8 (launched 2013) and Sentinel-2A (launched 2015) sensors provide 10 m to 30 m multi-spectral global coverage with a better than 5-day revisit. Although a national laboratory traceable cross-calibration comparison of the Landsat-8 Operational Land Imager (OLI) and the Sentinel-2A MultiSpectral Instrument (MSI) was undertaken pre-launch, there are a number of other sensor differences, notably due to spectral, spatial and angular differences. To examine these in a comprehensive way, Landsat-8 and Sentinel-2A data for approximately 20° × 10° of southern Africa acquired in the summer (January to March) and winter (July to September) of 2016 were compared. Only Landsat-8 and Sentinel-2A observations acquired within one-day apart were considered. The sensor data were registered and then each orbit projected into 30 m fixed global Web Enabled Landsat Data (GWELD) tiles defined in the MODIS sinusoidal equal area projection. Only corresponding sensor observations of each 30 m tile pixel that were flagged as cloud and snow-free, unsaturated, and that had no significant change in their one day separation, were compared. Both the Landsat-8 and Sentinel-2A data were atmospherically corrected using the Landsat Surface Reflectance Code (LaSRC) and were also corrected to nadir BRDF adjusted reflectance (NBAR). Top of atmosphere and surface reflectance for the spectrally corresponding visible, near infrared and shortwave infrared OLI and MSI bands, and derived normalized difference vegetation index (NDVI), were compared and their differences quantified using regression analyses. The resulting statistical transformations may be used to improve the consistency between the Landsat-8 OLI and Sentinel-2A MSI data. The importance and sensitivity of the results to correct filtering, atmospheric correction and adjustment to NBAR is demonstrated.

  6. Requirements, Science, and Measurements for Landsat 10 and Beyond: Perspectives from the Landsat Science Team (United States)

    Crawford, C. J.; Masek, J. G.; Roy, D. P.; Woodcock, C. E.; Wulder, M. A.


    The U.S. Geological Survey (USGS) and NASA are currently prioritizing requirements and investing in technology options for a "Landsat 10 and beyond" mission concept as part of the Sustainable Land Imaging (SLI) architecture. Following the successful February 2013 launch of the Landsat 8, the Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) have now added over 1 million images to the USGS Landsat archive. The USGS and NASA support and co-lead a Landsat Science Team made up largely of university and government experts to offer independent insight and guidance of program activities and directions. The rapid development of Landsat 9 reflects, in part, strong input from the 2012-2017 USGS Landsat Science Team (LST). During the last two years of the LST's tenure, individual LST members and within LST team working groups have made significant contributions to Landsat 10 and beyond's science traceability and future requirements justification. Central to this input, has been an effort to identify a trade space for enhanced measurement capabilities that maintains mission continuity with eight prior multispectral instruments, and will extend the Landsat Earth observation record beyond 55+ years with an approximate launch date of 2027. The trade space is framed by four fundamental principles in remote sensing theory and practice: (1) temporal resolution, (2) spatial resolution, (3) radiometric resolution, and (4) spectral coverage and resolution. The goal of this communication is to provide a synopsis of past and present 2012-2017 LST contributions to Landsat 10 and beyond measurement science and application priorities. A particular focus will be to document the links between new science and societal benefit areas with potential technical enhancements to the Landsat mission.

  7. A regional land use survey based on remote sensing and other data: A report on a LANDSAT and computer mapping project, volume 2 (United States)

    Nez, G. (Principal Investigator); Mutter, D.


    The author has identified the following significant results. The project mapped land use/cover classifications from LANDSAT computer compatible tape data and combined those results with other multisource data via computer mapping/compositing techniques to analyze various land use planning/natural resource management problems. Data were analyzed on 1:24,000 scale maps at 1.1 acre resolution. LANDSAT analysis software and linkages with other computer mapping software were developed. Significant results were also achieved in training, communication, and identification of needs for developing the LANDSAT/computer mapping technologies into operational tools for use by decision makers.


    Directory of Open Access Journals (Sweden)

    N. Aslan


    Full Text Available The main objectives of this study are (i to calculate Land Surface Temperature (LST from Landsat imageries, (ii to determine the UHI effects from Landsat 7 ETM+ (June 5, 2001 and Landsat 8 OLI (June 17, 2014 imageries, (iii to examine the relationship between LST and different Land Use/Land Cover (LU/LC types for the years 2001 and 2014. The study is implemented in the central districts of Antalya. Initially, the brightness temperatures are retrieved and the LST values are calculated from Landsat thermal images. Then, the LU/LC maps are created from Landsat pan-sharpened images using Random Forest (RF classifier. Normalized Difference Vegetation Index (NDVI image, ASTER Global Digital Elevation Model (GDEM and DMSP_OLS nighttime lights data are used as auxiliary data during the classification procedure. Finally, UHI effect is determined and the LST values are compared with LU/LC classes. The overall accuracies of RF classification results were computed higher than 88 % for both Landsat images. During 13-year time interval, it was observed that the urban and industrial areas were increased significantly. Maximum LST values were detected for dry agriculture, urban, and bareland classes, while minimum LST values were detected for vegetation and irrigated agriculture classes. The UHI effect was computed as 5.6 °C for 2001 and 6.8 °C for 2014. The validity of the study results were assessed using MODIS/Terra LST and Emissivity data and it was found that there are high correlation between Landsat LST and MODIS LST data (r2 = 0.7 and r2 = 0.9 for 2001 and 2014, respectively.

  9. Landsat and water pollution (United States)

    Castruccio, P.; Fowler, T.; Loats, H., Jr.


    Report presents data derived from satellite images predicting pollution loads after rainfall. It explains method for converting Landsat images of Eastern United States into cover maps for Baltimore/five county region.

  10. Landsat's international partners (United States)

    Byrnes, Raymond A.


    Since the launch of the first Landsat satellite 40 years ago, International Cooperators (ICs) have formed a key strategic alliance with the U.S. Geological Survey (USGS) to not only engage in Landsat data downlink services but also to enable a foundation for scientific and technical collaboration. The map below shows the locations of all ground stations operated by the United States and IC ground station network for the direct downlink and distribution of Landsat 5 (L5) and Landsat 7 (L7) image data. The circles show the approximate area over which each station has the capability for direct reception of Landsat data. The red circles show the components of the L5 ground station network, the green circles show components of the L7 station network, and the dashed circles show stations with dual (L5 and L7) status. The yellow circles show L5 short-term ("campaign") stations that contribute to the USGS Landsat archive. Ground stations in South Dakota and Australia currently serve as the primary data capture facilities for the USGS Landsat Ground Network (LGN). The Landsat Ground Station (LGS) is located at the USGS Earth Resources Observation and Science (EROS) Center in Sioux Falls, South Dakota. The Alice Springs (ASN) ground station is located at the Geoscience Australia facility in Alice Springs, Australia. These sites receive the image data, via X-band Radio Frequency (RF) link, and the spacecraft housekeeping data, via S-band RF link. LGS also provides tracking services and a command link to the spacecrafts.

  11. Significant results from using earth observation satellites for mineral and energy resource exploration (United States)

    Carter, William D.


    A large number of Earth-observation satellites orbit our world several times each day, providing new information about the land and sea surfaces and the overlying thin layer of atmosphere that makes our planet unique. Meteorological satellites have had the longest history of experimental use and most are now considered operational. The geologic information collected by the Landsat, Polar Orbiting Geophysical Observatory (POGO), Magsat, Heat Capacity Mapping Mission (HCMM) and Seasat land and ocean observation systems is being thoroughly tested, and some of these systems are now approaching operational use.

  12. LANDSAT menhaden and thread herring resources investigation. [Gulf of Mexico (United States)

    Kemmerer, A. J. (Principal Investigator); Brucks, J. T.; Butler, J. A.; Faller, K. H.; Holley, H. J.; Leming, T. D.; Savastano, K. J.; Vanselous, T. M.


    The author has identified the following significant results. The relationship between the distribution of menhaden and selected oceanographic parameters (water color, turbidity, and possibly chlorophyll concentrations) was established. Similar relationships for thread herring were not established nor were relationships relating to the abundance of either species. Use of aircraft and LANDSAT remote sensing instruments to measure or infer a set of basic oceanographic parameters was evaluated. Parameters which could be accurately inferred included surface water temperature, salinity, and color. Water turbidity (Secchi disk) was evaluated as marginally inferrable from the LANDSAT MSS data and chlorophyll-a concentrations as less than marginal. These evaluations considered the parameters only as experienced in the two test areas using available sensors and statistical techniques.

  13. Monitoring water quality from LANDSAT. [satellite observation of Virginia (United States)

    Barker, J. L.


    Water quality monitoring possibilities from LANDSAT were demonstrated both for direct readings of reflectances from the water and indirect monitoring of changes in use of land surrounding Swift Creek Reservoir in a joint project with the Virginia State Water Control Board and NASA. Film products were shown to have insufficient resolution and all work was done by digitally processing computer compatible tapes. Land cover maps of the 18,000 hectare Swift Creek Reservoir watershed, prepared for two dates in 1974, are shown. A significant decrease in the pine cover was observed in a 740 hectare construction site within the watershed. A measure of the accuracy of classification was obtained by comparing the LANDSAT results with visual classification at five sites on a U-2 photograph. Such changes in land cover can alert personnel to watch for potential changes in water quality.

  14. Application of LANDSAT to the surveillance and control of lake eutrophication in the Great Lakes Basin (United States)

    Rogers, R. H. (Principal Investigator)


    The author has identified the following significant results. Preliminary results in Saginaw Bay show that processed LANDSAT data provides a synoptic view of turbidity and circulation patterns that no degree of ground monitoring can provide. Processed imagery was produced to show nine discrete categories of turbidity, as indicated by nine Secchi depths between 0.3 and 3.3 meters. Analysis of lakes near Madison, Wisconsin show that inland lake water can be categorized by LANDSAT as clear, tannin, algal, and red clay. LANDSAT's capability to inventory watershed land use was throughly demonstrated in the Ohio-Kentucky-Indiana regional planning area. Computer tabulations providing area covered by each of 16 land use categories were rapidly and economically produced for each of the 225 watersheds and nine counties.

  15. Computer mapping of turbidity and circulation patterns in Saginaw Bay, Michigan from LANDSAT data (United States)

    Rogers, R. H. (Principal Investigator); Reed, L. E.; Smith, V. E.


    The author has identified the following significant results. LANDSAT was used as a basis for producing geometrically-corrected, color-coded imagery of turbidity and circulation patterns in Saginaw Bay, Michigan (Lake Huron). This imagery shows nine discrete categories of turbidity, as indicated by nine Secchi depths between 0.3 and 3.3 meters. The categorized imagery provided an economical basis for extrapolating water quality parameters from point samples to unsample areas. LANDSAT furnished a synoptic view of water mass boundaries that no amount of ground sampling or monitoring could provide.

  16. Comparison of LANDSAT-2 and field spectrometer reflectance signatures of south Texas rangeland plant communities (United States)

    Richardson, A. J.; Escobar, D. E.; Gausman, H. W.; Everitt, J. H. (Principal Investigator)


    The accuracy was assessed for an atmospheric correction method that depends on clear water bodies to infer solar and atmospheric parameters for radiative transfer equations by measuring the reflectance signature of four prominent south Texas rangeland plants with the LANDSAT satellite multispectral scanner (MSS) and a ground based spectroradiometer. The rangeland plant reflectances produced by the two sensors were correlated with no significant deviation of the slope from unity or of the intercept from zero. These results indicated that the atmospheric correction produced LANDSAT MSS estimates of rangeland plant reflectances that are as accurate as the ground based spectroradiometer.

  17. Landsat Data Continuity Mission (United States)



    The Landsat Data Continuity Mission (LDCM) is a partnership formed between the National Aeronautics and Space Administration (NASA) and the U.S. Geological Survey (USGS) to place the next Landsat satellite in orbit in January 2013. The Landsat era that began in 1972 will become a nearly 41-year global land record with the successful launch and operation of the LDCM. The LDCM will continue the acquisition, archiving, and distribution of multispectral imagery affording global, synoptic, and repetitive coverage of the Earth's land surfaces at a scale where natural and human-induced changes can be detected, differentiated, characterized, and monitored over time. The mission objectives of the LDCM are to (1) collect and archive medium resolution (30-meter spatial resolution) multispectral image data affording seasonal coverage of the global landmasses for a period of no less than 5 years; (2) ensure that LDCM data are sufficiently consistent with data from the earlier Landsat missions in terms of acquisition geometry, calibration, coverage characteristics, spectral characteristics, output product quality, and data availability to permit studies of landcover and land-use change over time; and (3) distribute LDCM data products to the general public on a nondiscriminatory basis at no cost to the user.

  18. Improved land use classification from Landsat and Seasat satellite imagery registered to a common map base (United States)

    Clark, J.


    In the case of Landsat Multispectral Scanner System (MSS) data, ambiguities in spectral signature can arise in urban areas. A study was initiated in the belief that Seasat digital SAR could help provide the spectral separability needed for a more accurate urban land use classification. A description is presented of the results of land use classifications performed on Landsat and preprocessed Seasat imagery that were registered to a common map base. The process of registering imagery and training site boundary coordinates to a common map has been reported by Clark (1980). It is found that preprocessed Seasat imagery provides signatures for urban land uses which are spectrally separable from Landsat signatures. This development appears to significantly improve land use classifications in an urban setting for class 12 (Commercial and Services), class 13 (Industrial), and class 14 (Transportation, Communications, and Utilities).

  19. Improving automated disturbance maps using snow-covered landsat time series stacks (United States)

    Kirk M. Stueve; Ian W. Housman; Patrick L. Zimmerman; Mark D. Nelson; Jeremy Webb; Charles H. Perry; Robert A. Chastain; Dale D. Gormanson; Chengquan Huang; Sean P. Healey; Warren B. Cohen


    Snow-covered winter Landsat time series stacks are used to develop a nonforest mask to enhance automated disturbance maps produced by the Vegetation Change Tracker (VCT). This method exploits the enhanced spectral separability between forested and nonforested areas that occurs with sufficient snow cover. This method resulted in significant improvements in Vegetation...

  20. Estimating the leaf area index (LAI) of black wattle from Landsat ...

    African Journals Online (AJOL)

    Regression analysis revealed that actual LAI had significant relationships with PAI and NDVI. The results indicate the potential of the Landsat ETM+ satellite imageries to estimate values of important canopy attributes of A. mearnsii that are related to stand productivity that may be used as inputs into process-based models ...

  1. Landsat 6 contract signed (United States)

    Maggs, William Ward

    A new agreement provides $220 million for development and construction of the Landsat 6 remote sensing satellite and its ground systems. The contract, signed on March 31, 1988, by the Department of Commerce (DOC) and the Earth Observation Satellite (EOSAT) Company of Lanham, Md., came just days after approval of DOC's Landsat commercialization plan by subcommittees of the House and Senate appropriations committees.The Landsat 6 spacecraft is due to be launched into orbit on a Titan II rocket in June 1991 from Vandenburg Air Force Base, Calif. The satellite will carry an Enhanced Thematic Mapper (ETM) sensor, an instrument sensitive to electromagnetic radiation in seven ranges or bands of wavelengths. The satellite's payload will also include the Sea Wide Field Sensor (Sea-WiFS), designed to provide information on sea surface temperature and ocean color. The sensor is being developed in a cooperative effort by EOSAT and the National Aeronautics and Space Administration (NASA). A less certain passenger is a proposed 5-m resolution, three-band sensor sensitive to visible light. EOSAT is trying to find both private financing for the device and potential buyers of the high-resolution imagery that it could produce. The company has been actively courting U.S. television networks, which have in the past used imagery from the European Système Probatoire d'Observation de la Terre (SPOT) satellite for news coverage.

  2. Interpreting Statistical Significance Test Results: A Proposed New "What If" Method. (United States)

    Kieffer, Kevin M.; Thompson, Bruce

    As the 1994 publication manual of the American Psychological Association emphasized, "p" values are affected by sample size. As a result, it can be helpful to interpret the results of statistical significant tests in a sample size context by conducting so-called "what if" analyses. However, these methods can be inaccurate…

  3. A time-series analysis of flood disaster around Lena river using Landsat TM/ETM+ (United States)

    Sakai, Toru; Hatta, Shigemi; Okumura, Makoto; Takeuchi, Wataru; Hiyama, Tetsuya; Inoue, Gen


    Tabaga (61.83°N, 129.60°E) was frozen hard until early May 2007. River-ice breakup began in patches on 13 May 2007. Then, the area of Lena river rapidly increased due to overhead flooding on 14 May 2007, and reached the peak on 15 May 2007. In the brief period of one or two days, the area of Lena river was more than twice. After this, the area of Lena river exponentially decreased over three months, and it was quite stable in late August 2007. A time-series of Landsat TM/ETM+ images could detect these large temporal variations. In addition, the temporal variations in the area of Lena river synchronized with water stage measured in the field. These results indicate that a time-series of Landsat TM/ETM+ images enables to monitor natural disturbances caused at short-term intervals, although significantly limited to local scales. The requirement of spatial and temporal resolution is often application specific in the context of the desired measurement goals. This type of research and resultant information is critical for the utilization of remote sensing data to the fullest extent.

  4. Land use change detection with LANDSAT-2 data for monitoring and predicting regional water quality degradation. [Arkansas (United States)

    Macdonald, H.; Steele, K. (Principal Investigator); Waite, W.; Rice, R.; Shinn, M.; Dillard, T.; Petersen, C.


    The author has identified the following significant results. Comparison between LANDSAT 1 and 2 imagery of Arkansas provided evidence of significant land use changes during the 1972-75 time period. Analysis of Arkansas historical water quality information has shown conclusively that whereas point source pollution generally can be detected by use of water quality data collected by state and federal agencies, sampling methodologies for nonpoint source contamination attributable to surface runoff are totally inadequate. The expensive undertaking of monitoring all nonpoint sources for numerous watersheds can be lessened by implementing LANDSAT change detection analyses.

  5. Landsat and agriculture—Case studies on the uses and benefits of Landsat imagery in agricultural monitoring and production (United States)

    Leslie, Colin R.; Serbina, Larisa O.; Miller, Holly M.


    Executive SummaryThe use of Landsat satellite imagery for global agricultural monitoring began almost immediately after the launch of Landsat 1 in 1972, making agricultural monitoring one of the longest-standing operational applications for the Landsat program. More recently, Landsat imagery has been used in domestic agricultural applications as an input for field-level production management. The enactment of the U.S. Geological Survey’s free and open data policy in 2008 and the launch of Landsat 8 in 2013 have both influenced agricultural applications. This report presents two primary sets of case studies on the applications and benefits of Landsat imagery use in agriculture. The first set examines several operational applications within the U.S. Department of Agriculture (USDA) and the second focuses on private sector applications for agronomic management.  Information on the USDA applications is provided in the U.S. Department of Agriculture Uses of Landsat Imagery for Global and Domestic Agricultural Monitoring section of the report in the following subsections:Estimating Crop Production.—Provides an overview of how Landsat satellite imagery is used to estimate crop production, including the spectral bands most frequently utilized in this application.Monitoring Consumptive Water Use.—Highlights the role of Landsat imagery in monitoring consumptive water use for agricultural production. Globally, a significant amount of agricultural production relies on irrigation, so monitoring water resources is a critical component of agricultural monitoring. National Agricultural Statistics Service—Cropland Data Layer.—Highlights the use of Landsat imagery in developing the annual Cropland Data Layer, a crop-specific land cover classification product that provides information on more than 100 crop categories grown in the United States. Foreign Agricultural Service—Global Agricultural Monitoring.—Highlights Landsat’s role in monitoring global agricultural

  6. LANDSAT-4 Science Characterization Early Results. Volume 4: Applications. [agriculture, soils land use, geology, hydrology, wetlands, water quality, biomass identification, and snow mapping (United States)

    Barker, J. L. (Editor)


    The excellent quality of TM data allows researchers to proceed directly with applications analyses, without spending a significant amount of time applying various corrections to the data. The early results derived of TM data are discussed for the following applications: agriculture, land cover/land use, soils, geology, hydrology, wetlands biomass, water quality, and snow.

  7. Multispectral Landsat images of Antartica

    Energy Technology Data Exchange (ETDEWEB)

    Lucchitta, B.K.; Bowell, J.A.; Edwards, K.L.; Eliason, E.M.; Fergurson, H.M.


    The U.S. Geological Survey has a program to map Antarctica by using colored, digitally enhanced Landsat multispectral scanner images to increase existing map coverage and to improve upon previously published Landsat maps. This report is a compilation of images and image mosaic that covers four complete and two partial 1:250,000-scale quadrangles of the McMurdo Sound region.

  8. p-Curve and Effect Size: Correcting for Publication Bias Using Only Significant Results. (United States)

    Simonsohn, Uri; Nelson, Leif D; Simmons, Joseph P


    Journals tend to publish only statistically significant evidence, creating a scientific record that markedly overstates the size of effects. We provide a new tool that corrects for this bias without requiring access to nonsignificant results. It capitalizes on the fact that the distribution of significant p values, p-curve, is a function of the true underlying effect. Researchers armed only with sample sizes and test results of the published findings can correct for publication bias. We validate the technique with simulations and by reanalyzing data from the Many-Labs Replication project. We demonstrate that p-curve can arrive at conclusions opposite that of existing tools by reanalyzing the meta-analysis of the "choice overload" literature. © The Author(s) 2014.

  9. Gene expression results in lipopolysaccharide-stimulated monocytes depend significantly on the choice of reference genes

    Directory of Open Access Journals (Sweden)

    Øvstebø Reidun


    Full Text Available Abstract Background Gene expression in lipopolysaccharide (LPS-stimulated monocytes is mainly studied by quantitative real-time reverse transcription PCR (RT-qPCR using GAPDH (glyceraldehyde 3-phosphate dehydrogenase or ACTB (beta-actin as reference gene for normalization. Expression of traditional reference genes has been shown to vary substantially under certain conditions leading to invalid results. To investigate whether traditional reference genes are stably expressed in LPS-stimulated monocytes or if RT-qPCR results are dependent on the choice of reference genes, we have assessed and evaluated gene expression stability of twelve candidate reference genes in this model system. Results Twelve candidate reference genes were quantified by RT-qPCR in LPS-stimulated, human monocytes and evaluated using the programs geNorm, Normfinder and BestKeeper. geNorm ranked PPIB (cyclophilin B, B2M (beta-2-microglobulin and PPIA (cyclophilin A as the best combination for gene expression normalization in LPS-stimulated monocytes. Normfinder suggested TBP (TATA-box binding protein and B2M as the best combination. Compared to these combinations, normalization using GAPDH alone resulted in significantly higher changes of TNF-α (tumor necrosis factor-alpha and IL10 (interleukin 10 expression. Moreover, a significant difference in TNF-α expression between monocytes stimulated with equimolar concentrations of LPS from N. meningitides and E. coli, respectively, was identified when using the suggested combinations of reference genes for normalization, but stayed unrecognized when employing a single reference gene, ACTB or GAPDH. Conclusions Gene expression levels in LPS-stimulated monocytes based on RT-qPCR results differ significantly when normalized to a single gene or a combination of stably expressed reference genes. Proper evaluation of reference gene stabiliy is therefore mandatory before reporting RT-qPCR results in LPS-stimulated monocytes.

  10. Integrating Landsat-derived disturbance maps with FIA inventory data: Applications for state-Level forest resource assessments (United States)

    Sonja Oswalt; Chengquan Huang; Hua Shi; James Vogelmann; Zhiliang Zhu; Samuel N. Goward; John Coulston


    Landsat images have been widely used for assessing forest characteristics and dynamics. Recently, significant progress has been made towards indepth exploration of the rich Landsat archive kept by the U.S. Geological Survey to improve our under standing of forest disturbance and recovery processes. In this study, we used Landsat images to map forest disturbances at...

  11. River morphodynamics from space: the Landsat frontier (United States)

    Schwenk, Jon; Khandelwal, Ankush; Fratkin, Mulu; Kumar, Vipin; Foufoula-Georgiou, Efi


    NASA's Landsat family of satellites have been observing the entire globe since 1984, providing over 30 years of snapshots with an 18 day frequency and 30 meter resolution. These publicly-available Landsat data are particularly exciting to researchers interested in river morphodynamics, who are often limited to use of historical maps, aerial photography, and field surveys with poor and irregular time resolutions and limited spatial extents. Landsat archives show potential for overcoming these limitations, but techniques and tools for accurately and efficiently mining the vault of scenes must first be developed. In this PICO presentation, we detail the problems we encountered while mapping and quantifying planform dynamics of over 1,300 km of the actively-migrating, meandering Ucayali River in Peru from Landsat imagery. We also present methods to overcome these obstacles and introduce the Matlab-based RivMAP (River Morphodynamics from Analysis of Planforms) toolbox that we developed to extract banklines and centerlines, compute widths, curvatures, and angles, identify cutoffs, and quantify planform changes via centerline migration and erosion/accretion over large spatial domains with high temporal resolution. Measurement uncertainties were estimated by analyzing immobile, abandoned oxbow lakes. Our results identify hotspots of planform changes, and combined with limited precipitation, stage, and topography data, we parse three simultaneous controls on river migration: climate, sediment, and meander cutoff. Overall, this study demonstrates the vast potential locked within Landsat archives to identify multi-scale controls on river migration, observe the co-evolution of width, curvature, discharge, and migration, and discover and develop new geomorphic insights.


    Directory of Open Access Journals (Sweden)

    Y. Jouybari-Moghaddam


    Full Text Available Land Surface Temperature (LST is one of the significant variables measured by remotely sensed data, and it is applied in many environmental and Geoscience studies. The main aim of this study is to develop an algorithm to retrieve the LST from Landsat-8 satellite data using Radiative Transfer Equation (RTE. However, LST can be retrieved from RTE, but, since the RTE has two unknown parameters including LST and surface emissivity, estimating LST from RTE is an under the determined problem. In this study, in order to solve this problem, an approach is proposed an equation set includes two RTE based on Landsat-8 thermal bands (i.e.: band 10 and 11 and two additional equations based on the relation between the Normalized Difference Vegetation Index (NDVI and emissivity of Landsat-8 thermal bands by using simulated data for Landsat-8 bands. The iterative least square approach was used for solving the equation set. The LST derived from proposed algorithm is evaluated by the simulated dataset, built up by MODTRAN. The result shows the Root Mean Squared Error (RMSE is less than 1.18°K. Therefore; the proposed algorithm can be a suitable and robust method to retrieve the LST from Landsat-8 satellite data.

  13. Least Square Approach for Estimating of Land Surface Temperature from LANDSAT-8 Satellite Data Using Radiative Transfer Equation (United States)

    Jouybari-Moghaddam, Y.; Saradjian, M. R.; Forati, A. M.


    Land Surface Temperature (LST) is one of the significant variables measured by remotely sensed data, and it is applied in many environmental and Geoscience studies. The main aim of this study is to develop an algorithm to retrieve the LST from Landsat-8 satellite data using Radiative Transfer Equation (RTE). However, LST can be retrieved from RTE, but, since the RTE has two unknown parameters including LST and surface emissivity, estimating LST from RTE is an under the determined problem. In this study, in order to solve this problem, an approach is proposed an equation set includes two RTE based on Landsat-8 thermal bands (i.e.: band 10 and 11) and two additional equations based on the relation between the Normalized Difference Vegetation Index (NDVI) and emissivity of Landsat-8 thermal bands by using simulated data for Landsat-8 bands. The iterative least square approach was used for solving the equation set. The LST derived from proposed algorithm is evaluated by the simulated dataset, built up by MODTRAN. The result shows the Root Mean Squared Error (RMSE) is less than 1.18°K. Therefore; the proposed algorithm can be a suitable and robust method to retrieve the LST from Landsat-8 satellite data.

  14. Description of test facilities bound to the research on sodium aerosols - some significant results

    Energy Technology Data Exchange (ETDEWEB)

    Dolias, M; Lafon, A; Vidard, M; Schaller, K H [DRNR/STRS - Centre de Cadarache, Saint-Paul-lez-Durance (France)


    This communication is dedicated to the description of the CEA (French Atomic Energy Authority) testing located at CADARACHE and which are utilized for the study of sodium aerosols behavior. These testing loops are necessary for studying the operating of equipment such as filters, sodium vapour traps, condensers and separators. It is also possible to study the effect of characteristics parameters on formation, coagulation and carrying away of sodium aerosols in the cover gas. Sodium aerosols deposits in a vertical annular space configuration with a cold area in its upper part are also studied. Some significant results emphasize the importance of operating conditions on the formation of aerosols. (author)

  15. Environmental significance of atmospheric emission resulting from in situ burning of oiled salt marsh

    International Nuclear Information System (INIS)

    Devai, I.; DeLaune, R.D.; Henry, C.B. Jr.; Roberts, P.O.; Lindau, C.W.


    The environmental significance of atmospheric emissions resulting from in-situ burning used as remediation technique for removal of petroleum hydrocarbons entering Louisiana coastal salt marshes was quantified. Research conducted documented atmospheric pollutants produced and emitted to the atmosphere as the result of burning of oil contaminated wetlands. Samples collected from the smoke plume contained a variety of gaseous sulfur and carbon compounds. Carbonyl sulfide and carbon disulfide were the main volatile sulfur compounds. In contrast, concentrations of sulfur dioxide were almost negligible. Concentrations of methane and carbon dioxide in the smoke plume increased compared to ambient levels. Air samples collected for aromatic hydrocarbons in the smoke plume were dominated by pyrogenic or combustion derived aromatic hydrocarbons. The particulate fraction was dominated by phenanthrene and the C-1 and C-2 alkylated phenanthrene homologues. The vapor fraction was dominated by naphthalene and the C-1 to C-3 naphthalene homologues. (author)

  16. Significant ELCAP analysis results: Summary report. [End-use Load and Consumer Assessment Program

    Energy Technology Data Exchange (ETDEWEB)

    Pratt, R.G.; Conner, C.C.; Drost, M.K.; Miller, N.E.; Cooke, B.A.; Halverson, M.A.; Lebaron, B.A.; Lucas, R.G.; Jo, J.; Richman, E.E.; Sandusky, W.F. (Pacific Northwest Lab., Richland, WA (USA)); Ritland, K.G. (Ritland Associates, Seattle, WA (USA)); Taylor, M.E. (USDOE Bonneville Power Administration, Portland, OR (USA)); Hauser, S.G. (Solar Energy Research Inst., Golden, CO (USA))


    The evolution of the End-Use Load and Consumer Assessment Program (ELCAP) since 1983 at Bonneville Power Administration (Bonneville) has been eventful and somewhat tortuous. The birth pangs of a data set so large and encompassing as this have been overwhelming at times. The early adolescent stage of data set development and use has now been reached and preliminary results of early analyses of the data are becoming well known. However, the full maturity of the data set and the corresponding wealth of analytic insights are not fully realized. This document is in some sense a milestone in the brief history of the program. It is a summary of the results of the first five years of the program, principally containing excerpts from a number of previous reports. It is meant to highlight significant accomplishments and analytical results, with a focus on the principal results. Many of the results have a broad application in the utility load research community in general, although the real breadth of the data set remains largely unexplored. The first section of the document introduces the data set: how the buildings were selected, how the metering equipment was installed, and how the data set has been prepared for analysis. Each of the sections that follow the introduction summarize a particular analytic result. A large majority of the analyses to date involve the residential samples, as these were installed first and had highest priority on the analytic agenda. Two exploratory analyses using commercial data are included as an introduction to the commercial analyses that are currently underway. Most of the sections reference more complete technical reports which the reader should refer to for details of the methodology and for more complete discussion of the results. Sections have been processed separately for inclusion on the data base.

  17. How the detector resolution affects the clinical significance of SBRT pre-treatment quality assurance results. (United States)

    Bruschi, A; Esposito, M; Pini, S; Ghirelli, A; Zatelli, G; Russo, S


    Aim of this work was to study how the detector resolution can affect the clinical significance of SBRT pre-treatment volumetric modulated arc therapy (VMAT) verification results. Three detectors (PTW OCTAVIUS 4D 729, 1500 and 100 SRS) used in five configurations with different resolution were compared: 729, 729 merged, 1500, 1500 merged and 1000 SRS. Absolute local gamma passing rates of 3D pre-treatment quality assurance (QA) were evaluated for 150 dose distributions in 30 plans. Five different kinds of error were introduced in order to establish the detection sensitivity of the three devices. Percentage dosimetric differences were evaluated between planned dosevolume histogram (DVH) and patients' predicted DVH calculated by PTW DVH 4D® software. The mean gamma passing rates and the standard deviations were 92.4% ± 3.7%, 94.6% ± 1.8%, 95.3% ± 4.2%, 97.4% ± 2.5% and 97.6% ± 1.4 respectively for 729, 729 merged, 1500, 1500 merged and 1000 SRS with 2% local dose/2mm criterion. The same trend was found on the sensitivity analysis: using a tight gamma analysis criterion (2%L/1mm) only the 1000 SRS detected every kind of error, while 729 and 1500 merged detected three and four kinds of error respectively. Regarding dose metrics extracted from DVH curves, D50% was within the tolerance level in more than 90% of cases only for the 1000 SRS. The detector resolution can significantly affect the clinical significance of SBRT pre-treatment verification results. The choice of a detector with resolution suitable to the investigated field size is of main importance to avoid getting false positive. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  18. Replacing gasoline with corn ethanol results in significant environmental problem-shifting. (United States)

    Yang, Yi; Bae, Junghan; Kim, Junbeum; Suh, Sangwon


    Previous studies on the life-cycle environmental impacts of corn ethanol and gasoline focused almost exclusively on energy balance and greenhouse gas (GHG) emissions and largely overlooked the influence of regional differences in agricultural practices. This study compares the environmental impact of gasoline and E85 taking into consideration 12 different environmental impacts and regional differences among 19 corn-growing states. Results show that E85 does not outperform gasoline when a wide spectrum of impacts is considered. If the impacts are aggregated using weights developed by the National Institute of Standards and Technology (NIST), overall, E85 generates approximately 6% to 108% (23% on average) greater impact compared with gasoline, depending on where corn is produced, primarily because corn production induces significant eutrophication impacts and requires intensive irrigation. If GHG emissions from the indirect land use changes are considered, the differences increase to between 16% and 118% (33% on average). Our study indicates that replacing gasoline with corn ethanol may only result in shifting the net environmental impacts primarily toward increased eutrophication and greater water scarcity. These results suggest that the environmental criteria used in the Energy Independence and Security Act (EISA) be re-evaluated to include additional categories of environmental impact beyond GHG emissions.

  19. SPOT: How good for geology? A comparison with LANDSAT MSS (United States)

    Sesoeren, A.


    Geological interpretation possibilities of SPOT MSS and LANDSAT MSS positive prints enlarged to the same scale were compared, using as a test area part of the Jebel Amour (Algeria). The SPOT imagery offers many advantages, filling the gap between remote sensing from space and aerial photography. The best results by visual interpretation are obtained in combining SPOT for the required details with LANDSAT for the synoptic veiw. Further improvements are expected from the use of SPOT stereo-pairs.

  20. Most significant preliminary results of the probabilistic safety analysis on the Juragua nuclear power plant

    International Nuclear Information System (INIS)

    Perdomo, Manuel


    Since 1990 the Group for PSA Development and Applications (GDA/APS) is working on the Level-1 PSA for the Juragua-1 NPP, as a part of an IAEA Technical Assistance Project. The main objective of this study, which is still under way, is to assess, in a preliminary way, the Reactor design safety to find its potential 'weak points' at the construction stage, using a eneric data base. At the same time, the study allows the PSA team to familiarize with the plant design and analysis techniques for the future operational PSA of the plant. This paper presents the most significant preliminary results of the study, which reveal some advantages of the safety characteristics of the plant design in comparison with the homologous VVER-440 reactors and some areas, where including slight modifications would improve the plant safety, considering the level of detail at which the study is carried out. (author). 13 refs, 1 fig, 2 tabs

  1. Exploiting Data Intensive Applications on High Performance Computers to Unlock Australia's Landsat Archive (United States)

    Purss, Matthew; Lewis, Adam; Edberg, Roger; Ip, Alex; Sixsmith, Joshua; Frankish, Glenn; Chan, Tai; Evans, Ben; Hurst, Lachlan


    Australia's Earth Observation Program has downlinked and archived satellite data acquired under the NASA Landsat mission for the Australian Government since the establishment of the Australian Landsat Station in 1979. Geoscience Australia maintains this archive and produces image products to aid the delivery of government policy objectives. Due to the labor intensive nature of processing of this data there have been few national-scale datasets created to date. To compile any Earth Observation product the historical approach has been to select the required subset of data and process "scene by scene" on an as-needed basis. As data volumes have increased over time, and the demand for the processed data has also grown, it has become increasingly difficult to rapidly produce these products and achieve satisfactory policy outcomes using these historic processing methods. The result is that we have been "drowning in a sea of uncalibrated data" and scientists, policy makers and the public have not been able to realize the full potential of the Australian Landsat Archive and its value is therefore significantly diminished. To overcome this critical issue, the Australian Space Research Program has funded the "Unlocking the Landsat Archive" (ULA) Project from April 2011 to June 2013 to improve the access and utilization of Australia's archive of Landsat data. The ULA Project is a public-private consortium led by Lockheed Martin Australia (LMA) and involving Geoscience Australia (GA), the Victorian Partnership for Advanced Computing (VPAC), the National Computational Infrastructure (NCI) at the Australian National University (ANU) and the Cooperative Research Centre for Spatial Information (CRC-SI). The outputs from the ULA project will become a fundamental component of Australia's eResearch infrastructure, with the Australian Landsat Archive hosted on the NCI and made openly available under a creative commons license. NCI provides access to researchers through significant HPC

  2. Low velocity gunshot wounds result in significant contamination regardless of ballistic characteristics. (United States)

    Weinstein, Joseph; Putney, Emily; Egol, Kenneth


    Controversy exists among the orthopedic community regarding the treatment of gunshot injuries. No consistent treatment algorithm exists for treatment of low energy gunshot wound (GSW) trauma. The purpose of this study was to critically examine the wound contamination following low velocity GSW based upon bullet caliber and clothing fiber type found within the injury track. Four types of handguns were fired at ballistic gel from a 10-foot distance. Various clothing materials were applied (denim, cotton, polyester, and wool) circumferentially around the tissue agar in a loose manor. A total of 32 specimens were examined. Each caliber handgun was fired a minimum of 5 times into a gel. Regardless of bullet caliber there was gross contamination of the entire bullet track in 100% of specimens in all scenarios and for all fiber types. Furthermore, as would be expected, the degree of contamination appeared to increase as the size of the bullet increased. Low velocity GSWs result in significant contamination regardless of bullet caliber and jacket type. Based upon our results further investigation of low velocity GSW tracks is warranted. Further clinical investigation should focus on the degree to which debridement should be undertaken.

  3. Statistical rice yield modeling using blended MODIS-Landsat based crop phenology metrics in Taiwan (United States)

    Chen, C. R.; Chen, C. F.; Nguyen, S. T.; Lau, K. V.


    Taiwan is a populated island with a majority of residents settled in the western plains where soils are suitable for rice cultivation. Rice is not only the most important commodity, but also plays a critical role for agricultural and food marketing. Information of rice production is thus important for policymakers to devise timely plans for ensuring sustainably socioeconomic development. Because rice fields in Taiwan are generally small and yet crop monitoring requires information of crop phenology associating with the spatiotemporal resolution of satellite data, this study used Landsat-MODIS fusion data for rice yield modeling in Taiwan. We processed the data for the first crop (Feb-Mar to Jun-Jul) and the second (Aug-Sep to Nov-Dec) in 2014 through five main steps: (1) data pre-processing to account for geometric and radiometric errors of Landsat data, (2) Landsat-MODIS data fusion using using the spatial-temporal adaptive reflectance fusion model, (3) construction of the smooth time-series enhanced vegetation index 2 (EVI2), (4) rice yield modeling using EVI2-based crop phenology metrics, and (5) error verification. The fusion results by a comparison bewteen EVI2 derived from the fusion image and that from the reference Landsat image indicated close agreement between the two datasets (R2 > 0.8). We analysed smooth EVI2 curves to extract phenology metrics or phenological variables for establishment of rice yield models. The results indicated that the established yield models significantly explained more than 70% variability in the data (p-value 0.8), in both cases. The root mean square error (RMSE) and mean absolute error (MAE) used to measure the model accuracy revealed the consistency between the estimated yields and the government's yield statistics. This study demonstrates advantages of using EVI2-based phenology metrics (derived from Landsat-MODIS fusion data) for rice yield estimation in Taiwan prior to the harvest period.

  4. LandSAT TM 1994 (United States)

    Kansas Data Access and Support Center — Before the Landsat commercialization contract was signed between the Department of Commerce and the Earth Observation Satellite Company (EOSAT) on September 27,...

  5. Introduction of e-learning in dental radiology reveals significantly improved results in final examination. (United States)

    Meckfessel, Sandra; Stühmer, Constantin; Bormann, Kai-Hendrik; Kupka, Thomas; Behrends, Marianne; Matthies, Herbert; Vaske, Bernhard; Stiesch, Meike; Gellrich, Nils-Claudius; Rücker, Martin


    Because a traditionally instructed dental radiology lecture course is very time-consuming and labour-intensive, online courseware, including an interactive-learning module, was implemented to support the lectures. The purpose of this study was to evaluate the perceptions of students who have worked with web-based courseware as well as the effect on their results in final examinations. Users (n(3+4)=138) had access to the e-program from any networked computer at any time. Two groups (n(3)=71, n(4)=67) had to pass a final exam after using the e-course. Results were compared with two groups (n(1)=42, n(2)=48) who had studied the same content by attending traditional lectures. In addition a survey of the students was statistically evaluated. Most of the respondents reported a positive attitude towards e-learning and would have appreciated more access to computer-assisted instruction. Two years after initiating the e-course the failure rate in the final examination dropped significantly, from 40% to less than 2%. The very positive response to the e-program and improved test scores demonstrated the effectiveness of our e-course as a learning aid. Interactive modules in step with clinical practice provided learning that is not achieved by traditional teaching methods alone. To what extent staff savings are possible is part of a further study. Copyright © 2010 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

  6. [The significance of the contamination of dental care articles. The results of a field study]. (United States)

    Hingst, V


    Permissible conclusions both from recent available literature and our own field-study results concerning the problematic nature of microbial contamination of dental hygiene articles and the resulting possible health hazard for the consumer can be summarized as follows: Manufacturing practices as are given in the basic instructions for production sites of the cosmetic industry, render a possible degree of microbial contamination. This largely rules out the danger of infection of the consumer upon acquisition of the dental hygiene product. Secondary contamination of these products, as inevitably is the case during use of dental hygiene articles, leads to microbial colonization especially of toothbrush bristles. The extent of this colonization depends at least partially upon the utilization age of the toothbrush. Also for this reason a toothbrush should be replaced by a new one after period of three months, six months at the latest and in all cases of inflammatory changes of the mouth and throat region. The contamination of both the glass or plastic container used for rinsing the teeth after brushing or for gargling can be held within certain limits by dry storage. Only in exceptional cases do mouthwashes show a small degree of contamination. Provided they contain antimicrobial substances, no therapeutically serviceable possibilities worth mentioning follow for the reduction of oropharyngeal flora. Microbial colonization of toothpastes as a result of secondary contamination following use is observed only in exceptional cases due to their preservative content. Significant germination of stagnated residual water in waterpicks often occurs, achieving germ counts up to more than 10(7) cfu per ml. Moreover, waterpicks can represent a biotope for Pseudomonas aeruginosa, and should be used neither by patients with open wounds or mucous membrane lesions in the oropharyngeal area, nor by patients with reduced immune resistance. Manufacturers of waterpicks are urged to impede

  7. Landsat: A global land-imaging mission (United States)



    Across four decades since 1972, Landsat satellites have continuously acquired space-based images of the Earth's land surface, coastal shallows, and coral reefs. The Landsat Program, a joint effort of the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA), was established to routinely gather land imagery from space. NASA develops remote-sensing instruments and spacecraft, then launches and validates the performance of the instruments and satellites. The USGS then assumes ownership and operation of the satellites, in addition to managing all ground reception, data archiving, product generation, and distribution. The result of this program is a long-term record of natural and human induced changes on the global landscape.

  8. "What If" Analyses: Ways to Interpret Statistical Significance Test Results Using EXCEL or "R" (United States)

    Ozturk, Elif


    The present paper aims to review two motivations to conduct "what if" analyses using Excel and "R" to understand the statistical significance tests through the sample size context. "What if" analyses can be used to teach students what statistical significance tests really do and in applied research either prospectively to estimate what sample size…

  9. Generating Daily Synthetic Landsat Imagery by Combining Landsat and MODIS Data. (United States)

    Wu, Mingquan; Huang, Wenjiang; Niu, Zheng; Wang, Changyao


    Owing to low temporal resolution and cloud interference, there is a shortage of high spatial resolution remote sensing data. To address this problem, this study introduces a modified spatial and temporal data fusion approach (MSTDFA) to generate daily synthetic Landsat imagery. This algorithm was designed to avoid the limitations of the conditional spatial temporal data fusion approach (STDFA) including the constant window for disaggregation and the sensor difference. An adaptive window size selection method is proposed in this study to select the best window size and moving steps for the disaggregation of coarse pixels. The linear regression method is used to remove the influence of differences in sensor systems using disaggregated mean coarse reflectance by testing and validation in two study areas located in Xinjiang Province, China. The results show that the MSTDFA algorithm can generate daily synthetic Landsat imagery with a high correlation coefficient (R) ranged from 0.646 to 0.986 between synthetic images and the actual observations. We further show that MSTDFA can be applied to 250 m 16-day MODIS MOD13Q1 products and the Landsat Normalized Different Vegetation Index (NDVI) data by generating a synthetic NDVI image highly similar to actual Landsat NDVI observation with a high R of 0.97.

  10. Anaglyph, Landsat Overlay: Wellington, New Zealand (United States)


    Wellington, the capital city of New Zealand, is located on the shores of Port Nicholson, a natural harbor at the south end of North Island. The city was founded in 1840 by British emigrants and now has a regional population of more than 400,000 residents. As seen here, the natural terrain imposes strong control over the urban growth pattern. Rugged hills generally rising to 300 meters (1,000 feet) help protect the city and harbor from strong winter winds.New Zealand is seismically active and faults are readily seen in the topography. The Wellington Fault forms the straight northwestern (upper left) shoreline of the harbor. Toward the southwest (lower left) the fault crosses through the city, then forms linear canyons in the hills before continuing offshore. Toward the northeast (upper right) the fault forms the sharp mountain front along the northern edge of the heavily populated Hutt Valley.This anaglyph was generated by first draping a Landsat Thematic Mapper image over a topographic map from the Shuttle Radar Topography Mission, then using the topographic data to create two differing perspectives, one for each eye. When viewed through special glasses, the result is a vertically exaggerated view of the Earth's surface in its full three dimensions. Anaglyph glasses cover the left eye with a red filter and cover the right eye with a blue filter.Landsat satellites have provided visible light and infrared images of the Earth continuously since 1972. SRTM topographic data match the 30 meter (99 foot) spatial resolution of most Landsat images and will provide a valuable complement for studying the historic and growing Landsat data archive. The Landsat 7 Thematic Mapper image used here was provided to the SRTM project by the United States Geological Survey, Earth Resources Observation Systems (EROS) data Center, Sioux Falls, South Dakota.Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour

  11. Future health care applications resulting from progress in the neurosciences: The significance of neural plasticity research

    NARCIS (Netherlands)

    Gelijns, A.C.; Graaff, P.J.; Lopes da Silva, F.A.; Gispen, W.H.


    Neurological, communicative and behavioral disorders afflict a significant part of the population in industrialized countries, and these disorders can be expected to gain in importance in the coming decades. In a considerable number of these dis-orders impairments in plasticity, i.e. deficiencies in

  12. Landsat-8: Science and product vision for terrestrial global change research (United States)

    Roy, David P.; Wulder, M.A.; Loveland, Thomas R.; Woodcock, C.E.; Allen, R. G.; Anderson, M. C.; Helder, D.; Irons, J.R.; Johnson, D.M.; Kennedy, R.; Scambos, T.A.; Schaaf, Crystal B.; Schott, J.R.; Sheng, Y.; Vermote, E. F.; Belward, A.S.; Bindschadler, R.; Cohen, W.B.; Gao, F.; Hipple, J. D.; Hostert, Patrick; Huntington, J.; Justice, C.O.; Kilic, A.; Kovalskyy, Valeriy; Lee, Z. P.; Lymburner, Leo; Masek, J.G.; McCorkel, J.; Shuai, Y.; Trezza, R.; Vogelmann, James; Wynne, R.H.; Zhu, Z.


    Landsat 8, a NASA and USGS collaboration, acquires global moderate-resolution measurements of the Earth's terrestrial and polar regions in the visible, near-infrared, short wave, and thermal infrared. Landsat 8 extends the remarkable 40 year Landsat record and has enhanced capabilities including new spectral bands in the blue and cirrus cloud-detection portion of the spectrum, two thermal bands, improved sensor signal-to-noise performance and associated improvements in radiometric resolution, and an improved duty cycle that allows collection of a significantly greater number of images per day. This paper introduces the current (2012–2017) Landsat Science Team's efforts to establish an initial understanding of Landsat 8 capabilities and the steps ahead in support of priorities identified by the team. Preliminary evaluation of Landsat 8 capabilities and identification of new science and applications opportunities are described with respect to calibration and radiometric characterization; surface reflectance; surface albedo; surface temperature, evapotranspiration and drought; agriculture; land cover, condition, disturbance and change; fresh and coastal water; and snow and ice. Insights into the development of derived ‘higher-level’ Landsat products are provided in recognition of the growing need for consistently processed, moderate spatial resolution, large area, long-term terrestrial data records for resource management and for climate and global change studies. The paper concludes with future prospects, emphasizing the opportunities for land imaging constellations by combining Landsat data with data collected from other international sensing systems, and consideration of successor Landsat mission requirements.

  13. Investor Outlook: Significance of the Positive LCA2 Gene Therapy Phase III Results. (United States)

    Schimmer, Joshua; Breazzano, Steven


    Spark Therapeutics recently reported positive phase III results for SPK-RPE65 targeting the treatment of visual impairment caused by RPE65 gene mutations (often referred to as Leber congenital amaurosis type 2, or LCA2, but may include other retinal disorders), marking an important inflection point for the field of gene therapy. The results highlight the ability to successfully design and execute a randomized trial of a gene therapy and also reinforce the potentially predictive nature of early preclinical and clinical data. The results are expected to pave the way for the first approved gene therapy product in the United States and should sustain investor interest and confidence in gene therapy for many approaches, including retina targeting and beyond.

  14. NASA 3D Models: Landsat 7 (United States)

    National Aeronautics and Space Administration — The Landsat Program is a series of Earth-observing satellite missions jointly managed by NASA and the U.S. Geological Survey. Since 1972, Landsat satellites have...

  15. Common genetic variants are significant risk factors for early menopause: results from the Breakthrough Generations Study. (United States)

    Murray, Anna; Bennett, Claire E; Perry, John R B; Weedon, Michael N; Jacobs, Patricia A; Morris, Danielle H; Orr, Nicholas; Schoemaker, Minouk J; Jones, Michael; Ashworth, Alan; Swerdlow, Anthony J


    Women become infertile approximately 10 years before menopause, and as more women delay childbirth into their 30s, the number of women who experience infertility is likely to increase. Tests that predict the timing of menopause would allow women to make informed reproductive decisions. Current predictors are only effective just prior to menopause, and there are no long-range indicators. Age at menopause and early menopause (EM) are highly heritable, suggesting a genetic aetiology. Recent genome-wide scans have identified four loci associated with variation in the age of normal menopause (40-60 years). We aimed to determine whether theses loci are also risk factors for EM. We tested the four menopause-associated genetic variants in a cohort of approximately 2000 women with menopause≤45 years from the Breakthrough Generations Study (BGS). All four variants significantly increased the odds of having EM. Comparing the 4.5% of individuals with the lowest number of risk alleles (two or three) with the 3.0% with the highest number (eight risk alleles), the odds ratio was 4.1 (95% CI 2.4-7.1, P=4.0×10(-7)). In combination, the four variants discriminated EM cases with a receiver operator characteristic area under the curve of 0.6. Four common genetic variants identified by genome-wide association studies, had a significant impact on the odds of having EM in an independent cohort from the BGS. The discriminative power is still limited, but as more variants are discovered they may be useful for predicting reproductive lifespan.

  16. Oral challenges with four apple cultivars result in significant differences in oral allergy symptoms. (United States)

    Nybom, Hilde; Cervin-Hoberg, Charlotte; Andersson, Morgan


    We analyzed the hypoallergenic potential of a recently bred apple selection with unusually low content of Mal d 1, using an oral challenge model with three additional apple cultivars for comparison. Sixty-six birch pollen-allergic individuals with a history of oral allergy syndrome after apple intake were subjected to a double-blind oral provocation with two apple cultivars (B:0654 and 'Discovery'). Thirteen also tested two other apple cultivars ('Ingrid Marie' and 'Gloster'). Three doses were given consecutively, 30 min apart: 10 g without peel, and 10 and 50 g with peel. A final assessment was conducted 30 min after the last intake. Oral symptoms were graded from 0 to 5. Total oral symptom score (TOS) included all scores for each cultivar at all time points. B:0654 induced significantly higher TOS than 'Discovery' when tested by 66 individuals, in spite of its lower Mal d 1 content. TOS values were higher in females and increased with increasing age of the individuals when challenged with 'Discovery'. Among the 13 individuals who tested all four cultivars, B:0654 produced a higher score after the second dose compared to 'Ingrid Marie'. This was also the case after the third dose compared to 'Ingrid Marie' and 'Gloster', and again 30 min after the last intake compared to each of the other three cultivars, as well as a higher TOS compared to each of the other three cultivars (all p safe and well tolerated, and produced significant differences among the apple cultivars. Contrary to expectations, B:0654 was less well tolerated than the other three cultivars. Copyright © 2013 S. Karger AG, Basel.

  17. Social networking strategies that aim to reduce obesity have achieved significant although modest results. (United States)

    Ashrafian, Hutan; Toma, Tania; Harling, Leanne; Kerr, Karen; Athanasiou, Thanos; Darzi, Ara


    The global epidemic of obesity continues to escalate. Obesity accounts for an increasing proportion of the international socioeconomic burden of noncommunicable disease. Online social networking services provide an effective medium through which information may be exchanged between obese and overweight patients and their health care providers, potentially contributing to superior weight-loss outcomes. We performed a systematic review and meta-analysis to assess the role of these services in modifying body mass index (BMI). Our analysis of twelve studies found that interventions using social networking services produced a modest but significant 0.64 percent reduction in BMI from baseline for the 941 people who participated in the studies' interventions. We recommend that social networking services that target obesity should be the subject of further clinical trials. Additionally, we recommend that policy makers adopt reforms that promote the use of anti-obesity social networking services, facilitate multistakeholder partnerships in such services, and create a supportive environment to confront obesity and its associated noncommunicable diseases. Project HOPE—The People-to-People Health Foundation, Inc.

  18. Tacrolimus interaction with nafcillin resulting in significant decreases in tacrolimus concentrations: A case report. (United States)

    Wungwattana, Minkey; Savic, Marizela


    Tacrolimus (TAC) is subject to many drug interactions as a result of its metabolism primarily via CYP450 isoenzyme 3A4. Numerous case reports of TAC and CYP3A4 inducers and inhibitors have been described including antimicrobials, calcium channel antagonists, and antiepileptic drugs. We present the case of a 13-year-old patient with cystic fibrosis and a history of liver transplantation, where subtherapeutic TAC concentrations were suspected to be a result of concomitant TAC and nafcillin (NAF) therapy. The observed drug interaction occurred on two separate hospital admissions, during both of which the patient exhibited therapeutic TAC concentrations prior to exposure to NAF, a CYP3A4 inducer. Upon discontinuation of NAF, TAC concentrations recovered in both instances. This case represents a drug-drug interaction between TAC and NAF that has not previously been reported to our knowledge. Despite the lack of existing reports of interaction between these two agents, this case highlights the importance of therapeutic drug monitoring and assessing for any potential drug-drug or drug-food interactions in patients receiving TAC therapy. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  19. Waste Minimization Improvements Achieved Through Six Sigma Analysis Result In Significant Cost Savings

    International Nuclear Information System (INIS)

    Mousseau, Jeffrey D.; Jansen, John R.; Janke, David H.; Plowman, Catherine M.


    Improved waste minimization practices at the Department of Energy's (DOE) Idaho National Engineering and Environmental Laboratory (INEEL) are leading to a 15% reduction in the generation of hazardous and radioactive waste. Bechtel, BWXT Idaho, LLC (BBWI), the prime management and operations contractor at the INEEL, applied the Six Sigma improvement process to the INEEL Waste Minimization Program to review existing processes and define opportunities for improvement. Our Six Sigma analysis team: composed of an executive champion, process owner, a black belt and yellow belt, and technical and business team members used this statistical based process approach to analyze work processes and produced ten recommendations for improvement. Recommendations ranged from waste generator financial accountability for newly generated waste to enhanced employee recognition programs for waste minimization efforts. These improvements have now been implemented to reduce waste generation rates and are producing positive results

  20. AREVA - 2012 annual results: significant turnaround in performance one year after launching the Action 2016 plan

    International Nuclear Information System (INIS)

    Duperray, Julien; Berezowskyj, Katherine; Kempkes, Vincent; Rosso, Jerome; Thebault, Alexandre; Scorbiac, Marie de; Repaire, Philippine du


    One year after launching Areva's Action 2016 strategic plan, the first results are in. AREVA is ahead of schedule in executing its recovery plan. While pursuing its efforts in the management of a few difficult projects (such as OL3), Areva group was able to return to a virtuous performance cycle rooted in strong growth in nuclear order intake and good progress on its cost reduction program. Commercially, despite the difficult economic environment, AREVA was able to capitalize on its leadership in the installed base and on its long-term partnerships with strategic customers, beginning with EDF, with which AREVA renewed a confident and constructive working relationship. Areva has secured 80% of its objective of one billion euros of savings by the end of 2015 to improve its competitiveness. The group also continued efforts to optimize working capital requirement and control the capital expenditure trajectory. Together, these results enabled AREVA to exceed the objectives set for 2012 for two key indicators of its strategic plan: EBITDA and free operating cash flow. Nearly 60% of the 2.1 billion euros devoted to capital expenditures for future growth in 2012 were funded by operations, a quasi-doubled share compared to 2011. Areva's floor target for asset disposals was achieved one year ahead of schedule, also helping the Group to control its net debt, which remained below 4 billion euros. In 2013, Areva is continuing to implement the Action 2016 plan to keep its turnaround on track. In summary: - Backlog renewed over the year 2012 to euro 45.4 bn thanks to the increase in nuclear order intake; - Sales revenue growth: euro 9.342 bn (+5.3% vs. 2011), led by nuclear and renewables operations; - Very sharp upturn in EBITDA: euro 1.007 bn (+euro 586 m vs. 2011) - Very net improvement in free operating cash flow: -euro 854 m (+euro 512 m vs. 2011); - Back to positive reported operating income: euro 118 m (+euro 1.984 bn vs. 2011); - 2012-2013 floor target for asset disposals

  1. Late Quaternary stratigraphy of the La Janda Basin (SW Spain) - first results and palaeoenvironmental significance (United States)

    Höbig, Nicole; Santisteban, Juan; Mediavilla, Rosa; May, Simon Matthias; Klasen, Nicole; Brückner, Helmut; van't Hoff, Jasmijn; Reicherter, Klaus


    The La Janda basin in southern Spain is a near-shore geo-bio-archive comprising a variable Quaternary depositional history, with shallow marine, lacustrine, palustrine, and terrestrial strata. In the 1930s the lake was drained and is serving now as a huge agricultural area. The 33 m-core recovered in fall 2016 along with several shallower drill cores up to c. 15 m, reveals insights into a unique mixed terrestrial palaeo-environmental archive in Andalucia influenced by the Atlantic Ocean and hence the North Atlantic Oscillation (NAO) within the Gulf of Cádiz. The basin's evolution was influenced both by the postglacial marine transgression and by an active tectonic fault controlling most of the accommodation space by causing subsidence. Our long core was accompanied by further corings along an E-W striking transect in order to reveal also the relation of the influence of tectonic activity with sedimentary sequences. Multi-Sensor Core Logging has been completed. Results of sedimentological, geochemical and micropalaeontological analyses will be presented in the frame of the climate variations during the Late Pleistocene and the Holocene, along with a preliminary age-depth model based on radiocarbon (AMS-14C) and optical stimulated luminescence (OSL) dating techniques. Our investigations ultimately aim at providing valuable information on major Late Pleistocene to Holocene climatic and palaeo-environmental fluctuations in the southernmost part of the Iberian Peninsula.

  2. A Limited Structural Modification Results in a Significantly More Efficacious Diazachrysene-Based Filovirus Inhibitor

    Directory of Open Access Journals (Sweden)

    Rekha G. Panchal


    Full Text Available Ebola (EBOV and Marburg (MARV filoviruses are highly infectious pathogens causing deadly hemorrhagic fever in humans and non-human primates. Promising vaccine candidates providing immunity against filoviruses have been reported. However, the sporadic nature and swift progression of filovirus disease underlines the need for the development of small molecule therapeutics providing immediate antiviral effects. Herein we describe a brief structural exploration of two previously reported diazachrysene (DAAC-based EBOV inhibitors. Specifically, three analogs were prepared to examine how slight substituent modifications would affect inhibitory efficacy and inhibitor-mediated toxicity during not only EBOV, but also MARV cellular infection. Of the three analogs, one was highly efficacious, providing IC50 values of 0.696 µM ± 0.13 µM and 2.76 µM ± 0.21 µM against EBOV and MARV infection, respectively, with little or no associated cellular toxicity. Overall, the structure-activity and structure-toxicity results from this study provide a framework for the future development of DAAC-based filovirus inhibitors that will be both active and non-toxic in vivo.

  3. Effects of Landsat 5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper plus radiometric and geometric calibrations and corrections on landscape characterization (United States)

    Vogelmann, James E.; Helder, Dennis; Morfitt, Ron; Choate, Michael J.; Merchant, James W.; Bulley, Henry


    The Thematic Mapper (TM) instruments onboard Landsats 4 and 5 provide high-quality imagery appropriate for many different applications, including land cover mapping, landscape ecology, and change detection. Precise calibration was considered to be critical to the success of the Landsat 7 mission and, thus, issues of calibration were given high priority during the development of the Enhanced Thematic Mapper Plus (ETM+). Data sets from the Landsat 5 TM are not routinely corrected for a number of radiometric and geometric artifacts, including memory effect, gain/bias, and interfocal plane misalignment. In the current investigation, the effects of correcting vs. not correcting these factors were investigated for several applications. Gain/bias calibrations were found to have a greater impact on most applications than did memory effect calibrations. Correcting interfocal plane offsets was found to have a moderate effect on applications. On June 2, 1999, Landsats 5 and 7 data were acquired nearly simultaneously over a study site in the Niobrara, NE area. Field radiometer data acquired at that site were used to facilitate crosscalibrations of Landsats 5 and 7 data. Current findings and results from previous investigations indicate that the internal calibrator of Landsat 5 TM tracked instrument gain well until 1988. After this, the internal calibrator diverged from the data derived from vicarious calibrations. Results from this study also indicate very good agreement between prelaunch measurements and vicarious calibration data for all Landsat 7 reflective bands except Band 4. Values are within about 3.5% of each other, except for Band 4, which differs by 10%. Coefficient of variation (CV) values derived from selected targets in the imagery were also analyzed. The Niobrara Landsat 7 imagery was found to have lower CV values than Landsat 5 data, implying that lower levels of noise characterize Landsat 7 data than current Landsat 5 data. It was also found that following

  4. Characterization of active fires in West African savannas by analysis of satellite data: Landsat Thematic Mapper

    International Nuclear Information System (INIS)

    Brustet, J.M.; Vickos, J.B.; Fontan, J.; Podaire, A.; Lavenu, F.


    Landsat Thematic Mapper provides valuable information on biomass burning, such as the apparent temperature of a fire and its shape. However, the surface determined by remote sensing does not exactly correspond to the burning area, due to an artificial enlargement of the fire front width. This enlargement of the fire front width. This enlargement may have diverse origins. In particular, it is difficult to estimate the temperature of the areas that are behind the fire front and that have been just burned. Emissions from these areas may be detectable by Landsat channels, thus resulting in the observed enlargement of the fire front. Additional experiments including remote sensing by plane are necessary to allow a more complete understanding of these phenomena. Biomass burning is an important source of atmospheric pollution on a global scale. This study indicates that a fire is a significant source of pollution on a local scale

  5. Spatiotemporal Change Detection Using Landsat Imagery: the Case Study of Karacabey Flooded Forest, Bursa, Turkey (United States)

    Akay, A. E.; Gencal, B.; Taş, İ.


    This short paper aims to detect spatiotemporal detection of land use/land cover change within Karacabey Flooded Forest region. Change detection analysis applied to Landsat 5 TM images representing July 2000 and a Landsat 8 OLI representing June 2017. Various image processing tools were implemented using ERDAS 9.2, ArcGIS 10.4.1, and ENVI programs to conduct spatiotemporal change detection over these two images such as band selection, corrections, subset, classification, recoding, accuracy assessment, and change detection analysis. Image classification revealed that there are five significant land use/land cover types, including forest, flooded forest, swamp, water, and other lands (i.e. agriculture, sand, roads, settlement, and open areas). The results indicated that there was increase in flooded forest, water, and other lands, while the cover of forest and swamp decreased.

  6. Significance of Phébus-FP results for plant safety in Switzerland

    International Nuclear Information System (INIS)

    Birchley, J.; Güntay, S.


    Highlights: • Prototypicality of Phebus is unique for severe accident integral code assessment. • MELCOR and SCDAP show good simulation capability. • Phebus revealed knowledge gaps concerning organic iodine source. • Complementary studies seek to reduce uncertainties. • New engineering technology is developed to resolve organic iodine issue. - Abstract: Switzerland, in common with other countries, uses source term estimates to formulate emergency plans in the unlikely event of an accident with release of activity to the environment. In the past estimates have typically been based on conservative treatments of the accident sequence, necessitated by the limited validation status of models used for the phenomena that control the reactor accident evolution. Although analyses using best-estimate tools frequently indicated substantially smaller releases – knowledge and data were insufficient to place reliance on the methods or the calculated results. The Phébus programme is unique in providing a source of integral transient data on fission product release, transport and chemical behaviour under prototypic conditions, capturing the entire portfolio of processes – transport, material and chemical – and their causal interaction. To this day, no other source of such data is available. These data provide a means to assess, improve and validate methods for source term evaluation and establish the needs for establishing new processes to mitigate the source term. There are strong synergies and complementarities between the Phébus project, the International Source Term Project, the iodine-related studies at PSI and the aerosol retention projects at PSI, and current moves toward improved management/mitigation of severe accidents. The Federal Nuclear Safety Inspectorate (ENSI), Paul Scherrer Institute (PSI) and the Swiss utilities running five nuclear power plants share in the findings. The need to strengthen the foundation on which we perform best

  7. Remote sensing of species diversity using Landsat 8 spectral variables (United States)

    Madonsela, Sabelo; Cho, Moses Azong; Ramoelo, Abel; Mutanga, Onisimo


    The application of remote sensing in biodiversity estimation has largely relied on the Normalized Difference Vegetation Index (NDVI). The NDVI exploits spectral information from red and near infrared bands of Landsat images and it does not consider canopy background conditions hence it is affected by soil brightness which lowers its sensitivity to vegetation. As such NDVI may be insufficient in explaining tree species diversity. Meanwhile, the Landsat program also collects essential spectral information in the shortwave infrared (SWIR) region which is related to plant properties. The study was intended to: (i) explore the utility of spectral information across Landsat-8 spectrum using the Principal Component Analysis (PCA) and estimate alpha diversity (α-diversity) in the savannah woodland in southern Africa, and (ii) define the species diversity index (Shannon (H‧), Simpson (D2) and species richness (S) - defined as number of species in a community) that best relates to spectral variability on the Landsat-8 Operational Land Imager dataset. We designed 90 m × 90 m field plots (n = 71) and identified all trees with a diameter at breast height (DbH) above 10 cm. H‧, D2 and S were used to quantify tree species diversity within each plot and the corresponding spectral information on all Landsat-8 bands were extracted from each field plot. A stepwise linear regression was applied to determine the relationship between species diversity indices (H‧, D2 and S) and Principal Components (PCs), vegetation indices and Gray Level Co-occurrence Matrix (GLCM) texture layers with calibration (n = 46) and test (n = 23) datasets. The results of regression analysis showed that the Simple Ratio Index derivative had a higher relationship with H‧, D2 and S (r2= 0.36; r2= 0.41; r2= 0.24 respectively) compared to NDVI, EVI, SAVI or their derivatives. Moreover the Landsat-8 derived PCs also had a higher relationship with H‧ and D2 (r2 of 0.36 and 0.35 respectively) than the

  8. Validating gap-filling of Landsat ETM+ satellite images in the Golestan Province, Iran

    NARCIS (Netherlands)

    Mohammdy, M.; Moradi, H.R.; Zeinivand, H.; Temme, A.J.A.M.; Pourghasemi, H.R.; Alizadeh, H.


    The Landsat series of satellites provides a valuable data source for land surface mapping and monitoring. Unfortunately, the scan line corrector (SLC) of the Landsat7 Enhanced Thematic Mapper plus (ETM+) sensor failed on May 13, 2003. This problem resulted in about 22 % of the pixels per scene not

  9. Landsat eyes help guard the world's forests (United States)

    Campbell, Jon


    SummaryThe Landsat program is a joint effort between the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA), but the partner agencies have distinct roles. NASA develops remote-sensing instruments and spacecraft, launches satellites, and validates their performance in orbit. The USGS owns and operates Landsat satellites in space and manages their data transmissions, including ground reception, archiving, product generation, and public distribution. In 2008, with support from the U.S. Department of the Interior, the USGS made its Landsat data free to anyone in the world.The current satellites in the Landsat program, Landsat 7 (launched in 1999) and Landsat 8 (launched in 2013), provide complete coverage of the Earth every eight days. A Landsat 9 satellite is scheduled for launch in late 2020.

  10. Landsat change detection can aid in water quality monitoring (United States)

    Macdonald, H. C.; Steele, K. F.; Waite, W. P.; Shinn, M. R.


    Comparison between Landsat-1 and -2 imagery of Arkansas provided evidence of significant land use changes during the 1972-75 time period. Analysis of Arkansas historical water quality information has shown conclusively that whereas point source pollution generally can be detected by use of water quality data collected by state and federal agencies, sampling methodologies for nonpoint source contamination attributable to surface runoff are totally inadequate. The expensive undertaking of monitoring all nonpoint sources for numerous watersheds can be lessened by implementing Landsat change detection analyses.


    Directory of Open Access Journals (Sweden)

    Zulaiha Zulaiha


    Full Text Available ABSTRACT: Given the pivotal role played by the Cantung River for the supervision and management of the public good becomes important. Incoming sediment load can damage the uncontrolled flow conditions of the Cantung river and estuary. Observations of suspended sediment can take advantage of multitemporal Landsat imagery. This study uses Landsat satellite image data corrected 5TM March 5, 1992 data acquisition path/row 117/62, Landsat data acquisition 5TM 22 May 1997 path/row 117/62, Landsat data acquisition 5TM March 27, 2000 the path/row 117/62. Several stages in processing the image, that is the conversion of DN to reflectance values, cropping, water-not water secession, and the class divide sediment concentration by density slicing technique. Spatial distribution of suspended sediment in the estuary of the Cantung River Landsat image processing results 5TM March 5, 1992, Landsat 5TM May 22, 1997, and March 27, 2000 Landsat 5TM show distribution patterns of suspended sediment from the River Cantung the same direction, that is northeast. Sediment concentrations were detected in the Landsat image processing 5TM March 5, 1992 the largest-value 27,564096 mg/l and the smallest 14,886048 mg/l. Sediment concentrations were detected in the Landsat image processing 5TM May 22, 1997 the largest-value 121,476776 mg/l and the smallest 12,647415 mg/l. Sediment concentrations were detected in the Landsat image processing 5TM March 27, 2000 most valuable 159,256704 mg/l and the smallest 10,584161 mg/l. Getting away from the effect Cantung River estuary sediment concentration of river flow Cantung tends to get smaller. Changes in the distribution area of the sediments of March 5, 1992 until March 27, 2000 amounted to 450 m2/year.   Keywords: Remote Sensing, Sedimentation, Landsat, Cantung River

  12. Incorporating Spatio-temporal Phenological Variation in Detecting Exotic Saltcedar Using Landsat Time Series (United States)

    Diao, C.; Wang, L.


    The invasion of exotic species compromises ecosystem functions and causes substantial economic losses at the global scale. Over the past century, non-native saltcedar has expanded into most riparian zones in southwestern United States and posed significant threats to the native biotic communities. Repeated monitoring of saltcedar distribution is essential for conservation agencies to locate highly susceptible areas and develop corresponding control strategies. Throughout the phenological cycle, the leaf senescence stage has been found to be the most crucial in spectrally detecting saltcedar. However, due to climate variability and anthropogenic forcing, the timing of saltcedar leaf senescence may vary over space and time. This spatial and inter-annual variation need to be accommodated to pinpoint the appropriate remotely sensed imagery for saltcedar mapping. The objective of this study was to develop a Landsat-based Multiyear Spectral Angle Clustering (MSAC) model to monitor the inter-annual leaf senescence of exotic saltcedar. At the Landsat scale, the time series analysis of vegetation phenology is usually limited by the temporal resolution of images. The MSAC model can overcome this limit and take advantage of the Landsat images from multiple years to compensate the lack of images in a single year. Results indicated the MSAC model provided a Landsat-based solution to capture the inter-annual leaf senescence of saltcedar. Compared to traditional NDVI-based phenological approaches, the proposed model achieved a more accurate classification results of saltcedar across years. The MSAC model provides unique opportunities to guide the selection of appropriate remotely sensed image for repetitive saltcedar mapping.

  13. LANDSAT menhaden and thread herring resources investigation. [Northern Gulf of Mexico (United States)

    Kemmerer, A. J. (Principal Investigator)


    The author has identified the following significant results. The most significant achievement realized thus far has been the successful completion of the data acquisition phase. This success must be attributed to the interest, support, and competency of the participants. The apparent consistency of water color and turbidity condition over time and between test sites at sites of menhaden capture is significant especially since color is readily measured with satellite and aircraft sensors and a LANDSAT MSS based computer model for inferring tubidity has been developed.

  14. Landsat Data Continuity Mission (LDCM) - Optimizing X-Band Usage (United States)

    Garon, H. M.; Gal-Edd, J. S.; Dearth, K. W.; Sank, V. I.


    The NASA version of the low-density parity check (LDPC) 7/8-rate code, shortened to the dimensions of (8160, 7136), has been implemented as the forward error correction (FEC) schema for the Landsat Data Continuity Mission (LDCM). This is the first flight application of this code. In order to place a 440 Msps link within the 375 MHz wide X band we found it necessary to heavily bandpass filter the satellite transmitter output . Despite the significant amplitude and phase distortions that accompanied the spectral truncation, the mission required BER is maintained at LDPC code and the amplitude and phase compensation provided in the receiver. Similar results were obtained with receivers from several vendors.

  15. Using ecological zones to increase the detail of Landsat classifications (United States)

    Fox, L., III; Mayer, K. E.


    Changes in classification detail of forest species descriptions were made for Landsat data on 2.2 million acres in northwestern California. Because basic forest canopy structures may exhibit very similar E-M energy reflectance patterns in different environmental regions, classification labels based on Landsat spectral signatures alone become very generalized when mapping large heterogeneous ecological regions. By adding a seven ecological zone stratification, a 167% improvement in classification detail was made over the results achieved without it. The seven zone stratification is a less costly alternative to the inclusion of complex collateral information, such as terrain data and soil type, into the Landsat data base when making inventories of areas greater than 500,000 acres.

  16. Kerr Reservoir LANDSAT experiment analysis for March 1981 (United States)

    Lecroy, S. R. (Principal Investigator)


    LANDSAT radiance data were used in an experiment conducted on the waters of Kerr Reservoir to determine if reliable algorithms could be developed that relate water quality parameters to remotely sensed data. A mix of different types of algorithms using the LANDSAT bands was generated to provide a thorough understanding of the relationships among the data involved. Except for secchi depth, the study demonstrated that for the ranges measured, the algorithms that satisfactorily represented the data encompass a mix of linear and nonlinear forms using only one LANDSAT band. Ratioing techniques did not improve the results since the initial design of the experiment minimized the errors against which this procedure is effective. Good correlations were found for total suspended solids, iron, turbidity, and secchi depth. Marginal correlations were discovered for nitrate and tannin + lignin. Quantification maps of Kerr Reservoir are presented for many of the water quality parameters using the developed algorithms.

  17. A Landsat study of water quality in Lake Okeechobee (United States)

    Gervin, J. C.; Marshall, M. L.


    This paper uses multiple regression techniques to investigate the relationship between Landsat radiance values and water quality measurements. For a period of over one year, the Central and Southern Florida Flood Control District sampled the water of Lake Okeechobee for chlorophyll, carotenoids, turbidity, and various nutrients at the time of Landsat overpasses. Using an overlay map of the sampling stations, Landsat radiance values were measured from computer compatible tapes using a GE image 100 and averaging over a 22-acre area at each station. These radiance values in four bands were used to form a number of functions (powers, logarithms, exponentials, and ratios), which were then compared with the ground measurements using multiple linear regression techniques. Several dates were used to provide generality and to study possible seasonal variations. Individual correlations were presented for the various water quality parameters and best fit equations were examined for chlorophyll and turbidity. The results and their relationship to past hydrological research were discussed.

  18. Combining Estimation of Green Vegetation Fraction in an Arid Region from Landsat 7 ETM+ Data

    Directory of Open Access Journals (Sweden)

    Kun Jia


    Full Text Available Fractional vegetation cover (FVC, or green vegetation fraction, is an important parameter for characterizing conditions of the land surface vegetation, and also a key variable of models for simulating cycles of water, carbon and energy on the land surface. There are several types of FVC estimation models using remote sensing data, and evaluating their performance over a specific region is of great significance. Therefore, this study firstly evaluated three types of FVC estimation models using Landsat 7 ETM+ data in an agriculture region of Heihe River Basin, China, and then proposed a combination strategy from different individual models to improve the FVC estimation accuracy, which employed the multiple linear regression (MLR and Bayesian model average (BMA methods. The validation results indicated that the spectral mixture analysis model with three endmembers (SMA3 achieved the best FVC estimation accuracy (determination coefficient (R2 = 0.902, root mean square error (RMSE = 0.076 among the seven individual models using Landsat 7 ETM+ data. In addition, the MLR and BMA combination methods could both improve FVC estimation accuracy (R2 = 0.913, RMSE = 0.063 and R2 = 0.904, RMSE = 0.069 for MLR and BMA, respectively. Therefore, it could be concluded that both MLR and BMA combination methods integrating FVC estimates from different models using Landsat 7 ETM+ data could effectively weaken the estimation errors of individual models and improve the final FVC estimation accuracy.

  19. Multitemporal Snow Cover Mapping in Mountainous Terrain for Landsat Climate Data Record Development (United States)

    Crawford, Christopher J.; Manson, Steven M.; Bauer, Marvin E.; Hall, Dorothy K.


    A multitemporal method to map snow cover in mountainous terrain is proposed to guide Landsat climate data record (CDR) development. The Landsat image archive including MSS, TM, and ETM+ imagery was used to construct a prototype Landsat snow cover CDR for the interior northwestern United States. Landsat snow cover CDRs are designed to capture snow-covered area (SCA) variability at discrete bi-monthly intervals that correspond to ground-based snow telemetry (SNOTEL) snow-water-equivalent (SWE) measurements. The June 1 bi-monthly interval was selected for initial CDR development, and was based on peak snowmelt timing for this mountainous region. Fifty-four Landsat images from 1975 to 2011 were preprocessed that included image registration, top-of-the-atmosphere (TOA) reflectance conversion, cloud and shadow masking, and topographic normalization. Snow covered pixels were retrieved using the normalized difference snow index (NDSI) and unsupervised classification, and pixels having greater (less) than 50% snow cover were classified presence (absence). A normalized SCA equation was derived to independently estimate SCA given missing image coverage and cloud-shadow contamination. Relative frequency maps of missing pixels were assembled to assess whether systematic biases were embedded within this Landsat CDR. Our results suggest that it is possible to confidently estimate historical bi-monthly SCA from partially cloudy Landsat images. This multitemporal method is intended to guide Landsat CDR development for freshwaterscarce regions of the western US to monitor climate-driven changes in mountain snowpack extent.

  20. Green leaf phenology at Landsat resolution: scaling from the plot to satellite (United States)

    Fisher, J. I.; Mustard, J. F.; Vadeboncour, M.


    Despite the large number of in situ, plot-level phenological measurements and satellite-derived phenological studies, there has been little success to date in merging these records temporally or spatially. In particular, while most phenological patterns and trends derived from satellites appear realistic and coherent, they may not reflect spatial and temporal patterns at the plot level. An obvious explanation is the drastic scale difference from plot-level to most satellite observations. In this research, we bridge this scale gap through higher resolution satellite records (Landsat) and quantify the accuracy of satellite-derived metrics with direct field measurements. We compiled fifty-seven Landsat scenes from southern New England (P12 R51) from 1984 to 2002. Green vegetation areal abundance for each scene was derived from spectral mixture analysis and a single set of endmembers. The leaf area signal was fit with a logistic-growth simulating sigmoid curve to derive phenological markers (half-maximum leaf-onset and offset). Spring leaf-onset dates in homogenous stands of deciduous forests displayed significant and persistent local variability. The local variability was validated with multiple springtime ground observations (r2 = 0.91). The highest degree of verified small-scale variation occurred where contiguous forests displayed leaf-onset gradients of 10-14 days over short distances (example, our results indicate that deciduous forests in the Providence, RI metropolitan area leaf out 5-7 days earlier than comparable rural areas. In preliminary work, we validated the Landsat-derived metrics with similar analyses of MODIS and AVHRR, and demonstrate that aggregating diverse local phenologies into coarse grids may convolute interpretations. Despite these complications, the platform-independent curve-fit methodology may be extended across platforms and field data. The methodologically consistent approach, in tandem with Landsat data, allows us to effectively scale

  1. Automated Agricultural Field Extraction from Multi-temporal Web Enabled Landsat Data (United States)

    Yan, L.; Roy, D. P.


    Agriculture has caused significant anthropogenic surface change. In many regions agricultural field sizes may be increasing to maximize yields and reduce costs resulting in decreased landscape spatial complexity and increased homogenization of land uses with potential for significant biogeochemical and ecological effects. To date, studies of the incidence, drivers and impacts of changing field sizes have not been undertaken over large areas because of computational constraints and because consistently processed appropriate resolution data have not been available or affordable. The Landsat series of satellites provides near-global coverage, long term, and appropriate spatial resolution (30m) satellite data to document changing field sizes. The recent free availability of all the Landsat data in the U.S. Landsat archive now provides the opportunity to study field size changes in a global and consistent way. Commercial software can be used to extract fields from Landsat data but are inappropriate for large area application because they require considerable human interaction. This paper presents research to develop and validate an automated computational Geographic Object Based Image Analysis methodology to extract agricultural fields and derive field sizes from Web Enabled Landsat Data (WELD) ( WELD weekly products (30m reflectance and brightness temperature) are classified into Satellite Image Automatic Mapper™ (SIAM™) spectral categories and an edge intensity map and a map of the probability of each pixel being agricultural are derived from five years of 52 weeks of WELD and corresponding SIAM™ data. These data are fused to derive candidate agriculture field segments using a variational region-based geometric active contour model. Geometry-based algorithms are used to decompose connected segments belonging to multiple fields into coherent isolated field objects with a divide and conquer strategy to detect and merge partial circle

  2. Geologic mapping using LANDSAT data (United States)

    Siegal, B. S.; Abrams, M. J.


    The feasibility of automated classification for lithologic mapping with LANDSAT digital data was evaluated using three classification algorithms. The two supervised algorithms analyzed, a linear discriminant analysis algorithm and a hybrid algorithm which incorporated the Parallelepiped algorithm and the Bayesian maximum likelihood function, were comparable in terms of accuracy; however, classification was only 50 per cent accurate. The linear discriminant analysis algorithm was three times as efficient as the hybrid approach. The unsupervised classification technique, which incorporated the CLUS algorithm, delineated the major lithologic boundaries and, in general, correctly classified the most prominent geologic units. The unsupervised algorithm was not as efficient nor as accurate as the supervised algorithms. Analysis of spectral data for the lithologic units in the 0.4 to 2.5 microns region indicated that a greater separability of the spectral signatures could be obtained using wavelength bands outside the region sensed by LANDSAT.

  3. Landsat imagery: a unique resource (United States)

    Miller, H.; Sexton, N.; Koontz, L.


    Landsat satellites provide high-quality, multi-spectral imagery of the surface of the Earth. These moderate-resolution, remotely sensed images are not just pictures, but contain many layers of data collected at different points along the visible and invisible light spectrum. These data can be manipulated to reveal what the Earth’s surface looks like, including what types of vegetation are present or how a natural disaster has impacted an area (Fig. 1).

  4. Temporal validation for landsat-based volume estimation model (United States)

    Renaldo J. Arroyo; Emily B. Schultz; Thomas G. Matney; David L. Evans; Zhaofei Fan


    Satellite imagery can potentially reduce the costs and time associated with ground-based forest inventories; however, for satellite imagery to provide reliable forest inventory data, it must produce consistent results from one time period to the next. The objective of this study was to temporally validate a Landsat-based volume estimation model in a four county study...

  5. An algorithm to retrieve Land Surface Temperature using Landsat-8 ...

    African Journals Online (AJOL)

    Ayodeji Ogunode;Mulemwa Akombelwa

    The results show temperature variation over a long period of time can be ... Remote sensing of LST using infrared radiation gives the average surface temperature of the scene ... advantage over previous Landsat series. ..... Li, F., Jackson, T. J., Kustas, W. P., Schmugge, T. J., French, A. N., Cosh, M. H. & Bindlish, R. 2004.

  6. Analysis and correction of Landsat 4 and 5 Thematic Mapper Sensor Data (United States)

    Bernstein, R.; Hanson, W. A.


    Procedures for the correction and registration and registration of Landsat TM image data are examined. The registration of Landsat-4 TM images of San Francisco to Landsat-5 TM images of the San Francisco using the interactive geometric correction program and the cross-correlation technique is described. The geometric correction program and cross-correlation results are presented. The corrections of the TM data to a map reference and to a cartographic database are discussed; geometric and cartographic analyses are applied to the registration results.

  7. Spectral Unmixing Analysis of Time Series Landsat 8 Images (United States)

    Zhuo, R.; Xu, L.; Peng, J.; Chen, Y.


    Temporal analysis of Landsat 8 images opens up new opportunities in the unmixing procedure. Although spectral analysis of time series Landsat imagery has its own advantage, it has rarely been studied. Nevertheless, using the temporal information can provide improved unmixing performance when compared to independent image analyses. Moreover, different land cover types may demonstrate different temporal patterns, which can aid the discrimination of different natures. Therefore, this letter presents time series K-P-Means, a new solution to the problem of unmixing time series Landsat imagery. The proposed approach is to obtain the "purified" pixels in order to achieve optimal unmixing performance. The vertex component analysis (VCA) is used to extract endmembers for endmember initialization. First, nonnegative least square (NNLS) is used to estimate abundance maps by using the endmember. Then, the estimated endmember is the mean value of "purified" pixels, which is the residual of the mixed pixel after excluding the contribution of all nondominant endmembers. Assembling two main steps (abundance estimation and endmember update) into the iterative optimization framework generates the complete algorithm. Experiments using both simulated and real Landsat 8 images show that the proposed "joint unmixing" approach provides more accurate endmember and abundance estimation results compared with "separate unmixing" approach.

  8. Landsat Science Team meeting: Winter 2015 (United States)

    Schroeder, Todd A.; Loveland, Thomas; Wulder, Michael A.; Irons, James R.


    The summer meeting of the joint U.S. Geological Survey (USGS)–NASA Landsat Science Team (LST) was held at the USGS’s Earth Resources Observation and Science (EROS) Center July 7-9, 2015, in Sioux Falls, SD. The LST co-chairs, Tom Loveland [EROS—Senior Scientist] and Jim Irons [NASA’s Goddard Space Flight Center (GSFC)—Landsat 8 Project Scientist], opened the three-day meeting on an upbeat note following the recent successful launch of the European Space Agency’s Sentinel-2 mission on June 23, 2015 (see image on page 14), and the news that work on Landsat 9 has begun, with a projected launch date of 2023.With over 60 participants in attendance, this was the largest LST meeting ever held. Meeting topics on the first day included Sustainable Land Imaging and Landsat 9 development, Landsat 7 and 8 operations and data archiving, the Landsat 8 Thermal Infrared Sensor (TIRS) stray-light issue, and the successful Sentinel-2 launch. In addition, on days two and three the LST members presented updates on their Landsat science and applications research. All presentations are available at Meetings.php.

  9. Assessing the role of climate and resource management on groundwater dependent ecosystem changes in arid environments with the Landsat archive (United States)

    Huntington, Justin; McGwire, Kenneth C.; Morton, Charles; Snyder, Keirith A.; Peterson, Sarah; Erickson, Tyler; Niswonger, Richard G.; Carroll, Rosemary W.H.; Smith, Guy; Allen, Richard


    along with downscaled North American Land Data Assimilation System gridded meteorological data, which are used for both atmospheric correction and correlation analysis. Results from the cross-sensor comparison indicate a benefit from the application of a consistent atmospheric correction method, and that NDVI derived from Landsat 7 and 8 are very similar within the study area. Results from continuous Landsat time series analysis clearly illustrate that there are strong correlations between changes in vegetation vigor, precipitation, evaporative demand, depth to groundwater, and riparian restoration. Trends in summer NDVI associated with riparian restoration and groundwater level changes were found to be statistically significant, and interannual summer NDVI was found to be moderately correlated to interannual water-year precipitation for baseline study sites. Results clearly highlight the complementary relationship between water-year PPT, NDVI, and evaporative demand, and are consistent with regional vegetation index and complementary relationship studies. This work is supporting land and water managers for evaluation of GDEs with respect to climate, groundwater, and resource management.

  10. Comparison of Sentinel-2A and Landsat-8 Nadir BRDF Adjusted Reflectance (NBAR) over Southern Africa (United States)

    Li, J.; Roy, D. P.; Zhang, H.


    The Landsat satellites have been providing moderate resolution imagery of the Earth's surface for over 40 years with continuity provided by the Landsat 8 and planned Landsat 9 missions. The European Space Agency Sentinel-2 satellite was successfully launched into a polar sun-synchronous orbit in 2015 and carries the Multi Spectral Instrument (MSI) that has Landsat-like bands and acquisition coverage. These new sensors acquire images at view angles ± 7.5° (Landsat) and ± 10.3° (Sentinel-2) from nadir that result in small directional effects in the surface reflectance. When data from adjoining paths, or from long time series are used, a model of the surface anisotropy is required to adjust observations to a uniform nadir view (primarily for visual consistency, vegetation monitoring, or detection of subtle surface changes). Recently a generalized approach was published that provides consistent Landsat view angle corrections to provide nadir BRDF-adjusted reflectance (NBAR). Because the BRDF shapes of different terrestrial surfaces are sufficiently similar over the narrow 15° Landsat field of view, a fixed global set of MODIS BRDF spectral model parameters was shown to be adequate for Landsat NBAR derivation with little sensitivity to the land cover type, condition, or surface disturbance. This poster demonstrates the application of this methodology to Sentinel-2 data over a west-east transect across southern Africa. The reflectance differences between adjacent overlapping paths in the forward and backward scatter directions are quantified for both before and after BRDF correction. Sentinel-2 and Landsat-8 reflectance and NBAR inter-comparison results considering different stages of cloud and saturation filtering, and filtering to reduce surface state differences caused by acquisition time differences, demonstrate the utility of the approach. The relevance and limitations of the corrections for providing consistent moderate resolution reflectance are discussed.

  11. Radiometric characterization of Landsat Collection 1 products (United States)

    Micijevic, Esad; Haque, Md. Obaidul; Mishra, Nischal


    Landsat data in the U.S. Geological Survey (USGS) archive are being reprocessed to generate a tiered collection of consistently geolocated and radiometrically calibrated products that are suitable for time series analyses. With the implementation of the collection management, no major updates will be made to calibration of the Landsat sensors within a collection. Only calibration parameters needed to maintain the established calibration trends without an effect on derived environmental records will be regularly updated, while all other changes will be deferred to a new collection. This first collection, Collection 1, incorporates various radiometric calibration updates to all Landsat sensors including absolute and relative gains for Landsat 8 Operational Land Imager (OLI), stray light correction for Landsat 8 Thermal Infrared Sensor (TIRS), absolute gains for Landsat 4 and 5 Thematic Mappers (TM), recalibration of Landsat 1-5 Multispectral Scanners (MSS) to ensure radiometric consistency among different formats of archived MSS data, and a transfer of Landsat 8 OLI reflectance based calibration to all previous Landsat sensors. While all OLI/TIRS, ETM+ and majority of TM data have already been reprocessed to Collection 1, a completion of MSS and remaining TM data reprocessing is expected by the end of this year. It is important to note that, although still available for download from the USGS web pages, the products generated using the Pre-Collection processing do not benefit from the latest radiometric calibration updates. In this paper, we are assessing radiometry of solar reflective bands in Landsat Collection 1 products through analysis of trends in on-board calibrator and pseudo invariant site (PICS) responses.

  12. LBA-ECO CD-34 Landsat Fractional Land Cover Analysis, Manaus, Brazil: 2004-2005 (United States)

    National Aeronautics and Space Administration — This data set provides the results of fractional land cover analysis for nonphotosynthetic vegetation (NPV) from two Landsat images of Manaus, Brazil, for October...

  13. [Effects of long-term isolation and anticipation of significant event on sleep: results of the project "Mars-520"]. (United States)

    Zavalko, I M; Rasskazova, E I; Gordeev, S A; Palatov, S Iu; Kovrov, G V


    The purpose of the research was to study effect of long-term isolation on night sleep. The data were collected during international ground simulation of an interplanetary manned flight--"Mars-500". The polysomnographic recordings of six healthy men were performed before, four times during and after 520-days confinement. During the isolation sleep efficiency and delta-latency decreased, while sleep latency increased. Post-hoc analysis demonstrate significant differences between background and the last (1.5 months before the end of the experiment) measure during isolation. Frequency of nights with low sleep efficiency rose on the eve of the important for the crew events (simulation of Mars landing and the end of the confinement). Two weeks after the landing simulation, amount of the nights with a low sleep efficiency significantly decreased. Therefore, anticipation of significant event under condition of long-term isolation might result in sleep worsening in previously healthy men, predominantly difficulties getting to sleep.

  14. [False positive results or what's the probability that a significant P-value indicates a true effect? (United States)

    Cucherat, Michel; Laporte, Silvy


    The use of statistical test is central in the clinical trial. At the statistical level, obtaining a Pinformation about the plausibility of the existence of treatment effect. With "Pfalse positive is very high. This is the case if the power is low, if there is an inflation of the alpha risk or if the result is exploratory or chance discoveries. This possibility is important to take into consideration when interpreting the results of clinical trials in order to avoid pushing ahead significant results in appearance, but which are likely to be actually false positive results. Copyright © 2017 Société française de pharmacologie et de thérapeutique. Published by Elsevier Masson SAS. All rights reserved.

  15. An initiative to improve the management of clinically significant test results in a large health care network. (United States)

    Roy, Christopher L; Rothschild, Jeffrey M; Dighe, Anand S; Schiff, Gordon D; Graydon-Baker, Erin; Lenoci-Edwards, Jennifer; Dwyer, Cheryl; Khorasani, Ramin; Gandhi, Tejal K


    The failure of providers to communicate and follow up clinically significant test results (CSTR) is an important threat to patient safety. The Massachusetts Coalition for the Prevention of Medical Errors has endorsed the creation of systems to ensure that results can be received and acknowledged. In 2008 a task force was convened that represented clinicians, laboratories, radiology, patient safety, risk management, and information systems in a large health care network with the goals of providing recommendations and a road map for improvement in the management of CSTR and of implementing this improvement plan during the sub-force sequent five years. In drafting its charter, the task broadened the scope from "critical" results to "clinically significant" ones; clinically significant was defined as any result that requires further clinical action to avoid morbidity or mortality, regardless of the urgency of that action. The task force recommended four key areas for improvement--(1) standardization of policies and definitions, (2) robust identification of the patient's care team, (3) enhanced results management/tracking systems, and (4) centralized quality reporting and metrics. The task force faced many challenges in implementing these recommendations, including disagreements on definitions of CSTR and on who should have responsibility for CSTR, changes to established work flows, limitations of resources and of existing information systems, and definition of metrics. This large-scale effort to improve the communication and follow-up of CSTR in a health care network continues with ongoing work to address implementation challenges, refine policies, prepare for a new clinical information system platform, and identify new ways to measure the extent of this important safety problem.

  16. Validation of the USGS Landsat Burned Area Essential Climate Variable (BAECV) across the conterminous United States (United States)

    Vanderhoof, Melanie; Fairaux, Nicole; Beal, Yen-Ju G.; Hawbaker, Todd J.


    agricultural lands of the Great Plains in central CONUS (62% and 57%, respectively). The BAECV product detected most (> 65%) fire events > 10 ha across the western CONUS (Arid and Mountain West ecoregions). Our approach and results demonstrate that a thorough validation of Landsat science products can be completed with independent Landsat-derived reference data, but could be strengthened by the use of complementary sources of high-resolution data.

  17. Landsat-8 Sensor Characterization and Calibration

    Directory of Open Access Journals (Sweden)

    Brian Markham


    Full Text Available Landsat-8 was launched on 11 February 2013 with two new Earth Imaging sensors to provide a continued data record with the previous Landsats. For Landsat-8, pushbroom technology was adopted, and the reflective bands and thermal bands were split into two instruments. The Operational Land Imager (OLI is the reflective band sensor and the Thermal Infrared Sensor (TIRS, the thermal. In addition to these fundamental changes, bands were added, spectral bandpasses were refined, dynamic range and data quantization were improved, and numerous other enhancements were implemented. As in previous Landsat missions, the National Aeronautics and Space Administration (NASA and United States Geological Survey (USGS cooperated in the development, launch and operation of the Landsat-8 mission. One key aspect of this cooperation was in the characterization and calibration of the instruments and their data. This Special Issue documents the efforts of the joint USGS and NASA calibration team and affiliates to characterize the new sensors and their data for the benefit of the scientific and application users of the Landsat archive. A key scientific use of Landsat data is to assess changes in the land-use and land cover of the Earth’s surface over the now 43-year record. [...

  18. Intensity-Modulated Radiotherapy Results in Significant Decrease in Clinical Toxicities Compared With Conventional Wedge-Based Breast Radiotherapy

    International Nuclear Information System (INIS)

    Harsolia, Asif; Kestin, Larry; Grills, Inga; Wallace, Michelle; Jolly, Shruti; Jones, Cortney; Lala, Moinaktar; Martinez, Alvaro; Schell, Scott; Vicini, Frank A.


    Purpose: We have previously demonstrated that intensity-modulated radiotherapy (IMRT) with a static multileaf collimator process results in a more homogenous dose distribution compared with conventional wedge-based whole breast irradiation (WBI). In the present analysis, we reviewed the acute and chronic toxicity of this IMRT approach compared with conventional wedge-based treatment. Methods and Materials: A total of 172 patients with Stage 0-IIB breast cancer were treated with lumpectomy followed by WBI. All patients underwent treatment planning computed tomography and received WBI (median dose, 45 Gy) followed by a boost to 61 Gy. Of the 172 patients, 93 (54%) were treated with IMRT, and the 79 patients (46%) treated with wedge-based RT in a consecutive fashion immediately before this cohort served as the control group. The median follow-up was 4.7 years. Results: A significant reduction in acute Grade 2 or worse dermatitis, edema, and hyperpigmentation was seen with IMRT compared with wedges. A trend was found toward reduced acute Grade 3 or greater dermatitis (6% vs. 1%, p = 0.09) in favor of IMRT. Chronic Grade 2 or worse breast edema was significantly reduced with IMRT compared with conventional wedges. No difference was found in cosmesis scores between the two groups. In patients with larger breasts (≥1,600 cm 3 , n = 64), IMRT resulted in reduced acute (Grade 2 or greater) breast edema (0% vs. 36%, p <0.001) and hyperpigmentation (3% vs. 41%, p 0.001) and chronic (Grade 2 or greater) long-term edema (3% vs. 30%, p 0.007). Conclusion: The use of IMRT in the treatment of the whole breast results in a significant decrease in acute dermatitis, edema, and hyperpigmentation and a reduction in the development of chronic breast edema compared with conventional wedge-based RT

  19. A study of atmospheric diffusion from the LANDSAT imagery. [pollution transport over the ocean (United States)

    Dejesusparada, N. (Principal Investigator); Viswanadham, Y.; Torsani, J. A.


    LANDSAT multispectral scanner data of the smoke plumes which originated in eastern Cabo Frio, Brazil and crossed over into the Atlantic Ocean, are analyzed to illustrate how high resolution LANDSAT imagery can aid meteorologists in evaluating specific air pollution events. The eleven LANDSAT images selected are for different months and years. The results show that diffusion is governed primarily by water and air temperature differences. With colder water, low level air is very stable and the vertical diffusion is minimal; but water warmer than the air induces vigorous diffusion. The applicability of three empirical methods for determining the horizontal eddy diffusivity coefficient in the Gaussian plume formula was evaluated with the estimated standard deviation of the crosswind distribution of material in the plume from the LANDSAT imagery. The vertical diffusion coefficient in stable conditions is estimated using Weinstock's formulation. These results form a data base for use in the development and validation of meso scale atmospheric diffusion models.

  20. Diazo processing of LANDSAT imagery: A low-cost instructional technique (United States)

    Lusch, D. P.


    Diazo processing of LANDSAT imagery is a relatively simple and cost effective method of producing enhanced renditions of the visual LANDSAT products. This technique is capable of producing a variety of image enhancements which have value in a teaching laboratory environment. Additionally, with the appropriate equipment, applications research which relys on accurate and repeatable results is possible. Exposure and development equipment options, diazo materials, and enhancement routines are discussed.

  1. Potent corticosteroid cream (mometasone furoate) significantly reduces acute radiation dermatitis: results from a double-blind, randomized study

    International Nuclear Information System (INIS)

    Bostroem, Aasa; Lindman, Henrik; Swartling, Carl; Berne, Berit; Bergh, Jonas


    Purpose: Radiation-induced dermatitis is a very common side effect of radiation therapy, and may necessitate interruption of the therapy. There is a substantial lack of evidence-based treatments for this condition. The aim of this study was to investigate the effect of mometasone furoate cream (MMF) on radiation dermatitis in a prospective, double-blind, randomized study. Material and methods: The study comprised 49 patients with node-negative breast cancer. They were operated on with sector resection and scheduled for postoperative radiotherapy using photons with identical radiation qualities and dosage to the breast parenchyma. The patients were randomized to receive either MMF or emollient cream. The cream was applied on the irradiated skin twice a week from the start of radiotherapy until the 12th fraction (24 Gy) and thereafter once daily until 3 weeks after completion of radiation. Both groups additionally received non-blinded emollient cream daily. The intensity of the acute radiation dermatitis was evaluated on a weekly basis regarding erythema and pigmentation, using a reflectance spectrophotometer together with visual scoring of the skin reactions. Results: MMF in combination with emollient cream treatment significantly decreased acute radiation dermatitis (P=0.0033) compared with emollient cream alone. There was no significant difference in pigmentation between the two groups. Conclusions: Adding MMF, a potent topical corticosteroid, to an emollient cream is statistically significantly more effective than emollient cream alone in reducing acute radiation dermatitis

  2. Do US Ambient Air Lead Levels Have a Significant Impact on Childhood Blood Lead Levels: Results of a National Study

    Directory of Open Access Journals (Sweden)

    LuAnn L. Brink


    Full Text Available Introduction. Although lead paint and leaded gasoline have not been used in the US for thirty years, thousands of US children continue to have blood lead levels (BLLs of concern. Methods. We investigated the potential association of modeled air lead levels and BLLs ≥ 10 μg/dL using a large CDC database with BLLs on children aged 0–3 years. Percent of children with BLLs ≥ 10 μg/dL (2000–2007 by county and proportion of pre-50 housing and SES variables were merged with the US EPA's National Air Toxics Assessment (NATA modeled air lead data. Results. The proportion with BLL ≥ 10 μg/dL was 1.24% in the highest air lead counties, and the proportion with BLL ≥ 10 μg/dL was 0.36% in the lowest air lead counties, resulting in a crude prevalence ratio of 3.4. Further analysis using multivariate negative binomial regression revealed that NATA lead was a significant predictor of % BLL ≥ 10 μg/dL after controlling for percent pre-l950 housing, percent rural, and percent black. A geospatial regression revealed that air lead, percent older housing, and poverty were all significant predictors of % BLL ≥ 10 μg/dL. Conclusions. More emphasis should be given to potential sources of ambient air lead near residential areas.

  3. The new Landsat 8 potential for remote sensing of colored dissolved organic matter (CDOM) (United States)

    Slonecker, Terry; Jones, Daniel K.; Pellerin, Brian A.


    Due to a combination of factors, such as a new coastal/aerosol band and improved radiometric sensitivity of the Operational Land Imager aboard Landsat 8, the atmospherically-corrected Surface Reflectance product for Landsat data, and the growing availability of corrected fDOM data from U.S. Geological Survey gaging stations, moderate-resolution remote sensing of fDOM may now be achievable. This paper explores the background of previous efforts and shows preliminary examples of the remote sensing and data relationships between corrected fDOM and Landsat 8 reflectance values. Although preliminary results before and after Hurricane Sandy are encouraging, more research is needed to explore the full potential of Landsat 8 to continuously map fDOM in a number of water profiles.

  4. The new Landsat 8 potential for remote sensing of colored dissolved organic matter (CDOM). (United States)

    Slonecker, E Terrence; Jones, Daniel K; Pellerin, Brian A


    Due to a combination of factors, such as a new coastal/aerosol band and improved radiometric sensitivity of the Operational Land Imager aboard Landsat 8, the atmospherically-corrected Surface Reflectance product for Landsat data, and the growing availability of corrected fDOM data from U.S. Geological Survey gaging stations, moderate-resolution remote sensing of fDOM may now be achievable. This paper explores the background of previous efforts and shows preliminary examples of the remote sensing and data relationships between corrected fDOM and Landsat 8 reflectance values. Although preliminary results before and after Hurricane Sandy are encouraging, more research is needed to explore the full potential of Landsat 8 to continuously map fDOM in a number of water profiles. Published by Elsevier Ltd.

  5. A one year Landsat 8 conterminous United States study of spatial and temporal patterns of cirrus and non-cirrus clouds and implications for the long term Landsat archive. (United States)

    Kovalskyy, V.; Roy, D. P.


    The successful February 2013 launch of the Landsat 8 satellite is continuing the 40+ year legacy of the Landsat mission. The payload includes the Operational Land Imager (OLI) that has a new 1370 mm band designed to monitor cirrus clouds and the Thermal Infrared Sensor (TIRS) that together provide 30m low, medium and high confidence cloud detections and 30m low and high confidence cirrus cloud detections. A year of Landsat 8 data over the Conterminous United States (CONUS), composed of 11,296 acquisitions, was analyzed comparing the spatial and temporal incidence of these cloud and cirrus states. This revealed (i) 36.5% of observations were detected with high confidence cloud with spatio-temporal patterns similar to those observed by previous Landsat 7 cloud analyses, (ii) 29.2% were high confidence cirrus, (iii) 20.9% were both high confidence cloud and high confidence cirrus, (iv) 8.3% were detected as high confidence cirrus but not as high confidence cloud. The results illustrate the value of the cirrus band for improved Landsat 8 terrestrial monitoring but imply that the historical CONUS Landsat archive has a similar 8% of undetected cirrus contaminated pixels. The implications for long term Landsat time series records, including the global Web Enabled Landsat Data (WELD) product record, are discussed.

  6. Geothermal Anomaly Mapping Using Landsat ETM+ Data in Ilan Plain, Northeastern Taiwan (United States)

    Chan, Hai-Po; Chang, Chung-Pai; Dao, Phuong D.


    Geothermal energy is an increasingly important component of green energy in the globe. A prerequisite for geothermal energy development is to acquire the local and regional geothermal prospects. Existing geophysical methods of estimating the geothermal potential are usually limited to the scope of prospecting because of the operation cost and site reachability in the field. Thus, explorations in a large-scale area such as the surface temperature and the thermal anomaly primarily rely on satellite thermal infrared imagery. This study aims to apply and integrate thermal infrared (TIR) remote sensing technology with existing geophysical methods for the geothermal exploration in Taiwan. Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) imagery is used to retrieve the land surface temperature (LST) in Ilan plain. Accuracy assessment of satellite-derived LST is conducted by comparing with the air temperature data from 11 permanent meteorological stations. The correlation coefficient of linear regression between air temperature and LST retrieval is 0.76. The MODIS LST product is used for the cross validation of Landsat derived LSTs. Furthermore, Landsat ETM+ multi-temporal brightness temperature imagery for the verification of the LST anomaly results were performed. LST Results indicate that thermal anomaly areas appear correlating with the development of faulted structure. Selected geothermal anomaly areas are validated in detail by field investigation of hot springs and geothermal drillings. It implies that occurrences of hot springs and geothermal drillings are in good spatial agreement with anomaly areas. In addition, the significant low-resistivity zones observed in the resistivity sections are echoed with the LST profiles when compared with in the Chingshui geothermal field. Despite limited to detecting the surficial and the shallow buried geothermal resources, this work suggests that TIR remote sensing is a valuable tool by providing an effective way of mapping

  7. Suppression of vegetation in LANDSAT ETM+ remote sensing images (United States)

    Yu, Le; Porwal, Alok; Holden, Eun-Jung; Dentith, Michael


    value and scaling all pixels at each vegetation index level by an amount that shifts the curve to the target digital number (DN). The main drawback of their algorithm is severe distortions of the DN values of non-vegetated areas, a suggested solution is masking outliers such as cloud, water, etc. We therefore extend this algorithm by masking non-vegetated areas. Our algorithm comprises the following three steps: (1) masking of barren or sparsely vegetated areas using a threshold based on a vegetation index that is calculated after atmosphere correction (dark pixel correction and ACTOR were compared) in order to conserve their original spectral information through the subsequent processing; (2) applying Crippen and Blom's forced invariance algorithm to suppress the spectral response of vegetation only in vegetated areas; and (3) combining the processed vegetated areas with the masked barren or sparsely vegetated areas followed by histogram equalization to eliminate the differences in color-scales between these two types of areas, and enhance the integrated image. The output images of both study areas showed significant improvement over the original images in terms of suppression of vegetation reflectance and enhancement of the underlying geological information. The processed images show clear banding, probably associated with lithological variations in the underlying rock formations. The colors of non-vegetated pixels are distorted in the unmasked results but in the same location the pixels in the masked results show regions of higher contrast. We conclude that the algorithm offers an effective way to enhance geological information in LANDSAT TM/ETM+ images of terrains with significant vegetation cover. It is also suitable to other multispectral satellite data have bands in similar wavelength regions. In addition, an application of this method to hyperspectral data may be possible as long as it can provide the vegetation band ratios.

  8. Landsat Science Team: 2017 Winter Meeting Summary (United States)

    Schroeder, Todd A.; Loveland, Thomas; Wulder, Michael A.; Irons, James R.


    The summer meeting of the joint U.S. Geological Survey (USGS)-NASA Landsat Science Team (LST) was held July 26-28, 2016, at South Dakota State University (SDSU) in Brookings, SD. LST co-chair Tom Loveland [USGS’s Earth Resources Observation and Science Center (EROS)] and Kevin Kephart [SDSU] welcomed more than 80 participants to the three-day meeting. That attendance at such meetings continues to increase—likely due to the development of new data products and sensor systems—further highlights the growing interest in the Landsat program. The main objectives of this meeting were to provide a status update on Landsat 7 and 8, review team member research activities, and to begin identifying priorities for future Landsat missions.

  9. Monitoring Thermal Pollution in Rivers Downstream of Dams with Landsat ETM+ Thermal Infrared Images

    Directory of Open Access Journals (Sweden)

    Feng Ling


    Full Text Available Dams play a significant role in altering the spatial pattern of temperature in rivers and contribute to thermal pollution, which greatly affects the river aquatic ecosystems. Understanding the temporal and spatial variation of thermal pollution caused by dams is important to prevent or mitigate its harmful effect. Assessments based on in-situ measurements are often limited in practice because of the inaccessibility of water temperature records and the scarcity of gauges along rivers. By contrast, thermal infrared remote sensing provides an alternative approach to monitor thermal pollution downstream of dams in large rivers, because it can cover a large area and observe the same zone repeatedly. In this study, Landsat Enhanced Thematic Mapper Plus (ETM+ thermal infrared imagery were applied to assess the thermal pollution caused by two dams, the Geheyan Dam and the Gaobazhou Dam, located on the Qingjiang River, a tributary of the Yangtze River downstream of the Three Gorges Reservoir in Central China. The spatial and temporal characteristics of thermal pollution were analyzed with water temperatures estimated from 54 cloud-free Landsat ETM+ scenes acquired in the period from 2000 to 2014. The results show that water temperatures downstream of both dams are much cooler than those upstream of both dams in summer, and the water temperature remains stable along the river in winter, showing evident characteristic of the thermal pollution caused by dams. The area affected by the Geheyan Dam reaches beyond 20 km along the downstream river, and that affected by the Gaobazhou Dam extends beyond the point where the Qingjiang River enters the Yangtze River. Considering the long time series and global coverage of Landsat ETM+ imagery, the proposed technique in the current study provides a promising method for globally monitoring the thermal pollution caused by dams in large rivers.


    Directory of Open Access Journals (Sweden)

    F. Chen


    Full Text Available A PRELIMINARY INVESTIGATION ON COMPARISON AND TRANSFORMATION OF SENTINEL-2 MSI AND LANDSAT 8 OLI Timely and accurate earth observation with short revisit interval is usually necessary, especially for emergency response. Currently, several new generation sensors provided with similar channel characteristics have been operated onboard different satellite platforms, including Sentinel-2 and Landsat 8. Joint use of the observations by different sensors offers an opportunity to meet the demands for emergency requirements. For example, through the combination of Landsat and Sentinel-2 data, the land can be observed every 2–3 days at medium spatial resolution. However, differences are expected in radiometric values (e.g., channel reflectance of the corresponding channels between two sensors. Spectral response function (SRF is taken as an important aspect of sensor settings. Accordingly, between-sensor differences due to SRFs variation need to be quantified and compensated. The comparison of SRFs shows difference (more or less in channel settings between Sentinel-2 Multi-Spectral Instrument (MSI and Landsat 8 Operational Land Imager (OLI. Effect of the difference in SRF on corresponding values between MSI and OLI was investigated, mainly in terms of channel reflectance and several derived spectral indices. Spectra samples from ASTER Spectral Library Version 2.0 and Hyperion data archives were used in obtaining channel reflectance simulation of MSI and OLI. Preliminary results show that MSI and OLI are well comparable in several channels with small relative discrepancy (< 5 %, including the Costal Aerosol channel, a NIR (855–875 nm channel, the SWIR channels, and the Cirrus channel. Meanwhile, for channels covering Blue, Green, Red, and NIR (785–900 nm, the between-sensor differences are significantly presented. Compared with the difference in reflectance of each individual channel, the difference in derived spectral index is more

  11. Evaluation of directional normalization methods for Landsat TM/ETM+ over primary Amazonian lowland forests (United States)

    Van doninck, Jasper; Tuomisto, Hanna


    Biodiversity mapping in extensive tropical forest areas poses a major challenge for the interpretation of Landsat images, because floristically clearly distinct forest types may show little difference in reflectance. In such cases, the effects of the bidirectional reflection distribution function (BRDF) can be sufficiently strong to cause erroneous image interpretation and classification. Since the opening of the Landsat archive in 2008, several BRDF normalization methods for Landsat have been developed. The simplest of these consist of an empirical view angle normalization, whereas more complex approaches apply the semi-empirical Ross-Li BRDF model and the MODIS MCD43-series of products to normalize directional Landsat reflectance to standard view and solar angles. Here we quantify the effect of surface anisotropy on Landsat TM/ETM+ images over old-growth Amazonian forests, and evaluate five angular normalization approaches. Even for the narrow swath of the Landsat sensors, we observed directional effects in all spectral bands. Those normalization methods that are based on removing the surface reflectance gradient as observed in each image were adequate to normalize TM/ETM+ imagery to nadir viewing, but were less suitable for multitemporal analysis when the solar vector varied strongly among images. Approaches based on the MODIS BRDF model parameters successfully reduced directional effects in the visible bands, but removed only half of the systematic errors in the infrared bands. The best results were obtained when the semi-empirical BRDF model was calibrated using pairs of Landsat observation. This method produces a single set of BRDF parameters, which can then be used to operationally normalize Landsat TM/ETM+ imagery over Amazonian forests to nadir viewing and a standard solar configuration.

  12. Statewide ban on recreational fires resulted in a significant decrease in campfire-related summer burn center admissions. (United States)

    Hoang, David Manh; Reid, Dixie; Lentz, Christopher William


    Every summer, there is an increase in the number of burn injuries caused by accidents around campfires. Because of the prevalence of drought, high winds, and uncontrolled wild fires, a statewide ban on recreational fires was instituted in New Mexico from June to July 2011. We hypothesized that this legislation would have a significant impact on burn admissions caused by campfire-related injuries. A retrospective review of summer admissions to a state burn center was conducted to assess the effect of this ban on recreational fire injuries, and these data were compared with that of the previous summer when no ban was in effect. All burn admissions to a state burn center were reviewed from Memorial Day to Labor Day in 2010 and 2011. Data collected included cause, % TBSA, age, days of hospitalization, intensive care unit days, and total surface area grafted. Nonparametric statistical analysis was performed with Fisher exact test for dichotomous data and Mann-Whitney test for continuous data with significance at P fires during the study period (n = 14 [17%] in 2010 and 4 [5%] in 2011; P = .02). This resulted in a decrease in the number of patient-days from 91 in 2010 to 25 in 2011. Half of the camp fire admissions required skin grafts to definitively close the wounds (6/14 in 2010 and 2/4 in 2011). Recreational fire bans targeted at controlling wildfires during conditions favoring rapid spread were associated with a 3- to 4-fold decrease in campfire-related burn admissions. Compared with a summer when no fire ban was in effect, the number of patient-days decreased from 91 to 25.

  13. An assessment of areal evapotranspiration using Landsat TM data

    Energy Technology Data Exchange (ETDEWEB)

    Chae, Hyo-Sok; Park, Jae-Young [Water Resources Research Institute, Taejeon(Korea); Song, Young-Soo [Chonbuk National Univ., Chonju(Korea)


    Surface energy balance components were evaluated by Landsat TM data and GIS with meteorological data. Calibration and validation for the applicability of this methodology were made through the estimating of the large-scale evapotranspiration (ET). In addition, sensitivity and error analysis was conducted to see the effects of the surface energy balance components on ET and the accuracy of each components. Bochong-chon located on the upper part of Guem River basin was selected as the case study area. Spatial distribution map of ET were produced for five dates: Jan. 1, Apr. 3, May. 10, and Nov. 27, 1995. The study results showed that ET was greatly varied with the aspect and the land use type on the surface. In the case of having northeast and southeast in the aspect, ET was linearly increased depending on growing net radiation. While surface temperature has a high value, NDVI(Normalized Difference Vegetation Index) has a low value in the vegetated area. Therefore, ground heat flux was increased but ET was relatively decreased. The results of sensitivity and error analysis showed that net radiation is most sensitive and effective, ranging from 12.5% to 23.6% of sensitivity. Furthermore, the surface temperature, air temperature, and wind speed have the significant effects on ET estimation using remotely sensed data. (author). 26 refs., 4 tabs., 8 figs.

  14. Results of efforts by the Convention on Biological Diversity to describe ecologically or biologically significant marine areas. (United States)

    Bax, Nicholas J; Cleary, Jesse; Donnelly, Ben; Dunn, Daniel C; Dunstan, Piers K; Fuller, Mike; Halpin, Patrick N


    In 2004, Parties to the Convention on Biological Diversity (CBD) addressed a United Nations (UN) call for area-based planning, including for marine-protected areas that resulted in a global effort to describe ecologically or biologically significant marine areas (EBSAs). We summarized the results, assessed their consistency, and evaluated the process developed by the Secretariat of the CBD to engage countries and experts in 9 regional workshops held from 2011 to 2014. Experts from 92 countries and 79 regional or international bodies participated. They considered 250 million km(2) of the world's ocean area (two-thirds of the total). The 204 areas they examined in detail differed widely in area (from 5.5 km(2) to 11.1 million km(2) ). Despite the initial focus of the CBD process on areas outside national jurisdiction, only 31 of the areas examined were solely outside national jurisdiction. Thirty-five extended into national jurisdictions, 137 were solely within national jurisdictions, and 28 included the jurisdictions of more than 1 country (1 area lacked precise boundaries). Data were sufficient to rank 88-99% of the areas relative to each of the 7 criteria for EBSAs agreed to previously by Parties to the CBD. The naturalness criterion ranked high for a smaller percentage of the EBSAs (31%) than other criteria (51-70%), indicating the difficulty in finding relatively undisturbed areas in the ocean. The highly participatory nature of the workshops, including easy and consistent access to the relevant information facilitated by 2 technical teams, contributed to the workshop participants success in identifying areas that could be ranked relative to most criteria and areas that extend across jurisdictional boundaries. The formal recognition of workshop results by the Conference of Parties to the CBD resulted in these 204 areas being identified as EBSAs by the 196 Parties. They represent the only suite of marine areas recognized by the international community for their

  15. Response to Instruction in Preschool: Results of Two Randomized Studies with Children At Significant Risk of Reading Difficulties (United States)

    Lonigan, Christopher J.; Phillips, Beth M.


    Although response-to-instruction (RTI) approaches have received increased attention, few studies have evaluated the potential impacts of RTI approaches with preschool populations. This manuscript presents results of two studies examining impacts of Tier II instruction with preschool children. Participating children were identified as substantially delayed in the acquisition of early literacy skills despite exposure to high-quality, evidence-based classroom instruction. Study 1 included 93 children (M age = 58.2 months; SD = 3.62) attending 12 Title I preschools. Study 2 included 184 children (M age = 58.2 months; SD = 3.38) attending 19 Title I preschools. The majority of children were Black/African American, and about 60% were male. In both studies, eligible children were randomized to receive either 11 weeks of need-aligned, small-group instruction or just Tier I. Tier II instruction in Study 1 included variations of activities for code- and language-focused domains with prior evidence of efficacy in non-RTI contexts. Tier II instruction in Study 2 included instructional activities narrower in scope, more intensive, and delivered to smaller groups of children. Impacts of Tier II instruction in Study 1 were minimal; however, there were significant and moderate-to-large impacts in Study 2. These results identify effective Tier II instruction but indicate that the context in which children are identified may alter the nature of Tier II instruction that is required. Children identified as eligible for Tier II in an RTI framework likely require more intensive and more narrowly focused instruction than do children at general risk of later academic difficulties. PMID:26869730

  16. Editor's choice--Use of disposable radiation-absorbing surgical drapes results in significant dose reduction during EVAR procedures. (United States)

    Kloeze, C; Klompenhouwer, E G; Brands, P J M; van Sambeek, M R H M; Cuypers, P W M; Teijink, J A W


    Because of the increasing number of interventional endovascular procedures with fluoroscopy and the corresponding high annual dose for interventionalists, additional dose-protecting measures are desirable. The purpose of this study was to evaluate the effect of disposable radiation-absorbing surgical drapes in reducing scatter radiation exposure for interventionalists and supporting staff during an endovascular aneurysm repair (EVAR) procedure. This was a randomized control trial in which 36 EVAR procedures were randomized between execution with and without disposable radiation-absorbing surgical drapes (Radpad: Worldwide Innovations & Technologies, Inc., Kansas City, US, type 5511A). Dosimetric measurements were performed on the interventionalist (hand and chest) and theatre nurse (chest) with and without the use of the drapes to obtain the dose reduction and effect on the annual dose caused by the drapes. Use of disposable radiation-absorbing surgical drapes resulted in dose reductions of 49%, 55%, and 48%, respectively, measured on the hand and chest of the interventionalist and the chest of the theatre nurse. The use of disposable radiation-absorbing surgical drapes significantly reduces scatter radiation exposure for both the interventionalist and the supporting staff during EVAR procedures. Copyright © 2013 European Society for Vascular Surgery. Published by Elsevier Ltd. All rights reserved.

  17. Landsat and water: case studies of the uses and benefits of landsat imagery in water resources (United States)

    Serbina, Larisa O.; Miller, Holly M.


    The Landsat program has been collecting and archiving moderate resolution earth imagery since 1972. The number of Landsat users and uses has increased exponentially since the enactment of a free and open data policy in 2008, which made data available free of charge to all users. Benefits from the information Landsat data provides vary from improving environmental quality to protecting public health and safety and informing decision makers such as consumers and producers, government officials and the public at large. Although some studies have been conducted, little is known about the total benefit provided by open access Landsat imagery. This report contains a set of case studies focused on the uses and benefits of Landsat imagery. The purpose of these is to shed more light on the benefits accrued from Landsat imagery and to gain a better understanding of the program’s value. The case studies tell a story of how Landsat imagery is used and what its value is to different private and public entities. Most of the case studies focus on the use of Landsat in water resource management, although some other content areas are included.

  18. An automated approach to mapping corn from Landsat imagery (United States)

    Maxwell, S.K.; Nuckols, J.R.; Ward, M.H.; Hoffer, R.M.


    Most land cover maps generated from Landsat imagery involve classification of a wide variety of land cover types, whereas some studies may only need spatial information on a single cover type. For example, we required a map of corn in order to estimate exposure to agricultural chemicals for an environmental epidemiology study. Traditional classification techniques, which require the collection and processing of costly ground reference data, were not feasible for our application because of the large number of images to be analyzed. We present a new method that has the potential to automate the classification of corn from Landsat satellite imagery, resulting in a more timely product for applications covering large geographical regions. Our approach uses readily available agricultural areal estimates to enable automation of the classification process resulting in a map identifying land cover as ‘highly likely corn,’ ‘likely corn’ or ‘unlikely corn.’ To demonstrate the feasibility of this approach, we produced a map consisting of the three corn likelihood classes using a Landsat image in south central Nebraska. Overall classification accuracy of the map was 92.2% when compared to ground reference data.

  19. Landsat Imagery-Based Above Ground Biomass Estimation and Change Investigation Related to Human Activities

    Directory of Open Access Journals (Sweden)

    Chaofan Wu


    Full Text Available Forest biomass is a significant indicator for substance accumulation and forest succession, and a spatiotemporal biomass map would provide valuable information for forest management and scientific planning. In this study, Landsat imagery and field data cooperated with a random forest regression approach were used to estimate spatiotemporal Above Ground Biomass (AGB in Fuyang County, Zhejiang Province of East China. As a result, the AGB retrieval showed an increasing trend for the past decade, from 74.24 ton/ha in 2004 to 99.63 ton/ha in 2013. Topography and forest management were investigated to find their relationships with the spatial distribution change of biomass. In general, the simulated AGB increases with higher elevation, especially in the range of 80–200 m, wherein AGB acquires the highest increase rate. Moreover, the forest policy of ecological forest has a positive effect on the AGB increase, particularly within the national level ecological forest. The result in this study demonstrates that human activities have a great impact on biomass distribution and change tendency. Furthermore, Landsat image-based biomass estimates would provide illuminating information for forest policy-making and sustainable development.

  20. Flood mapping from Sentinel-1 and Landsat-8 data: a case study from river Evros, Greece (United States)

    Kyriou, Aggeliki; Nikolakopoulos, Konstantinos


    Floods are suddenly and temporary natural events, affecting areas which are not normally covered by water. The influence of floods plays a significant role both in society and the natural environment, therefore flood mapping is crucial. Remote sensing data can be used to develop flood map in an efficient and effective way. This work is focused on expansion of water bodies overtopping natural levees of the river Evros, invading the surroundings areas and converting them in flooded. Different techniques of flood mapping were used using data from active and passive remote sensing sensors like Sentinlel-1 and Landsat-8 respectively. Space borne pairs obtained from Sentinel-1 were processed in this study. Each pair included an image during the flood, which is called "crisis image" and another one before the event, which is called "archived image". Both images covering the same area were processed producing a map, which shows the spread of the flood. Multispectral data From Landsat-8 were also processed in order to detect and map the flooded areas. Different image processing techniques were applied and the results were compared to the respective results of the radar data processing.

  1. Local search for optimal global map generation using mid-decadal landsat images (United States)

    Khatib, L.; Gasch, J.; Morris, Robert; Covington, S.


    NASA and the US Geological Survey (USGS) are seeking to generate a map of the entire globe using Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor data from the "mid-decadal" period of 2004 through 2006. The global map is comprised of thousands of scene locations and, for each location, tens of different images of varying quality to chose from. Furthermore, it is desirable for images of adjacent scenes be close together in time of acquisition, to avoid obvious discontinuities due to seasonal changes. These characteristics make it desirable to formulate an automated solution to the problem of generating the complete map. This paper formulates a Global Map Generator problem as a Constraint Optimization Problem (GMG-COP) and describes an approach to solving it using local search. Preliminary results of running the algorithm on image data sets are summarized. The results suggest a significant improvement in map quality using constraint-based solutions. Copyright ?? 2007, Association for the Advancement of Artificial Intelligence ( All rights reserved.

  2. Geomorphic domains and linear features on Landsat images, Circle Quadrangle, Alaska (United States)

    Simpson, S.L.


    feature data, corresponds to the strike of foliations in metamorphic rocks and magnetic anomalies reflecting compositional variations suggesting that most linear features in the southern part of the quadrangle probably are related to lithologic variations brought about by folding and foliation of metamorphic rocks. A second important trend interval, N.14-35E., may be related to thrusting south of the Tintina fault zone, as high concentrations of linear features within this interval are found in areas of mapped thrusts. Low concentrations of linear features are found in areas of most igneous intrusives. High concentrations of linear features do not correspond to areas of mineralization in any consistent or significant way that would allow concentration patterns to be easily used as an aid in locating areas of mineralization. The results of this remote sensing study indicate that there are several possibly important areas where further detailed studies are warranted.

  3. Mapping afforestation and its carbon stock using time-series Landsat stacks (United States)

    Liu, L.; Wu, Y.


    The Three Norths Shelter Forest Programme (TNSFP) is the largest afforestation reconstruction project in the world. Remote sensing is a crucial tool to map land cover and cover changes, but it is still challenging to accurately quantify the plantation and its carbon stock from time-series satellite images. In this paper, the Yulin district, Shaanxi province, representing a typical afforestation area in the TNSFP region, was selected as the study area, and there were twenty-nine Landsat MSS/TM/ETM+ epochs were collected from 1974 to 2012 to reconstruct the forest changes and carbon stock in last 40 years. Firstly, the Landsat ground surface reflectance (GSR) images from 1974 to 2013 were collected and processed based on 6S atmospheric transfer code and a relative reflectance normalization algorithm. Subsequently, we developed a vegetation change tracking method to reconstruct the forest change history (afforestation and deforestation) from the dense time-series Landsat GSR images based on the integrated forest z-score (IFZ) model, and the afforestation age was successfully retrieved from the Landsat time-series stacks in the last forty years and shown to be consistent with the surveyed tree ages, with a RMSE value of 4.32 years and a determination coefficient (R²) of 0.824. Then, the AGB regression models were successfully developed by integrating vegetation indices and tree age. The simple ratio vegetation index (SR) is the best candidate of the commonly used vegetation indices for estimating forest AGB, and the forest AGB model was significantly improved using the combination of SR and tree age, with R² values from 0.50 to 0.727. Finally, the forest AGB images were mapped at eight epochs from 1985 to 2013 using SR and afforestation age. The total forest AGB in six counties of Yulin District increased by 20.8 G kg, from 5.8 G kg in 1986 to 26.6 G kg in 2013, a total increase of 360%. For the forest area since 1974, the forest AGB density increased from 15.72 t

  4. Evaluation of Two Absolute Radiometric Normalization Algorithms for Pre-processing of Landsat Imagery

    Institute of Scientific and Technical Information of China (English)

    Xu Hanqiu


    In order to evaluate radiometric normalization techniques, two image normalization algorithms for absolute radiometric correction of Landsat imagery were quantitatively compared in this paper, which are the Illumination Correction Model proposed by Markham and Irish and the Illumination and Atmospheric Correction Model developed by the Remote Sensing and GIS Laboratory of the Utah State University. Relative noise, correlation coefficient and slope value were used as the criteria for the evaluation and comparison, which were derived from pseudo-invariant features identified from multitemtween the normalized multitemporal images were significantly reduced when the seasons of multitemporal images were different. However, there was no significant difference between the normalized and unnormalized images with a similar seasonal condition. Furthermore, the correction results of two algorithms are similar when the images are relatively clear with a uniform atmospheric condition. Therefore, the radiometric normalization procedures should be carried out if the multitemporal images have a significant seasonal difference.

  5. Evaluation of LANDSAT-4 Thematic Mapper Data as Applied to Geologic Exploration: Summary of Results. [Death Valley, California, Cement-Velma, Oklahoma; Big Horn and Wind River Basins, Wyoming; Spanish Peaks, Colorado; and the Four Corners area (Paradox Basin of Utah and Colorado) (United States)

    Dykstra, J. D.; Sheffield, C. A.; Everett, J. R.


    As with any tool applied to geologic exploration, maximum value results from the innovative integration of optimally processed LANDSAT-4 data with existing pertinent information and perceptive geologic thinking. The synoptic view of the satellite images and the relatively high resolution of the data permits recognization of regional tectonic patterns and their detailed mapping. The refined spatial and spectral characteristics and digital nature surface alterations associated with hydrothermal activity and microseepage of hydrocarbons. In general, as vegetation and soil cover increase, the value of spectral components of TM data decreases with respect to the value of the spatial component of the data. This observation reinforces the experience from working with MSS data that digital processing must be optimized both for the area and for the application.

  6. Landsat TM data processing for lithological discrimination in the Caraculo area (Namibe Province, SW Angola) (United States)

    Alberti, A.; Alessandro, V.; Pieruccini, U.; Pranzini, E.


    Landsat TM data were used for lithological discrimination and mapping in the little-known, semiarid 900 km 2 area around Caraculo station and the middle course of the Rio Giraul (Namibe Province, SW Angola) following two main procedures. The first of these was based on visual evaluation of three-band composites, band-ratio composites and Principal Component Analysis. The second method relied on the extraction of spectral signatures, and their use to obtain automatic classifications. Satisfactory results were reached with the first procedure, thus allowing - with limited support of ground information — the draft of a lithological map, while the second method was not systematically efficient, even for confirmation of data acquired with the first procedure. Image interpretation suggests that an extensive but hithertoun differentiated metasedimentary complex consisting of a heterogeneous supracrustal sequence should be subdivided into at least two units. Field observations proved that one of these is marked by a notable frequency of marbles and the other is characterized by a widespread occurrence of amphibolitic bodies. Moreover, a belt of undetermined (thermally metamorphosed ?) metamorphic rocks is interposed between them. The distinction of so far unidentified units, though restricted to interpretation of processed Landsat TM data, has significant geological implications also in the regional context and will be helpful in guiding future work with conventional geological methods.

  7. Remote sensing of geologic mineral occurrences for the Colorado mineral belt using LANDSAT data (United States)

    Carpenter, R. H. (Principal Investigator); Trexler, D. W.


    The author has identified the following significant results. LANDSAT imagery was examined as a practical and productive tool for mineral exploration along the Colorado Mineral Belt. An attempt was made to identify all large, active and/or abandoned mining districts on the imagery which initially were discovered by surface manifestations. A number of strong photolinements, circular features, and color anomalies were identified. Some of these form a part of the structural and igneous volcanic framework in which mineral deposits occur. No specific mineral deposits such as veins or porphyries were identified. Promising linear and concentric features were field checked at several locations. Some proved to be fault zones and calderas; others were strictly topographic features related to stream or glacial entrenchment. The Silverton Caldera region and the Idaho Springs-Central City district were chosen and studied as case histories to evaluate the application of LANDSAT imagery to mineral exploration. Evidence of specific mineralization related to ore deposits in these two areas were observed only on low level photography.

  8. Landsat 1-5 Multispectral Scanner V1 (United States)

    National Aeronautics and Space Administration — Abstract: The Landsat Multispectral Scanner (MSS) was a sensor onboard Landsats 1 through 5 and acquired images of the Earth nearly continuously from July 1972 to...

  9. Automated mapping of persistent ice and snow cover across the western U.S. with Landsat (United States)

    Selkowitz, David J.; Forster, Richard R.


    We implemented an automated approach for mapping persistent ice and snow cover (PISC) across the conterminous western U.S. using all available Landsat TM and ETM+ scenes acquired during the late summer/early fall period between 2010 and 2014. Two separate validation approaches indicate this dataset provides a more accurate representation of glacial ice and perennial snow cover for the region than either the U.S. glacier database derived from US Geological Survey (USGS) Digital Raster Graphics (DRG) maps (based on aerial photography primarily from the 1960s–1980s) or the National Land Cover Database 2011 perennial ice and snow cover class. Our 2010–2014 Landsat-derived dataset indicates 28% less glacier and perennial snow cover than the USGS DRG dataset. There are larger differences between the datasets in some regions, such as the Rocky Mountains of Northwest Wyoming and Southwest Montana, where the Landsat dataset indicates 54% less PISC area. Analysis of Landsat scenes from 1987–1988 and 2008–2010 for three regions using a more conventional, semi-automated approach indicates substantial decreases in glaciers and perennial snow cover that correlate with differences between PISC mapped by the USGS DRG dataset and the automated Landsat-derived dataset. This suggests that most of the differences in PISC between the USGS DRG and the Landsat-derived dataset can be attributed to decreases in PISC, as opposed to differences between mapping techniques. While the dataset produced by the automated Landsat mapping approach is not designed to serve as a conventional glacier inventory that provides glacier outlines and attribute information, it allows for an updated estimate of PISC for the conterminous U.S. as well as for smaller regions. Additionally, the new dataset highlights areas where decreases in PISC have been most significant over the past 25–50 years.

  10. Prognostic significance of increased bone marrow microcirculation in newly diagnosed multiple myeloma: results of a prospective DCE-MRI study

    Energy Technology Data Exchange (ETDEWEB)

    Merz, Maximilian; Hillengass, Jens [Department of Radiology, German Cancer Research Center, Heidelberg (Germany); University of Heidelberg, Department of Hematology, Oncology and Rheumatology, Heidelberg (Germany); Moehler, Thomas M.; Ritsch, Judith; Delorme, Stefan [Department of Radiology, German Cancer Research Center, Heidelberg (Germany); Baeuerle, Tobias [University of Erlangen-Nuremberg, Department of Radiology, Erlangen (Germany); Zechmann, Christian M. [Rinecker Proton Therapy, Muenchen (Germany); Wagner, Barbara; Hose, Dirk [University of Heidelberg, Department of Hematology, Oncology and Rheumatology, Heidelberg (Germany); Jauch, Anna [University of Heidelberg, Institute of Human Genetics, Heidelberg (Germany); Kunz, Christina; Hielscher, Thomas [German Cancer Research Center, Department of Biostatistics, Heidelberg (Germany); Laue, Hendrik [Fraunhofer MEVIS, Bremen (Germany); Goldschmidt, Hartmut [University of Heidelberg, Department of Hematology, Oncology and Rheumatology, Heidelberg (Germany); National Center for Tumor Diseases, Heidelberg (Germany)


    Aim of this prospective study was to investigate prognostic significance of increased bone marrow microcirculation as detected by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for survival and local complications in patients with multiple myeloma (MM). We performed DCE-MRI of the lumbar spine in 131 patients with newly diagnosed MM and analysed data according to the Brix model to acquire amplitude A and exchange rate constant k{sub ep}. In 61 patients a second MRI performed after therapy was evaluated to assess changes in vertebral height and identify vertebral fractures. Correlation analysis revealed significant positive association between beta2-microglobulin as well as immunoparesis with DCE-MRI parameters A and k{sub ep}. Additionally, A was negatively correlated with haemoglobin levels and k{sub ep} was positively correlated with LDH levels. Higher baseline k{sub ep} values were associated with decreased vertebral height in a second MRI (P = 0.007) and A values were associated with new vertebral fractures in the lower lumbar spine (P = 0.03 for L4). Pre-existing lytic bone lesions or remission after therapy had no impact on the occurrence of vertebral fractures. Multivariate analysis revealed that amplitude A is an independent adverse risk factor for overall survival. DCE-MRI is a non-invasive tool with significance for systemic prognosis and vertebral complications. (orig.)

  11. Landsat science team meeting: Summer 2015 (United States)

    Schroeder, Todd; Loveland, Thomas; Wulder, Michael A.; Irons, James R.


    The summer meeting of the joint U.S. Geological Survey (USGS)–NASA Landsat Science Team (LST) was held at the USGS’s Earth Resources Observation and Science (EROS) Center July 7-9, 2015, in Sioux Falls, SD. The LST co-chairs, Tom Loveland [EROS—Senior Scientist] and Jim Irons [NASA’s Goddard Space Flight Center (GSFC)—Landsat 8 Project Scientist], opened the three-day meeting on an upbeat note following the recent successful launch of the European Space Agency’s Sentinel-2 mission on June 23, 2015 (see image on page 14), and the news that work on Landsat 9 has begun, with a projected launch date of 2023.

  12. 2017 Landsat Science Team Summer Meeting Summary (United States)

    Crawford, Christopher J.; Loveland, Thomas R.; Wulder, Michael A.; Irons, James R.


    The summer meeting of the U.S. Geological Survey (USGS)-NASA Landsat Science Team (LST) was held June 11-13, 2017, at the USGS’s Earth Resources Observation and Science (EROS) Center near Sioux Falls, SD. This was the final meeting of the Second (2012-2017) LST.1 Frank Kelly [EROS—Center Director] welcomed the attendees and expressed his thanks to the LST members for their contributions. He then introduced video-recorded messages from South Dakota’s U.S. senators, John Thune and Mike Rounds, in which they acknowledged the efforts of the team in advancing the societal impacts of the Landsat Program.

  13. Landsat 7 - A challenge to America (United States)

    Colvocoresses, Alden P.

    Factors in favor of Landsat 7 are discussed; they include: reasonable cost, a base on which to examine global change, and the need for comprehensive and continuous satellite coverage of the earth at moderate (5-30 m) resolution, in view of various occurrences on the earth's surface, ranging from the Chernobyl disaster to deforestation to the Persian Gulf conflict. Attention is given to proposed parameters for Landsat 7 and suggested actions that should be taken by Congress, the Administration, and the public to implement this space program.

  14. Multi-temporal environmental analysis of oil field activities in south-central Oklahoma using Landsat thematic mapper, aerial photography and GIS

    International Nuclear Information System (INIS)

    Janks, J.S.; Edwards, G.S.; Prelat, A.E.


    Environmental assessments of oil field activities, historical and present, were made using a combination of Landsat Thematic Mapper, aerial photographic and GIS information. Landsat data was used to assess vegetation health in and around the oil fields, and aerial photography was used to document historic changes. We found no evidence of vegetation damage from the oil field activities, even though many fields are located along anticlines and drain into major waterways. GIS technology, mapping roads, wells, rivers, ponds and environmentally-sensitive areas, was used to minimize environmental effects on the placement of shotpoints and receivers. When either shotpoints or receivers were found to interfere with sensitive areas, the points were moved to nearby roads or other open locations. The application of this technology resulted in minimal environmental damage and significant cost savings

  15. Combination of Landsat and Sentinel-2 MSI data for initial assessing of burn severity (United States)

    Quintano, C.; Fernández-Manso, A.; Fernández-Manso, O.


    Nowadays Earth observation satellites, in particular Landsat, provide a valuable help to forest managers in post-fire operations; being the base of post-fire damage maps that enable to analyze fire impacts and to develop vegetation recovery plans. Sentinel-2A MultiSpectral Instrument (MSI) records data in similar spectral wavelengths that Landsat 8 Operational Land Imager (OLI), and has higher spatial and temporal resolutions. This work compares two types of satellite-based maps for evaluating fire damage in a large wildfire (around 8000 ha) located in Sierra de Gata (central-western Spain) on 6-11 August 2015. 1) burn severity maps based exclusively on Landsat data; specifically, on differenced Normalized Burn Ratio (dNBR) and on its relative versions (Relative dNBR, RdNBR, and Relativized Burn Ratio, RBR) and 2) burn severity maps based on the same indexes but combining pre-fire data from Landsat 8 OLI with post-fire data from Sentinel-2A MSI data. Combination of both Landsat and Sentinel-2 data might reduce the time elapsed since forest fire to the availability of an initial fire damage map. Interpretation of ortho-photograph Pléiades 1 B data (1:10,000) provided us the ground reference data to measure the accuracy of both burn severity maps. Results showed that Landsat based burn severity maps presented an adequate assessment of the damage grade (κ statistic = 0.80) and its spatial distribution in wildfire emergency response. Further using both Landsat and Sentinel-2 MSI data the accuracy of burn severity maps, though slightly lower (κ statistic = 0.70) showed an adequate level for be used by forest managers.

  16. Use of LANDSAT for Managing Nonpoint Source Pollution in Coastal Ecosystems of the U. S. Virgin Islands (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The data results show for the first time Landsat-based land use maps of both the terrestrial and benthic habitats of the U. S. Virgin Islands, spanning a period of...

  17. Clinical Significance of the Number of Depressive Symptoms in Major Depressive Disorder: Results from the CRESCEND Study. (United States)

    Park, Seon-Cheol; Sakong, Jeongkyu; Koo, Bon Hoon; Kim, Jae-Min; Jun, Tae-Youn; Lee, Min-Soo; Kim, Jung-Bum; Yim, Hyeon-Woo; Park, Yong Chon


    Our study aimed to establish the relationship between the number of depressive symptoms and the clinical characteristics of major depressive disorder (MDD). This would enable us to predict the clinical significance of the number of depressive symptoms in MDD patients. Using data from the Clinical Research Center for Depression (CRESCEND) study in Korea, 853 patients with DSM-IV MDD were recruited. The baseline and clinical characteristics of groups with different numbers of depressive symptoms were compared using the χ(2) test for discrete variables and covariance (ANCOVA) for continuous variables. In addition, the scores of these groups on the measurement tools were compared by ANCOVA after adjusting the potential effects of confounding variables. After adjusting the effects of monthly income and history of depression, a larger number of depressive symptoms indicated higher overall severity of depression (F [4, 756] = 21.458, P depressive symptoms (F [4, 767] = 19.145, P depressive symptoms can be used as an index of greater illness burden in clinical psychiatry.

  18. Analysis of Coastline Extraction from Landsat-8 OLI Imagery

    Directory of Open Access Journals (Sweden)

    Yaolin Liu


    Full Text Available Coastline extraction is a fundamental work for coastal resource management, coastal environmental protection and coastal sustainable development. Due to the free access and long-term record, Landsat series images have the potential to be used for coastline extraction. However, dynamic features of different types of coastlines (e.g., rocky, sandy, artificial, caused by sea level fluctuation from tidal, storm and reclamation, make it difficult to be accurately extracted with coarse spatial resolution, e.g., 30 m, of Landsat images. To access this problem, we analyze the performance of coastline extraction by integrating downscaling, pansharpening and water index approaches in increasing the accuracy of coastline extraction from the latest Landsat-8 Operational Land Imager (OLI imagery. In order to prove the availability of the proposed method, we designed three strategies: (1 Strategy 1 uses the traditional water index method to extract coastline directly from original 30 m Landsat-8 OLI multispectral (MS image; (2 Strategy 2 extracts coastlines from 15 m fused MS images generated by integrating 15 m panchromatic (PAN band and 30 m MS image with ten pansharpening algorithms; (3 Strategy 3 first downscales the PAN band to a finer spatial resolution (e.g., 7.5 m band, and then extracts coastlines from pansharpened MS images generated by integrating downscaled spatial resolution PAN band and 30 m MS image with ten pansharpening algorithms. Using the coastline extracted from ZiYuan-3 (ZY-3 5.8 m MS image as reference, accuracies of coastlines extracted from MS images in three strategies were validated visually and quantitatively. The results show that, compared with coastline extracted directly from 30 m Landsat-8 MS image (strategy 1, strategy 3 achieves the best accuracies with optimal mean net shoreline movement (MNSM of −2.54 m and optimal mean absolute difference (MAD of 11.26 m, followed by coastlines extracted in strategy 2 with optimal MNSM

  19. Modifications resulting in significant increases in the beam usage time of a 60 keV electron beam welder

    International Nuclear Information System (INIS)

    Zielinski, R.E.; Harrison, J.L.


    Short beam usage times were encountered using a 60 keV electron beam welder. These short times were the direct result of a buildup of a reaction product (WO 2 . 90 ) that occurred on graphite washers which housed the tungsten emitter plate. While it was not possible to prevent the reaction product, its growth rate was sufficiently altered by changing graphite materials and minor design changes of the washers. With these modifications beam usage times increased from an original 40 min to approximately 675 min

  20. Burned area detection based on Landsat time series in savannas of southern Burkina Faso (United States)

    Liu, Jinxiu; Heiskanen, Janne; Maeda, Eduardo Eiji; Pellikka, Petri K. E.


    West African savannas are subject to regular fires, which have impacts on vegetation structure, biodiversity and carbon balance. An efficient and accurate mapping of burned area associated with seasonal fires can greatly benefit decision making in land management. Since coarse resolution burned area products cannot meet the accuracy needed for fire management and climate modelling at local scales, the medium resolution Landsat data is a promising alternative for local scale studies. In this study, we developed an algorithm for continuous monitoring of annual burned areas using Landsat time series. The algorithm is based on burned pixel detection using harmonic model fitting with Landsat time series and breakpoint identification in the time series data. This approach was tested in a savanna area in southern Burkina Faso using 281 images acquired between October 2000 and April 2016. An overall accuracy of 79.2% was obtained with balanced omission and commission errors. This represents a significant improvement in comparison with MODIS burned area product (67.6%), which had more omission errors than commission errors, indicating underestimation of the total burned area. By observing the spatial distribution of burned areas, we found that the Landsat based method misclassified cropland and cloud shadows as burned areas due to the similar spectral response, and MODIS burned area product omitted small and fragmented burned areas. The proposed algorithm is flexible and robust against decreased data availability caused by clouds and Landsat 7 missing lines, therefore having a high potential for being applied in other landscapes in future studies.


    Directory of Open Access Journals (Sweden)

    M. A. Lazaridou


    Full Text Available Scientific and professional interests of civil engineering mainly include structures, hydraulics, geotechnical engineering, environment, and transportation issues. Topics included in the context of the above may concern urban environment issues, urban planning, hydrological modelling, study of hazards and road construction. Land cover information contributes significantly on the study of the above subjects. Land cover information can be acquired effectively by visual image interpretation of satellite imagery or after applying enhancement routines and also by imagery classification. The Landsat Data Continuity Mission (LDCM – Landsat 8 is the latest satellite in Landsat series, launched in February 2013. Landsat 8 medium spatial resolution multispectral imagery presents particular interest in extracting land cover, because of the fine spectral resolution, the radiometric quantization of 12bits, the capability of merging the high resolution panchromatic band of 15 meters with multispectral imagery of 30 meters as well as the policy of free data. In this paper, Landsat 8 multispectral and panchromatic imageries are being used, concerning surroundings of a lake in north-western Greece. Land cover information is extracted, using suitable digital image processing software. The rich spectral context of the multispectral image is combined with the high spatial resolution of the panchromatic image, applying image fusion – pansharpening, facilitating in this way visual image interpretation to delineate land cover. Further processing concerns supervised image classification. The classification of pansharpened image preceded multispectral image classification. Corresponding comparative considerations are also presented.

  2. Landsat 8 Multispectral and Pansharpened Imagery Processing on the Study of Civil Engineering Issues (United States)

    Lazaridou, M. A.; Karagianni, A. Ch.


    Scientific and professional interests of civil engineering mainly include structures, hydraulics, geotechnical engineering, environment, and transportation issues. Topics included in the context of the above may concern urban environment issues, urban planning, hydrological modelling, study of hazards and road construction. Land cover information contributes significantly on the study of the above subjects. Land cover information can be acquired effectively by visual image interpretation of satellite imagery or after applying enhancement routines and also by imagery classification. The Landsat Data Continuity Mission (LDCM - Landsat 8) is the latest satellite in Landsat series, launched in February 2013. Landsat 8 medium spatial resolution multispectral imagery presents particular interest in extracting land cover, because of the fine spectral resolution, the radiometric quantization of 12bits, the capability of merging the high resolution panchromatic band of 15 meters with multispectral imagery of 30 meters as well as the policy of free data. In this paper, Landsat 8 multispectral and panchromatic imageries are being used, concerning surroundings of a lake in north-western Greece. Land cover information is extracted, using suitable digital image processing software. The rich spectral context of the multispectral image is combined with the high spatial resolution of the panchromatic image, applying image fusion - pansharpening, facilitating in this way visual image interpretation to delineate land cover. Further processing concerns supervised image classification. The classification of pansharpened image preceded multispectral image classification. Corresponding comparative considerations are also presented.

  3. Clinical significance of low result of 1-h 50-g glucose-challenge test in pregnant women. (United States)

    Oawada, Nozomi; Aoki, Shigeru; Sakamaki, Kentaro; Obata, Soichiro; Seki, Kazuo; Hirahara, Fumiki


    The objective of this study is to examine the effect of low-glucose value on the 1-h 50-g glucose challenge test (GCT) on neonatal body weight in low-risk Asian singleton pregnant women. We retrospectively analyzed women who delivered a singleton neonate at term at a tertiary center and underwent GCT at 24-28 weeks of gestation between June 2001 and June 2015. The low GCT group was defined as low-birth weight, and macrosomia. The χ 2 test, Fisher's exact test, and Student's t test were used. There were 313 low GCT groups and 4611 control. The low GCT group were younger, had lower prepregnancy body weight, higher stature, and lower prepregnancy body mass index (BMI). After adjusting these variables, the low GCT group had a lower rate of LGA and a higher rate of SGA. Neonatal body weight is more influenced by maternal physique than by low GCT result (standardized coefficient (β); GCT 0.071, height 0.188, prepregnancy BMI 0.143). Neonatal body weight was only slightly influenced by low GCT result, but markedly influenced by maternal physique, such as height and prepregnancy BMI.

  4. Exercise testing in patients with variant angina: results, correlation with clinical and angiographic features and prognostic significance

    International Nuclear Information System (INIS)

    Waters, D.D.; Szlachcic, J.; Bourassa, M.G.; Scholl, J.-M.; Theroux, P.


    Eighty-two patients with variant angina underwent a treadmill exercise test using 14 ECG leads, and 67 also underwent exercise thallium-201 scans. The test induced ST elevation in 25 patients (30%), ST depression in 21 (26%) and no ST-segment abnormality in 36 (44%). ST elevation during exercise occurred in the same ECG leads as during spontaneous attacks at rest, and was always associated with a large perfusion defect on the exercise thallium scan. In contrast, exercise-induced ST depression often did not occur in the leads that exhibited ST elevation during episodes at rest. The ST-segment response to exercise did not accurately predict coronary anatomy: Coronary stenoses greater than or equal to 70% were present in 14 of 25 patients (56%) with ST elevation, in 13 of 21 (62%) with ST depression and in 14 of 36 (39%) with no ST-segment abnormality (NS). However, the degree of disease activity did correlate with the result of the exercise test: ST elevation occurred during exercise in 11 of 14 patients who had an average of more than two spontaneous attacks per day, in 12 of 24 who had between two attacks per day and two per week, and in only two of 31 who had fewer than two attacks per week (p<0.005). ST elevation during exercise was reproducible in five of five patients retested during an active phase of their disease, but not in three of three patients who had been angina-free for a least 1 month before the repeat test. We conclude that in variant angina patients, the results of an exercise test correlate well with the degree of disease activity but not with coronary anatomy, and do not define a high-risk subgroup

  5. The significance of radionuclides and trace elements in a back barrier tidal area: Results from the German Wadden

    International Nuclear Information System (INIS)

    Schnetger, B.; Hinrichs, J.; Dellwig, O.; Brumsack, H.-J.; Shaw, T.


    sediments indicate a change in the depositional energy at the NW German coast. Enrichments of elements diagnostic for heavy minerals show an increase in depositional energy from the Holocene to present conditions, i.e. the change from a natural to a human affected environment. Most possibly, this is caused by human influence on the coastal morphology. Mainland dikes seem to act as an energy barrier for the deposition of the fine-fraction. Besides the Helgoland mudhole as the most proximal depocenter, much of the mud (SPM) exported from the backbarrier systems is possibly transported to the western Skagerrak/Norwegian Channel. Anthropogenic and natural effects on subterranean estuaries can cause a significant change to these systems. Sea level rise, land reclamation, ground water mining and dike building have a direct impact. The effects of these changes are only beginning to be realized in this vital component of the coastal ecosystem. (author)

  6. Landsat Thematic Mapper monitoring of turbid inland water quality (United States)

    Lathrop, Richard G., Jr.


    This study reports on an investigation of water quality calibration algorithms under turbid inland water conditions using Landsat Thematic Mapper (TM) multispectral digital data. TM data and water quality observations (total suspended solids and Secchi disk depth) were obtained near-simultaneously and related using linear regression techniques. The relationships between reflectance and water quality for Green Bay and Lake Michigan were compared with results for Yellowstone and Jackson Lakes, Wyoming. Results show similarities in the water quality-reflectance relationships, however, the algorithms derived for Green Bay - Lake Michigan cannot be extrapolated to Yellowstone and Jackson Lake conditions.

  7. Chesapeake Bay plume dynamics from LANDSAT (United States)

    Munday, J. C., Jr.; Fedosh, M. S.


    LANDSAT images with enhancement and density slicing show that the Chesapeake Bay plume usually frequents the Virginia coast south of the Bay mouth. Southwestern (compared to northern) winds spread the plume easterly over a large area. Ebb tide images (compared to flood tide images) show a more dispersed plume. Flooding waters produce high turbidity levels over the shallow northern portion of the Bay mouth.

  8. Continuous Calibration Improvement in Solar Reflective Bands: Landsat 5 Through Landsat 8 (United States)

    Mishra, Nischal; Helder, Dennis; Barsi, Julia; Markham, Brian


    Launched in February 2013, the Operational Land Imager (OLI) on-board Landsat 8 continues to perform exceedingly well and provides high science quality data globally. Several design enhancements have been made in the OLI instrument relative to prior Landsat instruments: pushbroom imaging which provides substantially improved Signal-to-Noise Ratio (SNR), spectral bandpasses refinement to avoid atmospheric absorption features, 12 bit data resolution to provide a larger dynamic range that limits the saturation level, a set of well-designed onboard calibrators to monitor the stability of the sensor. Some of these changes such as refinements in spectral bandpasses compared to earlier Landsats and well-designed on-board calibrator have a direct impact on the improved radiometric calibration performance of the instrument from both the stability of the response and the ability to track the changes. The on-board calibrator lamps and diffusers indicate that the instrument drift is generally less than 0.1% per year across the bands. The refined bandpasses of the OLI indicate that temporal uncertainty of better than 0.5% is possible when the instrument is trended over vicarious targets such as Pseudo Invariant Calibration Sites (PICS), a level of precision that was never achieved with the earlier Landsat instruments. The stability measurements indicated by on-board calibrators and PICS agree much better compared to the earlier Landsats, which is very encouraging and bodes well for the future Landsat missions too.

  9. Perspective View with Landsat Overlay, Costa Rica (United States)


    This perspective view shows the Caribbean coastal plain of Costa Rica, with the Cordillera Central rising in the background and the Pacific Ocean in the distance. The prominent river in the center of the image is the Rio Sucio, which merges with the Rio Sarapiqui at the bottom of the image and eventually joins with Rio San Juan on the Nicaragua border.Like much of Central America, Costa Rica is generally cloud covered so very little satellite imagery is available. The ability of the Shuttle Radar Topography Mission (SRTM) instrument to penetrate clouds and make three-dimensional measurements will allow generation of the first complete high-resolution topographic map of the entire region. These data were used to generate the image.This three-dimensional perspective view was generated using elevation data from SRTM and an enhanced false-color Landsat 7 satellite image. Colors are from Landsat bands 5, 4, and 2 as red, green and blue, respectively. Topographic expression is exaggerated two times.Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter resolution of most Landsat images and will substantially help in analyses of the large and growing Landsat image archive. The Landsat 7 Thematic Mapper image used here was provided to the SRTM by the United States Geological Survey, Earth Resources Observation Systems (EROS) Data Center, Sioux Falls, S.D.Elevation data used in this image was acquired by the SRTM aboard the Space Shuttle Endeavour, launched on February 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to collect three-dimensional measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter-long (200-foot) mast, installed additional C-band and X-band antennas, and improved tracking and navigation devices

  10. a Comparative Analysis of Spatiotemporal Data Fusion Models for Landsat and Modis Data (United States)

    Hazaymeh, K.; Almagbile, A.


    In this study, three documented spatiotemporal data fusion models were applied to Landsat-7 and MODIS surface reflectance, and NDVI. The algorithms included the spatial and temporal adaptive reflectance fusion model (STARFM), sparse representation based on a spatiotemporal reflectance fusion model (SPSTFM), and spatiotemporal image-fusion model (STI-FM). The objectives of this study were to (i) compare the performance of these three fusion models using a one Landsat-MODIS spectral reflectance image pairs using time-series datasets from the Coleambally irrigation area in Australia, and (ii) quantitatively evaluate the accuracy of the synthetic images generated from each fusion model using statistical measurements. Results showed that the three fusion models predicted the synthetic Landsat-7 image with adequate agreements. The STI-FM produced more accurate reconstructions of both Landsat-7 spectral bands and NDVI. Furthermore, it produced surface reflectance images having the highest correlation with the actual Landsat-7 images. This study indicated that STI-FM would be more suitable for spatiotemporal data fusion applications such as vegetation monitoring, drought monitoring, and evapotranspiration.


    Directory of Open Access Journals (Sweden)

    W. Pervez


    Full Text Available This paper investigated the potential utility of Landsat-8 Operational Land Imager (OLI for change detection analysis and mapping application because of its superior technical design to previous Landsat series. The OLI SVM classified data was successfully classified with regard to all six test classes (i.e., bare land, built-up land, mixed trees, bushes, dam water and channel water. OLI support vector machine (SVM classified data for the four seasons (i.e., spring, autumn, winter, and summer was used to change detection results of six cases: (1 winter to spring which resulted reduction in dam water mapping and increases of bushes; (2 winter to summer which resulted reduction in dam water mapping and increase of vegetation; (3 winter to autumn which resulted increase in dam water mapping; (4 spring to summer which resulted reduction of vegetation and shallow water; (5 spring to autumn which resulted decrease of vegetation; and (6 summer to autumn which resulted increase of bushes and vegetation . OLI SVM classified data resulted higher overall accuracy and kappa coefficient and thus found suitable for change detection analysis.

  12. Applications of LANDSAT data to the integrated economic development of Mindoro, Phillipines (United States)

    Wagner, T. W.; Fernandez, J. C.


    LANDSAT data is seen as providing essential up-to-date resource information for the planning process. LANDSAT data of Mindoro Island in the Philippines was processed to provide thematic maps showing patterns of agriculture, forest cover, terrain, wetlands and water turbidity. A hybrid approach using both supervised and unsupervised classification techniques resulted in 30 different scene classes which were subsequently color-coded and mapped at a scale of 1:250,000. In addition, intensive image analysis is being carried out in evaluating the images. The images, maps, and aerial statistics are being used to provide data to seven technical departments in planning the economic development of Mindoro. Multispectral aircraft imagery was collected to compliment the application of LANDSAT data and validate the classification results.

  13. Updating stand-level forest inventories using airborne laser scanning and Landsat time series data (United States)

    Bolton, Douglas K.; White, Joanne C.; Wulder, Michael A.; Coops, Nicholas C.; Hermosilla, Txomin; Yuan, Xiaoping


    Vertical forest structure can be mapped over large areas by combining samples of airborne laser scanning (ALS) data with wall-to-wall spatial data, such as Landsat imagery. Here, we use samples of ALS data and Landsat time-series metrics to produce estimates of top height, basal area, and net stem volume for two timber supply areas near Kamloops, British Columbia, Canada, using an imputation approach. Both single-year and time series metrics were calculated from annual, gap-free Landsat reflectance composites representing 1984-2014. Metrics included long-term means of vegetation indices, as well as measures of the variance and slope of the indices through time. Terrain metrics, generated from a 30 m digital elevation model, were also included as predictors. We found that imputation models improved with the inclusion of Landsat time series metrics when compared to single-year Landsat metrics (relative RMSE decreased from 22.8% to 16.5% for top height, from 32.1% to 23.3% for basal area, and from 45.6% to 34.1% for net stem volume). Landsat metrics that characterized 30-years of stand history resulted in more accurate models (for all three structural attributes) than Landsat metrics that characterized only the most recent 10 or 20 years of stand history. To test model transferability, we compared imputed attributes against ALS-based estimates in nearby forest blocks (>150,000 ha) that were not included in model training or testing. Landsat-imputed attributes correlated strongly to ALS-based estimates in these blocks (R2 = 0.62 and relative RMSE = 13.1% for top height, R2 = 0.75 and relative RMSE = 17.8% for basal area, and R2 = 0.67 and relative RMSE = 26.5% for net stem volume), indicating model transferability. These findings suggest that in areas containing spatially-limited ALS data acquisitions, imputation models, and Landsat time series and terrain metrics can be effectively used to produce wall-to-wall estimates of key inventory attributes, providing an

  14. Post Landsat-D advanced concept evaluation /PLACE/ (United States)

    Alexander, L. D.; Alvarado, U. R.; Flatow, F. S.


    The aim of the Post Landsat-D Advanced Concept Evaluation (PLACE) program was to identify the key technology requirements of earth resources satellite systems for the 1985-2000 period. The program involved four efforts: (1) examination of future needs in the earth resources area, (2) creation of a space systems technology model capable of satisfying these needs, (3) identification of key technology requirements posed by this model, and (4) development of a methodology (PRISM) to assist in the priority structuring of the resulting technologies.

  15. Integrated Landsat Image Analysis and Hydrologic Modeling to Detect Impacts of 25-Year Land-Cover Change on Surface Runoff in a Philippine Watershed

    Directory of Open Access Journals (Sweden)

    Enrico Paringit


    Full Text Available Landsat MSS and ETM+ images were analyzed to detect 25-year land-cover change (1976–2001 in the critical Taguibo Watershed in Mindanao Island, Southern Philippines. This watershed has experienced historical modifications of its land-cover due to the presence of logging industries in the 1950s, and continuous deforestation due to illegal logging and slash-and-burn agriculture in the present time. To estimate the impacts of land-cover change on watershed runoff, land-cover information derived from the Landsat images was utilized to parameterize a GIS-based hydrologic model. The model was then calibrated with field-measured discharge data and used to simulate the responses of the watershed in its year 2001 and year 1976 land-cover conditions. The availability of land-cover information on the most recent state of the watershed from the Landsat ETM+ image made it possible to locate areas for rehabilitation such as barren and logged-over areas. We then created a “rehabilitated” land-cover condition map of the watershed (re-forestation of logged-over areas and agro-forestation of barren areas and used it to parameterize the model and predict the runoff responses of the watershed. Model results showed that changes in land-cover from 1976 to 2001 were directly related to the significant increase in surface runoff. Runoff predictions showed that a full rehabilitation of the watershed, especially in barren and logged-over areas, will be likely to reduce the generation of a huge volume of runoff during rainfall events. The results of this study have demonstrated the usefulness of multi-temporal Landsat images in detecting land-cover change, in identifying areas for rehabilitation, and in evaluating rehabilitation strategies for management of tropical watersheds through its use in hydrologic modeling.


    Directory of Open Access Journals (Sweden)

    A. Beiranvand Pour


    Full Text Available Landsat Thematic Mapper (TM and Shuttle Radar Topography Mission (SRTM data were used to produce geological maps in tropical environments. Lineament, lithology and landform maps were produced for all states in peninsular Malaysia in this study. Kedah, Perak and Terengganu states have been selected as case studies to demonstrate the results of the data and techniques used. Directional filtering technique was applied to Landsat TM bands 4, 5 and 3 for lineament mapping. The lithology map was produced using Landsat TM bands combination consist of bands 4, 3 and 2. Digital elevation model and landform map were produced using SRTM data in 3 Dimension (3D and 2 Dimension (2D perspective views, respectively. The produced geological maps and the remote sensing data and methods applied in this study are mostly appropriate for hazard risk mapping applications and mineral exploration projects in the peninsular Malaysia and tropical environments.

  17. The value of earth observations: methods and findings on the value of Landsat imagery (United States)

    Miller, Holly M.; Serbina, Larisa O.; Richardson, Leslie A.; Ryker, Sarah J.; Newman, Timothy R.


    Data from Earth observation systems are used extensively in managing and monitoring natural resources, natural hazards, and the impacts of climate change, but the value of such data can be difficult to estimate, particularly when it is available at no cost. Assessing the socioeconomic and scientific value of these data provides a better understanding of the existing and emerging research, science, and applications related to this information and contributes to the decision making process regarding current and future Earth observation systems. Recent USGS research on Landsat data has advanced the literature in this area by using a variety of methods to estimate value. The results of a 2012 survey of Landsat users, a 2013 requirements assessment, and 2013 case studies of applications of Landsat imagery are discussed.

  18. Browning of the landscape of interior Alaska based on 1986-2009 Landsat sensor NDVI (United States)

    Rebecca A. Baird; David Verbyla; Teresa N. Hollingsworth


    We used a time series of 1986-2009 Landsat sensor data to compute the Normalized Difference Vegetation Index (NDVI) for 30 m pixels within the Bonanza Creek Experimental Forest of interior Alaska. Based on simple linear regression, we found significant (p

  19. Continuous 1985-2012 Landsat monitoring to assess fire effects on meadows in Yosemite National Park, California (United States)

    Soulard, Christopher E.; Albano, Christine M.; Villarreal, Miguel; Walker, Jessica


    To assess how montane meadow vegetation recovered after a wildfire that occurred in Yosemite National Park, CA in 1996, Google Earth Engine image processing was applied to leverage the entire Landsat Thematic Mapper archive from 1985 to 2012. Vegetation greenness (normalized difference vegetation index [NDVI]) was summarized every 16 days across the 28-year Landsat time series for 26 meadows. Disturbance event detection was hindered by the subtle influence of low-severity fire on meadow vegetation. A hard break (August 1996) was identified corresponding to the Ackerson Fire, and monthly composites were used to compare NDVI values and NDVI trends within burned and unburned meadows before, immediately after, and continuously for more than a decade following the fire date. Results indicate that NDVI values were significantly lower at 95% confidence level for burned meadows following the fire date, yet not significantly lower at 95% confidence level in the unburned meadows. Burned meadows continued to exhibit lower monthly NDVI in the dormant season through 2012. Over the entire monitoring period, the negative-trending, dormant season NDVI slopes in the burned meadows were also significantly lower than unburned meadows at 90% confidence level. Lower than average NDVI values and slopes in the dormant season compared to unburned meadows, coupled with photographic evidence, strongly suggest that evergreen vegetation was removed from the periphery of some meadows after the fire. These analyses provide insight into how satellite imagery can be used to monitor low-severity fire effects on meadow vegetation.

  20. Spatiotemporal Variation in Mangrove Chlorophyll Concentration Using Landsat 8

    Directory of Open Access Journals (Sweden)

    Julio Pastor-Guzman


    Full Text Available There is a need to develop indicators of mangrove condition using remotely sensed data. However, remote estimation of leaf and canopy biochemical properties and vegetation condition remains challenging. In this paper, we (i tested the performance of selected hyperspectral and broad band indices to predict chlorophyll concentration (CC on mangrove leaves and (ii showed the potential of Landsat 8 for estimation of mangrove CC at the landscape level. Relative leaf CC and leaf spectral response were measured at 12 Elementary Sampling Units (ESU distributed along the northwest coast of the Yucatan Peninsula, Mexico. Linear regression models and coefficients of determination were computed to measure the association between CC and spectral response. At leaf level, the narrow band indices with the largest correlation with CC were Vogelmann indices and the MTCI (R2 > 0.5. Indices with spectral bands around the red edge (705–753 nm were more sensitive to mangrove leaf CC. At the ESU level Landsat 8 NDVI green, which uses the green band in its formulation explained most of the variation in CC (R2 > 0.8. Accuracy assessment between estimated CC and observed CC using the leave-one-out cross-validation (LOOCV method yielded a root mean squared error (RMSE = 15 mg·cm−2, and R2 = 0.703. CC maps showing the spatiotemporal variation of CC at landscape scale were created using the linear model. Our results indicate that Landsat 8 NDVI green can be employed to estimate CC in large mangrove areas where ground networks cannot be applied, and mapping techniques based on satellite data, are necessary. Furthermore, using upcoming technologies that will include two bands around the red edge such as Sentinel 2 will improve mangrove monitoring at higher spatial and temporal resolutions.

  1. Interpretasi Vulkanostratigrafi Daerah Mamuju Berdasarkan Analisis Citra Landsat-8

    Directory of Open Access Journals (Sweden)

    Frederikus Dian Indrastomo


    Full Text Available Mamuju and its surrounding area are constructed mainly by volcanic rocks. Volcanoclastic sedimentary rocks and limestones are laid above the volcanic rocks. Volcanic activities create some unique morphologies such as craters, lava domes, and pyroclastic flow paths as their volcanic products. These products are identified from their circular features characters on Landsat-8 imagery. After geometric and atmospheric corrections had been done, a visual interpretation on Landsat-8 imagery was conducted to identify structure, geomorphology, and geological condition of the area. Regional geological structures show trend to southeast – northwest direction which is affects the formation of Adang volcano. Geomorphology of the area are classified into 16 geomorphology units based on their genetic aspects, i.e Sumare fault block ridge, Mamuju cuesta ridge, Adang eruption crater, Labuhan Ranau eruption crater, Sumare eruption crater, Ampalas volcanic cone, Adang lava dome, Labuhan Ranau intrusion hill, Adang pyroclastic flow ridge, Sumare pyroclastic flow ridge, Adang volcanic remnant hills, Malunda volcanic remnant hills, Talaya volcanic remnant hills, Tapalang karst hills, Mamuju alluvium plains, and Karampuang reef terrace plains. Based on the Landsat-8 imagery interpretation result and field confirmation, the geology of Mamuju area is divided into volcanic rocks and sedimentary rocks. There are two groups of volcanic rocks; Talaya complex and Mamuju complex. The Talaya complex consists of Mambi, Malunda, and Kalukku volcanic rocks with andesitic composition, while Mamuju complex consist of Botteng, Ahu, Tapalang, Adang, Ampalas, Sumare, danLabuhanRanau volcanic rocks with andesite to leucitic basalt composition. The volcanostratigraphy of Mamuju area was constructed based on its structure, geomorphology and lithology distribution analysis. Volcanostratigraphy of Mamuju area is classified into Khuluk Talaya and Khuluk Mamuju. The Khuluk Talaya consists

  2. Two techniques for mapping and area estimation of small grains in California using Landsat digital data (United States)

    Sheffner, E. J.; Hlavka, C. A.; Bauer, E. M.


    Two techniques have been developed for the mapping and area estimation of small grains in California from Landsat digital data. The two techniques are Band Ratio Thresholding, a semi-automated version of a manual procedure, and LCLS, a layered classification technique which can be fully automated and is based on established clustering and classification technology. Preliminary evaluation results indicate that the two techniques have potential for providing map products which can be incorporated into existing inventory procedures and automated alternatives to traditional inventory techniques and those which currently employ Landsat imagery.

  3. Forest management applications of Landsat data in a geographic information system (United States)

    Maw, K. D.; Brass, J. A.


    The utility of land-cover data resulting from Landsat MSS classification can be greatly enhanced by use in combination with ancillary data. A demonstration forest management applications data base was constructed for Santa Cruz County, California, to demonstrate geographic information system applications of classified Landsat data. The data base contained detailed soils, digital terrain, land ownership, jurisdictional boundaries, fire events, and generalized land-use data, all registered to a UTM grid base. Applications models were developed from problems typical of fire management and reforestation planning.

  4. Using the Landsat data archive to assess long-term regional forest dynamics assessment in Eastern Europe, 1985-2012 (United States)

    Turubanova, S.; Potapov, P.; Krylov, A.; Tyukavina, A.; McCarty, J. L.; Radeloff, V. C.; Hansen, M. C.


    Dramatic political and economic changes in Eastern European countries following the dissolution of the "Eastern Bloc" and the collapse of the Soviet Union greatly affected land-cover and land-use trends. In particular, changes in forest cover dynamics may be attributed to the collapse of the planned economy, agricultural land abandonment, economy liberalization, and market conditions. However, changes in forest cover are hard to quantify given inconsistent forest statistics collected by different countries over the last 30 years. The objective of our research was to consistently quantify forest cover change across Eastern Europe from 1985 until 2012 using the complete Landsat data archive. We developed an algorithm for processing imagery from different Landsat platforms and sensors (TM and ETM+), aggregating these images into a common set of multi-temporal metrics, and mapping annual gross forest cover loss and decadal gross forest cover gain. Our results show that forest cover area increased from 1985 to 2012 by 4.7% across the region. Average annual gross forest cover loss was 0.41% of total forest cover area, with a statistically significant increase from 1985 to 2012. Most forest disturbance recovered fast, with only 12% of the areas of forest loss prior to 1995 not being recovered by 2012. Timber harvesting was the main cause of forest loss. Logging area declined after the collapse of socialism in the late 1980s, increased in the early 2000s, and decreased in most countries after 2007 due to the global economic crisis. By 2012, Central and Baltic Eastern European countries showed higher logging rates compared to their Western neighbours. Comparing our results with official forest cover and change estimates showed agreement in total forest area for year 2010, but with substantial disagreement between Landsat-based and official net forest cover area change. Landsat-based logging areas exhibit strong relationship with reported roundwood production at national

  5. Using GPS-surveyed intertidal zones to determine the validity of shorelines automatically mapped by Landsat water indices (United States)

    Kelly, Joshua T.; Gontz, Allen M.


    Satellite remote sensing has been used extensively in a variety of shoreline studies and validated using aerial photography. This ground truth method only represents an instantaneous depiction of the shoreline at the time of acquisition and does not take into account the spatial and temporal variability of the dynamic shoreline boundary. Landsat 8‧s Operational Land Imager sensor's capability to accurately delineate a shoreline is assessed by comparing all known Landsat water index-derived shorelines with two GPS-surveyed intertidal zones that coincide with the satellite flyover date, one of which had near-neap tide conditions. Seven indices developed for automatically classifying water pixels were evaluated for their ability to delineate shorelines. The shoreline is described here as the area above and below maximum low and high tide, otherwise known as the intertidal zone. The high-water line, or wet/dry sediment line, was chosen as the shoreline indicator to be mapped using a handheld GPS. The proportion of the Landsat-derived shorelines that fell within this zone and their alongshore profile lengths were calculated. The most frequently used water index and the predecessor to Modified Normalized Difference Water Index (MNDWI), Normalized Difference Water Index (NDWI), was found to be the least accurate by a significant margin. Other indices required calibration of their threshold value to achieve accurate results, thus diminishing their replicability success for other regions. MNDWI was determined to be the best index for automated shoreline mapping, based on its superior accuracy and repeatable, stable threshold value.

  6. Estimating Forest fAPAR from Multispectral Landsat-8 Data Using the Invertible Forest Reflectance Model INFORM

    Directory of Open Access Journals (Sweden)

    Huili Yuan


    Full Text Available The estimation of the Fraction of Absorbed Photosynthetically Active Radiation in forests (forest fAPAR from multi-spectral Landsat-8 data is investigated in this paper using a physically based radiative transfer model (Invertible Forest Reflectance Model, INFORM combined with an inversion strategy based on artificial neural nets (ANN. To derive the forest fAPAR for the Dabie mountain test site in China in 30 m spatial resolution (size approximately 3000 km2, a database of forest canopy spectral reflectances was simulated with INFORM taking into account structural variables such as leaf area index (LAI, crown coverage and stem density as well as leaf composition. To establish the relationship between forest fAPAR and the reflectance modeled by INFORM, a logarithmic relationship between LAI and fAPAR was used previously established using on-site field measurements. On this basis, predictive models between Landsat-8 reflectance and fAPAR were established using an artificial neural network. After calibrating INFORM for the test site, forty-two forest stands were used to validate the performance of the method. The results show that spectral signatures modeled by INFORM correspond reasonably well with the forest canopy reflectance spectra derived from Landsat data. Deviations increase with increasing angle between surface normal of the hilly terrain and sun incidence. The comparison of estimated and measured fAPAR (R2 = 0.47, RMSE = 0.11 demonstrates that INFORM can be inverted using neural nets to provide acceptable estimates of forest fAPAR. The accuracy of the predictions increased significantly when excluding pixels located in very steep terrain. This demonstrates that the applied topographic correction was not sufficiently accurate and should be improved for making optimum use of radiative transfer models such as INFORM.

  7. Seasonal Variation of Colored Dissolved Organic Matter in Barataria Bay, Louisiana, Using Combined Landsat and Field Data

    Directory of Open Access Journals (Sweden)

    Ishan Joshi


    Full Text Available Coastal bays, such as Barataria Bay, are important transition zones between the terrigenous and marine environments that are also optically complex due to elevated amounts of particulate and dissolved constituents. Monthly field data collected over a period of 15 months in 2010 and 2011 in Barataria Bay were used to develop an empirical band ratio algorithm for the Landsat-5 TM that showed a good correlation with the Colored Dissolved Organic Matter (CDOM absorption coefficient at 355 nm (ag355 (R2 = 0.74. Landsat-derived CDOM maps generally captured the major details of CDOM distribution and seasonal influences, suggesting the potential use of Landsat imagery to monitor biogeochemistry in coastal water environments. An investigation of the seasonal variation in ag355 conducted using Landsat-derived ag355 as well as field data suggested the strong influence of seasonality in the different regions of the bay with the marine end members (lower bay experiencing generally low but highly variable ag355 and the freshwater end members (upper bay experiencing high ag355 with low variability. Barataria Bay experienced a significant increase in ag355 during the freshwater release at the Davis Pond Freshwater Diversion (DPFD following the Deep Water Horizon oil spill in 2010 and following the Mississippi River (MR flood conditions in 2011, resulting in a weak linkage to salinity in comparison to the other seasons. Tree based statistical analysis showed the influence of high river flow conditions, high- and low-pressure systems that appeared to control ag355 by ~28%, 29% and 43% of the time duration over the study period at the marine end member just outside the bay. An analysis of CDOM variability in 2010 revealed the strong influence of the MR in controlling CDOM abundance in the lower bay during the high flow conditions, while strong winds associated with cold fronts significantly increase CDOM abundance in the upper bay, thus revealing the important

  8. Filling Landsat ETM+ SLC-off gaps using a segmentation model approach (United States)

    Maxwell, Susan


    The purpose of this article is to present a methodology for filling Landsat Scan Line Corrector (SLC)-off gaps with same-scene spectral data guided by a segmentation model. Failure of the SLC on the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) instrument resulted in a loss of approximately 25 percent of the spectral data. The missing data span across most of the image with scan gaps varying in size from two pixels near the center of the image to 14 pixels along the east and west edges. Even with the scan gaps, the radiometric and geometric qualities of the remaining portions of the image still meet design specifications and therefore contain useful information (see http:// for additional information). The U.S. Geological Survey EROS Data Center (EDC) is evaluating several techniques to fill the gaps in SLC-off data to enhance the usability of the imagery (Howard and Lacasse 2004) (PE&RS, August 2004). The method presented here uses a segmentation model approach that allows for same-scene spectral data to be used to fill the gaps. The segment model is generated from a complete satellite image with no missing spectral data (e.g., Landsat 5, Landsat 7 SLCon, SPOT). The model is overlaid on the Landsat SLC-off image, and the missing data within the gaps are then estimated using SLC-off spectral data that intersect the segment boundary. A major advantage of this approach is that the gaps are filled using spectral data derived from the same SLC-off satellite image.

  9. Study of the Nevada Test Site using Landsat satellite imagery

    International Nuclear Information System (INIS)

    Zimmerman, P.D.


    In the period covered by the purchase order CSIS has obtained one Landsat image and determined that two images previously supplied to the principal investigator under a subcontract with George Washington University were inherently defective. We have negotiated with EOSAT over the reprocessing of those scenes and anticipate final delivery within the next few weeks. A critical early purchase during the subcontract period was of an EXABYTE tape drive, Adaptec SCSI interface, and the appropriate software with which to read Landsat images at CSIS. This gives us the capability of reading and manipulating imagery in house without reliance on outside services which have not proven satisfactory. In addition to obtaining imagery for the study, we have also performed considerable analytic work on the newly and previously purchased images. A technique developed under an earlier subcontract for identifying underground nuclear tests at Pahute Mesa has been significantly refined, and similar techniques were applied to the summit of Rainier Mesa and to the Yucca Flats area. An entirely new technique for enhancing the spectral signatures of different regions of NTS was recently developed, and appears to have great promise of success

  10. Downscaling 250-m MODIS growing season NDVI based on multiple-date landsat images and data mining approaches (United States)

    Gu, Yingxin; Wylie, Bruce K.


    The satellite-derived growing season time-integrated Normalized Difference Vegetation Index (GSN) has been used as a proxy for vegetation biomass productivity. The 250-m GSN data estimated from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors have been used for terrestrial ecosystem modeling and monitoring. High temporal resolution with a wide range of wavelengths make the MODIS land surface products robust and reliable. The long-term 30-m Landsat data provide spatial detailed information for characterizing human-scale processes and have been used for land cover and land change studies. The main goal of this study is to combine 250-m MODIS GSN and 30-m Landsat observations to generate a quality-improved high spatial resolution (30-m) GSN database. A rule-based piecewise regression GSN model based on MODIS and Landsat data was developed. Results show a strong correlation between predicted GSN and actual GSN (r = 0.97, average error = 0.026). The most important Landsat variables in the GSN model are Normalized Difference Vegetation Indices (NDVIs) in May and August. The derived MODIS-Landsat-based 30-m GSN map provides biophysical information for moderate-scale ecological features. This multiple sensor study retains the detailed seasonal dynamic information captured by MODIS and leverages the high-resolution information from Landsat, which will be useful for regional ecosystem studies.

  11. Water Feature Extraction and Change Detection Using Multitemporal Landsat Imagery

    Directory of Open Access Journals (Sweden)

    Komeil Rokni


    Full Text Available Lake Urmia is the 20th largest lake and the second largest hyper saline lake (before September 2010 in the world. It is also the largest inland body of salt water in the Middle East. Nevertheless, the lake has been in a critical situation in recent years due to decreasing surface water and increasing salinity. This study modeled the spatiotemporal changes of Lake Urmia in the period 2000–2013 using the multi-temporal Landsat 5-TM, 7-ETM+ and 8-OLI images. In doing so, the applicability of different satellite-derived indexes including Normalized Difference Water Index (NDWI, Modified NDWI (MNDWI, Normalized Difference Moisture Index (NDMI, Water Ratio Index (WRI, Normalized Difference Vegetation Index (NDVI, and Automated Water Extraction Index (AWEI were investigated for the extraction of surface water from Landsat data. Overall, the NDWI was found superior to other indexes and hence it was used to model the spatiotemporal changes of the lake. In addition, a new approach based on Principal Components of multi-temporal NDWI (NDWI-PCs was proposed and evaluated for surface water change detection. The results indicate an intense decreasing trend in Lake Urmia surface area in the period 2000–2013, especially between 2010 and 2013 when the lake lost about one third of its surface area compared to the year 2000. The results illustrate the effectiveness of the NDWI-PCs approach for surface water change detection, especially in detecting the changes between two and three different times, simultaneously.

  12. Landsat satellite evidence of the decline of northern California bull kelp (United States)

    Renshaw, A.; Houskeeper, H. F.; Kudela, R. M.


    Bull kelp (Nereocystis luetkeana), a species of canopy-forming brown macroalga dominant in the Pacific Northwest of North America, provides critical ecological services such as habitat for a diverse array of marine species, nutrient regulation, photosynthesis, and regional marine carbon cycling. Starting around 2014, annual aerial surveys of bull kelp forests along California's northern coastline conducted by the California Department of Fish and Wildlife (CDFW) have reported a sudden 93% reduction in bull kelp canopy area. Remote sensing using satellite imagery is a robust, highly accurate tool for detecting and quantifying the abundance of the canopy-forming giant kelp, Macrocystis pyrifera; however, it has not been successfully applied to measuring northern bull kelp forests. One of the main difficulties associated with bull kelp detection via satellite is the small surface area of bull kelp canopies. As a result, bull kelp beds often only constitute part of a satellite pixel, making it difficult to obtain a kelp reflectance signal significantly different than water's reflectance signal. As part of the NASA Student Airborne Research Program (SARP), we test a novel method for assessing bull kelp canopy using a multiple endmember spectral mixing analysis (MESMA) applied to Landsat 5 and Landsat 8 imagery from 2003-2016. Water and kelp spectral endmembers are selected along the northern California coastline from Havens Neck cape to Point Arena. MESMA results are ground truthed with the CDFW aerial multispectral imagery data. This project will present a satellite-based time series of bull kelp canopy area and evaluate canopy change in a northern California kelp ecosystem.

  13. Downscaling of MODIS One Kilometer Evapotranspiration Using Landsat-8 Data and Machine Learning Approaches

    Directory of Open Access Journals (Sweden)

    Yinghai Ke


    Full Text Available This study presented a MODIS 8-day 1 km evapotranspiration (ET downscaling method based on Landsat 8 data (30 m and machine learning approaches. Eleven indicators including albedo, land surface temperature (LST, and vegetation indices (VIs derived from Landsat 8 data were first upscaled to 1 km resolution. Machine learning algorithms including Support Vector Regression (SVR, Cubist, and Random Forest (RF were used to model the relationship between the Landsat indicators and MODIS 8-day 1 km ET. The models were then used to predict 30 m ET based on Landsat 8 indicators. A total of thirty-two pairs of Landsat 8 images/MODIS ET data were evaluated at four study sites including two in United States and two in South Korea. Among the three models, RF produced the lowest error, with relative Root Mean Square Error (rRMSE less than 20%. Vegetation greenness related indicators such as Normalized Difference Vegetation Index (NDVI, Enhanced Vegetation Index (EVI, Soil Adjusted Vegetation Index (SAVI, and vegetation moisture related indicators such as Normalized Difference Infrared Index—Landsat 8 OLI band 7 (NDIIb7 and Normalized Difference Water Index (NDWI were the five most important features used in RF model. Temperature-based indicators were less important than vegetation greenness and moisture-related indicators because LST could have considerable variation during each 8-day period. The predicted Landsat downscaled ET had good overall agreement with MODIS ET (average rRMSE = 22% and showed a similar temporal trend as MODIS ET. Compared to the MODIS ET product, the downscaled product demonstrated more spatial details, and had better agreement with in situ ET observations (R2 = 0.56. However, we found that the accuracy of MODIS ET was the main control factor of the accuracy of the downscaled product. Improved coarse-resolution ET estimation would result in better finer-resolution estimation. This study proved the potential of using machine learning

  14. Web-based thyroid imaging reporting and data system: Malignancy risk of atypia of undetermined significance or follicular lesion of undetermined significance thyroid nodules calculated by a combination of ultrasonography features and biopsy results. (United States)

    Choi, Young Jun; Baek, Jung Hwan; Shin, Jung Hee; Shim, Woo Hyun; Kim, Seon-Ok; Lee, Won-Hong; Song, Dong Eun; Kim, Tae Yong; Chung, Ki-Wook; Lee, Jeong Hyun


    The purpose of this study was to construct a web-based predictive model using ultrasound characteristics and subcategorized biopsy results for thyroid nodules of atypia of undetermined significance/follicular lesion of undetermined significance (AUS/FLUS) to stratify the risk of malignancy. Data included 672 thyroid nodules from 656 patients from a historical cohort. We analyzed ultrasound images of thyroid nodules and biopsy results according to nuclear atypia and architectural atypia. Multivariate logistic regression analysis was performed to predict whether nodules were diagnosed as malignant or benign. The ultrasound features, including spiculated margin, marked hypoechogenicity, calcifications, biopsy results, and cytologic atypia, showed significant differences between groups. A 13-point risk scoring system was developed, and the area under the curve (AUC) of the receiver operating characteristic (ROC) curve of the development and validation sets were 0.837 and 0.830, respectively ( We devised a web-based predictive model using the combined information of ultrasound characteristics and biopsy results for AUS/FLUS thyroid nodules to stratify the malignant risk. © 2018 Wiley Periodicals, Inc.

  15. Small forest cuttings mapped with Landsat digital data (United States)

    Bryant, E.; Dodge, A. G.; Eger, M. J. E.


    The Cooperative Landsat Applications Research Group used computer classification of Landsat digital data to map forest cuttings (clearcuts) in northern New Hampshire. Cuttings as small as 3 hectares were identified. Several ages or conditions of clearcuts could be distinguished. Progress in two methods of duplicating classification categories from one Landsat pass to another are discussed. One method was used in making maps of areas in 1973, 1975, and 1978.

  16. Calculation of limits for significant unidirectional changes in two or more serial results of a biomarker based on a computer simulation model

    DEFF Research Database (Denmark)

    Lund, Flemming; Petersen, Per Hyltoft; Fraser, Callum G


    BACKGROUND: Reference change values (RCVs) were introduced more than 30 years ago and provide objective tools for assessment of the significance of differences in two consecutive results from an individual. However, in practice, more results are usually available for monitoring, and using the RCV...... the presented factors. The first result is multiplied by the appropriate factor for increase or decrease, which gives the limits for a significant difference.......BACKGROUND: Reference change values (RCVs) were introduced more than 30 years ago and provide objective tools for assessment of the significance of differences in two consecutive results from an individual. However, in practice, more results are usually available for monitoring, and using the RCV......,000 simulated data from healthy individuals, a series of up to 20 results from an individual was generated using different values for the within-subject biological variation plus the analytical variation. Each new result in this series was compared to the initial measurement result. These successive serial...

  17. LEDAPS Landsat Calibration, Reflectance, Atmospheric Correction Preprocessing Code (United States)

    National Aeronautics and Space Administration — ABSTRACT: The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) is a NASA project to map disturbance, regrowth, and permanent forest conversion...

  18. A Cubesat enabled Spatio-Temporal Enhancement Method (CESTEM) utilizing Planet, Landsat and MODIS data

    KAUST Repository

    Houborg, Rasmus; McCabe, Matthew


    using a multi-scale target sampling scheme that draws Landsat 8 reference data from a series of scenes by using MODIS-consistent surface reflectance time series to quantify relative changes in Landsat-scale reflectances over given Landsat

  19. Integrating age in the detection and mapping of incongruous patches in coffee (Coffea arabica) plantations using multi-temporal Landsat 8 NDVI anomalies (United States)

    Chemura, Abel; Mutanga, Onisimo; Dube, Timothy


    The development of cost-effective, reliable and easy to implement crop condition monitoring methods is urgently required for perennial tree crops such as coffee (Coffea arabica), as they are grown over large areas and represent long term and higher levels of investment. These monitoring methods are useful in identifying farm areas that experience poor crop growth, pest infestation, diseases outbreaks and/or to monitor response to management interventions. This study compares field level coffee mean NDVI and LSWI anomalies and age-adjusted coffee mean NDVI and LSWI anomalies in identifying and mapping incongruous patches across perennial coffee plantations. To achieve this objective, we first derived deviation of coffee pixels from the global coffee mean NDVI and LSWI values of nine sequential Landsat 8 OLI image scenes. We then evaluated the influence of coffee age class (young, mature and old) on Landsat-scale NDVI and LSWI values using a one-way ANOVA and since results showed significant differences, we adjusted NDVI and LSWI anomalies for age-class. We then used the cumulative inverse distribution function (α ≤ 0.05) to identify fields and within field areas with excessive deviation of NDVI and LSWI from the global and the age-expected mean for each of the Landsat 8 OLI scene dates spanning three seasons. Results from accuracy assessment indicated that it was possible to separate incongruous and healthy patches using these anomalies and that using NDVI performed better than using LSWI for both global and age-adjusted mean anomalies. Using the age-adjusted anomalies performed better in separating incongruous and healthy patches than using the global mean for both NDVI (Overall accuracy = 80.9% and 68.1% respectively) and for LSWI (Overall accuracy = 68.1% and 48.9% respectively). When applied to other Landsat 8 OLI scenes, the results showed that the proportions of coffee fields that were modelled incongruent decreased with time for the young age category and

  20. An Improved Mono-Window Algorithm for Land Surface Temperature Retrieval from Landsat 8 Thermal Infrared Sensor Data

    Directory of Open Access Journals (Sweden)

    Fei Wang


    Full Text Available The successful launch of the Landsat 8 satellite with two thermal infrared bands on February 11, 2013, for continuous Earth observation provided another opportunity for remote sensing of land surface temperature (LST. However, calibration notices issued by the United States Geological Survey (USGS indicated that data from the Landsat 8 Thermal Infrared Sensor (TIRS Band 11 have large uncertainty and suggested using TIRS Band 10 data as a single spectral band for LST estimation. In this study, we presented an improved mono-window (IMW algorithm for LST retrieval from the Landsat 8 TIRS Band 10 data. Three essential parameters (ground emissivity, atmospheric transmittance and effective mean atmospheric temperature were required for the IMW algorithm to retrieve LST. A new method was proposed to estimate the parameter of effective mean atmospheric temperature from local meteorological data. The other two essential parameters could be both estimated through the so-called land cover approach. Sensitivity analysis conducted for the IMW algorithm revealed that the possible error in estimating the required atmospheric water vapor content has the most significant impact on the probable LST estimation error. Under moderate errors in both water vapor content and ground emissivity, the algorithm had an accuracy of ~1.4 K for LST retrieval. Validation of the IMW algorithm using the simulated datasets for various situations indicated that the LST difference between the retrieved and the simulated ones was 0.67 K on average, with an RMSE of 0.43 K. Comparison of our IMW algorithm with the single-channel (SC algorithm for three main atmosphere profiles indicated that the average error and RMSE of the IMW algorithm were −0.05 K and 0.84 K, respectively, which were less than the −2.86 K and 1.05 K of the SC algorithm. Application of the IMW algorithm to Nanjing and its vicinity in east China resulted in a reasonable LST estimation for the region. Spatial

  1. Spatiotemporal Dynamics of Surface Water Extent from Three Decades of Seasonally Continuous Landsat Time Series at Subcontinental Scale (United States)

    Tulbure, M. G.; Broich, M.; Stehman, Stephen V.


    Surface water is a critical resource in semi-arid areas. The Murray-Darling Basin (MDB) of Australia, one of the largest semi-arid basins in the world is aiming to set a worldwide example of how to balance multiple interests (i.e. environment, agriculture and urban use), but has suffered significant water shrinkages during the Millennium Drought (1999-2009), followed by extensive flooding. Baseline information and systematic quantification of surface water (SW) extent and flooding dynamics in space and time are needed for managing SW resources across the basin but are currently lacking. To synoptically quantify changes in SW extent and flooding dynamics over MDB, we used seasonally continuous Landsat TM and ETM+ data (1986 - 2011) and generic machine learning algorithms. We further mapped flooded forest at a riparian forest site that experienced severe tree dieback due to changes in flooding regime. We used a stratified sampling design to assess the accuracy of the SW product across time. Accuracy assessment yielded an overall classification accuracy of 99.94%, with producer's and user's accuracy of SW of 85.4% and 97.3%, respectively. Overall accuracy was the same for Landsat 5 and 7 data but user's and producer's accuracy of water were higher for Landsat 7 than 5 data and stable over time. Our validated results document a rapid loss in SW bodies. The number, size, and total area of SW showed high seasonal variability with highest numbers in winter and lowest numbers in summer. SW extent per season per year showed high interannual and seasonal variability, with low seasonal variability during the Millennium Drought. Examples of current uses of the new dataset will be presented and include (1) assessing ecosystem response to flooding with implications for environmental water releases, one of the largest investment in environment in Australia; (2) quantifying drivers of SW dynamics (e.g. climate, human activity); (3) quantifying changes in SW dynamics and

  2. Development of remote sensing technology in New Zealand, part 1. Seismotectonic, structural, volcanologic and geomorphic study of New Zealand, part 2. Indigenous forest assessment, part 3. Mapping land use and environmental studies in New Zealand, part 4. New Zealand forest service LANDSAT projects, part 5. Vegetation map and landform map of Aupouri Peninsula, Northland, part 6. Geographical applications of LANDSAT mapping, part 7 (United States)

    Probine, M. C.; Suggate, R. P.; Mcgreevy, M. G.; Stirling, I. F. (Principal Investigator)


    The author has identified the following significant results. Inspection of pixels obtained from LANDSAT of New Zealand revealed that not only can ships and their wakes be detected, but that information on the size, state of motion, and direction of movement was inferred by calculating the total number of pixels occupied by the vessel and wake, the orientation of these pixels, and the sum of their radiance values above the background level. Computer enhanced images showing the Waimihia State Forest and much of Kaingaroa State Forest on 22 December 1975 were examined. Most major forest categories were distinguished on LANDSAT imagery. However, the LANDSAT imagery seemed to be most useful for updating and checking existing forest maps, rather than making new maps with many forest categories. Snow studies were performed using two basins: Six Mile Creek and Mt. Robert. The differences in radiance levels indicated that a greater areal snow cover in Six Mile Creek Basin with the effect of lower radiance values from vegetation/snow regions. A comparison of the two visible bands (MSS 4 and 5) demonstrate this difference for the two basins.

  3. Geological interpretation of Landsat TM imagery and aeromagnetic survey data, northern Precordillera region, Argentina (United States)

    Chernicoff, C. J.; Nash, C. R.


    This case study demonstrates a methodology for obtaining maximum geoscientific value from reconnaissance (1000 m line spacing) aeromagnetic data through integration with high-resolution satellite imagery. In this study, lithostratigraphic interpretation of optimally processed Landsat TM data at reconnaissance mapping scale (1:100,000) has been carried out as a precursor to geophysical interpretation, providing the basic 'framework' in which to view the imaged geophysical data. The Landsat-derived framework shows the correct positions and vergences of major structures, which characterize this part of the Andean foreland thrust-and-fold belt. Within the structural framework derived from satellite imagery, the locations of major shallow-source aeromagnetic anomalies related to intermediate/mafic extrusive and subvolcanic rocks and the controlling structures of these economically important magmatic events can be correctly interpreted. Results of the study indicate a significant, coherent, and previously unrecognized post-Permian, pre-Miocene volcanic/subvolcanic center, which is probably associated with regional sinistral strike-slip along a reactivated N-S accretionary suture and a pre-existing Precambrian/Paleozoic basement structure. Subsequent west-vergent thick-skinned thrusting associated with uplift of Sierra Valle Fertil Precambrian block has developed a set of distinctive NW-oriented strike-slip faults at the site of the volcanic center. The NW structures cut and rotate late Miocene thin-skinned structures associated with the Precordillera fold-and-thrust belt. Intrusive rocks associated with the inferred Oligocene volcanic center form easily recognizable, partially remanent dipole anomalies, are associated with alteration and Au mineralization (Cerro Guachi, El Pescado, Gnrl. Belgrano mines), and are located along NW-oriented sinistral splay faults. The strike-slip related tectonic/magmatic event is currently regarded as Oligocene in age and may correlate

  4. [Formula: see text]Determination of the smoking gun of intent: significance testing of forced choice results in social security claimants. (United States)

    Binder, Laurence M; Chafetz, Michael D


    Significantly below-chance findings on forced choice tests have been described as revealing "the smoking gun of intent" that proved malingering. The issues of probability levels, one-tailed vs. two-tailed tests, and the combining of PVT scores on significantly below-chance findings were addressed in a previous study, with a recommendation of a probability level of .20 to test the significance of below-chance results. The purpose of the present study was to determine the rate of below-chance findings in a Social Security Disability claimant sample using the previous recommendations. We compared the frequency of below-chance results on forced choice performance validity tests (PVTs) at two levels of significance, .05 and .20, and when using significance testing on individual subtests of the PVTs compared with total scores in claimants for Social Security Disability in order to determine the rate of the expected increase. The frequency of significant results increased with the higher level of significance for each subtest of the PVT and when combining individual test sections to increase the number of test items, with up to 20% of claimants showing significantly below-chance results at the higher p-value. These findings are discussed in light of Social Security Administration policy, showing an impact on policy issues concerning child abuse and neglect, and the importance of using these techniques in evaluations for Social Security Disability.

  5. Continental-Scale Mapping of Adelie Penguin Colonies from Landsat Imagery (United States)

    Schwaller, Mathew R.; Southwell, Colin; Emmerson, Louise


    Breeding distribution of the Adlie penguin, Pygoscelis adeliae, was surveyed with Landsat-7 Enhanced Thematic Mapper Plus (ETM+) data in an area covering approximately 330 of longitude along the coastline of Antarctica.An algorithm was designed to minimize radiometric noise and to retrieve Adlie penguin colony location and spatial extent from the ETM+data. In all, 9143 individual pixels were classified as belonging to an Adlie penguin colony class out of the entire dataset of 195 ETM+ scenes, where the dimension of each pixel is 30 m by 30 m,and each scene is approximately 180 km by 180 km. Pixel clustering identified a total of 187 individual Adlie penguin colonies, ranging in size from a single pixel (900 sq m) to a maximum of 875 pixels (0.788 sq km). Colony retrievals have a very low error of commission, on the order of 1% or less, and the error of omission was estimated to be 3% to 4% by population based on comparisons with direct observations from surveys across east Antarctica. Thus, the Landsat retrievals successfully located Adlie penguin colonies that accounted for 96 to 97% of the regional population used as ground truth. Geographic coordinates and the spatial extent of each colony retrieved from the Landsat data are available publically. Regional analysis found several areas where the Landsat retrievals suggest populations that are significantly larger than published estimates. Six Adlie penguin colonies were found that are believed to be previously unreported in the literature.

  6. Examining Land Cover and Greenness Dynamics in Hangzhou Bay in 1985–2016 Using Landsat Time-Series Data

    Directory of Open Access Journals (Sweden)

    Dengqiu Li


    Full Text Available Land cover changes significantly influence vegetation greenness in different regions. Dense Landsat time series stacks provide unique opportunity to analyze land cover change and vegetation greenness trends at finer spatial scale. In the past three decades, large reclamation activities have greatly changed land cover and vegetation growth of coastal areas. However, rarely has research investigated these frequently changed coastal areas. In this study, Landsat Normalized Difference Vegetation Index time series (1984–2016 data and the Breaks For Additive Seasonal and Trend algorithm were used to detect the intensity and dates of abrupt changes in a typical coastal area—Hangzhou Bay, China. The prior and posterior land cover categories of each change were classified using phenology information through a Random Forest model. The impacts of land cover change on vegetation greenness trends of the inland and reclaimed areas were analyzed through distinguishing gradual and abrupt changes. The results showed that the intensity and date of land cover change were detected successfully with overall accuracies of 88.7% and 86.1%, respectively. The continuous land cover dynamics were retrieved accurately with an overall accuracy of 91.0% for ten land cover classifications. Coastal reclamation did not alleviate local cropland occupation, but prompted the vegetation greenness of the reclaimed area. Most of the inland area showed a browning trend. The main contributors to the greenness and browning trends were also quantified. These findings will help the natural resource management community generate better understanding of coastal reclamation and make better management decisions.

  7. Perspective with Landsat Overlay, Mount Kilimanjaro, Tanzania (United States)


    Mount Kilimanjaro (Kilima Njaro or 'shining mountain' in Swahili), the highest point in Africa, reaches 5,895 meters (19,340 feet) above sea level, tall enough to maintain a permanent snow cap despite being just 330 kilometers (210 miles) south of the equator. It is the tallest free-standing mountain on the Earth's land surface world, rising about 4,600 meters (15,000 feet) above the surrounding plain. Kilimanjaro is a triple volcano (has three peaks) that last erupted perhaps more than 100,000 years ago but still exudes volcanic gases. It is accompanied by about 20 other nearby volcanoes, some of which are seen to the west (left) in this view, prominently including Mount Meru, which last erupted only about a century ago. The volcanic mountain slopes are commonly fertile and support thick forests, while the much drier grasslands of the plains are home to elephants, lions, and other savanna wildlife.This 3-D perspective view was generated using topographic data from the Shuttle Radar Topography Mission (SRTM), a Landsat 7 satellite image, and a false sky. Topographic expression is vertically exaggerated two times.Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter (98-foot) resolution of most Landsat images and will substantially help in analyzing the large and growing Landsat image archive, managed by the U.S. Geological Survey (USGS).Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on Feb. 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to collect 3-D measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter (approximately 200-foot) mast, installed additional C-band and X-band antennas, and improved tracking and

  8. The users, uses, and value of Landsat and other moderate-resolution satellite imagery in the United States-Executive report (United States)

    Miller, Holly M.; Sexton, Natalie R.; Koontz, Lynne; Loomis, John; Koontz, Stephen R.; Hermans, Caroline


    Moderate-resolution imagery (MRI), such as that provided by the Landsat satellites, provides unique spatial information for use by many people both within and outside of the United States (U.S.). However, exactly who these users are, how they use the imagery, and the value and benefits derived from the information are, to a large extent, unknown. To explore these issues, social scientists at the USGS Fort Collins Science Center conducted a study of U.S.-based MRI users from 2008 through 2010 in two parts: 1) a user identification and 2) a user survey. The objectives for this study were to: 1) identify and classify U.S.-based users of this imagery; 2) better understand how and why MRI, and specifically Landsat, is being used; and 3) qualitatively and quantitatively measure the value and societal benefits of MRI (focusing on Landsat specifically). The results of the survey revealed that respondents from multiple sectors use Landsat imagery in many different ways, as demonstrated by the breadth of project locations and scales, as well as application areas. The value of Landsat imagery to these users was demonstrated by the high importance placed on the imagery, the numerous benefits received from projects using Landsat imagery, the negative impacts if Landsat imagery was no longer available, and the substantial willingness to pay for replacement imagery in the event of a data gap. The survey collected information from users who are both part of and apart from the known user community. The diversity of the sample delivered results that provide a baseline of knowledge about the users, uses, and value of Landsat imagery. While the results supply a wealth of information on their own, they can also be built upon through further research to generate a more complete picture of the population of Landsat users as a whole.

  9. Assessment of The trophic state and Chlorophyll-a concentrations using Landsat OLI in Karaoun reservoir, Lebanon

    Directory of Open Access Journals (Sweden)

    Ali Fadel


    Full Text Available Fadel, A., Faour G. and Slim K. 2016. Assessment of the trophic state and chlorophyll-a concentrations using Landsat OLI in Karaoun reservoir, Lebanon. Lebanese Science Journal, 17(2: 130-145. Harmful algal blooms have become a worldwide environmental problem. A regular and cost-effective monitoring of these blooms is highly needed by lakes managers. Satellite remote sensing imagery like Landsat Operational Land Imager (OLI can be used to assess and monitor chlorophyll-a in water bodies over large areas in a cost-effective way. In this study, the accuracy of Landsat OLI to estimate chlorophyll-a was examined. Four field campaigns and cloud free images of Landsat OLI with 30 m resolution (01 May 2013, 21 August 2013, 10 July 2015, and 11 August 2015 were used in this study to determine the accuracy of Landsat OLI in estimating chlorophyll-a in a 12 km2 freshwater body, Karaoun reservoir. After atmospheric correction of these images, reflectance of single and multiple band combinations were compared to field chlorophyll-a data. Results of field campaigns showed that the trophic state of Karaoun reservoir is still eutrophic to hypereutrophic with high nutrient concentration and low phytoplankton biodiversity, dominated by cyanobacteria species, Microcystis aeruginosa and Aphanizomenon ovalisporum. On single band level, the in situ chlorophyll-a measurement correlated best with band 5 (0.85 - 0.88 µm, with R=0.75 and R2=0.57. Highest correlation (R=0.84 and R2=0.72 was obtained using band combination, B2:B4 band ratio multiplied by B5. Results indicated that Landsat OLI can be used effectively to determine chlorophyll-a concentration in lakes and reservoirs. We recommend the application of Landsat OLI as a satisfactory and cost effective method for monitoring chlorophyll-a in other lakes through-out the world

  10. How Similar Are Forest Disturbance Maps Derived from Different Landsat Time Series Algorithms?

    Directory of Open Access Journals (Sweden)

    Warren B. Cohen


    Full Text Available Disturbance is a critical ecological process in forested systems, and disturbance maps are important for understanding forest dynamics. Landsat data are a key remote sensing dataset for monitoring forest disturbance and there recently has been major growth in the development of disturbance mapping algorithms. Many of these algorithms take advantage of the high temporal data volume to mine subtle signals in Landsat time series, but as those signals become subtler, they are more likely to be mixed with noise in Landsat data. This study examines the similarity among seven different algorithms in their ability to map the full range of magnitudes of forest disturbance over six different Landsat scenes distributed across the conterminous US. The maps agreed very well in terms of the amount of undisturbed forest over time; however, for the ~30% of forest mapped as disturbed in a given year by at least one algorithm, there was little agreement about which pixels were affected. Algorithms that targeted higher-magnitude disturbances exhibited higher omission errors but lower commission errors than those targeting a broader range of disturbance magnitudes. These results suggest that a user of any given forest disturbance map should understand the map’s strengths and weaknesses (in terms of omission and commission error rates, with respect to the disturbance targets of interest.

  11. Modified Optimization Water Index (mowi) for LANDSAT-8 Oli/tirs (United States)

    Moradi, M.; Sahebi, M.; Shokri, M.


    Water is one of the most important resources that essential need for human life. Due to population growth and increasing need of human to water, proper management of water resources will be one of the serious challenges of next decades. Remote sensing data is the best way to the management of water resources due time and cost effectiveness over a greater range of temporal and spatial scales. Between many kinds of satellite data, from SAR to optic or from high resolution to low resolution, Landsat imagery is more interesting data for water detection and management of earth surface water. Landsat8 OLI/TIRS is the newest version of Landsat satellite series. In this paper, we investigated the full spectral potential of Landsat8 for water detection. It is developed many kinds of methods for this purpose that index based methods have some advantages than other methods. Pervious indices just use a limited number of spectral band. In this paper, Modified Optimization Water Index (MOWI) defined by consideration of a linear combination of bands that each coefficient of bands calculated by particle swarm algorithm. The result shows that modified optimization water index (MOWI) has a proper performance on different condition like cloud, cloud shadow and mountain shadow.

  12. Estimation of Airborne Lidar-Derived Tropical Forest Canopy Height Using Landsat Time Series in Cambodia

    Directory of Open Access Journals (Sweden)

    Tetsuji Ota


    Full Text Available In this study, we test and demonstrate the utility of disturbance and recovery information derived from annual Landsat time series to predict current forest vertical structure (as compared to the more common approaches, that consider a sample of airborne Lidar and single-date Landsat derived variables. Mean Canopy Height (MCH was estimated separately using single date, time series, and the combination of single date and time series variables in multiple regression and random forest (RF models. The combination of single date and time series variables, which integrate disturbance history over the entire time series, overall provided better MCH prediction than using either of the two sets of variables separately. In general, the RF models resulted in improved performance in all estimates over those using multiple regression. The lowest validation error was obtained using Landsat time series variables in a RF model (R2 = 0.75 and RMSE = 2.81 m. Combining single date and time series data was more effective when the RF model was used (opposed to multiple regression. The RMSE for RF mean canopy height prediction was reduced by 13.5% when combining the two sets of variables as compared to the 3.6% RMSE decline presented by multiple regression. This study demonstrates the value of airborne Lidar and long term Landsat observations to generate estimates of forest canopy height using the random forest algorithm.

  13. Assessment of Forest Degradation in Vietnam Using Landsat Time Series Data

    Directory of Open Access Journals (Sweden)

    James E. Vogelmann


    Full Text Available Landsat time series data were used to characterize forest degradation in Lam Dong Province, Vietnam. We conducted three types of image change analyses using Landsat time series data to characterize the land cover changes. Our analyses concentrated on the timeframe of 1973–2014, with much emphasis on the latter part of that range. We conducted a field trip through Lam Dong Province to develop a better understanding of the ground conditions of the region, during which we obtained many photographs of representative forest sites with Global Positioning System locations to assist us in our image interpretations. High-resolution Google Earth imagery and Landsat data of the region were used to validate results. In general, our analyses indicated that many land-use changes have occurred throughout Lam Dong Province, including gradual forest to non-forest transitions. Recent changes are most marked along the relatively narrow interfaces between agricultural and forest areas that occur towards the boundaries of the province. One important observation is that the most highly protected national reserves in the region have not changed much over the entire Landsat timeframe (1972–present. Spectral changes within these regions have not occurred at the same levels as those areas adjacent to the reserves.

  14. Monitoring of suspended sediment variation using Landsat and MODIS in the Saemangeum coastal area of Korea. (United States)

    Min, Jee-Eun; Ryu, Joo-Hyung; Lee, Seok; Son, Seunghyun


    Suspended sediment concentration (SS) is an important indicator of marine environmental changes due to natural causes such as tides, tidal currents, and river discharges, as well as human activities such as construction in coastal regions. In the Saemangeum area on the west coast of Korea, construction of a huge tidal dyke for land reclamation has strongly influenced the coastal environment. This study used remotely sensed data to analyze the SS changes in coastal waters caused by the dyke construction. Landsat and MODIS satellite images were used for the spatial analysis of finer patterns and for the detailed temporal analysis, respectively. Forty Landsat scenes and 105 monthly composite MODIS images observed during 1985-2010 were employed, and four field campaigns (from 2005 to 2006) were performed to verify the image-derived SS. The results of the satellite data analyses showed that the seawater was clear before the dyke construction, with SS values lower than 20 g/m(3). These values increased continuously as the dyke construction progressed. The maximum SS values appeared just before completion of the fourth dyke. Values decreased to below 5 g/m(3) after dyke construction. These changes indicated tidal current modification. Some eddies and plumes were observed in the images generated from Landsat data. Landsat and MODIS can reveal that coastal water turbidity was greatly reduced after completion of the construction. Copyright © 2011 Elsevier Ltd. All rights reserved.

  15. a Landsat Time-Series Stacks Model for Detection of Cropland Change (United States)

    Chen, J.; Chen, J.; Zhang, J.


    Global, timely, accurate and cost-effective cropland monitoring with a fine spatial resolution will dramatically improve our understanding of the effects of agriculture on greenhouse gases emissions, food safety, and human health. Time-series remote sensing imagery have been shown particularly potential to describe land cover dynamics. The traditional change detection techniques are often not capable of detecting land cover changes within time series that are severely influenced by seasonal difference, which are more likely to generate pseuso changes. Here,we introduced and tested LTSM ( Landsat time-series stacks model), an improved Continuous Change Detection and Classification (CCDC) proposed previously approach to extract spectral trajectories of land surface change using a dense Landsat time-series stacks (LTS). The method is expected to eliminate pseudo changes caused by phenology driven by seasonal patterns. The main idea of the method is that using all available Landsat 8 images within a year, LTSM consisting of two term harmonic function are estimated iteratively for each pixel in each spectral band .LTSM can defines change area by differencing the predicted and observed Landsat images. The LTSM approach was compared with change vector analysis (CVA) method. The results indicated that the LTSM method correctly detected the "true change" without overestimating the "false" one, while CVA pointed out "true change" pixels with a large number of "false changes". The detection of change areas achieved an overall accuracy of 92.37 %, with a kappa coefficient of 0.676.

  16. The use of landsat 7 enhanced thematic mapper plus for mapping leafy spurge (United States)

    Mladinich, C.S.; Bustos, M.R.; Stitt, S.; Root, R.; Brown, K.; Anderson, G.L.; Hager, S.


    Euphorbia esula L. (leafy spurge) is an invasive weed that is a major problem in much of the Upper Great Plains region, including parts of Montana, South Dakota, North Dakota, Nebraska, and Wyoming. Infestations in North Dakota alone have had a serious economic impact, estimated at $87 million annually in 1991, to the state's wildlife, tourism, and agricultural economy. Leafy spurge degrades prairie and badland ecosystems by displacing native grasses and forbs. It is a major threat to protected ecosystems in many national parks, national wild lands, and state recreational areas in the region. This study explores the use of Landsat 7 Enhanced Thematic Mapper Plus (Landsat) imagery and derived products as a management tool for mapping leafy spurge in Theodore Roosevelt National Park, in southwestern North Dakota. An unsupervised clustering approach was used to map leafy spurge classes and resulted in overall classification accuracies of approximately 63%. The uses of Landsat imagery did not provide the accuracy required for detailed mapping of small patches of the weed. However, it demonstrated the potential for mapping broad-scale (regional) leafy spurge occurrence. This paper offers recommendations on the suitability of Landsat imagery as a tool for use by resource managers to map and monitor leafy spurge populations over large areas.

  17. Mapping paddy rice distribution using multi-temporal Landsat imagery in the Sanjiang Plain, northeast China (United States)

    XIAO, Xiangming; DONG, Jinwei; QIN, Yuanwei; WANG, Zongming


    Information of paddy rice distribution is essential for food production and methane emission calculation. Phenology-based algorithms have been utilized in the mapping of paddy rice fields by identifying the unique flooding and seedling transplanting phases using multi-temporal moderate resolution (500 m to 1 km) images. In this study, we developed simple algorithms to identify paddy rice at a fine resolution at the regional scale using multi-temporal Landsat imagery. Sixteen Landsat images from 2010–2012 were used to generate the 30 m paddy rice map in the Sanjiang Plain, northeast China—one of the major paddy rice cultivation regions in China. Three vegetation indices, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Land Surface Water Index (LSWI), were used to identify rice fields during the flooding/transplanting and ripening phases. The user and producer accuracies of paddy rice on the resultant Landsat-based paddy rice map were 90% and 94%, respectively. The Landsat-based paddy rice map was an improvement over the paddy rice layer on the National Land Cover Dataset, which was generated through visual interpretation and digitalization on the fine-resolution images. The agricultural census data substantially underreported paddy rice area, raising serious concern about its use for studies on food security. PMID:27695637

  18. Landsat Remote Sensing Data as an Alternative Approach for ...

    African Journals Online (AJOL)

    Rungwe Volcanic Province (RVP) is mostly covered by extrusive rocks that overlain the Precambrian basement. The use of Landsat data in this area has revealed the need of effective use of these data in geological mapping programs in Tanzania. Landsat band ratios 5/1, 3/7, 5/7 and 5/4 as well as R: G: B composite ...

  19. Perspectives on monitoring gradual change across the continuity of Landsat sensors using time-series data (United States)

    Vogelmann, James; Gallant, Alisa L.; Shi, Hua; Zhu, Zhe


    There are many types of changes occurring over the Earth's landscapes that can be detected and monitored using Landsat data. Here we focus on monitoring “within-state,” gradual changes in vegetation in contrast with traditional monitoring of “abrupt” land-cover conversions. Gradual changes result from a variety of processes, such as vegetation growth and succession, damage from insects and disease, responses to shifts in climate, and other factors. Despite the prevalence of gradual changes across the landscape, they are largely ignored by the remote sensing community. Gradual changes are best characterized and monitored using time-series analysis, and with the successful launch of Landsat 8 we now have appreciable data continuity that extends the Landsat legacy across the previous 43 years. In this study, we conducted three related analyses: (1) comparison of spectral values acquired by Landsats 7 and 8, separated by eight days, to ensure compatibility for time-series evaluation; (2) tracking of multitemporal signatures for different change processes across Landsat 5, 7, and 8 sensors using anniversary-date imagery; and (3) tracking the same type of processes using all available acquisitions. In this investigation, we found that data representing natural vegetation from Landsats 5, 7, and 8 were comparable and did not indicate a need for major modification prior to use for long-term monitoring. Analyses using anniversary-date imagery can be very effective for assessing long term patterns and trends occurring across the landscape, and are especially good for providing insights regarding trends related to long-term and continuous trends of growth or decline. We found that use of all available data provided a much more comprehensive level of understanding of the trends occurring, providing information about rate, duration, and intra- and inter-annual variability that could not be readily gleaned from the anniversary date analyses. We observed that using all

  20. Large Area Crop Inventory Experiment (LACIE). Detecting and monitoring agricultural vegetative water stress over large areas using LANDSAT digital data. [Great Plains (United States)

    Thompson, D. R.; Wehmanen, O. A. (Principal Investigator)


    The author has identified the following significant results. The Green Number Index technique which uses LANDSAT digital data from 5X6 nautical mile sampling frames was expanded to evaluate its usefulness in detecting and monitoring vegetative water stress over the Great Plains. At known growth stages for wheat, segments were classified as drought or non drought. Good agreement was found between the 18 day remotely sensed data and a weekly ground-based crop moisture index. Operational monitoring of the 1977 U.S.S.R. and Australian wheat crops indicated drought conditions. Drought isoline maps produced by the Green Number Index technique were in good agreement with conventional sources.

  1. Evaluation of LANDSAT-2 (ERTS) images applied to geologic structures and mineral resources of South America. [Salar de Coposa, Chile and Salar of Uyuni, Bolivia (United States)

    Carter, W. D. (Principal Investigator); Kowalik, W. S.


    The author has identified the following significant results. The Salar of Coposa is located in northern Chile along the frontier with Bolivia. The surface was divided into six general classes of materials. Analysis of LANDSAT image 1243-14001 by use of interactive multispectral computer (Image 100) enabled accurate repetition of these general classes based on reflectance. The Salar of Uyuni is the largest of the South American evaporite deposits. Using image 1243-13595, and parallel piped computer classification of reflectance units, the Salar was divided into nine classes ranging from deep to shallow water, water over salt, salt saturated with water, and several classes of dry salt.


    Directory of Open Access Journals (Sweden)

    H. Miyazaki


    Full Text Available Methodology of automated human settlement mapping is highly needed for utilization of historical satellite data archives for urgent issues of urban growth in global scale, such as disaster risk management, public health, food security, and urban management. As development of global data with spatial resolution of 10-100 m was achieved by some initiatives using ASTER, Landsat, and TerraSAR-X, next goal has targeted to development of time-series data which can contribute to studies urban development with background context of socioeconomy, disaster risk management, public health, transport and other development issues. We developed an automated algorithm to detect human settlement by classification of built-up and non-built-up in time-series Landsat images. A machine learning algorithm, Local and Global Consistency (LLGC, was applied with improvements for remote sensing data. The algorithm enables to use MCD12Q1, a MODIS-based global land cover map with 500-m resolution, as training data so that any manual process is not required for preparation of training data. In addition, we designed the method to composite multiple results of LLGC into a single output to reduce uncertainty. The LLGC results has a confidence value ranging 0.0 to 1.0 representing probability of built-up and non-built-up. The median value of the confidence for a certain period around a target time was expected to be a robust output of confidence to identify built-up or non-built-up areas against uncertainties in satellite data quality, such as cloud and haze contamination. Four scenes of Landsat data for each target years, 1990, 2000, 2005, and 2010, were chosen among the Landsat archive data with cloud contamination less than 20%.We developed a system with the algorithms on the Data Integration and Analysis System (DIAS in the University of Tokyo and processed 5200 scenes of Landsat data for cities with more than one million people worldwide.

  3. Progress Towards a 2012 Landsat Launch (United States)

    Irons, Jim; Sabelhaus, Phil; Masek, Jeff; Cook, Bruce; Dabney, Phil; Loveland, Tom


    The Landsat Data Continuity Mission (LDCM) is on schedule for a December 2012 launch date. The mission is being managed by an interagency partnership between NASA and the U.S. Geological Survey (USGS). NASA leads the development and launch of the satellite observatory while leads ground system development. USGS will assume responsibility for operating the satellite and for collecting, archiving, and distributing the LDCM data following launch. When launched the satellite will carry two sensors into orbit. The Operational Land Imager (OLI) will collect data for nine shortwave spectral bands with a spatial resolution of 30 m (with a 15 m panchromatic band). The Thermal Infrared Sensor (TIRS) will coincidently collect data for two thermal infrared bands with a spatial resolution of 100 m. The OLI is fully assembled and tested and has been shipped by it?s manufacturer, Ball Aerospace and Technology Corporation, to the Orbital Sciences Corporation (Orbital) facility where it is being integrated onto the LDCM spacecraft. Pre-launch testing indicates that OLI will meet all performance specification with margin. TIRS is in development at the NASA Goddard Space Flight Center (GSFC) and is in final testing before shipping to the Orbital facility in January, 2012. The ground data processing system is in development at the USGS Earth Resources Observation and Science (EROS) Center. The presentation will describe the LDCM satellite system, provide the status of system development, and present prelaunch performance data for OLI and TIRS. The USGS has committed to renaming the satellite as Landsat 8 following launch.

  4. Operational calibration and validation of landsat data continuity mission (LDCM) sensors using the image assessment system (IAS) (United States)

    Micijevic, Esad; Morfitt, Ron


    Systematic characterization and calibration of the Landsat sensors and the assessment of image data quality are performed using the Image Assessment System (IAS). The IAS was first introduced as an element of the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) ground segment and recently extended to Landsat 4 (L4) and 5 (L5) Thematic Mappers (TM) and Multispectral Sensors (MSS) on-board the Landsat 1-5 satellites. In preparation for the Landsat Data Continuity Mission (LDCM), the IAS was developed for the Earth Observer 1 (EO-1) Advanced Land Imager (ALI) with a capability to assess pushbroom sensors. This paper describes the LDCM version of the IAS and how it relates to unique calibration and validation attributes of its on-board imaging sensors. The LDCM IAS system will have to handle a significantly larger number of detectors and the associated database than the previous IAS versions. An additional challenge is that the LDCM IAS must handle data from two sensors, as the LDCM products will combine the Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) spectral bands.

  5. Mapping forest tree species over large areas with partially cloudy Landsat imagery (United States)

    Turlej, K.; Radeloff, V.


    Forests provide numerous services to natural systems and humankind, but which services forest provide depends greatly on their tree species composition. That makes it important to track not only changes in forest extent, something that remote sensing excels in, but also to map tree species. The main goal of our work was to map tree species with Landsat imagery, and to identify how to maximize mapping accuracy by including partially cloudy imagery. Our study area covered one Landsat footprint (26/28) in Northern Wisconsin, USA, with temperate and boreal forests. We selected this area because it contains numerous tree species and variable forest composition providing an ideal study area to test the limits of Landsat data. We quantified how species-level classification accuracy was affected by a) the number of acquisitions, b) the seasonal distribution of observations, and c) the amount of cloud contamination. We classified a single year stack of Landsat-7, and -8 images data with a decision tree algorithm to generate a map of dominant tree species at the pixel- and stand-level. We obtained three important results. First, we achieved producer's accuracies in the range 70-80% and user's accuracies in range 80-90% for the most abundant tree species in our study area. Second, classification accuracy improved with more acquisitions, when observations were available from all seasons, and is the best when images with up to 40% cloud cover are included. Finally, classifications for pure stands were 10 to 30 percentage points better than those for mixed stands. We conclude that including partially cloudy Landsat imagery allows to map forest tree species with accuracies that were previously only possible for rare years with many cloud-free observations. Our approach thus provides important information for both forest management and science.

  6. Cross-sensor comparisons between Landsat 5 TM and IRS-P6 AWiFS and disturbance detection using integrated Landsat and AWiFS time-series images (United States)

    Chen, Xuexia; Vogelmann, James E.; Chander, Gyanesh; Ji, Lei; Tolk, Brian; Huang, Chengquan; Rollins, Matthew


    what were generated using the LTSS data set, and their kappa coefficients were higher than 0.97. These results indicate that AWiFS can be used instead of Landsat data to detect multitemporal disturbance in the event of Landsat data discontinuity.

  7. Refinamento de imagens termais do Landsat 5 - TM com base em classes de NDVI Sharpening of thermal Landsat 5 - TM imagery data based on NDVI classification

    Directory of Open Access Journals (Sweden)

    Argemiro Lucena de Araújo


    Full Text Available O objetivo desse estudo foi avaliar um método simplificado, baseado em classes de NDVI para refinamento das imagens de temperatura da superfície (Ts, obtidas pelo sensor TM do Landsat 5 referentes aos anos de 2005 e 2006. Para tanto, foram propostos e comparados três modelos de refinamento baseados no método de regressão linear. Os erros percentuais e erros médios quadráticos obtidos com a utilização dos modelos avaliados foram, respectivamente, da ordem de 0,37% e 1,38 ºC, enquanto o modelo original apresentou erro médio quadrático da ordem de 1,32 ºC. Foram constatados que os erros obtidos com as calibrações realizadas não influenciaram significativamente nos valores médios das imagens termais, e que os resultados contribuíram substancialmente para a melhoria da resolução espacial das mesmas. O refinamento permitiu ainda a identificação precisa de alvos da superfície e a identificação de feições não detectáveis na resolução original. Isto evidencia que o método simplificado sugerido neste estudo, permite um refinamento preciso com uma forma de obtenção mais simples em relação ao modelo original.The objective of this study was to use a simplified method based on NDVI classes for the sharpening of the Landsat 5 - TM surface temperature images (Ts obtained during the years of 2005 and 2006. Thus, three sharpening models, based on the linear regression method, were proposed and compared. The relative and the root mean square errors obtained through the suggested models were of 0.37% and 1.38 ºC, respectively, while the original model presented root mean square error of 1.32 ºC. It was verified that the errors obtained with the accomplished calibrations did not significantly influence in the average values of the thermal images and the results contributed substantially to the improvement of their spatial resolution. The sharpening allowed the precise identification of the targets and features undetectable at

  8. Valuing geospatial information: Using the contingent valuation method to estimate the economic benefits of Landsat satellite imagery (United States)

    Loomis, John; Koontz, Steve; Miller, Holly M.; Richardson, Leslie A.


    While the U.S. government does not charge for downloading Landsat images, the images have value to users. This paper demonstrates a method that can value Landsat and other imagery to users. A survey of downloaders of Landsat images found: (a) established US users have a mean value of $912 USD per scene; (b) new US users and users returning when imagery became free have a mean value of $367 USD per scene. Total US user benefits for the 2.38 million scenes downloaded is $1.8 billion USD. While these benefits indicate a high willingness-to-pay among many Landsat downloaders, it would be economically inefficient for the US government to charge for Landsat imagery. Charging a price of $100 USD a scene would result in an efficiency loss of $37.5 million a year. This economic information should be useful to policy-makers who must decide about the future of this and similar remote sensing programs.

  9. An Improved Single-Channel Method to Retrieve Land Surface Temperature from the Landsat-8 Thermal Band

    Directory of Open Access Journals (Sweden)

    Jordi Cristóbal


    Full Text Available Land surface temperature (LST is one of the sources of input data for modeling land surface processes. The Landsat satellite series is the only operational mission with more than 30 years of archived thermal infrared imagery from which we can retrieve LST. Unfortunately, stray light artifacts were observed in Landsat-8 TIRS data, mostly affecting Band 11, currently making the split-window technique impractical for retrieving surface temperature without requiring atmospheric data. In this study, a single-channel methodology to retrieve surface temperature from Landsat TM and ETM+ was improved to retrieve LST from Landsat-8 TIRS Band 10 using near-surface air temperature (Ta and integrated atmospheric column water vapor (w as input data. This improved methodology was parameterized and successfully evaluated with simulated data from a global and robust radiosonde database and validated with in situ data from four flux tower sites under different types of vegetation and snow cover in 44 Landsat-8 scenes. Evaluation results using simulated data showed that the inclusion of Ta together with w within a single-channel scheme improves LST retrieval, yielding lower errors and less bias than models based only on w. The new proposed LST retrieval model, developed with both w and Ta, yielded overall errors on the order of 1 K and a bias of −0.5 K validated against in situ data, providing a better performance than other models parameterized using w and Ta or only w models that yielded higher error and bias.

  10. Bayesian Method for Building Frequent Landsat-Like NDVI Datasets by Integrating MODIS and Landsat NDVI


    Limin Liao; Jinling Song; Jindi Wang; Zhiqiang Xiao; Jian Wang


    Studies related to vegetation dynamics in heterogeneous landscapes often require Normalized Difference Vegetation Index (NDVI) datasets with both high spatial resolution and frequent coverage, which cannot be satisfied by a single sensor due to technical limitations. In this study, we propose a new method called NDVI-Bayesian Spatiotemporal Fusion Model (NDVI-BSFM) for accurately and effectively building frequent high spatial resolution Landsat-like NDVI datasets by integrating Moderate Resol...

  11. Budapest, Hungary, Perspective View, SRTM Elevation Model with Landsat Overlay (United States)


    After draining the northern flank of the Alps Mountains in Germany and Austria, the Danube River flows east as it enters this west-looking scene (upper right) and forms the border between Slovakia and Hungary. The river then leaves the border as it enters Hungary and transects the Transdanubian Mountains, which trend southwest to northeast. Upon exiting the mountains, the river turns southward, flowing past Budapest (purplish blue area) and along the western margin of the Great Hungarian Plain.South and west of the Danube, the Transdanubian Mountains have at most only about 400 meters (about 1300 feet) of relief but they exhibit varied landforms, which include volcanic, tectonic, fluvial (river), and eolian (wind) features. A thick deposit of loess (dust deposits likely blown from ancient glacial outwash) covers much of this area, and winds from the northwest, funneled between the Alps and the Carpathian Mountains, are apparently responsible for a radial pattern of erosional streaks across the entire region.This image was generated from a Landsat satellite image draped over an elevation model produced by the Shuttle Radar Topography Mission (SRTM). The view uses a 3-times vertical exaggeration to enhance topographic expression. The false colors of the scene result from displaying Landsat bands 1, 4, and 7 in blue, green, and red, respectively. Band 1 is visible blue light, but bands 4 and 7 are reflected infrared light. This band combination maximizes color contrasts between the major land cover types, namely vegetation (green), bare ground (red), and water (blue). Shading of the elevation model was used to further highlight the topographic features.Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on February 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space

  12. Perspective view, Landsat overlay San Andreas Fault, Palmdale, California (United States)


    The prominent linear feature straight down the center of this perspective view is the San Andreas Fault. This segment of the fault lies near the city of Palmdale, California (the flat area in the right half of the image) about 60 kilometers (37 miles) north of Los Angeles. The fault is the active tectonic boundary between the North American plate on the right, and the Pacific plate on the left. Relative to each other, the Pacific plate is moving away from the viewer and the North American plate is moving toward the viewer along what geologists call a right lateral strike-slip fault. Two large mountain ranges are visible, the San Gabriel Mountains on the left and the Tehachapi Mountains in the upper right. The Lake Palmdale Reservoir, approximately 1.5 kilometers (0.9 miles) across, sits in the topographic depression created by past movement along the fault. Highway 14 is the prominent linear feature starting at the lower left edge of the image and continuing along the far side of the reservoir. The patterns of residential and agricultural development around Palmdale are seen in the Landsat imagery in the right half of the image. SRTM topographic data will be used by geologists studying fault dynamics and landforms resulting from active tectonics.This type of display adds the important dimension of elevation to the study of land use and environmental processes as observed in satellite images. The perspective view was created by draping a Landsat satellite image over an SRTM elevation model. Topography is exaggerated 1.5 times vertically. The Landsat image was provided by the United States Geological Survey's Earth Resources Observations Systems (EROS) Data Center, Sioux Falls, South Dakota.Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on February 11,2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR

  13. Impacts of dust aerosol and adjacency effects on the accuracy of Landsat 8 and RapidEye surface reflectances

    KAUST Repository

    Houborg, Rasmus; McCabe, Matthew


    The atmospheric correction of satellite data is challenging over desert agricultural systems, due to the relatively high aerosol optical thicknesses (τ550), bright soils, and a heterogeneous surface reflectance field. Indeed, the contribution of reflected radiation from adjacent pixels scattered into the field of view of a target pixel is considerable and can significantly affect the fidelity of retrieved reflectances. In this study, uncertainties and quantitative errors associated with the atmospheric correction of multi-spectral Landsat 8 and RapidEye data were characterized over a desert agricultural landscape in Saudi Arabia. Surface reflectances were retrieved using an implementation of the 6SV atmospheric correction code, and validated against field collected spectroradiometer measurements over desert, cultivated soil, and vegetated surface targets. A combination of satellite and Aerosol Robotic Network (AERONET) data were used to parameterize aerosol properties and atmospheric state parameters. With optimal specification of τ550 and aerosol optical properties and correction for adjacency effects, the relative Mean Absolute Deviation (MAD) for all bands combined was 5.4% for RapidEye and 6.8% for Landsat 8. However uncertainties associated with satellite-based τ550 retrievals were shown to introduce significant error into the reflectance estimates. With respect to deriving common vegetation indices from corrected reflectance data, the Normalized Difference Vegetation Index (NDVI) was associated with the smallest errors (3–8% MAD). Surface reflectance errors were highest for bands in the visible part of the spectrum, particularly the blue band (5–16%), while there was more consistency within the red-edge (~ 5%) and near-infrared (5–7%). Results were generally better constrained when a τ550-dependent aerosol model for desert dust particles, parameterized on the basis of nearby AERONET site data, was used in place of a generic rural or background

  14. Impacts of dust aerosol and adjacency effects on the accuracy of Landsat 8 and RapidEye surface reflectances

    KAUST Repository

    Houborg, Rasmus


    The atmospheric correction of satellite data is challenging over desert agricultural systems, due to the relatively high aerosol optical thicknesses (τ550), bright soils, and a heterogeneous surface reflectance field. Indeed, the contribution of reflected radiation from adjacent pixels scattered into the field of view of a target pixel is considerable and can significantly affect the fidelity of retrieved reflectances. In this study, uncertainties and quantitative errors associated with the atmospheric correction of multi-spectral Landsat 8 and RapidEye data were characterized over a desert agricultural landscape in Saudi Arabia. Surface reflectances were retrieved using an implementation of the 6SV atmospheric correction code, and validated against field collected spectroradiometer measurements over desert, cultivated soil, and vegetated surface targets. A combination of satellite and Aerosol Robotic Network (AERONET) data were used to parameterize aerosol properties and atmospheric state parameters. With optimal specification of τ550 and aerosol optical properties and correction for adjacency effects, the relative Mean Absolute Deviation (MAD) for all bands combined was 5.4% for RapidEye and 6.8% for Landsat 8. However uncertainties associated with satellite-based τ550 retrievals were shown to introduce significant error into the reflectance estimates. With respect to deriving common vegetation indices from corrected reflectance data, the Normalized Difference Vegetation Index (NDVI) was associated with the smallest errors (3–8% MAD). Surface reflectance errors were highest for bands in the visible part of the spectrum, particularly the blue band (5–16%), while there was more consistency within the red-edge (~ 5%) and near-infrared (5–7%). Results were generally better constrained when a τ550-dependent aerosol model for desert dust particles, parameterized on the basis of nearby AERONET site data, was used in place of a generic rural or background

  15. Quality Assessment of Landsat Surface Reflectance Products Using MODIS Data (United States)

    Feng, Min; Huang, Chengquan; Channan, Saurabh; Vermote, Eric; Masek, Jeffrey G.; Townshend, John R.


    Surface reflectance adjusted for atmospheric effects is a primary input for land cover change detection and for developing many higher level surface geophysical parameters. With the development of automated atmospheric correction algorithms, it is now feasible to produce large quantities of surface reflectance products using Landsat images. Validation of these products requires in situ measurements, which either do not exist or are difficult to obtain for most Landsat images. The surface reflectance products derived using data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS), however, have been validated more comprehensively. Because the MODIS on the Terra platform and the Landsat 7 are only half an hour apart following the same orbit, and each of the 6 Landsat spectral bands overlaps with a MODIS band, good agreements between MODIS and Landsat surface reflectance values can be considered indicators of the reliability of the Landsat products, while disagreements may suggest potential quality problems that need to be further investigated. Here we develop a system called Landsat-MODIS Consistency Checking System (LMCCS). This system automatically matches Landsat data with MODIS observations acquired on the same date over the same locations and uses them to calculate a set of agreement metrics. To maximize its portability, Java and open-source libraries were used in developing this system, and object-oriented programming (OOP) principles were followed to make it more flexible for future expansion. As a highly automated system designed to run as a stand-alone package or as a component of other Landsat data processing systems, this system can be used to assess the quality of essentially every Landsat surface reflectance image where spatially and temporally matching MODIS data are available. The effectiveness of this system was demonstrated using it to assess preliminary surface reflectance products derived using the Global Land Survey (GLS) Landsat

  16. Reconstructing turbidity in a glacially influenced lake using the Landsat TM and ETM+ surface reflectance climate data record archive, Lake Clark, Alaska (United States)

    Baughman, Carson; Jones, Benjamin M.; Bartz, Krista K.; Young, Daniel B.; Zimmerman, Christian E.


    Lake Clark is an important nursery lake for sockeye salmon (Oncorhynchus nerka) in the headwaters of Bristol Bay, Alaska, the most productive wild salmon fishery in the world. Reductions in water clarity within Alaska lake systems as a result of increased glacial runoff have been shown to reduce salmon production via reduced abundance of zooplankton and macroinvertebrates. In this study, we reconstruct long-term, lake-wide water clarity for Lake Clark using the Landsat TM and ETM+ surface reflectance products (1985–2014) and in situwater clarity data collected between 2009 and 2013. Analysis of a Landsat scene acquired in 2009, coincident with in situ measurements in the lake, and uncertainty analysis with four scenes acquired within two weeks of field data collection showed that Band 3 surface reflectance was the best indicator of turbidity (r2 = 0.55,RMSE turbidity for Lake Clark between 1991 and 2014. We did, however, detect interannual variation that exhibited a non-significant (r2 = 0.20) but positive correlation (r = 0.20) with regional mean summer air temperature and found the month of May exhibited a significant positive trend (r2 = 0.68, p = 0.02) in turbidity between 2000 and 2014. This study demonstrates the utility of hindcasting turbidity in a glacially influenced lake using the Landsat surface reflectance products. It may also help land and resource managers reconstruct turbidity records for lakes that lack in situ monitoring, and may be useful in predicting future water clarity conditions based on projected climate scenarios.

  17. What is the clinical significance of chest CT when the chest x-ray result is normal in patients with blunt trauma? (United States)

    Kea, Bory; Gamarallage, Ruwan; Vairamuthu, Hemamalini; Fortman, Jonathan; Lunney, Kevin; Hendey, Gregory W; Rodriguez, Robert M


    Computed tomography (CT) has been shown to detect more injuries than plain radiography in patients with blunt trauma, but it is unclear whether these injuries are clinically significant. This study aimed to determine the proportion of patients with normal chest x-ray (CXR) result and injury seen on CT and abnormal initial CXR result and no injury on CT and to characterize the clinical significance of injuries seen on CT as determined by a trauma expert panel. Patients with blunt trauma older than 14 years who received emergency department chest imaging as part of their evaluation at 2 urban level I trauma centers were enrolled. An expert trauma panel a priori classified thoracic injuries and subsequent interventions as major, minor, or no clinical significance. Of 3639 participants, 2848 (78.3%) had CXR alone and 791 (21.7%) had CXR and chest CT. Of 589 patients who had chest CT after a normal CXR result, 483 (82.0% [95% confidence interval [CI], 78.7-84.9%]) had normal CT results, and 106 (18.0% [95% CI, 15.1%-21.3%]) had CTs diagnosing injuries-primarily rib fractures, pulmonary contusion, and incidental pneumothorax. Twelve patients had injuries classified as clinically major (2.0% [95% CI, 1.2%-3.5%]), 78 were clinically minor (13.2% [95% CI, 10.7%-16.2%]), and 16 were clinically insignificant (2.7% (95% CI, 1.7%-4.4%]). Of 202 patients with CXRs suggesting injury, 177 (87.6% [95% CI, 82.4%-91.5%]) had chest CTs confirming injury and 25 (12.4% [95% CI, 8.5%-17.6%]) had no injury on CT. Chest CT after a normal CXR result in patients with blunt trauma detects injuries, but most do not lead to changes in patient management. Copyright © 2013 Elsevier Inc. All rights reserved.

  18. Evaluation of solar angle variation over digital processing of LANDSAT imagery. [Brazil (United States)

    Parada, N. D. J. (Principal Investigator); Novo, E. M. L. M.


    The effects of the seasonal variation of illumination over digital processing of LANDSAT images are evaluated. Original images are transformed by means of digital filtering to enhance their spatial features. The resulting images are used to obtain an unsupervised classification of relief units. After defining relief classes, which are supposed to be spectrally different, topographic variables (declivity, altitude, relief range and slope length) are used to identify the true relief units existing on the ground. The samples are also clustered by means of an unsupervised classification option. The results obtained for each LANDSAT overpass are compared. Digital processing is highly affected by illumination geometry. There is no correspondence between relief units as defined by spectral features and those resulting from topographic features.

  19. Cell type-dependent induction of DNA damage by 1800 MHz radiofrequency electromagnetic fields does not result in significant cellular dysfunctions.

    Directory of Open Access Journals (Sweden)

    Shanshan Xu

    Full Text Available BACKGROUND: Although IARC clarifies radiofrequency electromagnetic fields (RF-EMF as possible human carcinogen, the debate on its health impact continues due to the inconsistent results. Genotoxic effect has been considered as a golden standard to determine if an environmental factor is a carcinogen, but the currently available data for RF-EMF remain controversial. As an environmental stimulus, the effect of RF-EMF on cellular DNA may be subtle. Therefore, more sensitive method and systematic research strategy are warranted to evaluate its genotoxicity. OBJECTIVES: To determine whether RF-EMF does induce DNA damage and if the effect is cell-type dependent by adopting a more sensitive method γH2AX foci formation; and to investigate the biological consequences if RF-EMF does increase γH2AX foci formation. METHODS: Six different types of cells were intermittently exposed to GSM 1800 MHz RF-EMF at a specific absorption rate of 3.0 W/kg for 1 h or 24 h, then subjected to immunostaining with anti-γH2AX antibody. The biological consequences in γH2AX-elevated cell type were further explored with comet and TUNEL assays, flow cytometry, and cell growth assay. RESULTS: Exposure to RF-EMF for 24 h significantly induced γH2AX foci formation in Chinese hamster lung cells and Human skin fibroblasts (HSFs, but not the other cells. However, RF-EMF-elevated γH2AX foci formation in HSF cells did not result in detectable DNA fragmentation, sustainable cell cycle arrest, cell proliferation or viability change. RF-EMF exposure slightly but not significantly increased the cellular ROS level. CONCLUSIONS: RF-EMF induces DNA damage in a cell type-dependent manner, but the elevated γH2AX foci formation in HSF cells does not result in significant cellular dysfunctions.

  20. Detecting of forest afforestation and deforestation in Hainan Jianfengling Forest Park (China) using yearly Landsat time-series images (United States)

    Jiao, Quanjun; Zhang, Xiao; Sun, Qi


    The availability of dense time series of Landsat images pro-vides a great chance to reconstruct forest disturbance and change history with high temporal resolution, medium spatial resolution and long period. This proposal aims to apply forest change detection method in Hainan Jianfengling Forest Park using yearly Landsat time-series images. A simple detection method from the dense time series Landsat NDVI images will be used to reconstruct forest change history (afforestation and deforestation). The mapping result showed a large decrease occurred in the extent of closed forest from 1980s to 1990s. From the beginning of the 21st century, we found an increase in forest areas with the implementation of forestry measures such as the prohibition of cutting and sealing in our study area. Our findings provide an effective approach for quickly detecting forest changes in tropical original forest, especially for afforestation and deforestation, and a comprehensive analysis tool for forest resource protection.

  1. Use of LANDSAT 8 images for depth and water quality assessment of El Guájaro reservoir, Colombia (United States)

    González-Márquez, Luis Carlos; Torres-Bejarano, Franklin M.; Torregroza-Espinosa, Ana Carolina; Hansen-Rodríguez, Ivette Renée; Rodríguez-Gallegos, Hugo B.


    The aim of this study was to evaluate the viability of using Landsat 8 spectral images to estimate water quality parameters and depth in El Guájaro Reservoir. On February and March 2015, two samplings were carried out in the reservoir, coinciding with the Landsat 8 images. Turbidity, dissolved oxygen, electrical conductivity, pH and depth were evaluated. Through multiple regression analysis between measured water quality parameters and the reflectance of the pixels corresponding to the sampling stations, statistical models with determination coefficients between 0.6249 and 0.9300 were generated. Results indicate that from a small number of measured parameters we can generate reliable models to estimate the spatial variation of turbidity, dissolved oxygen, pH and depth, as well the temporal variation of electrical conductivity, so models generated from Landsat 8 can be used as a tool to facilitate the environmental, economic and social management of the reservoir.

  2. Detecting Uniform Areas for Vicarious Calibration using Landsat TM Imagery: A Study using the Arabian and Saharan Deserts (United States)

    Hilbert, Kent; Pagnutti, Mary; Ryan, Robert; Zanoni, Vicki


    This paper discusses a method for detecting spatially uniform sites need for radiometric characterization of remote sensing satellites. Such information is critical for scientific research applications of imagery having moderate to high resolutions (African Saharan and Arabian deserts contained extremely uniform sites with respect to spatial characteristics. We developed an algorithm for detecting site uniformity and applied it to orthorectified Landsat Thematic Mapper (TM) imagery over eight uniform regions of interest. The algorithm's results were assessed using both medium-resolution (30-m GSD) Landsat 7 ETM+ and fine-resolution (research shows that Landsat TM products appear highly useful for detecting potential calibration sites for system characterization. In particular, the approach detected spatially uniform regions that frequently occur at multiple scales of observation.

  3. Estimating the chlorophyll content in the waters of Guanabara Bay from the LANDSAT multispectral scanning digital data (United States)

    Dejesusparada, N. (Principal Investigator); Bentancurt, J. J. V.; Herz, B. R.; Molion, L. B.


    Detection of water quality in Guanabara Bay using multispectral scanning digital data taken from LANDSAT satellites was examined. To test these processes, an empirical (statistical) approach was choosen to observe the degree of relationship between LANDSAT data and the in situ data taken simultaneously. The linear and nonlinear regression analyses were taken from among those developed by INPE in 1978. Results indicate that the major regression was in the number six MSS band, atmospheric effects, which indicated a correction coefficient of 0.99 and an average error of 6.59 micrograms liter. This error was similar to that obtained in the laboratory. The chlorophyll content was between 0 and 100 micrograms/liter, as taken from the MSS of LANDSAT.

  4. Women with provoked vestibulodynia experience clinically significant reductions in pain regardless of treatment: results from a 2-year follow-up study. (United States)

    Davis, Seth N P; Bergeron, Sophie; Binik, Yitzchak M; Lambert, Bernard


    Provoked vestibulodynia (PVD) is a prevalent genital pain syndrome that has been assumed to be chronic, with little spontaneous remission. Despite this assumption, there is a dearth of empirical evidence regarding the progression of PVD in a natural setting. Although many treatments are available, there is no single treatment that has demonstrated efficacy above others. The aims of this secondary analysis of a prospective study were to (i) assess changes over a 2-year period in pain, depressive symptoms, and sexual outcomes in women with PVD; and (ii) examine changes based on treatment(s) type. Participants completed questionnaire packages at Time 1 and a follow-up package 2 years later. Visual analog scale of genital pain, Global Measure of Sexual Satisfaction, Female Sexual Function Index, Beck Depression Inventory, Dyadic Adjustment Scale, and sexual intercourse attempts over the past month. Two hundred thirty-nine women with PVD completed both time one and two questionnaires. For the sample as a whole, there was significant improvement over 2 years on pain ratings, sexual satisfaction, sexual function, and depressive symptoms. The most commonly received treatments were physical therapy, sex/psychotherapy, and medical treatment, although 41.0% did not undergo any treatment. Women receiving no treatment also improved significantly on pain ratings. No single treatment type predicted better outcome for any variable except depressive symptoms, in which women who underwent surgery were more likely to improve. These results suggest that PVD may significantly reduce in severity over time. Participants demonstrated clinically significant pain improvement, even when they did not receive treatment. Furthermore, the only single treatment type predicting better outcomes was surgery, and only for depressive symptoms, accounting for only 2.3% of the variance. These data do not demonstrate the superiority of any one treatment and underscore the need to have control groups in

  5. Application of Landsat 5-TM and GIS data to elk habitat studies in northern Idaho (United States)

    Hayes, Stephen Gordon


    An extensive geographic information system (GIS) database and a large radiotelemetry sample of elk (n = 153) were used to study habitat use and selection differences between cow and bull elk (Cervus elaphus) in the Coeur d'Alene Mountains of Idaho. Significant sex differences in 40 ha area use, and interactive effects of sex and season on selection of 40 ha areas from home ranges were found. In all seasons, bulls used habitats with more closed canopy forest, more hiding cover, and less shrub and graminoid cover, than cows. Cows selected areas with shrub and graminoid cover in winter and avoided areas with closed canopy forest and hiding cover in winter and summer seasons. Both sexes selected 40 ha areas of unfragmented hiding cover and closed canopy forest during the hunting season. Bulls also avoided areas with high open road densities during the rut and hunting season. These results support present elk management recommendations, but our observations of sexual segregation provide biologists with an opportunity to refine habitat management plans to target bulls and cows specifically. Furthermore, the results demonstrate that hiding cover and canopy closure can be accurately estimated from Landsat 5-TM imagery and GIS soil data at a scale and resolution to which elk respond. As a result, our habitat mapping methods can be applied to large areas of private and public land with consistent, cost-efficient results. Non-Lambertian correction models of Landsat 5-TM imagery were compared to an uncorrected image to determine if topographic normalization increased the accuracy of elk habitat maps of forest structure in northern Idaho. The non-Lambertian models produced elk habitat maps with overall and kappa statistic accuracies as much as 21.3% higher (p < 0.0192) than the uncorrected image. Log-linear models and power analysis were used to study the dependence of commission and omission error rates on topographic normalization, vegetation type, and solar incidence angle

  6. The low risk of precancer after a screening result of human papillomavirus-negative/atypical squamous cells of undetermined significance papanicolaou and implications for clinical management. (United States)

    Gage, Julia C; Katki, Hormuzd A; Schiffman, Mark; Castle, Philip E; Fetterman, Barbara; Poitras, Nancy E; Lorey, Thomas; Cheung, Li C; Behrens, Catherine; Sharma, Abha; Zhao, Fang-Hui; Cuzick, Jack; Yang, Zi Hua; Kinney, Walter K


    Different US practice guidelines have conflicting recommendations for when women should return after a screening result of human papillomavirus (HPV)-negative with an equivocal Papanicolaou (Pap) result of atypical squamous cells of undetermined significance (ASC-US) (ie, return in either 3 or 5 years). One way to determine management is to compare the risk of precancer/cancer after an HPV-negative/ASC-US result with the risks after other negative screening results. For example, if the risk after an HPV-negative/ASC-US result was similar to the risk after a negative Pap test, a 3-year return would be preferred because guidelines agree that women with negative Pap test results should return in 3 years. Alternatively, if the risk after an HPV-negative/ASC-US result is similar to that after a cotest-negative result (HPV negative/Pap test negative), a 5-year return would be preferred because guidelines agree that women testing cotest negative should return in 5 years. The authors compared risks of cervical intraepithelial neoplasia of grade 3 or higher (CIN3+) and cervical cancer among women aged 30 years to 64 years at Kaiser Permanente Northern California with the following test results from 2003 through 2012: 17,191 women testing HPV negative/ASC-US; 980,268 women testing Pap test negative (regardless of HPV result); and 892,882 women testing cotest negative. The 5-year CIN3+ and cancer risks after an HPV-negative/ASC-US result were closer to the risks after a negative Pap test result (CIN3+: 0.48% vs 0.31% [P =.0019]; and cancer: 0.043% vs 0.031% [P =.4]) than after a negative cotest (CIN3+: 0.48% vs 0.11% [P<.0001]; and cancer: 0.043% vs 0.014% [P =.016]). Women testing HPV negative/ASC-US were found to have precancer/cancer risks that were more closely aligned with women with negative Pap test results, suggesting that women testing HPV negative/ASC-US should be managed similarly to women testing negative on Pap tests with a 3-year return for screening. © 2014

  7. Landsat TM and ETM+ Kansas Satellite Image Database (KSID) (United States)

    Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2000-2001 consists of terrain-corrected, precision rectified spring, summer, and fall Landsat 5 Thematic Mapper (TM) and...

  8. LANDSAT-1 data, its use in a soil survey program (United States)

    Westin, F. C.; Frazee, C. J.


    The following applications of LANDSAT imagery were investigated: assistance in recognizing soil survey boundaries, low intensity soil surveys, and preparation of a base map for publishing thematic soils maps. The following characteristics of LANDSAT imagery were tested as they apply to the recognition of soil boundaries in South Dakota and western Minnesota: synoptic views due to the large areas covered, near-orthography and lack of distortion, flexibility of selecting the proper season, data recording in four parts of the spectrum, and the use of computer compatible tapes. A low intensity soil survey of Pennington County, South Dakota was completed in 1974. Low intensity inexpensive soil surveys can provide the data needed to evaluate agricultural land for the remaining counties until detailed soil surveys are completed. In using LANDSAT imagery as a base map for publishing thematic soil maps, the first step was to prepare a mosaic with 20 LANDSAT scenes from several late spring passes in 1973.

  9. Global Man-made Impervious Surface (GMIS) Dataset From Landsat (United States)

    National Aeronautics and Space Administration — The Global Man-made Impervious Surface (GMIS) Dataset From Landsat consists of global estimates of fractional impervious cover derived from the Global Land Survey...

  10. Revealing livestock effects on bunchgrass vegetation with Landsat ETM+ data across a grazing season (United States)

    Jansen, Vincent S.

    Remote sensing provides monitoring solutions for more informed grazing management. To investigate the ability to detect the effects of cattle grazing on bunchgrass vegetation with Landsat Enhanced Thematic Mapper Plus (ETM+) data, we conducted a study on the Zumwalt Prairie in northeastern Oregon across a gradient of grazing intensities. Biophysical vegetation data was collected on vertical structure, biomass, and cover at three different time periods during the grazing season: June, August, and October 2012. To relate these measures to the remotely sensed Landsat ETM+ data, Pearson's correlations and multiple regression models were computed. Using the best models, predicted vegetation metrics were then mapped across the study area. Results indicated that models using common vegetation indices had the ability to discern different levels of grazing across the study area. Results can be distributed to land managers to help guide grassland conservation by improving monitoring of bunchgrass vegetation for sustainable livestock management.

  11. Assessment of the Trophic State and Chlorophyll-A Concentrations using Landsat OLI in Karaoun Reservoir Lebanon

    International Nuclear Information System (INIS)

    Fadel, A.; Faour, GH.; Slim, K.


    Harmful algal blooms have become a worldwide environmental problem. A regular and cost -effective monitoring of these blooms is highly needed by lakes managers. Satellite remote sensing imagery like Landsat Operational Land Imager (OLI) can be used to assess and monitor chlorophyll-a in water bodies over large areas in a cost-effective way. In this study, the accuracy of Landsat OLI to estimate chlorophyll-a was examined. Four field campaigns and cloud free images of Landsat OLI with 30 m resolution (01 May 2013, 21 August 2013, 10 July 2015, and 11 August 2015) were used in this study to determine the accuracy of Landsat OLI in estimating chlorophyll-a in a 12 km2 fresh water body, Karaoun reservoir. After atmospheric correction of these images, reflectance of single and multiple band combinations were compared to field chlorophyll-a data. Results of field campaigns showed that the trophic state of Karaoun reservoir is still eutrophic to hypereutrophic withhigh nutrient concentration andlow phytoplankton biodiversity, dominatedby cyanobacteria species, Microcystis aeruginosa and Aphanizomenon ovalisporum. On single band level, the n situ chlorophyll-a measurement correlated best with band 5 (0.85 -0.88 μm), with R=0.75 and R2=0.57.Highest correlation (R=0.84 and R2=0.72) was obtained using band combination, B2:B4 band ratio multiplied by B5. Results indicated that Landsat OLI can be used effectively to determine chlorophyll-a concentration in lakes and reservoirs. We recommend the application of Landsat OLI as a satisfactory and cost effective method for monitoring chlorophyll-a in other lakes through-out the world. (author)

  12. Mapping fractional woody cover in semi-arid savannahs using multi-seasonal composites from Landsat data (United States)

    Higginbottom, Thomas P.; Symeonakis, Elias; Meyer, Hanna; van der Linden, Sebastian


    Increasing attention is being directed at mapping the fractional woody cover of savannahs using Earth-observation data. In this study, we test the utility of Landsat TM/ ETM-based spectral-temporal variability metrics for mapping regional-scale woody cover in the Limpopo Province of South Africa, for 2010. We employ a machine learning framework to compare the accuracies of Random Forest models derived using metrics calculated from different seasons. We compare these results to those from fused Landsat-PALSAR data to establish if seasonal metrics can compensate for structural information from the PALSAR signal. Furthermore, we test the applicability of a statistical variable selection method, the recursive feature elimination (RFE), in the automation of the model building process in order to reduce model complexity and processing time. All of our tests were repeated at four scales (30, 60, 90, and 120 m-pixels) to investigate the role of spatial resolution on modelled accuracies. Our results show that multi-seasonal composites combining imagery from both the dry and wet seasons produced the highest accuracies (R2 = 0.77, RMSE = 9.4, at the 120 m scale). When using a single season of observations, dry season imagery performed best (R2 = 0.74, RMSE = 9.9, at the 120 m resolution). Combining Landsat and radar imagery was only marginally beneficial, offering a mean relative improvement of 1% in accuracy at the 120 m scale. However, this improvement was concentrated in areas with lower densities of woody coverage (continue to exploit the Landsat archive, but should aim to use multi-seasonal derived information. When the coarser 120 m pixel scale is adequate, integration of Landsat and SAR data should be considered, especially in areas with lower woody cover densities. The use of multiple seasonal compositing periods offers promise for large-area mapping of savannahs, even in regions with a limited historical Landsat coverage.

  13. An Initial Analysis of LANDSAT-4 Thematic Mapper Data for the Discrimination of Agricultural, Forested Wetland, and Urban Land Covers (United States)

    Quattrochi, D. A.


    An initial analysis of LANDSAT 4 Thematic Mapper (TM) data for the discrimination of agricultural, forested wetland, and urban land covers is conducted using a scene of data collected over Arkansas and Tennessee. A classification of agricultural lands derived from multitemporal LANDSAT Multispectral Scanner (MSS) data is compared with a classification of TM data for the same area. Results from this comparative analysis show that the multitemporal MSS classification produced an overall accuracy of 80.91% while the TM classification yields an overall classification accuracy of 97.06% correct.

  14. Landsat 8 Data Modeled as DGGS Data Cubes (United States)

    Sherlock, M. J.; Tripathi, G.; Samavati, F.


    In the context of tracking recent global changes in the Earth's landscape, Landsat 8 provides high-resolution multi-wavelength data with a temporal resolution of sixteen days. Such a live dataset can benefit novel applications in environmental monitoring. However, a temporal analysis of this dataset in its native format is a challenging task mostly due to the huge volume of geospatial images and imperfect overlay of different day Landsat 8 images. We propose the creation of data cubes derived from Landsat 8 data, through the use of a Discrete Global Grid System (DGGS). DGGS referencing of Landsat 8 data provides a cell-based representation of the pixel values for a fixed area on earth, indexed by keys. Having the calibrated cell-based Landsat 8 images can speed up temporal analysis and facilitate parallel processing using distributed systems. In our method, the Landsat 8 dataset hosted on Amazon Web Services (AWS) is downloaded using a web crawler and stored on a filesystem. We apply the cell-based DGGS referencing (using Pyxis SDK) to Landsat 8 images which provide a rhombus based tessellation of equal area cells for our use-case. After this step, the cell-images which overlay perfectly on different days, are stacked in the temporal dimension and stored into data cube units. The depth of the cube represents the number of temporal images of the same cell and can be updated when new images are received each day. Harnessing the regular spatio-temporal structure of data cubes, we want to compress, query, transmit and visualize big Landsat 8 data in an efficient way for temporal analysis.

  15. Cádiz bay walers lurbidily varialions from Landsat TM images analysis


    Gutiérrez Mas, José Manuel; Luna del Barco, A.; Parrado Román, J. M.; Sánchez, E.; Fernández Palacios, A.; Ojeda, J.


    Landsat TM images has been analysed to obtain extent and direction data about turbidity flumes in several hydrodinamic sinoptic situations in Cadiz bay waters. Results are beside data from water samples. Five turbidity levels has been differentiated: very high turbidity, high, middle, low and very low, and three geographic sectors: a) Inner zone, closed to coast and with shoal waters of high and very high turbidity. This sector is very affected by littoral processes (tidals, surge and contine...

  16. Geometric pattern recognition techniques applied to land Landsat digital data for uranium exploration

    International Nuclear Information System (INIS)


    Although the results we obtained cannot be described as providing a new tool for uranium exploration, we saw clear evidence that computed texture measures are describing some element of the Landsat data source that cannot be readily observed or analyzed by human interpreters. The success of Eigenband 3 is less surprising, since we had other evidence suggesting that such a band ought to be relevant to image textures

  17. Ten Years of Forest Cover Change in the Sierra Nevada Detected Using Landsat Satellite Image Analysis (United States)

    Potter, Christopher S.


    A detailed geographic record of recent vegetation regrowth and disturbance patterns in forests of the Sierra Nevada remains a gap that can be filled with remote sensing data. Landsat (TM) imagery was analyzed to detect 10 years of recent changes (between 2000 and 2009) in forest vegetation cover for areas burned by wildfires between years of 1995 to 1999 in the region. Results confirmed the prevalence of regrowing forest vegetation during the period 2000 and 2009 over 17% of the combined burned areas.

  18. Mapping and Evaluation of NDVI Trends from Synthetic Time Series Obtained by Blending Landsat and MODIS Data around a Coalfield on the Loess Plateau

    Directory of Open Access Journals (Sweden)

    Kun Wang


    Full Text Available The increasingly intensive and extensive coal mining activities on the Loess Plateau pose a threat to the fragile local ecosystems. Quantifying the effects of coal mining activities on environmental conditions is of great interest for restoring and managing the local ecosystems and resources. This paper generates dense NDVI (Normalized Difference Vegetation Index time series between 2000 and 2011 at a spatial resolution of 30 m by blending Landsat and MODIS (Moderate Resolution Imaging Spectroradiometer data using the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM and further evaluates its capability for mapping vegetation trends around a typical coalfield on the Loss Plateau. Synthetic NDVI images were generated using (1 STARFM-generated NIR (near infrared and red band reflectance data (scheme 1 and (2 Landsat and MODIS NDVI images directly as inputs for STARFM (scheme 2. By comparing the synthetic NDVI images with the corresponding Landsat NDVI, we found that scheme 2 consistently generated better results (0.70 < R2 < 0.76 than scheme 1 (0.56 < R2 < 0.70 in this study area. Trend analysis was then performed with the synthetic dense NDVI time series and the annual maximum NDVI (NDVImax time series. The accuracy of these trends was evaluated by comparing to those from the corresponding MODIS time series, and it was concluded that both the trends from synthetic/MODIS NDVI dense time series and synthetic/MODIS NDVImax time series (2000–2011 were highly consistent. Compared to trends from MODIS time series, trends from synthetic time series are better able to capture fine scale vegetation changes. STARFM-generated synthetic NDVI time series could be used to quantify the effects of mining activities on vegetation, but the test areas should be selected with caution, as the trends derived from synthetic and MODIS time series may be significantly different in some areas.

  19. Machine learning-based Landsat-MODIS data fusion approach for 8-day 30m evapotranspiration monitoring (United States)

    Im, J.; Ke, Y.; Park, S.


    Continuous monitoring of evapotranspiration (ET) is important for understanding of hydrological cycles and energy flux dynamics. At regional and local scales, routine ET estimation is a critical for efficient water management, drought impact assessment and ecosystem health monitoring, etc. Remote sensing has long been recognized to be able to provide ET monitoring over large areas. However, no single satellite could provide temporally continuous ET at relatively high spatial resolution due to the trade-off between the spatial and temporal resolution of current satellite sensors. Landsat-series satellites provide optical and thermal imagery at 30-100m resolution, whereas the 16-day revisit cycle hinders the observation of ET dynamics; MODIS provides sources of ET estimation at daily basis, but the 500-1000m ground sampling distance is too coarse for field level applications. In this study, we present a machine learning and STARFM based method for Landsat/MODIS ET fusion. The approach first downscales MODIS 8-day 1km ET (MOD16A2) to 30m based on eleven Landsat-derived indicators such as NDVI, EVI, NDWI etc on the cloud-free Landsat-available days using Random Forest approach. For the days when Landsat data are not available, downscaled ET is synthesized by MODIS and Landsat data fusion with STARFM and STI-FM approaches. The models are evaluated using in situ flux tower measurements at US-ARM and US-Twt AmeriFlux sites the United States. Results show that the downscaled 30m ET have good agreement with MODIS ET (RMSE=0.42-3.4mm/8days, rRMSE=3.2%-26%) and the downscaled ET have higher accuracy than MODIS ET when compared to in-situ measurements.

  20. LANDSAT-4 MSS and Thematic Mapper data quality and information content analysis (United States)

    Anuta, P.; Bartolucci, L.; Dean, E.; Lozano, F.; Malaret, E.; Mcgillem, C. D.; Valdes, J.; Valenzuela, C.


    LANDSAT-4 thematic mapper (TM) and multispectral scanner (MSS) data were analyzed to obtain information on data quality and information content. Geometric evaluations were performed to test band-to-band registration accuracy. Thematic mapper overall system resolution was evaluated using scene objects which demonstrated sharp high contrast edge responses. Radiometric evaluation included detector relative calibration, effects of resampling, and coherent noise effects. Information content evaluation was carried out using clustering, principal components, transformed divergence separability measure, and supervised classifiers on test data. A detailed spectral class analysis (multispectral classification) was carried out to compare the information content of the MSS and TM for a large number of scene classes. A temperature-mapping experiment was carried out for a cooling pond to test the quality of thermal-band calibration. Overall TM data quality is very good. The MSS data are noisier than previous LANDSAT results.

  1. Regional analysis of tertiary volcanic Calderas (western U.S.) using Landsat Thematic Mapper imagery (United States)

    Spatz, David M.; Taranik, James V.


    The Landsat Thematic Mapper (TM) imagery of the Basin and Range province of southern Nevada was analyzed to identify and map volcanic rock assemblages at three Tertiary calderas. It was found that the longer-wavelength visible and the NIR TM Bands 3, 5, and 7 provide more effective lithologic discrimination than the shorter-wavelength bands, due partly to deeper penetration of the longer-wavelength bands, resulting in more lithologically driven radiances. Shorter-wavelength TM Bands 1 and 2 are affected more by surficial weathering products including desert varnish which may or may not provide an indirect link to lithologic identity. Guidelines for lithologic analysis of volcanic terrains using Landsat TM imagery are outlined.

  2. Normalizing Landsat and ASTER Data Using MODIS Data Products for Forest Change Detection (United States)

    Gao, Feng; Masek, Jeffrey G.; Wolfe, Robert E.; Tan, Bin


    Monitoring forest cover and its changes are a major application for optical remote sensing. In this paper, we present an approach to integrate Landsat, ASTER and MODIS data for forest change detection. Moderate resolution (10-100m) images (e.g. Landsat and ASTER) acquired from different seasons and times are normalized to one "standard" date using MODIS data products as reference. The normalized data are then used to compute forest disturbance index for forest change detection. Comparing to the results from original data, forest disturbance index from the normalized images is more consistent spatially and temporally. This work demonstrates an effective approach for mapping forest change over a large area from multiple moderate resolution sensors on various acquisition dates.

  3. Land cover classification of Landsat 8 satellite data based on Fuzzy Logic approach (United States)

    Taufik, Afirah; Sakinah Syed Ahmad, Sharifah


    The aim of this paper is to propose a method to classify the land covers of a satellite image based on fuzzy rule-based system approach. The study uses bands in Landsat 8 and other indices, such as Normalized Difference Water Index (NDWI), Normalized difference built-up index (NDBI) and Normalized Difference Vegetation Index (NDVI) as input for the fuzzy inference system. The selected three indices represent our main three classes called water, built- up land, and vegetation. The combination of the original multispectral bands and selected indices provide more information about the image. The parameter selection of fuzzy membership is performed by using a supervised method known as ANFIS (Adaptive neuro fuzzy inference system) training. The fuzzy system is tested for the classification on the land cover image that covers Klang Valley area. The results showed that the fuzzy system approach is effective and can be explored and implemented for other areas of Landsat data.

  4. Individuals with clinically significant insomnia symptoms are characterised by a negative sleep-related expectancy bias: Results from a cognitive-experimental assessment. (United States)

    Courtauld, Hannah; Notebaert, Lies; Milkins, Bronwyn; Kyle, Simon D; Clarke, Patrick J F


    Cognitive models of insomnia consistently suggest that negative expectations regarding the consequences of poor sleep contribute to the maintenance of insomnia. To date, however, no research has sought to determine whether insomnia is indeed characterised by such a negative sleep-related expectancy bias, using objective cognitive assessment tasks which are more immune to response biases than questionnaire assessments. Therefore, the current study employed a reaction-time task assessing biased expectations among a group with clinically significant insomnia symptoms (n = 30) and a low insomnia symptoms group (n = 40). The task involved the presentation of scenarios describing the consequences of poor sleep, and non-sleep related activities, which could be resolved in a benign or a negative manner. The results demonstrated that the high insomnia symptoms group were disproportionately fast to resolve sleep-related scenarios in line with negative outcomes, as compared to benign outcomes, relative to the low insomnia symptoms group. The two groups did not differ in their pattern of resolving non-sleep related scenarios. This pattern of findings is entirely consistent with a sleep-specific expectancy bias operating in individuals with clinically significant insomnia symptoms, and highlights the potential of cognitive-experimental assessment tasks to objectively index patterns of biased cognition in insomnia. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Near-Real-Time Monitoring of Insect Defoliation Using Landsat Time Series

    Directory of Open Access Journals (Sweden)

    Valerie J. Pasquarella


    Full Text Available Introduced insects and pathogens impact millions of acres of forested land in the United States each year, and large-scale monitoring efforts are essential for tracking the spread of outbreaks and quantifying the extent of damage. However, monitoring the impacts of defoliating insects presents a significant challenge due to the ephemeral nature of defoliation events. Using the 2016 gypsy moth (Lymantria dispar outbreak in Southern New England as a case study, we present a new approach for near-real-time defoliation monitoring using synthetic images produced from Landsat time series. By comparing predicted and observed images, we assessed changes in vegetation condition multiple times over the course of an outbreak. Initial measures can be made as imagery becomes available, and season-integrated products provide a wall-to-wall assessment of potential defoliation at 30 m resolution. Qualitative and quantitative comparisons suggest our Landsat Time Series (LTS products improve identification of defoliation events relative to existing products and provide a repeatable metric of change in condition. Our synthetic-image approach is an important step toward using the full temporal potential of the Landsat archive for operational monitoring of forest health over large extents, and provides an important new tool for understanding spatial and temporal dynamics of insect defoliators.

  6. Landsat 5 TM images and DEM in lithologic mapping of Payen Volcanic Field (Mendoza Province, Argentina)

    International Nuclear Information System (INIS)

    Fornaciai, A.; Bisson, M.; Mazzarini, F.; Del Carlo, P.; Pasquare, G.


    Satellite image such as Landsat 5 TM scene provides excellent representation of Earth and synoptic view of large geographic areas in different band combination. Landsat TM images allow automatic and semi-automatic classification of land cover, nevertheless the software frequently may some difficulties in distinguishing between similar radiometric surfaces. In this case, the use of Digital Elevation Model (DEM) can be an important tool to identify different surface covers. In this study, several False Color Composite (FCC) of Landsat 5 TM Image, DEM and the respective draped image of them, were used to delineate lithological boundaries and tectonic features of regional significance of the Paven Volcanic Field (PVF). PFV is a Quaternary fissural structure belonging to the black-arc extensional areas of the Andes in the Mendoza Province (Argentina) characterized by many composite basaltic lava flow fields. The necessity to identify different lava flows with the same composition, and then with same spectral features, allows to highlight the improvement of synergic use of TM images and shaded DEM in the visual interpretation. Information obtained from Satellite data and DEM have been compared with previous geological maps and transferred into a topographical base map. Based on these data a new lithological map at 1:100.000 scale has been presented [it

  7. Automated Sargassum Detection for Landsat Imagery (United States)

    McCarthy, S.; Gallegos, S. C.; Armstrong, D.


    We implemented a system to automatically detect Sargassum, a floating seaweed, in 30-meter LANDSAT-8 Operational Land Imager (OLI) imagery. Our algorithm for Sargassum detection is an extended form of Hu's approach to derive a floating algae index (FAI) [1]. Hu's algorithm was developed for Moderate Resolution Imaging Spectroradiometer (MODIS) data, but we extended it for use with the OLI bands centered at 655, 865, and 1609 nm, which are comparable to the MODIS bands located at 645, 859, and 1640 nm. We also developed a high resolution true color product to mask cloud pixels in the OLI scene by applying a threshold to top of the atmosphere (TOA) radiances in the red (655 nm), green (561 nm), and blue (443 nm) wavelengths, as well as a method for removing false positive identifications of Sargassum in the imagery. Hu's algorithm derives a FAI for each Sargassum identified pixel. Our algorithm is currently set to only flag the presence of Sargassum in an OLI pixel by classifying any pixel with a FAI > 0.0 as Sargassum. Additionally, our system geo-locates the flagged Sargassum pixels identified in the OLI imagery into the U.S. Navy Global HYCOM model grid. One element of the model grid covers an area 0.125 degrees of latitude by 0.125 degrees of longitude. To resolve the differences in spatial coverage between Landsat and HYCOM, a scheme was developed to calculate the percentage of pixels flagged within the grid element and if above a threshold, it will be flagged as Sargassum. This work is a part of a larger system, sponsored by NASA/Applied Science and Technology Project at J.C. Stennis Space Center, to forecast when and where Sargassum will land on shore. The focus area of this work is currently the Texas coast. Plans call for extending our efforts into the Caribbean. References: [1] Hu, Chuanmin. A novel ocean color index to detect floating algae in the global oceans. Remote Sensing of Environment 113 (2009) 2118-2129.

  8. Water Productivity Mapping (WPM Using Landsat ETM+ Data for the Irrigated Croplands of the Syrdarya River Basin in Central Asia

    Directory of Open Access Journals (Sweden)

    Sabirjan Isaev


    Full Text Available The overarching goal of this paper was to espouse methods and protocols for water productivity mapping (WPM using high spatial resolution Landsat remote sensing data. In a world where land and water for agriculture are becoming increasingly scarce, growing “more crop per drop” (increasing water productivity becomes crucial for food security of future generations. The study used time-series Landsat ETM+ data to produce WPMs of irrigated crops, with emphasis on cotton in the Galaba study area in the Syrdarya river basin of Central Asia. The WPM methods and protocols using remote sensing data consisted of: (1 crop productivity (ton/ha maps (CPMs involvingcrop type classification, crop yield and biophysical modeling, and extrapolating yield models to larger areas using remotely sensed data; (2 crop water use (m3/ha maps (WUMs (or actual seasonal evapotranspiration or actual ET developed through Simplified Surface Energy Balance (SSEB model; and (3 water productivity (kg/m3 maps (WPMs produced by dividing raster layers of CPMs by WUMs. The SSEB model calculated WUMs (actual ET by multiplying the ET fractionby reference ET. The ETfraction was determined using Landsat thermal imagery by selecting the “hot” pixels (zero ET and “cold” pixels (maximum ET. The grass reference ET was calculated by FAO Penman-Monteith method using meteorological data. The WPMs for the Galaba study area demonstrated a wide variations (0-0.54 kg/m3 in water productivity of cotton fields with overwhelming proportion (87% of the area having WP less than 0.30 kg/m3, 11% of the area having WP in range of 0.30-0.36 kg/m3, and only 2% of the area with WP greater than 0.36 kg/m3. These results clearly imply that there are opportunities for significant WP increases in overwhelming proportion of the existing croplands. The areas of low WP are spatially pin-pointed and can be used as focus for WP improvements

  9. Distinguishing Bark Beetle-infested Vegetation by Tree Species Types and Stress Levels using Landsat Data (United States)

    Sivanpillai, R.; Ewers, B. E.; Speckman, H. N.; Miller, S. N.


    In the Western United States, more than 3 million hectares of lodgepole pine forests have been impacted by the Mountain pine beetle outbreak, while another 166,000 hectares of spruce-fir forests have been attacked by Spruce beetle. Following the beetle attack, the trees lose their hydraulic conductivity thus altering their carbon and water fluxes. These trees go through various stages of stress until mortality, described by color changes in their needles prior to losing them. Modeling the impact of these vegetation types require thematically precise land cover data that distinguishes lodgepole pine and spruce-fir forests along with the stage of impact since the ecosystem fluxes are different for these two systems. However, the national and regional-scale land cover datasets derived from remotely sensed data do not have this required thematic precision. We evaluated the feasibility of multispectral data collected by Landsat 8 to distinguish lodgepole pine and spruce fir, and subsequently model the different stages of attack using field data collected in Medicine Bow National Forest (Wyoming, USA). Operational Land Imager, onboard Landsat 8 has more spectral bands and higher radiometric resolution (12 bit) in comparison to sensors onboard earlier Landsat missions which could improve the ability to distinguish these vegetation types and their stress conditions. In addition to these characteristics, its repeat coverage, rigorous radiometric calibration, wide swath width, and no-cost data provide unique advantages to Landsat data for mapping large geographic areas. Initial results from this study highlight the importance of SWIR bands for distinguishing different levels of stress, and the need for ancillary data for distinguishing species types. Insights gained from this study could lead to the generation of land cover maps with higher thematic precision, and improve the ability to model various ecosystem processes as a result of these infestations.

  10. Monitoring Annual Urban Changes in a Rapidly Growing Portion of Northwest Arkansas with a 20-Year Landsat Record

    Directory of Open Access Journals (Sweden)

    Ryan Reynolds


    Full Text Available Northwest Arkansas has undergone a significant urban transformation in the past several decades and is considered to be one of the fastest growing regions in the United States. The urban area expansion and the associated demographic increases bring unprecedented pressure to the environment and natural resources. To better understand the consequences of urbanization, accurate and long-term depiction on urban dynamics is critical. Although urban mapping activities using remote sensing have been widely conducted, long-term urban growth mapping at an annual pace is rare and the low accuracy of change detection remains a challenge. In this study, a time series Landsat stack covering the period from 1995 to 2015 was employed to detect the urban dynamics in Northwest Arkansas via a two-stage classification approach. A set of spectral indices that have been proven to be useful in urban area extraction together with the original Landsat spectral bands were used in the maximum likelihood classifier and random forest classifier to distinguish urban from non-urban pixels for each year. A temporal trajectory polishing method, involving temporal filtering and heuristic reasoning, was then applied to the sequence of classified urban maps for further improvement. Based on a set of validation samples selected for five distinct years, the average overall accuracy of the final polished maps was 91%, which improved the preliminary classifications by over 10%. Moreover, results from this study also indicated that the temporal trajectory polishing method was most effective with initial low accuracy classifications. The resulting urban dynamic map is expected to provide unprecedented details about the area, spatial configuration, and growing trends of urban land-cover in Northwest Arkansas.

  11. Comparative analysis of Worldview-2 and Landsat 8 for coastal saltmarsh mapping accuracy assessment (United States)

    Rasel, Sikdar M. M.; Chang, Hsing-Chung; Diti, Israt Jahan; Ralph, Tim; Saintilan, Neil


    Coastal saltmarsh and their constituent components and processes are of an interest scientifically due to their ecological function and services. However, heterogeneity and seasonal dynamic of the coastal wetland system makes it challenging to map saltmarshes with remotely sensed data. This study selected four important saltmarsh species Pragmitis australis, Sporobolus virginicus, Ficiona nodosa and Schoeloplectus sp. as well as a Mangrove and Pine tree species, Avecinia and Casuarina sp respectively. High Spatial Resolution Worldview-2 data and Coarse Spatial resolution Landsat 8 imagery were selected in this study. Among the selected vegetation types some patches ware fragmented and close to the spatial resolution of Worldview-2 data while and some patch were larger than the 30 meter resolution of Landsat 8 data. This study aims to test the effectiveness of different classifier for the imagery with various spatial and spectral resolutions. Three different classification algorithm, Maximum Likelihood Classifier (MLC), Support Vector Machine (SVM) and Artificial Neural Network (ANN) were tested and compared with their mapping accuracy of the results derived from both satellite imagery. For Worldview-2 data SVM was giving the higher overall accuracy (92.12%, kappa =0.90) followed by ANN (90.82%, Kappa 0.89) and MLC (90.55%, kappa = 0.88). For Landsat 8 data, MLC (82.04%) showed the highest classification accuracy comparing to SVM (77.31%) and ANN (75.23%). The producer accuracy of the classification results were also presented in the paper.

  12. Mapping Deciduous Rubber Plantation Areas and Stand Ages with PALSAR and Landsat Images

    Directory of Open Access Journals (Sweden)

    Weili Kou


    Full Text Available Accurate and updated finer resolution maps of rubber plantations and stand ages are needed to understand and assess the impacts of rubber plantations on regional ecosystem processes. This study presented a simple method for mapping rubber plantation areas and their stand ages by integration of PALSAR 50-m mosaic images and multi-temporal Landsat TM/ETM+ images. The L-band PALSAR 50-m mosaic images were used to map forests (including both natural forests and rubber trees and non-forests. For those PALSAR-based forest pixels, we analyzed the multi-temporal Landsat TM/ETM+ images from 2000 to 2009. We first studied phenological signatures of deciduous rubber plantations (defoliation and foliation and natural forests through analysis of surface reflectance, Normal Difference Vegetation Index (NDVI, Enhanced Vegetation Index (EVI, and Land Surface Water Index (LSWI and generated a map of rubber plantations in 2009. We then analyzed phenological signatures of rubber plantations with different stand ages and generated a map, in 2009, of rubber plantation stand ages (≤5, 6–10, >10 years-old based on multi-temporal Landsat images. The resultant maps clearly illustrated how rubber plantations have expanded into the mountains in the study area over the years. The results in this study demonstrate the potential of integrating microwave (e.g., PALSAR and optical remote sensing in the characterization of rubber plantations and their expansion over time.

  13. Call-to-balloon time dashboard in patients with ST-segment elevation myocardial infarction results in significant improvement in the logistic chain. (United States)

    Hermans, Maaike P J; Velders, Matthijs A; Smeekes, Martin; Drexhage, Olivier S; Hautvast, Raymond W M; Ytsma, Timon; Schalij, Martin J; Umans, Victor A W M


    Timely reperfusion with primary percutaneous coronary intervention (pPCI) in ST-segment elevation myocardial infarction (STEMI) patients is associated with superior clinical outcomes. Aiming to reduce ischaemic time, an innovative system for home-to-hospital (H2H) time monitoring was implemented, which enabled real-time evaluation of ischaemic time intervals, regular feedback and improvements in the logistic chain. The objective of this study was to assess the results after implementation of the H2H dashboard for monitoring and evaluation of ischaemic time in STEMI patients. Ischaemic time in STEMI patients transported by emergency medical services (EMS) and treated with pPCI in the Noordwest Ziekenhuis, Alkmaar before (2008-2009; n=495) and after the implementation of the H2H dashboard (2011-2014; n=441) was compared. Median time intervals were significantly shorter in the H2H group (door-to-balloon time 32 [IQR 25-43] vs. 40 [IQR 28-55] minutes, p-value dashboard was independently associated with shorter time delays. Real-time monitoring and feedback on time delay with the H2H dashboard improves the logistic chain in STEMI patients, resulting in shorter ischaemic time intervals.

  14. Medico-economic evaluation of healthcare products. Methodology for defining a significant impact on French health insurance costs and selection of benchmarks for interpreting results. (United States)

    Dervaux, Benoît; Baseilhac, Eric; Fagon, Jean-Yves; Biot, Claire; Blachier, Corinne; Braun, Eric; Debroucker, Frédérique; Detournay, Bruno; Ferretti, Carine; Granger, Muriel; Jouan-Flahault, Chrystel; Lussier, Marie-Dominique; Meyer, Arlette; Muller, Sophie; Pigeon, Martine; De Sahb, Rima; Sannié, Thomas; Sapède, Claudine; Vray, Muriel


    Decree No. 2012-1116 of 2 October 2012 on medico-economic assignments of the French National Authority for Health (Haute autorité de santé, HAS) significantly alters the conditions for accessing the health products market in France. This paper presents a theoretical framework for interpreting the results of the economic evaluation of health technologies and summarises the facts available in France for developing benchmarks that will be used to interpret incremental cost-effectiveness ratios. This literature review shows that it is difficult to determine a threshold value but it is also difficult to interpret then incremental cost effectiveness ratio (ICER) results without a threshold value. In this context, round table participants favour a pragmatic approach based on "benchmarks" as opposed to a threshold value, based on an interpretative and normative perspective, i.e. benchmarks that can change over time based on feedback. © 2014 Société Française de Pharmacologie et de Thérapeutique.

  15. Surgical results in patients with unruptured asymptomatic cerebral aneurysms. Significance of evaluation of neuropsychological function, magnetic resonance images and cerebral blood flow

    International Nuclear Information System (INIS)

    Kumon, Yoshiaki; Watanabe, Hideaki; Igase, Keiji; Nagato, Shigeyuki; Fukumoto, Shinya; Iwata, Shinji; Ohue, Shiro; Ohnishi, Takanori


    We evaluated neuropsychological function, magnetic resonance (MR) images and cerebral blood flow (CBF) in patients with unruptured asymptomatic cerebral aneurysms. Among consecutive operations (n=73) on 70 patients since 2000, direct surgery was performed in 53 operations on 50 patients, and intravascular surgery was performed in 20 operations on 20 patients. Surgical results of direct surgery were studied. Direct surgery was selected mainly for patients with small and anterior circulation aneurysms. MR imaging was conducted 1 week after surgery, and Wechsler Adult Intelligence Scale-Revised (WAIS-R) examination and CBF measurement using 133 Xe-SPECT were done before and 1 month after surgery. Abnormal neurological findings were recognized postoperatively in 26% of surgeries. Among them, visual disturbance was permanent in 4% of surgeries, all of which were surgeries for paraclinoid internal carotid artery aneurysms. WAIS-R results deteriorated in 26% of surgeries at 1 month and at least in 5% of surgeries at 1 year after surgery. MR images at 1 week after surgery revealed brain damage in 30% of surgeries and subdural fluid collection in 19% of surgeries. Patients with large brain damage or thick subdural fluid collection frequently showed neurological deficits and/or WAISR deterioration. These complications were recognized frequently in patients with ACoA aneurysms. Resting CBF decreased significantly in the area supplied by the anterior cerebral artery and anterior border zone on the operated side postoperatively. The brain damage and subdural fluid collection were observed frequently and caused neurological deficits and neuropsychological dysfunction, although these were usually transient. It may be necessary to evaluate neuropsychological function, MRI and CBF in patients with unruptured asymptomatic cerebral aneurysms to improve surgical results. (author)

  16. Improving artificial forest biomass estimates using afforestation age information from time series Landsat stacks. (United States)

    Liu, Liangyun; Peng, Dailiang; Wang, Zhihui; Hu, Yong


    China maintains the largest artificial forest area in the world. Studying the dynamic variation of forest biomass and carbon stock is important to the sustainable use of forest resources and understanding of the artificial forest carbon budget in China. In this study, we investigated the potential of Landsat time series stacks for aboveground biomass (AGB) estimation in Yulin District, a key region of the Three-North Shelter region of China. Firstly, the afforestation age was successfully retrieved from the Landsat time series stacks in the last 40 years (from 1974 to 2013) and shown to be consistent with the surveyed tree ages, with a root-mean-square error (RMSE) value of 4.32 years and a determination coefficient (R (2)) of 0.824. Then, the AGB regression models were successfully developed by integrating vegetation indices and tree age. The simple ratio vegetation index (SR) is the best candidate of the commonly used vegetation indices for estimating forest AGB, and the forest AGB model was significantly improved using the combination of SR and tree age, with R (2) values from 0.50 to 0.727. Finally, the forest AGB images were mapped at eight epochs from 1985 to 2013 using SR and afforestation age. The total forest AGB in seven counties of Yulin District increased by 20.8 G kg, from 5.8 G kg in 1986 to 26.6 G kg in 2013, a total increase of 360 %. For the persistent forest area since 1974, the forest AGB density increased from 15.72 t/ha in 1986 to 44.53 t/ha in 2013, with an annual rate of about 0.98 t/ha. For the artificial forest planted after 1974, the AGB density increased about 1.03 t/ha a year from 1974 to 2013. The results present a noticeable carbon increment for the planted artificial forest in Yulin District over the last four decades.

  17. Significant Variation of Post-critical SsPmp Amplitude as a Result of Variation in Near-surface Velocity: Observations from the Yellowknife Array (United States)

    Ferragut, G.; Liu, T.; Klemperer, S. L.


    In recent years Virtual Deep Seismic Sounding (VDSS) emerged as a novel method to image the Moho, which uses the post-critical reflection P waves at the Moho generated by teleseismic S waves at the free surface near the receivers (SsPmp). However, observed SsPmp sometimes have significantly lower amplitude than predicted, raising doubts among the seismic community on the theoretical basis of the method. With over two decades of continuous digital broadband records and major subduction zones in the range of 30-50 degrees, the Yellowknife Array in northern Canada provides a rich opportunity for observation of post-critical SsPmp. We analyze S wave coda of events with epicenter distances of 30-50°, and pay special attention to earthquakes in a narrow azimuth range that ­­­encompasses the Kamchatka Peninsula. Among 21 events with strong direct S energy on the radial components, we observe significant variation of SsPmp energy. After associating the SsPmp energy with the virtual source location of each event, we observe a general trend of decreasing SsPmp energy from NE to SW. As the trend coincides with the transition from exposed basement of the Slave Craton to Paleozoic platform covered by Phanerozoic sediment, we interpret the decreasing SsPmp energy as a result of lower S velocity at the virtual sources, which reduces S-to-P reflection coefficients. We plan to include more events from the Aleutian Islands, the virtual sources of which are primarily located in the Paleozoic platform. This will allow us to further investigate the relationship between SsPmp amplitude and near-surface velocity.

  18. LBA-ECO LC-24 Landsat TM and ETM+ Land Cover, Southern Para, Brazil: 1984-2003 (United States)

    National Aeronautics and Space Administration — ABSTRACT: This data set is a five-class land cover for Southern Para for the years 1984 (Landsat MSS), 1988 (Landsat TM), 1996, and 2003 (Landsat ETM+). The final...

  19. LBA-ECO LC-24 Landsat TM and ETM+ Land Cover, Southern Para, Brazil: 1984-2003 (United States)

    National Aeronautics and Space Administration — This data set is a five-class land cover for Southern Para for the years 1984 (Landsat MSS), 1988 (Landsat TM), 1996, and 2003 (Landsat ETM+). The final...

  20. Landsat Data Continuity Mission - Launch Fever (United States)

    Irons, James R.; Loveland, Thomas R.; Markham, Brian L.; Masek, Jeffrey G.; Cook, Bruce; Dwyer, John L.


    The year 2013 will be an exciting period for those that study the Earth land surface from space, particularly those that observe and characterize land cover, land use, and the change of cover and use over time. Two new satellite observatories will be launched next year that will enhance capabilities for observing the global land surface. The United States plans to launch the Landsat Data Continuity Mission (LDCM) in January. That event will be followed later in the year by the European Space Agency (ESA) launch of the first Sentinel 2 satellite. Considered together, the two satellites will increase the frequency of opportunities for viewing the land surface at a scale where human impact and influence can be differentiated from natural change. Data from the two satellites will provide images for similar spectral bands and for comparable spatial resolutions with rigorous attention to calibration that will facilitate cross comparisons. This presentation will provide an overview of the LDCM satellite system and report its readiness for the January launch.

  1. Landsat Science: 40 Years of Innovation and Opportunity (United States)

    Cook, Bruce D.; Irons, James R.; Masek, Jeffrey G.; Loveland, Thomas R.


    Landsat satellites have provided unparalleled Earth-observing data for nearly 40 years, allowing scientists to describe, monitor and model the global environment during a period of time that has seen dramatic changes in population growth, land use, and climate. The success of the Landsat program can be attributed to well-designed instrument specifications, astute engineering, comprehensive global acquisition and calibration strategies, and innovative scientists who have developed analytical techniques and applications to address a wide range of needs at local to global scales (e.g., crop production, water resource management, human health and environmental quality, urbanization, deforestation and biodiversity). Early Landsat contributions included inventories of natural resources and land cover classification maps, which were initially prepared by a visual interpretation of Landsat imagery. Over time, advances in computer technology facilitated the development of sophisticated image processing algorithms and complex ecosystem modeling, enabling scientists to create accurate, reproducible, and more realistic simulations of biogeochemical processes (e.g., plant production and ecosystem dynamics). Today, the Landsat data archive is freely available for download through the USGS, creating new opportunities for scientists to generate global image datasets, develop new change detection algorithms, and provide products in support of operational programs such as Reducing Emissions from Deforestation and Forest Degradation in Developing Countries (REDD). In particular, the use of dense (approximately annual) time series to characterize both rapid and progressive landscape change has yielded new insights into how the land environment is responding to anthropogenic and natural pressures. The launch of the Landsat Data Continuity Mission (LDCM) satellite in 2012 will continue to propel innovative Landsat science.

  2. Identification of Water Bodies in a Landsat 8 OLI Image Using a J48 Decision Tree. (United States)

    Acharya, Tri Dev; Lee, Dong Ha; Yang, In Tae; Lee, Jae Kang


    Water bodies are essential to humans and other forms of life. Identification of water bodies can be useful in various ways, including estimation of water availability, demarcation of flooded regions, change detection, and so on. In past decades, Landsat satellite sensors have been used for land use classification and water body identification. Due to the introduction of a New Operational Land Imager (OLI) sensor on Landsat 8 with a high spectral resolution and improved signal-to-noise ratio, the quality of imagery sensed by Landsat 8 has improved, enabling better characterization of land cover and increased data size. Therefore, it is necessary to explore the most appropriate and practical water identification methods that take advantage of the improved image quality and use the fewest inputs based on the original OLI bands. The objective of the study is to explore the potential of a J48 decision tree (JDT) in identifying water bodies using reflectance bands from Landsat 8 OLI imagery. J48 is an open-source decision tree. The test site for the study is in the Northern Han River Basin, which is located in Gangwon province, Korea. Training data with individual bands were used to develop the JDT model and later applied to the whole study area. The performance of the model was statistically analysed using the kappa statistic and area under the curve (AUC). The results were compared with five other known water identification methods using a confusion matrix and related statistics. Almost all the methods showed high accuracy, and the JDT was successfully applied to the OLI image using only four bands, where the new additional deep blue band of OLI was found to have the third highest information gain. Thus, the JDT can be a good method for water body identification based on images with improved resolution and increased size.

  3. Using Landsat Spectral Indices in Time-Series to Assess Wildfire Disturbance and Recovery

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    Samuel Hislop


    Full Text Available Satellite earth observation is being increasingly used to monitor forests across the world. Freely available Landsat data stretching back four decades, coupled with advances in computer processing capabilities, has enabled new time-series techniques for analyzing forest change. Typically, these methods track individual pixel values over time, through the use of various spectral indices. This study examines the utility of eight spectral indices for characterizing fire disturbance and recovery in sclerophyll forests, in order to determine their relative merits in the context of Landsat time-series. Although existing research into Landsat indices is comprehensive, this study presents a new approach, by comparing the distributions of pre and post-fire pixels using Glass’s delta, for evaluating indices without the need of detailed field information. Our results show that in the sclerophyll forests of southeast Australia, common indices, such as the Normalized Difference Vegetation Index (NDVI and the Normalized Burn Ratio (NBR, both accurately capture wildfire disturbance in a pixel-based time-series approach, especially if images from soon after the disturbance are available. However, for tracking forest regrowth and recovery, indices, such as NDVI, which typically capture chlorophyll concentration or canopy ‘greenness’, are not as reliable, with values returning to pre-fire levels in 3–5 years. In comparison, indices that are more sensitive to forest moisture and structure, such as NBR, indicate much longer (8–10 years recovery timeframes. This finding is consistent with studies that were conducted in other forest types. We also demonstrate that additional information regarding forest condition, particularly in relation to recovery, can be extracted from less well known indices, such as NBR2, as well as textural indices incorporating spatial variance. With Landsat time-series gaining in popularity in recent years, it is critical to

  4. Monitoring of urban growth in the state of Hidalgo using Landsat images

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    Laura Cano Salinas


    Given this background, this paper is focused on the generation of geographic information for regional urban planning and the overall aim is to examine urban growth rate during the period 2000-2014 in the state of Hidalgo, Mexico and identify potential areas of expansion from Landsat images. The methodology was based on techniques of remote sensing and Geographical Information System (GIS. The inputs used were six Landsat scenes: three for 2000 year and three for 2014. Image processing was performed on ERDAS Imagine® 9.1 and the spatial analysis of urban coverage statewide on ArcGIS 10.0 by ESRI®. First, the radiometric correction was made and we obtained the urban polygons of the 2000 year through of supervised classification. The 2014 urban layer was digitized manually due to the spectral incompatibility between the bands of the Landsat sensor 5 and 7, and the Landsat sensor 8. Then, we build a road density map and the spatial relationship of the urban centers with the road influence area was evaluated. For the year 2000, 103 urban polygons were mapped, whilst for 2014 were identified ten polygons more with a mapped minimum area of 24 ha. The main results indicated that in the state has increased 72.3 km2 urban area from 2000 to 2014. This represents an average growth rate of 1.8% per year. The most widespread municipalities are located in the region of Valle del Mezquital, however, Mineral de la Reforma, Tetepango, Tizayuca and Pachuca showed growth rates of 183.44%, 102% 94% and 68.5% in fourteen years, respectively. According to the road map density, these municipalities are located in areas of greatest influence of infrastructure as the Arco Norte highway in the state. The above findings, lead us to conclude that the Mezquital Valley and the Basin of Mexico are potential areas of urban spreading and it is associated with road development in the Central Mexico.

  5. A prototype for automation of land-cover products from Landsat Surface Reflectance Data Records (United States)

    Rover, J.; Goldhaber, M. B.; Steinwand, D.; Nelson, K.; Coan, M.; Wylie, B. K.; Dahal, D.; Wika, S.; Quenzer, R.


    Landsat data records of surface reflectance provide a three-decade history of land surface processes. Due to the vast number of these archived records, development of innovative approaches for automated data mining and information retrieval were necessary. Recently, we created a prototype utilizing open source software libraries for automatically generating annual Anderson Level 1 land cover maps and information products from data acquired by the Landsat Mission for the years 1984 to 2013. The automated prototype was applied to two target areas in northwestern and east-central North Dakota, USA. The approach required the National Land Cover Database (NLCD) and two user-input target acquisition year-days. The Landsat archive was mined for scenes acquired within a 100-day window surrounding these target dates, and then cloud-free pixels where chosen closest to the specified target acquisition dates. The selected pixels were then composited before completing an unsupervised classification using the NLCD. Pixels unchanged in pairs of the NLCD were used for training decision tree models in an iterative process refined with model confidence measures. The decision tree models were applied to the Landsat composites to generate a yearly land cover map and related information products. Results for the target areas captured changes associated with the recent expansion of oil shale production and agriculture driven by economics and policy, such as the increase in biofuel production and reduction in Conservation Reserve Program. Changes in agriculture, grasslands, and surface water reflect the local hydrological conditions that occurred during the 29-year span. Future enhancements considered for this prototype include a web-based client, ancillary spatial datasets, trends and clustering algorithms, and the forecasting of future land cover.

  6. a Preliminary Investigation on Comparison and Transformation of SENTINEL-2 MSI and Landsat 8 Oli (United States)

    Chen, F.; Lou, S.; Fan, Q.; Li, J.; Wang, C.; Claverie, M.


    A PRELIMINARY INVESTIGATION ON COMPARISON AND TRANSFORMATION OF SENTINEL-2 MSI AND LANDSAT 8 OLI Timely and accurate earth observation with short revisit interval is usually necessary, especially for emergency response. Currently, several new generation sensors provided with similar channel characteristics have been operated onboard different satellite platforms, including Sentinel-2 and Landsat 8. Joint use of the observations by different sensors offers an opportunity to meet the demands for emergency requirements. For example, through the combination of Landsat and Sentinel-2 data, the land can be observed every 2-3 days at medium spatial resolution. However, differences are expected in radiometric values (e.g., channel reflectance) of the corresponding channels between two sensors. Spectral response function (SRF) is taken as an important aspect of sensor settings. Accordingly, between-sensor differences due to SRFs variation need to be quantified and compensated. The comparison of SRFs shows difference (more or less) in channel settings between Sentinel-2 Multi-Spectral Instrument (MSI) and Landsat 8 Operational Land Imager (OLI). Effect of the difference in SRF on corresponding values between MSI and OLI was investigated, mainly in terms of channel reflectance and several derived spectral indices. Spectra samples from ASTER Spectral Library Version 2.0 and Hyperion data archives were used in obtaining channel reflectance simulation of MSI and OLI. Preliminary results show that MSI and OLI are well comparable in several channels with small relative discrepancy (model is not ensured when the target belongs to another spectra collection. If an improper transformation model is selected, the between-sensor discrepancy will even largely increase. In conclusion, improvement in between-sensor consistency is possibly a challenge, through linear transformation based on model(s) generated from other spectra collections.

  7. Landsat and Local Land Surface Temperatures in a Heterogeneous Terrain Compared to MODIS Values

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    Gemma Simó


    Full Text Available Land Surface Temperature (LST as provided by remote sensing onboard satellites is a key parameter for a number of applications in Earth System studies, such as numerical modelling or regional estimation of surface energy and water fluxes. In the case of Moderate Resolution Imaging Spectroradiometer (MODIS onboard Terra or Aqua, pixels have resolutions near 1 km 2 , LST values being an average of the real subpixel variability of LST, which can be significant for heterogeneous terrain. Here, we use Landsat 7 LST decametre-scale fields to evaluate the temporal and spatial variability at the kilometre scale and compare the resulting average values to those provided by MODIS for the same observation time, for the very heterogeneous Campus of the University of the Balearic Islands (Mallorca, Western Mediterranean, with an area of about 1 km 2 , for a period between 2014 and 2016. Variations of LST between 10 and 20 K are often found at the sub-kilometre scale. In addition, MODIS values are compared to the ground truth for one point in the Campus, as obtained from a four-component net radiometer, and a bias of 3.2 K was found in addition to a Root Mean Square Error (RMSE of 4.2 K. An indication of a more elaborated local measurement strategy in the Campus is given, using an array of radiometers distributed in the area.


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    F. Huang


    Full Text Available Based on the information from integrated Landsat TM/ETM images and geographic information systems (GIS, using dynamic model, landscape indices and temporal trajectory analysis, spatio-temporal changes in forest in the northern area of Changbai Mountains were investigated in the past 20 years. The results showed that the forests decreased by 141461 ha at the annual decrease rate of 0.19% from 1986 to 2006. The numbers of forest patch increased, while the patch size of forest land declined. Forestland experienced the process of substantial fragmentation. Close forest showed a net reduction of 13.3×104ha. The typical trajectories of forest changes included forestland-forestland-cropland, forestland-cropland-cropland, forestland-forestland-grassland and forestland-cropland-built-up land. The total area of human-induced change is 1.7 times than that of natural change in the study area. Population, cropland area and gross domestic product increased significantly as forests decreased.

  9. results

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    Salabura Piotr


    Full Text Available HADES experiment at GSI is the only high precision experiment probing nuclear matter in the beam energy range of a few AGeV. Pion, proton and ion beams are used to study rare dielectron and strangeness probes to diagnose properties of strongly interacting matter in this energy regime. Selected results from p + A and A + A collisions are presented and discussed.

  10. Landsat analysis of the Yangjiatan tungsten district, Hunan Province, People's Republic of China (United States)

    Carter, W.D.; Kiilsgaard, T.H.


    The Yangjiatan tungsten district at latitude 27??28??? N. and longitude 111??54???E. is located about 140 km southwest of the city of Changsha and 35 km northeast of the town of Shaoyang, southeast Hunan Province, People's Republic of China. The deposits, consisting largely of scheelite in veins (Wang, 1975), are contained in highly folded and faulted sedimentary rocks of Paleozoic, Mesozoic, and Cenozoic age intruded by granitic plutons that are circular in plan view. The major faults and folds trend in a northeasterly direction; whereas, the plutons are clustered in a more easterly trending band across the Landsat image. Landsat image E-2338-02202, acquired December 26, 1975, is number 470 in the "Landsat Image Atlas of the People's Republic of China" printed by the Publishing House of Geology in 1979. A computer-compatible tape of the image was analyzed and used as a demonstration project under a United Nations technical assistance program. Supervised classification of soils, rocks, and vegetation; band ratioing to detect limonite alteration; and edge enhancement were all conducted to demonstrate the flexibility and capability of interactive computer systems. Field evaluation of the results of this work will be conducted by colleagues of the Remote Sensing Center for Geology, Ministry of Geology, in China. ?? 1983.

  11. Investigating Land Surface Temperature Changes Using Landsat Data in Konya, Turkey

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    O. Orhan


    Full Text Available The main purpose of this paper is to investigate multi-temporal land surface temperature (LST and Normalized Difference Vegetation Index (NDVI changes of Konya in Turkey using remotely sensed data. Konya is located in the semi-arid central Anatolian region of Turkey and hosts many important wetland sites including Salt Lake. Six images taken by Landsat-5 TM and Landsat 8- OLI satellites were used as the basic data source. These raw images were taken in 1984, 2011 and 2014 intended as long-term and short-term. Firstly, those raw images was corrected radiometric and geometrically within the scope of project. Three mosaic images were obtained by using the full-frame images of Landsat-5 TM / 8- OLI which had been already transformed comparison each other. Then, Land Surface Temperature (LST, Normalized Difference Vegetation Index (NDVI maps have been produced to determine the dimension of the drought. The obtained results showed that surface temperature rates in the basin increased about 5°C between 1984 and 2014 as long periods, increased about 2-3°C between 2011and 2014 as short periods. Meteorological data supports the increase in temperature.

  12. Remote Sensing of Residue Management in Farms using Landsat 8 Sensor Imagery

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    M. A Rostami


    study were NDVI, BAI, NBR and NBRT. Classification accuracy was evaluated and expressed by confusion matrix and Kappa coefficient. Natural surfaces are rarely composed of a single uniform material. Spectral mixing occurs when materials with different spectral properties are represented by a single image pixel. The condition where scale of the mixing is large (macroscopic, mixing would occur in a linear fashion. However for microscopic situations, the mixing is generally nonlinear. The linear model ahich wasadopted in this study, assumes that there is no interaction between materials. Assumption of LSUA is that each pixel on the surface is a physical mixture of several constituents weighted by surface abundance, and the spectrum of the mixture is a linear combination of the endmember reflectance spectra. Within the context of this study, LSUA is a classification method that can determine contribution of each material (or endmember such as soil or residue for each image pixel. Results and Discussion The spectral response curve extracted from Landsat 8 image used as input into the LSUA model in ENVI software. As expected, crop burned residue (Ash spectra had lower reflectance when compared to the soil, residue and green plant spectra. The contrast between residue, green plant, soil and residue ash spectra was particularly evident in the NIR and SWIR bands. It is suggested that these bands are essential for residue discrimination. Differences of reflectance in the visible bands were minimal, providing little discrimination between residue, green plant, soil and residue ash. Burned area estimated by LSUA method from Landsat 8 image was correlated against the ground data (measured coincident to the ground data. The overall accuracy of classification with BAI index and LSUA method was 91.7 and 88.3 and Kappa coefficient was 0.89 and 0.84 respectively. Results indicated that burned field area can be located and its area can be estimated using Landsat 8 images. The Index BAI was

  13. What Can We Learn About Glaciers and Ice Sheets From 30 Years of Landsat Imagery? (United States)

    Gardner, A. S.; Scambos, T.; Fahnestock, M. A.; Moholdt, G.; Nilsson, J.


    Glacier and ice sheets are known to be rapidly changing and currently account for two thirds of observed sea level rise. Attributing the causes of the rapid decline in land ice requires separation of mass change processes, i.e. accumulation of precipitation, meltwater runoff, and solid ice discharge. Here we examine a 30 year record of Landsat imagery to determine trends in glacier velocity at a global scale in an attempt to identify anomalies in glacier flow that are contributing to changes in land ice mass. The Landsat archive represents a treasure trove of information with hundreds of thousands of images acquired over glaciers and ice sheets during the past 30 years. Gleaning useful and consistent surface displacement information from a multiple sensor archive that is heavily contaminated by cloud, saturated images, poorly resolved sensor geometry, and data gaps has proved challenging. Temporal stacking of displacement fields (Dehecq et al., 2015) and correcting for unresolved topography (Roseanau et al., 2012) have been shown to greatly improve derived velocities. Here we present results from a global processing of the complete Landsat archive for information on glacier surface displacements. We highlight patterns of coherent regional change as well as well as rapid basin-scale changes in glacier flow.

  14. The (InSignificance of Socio-Demographic Factors as Possible Determinants of Vietnamese Social Scientists’ Contribution-Adjusted Productivity: Preliminary Results from 2008–2017 Scopus Data

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    Thu-Trang Vuong


    Full Text Available As collaboration has become widespread in academia, and the number of authors per article has increased, the publication count is no longer an accurate indicator of scientific output in many cases. To overcome this limitation, this study defined and computed a relative count of publications called ‘CP’ (credit-based contribution points, based on the sequence-determines-credit (SDC method, which takes into account the level of contribution of each author. Analyses were done on a sample of 410 Vietnamese social scientists whose publications were indexed in the Scopus database during 2008–2017. The results showed that the average CP of Vietnamese researchers in the field of social sciences and humanities is very low: more than 88% of authors have a CP less than five over a span 10 years. Researchers with a higher CP were mostly 40–50 years old; however, even for this sub-group, the mean CP was only 3.07. Multiple attributes of first-authorship—including knowledge, research skills, and critical thinking—could boost the CP by a ratio of 1:1.06. There is no evidence of gender differences in productivity, however, there is a regional difference. These findings offer significant insights into the education system in regard to science and technology, namely policy implications for science funding and management strategies for research funds.

  15. Analysis of Thermal Structure of Arctic Lakes at Local and Regional Scales Using in Situ and Multidate Landsat-8 Data (United States)

    Huang, Yan; Liu, Hongxing; Hinkel, Kenneth; Yu, Bailang; Beck, Richard; Wu, Jianping


    The Arctic coastal plain is covered with numerous thermokarst lakes. These lakes are closely linked to climate and environmental change through their heat and water budgets. We examined the intralake thermal structure at the local scale and investigated the water temperature pattern of lakes at the regional scale by utilizing extensive in situ measurements and multidate Landsat-8 remote sensing data. Our analysis indicates that the lake skin temperatures derived from satellite thermal sensors during most of the ice-free summer period effectively represent the lake bulk temperature because the lakes are typically well-mixed and without significant vertical stratification. With the relatively high-resolution Landsat-8 thermal data, we were able to quantitatively examine intralake lateral temperature differences and gradients in relation to geographical location, topography, meteorological factors, and lake morphometry for the first time. Our results suggest that wind speed and direction not only control the vertical stratification but also influences lateral differences and gradients of lake surface temperature. Wind can considerably reduce the intralake temperature gradient. Interestingly, we found that geographical location (latitude, longitude, distance to the ocean) and lake morphometry (surface size, depth, volume) not only control lake temperature regionally but also affect the lateral temperature gradient and homogeneity level within each individual lake. For the Arctic coastal plain, at regional scales, inland and southern lakes tend to have larger horizontal temperature differences and gradients compared to coastal and northern lakes. At local scales, large and shallow lakes tend to have large lateral temperature differences relative to small and deep lakes.

  16. The Potential of Using Landsat 7 Data for the Classification of Sea Ice Surface Conditions During Summer (United States)

    Markus, Thorsten; Cavalieri, Donald J.; Ivanoff, Alvaro; Koblinsky, Chester J. (Technical Monitor)


    During spring and summer, the Surface of the Arctic sea ice cover undergoes rapid changes that greatly affect the surface albedo and significantly impact the further decay of the sea ice. These changes are primarily the development of a wet snow cover and the development of melt ponds. As melt pond diameters generally do not exceed a couple of meters, the spatial resolutions of sensors like AVHRR and MODIS are too coarse for their identification. Landsat 7, on the other hand, has a spatial resolution of 30 m (15 m for the pan-chromatic band). The different wavelengths (bands) from blue to near-infrared offer the potential to distinguish among different surface conditions. Landsat 7 data for the Baffin Bay region for June 2000 have been analyzed. The analysis shows that different surface conditions, such as wet snow and meltponded areas, have different signatures in the individual Landsat bands. Consistent with in-situ albedo measurements, melt ponds show up as blueish whereas dry and wet ice have a white to gray appearance in the Landsat true-color image. These spectral differences enable the distinction of melt ponds. The melt pond fraction for the scene studied in this paper was 37%.

  17. Bridging the Divide: Translating Landsat Research Into Usable Science (United States)

    Rocchio, L. E.; Davis, A. L.


    Science has long served humankind. Breakthroughs in medicine have increased longevity and advances in technology have made modern-day conveniences possible. Yet, social benefits begotten by the environmental sciences, although critical for the survival of humanity, have not always been as widely recognized or used. To benefit today's rapidly growing population, the divides between environmental research, applied environmental science, and use of this information by decision makers must be bridged. Lessons about the translation from research to usable science can be learned from the four decades of Landsat history, and these lessons can serve as useful models for bridging the gaps between new technology, scientific research, and the use of that research and technology in real-world problem solving. In 1965, William Pecora, then-director of the U.S. Geological Survey, proposed the idea of a remote sensing satellite program to gather facts about natural resources of Earth. For the next seven years, an intense campaign showing the depth and diversity of satellite imagery applications was waged. This led to the 1972 launch of the first civilian land-observing satellite, Landsat 1. By 1975, successful application research based on Landsat 1 imagery prompted then-NASA Administrator Dr. James Fletcher to proclaim that if one space age development would save the world, it would be Landsat and its successor satellites. Thirty-four years of continual Landsat imaging and related-research has lead to the implementation of many socially beneficial applications, such as improved water management techniques, crop insurance fraud reduction, illicit crop inventories, natural disaster relief planning, continent-scale carbon estimates, and extensive cartographic advances. Despite these successes, the challenge of translating Landsat research into realized social benefits remains. Even in this geospatially-savvy era, the utility of Landsat largely escapes policymakers. Here, in an

  18. Stable and accurate methods for identification of water bodies from Landsat series imagery using meta-heuristic algorithms (United States)

    Gamshadzaei, Mohammad Hossein; Rahimzadegan, Majid


    Identification of water extents in Landsat images is challenging due to surfaces with similar reflectance to water extents. The objective of this study is to provide stable and accurate methods for identifying water extents in Landsat images based on meta-heuristic algorithms. Then, seven Landsat images were selected from various environmental regions in Iran. Training of the algorithms was performed using 40 water pixels and 40 nonwater pixels in operational land imager images of Chitgar Lake (one of the study regions). Moreover, high-resolution images from Google Earth were digitized to evaluate the results. Two approaches were considered: index-based and artificial intelligence (AI) algorithms. In the first approach, nine common water spectral indices were investigated. AI algorithms were utilized to acquire coefficients of optimal band combinations to extract water extents. Among the AI algorithms, the artificial neural network algorithm and also the ant colony optimization, genetic algorithm, and particle swarm optimization (PSO) meta-heuristic algorithms were implemented. Index-based methods represented different performances in various regions. Among AI methods, PSO had the best performance with average overall accuracy and kappa coefficient of 93% and 98%, respectively. The results indicated the applicability of acquired band combinations to extract accurately and stably water extents in Landsat imagery.

  19. Application of spectrometer cropscan MSR 16R and Landsat imagery for identification the spectral characteristics of land cover (United States)

    Tampubolon, Togi; Abdullah, Khiruddin bin; San, Lim Hwee


    The spectral characteristics of land cover are basic references in classifying satellite image for geophysics analysis. It can be obtained from the measurements using spectrometer and satellite image processing. The aims of this study to investigate the spectral characteristics of land cover based on the results of measurement using Spectrometer Cropscan MSR 16R and Landsat satellite imagery. The area of study in this research is in Medan, (Deli Serdang, North Sumatera) Indonesia. The scope of this study is the basic survey from the measurements of spectral land cover which is covered several type of land such as a cultivated and managed terrestrial areas, natural and semi-natural, cultivated aquatic or regularly flooded areas, natural and semi-natural aquatic, artificial surfaces and associated areas, bare areas, artificial waterbodies and natural waterbodies. The measurement and verification were conducted using a spectrometer provided their spectral characteristics and Landsat imagery, respectively. The results of the spectral characteristics of land cover shows that each type of land cover have a unique characteristic. The correlation of spectral land cover based on spectrometer Cropscan MSR 16R and Landsat satellite image are above 90 %. However, the land cover of artificial waterbodiese have a correlation under 40 %. That is because the measurement of spectrometer Cropscan MSR 16R and acquisition of Landsat satellite imagery has a time different.

  20. Functional significance of a novel 7-factor model of DSM-5 PTSD symptoms: results from the National Health and Resilience in Veterans study. (United States)

    Pietrzak, Robert H; Tsai, Jack; Armour, Cherie; Mota, Natalie; Harpaz-Rotem, Ilan; Southwick, Steven M


    While posttraumatic stress disorder (PTSD) symptoms in the recently published Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) are clustered into four factors, emerging confirmatory factor analytic studies suggest that this disorder is best characterized by seven symptom clusters, including re-experiencing, avoidance, negative affect, anhedonia, externalizing behaviors, and anxious and dysphoric arousal symptoms. To date, however, data are lacking regarding the relation between this novel model of DSM-5 PTSD symptoms and measures of clinical significance in this population (e.g., functioning). Using data from the National Health and Resilience in Veterans Study (NHRVS), a contemporary, nationally representative sample of 1484 U.S. veterans, we evaluated clinical and functional correlates of a novel 7-factor model of DSM-5 PTSD symptoms. Differential patterns of associations were observed between DSM-5 PTSD symptom clusters, and psychiatric comorbidities, suicidal ideation, hostility, and functioning and quality of life. Anhedonia symptoms, in particular, were strongly related to current depression, as well as reduced mental functioning and quality of life. Externalizing behaviors were most strongly related to hostility, supporting the convergent validity of this construct. Cross-sectional design and employment of self-report measures. These results suggest that a more refined 7-factor model of DSM-5 PTSD symptoms may provide greater specificity in understanding associations with comorbid psychopathology, suicidal ideation, and functioning and quality of life in U.S. veterans. They further suggest that prevention and treatment efforts that target distinct aspects of the PTSD phenotype may be more effective in mitigating key clinical and functional outcomes in this population. Published by Elsevier B.V.

  1. Landsat Thematic Mapper digital information content for agricultural environments (United States)

    Haack, Barry; Bryant, Nevin; Adams, Steven


    Landsat Thematic Mapper (TM) data collected for Imperial Valley, California in December, 1982 were digitally examined to assess their utility to distinguish among agricultural and other land-covers. Statistics for thirty-seven training sites representing a variety of crops plus urban, water and desert land-covers were obtained and analyzed using transformed divergence (TD) calculations. TD values were employed to assess intraclass variability and the best bands for classification. Four subscenes were selected for clustering or unsupervised signature extraction. These areas were agriculture, urban, desert and water land-covers. The number of clusters for these subscenes were examined and the best TM bands for interclass separability were identified. The results of the clustering and training site analyses for interclass separability were compared. The TM data were useful for the digital delimitation of most crops and other cover types in this analysis. Four bands of data are adequate for classification with the best results obtained by the selection of one band from each of the available portions of the electromagnetic spectrum. Different band combinations are best for various land-cover intraclass separability.

  2. Topographic Correction of Landsat TM-5 and Landsat OLI-8 Imagery to Improve the Performance of Forest Classification in the Mountainous Terrain of Northeast Thailand

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    Uday Pimple


    Full Text Available The accurate mapping and monitoring of forests is essential for the sustainable management of forest ecosystems. Advancements in the Landsat satellite series have been very useful for various forest mapping applications. However, the topographic shadows of irregular mountains are major obstacles to accurate forest classification. In this paper, we test five topographic correction methods: improved cosine correction, Minnaert, C-correction, Statistical Empirical Correction (SEC and Variable Empirical Coefficient Algorithm (VECA, with multisource digital elevation models (DEM to reduce the topographic relief effect in mountainous terrain produced by the Landsat Thematic Mapper (TM-5 and Operational Land Imager (OLI-8 sensors. The effectiveness of the topographic correction methods are assessed by visual interpretation and the reduction in standard deviation (SD, by means of the coefficient of variation (CV. Results show that the SEC performs best with the Shuttle Radar Topographic Mission (SRTM 30 m × 30 m DEM. The random forest (RF classifier is used for forest classification, and the overall accuracy of forest classification is evaluated to compare the performances of the topographic corrections. Our results show that the C-correction, SEC and VECA corrected imagery were able to improve the forest classification accuracy of Landsat TM-5 from 78.41% to 81.50%, 82.38%, and 81.50%, respectively, and OLI-8 from 81.06% to 81.50%, 82.38%, and 81.94%, respectively. The highest accuracy of forest type classification is obtained with the newly available high-resolution SRTM DEM and SEC method.

  3. Glacial lake monitoring in the Karakoram Range using historical Landsat Thematic Mapper archive (1982 - 2014) (United States)

    Chan, J. Y. H.; Kelly, R. E. J.; Evans, S. G.


    Glacierized regions are one of the most dynamic land surface environments on the planet (Evans and Delaney, In Press). They are susceptible to various types of natural hazards such as landslides, glacier avalanches, and glacial lake outburst floods (GLOF). GLOF events are increasingly common and present catastrophic flood hazards, the causes of which are sensitive to climate change in complex high mountain topography (IPCC, 2013). Inundation and debris flows from GLOF events have repeatedly caused significant infrastructure damages and loss of human lives in the high mountain regions of the world (Huggel et al, 2002). The research is designed to develop methods for the consistent detection of glacier lakes formation during the Landsat Thematic Mapper (TM) era (1982 - present), to quantify the frequency of glacier lake development and estimate lake volume using Landsat imagery and digital elevation model (DEM) data. Landsat TM scenes are used to identify glacier lakes in the Shimshal and Shaksgam valley, particularly the development of Lake Virjeab in year 2000 and Kyagar Lake in 1998. A simple thresholding technique using Landsat TM infrared bands, along with object-based segmentation approaches are used to isolate lake extent. Lake volume is extracted by intersecting the lake extent with the DEM surface. Based on previous studies and DEM characterization in the region, Shuttle Radar Topography Mission (SRTM) DEM is preferred over Advanced Spaceborne Thermal Emission and Reflection (ASTER) GDEM due to higher accuracy. Calculated errors in SRTM height estimates are 5.81 m compared with 8.34 m for ASTER. SRTM data are preferred because the DEM measurements were made over short duration making the DEM internally consistent. Lake volume derived from the Landsat TM imagery and DEM are incorporated into a simple GLOF model identified by Clague and Matthews (1973) to estimate the potential peak discharge (Qmax) of a GLOF event. We compare the simple Qmax estimates with

  4. Preparing Landsat Image Time Series (LITS for Monitoring Changes in Vegetation Phenology in Queensland, Australia

    Directory of Open Access Journals (Sweden)

    Santosh Bhandari


    Full Text Available Time series of images are required to extract and separate information on vegetation change due to phenological cycles, inter-annual climatic variability, and long-term trends. While images from the Landsat Thematic Mapper (TM sensor have the spatial and spectral characteristics suited for mapping a range of vegetation structural and compositional properties, its 16-day revisit period combined with cloud cover problems and seasonally limited latitudinal range, limit the availability of images at intervals and durations suitable for time series analysis of vegetation in many parts of the world. Landsat Image Time Series (LITS is defined here as a sequence of Landsat TM images with observations from every 16 days for a five-year period, commencing on July 2003, for a Eucalyptus woodland area in Queensland, Australia. Synthetic Landsat TM images were created using the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM algorithm for all dates when images were either unavailable or too cloudy. This was done using cloud-free scenes and a MODIS Nadir BRDF Adjusted Reflectance (NBAR product. The ability of the LITS to measure attributes of vegetation phenology was examined by: (1 assessing the accuracy of predicted image-derived Foliage Projective Cover (FPC estimates using ground-measured values; and (2 comparing the LITS-generated normalized difference vegetation index (NDVI and MODIS NDVI (MOD13Q1 time series. The predicted image-derived FPC products (value ranges from 0 to 100% had an RMSE of 5.6. Comparison between vegetation phenology parameters estimated from LITS-generated NDVI and MODIS NDVI showed no significant difference in trend and less than 16 days (equal to the composite period of the MODIS data used difference in key seasonal parameters, including start and end of season in most of the cases. In comparison to similar published work, this paper tested the STARFM algorithm in a new (broadleaf forest environment and also

  5. Landsat 7 ETM/1G satellite imagery - Hawaiian Islands cloud-free mosaics (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Cloud-free Landsat satellite imagery mosaics of the islands of the main 8 Hawaiian Islands (Hawaii, Maui, Kahoolawe, Lanai, Molokai, Oahu, Kauai and Niihau). Landsat...

  6. Global Human Built-up And Settlement Extent (HBASE) Dataset From Landsat (United States)

    National Aeronautics and Space Administration — The Global Human Built-up And Settlement Extent (HBASE) Dataset from Landsat is a global map of HBASE derived from the Global Land Survey (GLS) Landsat dataset for...

  7. Use of LANDSAT imagery for soil survey (United States)

    Dejesusparada, N. (Principal Investigator); Filho, M. V.; Higa, N. T.; Celsodecarvalho, V.


    The author has identified the following significant results. The MSS channels 6 and 7 were considered the best to study the relative tonality of different spectral responses of soils, while channels 5 and 7 were best for natural vegetation, drainage patterns, and land use. Frequency ratio was the recommended index for use when analyzing a drainage pattern quantitatively.

  8. Report: ECHO Data Quality Audit – Phase I Results: The Integrated Compliance Information System Needs Security Controls to Protect Significant Non-Compliance Data (United States)

    Report #09-P-0226, August 31, 2009. End users of the Permit Compliance System and Integrated Compliance Information System National Pollutant Discharge Elimination System can override the Significant Non-Compliance data field without more access controls.

  9. Prognostic significance of precordial ST segment depression during inferior myocardial infarction in the thrombolytic era: Results in 16,521 patients

    NARCIS (Netherlands)

    E.D. Peterson; W.R. Hathaway; K.M. Zabel; K.S. Pieper (Karen); C.B. Granger (Christopher); G.S. Wagner (Galen); E.J. Topol (Eric); E.R. Bates (Eric); M.L. Simoons (Maarten); R.M. Califf (Robert)


    textabstractObjectives. We examined the prognostic significance of precordial ST segment depression among patients with an acute inferior myocardial infarction. Background. Although precordial ST segment depression has been associated with a poor prognosis, this correlation has not been adequately

  10. Treatment with a belly-board device significantly reduces the volume of small bowel irradiated and results in low acute toxicity in adjuvant radiotherapy for gynecologic cancer: results of a prospective study

    International Nuclear Information System (INIS)

    Martin, Joseph; Fitzpatrick, Kathryn; Horan, Gail; McCloy, Roisin; Buckney, Steve; O'Neill, Louise; Faul, Clare


    Background and purpose: To determine whether treatment prone on a belly-board significantly reduces the volume of small bowel irradiated in women receiving adjuvant radiotherapy for gynecologic cancer, and to prospectively study acute small bowel toxicity using an accepted recording instrument. Material and methods: Thirty-two gynecologic patients underwent simulation with CT scanning supine and prone. Small bowel was delineated on every CT slice, and treatment was prone on the belly-board using 3-5 fields-typically Anterior, Right and Left Lateral, plus or minus Lateral Boosts. Median prescribed dose was 50.4 Gy and all treatments were delivered in 1.8 Gy fractions. Concomitant Cisplatin was administered in 13 patients with cervical carcinoma. Comparison of small bowel dose-volumes was made between supine and prone, with each subject acting as their own matched pair. Acute small bowel toxicity was prospectively measured using the Common Toxicity Criteria: Version 2.0. Results: Treatment prone on the belly-board significantly reduced the volume of small bowel receiving ≥100; ≥95; ≥90; and ≥80% of the prescribed dose, but not ≥50%. This was found whether volume was defined in cubic centimeters or % of total small bowel volume. Of 29 evaluable subjects, 2 (7%) experienced 1 episode each of grade 3 diarrhoea. All other toxicity events were grade 2 or less and comprised diarrhoea (59%), abdominal pain or cramping (48%), nausea (38%), anorexia (17%), vomiting (10%). There were no Grade 4 events and no treatment days were lost due to toxicity. Conclusions: Treatment prone on a belly-board device results in significant small bowel sparing, during adjuvant radiotherapy for gynecologic cancer. The absence of Grade 4 events or Treatment Days Lost compares favorably with the published literature

  11. Evaluation of forest cover estimates for Haiti using supervised classification of Landsat data (United States)

    Churches, Christopher E.; Wampler, Peter J.; Sun, Wanxiao; Smith, Andrew J.


    This study uses 2010-2011 Landsat Thematic Mapper (TM) imagery to estimate total forested area in Haiti. The thematic map was generated using radiometric normalization of digital numbers by a modified normalization method utilizing pseudo-invariant polygons (PIPs), followed by supervised classification of the mosaicked image using the Food and Agriculture Organization (FAO) of the United Nations Land Cover Classification System. Classification results were compared to other sources of land-cover data produced for similar years, with an emphasis on the statistics presented by the FAO. Three global land cover datasets (GLC2000, Globcover, 2009, and MODIS MCD12Q1), and a national-scale dataset (a land cover analysis by Haitian National Centre for Geospatial Information (CNIGS)) were reclassified and compared. According to our classification, approximately 32.3% of Haiti's total land area was tree covered in 2010-2011. This result was confirmed using an error-adjusted area estimator, which predicted a tree covered area of 32.4%. Standardization to the FAO's forest cover class definition reduces the amount of tree cover of our supervised classification to 29.4%. This result was greater than the reported FAO value of 4% and the value for the recoded GLC2000 dataset of 7.0%, but is comparable to values for three other recoded datasets: MCD12Q1 (21.1%), Globcover (2009) (26.9%), and CNIGS (19.5%). We propose that at coarse resolutions, the segmented and patchy nature of Haiti's forests resulted in a systematic underestimation of the extent of forest cover. It appears the best explanation for the significant difference between our results, FAO statistics, and compared datasets is the accuracy of the data sources and the resolution of the imagery used for land cover analyses. Analysis of recoded global datasets and results from this study suggest a strong linear relationship (R2 = 0.996 for tree cover) between spatial resolution and land cover estimates.

  12. Forest Disturbance Mapping Using Dense Synthetic Landsat/MODIS Time-Series and Permutation-Based Disturbance Index Detection

    Directory of Open Access Journals (Sweden)

    David Frantz


    Full Text Available Spatio-temporal information on process-based forest loss is essential for a wide range of applications. Despite remote sensing being the only feasible means of monitoring forest change at regional or greater scales, there is no retrospectively available remote sensor that meets the demand of monitoring forests with the required spatial detail and guaranteed high temporal frequency. As an alternative, we employed the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM to produce a dense synthetic time series by fusing Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS nadir Bidirectional Reflectance Distribution Function (BRDF adjusted reflectance. Forest loss was detected by applying a multi-temporal disturbance detection approach implementing a Disturbance Index-based detection strategy. The detection thresholds were permutated with random numbers for the normal distribution in order to generate a multi-dimensional threshold confidence area. As a result, a more robust parameterization and a spatially more coherent detection could be achieved. (i The original Landsat time series; (ii synthetic time series; and a (iii combined hybrid approach were used to identify the timing and extent of disturbances. The identified clearings in the Landsat detection were verified using an annual woodland clearing dataset from Queensland’s Statewide Landcover and Trees Study. Disturbances caused by stand-replacing events were successfully identified. The increased temporal resolution of the synthetic time series indicated promising additional information on disturbance timing. The results of the hybrid detection unified the benefits of both approaches, i.e., the spatial quality and general accuracy of the Landsat detection and the increased temporal information of synthetic time series. Results indicated that a temporal improvement in the detection of the disturbance date could be achieved relative to the irregularly spaced Landsat

  13. Velocities of antarctic outlet glaciers determined from sequential Landsat images (United States)

    MacDonald, Thomas R.; Ferrigno, Jane G.; Williams, Richard S.; Lucchitta, Baerbel K.


    Approximately 91.0 percent of the volume of present-day glacier ice on Earth is in Antarctica; Greenland contains about another 8.3 percent of the volume. Thus, together, these two great ice sheets account for an estimated 99.3 percent of the total. Long-term changes in the volume of glacier ice on our planet are the result of global climate change. Because of the relationship of global ice volume to sea level (± 330 cubic kilometers of glacier ice equals ± 1 millimeter sea level), changes in the mass balance of the antarctic ice sheet are of particular importance.Whether the mass balance of the east and west antarctic ice sheets is positive or negative is not known. Estimates of mass input by total annual precipitation for the continent have been made from scattered meteorological observations (Swithinbank 1985). The magnitude of annual ablation of the ice sheet from calving of outlet glaciers and ice shelves is also not well known. Although the velocities of outlet glaciers can be determined from field measurements during the austral summer,the technique is costly, does not cover a complete annual cycle,and has been applied to just a few glaciers. To increase the number of outlet glaciers in Antarctica for which velocities have been determined and to provide additional data for under-standing the dynamics of the antarctic ice sheets and their response to global climate change, sequential Landsat image of several outlet glaciers were measured.

  14. Assessment of Forest Damage in Croatia using Landsat-8 OLI Images

    Directory of Open Access Journals (Sweden)

    Anita Simic Milas


    Full Text Available Background and Purpose: Rapid assessments of forest damage caused by natural disasters such as ice-break, wind, flooding, hurricane, or forest fires are necessary for mitigation and forest management. Forest damage directly impacts carbon uptake and biogeochemical cycles, and thus, has an impact on climate change. It intensifies erosion and flooding, and influences socio-economic well-being of population. Quantification of forest cover change represents a challenge for the scientific community as damaged areas are often in the mountainous and remote regions. Forested area in the western Croatia was considerably damaged by ice-breaking and flooding in 2014. Satellite remote sensing technology has opened up new possibilities for detecting and quantifying forest damage. Several remote sensing tools are available for rapid assessment of forest damage. These include aerial photographic interpretation, and airborne and satellite imagery. This study evaluates the capability of Landsat-8 optical data and a vegetation index for mapping forest damage in Croatia that occurred during the winter of 2014. Materials and Methods: The change detection analysis in this study was based on the Normalized Difference Vegetation Index (NDVI difference approach, where pre- and post- event Landsat-8 images were employed in the ENVI image change workflow. The validation was done by comparing the satellite-generated change detection map with the ground truth data based on field observations and spatial data of forest management units and plans. Results: The overall damage assessment from this study suggests that the total damaged area covers 45,265.32 ha of forest. It is 19.20% less than estimated by Vuletić et al. [3] who found that 56,021.86 ha of forest were affected. Most damage was observed in the mixed, broadleaf and coniferous forest. The change errors of commission and omission were calculated to be 35.73% and 31.60%, respectively. Conclusions: Landsat-8 optical

  15. Landsat-based monitoring of crop water demand in the San Joaquin Valley (United States)

    Johnson, L.; Trout, T.; Wang, D.; Melton, F. S.


    Fresh water resources are becoming increasingly scarce in California due to urbanization, environmental regulation, and groundwater depletion. The strain is projected to worsen under various climate change scenarios and is exacerbated by declining water delivery infrastructure. It is estimated that irrigated agriculture currently commands more than 70% of the state’s water supply, and many growers are striving to improve water use efficiency in order to help maintain the state’s rich agricultural heritage. Remote sensing technology offers the potential to monitor cropland evapotranspiration (ET) regionally, while making farm-based irrigation scheduling more practical, convenient, and possibly more accurate. Landsat5-TM imagery was used in this study to monitor basal crop evapotranspiration (ETcb), which is primarily related to plant transpiration, for several San Joaquin Valley fields throughout the 2008 growing season. A ground-based digital camera was used to measure fractional cover of 48 study fields planted to 18 different crop types (row crops, grains, orchard, and vineyard) of varying maturity over 12 dates coinciding with Landsat overpasses. Landsat L1T terrain-corrected images were atmospherically corrected to surface reflectance by an implementation of the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS), then converted to normalized difference vegetation index (NDVI) on a per-pixel basis. A strong linear relationship between NDVI and fractional cover was observed (r2=0.96), and a resulting conversion equation was used to transform all imagery to fractional cover. Conversion equations previously developed by use of weighting lysimeters were then used to transform fractional cover to basal crop coefficient (Kcb; ratio of crop transpiration plus a small diffusive soil evaporation component to reference ET). Finally, measurements of grass reference ET (ETo) from the California Irrigation Management Information System were used to

  16. Early Spring Post-Fire Snow Albedo Dynamics in High Latitude Boreal Forests Using Landsat-8 OLI Data (United States)

    Wang, Zhuosen; Erb, Angela M.; Schaaf, Crystal B.; Sun, Qingsong; Liu, Yan; Yang, Yun; Shuai, Yanmin; Casey, Kimberly A.; Roman, Miguel O.


    Taking advantage of the improved radiometric resolution of Landsat-8 OLI which, unlike previous Landsat sensors, does not saturate over snow, the progress of fire recovery progress at the landscape scale (less than 100 m) is examined. High quality Landsat-8 albedo retrievals can now capture the true reflective and layered character of snow cover over a full range of land surface conditions and vegetation densities. This new capability particularly improves the assessment of post-fire vegetation dynamics across low- to high-burn severity gradients in Arctic and boreal regions in the early spring, when the albedos during recovery show the greatest variation. We use 30 m resolution Landsat-8 surface reflectances with concurrent coarser resolution (500 m) MODIS high quality full inversion surface Bidirectional Reflectance Distribution Functions (BRDF) products to produce higher resolution values of surface albedo. The high resolution full expression shortwave blue sky albedo product performs well with an overall RMSE of 0.0267 between tower and satellite measures under both snow-free and snow-covered conditions. While the importance of post-fire albedo recovery can be discerned from the MODIS albedo product at regional and global scales, our study addresses the particular importance of early spring post-fire albedo recovery at the landscape scale by considering the significant spatial heterogeneity of burn severity, and the impact of snow on the early spring albedo of various vegetation recovery types. We found that variations in early spring albedo within a single MODIS gridded pixel can be larger than 0.6. Since the frequency and severity of wildfires in Arctic and boreal systems is expected to increase in the coming decades, the dynamics of albedo in response to these rapid surface changes will increasingly impact the energy balance and contribute to other climate processes and physical feedback mechanisms. Surface radiation products derived from Landsat-8 data will

  17. Harmonic regression of Landsat time series for modeling attributes from national forest inventory data (United States)

    Barry T. Wilson; Joseph F. Knight; Ronald E. McRoberts


    Imagery from the Landsat Program has been used frequently as a source of auxiliary data for modeling land cover, as well as a variety of attributes associated with tree cover. With ready access to all scenes in the archive since 2008 due to the USGS Landsat Data Policy, new approaches to deriving such auxiliary data from dense Landsat time series are required. Several...

  18. The prognostic significance of early treatment response in pediatric relapsed acute myeloid leukemia : results of the international study Relapsed AML 2001/01

    NARCIS (Netherlands)

    Creutzig, Ursula; Zimmermann, Martin; Dworzak, Michael N.; Gibson, Brenda; Tamminga, Rienk; Abrahamsson, Jonas; Ha, Shau-Yin; Hasle, Henrik; Maschan, Alexey; Bertrand, Yves; Leverger, Guy; von Neuhoff, Christine; Razzouk, Bassem; Rizzari, Carmelo; Smisek, Petr; Smith, Owen P.; Stark, Batia; Reinhardt, Dirk; Kaspers, Gertjan L.


    The prognostic significance of early response to treatment has not been reported in relapsed pediatric acute myeloid leukemia. In order to identify an early and easily applicable prognostic factor allowing subsequent treatment modifications, we assessed leukemic blast counts in the bone marrow by

  19. Principles of computer processing of Landsat data for geologic applications (United States)

    Taranik, James V.


    The main objectives of computer processing of Landsat data for geologic applications are to improve display of image data to the analyst or to facilitate evaluation of the multispectral characteristics of the data. Interpretations of the data are made from enhanced and classified data by an analyst trained in geology. Image enhancements involve adjustments of brightness values for individual picture elements. Image classification involves determination of the brightness values of picture elements for a particular cover type. Histograms are used to display the range and frequency of occurrence of brightness values. Landsat-1 and -2 data are preprocessed at Goddard Space Flight Center (GSFC) to adjust for the detector response of the multispectral scanner (MSS). Adjustments are applied to minimize the effects of striping, adjust for bad-data lines and line segments and lost individual pixel data. Because illumination conditions and landscape characteristics vary considerably and detector response changes with time, the radiometric adjustments applied at GSFC are seldom perfect and some detector striping remain in Landsat data. Rotation of the Earth under the satellite and movements of the satellite platform introduce geometric distortions in the data that must also be compensated for if image data are to be correctly displayed to the data analyst. Adjustments to Landsat data are made to compensate for variable solar illumination and for atmospheric effects. GeoMetric registration of Landsat data involves determination of the spatial location of a pixel in. the output image and the determination of a new value for the pixel. The general objective of image enhancement is to optimize display of the data to the analyst. Contrast enhancements are employed to expand the range of brightness values in Landsat data so that the data can be efficiently recorded in a manner desired by the analyst. Spatial frequency enhancements are designed to enhance boundaries between features

  20. LANDSAT-D ground segment operations plan, revision A (United States)

    Evans, B.


    The basic concept for the utilization of LANDSAT ground processing resources is described. Only the steady state activities that support normal ground processing are addressed. This ground segment operations plan covers all processing of the multispectral scanner and the processing of thematic mapper through data acquisition and payload correction data generation for the LANDSAT 4 mission. The capabilities embedded in the hardware and software elements are presented from an operations viewpoint. The personnel assignments associated with each functional process and the mechanisms available for controlling the overall data flow are identified.

  1. Monitoring Quarry Area with Landsat Long Time-Series for Socioeconomic Study

    Directory of Open Access Journals (Sweden)

    Haoteng Zhao


    Full Text Available Quarry sites result from human activity, which includes the removal of original vegetation and the overlying soil to dig out stones for building use. Therefore, the dynamics of the quarry area provide a unique view of human mining activities. Actually, the topographic changes caused by mining activities are also a result of the development of the local economy. Thus, monitoring the quarry area can provide information about the policies of the economy and environmental protection. In this paper, we developed a combined method of machine learning classification and quarry region analysis to estimate the quarry area in a quarry region near Beijing. A temporal smoothing based on the classification results of all years was applied in post-processing to remove outliers and obtain gently changing sequences along the monitoring term. The method was applied to Landsat images to derive a quarry distribution map and quarry area time series from 1984 to 2017, revealing significant inter-annual variability. The time series revealed a five-stage development of the quarry area with different growth patterns. As the study region lies on two jurisdictions—Tianjin and Hebei—a comparison of the quarry area changes in the two jurisdictions was applied, which revealed that the different policies in the two regions could impose different impacts on the development of a quarry area. An analysis concerning the relationship between quarry area and gross regional product (GRP was performed to explore the potential application on socioeconomic studies, and we found a strong positive correlation between quarry area and GRP in Langfang City, Hebei Province. These results demonstrate the potential benefit of annual monitoring over the long-term for socioeconomic studies, which can be used for mining decision making.

  2. Mapping and Change Analysis in Mangrove Forest by Using Landsat Imagery (United States)

    Dan, T. T.; Chen, C. F.; Chiang, S. H.; Ogawa, S.


    Mangrove is located in the tropical and subtropical regions and brings good services for native people. Mangrove in the world has been lost with a rapid rate. Therefore, monitoring a spatiotemporal distribution of mangrove is thus critical for natural resource management. This research objectives were: (i) to map the current extent of mangrove in the West and Central Africa and in the Sundarbans delta, and (ii) to identify change of mangrove using Landsat data. The data were processed through four main steps: (1) data pre-processing including atmospheric correction and image normalization, (2) image classification using supervised classification approach, (3) accuracy assessment for the classification results, and (4) change detection analysis. Validation was made by comparing the classification results with the ground reference data, which yielded satisfactory agreement with overall accuracy 84.1% and Kappa coefficient of 0.74 in the West and Central Africa and 83.0% and 0.73 in the Sundarbans, respectively. The result shows that mangrove areas have changed significantly. In the West and Central Africa, mangrove loss from 1988 to 2014 was approximately 16.9%, and only 2.5% was recovered or newly planted at the same time, while the overall change of mangrove in the Sundarbans increased approximately by 900 km2 of total mangrove area. Mangrove declined due to deforestation, natural catastrophes deforestation and mangrove rehabilitation programs. The overall efforts in this study demonstrated the effectiveness of the proposed method used for investigating spatiotemporal changes of mangrove and the results could provide planners with invaluable quantitative information for sustainable management of mangrove ecosystems in these regions.

  3. Use of landsat ETM+ SLC-off segment-based gap-filled imagery for crop type mapping (United States)

    Maxwell, S.K.; Craig, M.E.


    Failure of the Scan Line Corrector (SLC) on the Landsat ETM+ sensor has had a major impact on many applications that rely on continuous medium resolution imagery to meet their objectives. The United States Department of Agriculture (USDA) Cropland Data Layer (CDL) program uses Landsat imagery as the primary source of data to produce crop-specific maps for 20 states in the USA. A new method has been developed to fill the image gaps resulting from the SLC failure to support the needs of Landsat users who require coincident spectral data, such as for crop type mapping and monitoring. We tested the new gap-filled method for a CDL crop type mapping project in eastern Nebraska. Scan line gaps were simulated on two Landsat 5 images (spring and late summer 2003) and then gap-filled using landscape boundary models, or segment models, that were derived from 1992 and 2002 Landsat images (used in the gap-fill process). Various date combinations of original and gap-filled images were used to derive crop maps using a supervised classification process. Overall kappa values were slightly higher for crop maps derived from SLC-off gap-filled images compared to crop maps derived from the original imagery (0.3–1.3% higher). Although the age of the segment model used to derive the SLC-off gap-filled product did not negatively impact the overall agreement, differences in individual cover type agreement did increase (−0.8%–1.6% using the 2002 segment model to −5.0–5.1% using the 1992 segment model). Classification agreement also decreased for most of the classes as the size of the segment used in the gap-fill process increased.

  4. Ibuprofen therapy resulted in significantly decreased tissue bacillary loads and increased survival in a new murine experimental model of active tuberculosis. (United States)

    Vilaplana, Cristina; Marzo, Elena; Tapia, Gustavo; Diaz, Jorge; Garcia, Vanesa; Cardona, Pere-Joan


    C3HeB/FeJ mice infected with Mycobacterium tuberculosis were used in an experimental animal model mimicking active tuberculosis in humans to evaluate the effect of antiinflammatory agents. No other treatment but ibuprofen was given, and it was administered when the animals' health started to deteriorate. Animals treated with ibuprofen had statistically significant decreases in the size and number of lung lesions, decreases in the bacillary load, and improvements in survival, compared with findings for untreated animals. Because antiinflammatory agents are already on the market, further clinical trials should be done to evaluate this effect in humans as soon as possible, to determine their suitability as coadjuvant tuberculosis treatment.

  5. Cognitive-behavioral therapy (CBT) versus acceptance and commitment therapy (ACT) for dementia family caregivers with significant depressive symptoms: Results of a randomized clinical trial. (United States)

    Losada, Andrés; Márquez-González, María; Romero-Moreno, Rosa; Mausbach, Brent T; López, Javier; Fernández-Fernández, Virginia; Nogales-González, Celia


    The differential efficacy of acceptance and commitment therapy (ACT) and cognitive-behavioral therapy (CBT) for dementia family caregivers' is analyzed through a randomized controlled trial. Participants were 135 caregivers with high depressive symptomatology who were randomly allocated to the intervention conditions or a control group (CG). Pre-, postintervention, and follow-up measurements assessed depressive symptomatology, anxiety, leisure, dysfunctional thoughts, and experiential avoidance. Depression: Significant effects of interventions compared with CG were found for CBT (p dementia caregivers. (c) 2015 APA, all rights reserved).

  6. Addition of 2-(ethylamino)acetonitrile group to nitroxoline results in significantly improved anti-tumor activity in vitro and in vivo. (United States)

    Mitrović, Ana; Sosič, Izidor; Kos, Špela; Tratar, Urša Lampreht; Breznik, Barbara; Kranjc, Simona; Mirković, Bojana; Gobec, Stanislav; Lah, Tamara; Serša, Gregor; Kos, Janko


    Lysosomal cysteine peptidase cathepsin B, involved in multiple processes associated with tumor progression, is validated as a target for anti-cancer therapy. Nitroxoline, a known antimicrobial agent, is a potent and selective inhibitor of cathepsin B, hence reducing tumor progression in vitro and in vivo . In order to further improve its anti-cancer properties we developed a number of derivatives using structure-based chemical synthesis. Of these, the 7-aminomethylated derivative (compound 17 ) exhibited significantly improved kinetic properties over nitroxoline, inhibiting cathepsin B endopeptidase activity selectively. In the present study, we have evaluated its anti-cancer properties. It was more effective than nitroxoline in reducing tumor cell invasion and migration, as determined in vitro on two-dimensional cell models and tumor spheroids, under either endpoint or real time conditions. Moreover, it exhibited improved action over nitroxoline in impairing tumor growth in vivo in LPB mouse fibrosarcoma tumors in C57Bl/6 mice. Taken together, the addition of a 2-(ethylamino)acetonitrile group to nitroxoline at position 7 significantly improves its pharmacological characteristics and its potential for use as an anti-cancer drug.

  7. Prognostic significance of equivocal human epidermal growth factor receptor 2 results and clinical utility of alternative chromosome 17 genes in patients with invasive breast cancer: A cohort study. (United States)

    Sneige, Nour; Hess, Kenneth R; Multani, Asha S; Gong, Yun; Ibrahim, Nuhad K


    The 2013 testing guidelines for determining the human epidermal growth factor receptor 2 (HER2) status include new cutoff points for the HER2/chromosome enumeration probe 17 (CEP17) ratio and the average HER2 copy number per cell, and they recommend using a reflex test with alternative chromosome 17 probes (Ch17Ps) to resolve equivocal HER2 results. This study sought to determine the clinical utility of alternative Ch17Ps in equivocal cases and the effects of equivocal results and/or a change in the HER2 status on patients' outcomes. The University of Texas MD Anderson Cancer Center database of HER2 dual-probe fluorescence in situ hybridization results from 2000 to 2010 was searched for cases of invasive breast cancer with HER2/CEP17 ratios Cancer 2017;123:1115-1123. © 2016 American Cancer Society. © 2016 American Cancer Society.

  8. New insights on therapeutic touch: a discussion of experimental methodology and design that resulted in significant effects on normal human cells and osteosarcoma. (United States)

    Monzillo, Eloise; Gronowicz, Gloria


    Our purpose is to discuss the study design and innovative approaches that led to finding significant effects of one energy medicine therapy, Therapeutic Touch (TT), on cells. In the original published studies, TT was shown to significantly increase human osteoblast DNA synthesis, differentiation, and mineralization; increase in a dose-dependent manner the growth of other human cell types; and decrease the differentiation and mineralization of a human osteosarcoma-derived cell line. A unique feature of the study's methodology and design that contributed to the success of the findings was that a basic level of skill and maturity of the TT practitioner was quantified for producing observable and replicable outcomes in a test administered to all TT practitioners. Only those practitioners that passed the test were selected for the study. (2) The practitioners were required to keep a journal, which appeared to promote their ability to stay centered and replicate their treatments over months of cell experimentation. (3) The origin of the cells that the practitioners were treating was explained to them, although they were blinded to cell type during the experiments. (4) Only early passage cells were used to maintain a stable cell phenotype. (5) Standard protocols for performing TT in the room were followed to ensure reproducible conditions. (6) Placebo controls and untreated controls were used for each experiment. (7) The principal investigator and technicians performing the assays were blinded as to the experimental groups, and all assays and procedures were well established in the laboratory prior to the start of the TT experiments. The absence of studies on the human biofield from mainstream scientific literature is also discussed by describing the difficulties encountered in publishing. These roadblocks contribute to our lack of understanding of the human biofield and energy medicine modalities in science. In conclusion, this report seeks to encourage well

  9. Consumption of a healthy dietary pattern results in significant reductions in C-reactive protein levels in adults: a meta-analysis. (United States)

    Neale, E P; Batterham, M J; Tapsell, L C


    Consumption of healthy dietary patterns has been associated with reduced risk of cardiovascular disease and metabolic syndrome. Dietary intervention targets disease prevention, so studies increasingly use biomarkers of underlying inflammation and metabolic syndrome progression to examine the diet-health relationship. The extent to which these biomarkers contribute to the body of evidence on healthy dietary patterns is unknown. The aim of this meta-analysis was to determine the effect of healthy dietary patterns on biomarkers associated with adiposity, insulin resistance, and inflammation in adults. A systematic search of Scopus, PubMed, Web of Science, and Cochrane Central Register of Controlled Trials (all years to April 2015) was conducted. Inclusion criteria were randomized controlled trials; effects of dietary patterns assessed on C-reactive protein (CRP), total adiponectin, high-molecular-weight adiponectin, tumor necrosis factor-α, adiponectin:leptin, resistin, or retinol binding protein 4. Random effects meta-analyses were conducted to assess the weighted mean differences in change or final mean values for each outcome. Seventeen studies were included in the review. These reflected research on dietary patterns associated with the Mediterranean diet, Nordic diet, Tibetan diet, and the Dietary Approaches to Stop Hypertension diet. Consumption of a healthy dietary pattern was associated with significant reductions in CRP (weighted mean difference, -0.75 [-1.16, -0.35]; P = .0003). Non-significant changes were found for all other biomarkers. This analysis found evidence for favorable effects of healthy dietary patterns on CRP, with limited evidence for other biomarkers. Future research should include additional randomized controlled trials incorporating a greater range of dietary patterns and biomarkers. Copyright © 2016 Elsevier Inc. All rights reserved.

  10. Combining land use data acquired from Landsat with soil map data (United States)

    Westin, F. C.; Brandner, T. M.


    A method currently used to derive agrophysical units (APUs), i.e., geographical areas having definable/comparable agronomic and physical parameters which reflect a range in agricultural use and management, is discussed with reference to results obtained for South Dakota and an area in China. The method consists of combining agricultural land use data acquired from Landsat with soil map data. The resulting map units are soil associations characterized by cropland use intensity, and they can be used to identify major cropland areas and to develop a rating reflecting the relative potential of the soils in the delineated area for crop production, as well as to update small-scale soil maps.

  11. Spatial-temporal eco-environmental vulnerability assessment and its influential factors based on Landsat data (United States)

    Anh, N. K.; Liou, Y. A.; Ming-Hsu, L.


    Regional land use/land cover (LULC) changes lead to various changes in ecological processes and, in turn, alter regional micro-climate. To understand eco-environmental responses to LULC changes, eco-environmental evaluation is thus required with aims to identify vulnerable regions and influential factors, so that practical measures for environmental protection and management may be proposed. The Thua Thien - Hue Province has been experiencing urbanization at a rapid rate in both population and physical size. The urban land, agricultural land, and aquaculture activities have been invasively into natural space and caused eco-environment deterioration by land desertification, soil erosion, shrinking forest resources,…etc. In this study, an assessment framework that is composed by 11 variables with 9 of them constructed from Landsat time series is proposed to serve as basis to examine eco-environmental vulnerability in the Thua Thien - Hue Province in years 1989, 2003, and 2014. An eco-environmental vulnerability map is assorted into six vulnerability levels consisting of potential, slight, light, medium, heavy, and very heavy vulnerabilities. Result shows that there is an increasing trend in eco-environmental vulnerability in general with expected evolving distributions in heavy and very heavy vulnerability levels, which mainly lying on developed land, bare land, semi bare land, agricultural land, and poor and recovery forests. In contrast, there is a significant decline in potential vulnerability level. The contributing factors of an upward trend in medium, heavy, and very heavy levels include: (i) a large natural forest converted to plantation forest and agriculture land; and (ii) significant expansion of developed land leading to difference in thermal signatures in urban areas as compared with those of the surrounding areas. It is concluded that anthropogenic processes with transformation on LULC has amplified the vulnerability of eco-environment in the study

  12. North American forest disturbance mapped from a decadal Landsat record (United States)

    Jeffrey G. Masek; Chengquan Huang; Robert Wolfe; Warren Cohen; Forrest Hall; Jonathan Kutler; Peder. Nelson


    Forest disturbance and recovery are critical ecosystem processes, but the spatial pattern of disturbance has never been mapped across North America. The LEDAPS (Landsat Ecosystem Disturbance Adaptive Processing System) project has assembled a wall-to-wall record of stand-clearing disturbance (clearcut harvest, fire) for the United States and Canada for the period 1990-...


    The objectives of this project were (1) to develop a universal index for measuring Turbidity and Chlorophyll-A from remote sensing data and (2) to correlate satellite image parameters from Landsat-7 data with field measurements of water quality for five parameters: Chlorophyll-A ...

  14. United States forest disturbance trends observed with landsat time series (United States)

    Jeffrey G. Masek; Samuel N. Goward; Robert E. Kennedy; Warren B. Cohen; Gretchen G. Moisen; Karen Schleweiss; Chengquan. Huang


    Disturbance events strongly affect the composition, structure, and function of forest ecosystems; however, existing US land management inventories were not designed to monitor disturbance. To begin addressing this gap, the North American Forest Dynamics (NAFD) project has examined a geographic sample of 50 Landsat satellite image time series to assess trends in forest...

  15. landsat remote sensing data as an alternative approach

    African Journals Online (AJOL)


    The use of Landsat data in this area has revealed the need of effective use of these data in ... and efficient in all aspects of cost. ... Removal of noise and cloud cover effects can well be ... approximatelly1000 km from the business city of Dar es ...

  16. Landsat's role in ecological applications of remote sensing. (United States)

    Warren B. Cohen; Samuel N. Goward


    Remote sensing, geographic information systems, and modeling have combined to produce a virtual explosion of growth in ecological investigations and applications that are explicitly spatial and temporal. Of all remotely sensed data, those acquired by landsat sensors have played the most pivotal role in spatial and temporal scaling. Modern terrestrial ecology relies on...

  17. Sun position calculator (SPC) for Landsat imagery with geodetic latitudes (United States)

    Seong, Jeong C.


    Landsat imagery comes with sun position information such as azimuth and sun elevation, but they are available only at the center of a scene. To aid in the use of Landsat imagery for various solar radiation applications such as topographic correction, solar power, urban heat island, agriculture, climate and vegetation, it is necessary to calculate the sun position information at every pixel. This research developed a PC application that creates sun position data layers in ArcGIS at every pixel in a Landsat scene. The SPC program is composed of two major routines - converting universal transverse Mercator (UTM) projection coordinates to geographic longitudes and latitudes, and calculating sun position information based on the Meeus' routine. For the latter, an innovative method was also implemented to account for the Earth's flattening on an ellipsoid. The Meeus routine implemented in this research showed about 0.2‧ of mean absolute difference from the National Renewable Energy Laboratory (NREL) Solar Position Algorithm (SPA) routine when solar zenith and azimuth angles were tested with every 30 min data at four city locations (Fairbanks, Atlanta, Sydney and Rio Grande) on June 30, 2014. The Meeus routine was about ten times faster than the SPA routine. Professionals who need the Sun's position information for Landsat imagery will benefit from the SPC application.

  18. Anxiety can significantly explain bolus perception in the context of hypotensive esophageal motility: Results of a large multicenter study in asymptomatic individuals. (United States)

    Cisternas, D; Scheerens, C; Omari, T; Monrroy, H; Hani, A; Leguizamo, A; Bilder, C; Ditaranto, A; Ruiz de León, A; Pérez de la Serna, J; Valdovinos, M A; Coello, R; Abrahao, L; Remes-Troche, J; Meixueiro, A; Zavala, M A; Marin, I; Serra, J


    Previous studies have not been able to correlate manometry findings with bolus perception. The aim of this study was to evaluate correlation of different variables, including traditional manometric variables (at diagnostic and extreme thresholds), esophageal shortening, bolus transit, automated impedance manometry (AIM) metrics and mood with bolus passage perception in a large cohort of asymptomatic individuals. High resolution manometry (HRM) was performed in healthy individuals from nine centers. Perception was evaluated using a 5-point Likert scale. Anxiety was evaluated using Hospitalized Anxiety and Depression scale (HAD). Subgroup analysis was also performed classifying studies into normal, hypotensive, vigorous, and obstructive patterns. One hundred fifteen studies were analyzed (69 using HRM and 46 using high resolution impedance manometry (HRIM); 3.5% swallows in 9.6% of volunteers were perceived. There was no correlation of any of the traditional HRM variables, esophageal shortening, AIM metrics nor bolus transit with perception scores. There was no HRM variable showing difference in perception when comparing normal vs extreme values (percentile 1 or 99). Anxiety but not depression was correlated with perception. Among hypotensive pattern, anxiety was a strong predictor of variance in perception (R 2 up to .70). Bolus perception is less common than abnormal motility among healthy individuals. Neither esophageal motor function nor bolus dynamics evaluated with several techniques seems to explain differences in bolus perception. Different mechanisms seem to be relevant in different manometric patterns. Anxiety is a significant predictor of bolus perception in the context of hypotensive motility. © 2017 John Wiley & Sons Ltd.

  19. Evaluation of the routine antimicrobial susceptibility testing results of clinically significant anaerobic bacteria in a Slovenian tertiary-care hospital in 2015. (United States)

    Jeverica, Samo; Kolenc, Urša; Mueller-Premru, Manica; Papst, Lea


    The aim of our study was to determined antimicrobial susceptibility profiles of 2673 clinically significant anaerobic bacteria belonging to the major genera, isolated in 2015 in a large tertiary-care hospital in Slovenia. The species identification was performed by MALDI-TOF mass spectrometry. Antimicrobial susceptibility was determined immediately at the isolation of the strains against: penicillin, co-amoxiclav, imipenem, clindamycin and metronidazole, using gradient diffusion methodology and EUCAST breakpoints. The most frequent anaerobes were Bacteroides fragilis group with 31% (n = 817), Gram positive anaerobic cocci (GPACs) with 22% (n = 589), Prevotella with 14% (n = 313) and Propionibacterium with 8% (n = 225). Metronidazole has retained full activity (100%) against all groups of anaerobic bacteria intrinsically susceptible to it. Co-amoxiclav and imipenem were active against most tested anaerobes with zero or low resistance rates. However, observed resistance to co-amoxiclav (8%) and imipenem (1%) is worrying especially among B. fragilis group isolates. High overall resistance (23%) to clindamycin was detected in our study and was highest among the genera Prevotella, Bacteroides, Parabacteroides, GPACs and Clostridium. Routine testing of antimicrobial susceptibility of clinically relevant anaerobic bacteria is feasible and provides good surveillance data. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  20. Dichorionic twin ultrasound surveillance: sonography every 4 weeks significantly underperforms sonography every 2 weeks: results of the Prospective Multicenter ESPRiT Study. (United States)

    Corcoran, Siobhan; Breathnach, Fionnuala; Burke, Gerard; McAuliffe, Fionnuala; Geary, Michael; Daly, Sean; Higgins, John; Hunter, Alyson; Morrison, John J; Higgins, Shane; Mahony, Rhona; Dicker, Patrick; Tully, Elizabeth; Malone, Fergal D


    A 2-week ultrasound scanning schedule for monochorionic twins is endorsed widely. There is a lack of robust data to inform a schedule for the surveillance of dichorionic gestations. We aimed to determine how ultrasound scanning that is performed at 2- or 4-week intervals (or every 4 weeks before 32 weeks' gestation and every 2 weeks thereafter) may impact the prenatal detection of fetal growth restriction (FGR) and ultimately influence timing of delivery. In a consecutive cohort of 789 dichorionic twin pregnancies that were recruited prospectively for the multicenter Evaluation of Sonographic Predictors of Restricted Growth in Twins study, ultrasound determination of fetal growth and interrogation of umbilical and middle cerebral artery Doppler scans were performed every 2 weeks from 24 weeks' gestation until delivery. Complete delivery and perinatal outcome data were recorded for all pregnancies. Where delivery was prompted by FGR, abnormal umbilical artery Doppler examination or poor biophysical profile and in the absence of ruptured membranes, onset of labor, preeclampsia, or antepartum hemorrhage, the delivery was considered "ultrasound-indicated." For ultrasound-indicated deliveries, detection probabilities for FGR/abnormal umbilical artery Doppler scans/poor biophysical were determined according to the interval between examinations, by the suppression if alternate examination data. Among 789 dichorionic twin pregnancies, 66 pairs (8%) had an "ultrasound indicated" delivery. Detection of FGR was reduced from 88-69%, and detection of abnormal umbilical artery Doppler was reduced from 82-62% when a 4-week ultrasound schedule was simulated. Both of these reductions reached statistical significance. There was a nonsignificant trend toward a reduction in the recording of oligohydramnios with a 4-week interval between examinations. This study suggests that the ultrasound surveillance program of every 2 weeks that is recommended currently for monochorionic twins

  1. Prevalence and prognostic significance of ECG abnormalities in HIV-infected patients: results from the Strategies for Management of Antiretroviral Therapy study

    DEFF Research Database (Denmark)

    Soliman, Elsayed Z; Prineas, Ronald J; Roediger, Mollie P


    BACKGROUND: It remains debated whether to include resting electrocardiogram (ECG) in the routine care of human immunodeficiency virus (HIV)-infected patients. METHODS: This analysis included 4518 HIV-infected patients (28% women and 29% blacks) from the Strategies for Management of Antiretroviral...... Therapy study, a clinical trial aimed to compare 2 HIV treatment strategies. ECG abnormalities were classified using the Minnesota Code. Cox proportional hazards analysis was used to examine the association between baseline ECG abnormalities and incident cardiovascular disease (CVD). RESULTS: More than...... half of the participants (n = 2325, or 51.5%) had either minor or major ECG abnormalities. Minor ECG abnormalities (48.6%) were more common than major ECG abnormalities (7.7%). During a median follow-up of 28.7 months, 155 participants (3.4%) developed incident CVD. After adjusting for the study...

  2. The Significance of Land Cover Delineation on Soil Erosion Assessment. (United States)

    Efthimiou, Nikolaos; Psomiadis, Emmanouil


    The study aims to evaluate the significance of land cover delineation on soil erosion assessment. To that end, RUSLE (Revised Universal Soil Loss Equation) was implemented at the Upper Acheloos River catchment, Western Central Greece, annually and multi-annually for the period 1965-92. The model estimates soil erosion as the linear product of six factors (R, K, LS, C, and P) considering the catchment's climatic, pedological, topographic, land cover, and anthropogenic characteristics, respectively. The C factor was estimated using six alternative land use delineations of different resolution, namely the CORINE Land Cover (CLC) project (2000, 2012 versions) (1:100,000), a land use map conducted by the Greek National Agricultural Research Foundation (NAGREF) (1:20,000), a land use map conducted by the Greek Payment and Control Agency for Guidance and Guarantee Community Aid (PCAGGCA) (1:5,000), and the Landsat 8 16-day Normalized Difference Vegetation Index (NDVI) dataset (30 m/pixel) (two approximations) based on remote sensing data (satellite image acquired on 07/09/2016) (1:40,000). Since all other factors remain unchanged per each RUSLE application, the differences among the yielded results are attributed to the C factor (thus the land cover pattern) variations. Validation was made considering the convergence between simulated (modeled) and observed sediment yield. The latter was estimated based on field measurements conducted by the Greek PPC (Public Power Corporation). The model performed best at both time scales using the Landsat 8 (Eq. 13) dataset, characterized by a detailed resolution and a satisfactory categorization, allowing the identification of the most susceptible to erosion areas.

  3. Harmonized Landsat/Sentinel-2 Reflectance Products for Land Monitoring (United States)

    Masek, J. G.; Ju, J.; Claverie, M.; Vermote, E.; Dungan, J. L.; Roger, J. C.; Skakun, S.; Justice, C. O.


    Many land applications require more frequent observations than can be obtained from a single "Landsat class" sensor. Agricultural monitoring, inland water quality assessment, stand-scale phenology, and numerous other applications all require near-daily imagery at better than 1ha resolution. Thus the land science community has begun expressing a desire for a "30-meter MODIS" global monitoring capability. One cost-effective way to achieve this goal is via merging data from multiple, international observatories into a single virtual constellation. The Harmonized Landsat/Sentinel-2 (HLS) project has been working to generate a seamless surface reflectance product by combining observations from USGS/NASA Landsat-8 and ESA Sentinel-2. Harmonization in this context requires a series of radiometric and geometric transforms to create a single surface reflectance time series agnostic to sensor origin. Radiometric corrections include a common atmospheric correction using the Landsat-8 LaSRC/6S approach, a simple BRDF adjustment to constant solar and nadir view angle, and spectral bandpass adjustments to fit the Landsat-8 OLI reference. Data are then resampled to a consistent 30m UTM grid, using the Sentinel-2 global tile system. Cloud and shadow masking are also implemented. Quality assurance (QA) involves comparison of the output 30m HLS products with near-simultaneous MODIS nadir-adjusted observations. Prototoype HLS products have been processed for 7% of the global land area using the NASA Earth Exchange (NEX) compute environment at NASA Ames, and can be downloaded from the HLS web site ( A wall-to-wall North America data set is being prepared for 2018.This talk will review the objectives and status of the HLS project, and illustrate applications of high-density optical time series data for agriculture and ecology. We also discuss lessons learned from HLS in the general context of implementing virtual constellations.

  4. Estimating urban vegetation fraction across 25 cities in pan-Pacific using Landsat time series data (United States)

    Lu, Yuhao; Coops, Nicholas C.; Hermosilla, Txomin


    Urbanization globally is consistently reshaping the natural landscape to accommodate the growing human population. Urban vegetation plays a key role in moderating environmental impacts caused by urbanization and is critically important for local economic, social and cultural development. The differing patterns of human population growth, varying urban structures and development stages, results in highly varied spatial and temporal vegetation patterns particularly in the pan-Pacific region which has some of the fastest urbanization rates globally. Yet spatially-explicit temporal information on the amount and change of urban vegetation is rarely documented particularly in less developed nations. Remote sensing offers an exceptional data source and a unique perspective to map urban vegetation and change due to its consistency and ubiquitous nature. In this research, we assess the vegetation fractions of 25 cities across 12 pan-Pacific countries using annual gap-free Landsat surface reflectance products acquired from 1984 to 2012, using sub-pixel, spectral unmixing approaches. Vegetation change trends were then analyzed using Mann-Kendall statistics and Theil-Sen slope estimators. Unmixing results successfully mapped urban vegetation for pixels located in urban parks, forested mountainous regions, as well as agricultural land (correlation coefficient ranging from 0.66 to 0.77). The greatest vegetation loss from 1984 to 2012 was found in Shanghai, Tianjin, and Dalian in China. In contrast, cities including Vancouver (Canada) and Seattle (USA) showed stable vegetation trends through time. Using temporal trend analysis, our results suggest that it is possible to reduce noise and outliers caused by phenological changes particularly in cropland using dense new Landsat time series approaches. We conclude that simple yet effective approaches of unmixing Landsat time series data for assessing spatial and temporal changes of urban vegetation at regional scales can provide

  5. Modeling a historical mountain pine beetle outbreak using Landsat MSS and multiple lines of evidence (United States)

    Assal, Timothy J.; Sibold, Jason; Reich, Robin M.


    Mountain pine beetles are significant forest disturbance agents, capable of inducing widespread mortality in coniferous forests in western North America. Various remote sensing approaches have assessed the impacts of beetle outbreaks over the last two decades. However, few studies have addressed the impacts of historical mountain pine beetle outbreaks, including the 1970s event that impacted Glacier National Park. The lack of spatially explicit data on this disturbance represents both a major data gap and a critical research challenge in that wildfire has removed some of the evidence from the landscape. We utilized multiple lines of evidence to model forest canopy mortality as a proxy for outbreak severity. We incorporate historical aerial and landscape photos, aerial detection survey data, a nine-year collection of satellite imagery and abiotic data. This study presents a remote sensing based framework to (1) relate measurements of canopy mortality from fine-scale aerial photography to coarse-scale multispectral imagery and (2) classify the severity of mountain pine beetle affected areas using a temporal sequence of Landsat data and other landscape variables. We sampled canopy mortality in 261 plots from aerial photos and found that insect effects on mortality were evident in changes to the Normalized Difference Vegetation Index (NDVI) over time. We tested multiple spectral indices and found that a combination of NDVI and the green band resulted in the strongest model. We report a two-step process where we utilize a generalized least squares model to account for the large-scale variability in the data and a binary regression tree to describe the small-scale variability. The final model had a root mean square error estimate of 9.8% canopy mortality, a mean absolute error of 7.6% and an R2 of 0.82. The results demonstrate that a model of percent canopy mortality as a continuous variable can be developed to identify a gradient of mountain pine beetle severity on the

  6. Mapping the Dabus Wetlands, Ethiopia, Using Random Forest Classification of Landsat, PALSAR and Topographic Data

    Directory of Open Access Journals (Sweden)

    Pierre Dubeau


    Full Text Available The Dabus Wetland complex in the highlands of Ethiopia is within the headwaters of the Nile Basin and is home to significant ecological communities and rare or endangered species. Its many interrelated wetland types undergo seasonal and longer-term changes due to weather and climate variations as well as anthropogenic land use such as grazing and burning. Mapping and monitoring of these wetlands has not been previously undertaken due primarily to their relative isolation and lack of resources. This study investigated the potential of remote sensing based classification for mapping the primary vegetation groups in the Dabus Wetlands using a combination of dry and wet season data, including optical (Landsat spectral bands and derived vegetation and wetness indices, radar (ALOS PALSAR L-band backscatter, and elevation (SRTM derived DEM and other terrain metrics as inputs to the non-parametric Random Forest (RF classifier. Eight wetland types and three terrestrial/upland classes were mapped using field samples of observed plant community composition and structure groupings as reference information. Various tests to compare results using different RF input parameters and data types were conducted. A combination of multispectral optical, radar and topographic variables provided the best overall classification accuracy, 94.4% and 92.9% for the dry and wet season, respectively. Spectral and topographic data (radar data excluded performed nearly as well, while accuracies using only radar and topographic data were 82–89%. Relatively homogeneous classes such as Papyrus Swamps, Forested Wetland, and Wet Meadow yielded the highest accuracies while spatially complex classes such as Emergent Marsh were more difficult to accurately classify. The methods and results presented in this paper can serve as a basis for development of long-term mapping and monitoring of these and other non-forested wetlands in Ethiopia and other similar environmental settings.

  7. Thermal significance of potassium feldspar K-Ar ages inferred from /sup 40/Ar//sup 39/Ar age spectrum results

    Energy Technology Data Exchange (ETDEWEB)

    Harrison, T.M.; McDougall, I. (Australian National Univ., Canberra. Research School of Earth Sciences)


    /sup 40/Ar//sup 39/Ar age spectrum analyses of three microcline separates from the Separation Point Batholith, northwest Nelson, New Zealand, which cooled slowly through the temperature zone of partial radiogenic /sup 40/Ar accumulation are characterized by a linear age increase over the first 65 percent of gas release with the lowest ages corresponding to the time that the samples cooled below about 100/sup 0/C. The last 35 percent of /sup 39/Ar released from the microclines yields plateau ages which reflect the different bulk mineral ages, and correspond to cooling temperatures between about 130 to 160/sup 0/C. Theoretical calculations confirm the likelihood of diffusion gradients in feldspars cooling at rates =< 5/sup 0/C-Ma/sup -1/. Diffusion parameters calculated from the /sup 39/Ar release yield an activation energy, E = 28.8 +- 1.9 kcal-mol/sup -1/, and a frequency factor/grain size parameter, D/sub 0//l/sup 2/ = 5.6sub(-3.9)sup(+14) sec/sup -1/. This Arrhenius relationship corresponds to a closure temperature of 132 +- 13/sup 0/C which is very similar to the independently estimated temperature. From the observed diffusion compensation correlation, this D/sub 0//l/sup 2/ implies an average diffusion half-width of about 3, similar to the half-width of the perthite lamellae in the feldspars. The results are discussed.

  8. Clinical applicability and prognostic significance of molecular response assessed by fluorescent-PCR of immunoglobulin genes in multiple myeloma. Results from a GEM/PETHEMA study. (United States)

    Martinez-Lopez, Joaquin; Fernández-Redondo, Elena; García-Sánz, Ramón; Montalbán, María Angeles; Martínez-Sánchez, Pilar; Pavia, Bruno; Mateos, María Victoria; Rosiñol, Laura; Martín, Marisa; Ayala, Rosa; Martínez, Rafael; Blanchard, María Jesus; Alegre, Adrian; Besalduch, Joan; Bargay, Joan; Hernandez, Miguel T; Sarasquete, María Eugenia; Sanchez-Godoy, Pedro; Fernández, Manuela; Blade, Joan; San Miguel, Jesús F; Lahuerta, Juan Jose


    Minimal residual disease monitoring is becoming increasingly important in multiple myeloma (MM), but multiparameter flow cytometry (MFC) and allele-specific oligonucleotide polymerase chain reaction (ASO-PCR) techniques are not routinely available. This study investigated the prognostic influence of achieving molecular response assessed by fluorescent-PCR (F-PCR) in 130 newly diagnosed MM patients from Grupo Español Multidisciplinar de Melanoma (GEM)2000/GEM05 trials (NCT00560053, NCT00443235, NCT00464217) who achieved almost very good partial response after induction therapy. As a reference, we used the results observed with simultaneous MFC. F-PCR at diagnosis was performed on DNA using three different multiplex PCRs: IGH D-J, IGK V-J and KDE rearrangements. The applicability of F-PCR was 91·5%. After induction therapy, 64 patients achieved molecular response and 66 non-molecular response; median progression-free survival (PFS) was 61 versus 36 months, respectively (P = 0·001). Median overall survival (OS) was not reached (NR) in molecular response patients (5-year survival: 75%) versus 66 months in the non-molecular response group (P = 0·03). The corresponding PFS and OS values for patients with immunophenotypic versus non-immunophenotypic response were 67 versus 42 months (P = 0·005) and NR (5-year survival: 95%) versus 69 months (P = 0·004), respectively. F-PCR analysis is a rapid, affordable, and easily performable technique that, in some circumstances, may be a valid approach for minimal residual disease investigations in MM. © 2013 John Wiley & Sons Ltd.

  9. Alaskan resources, current development. Traditional cultural values, and the role of LANDSAT data in current and future land use management planning (United States)

    Laperriere, A. J.


    Past, present, and proposed applications of LANDSAT data for renewable resource assessments in Alaska are described. Specific projects briefly discussed include: a feasibility investigation applying LANDSAT data to caribou habitat mapping in northeast Alaska, analysis of a native corporate region in southwest Alaska, analysis of a game management unit in interior Alaska, and two proposed analyses in northwest Alaska. These analyses principally address range evaluations concerning caribou, moose, and Dall sheep, but results have application to other renewable resource themes. Application of resource assessment results to a statewide land use management plan is discussed.

  10. Preliminary classification of water areas within the Atchafalaya Basin Floodway System by using landsat imagery (United States)

    Allen, Yvonne C.; Constant, Glenn C.; Couvillion, Brady R.


    The southern portion of the Atchafalaya Basin Floodway System (ABFS) is a large area (2,571 km2) in south central Louisiana bounded on the east and west sides by a levee system. The ABFS is a sparsely populated area that includes some of the Nation's most significant extents of bottomland hardwoods, swamps, bayous, and backwater lakes, holding a rich abundance and diversity of terrestrial and aquatic species. The seasonal flow of water through the ABFS is critical to maintaining its ecological integrity. Because of strong interdependencies among species, habitat quality, and water flow in the ABFS, there is a need to better define the paths by which water moves at various stages of the hydrocycle. Although river level gages have collected a long historical record of water level variation, very little synoptic information has been available regarding the distribution and character of water at more remote locations in the basin. Most water management plans for the ABFS strive to improve water quality by increasing water flow and circulation from the main stem of the Atchafalaya River into isolated areas. To describe the distribution of land and water on a basin-wide scale, we chose to use Landsat 5 and Landsat 7 imagery to determine the extent of water distribution from 1985 to 2006 and at a variety of river stages. Because the visual signature of river water is high turbidity, we also used Landsat imagery to describe the distribution of turbid water in the ABFS. The ability to track water flow patterns by tracking turbid waters will enhance the characterization of water movement and aid in planning.

  11. [The significance of the results of crash-tests with the use of the models of the pedestrians' lower extremities for the prevention of the traffic road accidents]. (United States)

    Smirenin, S A; Fetisov, V A; Grigoryan, V G; Gusarov, A A; Kucheryavets, Yu O

    The disabling injuries inflicted during road traffic accidents (RTA) create a serious challenge for the public health services and are at the same time a major socio-economic problem in the majority of the countries throughout the world. The injuries to the lower extremities of the pedestrians make up the largest fraction of the total number of the non-lethal RTA injuries. Most of them are responsible for the considerable deterioration of the quality of life for the participants in the accidents during the subsequent period. The objective of the present study was to summarize the currently available results of experimental testing of the biomechanical models of the pedestrians' lower extremities in the framework of the program for the prevention of the road traffic accidents as proposed by the World Health Organization (WHO, 2004). The European Enhanced Safety Vehicle Committee (EEVC) has developed a series of crash-tests with the use of the models of the pedestrians' lower extremities simulating the vehicle bumper-pedestrian impact. The models are intended for the assessment of the risk of the tibia fractures and the injuries to the knee joint ligaments. The experts of EEVC proposed the biomechanical criteria for the acceleration of the knee and talocrural parts of the lower limbs as well as for the shear displacement of the knee and knee-bending angle. The engineering solution of this problem is based on numerous innovation proposals being implemented in the machine-building industry with the purpose of reducing the stiffness of structural elements of the bumper and other front components of a modern vehicle designed to protect the pedestrians from severe injuries that can be inflicted in the road traffic accidents. The activities of the public health authorities (in the first place, bureaus of forensic medical expertise and analogous facilities) have a direct bearing on the solution of the problem of control of road traffic injuries because they are possessed of

  12. Why do humans have such a prominent nose? The final result of phylogenesis: a significant reduction of the splanchocranium on account of the neurocranium. (United States)

    Mladina, Ranko; Skitarelić, Neven; Vuković, Katarina


    surrounding bones, and the other one gets more room for the further development according to human's intellectual needs. The final morphologic result of the squeezing of the splanchocranium, in fact a side-effect of these phylogenetic changes, is a protrusion of its most anterior parts more anteriorly, that is a prominent nose in humans which is a hallmark of the modern man.

  13. Land Use and Land Cover Change in Guangzhou, China, from 1998 to 2003, Based on Landsat TM /ETM+ Imagery

    Directory of Open Access Journals (Sweden)

    Yunpeng Wang


    Full Text Available Land use and land cover change is a major issue in global environment change,and is especially significant in rapidly developing regions in the world. With its economicdevelopment, population growth, and urbanization, Guangzhou, a major metropolitan inSouth China, have experienced a dramatic land use and land cover (LULC change over thepast 30 years. Fast LULC change have resulted in degradation of its ecosystems andaffected adversely the environment. It is urgently needed to monitor its LULC changes andto analyses the consequences of these changes in order to provide information for policy-makers to support sustainable development. This study employed two Landsat TM/ETM images in the dry season to detect LULC patterns in 1998 and 2003, and to examine LULCchanges during the period from 1998 to 2003. The type, rate, and pattern of the changesamong five counties of Guangzhou Municipality were analyzed in details by post-classification method. LULC conversion matrix was produced for each county in order toexplore and explain the urban expansion and cropland loss, the most significant types ofLULC change. Land use conversion matrixes of five counties were discussed respectivelyin order to explore and explain the inherence of land use change. The results showed thaturban expansion in these five counties kept an even rate of increase, while substantialamount of cropland vanished during the period. It is also noted that the conversion between cropland and orchard land was intensive. Forest land became the main source of new croplands.

  14. Generating Global Leaf Area Index from Landsat: Algorithm Formulation and Demonstration (United States)

    Ganguly, Sangram; Nemani, Ramakrishna R.; Zhang, Gong; Hashimoto, Hirofumi; Milesi, Cristina; Michaelis, Andrew; Wang, Weile; Votava, Petr; Samanta, Arindam; Melton, Forrest; hide


    This paper summarizes the implementation of a physically based algorithm for the retrieval of vegetation green Leaf Area Index (LAI) from Landsat surface reflectance data. The algorithm is based on the canopy spectral invariants theory and provides a computationally efficient way of parameterizing the Bidirectional Reflectance Factor (BRF) as a function of spatial resolution and wavelength. LAI retrievals from the application of this algorithm to aggregated Landsat surface reflectances are consistent with those of MODIS for homogeneous sites represented by different herbaceous and forest cover types. Example results illustrating the physics and performance of the algorithm suggest three key factors that influence the LAI retrieval process: 1) the atmospheric correction procedures to estimate surface reflectances; 2) the proximity of Landsatobserved surface reflectance and corresponding reflectances as characterized by the model simulation; and 3) the quality of the input land cover type in accurately delineating pure vegetated components as opposed to mixed pixels. Accounting for these factors, a pilot implementation of the LAI retrieval algorithm was demonstrated for the state of California utilizing the Global Land Survey (GLS) 2005 Landsat data archive. In a separate exercise, the performance of the LAI algorithm over California was evaluated by using the short-wave infrared band in addition to the red and near-infrared bands. Results show that the algorithm, while ingesting the short-wave infrared band, has the ability to delineate open canopies with understory effects and may provide useful information compared to a more traditional two-band retrieval. Future research will involve implementation of this algorithm at continental scales and a validation exercise will be performed in evaluating the accuracy of the 30-m LAI products at several field sites. ©

  15. Human-induced geomorphology: Modeling slope failure in Dominical, Costa Rica using Landsat imagery (United States)

    Miller, Andrew J.

    Unchecked human development has ravaged the region between Dominical and Uvita, Costa Rica. Much of the development transition has been driven by tourism and further foreign direct investment in residential, service and commercial enterprises. The resulting land-use/land-cover change has removed traditional forest cover in exchange for impervious surfaces, physical structures, and bare ground which is no longer mechanically supported by woody vegetation. Combined with a tropical climate, deeply weathered soils and lithography which are prone to erosion, land cover change has led to an increase in slope failure occurrences. Given the remoteness of the Dominical-Uvita region, its rate of growth and the lack of monitoring, new techniques for monitoring land use and slope failure susceptibility are needed. Two new indices are presented here that employ a Digital Elevation Model (DEM) and widely available Landsat imagery to assist in this endeavor. The first index, or Vegetation Influenced Landslide Index (VILI), incorporates slope derived from a DEM and Lu et al.'s (2007) Surface Cover Index to quantify vegetative cover as a means of mechanical stabilization in landslide prone areas. The second index, or Slope Multiplier Index (SMI), uses individual Landsat data bands and basic Landsat band ratios as environmental proxies to replicate soil, vegetative and hydrologic properties. Both models achieve accuracy over 70% and rival results from more complicated published literature. The accuracy of the indices was assessed with the creation of a landslide inventory developed from field observations occurring in December 2007 and November 2008. The creation of these indices represents an efficient and accurate way of determining landslide susceptibility zonation in data poor areas where environmental protection practitioners may be overextended, under-trained or both.


    Directory of Open Access Journals (Sweden)

    T. Dahms


    Full Text Available Open and free access to multi-frequent high-resolution data (e.g. Sentinel – 2 will fortify agricultural applications based on satellite data. The temporal and spatial resolution of these remote sensing datasets directly affects the applicability of remote sensing methods, for instance a robust retrieving of biophysical parameters over the entire growing season with very high geometric resolution. In this study we use machine learning methods to predict biophysical parameters, namely the fraction of absorbed photosynthetic radiation (FPAR, the leaf area index (LAI and the chlorophyll content, from high resolution remote sensing. 30 Landsat 8 OLI scenes were available in our study region in Mecklenburg-Western Pomerania, Germany. In-situ data were weekly to bi-weekly collected on 18 maize plots throughout the summer season 2015. The study aims at an optimized prediction of biophysical parameters and the identification of the best explaining spectral bands and vegetation indices. For this purpose, we used the entire in-situ dataset from 24.03.2015 to 15.10.2015. Random forest and conditional inference forests were used because of their explicit strong exploratory and predictive character. Variable importance measures allowed for analysing the relation between the biophysical parameters with respect to the spectral response, and the performance of the two approaches over the plant stock evolvement. Classical random forest regression outreached the performance of conditional inference forests, in particular when modelling the biophysical parameters over the entire growing period. For example, modelling biophysical parameters of maize for the entire vegetation period using random forests yielded: FPAR: R² = 0.85; RMSE = 0.11; LAI: R² = 0.64; RMSE = 0.9 and chlorophyll content (SPAD: R² = 0.80; RMSE=4.9. Our results demonstrate the great potential in using machine-learning methods for the interpretation of long-term multi-frequent remote sensing

  17. Modelling Biophysical Parameters of Maize Using Landsat 8 Time Series (United States)

    Dahms, Thorsten; Seissiger, Sylvia; Conrad, Christopher; Borg, Erik


    Open and free access to multi-frequent high-resolution data (e.g. Sentinel - 2) will fortify agricultural applications based on satellite data. The temporal and spatial resolution of these remote sensing datasets directly affects the applicability of remote sensing methods, for instance a robust retrieving of biophysical parameters over the entire growing season with very high geometric resolution. In this study we use machine learning methods to predict biophysical parameters, namely the fraction of absorbed photosynthetic radiation (FPAR), the leaf area index (LAI) and the chlorophyll content, from high resolution remote sensing. 30 Landsat 8 OLI scenes were available in our study region in Mecklenburg-Western Pomerania, Germany. In-situ data were weekly to bi-weekly collected on 18 maize plots throughout the summer season 2015. The study aims at an optimized prediction of biophysical parameters and the identification of the best explaining spectral bands and vegetation indices. For this purpose, we used the entire in-situ dataset from 24.03.2015 to 15.10.2015. Random forest and conditional inference forests were used because of their explicit strong exploratory and predictive character. Variable importance measures allowed for analysing the relation between the biophysical parameters with respect to the spectral response, and the performance of the two approaches over the plant stock evolvement. Classical random forest regression outreached the performance of conditional inference forests, in particular when modelling the biophysical parameters over the entire growing period. For example, modelling biophysical parameters of maize for the entire vegetation period using random forests yielded: FPAR: R² = 0.85; RMSE = 0.11; LAI: R² = 0.64; RMSE = 0.9 and chlorophyll content (SPAD): R² = 0.80; RMSE=4.9. Our results demonstrate the great potential in using machine-learning methods for the interpretation of long-term multi-frequent remote sensing datasets to model

  18. Oil exploration in Central Arabian Arch using Landsat images

    Energy Technology Data Exchange (ETDEWEB)

    Sabins, F.F. (Remote Sensing Engerprises, Inc., Fullerton, CA (United States))


    Beginning in 1988, the Chevron Remote Sensing Research Group and Aramco digitally processed and interpreted seven Landsat thematic mapper images of the Central Arabian Arch for two purposes: 1. Map geology at 1:250,000 scale; 2. Identify anomalies that may be surface expression of structural traps. The well-exposed outcrops are predominantly marine strata of Mesozoic age with regional dips to east and southeast at less than 2[degrees]. This structural setting lacks the patterns of arcuate and offset beds that characterize folds and faults in more strongly deformed terrains. Therefore we developed a model to predict the image expression of structures in this homoclinal terrain. We based the model on oil fields in the Arabian Gulf region that are drape anticlines overlying high-angle faults that offset basement rocks and Palecizoic strata. The anticlines grade upward into structural terraces caused by flattening of the regional dip. Erosion of the terraces produces subtle topographic and stratigraphic anomalies that are recognizable on the images. The model was used to interpret a number of image anomalies. We field-checked the anomalies and eliminated a few. Aramco then acquired seismic data for several of the more promising anomalies that confirmed the presence of subsurface structure. Drilling resulted in discovery of Raghib and Dilam fields that produce from the Unayzah Sandstone (Permian). Initial production in the discovery and development wells ranges from 3000 to 4300 BOPD with gravity of 44 to 46[degrees] API. The source of this high-quality oil is the Qusaiba Shale (Silurian). The new discoveries are approximately 100 km from the nearest fields. Less than two years elapsed from beginning of digital image processing to completion of the discovery wells.

  19. Oil exploration in Central Arabian Arch using Landsat images

    Energy Technology Data Exchange (ETDEWEB)

    Sabins, F.F. [Remote Sensing Engerprises, Inc., Fullerton, CA (United States)


    Beginning in 1988, the Chevron Remote Sensing Research Group and Aramco digitally processed and interpreted seven Landsat thematic mapper images of the Central Arabian Arch for two purposes: 1. Map geology at 1:250,000 scale; 2. Identify anomalies that may be surface expression of structural traps. The well-exposed outcrops are predominantly marine strata of Mesozoic age with regional dips to east and southeast at less than 2{degrees}. This structural setting lacks the patterns of arcuate and offset beds that characterize folds and faults in more strongly deformed terrains. Therefore we developed a model to predict the image expression of structures in this homoclinal terrain. We based the model on oil fields in the Arabian Gulf region that are drape anticlines overlying high-angle faults that offset basement rocks and Palecizoic strata. The anticlines grade upward into structural terraces caused by flattening of the regional dip. Erosion of the terraces produces subtle topographic and stratigraphic anomalies that are recognizable on the images. The model was used to interpret a number of image anomalies. We field-checked the anomalies and eliminated a few. Aramco then acquired seismic data for several of the more promising anomalies that confirmed the presence of subsurface structure. Drilling resulted in discovery of Raghib and Dilam fields that produce from the Unayzah Sandstone (Permian). Initial production in the discovery and development wells ranges from 3000 to 4300 BOPD with gravity of 44 to 46{degrees} API. The source of this high-quality oil is the Qusaiba Shale (Silurian). The new discoveries are approximately 100 km from the nearest fields. Less than two years elapsed from beginning of digital image processing to completion of the discovery wells.

  20. The application of LANDSAT remote sensing technology to natural resources management. Section 1: Introduction to VICAR - Image classification module. Section 2: Forest resource assessment of Humboldt County. (United States)

    Fox, L., III (Principal Investigator); Mayer, K. E.


    A teaching module on image classification procedures using the VICAR computer software package was developed to optimize the training benefits for users of the VICAR programs. The field test of the module is discussed. An intensive forest land inventory strategy was developed for Humboldt County. The results indicate that LANDSAT data can be computer classified to yield site specific forest resource information with high accuracy (82%). The "Douglas-fir 80%" category was found to cover approximately 21% of the county and "Mixed Conifer 80%" covering about 13%. The "Redwood 80%" resource category, which represented dense old growth trees as well as large second growth, comprised 4.0% of the total vegetation mosaic. Furthermore, the "Brush" and "Brush-Regeneration" categories were found to be a significant part of the vegetative community, with area estimates of 9.4 and 10.0%.

  1. 55-year (1960-2015) spatiotemporal shoreline change analysis using historical DISP and Landsat time series data in Shanghai (United States)

    Qiao, Gang; Mi, Huan; Wang, Weian; Tong, Xiaohua; Li, Zhongbin; Li, Tan; Liu, Shijie; Hong, Yang


    Shoreline change has been an increasing concern for low-lying and vulnerable coastal zones worldwide, especially in estuarine delta regions, which generally have significant economic development, large human settlements and infrastructures. Thus, long time-series shoreline change data are useful for understanding how shorelines respond to natural and anthropogenic activities, as well as for providing greater insights into coastal protection and sustainable development in the future. For the first time, this study analyzes 55 years of spatiotemporal shoreline changes in Shanghai, China, by integrating the historical Declassified Intelligence Satellite Photography (DISP) and Landsat time series data at five-year intervals from 1960 to 2015. Twelve shorelines were interpreted from DISP and Landsat images. The spatiotemporal changes in the shorelines were explored at five-year intervals within the study period for the Shanghai mainland and islands. The results indicate that shorelines in Shanghai accreted significantly over the last 55 years, but different accretion patterns were observed in Chongming Dongtan. The rate of shoreline change varied in different areas, and the most noticeable expansions were Chongming Beitan, Chongming Dongtan, Hengsha Dongtan, and Nanhuizui. The length of the entire shoreline increased by 25.7% from 472.6 km in 1960 to 594.2 km in 2015. Due to the shoreline changes, the Shanghai area expanded by 1,192.5 km2 by 2015, which was an increase of 19.9% relative to its 1960 area. The Digital Shoreline Analysis System (DSAS) was used to compute rate-of-change statistics. Between 1960 and 2015, 10.6% of the total transects exceeded 3 km of Net Shoreline Movement (NSM), with a maximum value of approximately 20 km at eastern Hengsha Island. The average Weighted Linear Regression Rate (WLR) of the Shanghai shoreline was 52.2 m/yr from 1960 to 2015; there was 94.1% accretion, 3.1% erosion, and 2.8% with no significant change. In addition, the driving


    Directory of Open Access Journals (Sweden)

    Elias Fernando Berra


    Full Text Available relating spectral answers with biophysical parameters aim estimate variables, like wood volume, without the necessity of frequent field measurements. The objective was to develop models to estimate wood volume by Landsat 5 TM images, supported by regional forest inventory data. The image was geo-referenced and converted to spectral reflectance. After, the images-index NDVI (Normalized Difference Vegetation Index and SR (Simple Ratio was generated. The reflectance values of the bands (TM1, TM2, TM3 e TM4 and of the indices (NDVI and SR was related with the wood volume. The biggest correlation with volume was with the NDVI and SR indices. The variables selection was made by Stepwise method, which returned three regression models as significant to explain the variation in volume. Finally, the best fitted model was selected (volume = -830,95 + 46,05 (SR + 107,47 (TM2, which was applied on the Landsat image where the pixels had started to represent the estimated volume in m³/ha on the Eucalyptus sp. production units. This model, significant at 95% confidence level, explains 68% of the wood volume variation.

  3. A procedure used for a ground truth study of a land use map of North Alabama generated from LANDSAT data (United States)

    Downs, S. W., Jr.; Sharma, G. C.; Bagwell, C.


    A land use map of a five county area in North Alabama was generated from LANDSAT data using a supervised classification algorithm. There was good overall agreement between the land use designated and known conditions, but there were also obvious discrepancies. In ground checking the map, two types of errors were encountered - shift and misclassification - and a method was developed to eliminate or greatly reduce the errors. Randomly selected study areas containing 2,525 pixels were analyzed. Overall, 76.3 percent of the pixels were correctly classified. A contingency coefficient of correlation was calculated to be 0.7 which is significant at the alpha = 0.01 level. The land use maps generated by computers from LANDSAT data are useful for overall land use by regional agencies. However, care must be used when making detailed analysis of small areas. The procedure used for conducting the ground truth study together with data from representative study areas is presented.

  4. Mapping Impervious Surfaces Globally at 30m Resolution Using Landsat Global Land Survey Data (United States)

    Brown de Colstoun, E.; Huang, C.; Wolfe, R. E.; Tan, B.; Tilton, J.; Smith, S.; Phillips, J.; Wang, P.; Ling, P.; Zhan, J.; Xu, X.; Taylor, M. P.


    Impervious surfaces, mainly artificial structures and roads, cover less than 1% of the world's land surface (1.3% over USA). Regardless of the relatively small coverage, impervious surfaces have a significant impact on the environment. They are the main source of the urban heat island effect, and affect not only the energy balance, but also hydrology and carbon cycling, and both land and aquatic ecosystem services. In the last several decades, the pace of converting natural land surface to impervious surfaces has increased. Quantitatively monitoring the growth of impervious surface expansion and associated urbanization has become a priority topic across both the physical and social sciences. The recent availability of consistent, global scale data sets at 30m resolution such as the Global Land Survey from the Landsat satellites provides an unprecedented opportunity to map global impervious cover and urbanization at this resolution for the first time, with unprecedented detail and accuracy. Moreover, the spatial resolution of Landsat is absolutely essential to accurately resolve urban targets such a buildings, roads and parking lots. With long term GLS data now available for the 1975, 1990, 2000, 2005 and 2010 time periods, the land cover/use changes due to urbanization can now be quantified at this spatial scale as well. In the Global Land Survey - Imperviousness Mapping Project (GLS-IMP), we are producing the first global 30 m spatial resolution impervious cover data set. We have processed the GLS 2010 data set to surface reflectance (8500+ TM and ETM+ scenes) and are using a supervised classification method using a regression tree to produce continental scale impervious cover data sets. A very large set of accurate training samples is the key to the supervised classifications and is being derived through the interpretation of high spatial resolution (~2 m or less) commercial satellite data (Quickbird and Worldview2) available to us through the unclassified

  5. A Harmonized Landsat-Sentinel-2 Surface Reflectance product: a resource for Agricultural Monitoring (United States)

    Masek, J. G.; Claverie, M.; Ju, J.; Vermote, E.; Justice, C. O.


    The combination of Landsat and Sentinel-2 data offers a unique opportunity to observe globally the land every 2-3 days at medium (reflectance data from Landsat and Sentinel-2 missions and to deliver them to the community in a combined, seamless form. The HLS will be beneficial for global agricultural monitoring applications that require medium spatial resolution and weekly or more frequent observations. In particular, the provided opportunity to track crop phenology at the scale of individual fields will support detailed mapping of crop type and type-specific vegetation conditions. To create a compatible set of radiometric measurements, the HLS product relies on rigorous pre- and post-launch cross-calibration (Landsat-8 OLI and Sentinel-2 MSI) activities. The processing chain includes the following components: atmospheric correction, cloud/shadow masking, nadir BRDF-adjustment, spectral-adjustment, regridding, and temporal composite. The atmospheric correction and cloud masking is based on the OLI atmospheric correction developed at NASA-GSFC and has been adapted to the MSI data. The BRDF-adjustment is based on a disaggregation technique using MODIS-based BRDF coefficients. The technique has been evaluated using the multi-angular acquisition from the SPOT 4 and 5 (Take5) experiments. The spectral-adjustment relies on a linear regression that has been calibrated and evaluated using synthetic data and surface reflectance processed from a large number of hyperspectral EO-1 Hyperion scenes. Finally, significant effort is placed on product validation and evaluation. The delivered data set will include surface reflectance products at different levels: Using the native gridding, i.e. UTM, 30m for Landsat-8, and UTM, 10-20m for Sentinel-2 Using a common global gridding (Sinusoidal, 30m) Temporal composite (Sinusoidal, 30m, 5-day) During the first year of operation of Sentinel-2A, the HLS will be prototyped over a selection of 30 sites that includes some of the JECAM sites

  6. Evaluation of LANDSAT-2 (ERTS) images applied to geologic structures and mineral resources of South America (United States)

    Carter, W. D. (Principal Investigator)


    The author has identified the following significant results. Work with the Image 100 clearly demonstrates that radiance values of LANDSAT data can be used for correlation of geologic formations across international boundaries. The Totora Formation of the Corocoro Group of Tertiary age was traced from known outcrops near Tiahuanaco, Bolivia, along the south side of Lake Titicaca westward into Peru where the same rocks are considered to be Cretaceous in age. This inconsistency suggests: (1) that a review of this formation is needed by joint geological surveys of both countries to determine similarities, differences, and the true age; (2) that recognition of the extension of the copper-bearing Totora Formation of Bolivia into Peru may provide Peru with a new target for exploration. Equal radiance maps made by use of the Image 100 system show as many as eight different units within salar deposits (salt flats) of the Bolivian Altiplano. Standard film processed images show them as nearly uniform areas of white because of lack of dynamic range in film products. The Image 100 system, therefore, appears to be of great assistance in subdividing the salt flats on the basis of moisture distribution, surface roughness, and distribution of windblown materials. Field work is needed to determine these relationships to mineral composition and distribution. Images representing seasonal changes should also improve the accuracy of such maps. Radiance values of alteration zones related to the occurrence of porphyry copper ores were measured at the San Juan del Abra deposit of northern Chile using the Image 100 system. The extent to which these same values may be used to detect similar alteration zones in other areas has not yet been tested.

  7. Examining the Capability of Supervised Machine Learning Classifiers in Extracting Flooded Areas from Landsat TM Imagery: A Case Study from a Mediterranean Flood

    Directory of Open Access Journals (Sweden)

    Gareth Ireland


    Full Text Available This study explored the capability of Support Vector Machines (SVMs and regularised kernel Fisher’s discriminant analysis (rkFDA machine learning supervised classifiers in extracting flooded area from optical Landsat TM imagery. The ability of both techniques was evaluated using a case study of a riverine flood event in 2010 in a heterogeneous Mediterranean region, for which TM imagery acquired shortly after the flood event was available. For the two classifiers, both linear and non-linear (kernel versions were utilised in their implementation. The ability of the different classifiers to map the flooded area extent was assessed on the basis of classification accuracy assessment metrics. Results showed that rkFDA outperformed SVMs in terms of accurate flooded pixels detection, also producing fewer missed detections of the flooded area. Yet, SVMs showed less false flooded area detections. Overall, the non-linear rkFDA classification method was the more accurate of the two techniques (OA = 96.23%, K = 0.877. Both methods outperformed the standard Normalized Difference Water Index (NDWI thresholding (OA = 94.63, K = 0.818 by roughly 0.06 K points. Although overall accuracy results for the rkFDA and SVMs classifications only showed a somewhat minor improvement on the overall accuracy exhibited by the NDWI thresholding, notably both classifiers considerably outperformed the thresholding algorithm in other specific accuracy measures (e.g. producer accuracy for the “not flooded” class was ~10.5% less accurate for the NDWI thresholding algorithm in comparison to the classifiers, and average per-class accuracy was ~5% less accurate than the machine learning models. This study provides evidence of the successful application of supervised machine learning for classifying flooded areas in Landsat imagery, where few studies so far exist in this direction. Considering that Landsat data is open access and has global coverage, the results of this study

  8. Landsat 9 OLI 2 focal plane subsystem: design, performance, and status (United States)

    Malone, Kevin J.; Schrein, Ronald J.; Bradley, M. Scott; Irwin, Ronda; Berdanier, Barry; Donley, Eric


    The Landsat 9 mission will continue the legacy of Earth remote sensing that started in 1972. The Operational Land Imager 2 (OLI 2) is one of two instruments on the Landsat 9 satellite. The OLI 2 instrument is essentially a copy of the OLI instrument flying on Landsat 8. A key element of the OLI 2 instrument is the focal plane subsystem, or FPS, which consists of the focal plane array (FPA), the focal plane electronics (FPE) box, and low-thermal conductivity cables. This paper presents design details of the OLI 2 FPS. The FPA contains 14 critically-aligned focal plane modules (FPM). Each module contains 6 visible/near-IR (VNIR) detector arrays and three short-wave infrared (SWIR) arrays. A complex multi-spectral optical filter is contained in each module. Redundant pixels for each array provide exceptional operability. Spare detector modules from OLI were recharacterized after six years of storage. Radiometric test results are presented and compared with data recorded in 2010. Thermal, optical, mechanical and structural features of the FPA will be described. Special attention is paid to the thermal design of the FPA since thermal stability is crucial to ensuring low-noise and low-drift operation of the detectors which operate at -63°C. The OLI 2 FPE provides power, timing, and control to the focal plane modules. It also digitizes the video data and formats it for the solid-state recorder. Design improvements to the FPA-FPE cables will be discussed and characterization data will be presented. The paper will conclude with the status of the flight hardware assembly and testing.

  9. High Resolution Mapping of Drought Impacts on Small Waterbodies using Sentinel 1 SAR and Landsat Observations (United States)

    Slinski, K.; Hogue, T. S.; McCray, J. E.


    Drought in semi-arid areas can have substantial impact on ephemeral and small water bodies, which provide critical ecological habitat and have important socio-economic value. This is particularly true in the pastoral areas of East Africa, where these ecosystems provide local communities with water for human and animal consumption and pasture for livestock. However, monitoring the impact of drought on ephemeral and small water bodies in East Africa is challenging because of sparse in situ observational systems. Satellite remote sensing observations have been shown to be a viable option for monitoring surface water change in data-poor regions. Landsat data is widely used to detect open water, but the use of Landsat data in small waterbody studies is limited by its 30-meter spatial resolution. New remote sensing-based tools are necessary to better understand the vulnerability of ephemeral and small waterbodies in semi-arid areas to drought and to monitor drought impacts. This study combines Landsat and Sentinel 1 SAR observations to create a series of monthly waterbody maps over the Awash River basin in Ethiopia depicting the change in surface water from October 2014 to March 2017. The study time period corresponds with a major drought event in the area. Waterbody maps were generated using a 10-meter resolution and utilized to monitor drought impacts on ephemeral and small waterbodies in the Awash River basin over the course of the drought event. Initial results show that surface waterbodies in the lower catchments of the Awash basin were more severely impacted by the drought event than the upper catchments. It is anticipated that the new information provided by this tool will inform decisions affecting the water, energy, agriculture and other sectors in East Africa reliant on water resources, enabling water authorities to better manage future drought events.

  10. Volcano stratigraphy interpretation of Mamuju area based on Landsat-8 imagery analysis

    International Nuclear Information System (INIS)

    Frederikus Dian Indrastomo; I Gde Sukadana; Dhatu Kamajati; Asep Saepuloh; Agus Handoyo Harsolumakso


    Mamuju and its surrounding area are constructed mainly by volcanic rocks. Volcanoclastic sedimentary rocks and limestones are laid above the volcanic rocks. Volcanic activities create some unique morphologies such as craters, lava domes, and pyroclastic flow paths as their volcanic products. These products are identified from their circular features characters on Landsat-8 imagery. Geometric and atmospheric corrections had been done, a visual interpretation on Landsat-8 imagery was conducted to identify structure, geomorphology, and geological condition of the area. Regional geological structures show trend to southeast – northwest direction which is affects the formation of Adang volcano. Geomorphology of the area are classified into 16 geomorphology units based on their genetic aspects, i.e Sumare fault block ridge, Mamuju cuesta ridge, Adang eruption crater, Labuhan Ranau eruption crater, Sumare eruption crater, Ampalas volcanic cone, Adang lava dome, Labuhan Ranau intrusion hill, Adang pyroclastic flow ridge, Sumare pyroclastic flow ridge, Adang volcanic remnant hills, Malunda volcanic remnant hills, Talaya volcanic remnant hills, Tapalang karst hills, Mamuju alluvium plains, and Karampuang reef terrace plains. Based on the Landsat-8 imagery interpretation result and field confirmation, the geology of Mamuju area is divided into volcanic rocks and sedimentary rocks. There are two groups of volcanic rocks; Talaya complex and Mamuju complex. The Talaya complex consists of Mambi, Malunda, and Kalukku volcanic rocks with andesitic composition, while Mamuju complex consist of Botteng, Ahu, Tapalang, Adang, Ampalas, Sumare, and Labuhan Ranau volcanic rocks with andesite to leucitic basalt composition. The volcano stratigraphy of Mamuju area was constructed based on its structure, geomorphology and lithology distribution analysis. Volcano stratigraphy of Mamuju area is classified into Khuluk Talaya and Khuluk Mamuju. The Khuluk Talaya consists of Gumuk Mambi, Gumuk

  11. Analysis of the Relationship between Land Surface Temperature and Wildfire Severity in a Series of Landsat Images

    Directory of Open Access Journals (Sweden)

    Lidia Vlassova


    Full Text Available The paper assesses spatio-temporal patterns of land surface temperature (LST and fire severity in the Las Hurdes wildfire of Pinus pinaster forest, which occurred in July 2009, in Extremadura (Spain, from a time series of fifteen Landsat 5 TM images corresponding to 27 post-fire months. The differenced Normalized Burn Ratio (dNBR was used to evaluate burn severity. The mono-window algorithm was applied to estimate LST from the Landsat thermal band. The burned zones underwent a significant increase in LST after fire. Statistically significant differences have been detected between the LST within regions of burn severity categories. More substantial changes in LST are observed in zones of greater fire severity, which can be explained by the lower emissivity of combustion products found in the burned area and changes in the energy balance related to vegetation removal. As time progresses over the 27 months after fire, LST differences decrease due to vegetation regeneration. The differences in LST and Normalized Difference Vegetation Index (NDVI values between burn severity categories in each image are highly correlated (r = 0.84. Spatial patterns of severity and post-fire LST obtained from Landsat time series enable an evaluation of the relationship between these variables to predict the natural dynamics of burned areas.

  12. Perspective View with Landsat Overlay, Salt Lake City, Utah (United States)


    Most of the population of Utah lives just west of the Wasatch Mountains in the north central part of the state. This broad east-northeastward view shows that region with the cities of Ogden, Salt Lake City, and Provo seen from left to right. The Great Salt Lake (left) and Utah Lake (right) are quite shallow and appear greenish in this enhanced natural color view. Thousands of years ago ancient Lake Bonneville covered all of the lowlands seen here. Its former shoreline is clearly seen as a wave-cut bench and/or light colored 'bathtub ring' at several places along the base of the mountain front - evidence seen from space of our ever-changing planet.This 3-D perspective view was generated using topographic data from the Shuttle Radar Topography Mission (SRTM), a Landsat 5 satellite image mosaic, and a false sky. Topographic expression is exaggerated four times.Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter (98-foot) resolution of most Landsat images and will substantially help in analyzing the large and growing Landsat image archive, managed by the U.S. Geological Survey (USGS).Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on Feb. 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. SRTM was designed to collect 3-D measurements of the Earth's surface. To collect the 3-D data, engineers added a 60-meter (approximately 200-foot) mast, installed additional C-band and X-band antennas, and improved tracking and navigation devices. The mission is a cooperative project between NASA, the National Imagery and Mapping Agency (NIMA) of the U.S. Department of Defense and the German and Italian space agencies. It is managed by NASA's Jet Propulsion Laboratory, Pasadena, Calif


    Directory of Open Access Journals (Sweden)

    F. Bayat


    on board on previous Landsat sensors. Third, TIRS is one of the best space born and high spatial resolution with 30 m. in this regards, Landsat-8 can use the Split-Window (SW algorithm for retrieving SST dataset. Although several SWs have been developed to use with other sensors, some adaptations are required in order to implement them for the TIRS spectral bands. Therefore, the objective of this paper is to develop a SW, adapted for use with Landsat-8 TIRS data, along with its accuracy assessment. In this research, that has been done for modelling SST using thermal Landsat 8-imagery of the Persian Gulf. Therefore, by incorporating contemporary in situ data and SST map estimated from other sensors like MODIS, we examine our proposed method with coefficient of determination (R2 and root mean square error (RMSE on check point to model SST retrieval for Landsat-8 imagery. Extracted results for implementing different SW's clearly shows superiority of utilized method by R2 = 0.95 and RMSE = 0.24.

  14. Regional crop gross primary production and yield estimation using fused Landsat-MODIS data (United States)

    He, M.; Kimball, J. S.; Maneta, M. P.; Maxwell, B. D.; Moreno, A.


    Accurate crop yield assessments using satellite-based remote sensing are of interest for the design of regional policies that promote agricultural resiliency and food security. However, the application of current vegetation productivity algorithms derived from global satellite observations are generally too coarse to capture cropland heterogeneity. Merging information from sensors with reciprocal spatial and temporal resolution can improve the accuracy of these retrievals. In this study, we estimate annual crop yields for seven important crop types -alfalfa, barley, corn, durum wheat, peas, spring wheat and winter wheat over Montana, United States (U.S.) from 2008 to 2015. Yields are estimated as the product of gross primary production (GPP) and a crop-specific harvest index (HI) at 30 m spatial resolution. To calculate GPP we used a modified form of the MOD17 LUE algorithm driven by a 30 m 8-day fused NDVI dataset constructed by blending Landsat (5 or 7) and MODIS Terra reflectance data. The fused 30-m NDVI record shows good consistency with the original Landsat and MODIS data, but provides better spatiotemporal information on cropland vegetation growth. The resulting GPP estimates capture characteristic cropland patterns and seasonal variations, while the estimated annual 30 m crop yield results correspond favorably with county-level crop yield data (r=0.96, pcrop yield performance was generally lower, but still favorable in relation to field-scale crop yield surveys (r=0.42, p<0.01). Our methods and results are suitable for operational applications at regional scales.

  15. Assessing and mapping the severity of soil erosion using the 30-m Landsat multispectral satellite data in the former South African homelands of Transkei (United States)

    Seutloali, Khoboso E.; Dube, Timothy; Mutanga, Onisimo


    Soil erosion is increasingly recognised as the principal cause of land degradation, loss of agricultural land area and siltation of surrounding water waterbodies. Accurate and up-to-date soil erosion mapping is key in understanding its severity if these negative impacts are to be minimised and affected areas rehabilitated. The aim of this work was to map the severity of soil erosion, based on the 30-m Landsat series multispectral satellite data in the former South African homelands of Transkei between the year 1994 and 2010. Further, the study assessed if the observed soil erosion trends and morphology that existed in this area could be explained by biophysical factors (i.e. slope, stream erosivity, topographic wetness index) retrieved from the 30-m ASTER Digital Elevation Model (DEM). The results of this study indicate that the Transkei region experiences varying erosion levels from moderate to very severe. The large portion of the land area under the former homelands was largely affected by rill erosion with approximately 74% occurring in the year 1984 and 54% in 2010. The results also revealed specific thresholds of soil erosion drivers. These include steeper areas (≥30°), high stream power index greater than 2.0 (stream erosivity), relatively lower vegetation cover (≤15%) and low topographic wetness index (≤5%). The results of this work demonstrate the severity of soil erosion in the Southern African former homelands of Transkei for the year 1984 and 2010. Additionally, this work has demonstrated the significance of the 30-m Landsat multispectral sensor in examining soil erosion occurrence at a regional scale where in-depth field work still remains a challenging task.

  16. Landsat Data Continuity Mission (LDCM) Standard Product Generation and Characteristics (United States)

    Micijevic, E.; Hayes, R.


    The LDCM's Landsat 8 (L8), planned for launch in February 2013, is the latest satellite in the 40 year history of the Landsat program. The satellite will have two imagers: the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). The data from both sensors will be processed and combined into the final Level 1 Terrain (L1T) standard product by the Landsat Product Generation System (LPGS) at the USGS Earth Resources Observation and Science (EROS). Landsat 8 products will nominally have 11 image bands; however, products will still be created if OLI only, or TIRS only collections are acquired. The LPGS is designed to create L1T products from Level 0 data by merging OLI and TIRS outputs and performing systematic radiometric and geometric corrections, followed by precision and terrain corrections that include Ground Control Points (GCP), and a Digital Elevation Model (DEM) for topographic accuracy. Scenes that have a quality score of 9 or greater and a percent cloud cover less than 40 will be automatically processed. In addition, any archived scene, regardless of cloud cover, can be requested for processing through USGS EROS clients, GloVis or Earth Explorer. While most data will be processed as Level L1T, some scenes will not have ground control or elevation data necessary for precision or terrain correction, respectively. In these cases, the best level of correction will be applied (Level 1G-systematic or Level 1Gt-systematic terrain). The standard Level 1T products will contain scaled Top of Atmosphere (TOA) reflectance data, only for OLI. The conversion between radiance and reflectance within radiometric processing (L1R) will be performed using the band specific coefficients that are proportional to the respective exoatmospheric solar irradiances and the Earth-Sun distance for the scene's acquisition day. The TIRS data will contain scaled at-sensor radiances and no at-sensor brightness temperature or emissivity conversions are planned. For users that

  17. Techniques for land use change detection using Landsat imagery (United States)

    Angelici, G. L.; Bryant, N. A.; Friedman, S. Z.


    A variety of procedures were developed for the delineation of areas of land use change using Landsat Multispectral Scanner data and the generation of statistics revealing the nature of the changes involved (i.e., number of acres changed from rural to urban). Techniques of the Image Based Information System were utilized in all stages of the procedure, from logging the Landsat data and registering two frames of imagery, to extracting the changed areas and printing tabulations of land use change in acres. Two alternative methods of delineating land use change are presented while enumerating the steps of the entire process. The Houston, Texas urban area, and the Orlando, Florida urban area, are used as illustrative examples of various procedures.

  18. Space science for applications - The history of Landsat (United States)

    Mach, P. E.


    The history of the Landsat project is discussed in terms of three historical phases, each characterized by a dominant problem. From 1964 to 1967, the challenge was to develop interagency cooperation and to achieve consensus on basic plans for the satellite. Between 1968 and 1971, the cooperating agencies had to persuade the Bureau of the Budget to provide funding for the project. Since 1972, the challenge to NASA has been to encourage applications of the Landsat data and plan the shift from an experimental program to an operational one. The tension between experimental and operational goals has run through all these phases, and the conflicts between agencies is detailed, as well as the interaction between technological and political systems.

  19. Agricultural crop mapping and classification by Landsat images to evaluate water use in the Lake Urmia basin, North-west Iran (United States)

    Fazel, Nasim; Norouzi, Hamid; Madani, Kaveh; Kløve, Bjørn


    Lake Urmia, once one of the largest hypersaline lakes in the world has lost more than 90% of its surface body mainly due to the intensive expansion of agriculture, using more than 90% of all water in the region. Access to accurate and up-to-date information on the extent and distribution of individual crop types, associated with land use changes and practices, has significant value in intensively agricultural regions. Explicit information of croplands can be useful for sustainable water resources, land and agriculture planning and management. Remote sensing, has been proven to be a more cost-effective alternative to the traditional statistically-based ground surveys for crop coverage areas that are costly and provide insufficient information. Satellite images along with ground surveys can provide the necessary information of spatial coverage and spectral responses of croplands for sustainable agricultural management. This study strives to differentiate different crop types and agricultural practices to achieve a higher detailed crop map of the Lake Urmia basin. The mapping approach consists of a two-stage supervised classification of multi-temporal multi-spectral high resolution images obtained from Landsat imagery archive. Irrigated and non-irrigated croplands and orchards were separated from other major land covers (urban, ranges, bare-lands, and water) in the region by means of maximum Likelihood supervised classification method. The field data collected during 2015 and land use maps generated in 2007 and Google Earth comparisons were used to form a training data set to perform the supervised classification. In the second stage, non-agricultural lands were masked and the supervised classification was applied on the Landsat images stack to identify seven major croplands in the region (wheat and barley, beetroot, corn, sunflower, alfalfa, vineyards, and apple orchards). The obtained results can be of significant value to the Urmia Lake restoration efforts which

  20. Subpixel Inundation Mapping Using Landsat-8 OLI and UAV Data for a Wetland Region on the Zoige Plateau, China

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    Haoming Xia


    Full Text Available Wetland inundation is crucial to the survival and prosperity of fauna and flora communities in wetland ecosystems. Even small changes in surface inundation may result in a substantial impact on the wetland ecosystem characteristics and function. This study presented a novel method for wetland inundation mapping at a subpixel scale in a typical wetland region on the Zoige Plateau, northeast Tibetan Plateau, China, by combining use of an unmanned aerial vehicle (UAV and Landsat-8 Operational Land Imager (OLI data. A reference subpixel inundation percentage (SIP map at a Landsat-8 OLI 30 m pixel scale was first generated using high resolution UAV data (0.16 m. The reference SIP map and Landsat-8 OLI imagery were then used to develop SIP estimation models using three different retrieval methods (Linear spectral unmixing (LSU, Artificial neural networks (ANN, and Regression tree (RT. Based on observations from 2014, the estimation results indicated that the estimation model developed with RT method could provide the best fitting results for the mapping wetland SIP (R2 = 0.933, RMSE = 8.73% compared to the other two methods. The proposed model with RT method was validated with observations from 2013, and the estimated SIP was highly correlated with the reference SIP, with an R2 of 0.986 and an RMSE of 9.84%. This study highlighted the value of high resolution UAV data and globally and freely available Landsat data in combination with the developed approach for monitoring finely gradual inundation change patterns in wetland ecosystems.

  1. Estimation on rubber tree disturbance caused by typhoon Damery (200518) with Landsat and MODIS data in Hainan Island of China (United States)

    Tan, Chenyan; Fang, Weihua; Li, Jian


    In 2005, Typhoon Damery (200518) caused severe damage to the rubber trees in Hainan Island with its destructive winds and rainfall. Selection of proper vegetation indices using multi-source remote sensing data is critical to the assessment of forest disturbance and damage loss for this event. In this study, we will compare the performance of seven vegetation indices derived from MODIS and Landsat TM imageries prior to and after typhoon Damery, in order to select an optimal index for identifying rubber tree disturbance. The indices to be compared are normalized difference vegetation index (NDVI), Normalized Difference Water Index (NDWI), Normalized Difference Infrared Index (NDII), Enhanced vegetation index (EVI), Leaf area index (LAI), forest z-score (IFZ), and Disturbance Index (DI). The ground truth data of rubber tree damage collected through field investigation was used to verify and compare the results. Our preliminary result for the area with ground-truth data shows that DI has the most significant performance for disturbance detection for this typhoon event. This index DI is then applied to all the areas in Hainan Island hit by Darmey to evaluate the overall forest damage severity. At last, rubber tree damage severity is analyzed with other typhoon hazard factors such as wind, topography, soil and precipitation.

  2. Examining spectral properties of Landsat 8 OLI for predicting above-ground carbon of Labanan Forest, Berau (United States)

    Suhardiman, A.; Tampubolon, B. A.; Sumaryono, M.


    Many studies revealed significant correlation between satellite image properties and forest data attributes such as stand volume, biomass or carbon stock. However, further study is still relevant due to advancement of remote sensing technology as well as improvement on methods of data analysis. In this study, the properties of three vegetation indices derived from Landsat 8 OLI were tested upon above-ground carbon stock data from 50 circular sample plots (30-meter radius) from ground survey in PT. Inhutani I forest concession in Labanan, Berau, East Kalimantan. Correlation analysis using Pearson method exhibited a promising results when the coefficient of correlation (r-value) was higher than 0.5. Further regression analysis was carried out to develop mathematical model describing the correlation between sample plots data and vegetation index image using various mathematical models.Power and exponential model were demonstrated a good result for all vegetation indices. In order to choose the most adequate mathematical model for predicting Above-ground Carbon (AGC), the Bayesian Information Criterion (BIC) was applied. The lowest BIC value (i.e. -376.41) shown by Transformed Vegetation Index (TVI) indicates this formula, AGC = 9.608*TVI21.54, is the best predictor of AGC of study area.

  3. Uma biblioteca de pontos de controle para imagens MSS Landsat


    Fernando Augusto Mitsuo Ii


    O objetivo deste trabalho e desenvolver um sistema para criacao, manutencao e gerenciamento de uma biblioteca de pontos de controle para imagens MSS Landsat. Um ponto de controle e uma caracteristica fisicamente detectavel numa cena, cuja localizacao geodesica e precisamente conhecida. O uso destes pontos e de fundamental importancia num sistema de correcao geometrica de imagens de satelite. A biblioteca permitira que pontos de controle pertencentes a uma dada cena sejam recuperados de uma ma...

  4. Research and development of LANDSAT-based crop inventory techniques (United States)

    Horvath, R.; Cicone, R. C.; Malila, W. A. (Principal Investigator)


    A wide spectrum of technology pertaining to the inventory of crops using LANDSAT without in situ training data is addressed. Methods considered include Bayesian based through-the-season methods, estimation technology based on analytical profile fitting methods, and expert-based computer aided methods. Although the research was conducted using U.S. data, the adaptation of the technology to the Southern Hemisphere, especially Argentina was considered.

  5. Near Real-Time Browsable Landsat-8 Imagery

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    Cheng-Chien Liu


    Full Text Available The successful launch and operation of Landsat-8 extends the remarkable 40-year acquisition of space-based land remote-sensing data. To respond quickly to emergency needs, real-time data are directly downlinked to 17 ground stations across the world on a routine basis. With a size of approximately 1 Gb per scene, however, the standard level-1 product provided by these stations is not able to serve the general public. Users would like to browse the most up-to-date and historical images of their regions of interest (ROI at full-resolution from all kinds of devices without the need for tedious data downloading, decompressing, and processing. This paper reports on the Landsat-8 automatic image processing system (L-8 AIPS that incorporates the function of mask developed by United States Geological Survey (USGS, the pan-sharpening technique of spectral summation intensity modulation, the adaptive contrast enhancement technique, as well as the Openlayers and Google Maps/Earth compatible superoverlay technique. Operation of L-8 AIPS enables the most up-to-date Landsat-8 images of Taiwan to be browsed with a clear contrast enhancement regardless of the cloud condition, and in only one hour’s time after receiving the raw data from the USGS Level 1 Product Generation System (LPGS. For any ROI in Taiwan, all historical Landsat-8 images can also be quickly viewed in time series at full resolution (15 m. The debris flow triggered by Typhoon Soudelor (8 August 2015, as well as the barrier lake formed and the large-scale destruction of vegetation after Typhoon Nepartak (7 July 2016, are given as three examples of successful applications to demonstrate that the gap between the user’s needs and the existing Level-1 product from LPGS can be bridged by providing browsable images in near real-time.

  6. Spatio-Temporal Assessment of Margalla Hills Forest by Using Landsat Imagery for Year 2000 and 2018 (United States)

    Batool, R.; Javaid, K.


    Environmental imbalance due to human activities has shown serious threat to ecosystem and produced negative impacts. The main goal of this study is to identify, monitor and classify temporal changes of forest cover, build up and open spaces in Margalla Hills National Park, Islamabad. Geographic Information Sciences (GISc) and Remote Sensing (RS) techniques has been used for the assessment of analysis. LANDSAT-7 Enhanced Thematic Mapper (ETM+) and LANDSAT-8 Operational Land Imager (OLI) were utilized for obtaining data of year 2000 and 2018. Temporal changes were evaluated after applying supervised classification and discrimination was analyzed by Per-Pixel based change detection. Results depicts forest cover decrease from 87 % to 74 % whereas build up has increased from 5 % to 7 % over the span. Consequences also justify the presence of open land in study area that has been increased from 2 % to 7 % respectively.

  7. Use of Landsat series data to analyse the spatial and temporal variations of land degradation in a dispersive soil environment: A case of King Sabata Dalindyebo local municipality in the Eastern Cape Province, South Africa (United States)

    Dube, Timothy; Mutanga, Onisimo; Sibanda, Mbulisi; Seutloali, Khoboso; Shoko, Cletah


    Land degradation as a result of inappropriate land use practices, such as overgrazing and cultivation on steep slopes, etc. is one of the major global environmental challenges. Specifically, land degradation threatens the productivity and sustainability of the natural environment, agriculture, and most importantly rural economies in most developing countries, particularly the sub-Saharan region. The main aim of this study was therefore, to assess the potential and strength of using the free or readily available Landsat series data in mapping degraded land areas at the King Sabata Dalindyebo local municipality in the Eastern Cape, South Africa (1984-2010). Data analysis was done using a robust non-parametric classification ensemble; Discriminant Analysis (DA). The results show that degraded areas vary over the years. For example, the results show that the year 1994 and 2004 incurred high degradation levels, when compared to the year 1984 and 2010. Moreover, the observed degradation significantly (α = 0.05) varies with soil type. The chromic acrisols have the highest levels of erosion (approx. 80% in 1984), when compared to humic-umbric acrisols (less than 10% for the entire period under study). It can also be observed that considerable part of degradation occurred in the northern part of the municipal district. Overall, the findings of this research underlines the importance and efficacy of multispectral Landsat series data-set in mapping and monitoring levels of land degradation in data-scarce catchments.

  8. Cross calibration of the Landsat-7 ETM+ and EO-1 ALI sensor (United States)

    Chander, G.; Meyer, D.J.; Helder, D.L.


    As part of the Earth Observer 1 (EO-1) Mission, the Advanced Land Imager (ALI) demonstrates a potential technological direction for Landsat Data Continuity Missions. To evaluate ALI's capabilities in this role, a cross-calibration methodology has been developed using image pairs from the Landsat-7 (L7) Enhanced Thematic Mapper Plus (ETM+) and EO-1 (ALI) to verify the radiometric calibration of ALI with respect to the well-calibrated L7 ETM+ sensor. Results have been obtained using two different approaches. The first approach involves calibration of nearly simultaneous surface observations based on image statistics from areas observed simultaneously by the two sensors. The second approach uses vicarious calibration techniques to compare the predicted top-of-atmosphere radiance derived from ground reference data collected during the overpass to the measured radiance obtained from the sensor. The results indicate that the relative sensor chip assemblies gains agree with the ETM+ visible and near-infrared bands to within 2% and the shortwave infrared bands to within 4%.

  9. Detecting Historical Vegetation Changes in the Dunhuang Oasis Protected Area Using Landsat Images

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    Xiuxia Zhang


    Full Text Available Abstract: Given its proximity to an artificial oasis, the Donghu Nature Reserve in the Dunhuang Oasis has faced environmental pressure and vegetation disturbances in recent decades. Satellite vegetation indices (VIs can be used to detect such changes in vegetation if the satellite images are calibrated to surface reflectance (SR values. The aim of this study was to select a suitable VI based on the Landsat Climate Data Record (CDR products and the absolute radiation-corrected results of Landsat L1T images to detect the spatio-temporal changes in vegetation for the Donghu Reserve during 1986–2015. The results showed that the VI difference (ΔVI images effectively reduced the changes in the source images. Compared with the other VIs, the soil-adjusted vegetation index (SAVI displayed greater robustness to atmospheric effects in the two types of SR images and was more responsive to vegetation changes caused by human factors. From 1986 to 2015, the positive changes in vegetation dominated the overall change trend, with changes in vegetation in the reserve decreasing during 1990–1995, increasing until 2005–2010, and then decreasing again. The vegetation changes were mainly distributed at the edge of the artificial oasis outside the reserve. The detected changes in vegetation in the reserve highlight the increased human pressure on the reserve.

  10. Identification of brome grass infestations in southwest Oklahoma using multi-temporal Landsat imagery (United States)

    Yan, D.; de Beurs, K.


    The extensive infestation of brome grasses (Cheatgrass, Rye brome and Japanese brome) in southwest Oklahoma imposes negative impacts on local economy and ecosystem in terms of decreasing crop and forage production and increasing fire risk. Previously proposed methodologies on brome grass detection are found ill-suitable for southwest Oklahoma as a result of similar responses of background vegetation to inter-annual variability of rainfall. In this study, we aim to identify brome grass infestations by detecting senescent brome grasses using the 2011 Cultivated Land Cover Data Sets and the difference Normalized Difference Infrared Index (NDII) derived from multi-temporal Landsat imagery. Landsat imageries acquired on May 18th and June 10th 2013 by Operational Land Imager and Enhanced Thematic Mapper plus were used. The imagery acquisition dates correspond to the peak growth and senescent time of brome grasses, respectively. The difference NDII was calculated by subtracting the NDII image acquired in May from the June NDII image. Our hypotheses is that senescent brome grasses and crop/pasture fields harvested between the two image acquisition dates can be distinguished from background land cover classes because of their increases in NDII due to decreased water absorption by senescent vegetation in the shortwave infrared region. The Cultivated Land Cover Data Sets were used to further separate senescent brome grass patches from newly harvested crop/pasture fields. Ground truth data collected during field trips in June, July and August of 2013 were used to validate the detection results.

  11. Online Global Land Surface Temperature Estimation from Landsat

    Directory of Open Access Journals (Sweden)

    David Parastatidis


    Full Text Available This study explores the estimation of land surface temperature (LST for the globe from Landsat 5, 7 and 8 thermal infrared sensors, using different surface emissivity sources. A single channel algorithm is used for consistency among the estimated LST products, whereas the option of using emissivity from different sources provides flexibility for the algorithm’s implementation to any area of interest. The Google Earth Engine (GEE, an advanced earth science data and analysis platform, allows the estimation of LST products for the globe, covering the time period from 1984 to present. To evaluate the method, the estimated LST products were compared against two reference datasets: (a LST products derived from ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer, as higher-level products based on the temperature-emissivity separation approach; (b Landsat LST data that have been independently produced, using different approaches. An overall RMSE (root mean square error of 1.52 °C was observed and it was confirmed that the accuracy of the LST product is dependent on the emissivity; different emissivity sources provided different LST accuracies, depending on the surface cover. The LST products, for the full Landsat 5, 7 and 8 archives, are estimated “on-the-fly” and are available on-line via a web application.

  12. A new approach for hydrothermal alteration mapping by selecting and interpreting principal components in Landsat ETM+ images

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    Mohammad Kashkoei Jahroomi


    Full Text Available Introduction In remote sensing studies, especially those in which multi-spectral image data are used, (i.e., Landsat-7 Enhanced Thematic Mapper, various statistical methods are often applied for image enhancement and feature extraction (Reddy, 2008. Principal component analysis is a multivariate statistical technique which is frequently used in multidimensional data analysis. This method attempts to extract and place the spectral information into a smaller set of new components that are more interpretable. However, the results obtained from this method are not so straightforward and require somewhat sophisticated techniques to interpret (Drury, 2001. In this paper we present a new approach for mapping of hydrothermal alteration by analyzing and selecting the principal components extracted through processing of Landsat ETM+ images. The study area is located in a mountainous region of southern Kerman. Geologically, it lies in the volcanic belt of central Iran adjacent to the Gogher-Baft ophiolite zone. The region is highly altered with sericitic, propyliticand argillic alterationwell developed, and argillic alteration is limited (Jafari, 2009; Masumi and Ranjbar, 2011. Multispectral data of Landsat ETM+ was acquired (path 181, row 34 in this study. In these images the color composites of Band 7, Band 4 and Band 1 in RGB indicate the lithology outcropping in the study area. The principal component analysis (PCA ofimage data is often implemented computationally using three steps: (1 Calculation of the variance, covariance matrix or correlation matrix of the satellite sensor data. (2 Computation of the eigenvalues and eigenvectors of the variance-covariance matrix or correlation matrix, and (3 Linear transformation of the image data using the coefficients of the eigenvector matrix. Results By applying PCA to the spectral data, according to the eigenvectors obtained, 6 principal components were extracted from the data set. In the PCA matrix, theeigen

  13. Regional scale net radiation estimation by means of Landsat and TERRA/AQUA imagery and GIS modeling (United States)

    Cristóbal, J.; Ninyerola, M.; Pons, X.; Llorens, P.; Poyatos, R.


    balance among the net shortwave radiation Rn and the net longwave radiation. In addition, two types of approaches have been carried out for its determination: the estimation of the variables implied in the calculation of Rn at daily level (Rndl); and the calculation of the Rn at the time of satellite pass (Rni) and its subsequent conversion to daily Rn by means of the Rn ratio. Net shortwave radiation has been computed by means of albedo and a solar radiation model obtained through a DEM following the methodology of Pons and Ninyerola (2008).This methodology takes into account the position of the Sun, the angles of incidence, the projected shadows and the distance from the Earth to the Sun at one hour intervals. The diffuse radiation is estimated from the direct radiaton and the exoatmospheric direct solar irradiance is estimated with the Page equation (1986) and fitted by Baldasano et al. (1994). Net longwave radiation has been calculated through land surface temperature and emissivity, atmospheric water vapour and air temperature. Air temperature has been modeled by means of multiple regression analysis and GIS interpolation using ground meteorological stations. Finally, air emissivity has been computed using air temperature models and atmospheric water vapour following the methodology developed by Dilley and O'Brien (1998). Finally, models have been validated through a set of 13 ground meteorological standard stations and an experimental station placed in a Mediterranean mountain area over a Pinus sylvestris stand. Obtained results show a mean RMSE of 20 W m-2 in the case of Landsat and a mean RMSE of 22 W m-2 in the case of TERRA/AQUA MODIS, being these results in agreement with other published results, but also offering better RMSE in some cases. Keywords: Net radiation, Landsat, TERRA/AQUA MODIS, GIS modeling, regional scale.

  14. Comparison of satellite imagery from LISS-III/Resourcesat-1 and TM/Landsat 5 to estimate stand-level timber volume

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    Elias Fernando Berra


    Full Text Available After Landsat 5 activities were discontinued, sensors on board ResourceSat-1 satellite have been pointed as an option for Landsat series. The aim of this study is to estimate timber volume from a slash pine (Pinus elliottii Engelm. stand using images from both LISS-III/ResourceSat-1 and TM/Landsat 5 sensors, cross comparing their performances. Reflectance values from the four spectral bands considered equivalent for both sensors were compared regarding sensitivity to changes in timber volume. Trends were similar, with direct relationship in the near-infrared bands and inverse relationships in the visible and mid-infrared bands. Significant differences were only found in the equivalent band of green. Multiple linear regressions were used to select spectral bands that would better explain variations in timber volume. The best fit equations for each sensor were inverted to generate maps of timber volume, estimates which were compared at pixel and stand level. None of the scales showed significant differences between estimates generated from the two sensors. We concluded that LISS-III and TM have generally very similar performance for monitoring timber volume, and LISS-III could therefore be potentially used as a complement or substitute to Landsat series.

  15. Using the Direct Sampling Multiple-Point Geostatistical Method for Filling Gaps in Landsat 7 ETM+ SLC-off Imagery

    KAUST Repository

    Yin, Gaohong


    Since the failure of the Scan Line Corrector (SLC) instrument on Landsat 7, observable gaps occur in the acquired Landsat 7 imagery, impacting the spatial continuity of observed imagery. Due to the highly geometric and radiometric accuracy provided by Landsat 7, a number of approaches have been proposed to fill the gaps. However, all proposed approaches have evident constraints for universal application. The main issues in gap-filling are an inability to describe the continuity features such as meandering streams or roads, or maintaining the shape of small objects when filling gaps in heterogeneous areas. The aim of the study is to validate the feasibility of using the Direct Sampling multiple-point geostatistical method, which has been shown to reconstruct complicated geological structures satisfactorily, to fill Landsat 7 gaps. The Direct Sampling method uses a conditional stochastic resampling of known locations within a target image to fill gaps and can generate multiple reconstructions for one simulation case. The Direct Sampling method was examined across a range of land cover types including deserts, sparse rural areas, dense farmlands, urban areas, braided rivers and coastal areas to demonstrate its capacity to recover gaps accurately for various land cover types. The prediction accuracy of the Direct Sampling method was also compared with other gap-filling approaches, which have been previously demonstrated to offer satisfactory results, under both homogeneous area and heterogeneous area situations. Studies have shown that the Direct Sampling method provides sufficiently accurate prediction results for a variety of land cover types from homogeneous areas to heterogeneous land cover types. Likewise, it exhibits superior performances when used to fill gaps in heterogeneous land cover types without input image or with an input image that is temporally far from the target image in comparison with other gap-filling approaches.

  16. A contemporary decennial global Landsat sample of changing agricultural field sizes (United States)

    White, Emma; Roy, David


    Agriculture has caused significant human induced Land Cover Land Use (LCLU) change, with dramatic cropland expansion in the last century and significant increases in productivity over the past few decades. Satellite data have been used for agricultural applications including cropland distribution mapping, crop condition monitoring, crop production assessment and yield prediction. Satellite based agricultural applications are less reliable when the sensor spatial resolution is small relative to the field size. However, to date, studies of agricultural field size distributions and their change have been limited, even though this information is needed to inform the design of agricultural satellite monitoring systems. Moreover, the size of agricultural fields is a fundamental description of rural landscapes and provides an insight into the drivers of rural LCLU change. In many parts of the world field sizes may have increased. Increasing field sizes cause a subsequent decrease in the number of fields and therefore decreased landscape spatial complexity with impacts on biodiversity, habitat, soil erosion, plant-pollinator interactions, and impacts on the diffusion of herbicides, pesticides, disease pathogens, and pests. The Landsat series of satellites provide the longest record of global land observations, with 30m observations available since 1982. Landsat data are used to examine contemporary field size changes in a period (1980 to 2010) when significant global agricultural changes have occurred. A multi-scale sampling approach is used to locate global hotspots of field size change by examination of a recent global agricultural yield map and literature review. Nine hotspots are selected where significant field size change is apparent and where change has been driven by technological advancements (Argentina and U.S.), abrupt societal changes (Albania and Zimbabwe), government land use and agricultural policy changes (China, Malaysia, Brazil), and/or constrained by

  17. Tabular data base construction and analysis from thematic classified Landsat imagery of Portland, Oregon (United States)

    Bryant, N. A.; George, A. J., Jr.; Hegdahl, R.


    A systematic verification of Landsat data classifications of the Portland, Oregon metropolitan area has been undertaken on the basis of census tract data. The degree of systematic misclassification due to the Bayesian classifier used to process the Landsat data was noted for the various suburban, industrialized and central business districts of the metropolitan area. The Landsat determinations of residential land use were employed to estimate the number of automobile trips generated in the region and to model air pollution hazards.

  18. Mackenzie River Delta morphological change based on Landsat time series (United States)

    Vesakoski, Jenni-Mari; Alho, Petteri; Gustafsson, David; Arheimer, Berit; Isberg, Kristina


    Arctic rivers are sensitive and yet quite unexplored river systems to which the climate change will impact on. Research has not focused in detail on the fluvial geomorphology of the Arctic rivers mainly due to the remoteness and wideness of the watersheds, problems with data availability and difficult accessibility. Nowadays wide collaborative spatial databases in hydrology as well as extensive remote sensing datasets over the Arctic are available and they enable improved investigation of the Arctic watersheds. Thereby, it is also important to develop and improve methods that enable detecting the fluvio-morphological processes based on the available data. Furthermore, it is essential to reconstruct and improve the understanding of the past fluvial processes in order to better understand prevailing and future fluvial processes. In this study we sum up the fluvial geomorphological change in the Mackenzie River Delta during the last ~30 years. The Mackenzie River Delta (~13 000 km2) is situated in the North Western Territories, Canada where the Mackenzie River enters to the Beaufort Sea, Arctic Ocean near the city of Inuvik. Mackenzie River Delta is lake-rich, productive ecosystem and ecologically sensitive environment. Research objective is achieved through two sub-objectives: 1) Interpretation of the deltaic river channel planform change by applying Landsat time series. 2) Definition of the variables that have impacted the most on detected changes by applying statistics and long hydrological time series derived from Arctic-HYPE model (HYdrologic Predictions for Environment) developed by Swedish Meteorological and Hydrological Institute. According to our satellite interpretation, field observations and statistical analyses, notable spatio-temporal changes have occurred in the morphology of the river channel and delta during the past 30 years. For example, the channels have been developing in braiding and sinuosity. In addition, various linkages between the studied

  19. Low cost monitoring from space using Landsat TM time series and open source technologies: the case study of Iguazu park (United States)

    Nole, Gabriele; Lasaponara, Rosa


    Up to nowadays, satellite data have become increasingly available, thus offering a low cost or even free of charge unique tool, with a great potential for operational monitoring of vegetation cover, quantitative assessment of urban expansion and urban sprawl, as well as for monitoring of land use changes and soil consumption. This growing observational capacity has also highlighted the need for research efforts aimed at exploring the potential offered by data processing methods and algorithms, in order to exploit as much as possible this invaluable space-based data source. The work herein presented concerns an application study on the monitoring of vegetation cover and urban sprawl conducted with the use of satellite Landsat TM data. The selected test site is the Iguazu park highly significant, being it one of the most threatened global conservation priorities ( In order to produce synthetic maps of the investigated areas to monitor the status of vegetation and ongoing subtle changes, satellite Landsat TM data images were classified using two automatic classifiers, Maximum Likelihood (MLC) and Support Vector Machines (SVMs) applied by changing setting parameters, with the aim to compare their respective performances in terms of robustness, speed and accuracy. All process steps have been developed integrating Geographical Information System and Remote Sensing, and adopting free and open source software. Results pointed out that the SVM classifier with RBF kernel was generally the best choice (with accuracy higher than 90%) among all the configurations compared, and the use of multiple bands globally improves classification. One of the critical elements found in the case of monitoring of urban area expansion is given by the presence of urban garden mixed with urban fabric. The use of different configurations for the SVMs, i.e. different kernels and values of the setting parameters, allowed us to calibrate the classifier also to

  20. Digital color analysis of color-ratio composite LANDSAT scenes. [Nevada (United States)

    Raines, G. L.


    A method is presented that can be used to calculate approximate Munsell coordinates of the colors produced by making a color composite from three registered images. Applied to the LANDSAT MSS data of the Goldfield, Nevada, area, this method permits precise and quantitative definition of the limonitic areas originally observed in a LANDSAT color ratio composite. In addition, areas of transported limonite can be discriminated from the limonite in the hydrothermally altered areas of the Goldfield mining district. From the analysis, the numerical distinction between limonitic and nonlimonitic ground is generally less than 3% using the LANDSAT bands and as much as 8% in ratios of LANDSAT MSS bands.

  1. Seasonally-managed wetland footprint delineation using Landsat ETM+ satellite imagery

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    Quinn, Nigel W. T. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Epshtein, Olga [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Arizona State Univ., Tempe, AZ (United States). School of Sustainable Engineering and the Built Environment


    One major challenge in water resource management is the estimation of evapotranspiration losses from seasonally managed wetlands. Quantifying these losses is complicated by the dynamic nature of the wetlands' areal footprint during the periods of flood-up and drawdown. In this paper, we present a data-lean solution to this problem using an example application in the San Joaquin Basin, California. Through analysis of high-resolution Landsat Enhanced Thematic Mapper Plus (ETM+) satellite imagery, we develop a metric to better capture the extent of total flooded wetland area. The procedure is validated using year-long, continuously-logged field datasets for two wetlands within the study area. The proposed classification which uses a Landsat ETM + Band 5 (mid-IR wavelength) to Band 2 (visible green wavelength) ratio improves estimates by 30–50% relative to previous wetland delineation studies. Finally, requiring modest ancillary data, the study results provide a practical and efficient option for wetland management in data-sparse regions or un-gauged watersheds.

  2. Determining the rate of forest conversion in Mato Grosso, Brazil, using Landsat MSS and AVHRR data (United States)

    Nelson, Ross; Horning, Ned; Stone, Thomas A.


    AVHRR-LAC thermal data and Landsat MSS and TM spectral data were used to estimate the rate of forest clearing in Mato Grosso, Brazil, between 1981 and 1984. The Brazilian state was stratified into forest and nonforest. A list sampling procedure was used in the forest stratum to select Landsat MSS scenes for processing based on estimates of fire activity in the scenes. Fire activity in 1984 was estimated using AVHRR-LAC thermal data. State-wide estimates of forest conversion indicate that between 1981 and 1984, 353,966 ha + or - 77,000 ha (0.4 percent of the state area) were converted per year. No evidence of reforestation was found in this digital sample. The relationship between forest clearing rate (based on MSS-TM analysis) and fire activity (estimated using AVHRR data) was noisy (R-squared = 0.41). The results suggest that AVHRR data may be put to better use as a stratification tool than as a subsidiary variable in list sampling.

  3. A SMAP Supervised Classification of Landsat Images for Urban Sprawl Evaluation

    Directory of Open Access Journals (Sweden)

    Flavia Di Palma


    Full Text Available The negative impacts of land take on natural components and economic resources affect planning choices and territorial policies. The importance of land take monitoring, in Italy, has been only recently considered, but despite this awareness, in the great part of the country, effective monitoring and containment measures have not been started, yet. This research proposes a methodology to map and monitor land use changes. To this end, a time series from 1985–2010, based on the multi-temporal Landsat data Thematic Mapper (TM, has been analyzed in the Vulture Alto-Bradano area, a mountain zone of the Basilicata region (Southern Italy. Results confirm a double potentiality of using these data: on the one hand, the use of multi-temporal Landsat data allows going very back in time, producing accurate datasets that provide a phenomenon trend over time; on the other hand, these data can be considered a first experience of open data in the field of spatial information. The proposed methodology provides agencies, local authorities and practitioners with a valuable tool to implement monitoring actions. This represents the first step to pursue territorial governance methods based on sustainability, limiting the land take.

  4. Exploration for porphyry copper deposits in Pakistan using digital processing of Landsat-1 data (United States)

    Schmidt, R. G.


    Rock-type classification by digital-computer processing of Landsat-1 multispectral scanner data has been used to select 23 prospecting targets in the Chagai District, Pakistan, five of which have proved to be large areas of hydrothermally altered porphyry containing pyrite. Empirical maximum and minimum apparent reflectance limits were selected for each multispectral scanner band in each rock type classified, and a relatively unrefined classification table was prepared. Where the values for all four bands fitted within the limits designated for a particular class, a symbol for the presumed rock type was printed by the computer at the appropriate location. Drainage channels, areas of mineralized quartz diorite, areas of pyrite-rich rock, and the approximate limit of propylitic alteration were very well delineated on the computer-generated map of the test area. The classification method was used to evaluate 2,100 sq km in the Mashki Chah region. The results of the experiment show that outcrops of hydrothermally altered and mineralized rock can be identified from Landsat-1 data under favorable conditions.

  5. Land-cover classification in a moist tropical region of Brazil with Landsat TM imagery. (United States)

    Li, Guiying; Lu, Dengsheng; Moran, Emilio; Hetrick, Scott


    This research aims to improve land-cover classification accuracy in a moist tropical region in Brazil by examining the use of different remote sensing-derived variables and classification algorithms. Different scenarios based on Landsat Thematic Mapper (TM) spectral data and derived vegetation indices and textural images, and different classification algorithms - maximum likelihood classification (MLC), artificial neural network (ANN), classification tree analysis (CTA), and object-based classification (OBC), were explored. The results indicated that a combination of vegetation indices as extra bands into Landsat TM multispectral bands did not improve the overall classification performance, but the combination of textural images was valuable for improving vegetation classification accuracy. In particular, the combination of both vegetation indices and textural images into TM multispectral bands improved overall classification accuracy by 5.6% and kappa coefficient by 6.25%. Comparison of the different classification algorithms indicated that CTA and ANN have poor classification performance in this research, but OBC improved primary forest and pasture classification accuracies. This research indicates that use of textural images or use of OBC are especially valuable for improving the vegetation classes such as upland and liana forest classes having complex stand structures and having relatively large patch sizes.

  6. Ten Years of Land Cover Change on the California Coast Detected using Landsat Satellite Image Analysis (United States)

    Potter, Christopher S.


    Landsat satellite imagery was analyzed to generate a detailed record of 10 years of vegetation disturbance and regrowth for Pacific coastal areas of Marin and San Francisco Counties. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology, a transformation of Tasseled-Cap data space, was applied to detected changes in perennial coastal shrubland, woodland, and forest cover from 1999 to 2009. Results showed several principal points of interest, within which extensive contiguous areas of similar LEDAPS vegetation change (either disturbed or restored) were detected. Regrowth areas were delineated as burned forest areas in the Point Reyes National Seashore (PRNS) from the 1995 Vision Fire. LEDAPS-detected disturbance patterns on Inverness Ridge, PRNS in areas observed with dieback of tanoak and bay laurel trees was consistent with defoliation by sudden oak death (Phytophthora ramorum). LEDAPS regrowth pixels were detected over much of the predominantly grassland/herbaceous cover of the Olema Valley ranchland near PRNS. Extensive restoration of perennial vegetation cover on Crissy Field, Baker Beach and Lobos Creek dunes in San Francisco was identified. Based on these examples, the LEDAPS methodology will be capable of fulfilling much of the need for continual, low-cost monitoring of emerging changes to coastal ecosystems.

  7. An Object-Based Approach for Fire History Reconstruction by Using Three Generations of Landsat Sensors

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    Thomas Katagis


    Full Text Available In this study, the capability of geographic object-based image analysis (GEOBIA in the reconstruction of the recent fire history of a typical Mediterranean area was investigated. More specifically, a semi-automated GEOBIA procedure was developed and tested on archived and newly acquired Landsat Multispectral Scanner (MSS, Thematic Mapper (TM, and Operational Land Imager (OLI images in order to accurately map burned areas in the Mediterranean island of Thasos. The developed GEOBIA ruleset was built with the use of the TM image and then applied to the other two images. This process of transferring the ruleset did not require substantial adjustments or any replacement of the initially selected features used for the classification, thus, displaying reduced complexity in processing the images. As a result, burned area maps of very high accuracy (over 94% overall were produced. In addition to the standard error matrix, the employment of additional measures of agreement between the produced maps and the reference data revealed that “spatial misplacement” was the main source of classification error. It can be concluded that the proposed approach can be potentially used for reconstructing the recent (40-year fire history in the Mediterranean, based on extended time series of Landsat or similar data.

  8. The Efficiency of Random Forest Method for Shoreline Extraction from LANDSAT-8 and GOKTURK-2 Imageries (United States)

    Bayram, B.; Erdem, F.; Akpinar, B.; Ince, A. K.; Bozkurt, S.; Catal Reis, H.; Seker, D. Z.


    Coastal monitoring plays a vital role in environmental planning and hazard management related issues. Since shorelines are fundamental data for environment management, disaster management, coastal erosion studies, modelling of sediment transport and coastal morphodynamics, various techniques have been developed to extract shorelines. Random Forest is one of these techniques which is used in this study for shoreline extraction.. This algorithm is a machine learning method based on decision trees. Decision trees analyse classes of training data creates rules for classification. In this study, Terkos region has been chosen for the proposed method within the scope of "TUBITAK Project (Project No: 115Y718) titled "Integration of Unmanned Aerial Vehicles for Sustainable Coastal Zone Monitoring Model - Three-Dimensional Automatic Coastline Extraction and Analysis: Istanbul-Terkos Example". Random Forest algorithm has been implemented to extract the shoreline of the Black Sea where near the lake from LANDSAT-8 and GOKTURK-2 satellite imageries taken in 2015. The MATLAB environment was used for classification. To obtain land and water-body classes, the Random Forest method has been applied to NIR bands of LANDSAT-8 (5th band) and GOKTURK-2 (4th band) imageries. Each image has been digitized manually and shorelines obtained for accuracy assessment. According to accuracy assessment results, Random Forest method is efficient for both medium and high resolution images for shoreline extraction studies.


    Directory of Open Access Journals (Sweden)

    B. Bayram


    Full Text Available Coastal monitoring plays a vital role in environmental planning and hazard management related issues. Since shorelines are fundamental data for environment management, disaster management, coastal erosion studies, modelling of sediment transport and coastal morphodynamics, various techniques have been developed to extract shorelines. Random Forest is one of these techniques which is used in this study for shoreline extraction.. This algorithm is a machine learning method based on decision trees. Decision trees analyse classes of training data creates rules for classification. In this study, Terkos region has been chosen for the proposed method within the scope of "TUBITAK Project (Project No: 115Y718 titled "Integration of Unmanned Aerial Vehicles for Sustainable Coastal Zone Monitoring Model – Three-Dimensional Automatic Coastline Extraction and Analysis: Istanbul-Terkos Example". Random Forest algorithm has been implemented to extract the shoreline of the Black Sea where near the lake from LANDSAT-8 and GOKTURK-2 satellite imageries taken in 2015. The MATLAB environment was used for classification. To obtain land and water-body classes, the Random Forest method has been applied to NIR bands of LANDSAT-8 (5th band and GOKTURK-2 (4th band imageries. Each image has been digitized manually and shorelines obtained for accuracy assessment. According to accuracy assessment results, Random Forest method is efficient for both medium and high resolution images for shoreline extraction studies.

  10. Reconstructing the Spatio-Temporal Development of Irrigation Systems in Uzbekistan Using Landsat Time Series

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    Thomas Koellner


    Full Text Available The expansion of irrigated agriculture during the Soviet Union (SU era made Central Asia a leading cotton production region in the world. However, the successor states of the SU in Central Asia face on-going environmental damages and soil degradation that are endangering the sustainability of agricultural production. With Landsat MSS and TM data from 1972/73, 1977, 1987, 1998, and 2000 the expansion and densification of the irrigated cropland could be reconstructed in the Kashkadarya Province of Uzbekistan, Central Asia. Classification trees were generated by interpreting multitemporal normalized difference vegetation index data and crop phenological knowledge. Assessments based on image-derived validation samples showed good accuracy. Official statistics were found to be of limited use for analyzing the plausibility of the results, because they hardly represent the area that is cropped in the very dry study region. The cropping area increased from 134,800 ha in 1972/73 to 470,000 ha in 2009. Overlaying a historical soil map illustrated that initially sierozems were preferred for irrigated agriculture, but later the less favorable solonchaks and solonetzs were also explored, illustrating the strategy of agricultural expansion in the Aral Sea Basin. Winter wheat cultivation doubled between 1987 and 1998 to approximately 211,000 ha demonstrating its growing relevance for modern Uzbekistan. The spatial-temporal approach used enhances the understanding of natural conditions before irrigation is employed and supports decision-making for investments in irrigation infrastructure and land cultivation throughout the Landsat era.

  11. Improved Topographic Normalization for Landsat TM Images by Introducing the MODIS Surface BRDF

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    Yanli Zhang


    Full Text Available In rugged terrain, the accuracy of surface reflectance estimations is compromised by atmospheric and topographic effects. We propose a new method to simultaneously eliminate atmospheric and terrain effects in Landsat Thematic Mapper (TM images based on a 30 m digital elevation model (DEM and Moderate Resolution Imaging Spectroradiometer (MODIS atmospheric products. Moreover, we define a normalized factor of a Bidirectional Reflectance Distribution Function (BRDF to convert the sloping pixel reflectance into a flat pixel reflectance by using the Ross Thick-Li Sparse BRDF model (Ambrals algorithm and MODIS BRDF/albedo kernel coefficient products. Sole atmospheric correction and topographic normalization were performed for TM images in the upper stream of the Heihe River Basin. The results show that using MODIS atmospheric products can effectively remove atmospheric effects compared with the Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH model and the Landsat Climate Data Record (CDR. Moreover, superior topographic effect removal can be achieved by considering the surface BRDF when compared with the surface Lambertian assumption of topographic normalization.

  12. SRTM Perspective View with Landsat Overlay: San Jose, Costa Rica (United States)


    This perspective view shows the capital city of San Jose, Costa Rica, in the right center of the image (gray area). Rising behind it are the volcanoes Irazu, 3402 meters high (11,161 feet) and Turrialba, 3330 meters high (10,925 feet.)Irazu is the highest volcano in Costa Rica and is located in the Irazu Volcano National Park, established in 1955. There have been at least 23 eruptions of Irazu since 1723, the most recent during 1963 to 1965. This activity sent tephra and secondary mudflows into cultivated areas, caused at least 40 deaths, and destroyed 400 houses and some factories.This image was generated in support of the Central American Commission for Environment and Development through an agreement with NASA. The Commission involves eight nations working to develop the Mesoamerican Biological Corridor, an effort to study and preserve some of the most biologically diverse regions of the planet.This three-dimensional perspective view was generated using topographic data from the Shuttle Radar Topography Mission (SRTM) and an enhanced false-color Landsat 7 satellite image. Colors are from Landsat bands 5, 4, and 2 as red, green and blue, respectively. Topographic expression is exaggerated 2X.Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter resolution of most Landsat images and will substantially help in analyses of the large and growing Landsat image archive. The Landsat 7 Thematic Mapper image used here was provided to the SRTM by the United States Geological Survey, Earth Resources Observation Systems (EROS) Data Center, Sioux Falls, South Dakota.Elevation data used in this image was acquired by the Shuttle Radar Topography Mission (SRTM) aboard the Space Shuttle Endeavour, launched on February 11,2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) that flew twice on the Space Shuttle Endeavour in 1994. SRTM

  13. SRTM Perspective View with Landsat Overlay: Costa Rica Coastal Plain (United States)


    This perspective view shows the northern coastal plain of Costa Rica with the Cordillera Central, composed of a number of active and dormant volcanoes, rising in the background. This view looks toward the south over the Rio San Juan, which marks the boundary between Costa Rica and Nicaragua. The smaller river joining Rio San Juan in the center of the image is Rio Sarapiqui, which is navigable upstream as far inland as Puerto Viejo (Old Port) de Sarapiqui at the mountain's base. This river was an important transportation route for those few hardy settlers who first moved into this region, although as recently as 1953 a mere three thatched-roof houses were all that comprised the village of Puerto Viejo.This coastal plain is a sedimentary basin formed about 50 million years ago composed of river alluvium and lahar (mud and ash flow) deposits from the volcanoes of the Cordillera Central. It comprises the province of Heredia (the smallest of Costa Rica's seven) and demonstrates a wide range of climatic conditions, from warm and humid lowlands to cool and damp highlands, and including the mild but seasonally wet and dry Central Valley.This image was generated in support of the Central American Commission for Environment and Development through an agreement with NASA. The Commission involves eight nations working to develop the Mesoamerican Biological Corridor, an effort to study and preserve some of the most biologically diverse regions of the planet.This three-dimensional perspective view was generated using topographic data from the Shuttle Radar Topography Mission (SRTM) and an enhanced false-color Landsat 7 satellite image. Colors are from Landsat bands 5, 4, and 2 as red, green and blue, respectively. Topographic expression is exaggerated 2X.Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter resolution of most Landsat images and will substantially help in analyses of the large and growing Landsat

  14. Perspective View with Landsat Overlay, Lakes Managua and Nicaragua (United States)


    This perspective view shows Lakes Managua and Nicaragua near the Pacific coast of Nicaragua. Lake Managua is the 65-kilometer (40-mile)-long fresh water lake in the foreground of this south-looking view, emptying via the Tipitapa River into the much larger Lake Nicaragua in the distance. The capital city of Managua, with a population of more than 500,000, is located along the southern shore of Lake Managua, the area with the highest population density in Nicaragua.The physical setting of Lake Managua is dominated by the numerous volcanic features aligned in a northwest-southeast axis. The cone-like feature in the foreground is Momotombo, a 1,280-meter (4,199-foot)-high stratovolcano located on the northwest end of the lake. Two water-filled volcanic craters (Apoyegue and Jiloa volcanoes) reside on the Chiltepe Peninsula protruding into the lake from the west. Two volcanoes can also be seen on the island of Ometepe in Lake Nicaragua: El Maderas rising to 1,394 meters (4,573 feet) and the active El Conception at 1,610 meters (5,282 feet).This three-dimensional perspective view was generated using topographic data from the Shuttle Radar Topography Mission (SRTM) and an enhanced false-color Landsat 7 satellite image. Colors are from Landsat bands 5, 4, and 2 as red, green and blue, respectively. Topographic expression is exaggerated two times.Landsat has been providing visible and infrared views of the Earth since 1972. SRTM elevation data matches the 30-meter resolution of most Landsat images and will substantially help in analyses of the large and growing Landsat image archive. The Landsat 7 Thematic Mapper image used here was provided to the SRTM by the United States Geological Survey, Earth Resources Observation Systems (EROS) Data Center, Sioux Falls, S.D.Elevation data used in this image was acquired by the SRTM aboard the Space Shuttle Endeavour, launched on February 11, 2000. SRTM used the same radar instrument that comprised the Spaceborne Imaging Radar

  15. An Operational Scheme for Deriving Standardised Surface Reflectance from Landsat TM/ETM+ and SPOT HRG Imagery for Eastern Australia

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    Neil Flood


    Full Text Available Operational monitoring of vegetation and land surface change over large areas can make good use of satellite sensors that measure radiance reflected from the Earth’s surface. Monitoring programs use multiple images for complete spatial coverage over time. Accurate retrievals of vegetation cover and vegetation change estimates can be hampered by variation, in both space and time, in the measured radiance, caused by atmospheric conditions, topography, sensor location, and sun elevation. In order to obtain estimates of cover that are comparable between images, and to retrieve accurate estimates of change, these sources of variation must be removed. In this paper we present a preprocessing scheme for minimising atmospheric, topographic and bi-directional reflectance effects on Landsat-5 TM, Landsat-7 ETM+ and SPOT-5 HRG imagery. The approach involves atmospheric correction to compute surface-leaving radiance, and bi-directional reflectance modelling to remove the effects of topography and angular variation in reflectance. The bi-directional reflectance model has been parameterised for eastern Australia, but the general approach is more widely applicable. The result is surface reflectance standardised to a fixed viewing and illumination geometry. The method can be applied to the entire record for these instruments, without intervention, which is of increasing importance with the increased availability of long term image archives. Validation shows that the corrections improve the estimation of reflectance at any given angular configuration, thus allowing the removal from the reflectance signal of much variation due to factors independent of the land surface. The method has been used to process over 45,000 Landsat-5 TM and Landsat-7 ETM+ scenes and 2,500 SPOT-5 scenes, over eastern Australia, and is now in use in operational monitoring programs.

  16. Mapping and estimating the total living biomass and carbon in low-biomass woodlands using Landsat 8 CDR data

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    Belachew Gizachew


    Full Text Available Abstract Background A functional forest carbon measuring, reporting and verification (MRV system to support climate change mitigation policies, such as REDD+, requires estimates of forest biomass carbon, as an input to estimate emissions. A combination of field inventory and remote sensing is expected to provide those data. By linking Landsat 8 and forest inventory data, we (1 developed linear mixed effects models for total living biomass (TLB estimation as a function of spectral variables, (2 developed a 30 m resolution map of the total living carbon (TLC, and (3 estimated the total TLB stock of the study area. Inventory data consisted of tree measurements from 500 plots in 63 clusters in a 15,700 km2 study area, in miombo woodlands of Tanzania. The Landsat 8 data comprised two climate data record images covering the inventory area. Results We found a linear relationship between TLB and Landsat 8 derived spectral variables, and there was no clear evidence of spectral data saturation at higher biomass values. The root-mean-square error of the values predicted by the linear model linking the TLB and the normalized difference vegetation index (NDVI is equal to 44 t/ha (49 % of the mean value. The estimated TLB for the study area was 140 Mt, with a mean TLB density of 81 t/ha, and a 95 % confidence interval of 74–88 t/ha. We mapped the distribution of TLC of the study area using the TLB model, where TLC was estimated at 47 % of TLB. Conclusion The low biomass in the miombo woodlands, and the absence of a spectral data saturation problem suggested that Landsat 8 derived NDVI is suitable auxiliary information for carbon monitoring in the context of REDD+, for low-biomass, open-canopy woodlands.

  17. Updating the 2001 National Land Cover Database land cover classification to 2006 by using Landsat imagery change detection methods (United States)

    Xian, George; Homer, Collin G.; Fry, Joyce


    The recent release of the U.S. Geological Survey (USGS) National Land Cover Database (NLCD) 2001, which represents the nation's land cover status based on a nominal date of 2001, is widely used as a baseline for national land cover conditions. To enable the updating of this land cover information in a consistent and continuous manner, a prototype method was developed to update land cover by an individual Landsat path and row. This method updates NLCD 2001 to a nominal date of 2006 by using both Landsat imagery and data from NLCD 2001 as the baseline. Pairs of Landsat scenes in the same season in 2001 and 2006 were acquired according to satellite paths and rows and normalized to allow calculation of change vectors between the two dates. Conservative thresholds based on Anderson Level I land cover classes were used to segregate the change vectors and determine areas of change and no-change. Once change areas had been identified, land cover classifications at the full NLCD resolution for 2006 areas of change were completed by sampling from NLCD 2001 in unchanged areas. Methods were developed and tested across five Landsat path/row study sites that contain several metropolitan areas including Seattle, Washington; San Diego, California; Sioux Falls, South Dakota; Jackson, Mississippi; and Manchester, New Hampshire. Results from the five study areas show that the vast majority of land cover change was captured and updated with overall land cover classification accuracies of 78.32%, 87.5%, 88.57%, 78.36%, and 83.33% for these areas. The method optimizes mapping efficiency and has the potential to provide users a flexible method to generate updated land cover at national and regional scales by using NLCD 2001 as the baseline.

  18. An Effort to Map and Monitor Baldcypress Forest Areas in Coastal Louisiana, Using Landsat, MODIS, and ASTER Satellite Data (United States)

    Spruce, Joseph P.; Sader, Steve; Smoot, James


    This presentation discusses a collaborative project to develop, test, and demonstrate baldcypress forest mapping and monitoring products for aiding forest conservation and restoration in coastal Louisiana. Low lying coastal forests in the region are being negatively impacted by multiple factors, including subsidence, salt water intrusion, sea level rise, persistent flooding, hydrologic modification, annual insect-induced forest defoliation, timber harvesting, and conversion to urban land uses. Coastal baldcypress forests provide invaluable ecological services in terms of wildlife habitat, forest products, storm buffers, and water quality benefits. Before this project, current maps of baldcypress forest concentrations and change did not exist or were out of date. In response, this project was initiated to produce: 1) current maps showing the extent and location of baldcypress dominated forests; and 2) wetland forest change maps showing temporary and persistent disturbance and loss since the early 1970s. Project products are being developed collaboratively with multiple state and federal agencies. Products are being validated using available reference data from aerial, satellite, and field survey data. Results include Landsat TM- based classifications of baldcypress in terms of cover type and percent canopy cover. Landsat MSS data was employed to compute a circa 1972 classification of swamp and bottomland hardwood forest types. Landsat data for 1972-2010 was used to compute wetland forest change products. MODIS-based change products were applied to view and assess insect-induced swamp forest defoliation. MODIS, Landsat, and ASTER satellite data products were used to help assess hurricane and flood impacts to coastal wetland forests in the region.

  19. Lake Area Analysis Using Exponential Smoothing Model and Long Time-Series Landsat Images in Wuhan, China

    Directory of Open Access Journals (Sweden)

    Gonghao Duan


    Full Text Available The loss of lake area significantly influences the climate change in a region, and this loss represents a serious and unavoidable challenge to maintaining ecological sustainability under the circumstances of lakes that are being filled. Therefore, mapping and forecasting changes in the lake is critical for protecting the environment and mitigating ecological problems in the urban district. We created an accessible map displaying area changes for 82 lakes in the Wuhan city using remote sensing data in conjunction with visual interpretation by combining field data with Landsat 2/5/7/8 Thematic Mapper (TM time-series images for the period 1987–2013. In addition, we applied a quadratic exponential smoothing model to forecast lake area changes in Wuhan city. The map provides, for the first time, estimates of lake development in Wuhan using data required for local-scale studies. The model predicted a lake area reduction of 18.494 km2 in 2015. The average error reached 0.23 with a correlation coefficient of 0.98, indicating that the model is reliable. The paper provided a numerical analysis and forecasting method to provide a better understanding of lake area changes. The modeling and mapping results can help assess aquatic habitat suitability and property planning for Wuhan lakes.

  20. A combined spectral and object-based approach to transparent cloud removal in an operational setting for Landsat ETM+ (United States)

    Watmough, Gary R.; Atkinson, Peter M.; Hutton, Craig W.


    The automated cloud cover assessment (ACCA) algorithm has provided automated estimates of cloud cover for the Landsat ETM+ mission since 2001. However, due to the lack of a band around 1.375 μm, cloud edges and transparent clouds such as cirrus cannot be detected. Use of Landsat ETM+ imagery for terrestrial land analysis is further hampered by the relatively long revisit period due to a nadir only viewing sensor. In this study, the ACCA threshold parameters were altered to minimise omission errors in the cloud masks. Object-based analysis was used to reduce the commission errors from the extended cloud filters. The method resulted in the removal of optically thin cirrus cloud and cloud edges which are often missed by other methods in sub-tropical areas. Although not fully automated, the principles of the method developed here provide an opportunity for using otherwise sub-optimal or completely unusable Landsat ETM+ imagery for operational applications. Where specific images are required for particular research goals the method can be used to remove cloud and transparent cloud helping to reduce bias in subsequent land cover classifications.

  1. Selection and quality assessment of Landsat data for the North American forest dynamics forest history maps of the US (United States)

    Schleeweis, Karen; Goward, Samuel N.; Huang, Chengquan; Dwyer, John L.; Dungan, Jennifer L.; Lindsey, Mary A.; Michaelis, Andrew; Rishmawi, Khaldoun; Masek, Jeffery G.


    Using the NASA Earth Exchange platform, the North American Forest Dynamics (NAFD) project mapped forest history wall-to-wall, annually for the contiguous US (1986–2010) using the Vegetation Change Tracker algorithm. As with any effort to identify real changes in remotely sensed time-series, data gaps, shifts in seasonality, misregistration, inconsistent radiometry and cloud contamination can be sources of error. We discuss the NAFD image selection and processing stream (NISPS) that was designed to minimize these sources of error. The NISPS image quality assessments highlighted issues with the Landsat archive and metadata including inadequate georegistration, unreliability of the pre-2009 L5 cloud cover assessments algorithm, missing growing-season imagery and paucity of clear views. Assessment maps of Landsat 5–7 image quantities and qualities are presented that offer novel perspectives on the growing-season archive considered for this study. Over 150,000+ Landsat images were considered for the NAFD project. Optimally, one high quality cloud-free image in each year or a total of 12,152 images would be used. However, to accommodate data gaps and cloud/shadow contamination 23,338 images were needed. In 220 specific path-row image years no acceptable images were found resulting in data gaps in the annual national map products.

  2. Reclamation of mosquito breeding sites using Landsat-8 remote sensing data: A case study of Birnin Kebbi, Nigeria (United States)

    Amusuk, Danboyi Joseph; Hashim, Mazlan; Beiranvand Pour, Amin


    It is believed by recent releases of World Health Organization (WHO) that more than half of the world's population (3.2 billion) live in areas that are at risk of malaria transmission. Although increased efforts are dramatically reducing the malaria burden in some places where the rate of new cases indicates a fall by 37% globally and 60% death rate. Unfortunately, the subSaharan Africa still shares 89% of malaria and 91% of malaria deaths. Essentially, attacking the causative vectors and reclamation of the vector breeding sites could be remarkable for the rolling back the malaria epidemic project. Consequently, it is essential to explore the possibility of using recent Landsat-8 data remote sensing data and applications of Geographic Information System (GIS) technique in contributing to the realization of this objective. This investigation used for identifying mosquito breeding habitat (Derelict Ponds) zones the application of supervised classification of the Landsat-8 image in conjunction with GIS layering which allowed identification of high risk prone regions for mosquito breeding habitat. The methodology delineated 10 spatial locations of the Derelict Ponds (DP) spread around the Birnin Kebbi urban environment. Moreover, the results combined with comparative analysis of the link between warm climatic (temperature and rainfall data) conditions and Malaria prevalence that is associated with urban poverty. This study indicates that the application of Landsat-8 data and GIS techniques can be a useful tool for planning and management of environmental health and mapping of hot spot environmental problem areas.

  3. Predicting forest height using the GOST, Landsat 7 ETM+, and airborne LiDAR for sloping terrains in the Greater Khingan Mountains of China (United States)

    Gu, Chengyan; Clevers, Jan G. P. W.; Liu, Xiao; Tian, Xin; Li, Zhouyuan; Li, Zengyuan


    Sloping terrain of forests is an overlooked factor in many models simulating the canopy bidirectional reflectance distribution function, which limits the estimation accuracy of forest vertical structure parameters (e.g., forest height). The primary objective of this study was to predict forest height on sloping terrain over large areas with the Geometric-Optical Model for Sloping Terrains (GOST) using airborne Light Detection and Ranging (LiDAR) data and Landsat 7 imagery in the western Greater Khingan Mountains of China. The Sequential Maximum Angle Convex Cone (SMACC) algorithm was used to generate image endmembers and corresponding abundances in Landsat imagery. Then, LiDAR-derived forest metrics, topographical factors and SMACC abundances were used to calibrate and validate the GOST, which aimed to accurately decompose the SMACC mixed forest pixels into sunlit crown, sunlit background and shade components. Finally, the forest height of the study area was retrieved based on a back-propagation neural network and a look-up table. Results showed good performance for coniferous forests on all slopes and at all aspects, with significant coefficients of determination above 0.70 and root mean square errors (RMSEs) between 0.50 m and 1.00 m based on ground observed validation data. Higher RMSEs were found in areas with forest heights below 5 m and above 17 m. For 90% of the forested area, the average RMSE was 3.58 m. Our study demonstrates the tremendous potential of the GOST for quantitative mapping of forest height on sloping terrains with multispectral and LiDAR inputs.


    Directory of Open Access Journals (Sweden)

    S. H. Chiang


    Full Text Available Forest is a very important ecosystem and natural resource for living things. Based on forest inventories, government is able to make decisions to converse, improve and manage forests in a sustainable way. Field work for forestry investigation is difficult and time consuming, because it needs intensive physical labor and the costs are high, especially surveying in remote mountainous regions. A reliable forest inventory can give us a more accurate and timely information to develop new and efficient approaches of forest management. The remote sensing technology has been recently used for forest investigation at a large scale. To produce an informative forest inventory, forest attributes, including tree species are unavoidably required to be considered. In this study the aim is to classify forest tree species in Erdenebulgan County, Huwsgul province in Mongolia, using Maximum Entropy method. The study area is covered by a dense forest which is almost 70% of total territorial extension of Erdenebulgan County and is located in a high mountain region in northern Mongolia. For this study, Landsat satellite imagery and a Digital Elevation Model (DEM were acquired to perform tree species mapping. The forest tree species inventory map was collected from the Forest Division of the Mongolian Ministry of Nature and Environment as training data and also used as ground truth to perform the accuracy assessment of the tree species classification. Landsat images and DEM were processed for maximum entropy modeling, and this study applied the model with two experiments. The first one is to use Landsat surface reflectance for tree species classification; and the second experiment incorporates terrain variables in addition to the Landsat surface reflectance to perform the tree species classification. All experimental results were compared with the tree species inventory to assess the classification accuracy. Results show that the second one which uses Landsat surface

  5. Forest Tree Species Distribution Mapping Using Landsat Satellite Imagery and Topographic Variables with the Maximum Entropy Method in Mongolia (United States)

    Hao Chiang, Shou; Valdez, Miguel; Chen, Chi-Farn


    Forest is a very important ecosystem and natural resource for living things. Based on forest inventories, government is able to make decisions to converse, improve and manage forests in a sustainable way. Field work for forestry investigation is difficult and time consuming, because it needs intensive physical labor and the costs are high, especially surveying in remote mountainous regions. A reliable forest inventory can give us a more accurate and timely information to develop new and efficient approaches of forest management. The remote sensing technology has been recently used for forest investigation at a large scale. To produce an informative forest inventory, forest attributes, including tree species are unavoidably required to be considered. In this study the aim is to classify forest tree species in Erdenebulgan County, Huwsgul province in Mongolia, using Maximum Entropy method. The study area is covered by a dense forest which is almost 70% of total territorial extension of Erdenebulgan County and is located in a high mountain region in northern Mongolia. For this study, Landsat satellite imagery and a Digital Elevation Model (DEM) were acquired to perform tree species mapping. The forest tree species inventory map was collected from the Forest Division of the Mongolian Ministry of Nature and Environment as training data and also used as ground truth to perform the accuracy assessment of the tree species classification. Landsat images and DEM were processed for maximum entropy modeling, and this study applied the model with two experiments. The first one is to use Landsat surface reflectance for tree species classification; and the second experiment incorporates terrain variables in addition to the Landsat surface reflectance to perform the tree species classification. All experimental results were compared with the tree species inventory to assess the classification accuracy. Results show that the second one which uses Landsat surface reflectance coupled

  6. Mapping Annual Forest Cover in Sub-Humid and Semi-Arid Regions through Analysis of Landsat and PALSAR Imagery

    Directory of Open Access Journals (Sweden)

    Yuanwei Qin


    Full Text Available Accurately mapping the spatial distribution of forests in sub-humid to semi-arid regions over time is important for forest management but a challenging task. Relatively large uncertainties still exist in the spatial distribution of forests and forest changes in the sub-humid and semi-arid regions. Numerous publications have used either optical or synthetic aperture radar (SAR remote sensing imagery, but the resultant forest cover maps often have large errors. In this study, we propose a pixel- and rule-based algorithm to identify and map annual forests from 2007 to 2010 in Oklahoma, USA, a transitional region with various climates and landscapes, using the integration of the L-band Advanced Land Observation Satellite (ALOS PALSAR Fine Beam Dual Polarization (FBD mosaic dataset and Landsat images. The overall accuracy and Kappa coefficient of the PALSAR/Landsat forest map were about 88.2% and 0.75 in 2010, with the user and producer accuracy about 93.4% and 75.7%, based on the 3270 random ground plots collected in 2012 and 2013. Compared with the forest products from Japan Aerospace Exploration Agency (JAXA, National Land Cover Database (NLCD, Oklahoma Ecological Systems Map (OKESM and Oklahoma Forest Resource Assessment (OKFRA, the PALSAR/Landsat forest map showed great improvement. The area of the PALSAR/Landsat forest was about 40,149 km2 in 2010, which was close to the area from OKFRA (40,468 km2, but much larger than those from JAXA (32,403 km2 and NLCD (37,628 km2. We analyzed annual forest cover dynamics, and the results show extensive forest cover loss (2761 km2, 6.9% of the total forest area in 2010 and gain (3630 km2, 9.0% in southeast and central Oklahoma, and the total area of forests increased by 684 km2 from 2007 to 2010. This study clearly demonstrates the potential of data fusion between PALSAR and Landsat images for mapping annual forest cover dynamics in sub-humid to semi-arid regions, and the resultant forest maps would be

  7. A cloud shadow detection method combined with cloud height iteration and spectral analysis for Landsat 8 OLI data (United States)

    Sun, Lin; Liu, Xinyan; Yang, Yikun; Chen, TingTing; Wang, Quan; Zhou, Xueying


    Although enhanced over prior Landsat instruments, Landsat 8 OLI can obtain very high cloud detection precisions, but for the detection of cloud shadows, it still faces great challenges. Geometry-based cloud shadow detection methods are considered the most effective and are being improved constantly. The Function of Mask (Fmask) cloud shadow detection method is one of the most representative geometry-based methods that has been used for cloud shadow detection with Landsat 8 OLI. However, the Fmask method estimates cloud height employing fixed temperature rates, which are highly uncertain, and errors of large area cloud shadow detection can be caused by errors in estimations of cloud height. This article improves the geometry-based cloud shadow detection method for Landsat OLI from the following two aspects. (1) Cloud height no longer depends on the brightness temperature of the thermal infrared band but uses a possible dynamic range from 200 m to 12,000 m. In this case, cloud shadow is not a specific location but a possible range. Further analysis was carried out in the possible range based on the spectrum to determine cloud shadow location. This effectively avoids the cloud shadow leakage caused by the error in the height determination of a cloud. (2) Object-based and pixel spectral analyses are combined to detect cloud shadows, which can realize cloud shadow detection from two aspects of target scale and pixel scale. Based on the analysis of the spectral differences between the cloud shadow and typical ground objects, the best cloud shadow detection bands of Landsat 8 OLI were determined. The combined use of spectrum and shape can effectively improve the detection precision of cloud shadows produced by thin clouds. Several cloud shadow detection experiments were carried out, and the results were verified by the results of artificial recognition. The results of these experiments indicated that this method can identify cloud shadows in different regions with correct

  8. Mapping paddy rice planting area in northeastern Asia with Landsat 8 images, phenology-based algorithm and Google Earth Engine (United States)

    Dong, Jinwei; Xiao, Xiangming; Menarguez, Michael A.; Zhang, Geli; Qin, Yuanwei; Thau, David; Biradar, Chandrashekhar; Moore, Berrien


    Area and spatial distribution information of paddy rice are important for understanding of food security, water use, greenhouse gas emission, and disease transmission. Due to climatic warming and increasing food demand, paddy rice has been expanding rapidly in high latitude areas in the last decade, particularly in northeastern (NE) Asia. Current knowledge about paddy rice fields in these cold regions is limited. The phenology- and pixel-based paddy rice mapping (PPPM) algorithm, which identifies the flooding signals in the rice transplanting phase, has been effectively applied in tropical areas, but has not been tested at large scale of cold regions yet. Despite the effects from more snow/ice, paddy rice mapping in high latitude areas is assumed to be more encouraging due to less clouds, lower cropping intensity, and more observations from Landsat sidelaps. Moreover, the enhanced temporal and geographic coverage from Landsat 8 provides an opportunity to acquire phenology information and map paddy rice. This study evaluated the potential of Landsat 8 images on annual paddy rice mapping in NE Asia which was dominated by single cropping system, including Japan, North Korea, South Korea, and NE China. The cloud computing approach was used to process all the available Landsat 8 imagery in 2014 (143 path/rows, ~3290 scenes) with the Google Earth Engine (GEE) platform. The results indicated that the Landsat 8, GEE, and improved PPPM algorithm can effectively support the yearly mapping of paddy rice in NE Asia. The resultant paddy rice map has a high accuracy with the producer (user) accuracy of 73% (92%), based on the validation using very high resolution images and intensive field photos. Geographic characteristics of paddy rice distribution were analyzed from aspects of country, elevation, latitude, and climate. The resultant 30-m paddy rice map is expected to provide unprecedented details about the area, spatial distribution, and landscape pattern of paddy rice fields

  9. An Analysis LANDSAT-4 Thematic Mapper Geometric Properties (United States)

    Walker, R. E.; Zobrist, A. L.; Bryant, N. A.; Gokhman, B.; Friedman, S. Z.; Logan, T. L.


    LANDSAT Thematic Mapper P-data of Washington, D. C., Harrisburg, PA, and Salton Sea, CA are analyzed to determine magnitudes and causes of error in the geometric conformity of the data to known Earth surface geometry. Several tests of data geometry are performed. Intraband and interband correlation and registration are investigated, exclusive of map based ground truth. The magnitudes and statistical trends of pixel offsets between a single band's mirror scans (due to processing procedures) are computed, and the inter-band integrity of registration is analyzed. A line to line correlation analysis is included.

  10. Landsat analysis of tropical forest succession employing a terrain model (United States)

    Barringer, T. H.; Robinson, V. B.; Coiner, J. C.; Bruce, R. C.


    Landsat multispectral scanner (MSS) data have yielded a dual classification of rain forest and shadow in an analysis of a semi-deciduous forest on Mindonoro Island, Philippines. Both a spatial terrain model, using a fifth side polynomial trend surface analysis for quantitatively estimating the general spatial variation in the data set, and a spectral terrain model, based on the MSS data, have been set up. A discriminant analysis, using both sets of data, has suggested that shadowing effects may be due primarily to local variations in the spectral regions and can therefore be compensated for through the decomposition of the spatial variation in both elevation and MSS data.

  11. Near Real-Time Browsable Landsat-8 Imagery


    Cheng-Chien Liu; Ryosuke Nakamura; Ming-Hsun Ko; Tomoya Matsuo; Soushi Kato; Hsiao-Yuan Yin; Chung-Shiou Huang


    The successful launch and operation of Landsat-8 extends the remarkable 40-year acquisition of space-based land remote-sensing data. To respond quickly to emergency needs, real-time data are directly downlinked to 17 ground stations across the world on a routine basis. With a size of approximately 1 Gb per scene, however, the standard level-1 product provided by these stations is not able to serve the general public. Users would like to browse the most up-to-date and historical images of thei...

  12. Inventory and change detection of urban land cover in Illinois using Landsat Thematic Mapper data

    International Nuclear Information System (INIS)

    Cook, E.A.; Iverson, L.R.


    In order to provide information about urban forests and other vegetative land cover in Illinois cities, Landsat TM data from June 17, 1988, were classified for the Chicago metropolitan region and five urban areas of central Illinois. Ten land cover classes were identified, including three types of forestland, cropland, two grassland categories, two urban classes, water, and miscellaneous vegetation. The cities inventoried have a significantly higher proportion of forests and forested residential areas than the surrounding rural areas because of preservation measures and accruement of tree cover from landscaping. Short-term change in land cover for the Chicago region was also assessed by postclassification comparison of the 1988 data with similarly derived data from a June 3, 1985, TM scene. The largest single category of change in the six-county area was cropland to urban land use. A majority of cover loss was conversion of forested tracts to residential areas, and forest cover increase was negligible. 16 refs

  13. Shape selection in Landsat time series: A tool for monitoring forest dynamics (United States)

    Gretchen G. Moisen; Mary C. Meyer; Todd A. Schroeder; Xiyue Liao; Karen G. Schleeweis; Elizabeth A. Freeman; Chris Toney


    We present a new methodology for fitting nonparametric shape-restricted regression splines to time series of Landsat imagery for the purpose of modeling, mapping, and monitoring annual forest disturbance dynamics over nearly three decades. For each pixel and spectral band or index of choice in temporal Landsat data, our method delivers a smoothed rendition of...

  14. Opening the archive: how free data has enabled the science and monitoring promise of Landsat (United States)

    Michael A. Wulder; Jeffrey G. Masek; Warren B. Cohen; Thomas R. Loveland; Curtis E. Woodcock


    Landsat occupies a unique position in the constellation of civilian earth observation satellites, with a long and rich scientific and applications heritage. With nearly 40 years of continuous observation—since launch of the first satellite in 1972—the Landsat program has benefited from insightful technical specification, robust engineering, and the necessary...

  15. Harmonic analysis of dense time series of landsat imagery for modeling change in forest conditions (United States)

    Barry Tyler. Wilson


    This study examined the utility of dense time series of Landsat imagery for small area estimation and mapping of change in forest conditions over time. The study area was a region in north central Wisconsin for which Landsat 7 ETM+ imagery and field measurements from the Forest Inventory and Analysis program are available for the decade of 2003 to 2012. For the periods...

  16. Regional analysis of Landsat data concerning unconformity-vein uranium deposits, Pine Creek Geosyncline, Australia

    International Nuclear Information System (INIS)

    Raines, G.L.


    Linear features mapped from enhanced Landsat images in zones defining lineaments trending northeast and east-northeast across the uranium area of northern Australia. A model using Landsat data to select areas for uranium exploration is proposed, based on the observed spatial relation of uranium deposits and the newly defined major lineaments

  17. Using Landsat-derived disturbance history (1972-2010) to predict current forest structure (United States)

    Dirk Pflugmacher; Warren B. Cohen; Robert E. Kennedy


    Lidar is currently the most accurate method for remote estimation of forest structure, but it has limited spatial and temporal coverage. Conversely, Landsat data are more widely available, but exhibit a weaker relationship with structure under medium to high leaf area conditions. One potentially valuable means of enhancing the relationship between Landsat reflectance...

  18. Landsat Pathfinder tropical forest information management system (United States)

    Salas, W.; Chomentowski, W.; Harville, J.; Skole, D.; Vellekamp, K.


    A Tropical Forest Information Management System_(TFIMS) has been designed to fulfill the needs of HTFIP in such a way that it tracks all aspects of the generation and analysis of the raw satellite data and the derived deforestation dataset. The system is broken down into four components: satellite image selection, processing, data management and archive management. However, as we began to think of how the TFIMS could also be used to make the data readily accessible to all user communities we realized that the initial system was too project oriented and could only be accessed locally. The new system needed development in the areas of data ingest and storage, while at the same time being implemented on a server environment with a network interface accessible via Internet. This paper summarizes the overall design of the existing prototype (version 0) information management system and then presents the design of the new system (version 1). The development of version 1 of the TFIMS is ongoing. There are no current plans for a gradual transition from version 0 to version 1 because the significant changes are in how the data within the HTFIP will be made accessible to the extended community of scientists, policy makers, educators, and students and not in the functionality of the basic system.

  19. A forester's look at the application of image manipulation techniques to multitemporal Landsat data (United States)

    Williams, D. L.; Stauffer, M. L.; Leung, K. C.


    Registered, multitemporal Landsat data of a study area in central Pennsylvania were analyzed to detect and assess changes in the forest canopy resulting from insect defoliation. Images taken July 19, 1976, and June 27, 1977, were chosen specifically to represent forest canopy conditions before and after defoliation, respectively. Several image manipulation and data transformation techniques, developed primarily for estimating agricultural and rangeland standing green biomass, were applied to these data. The applicability of each technique for estimating the severity of forest canopy defoliation was then evaluated. All techniques tested had highly correlated results. In all cases, heavy defoliation was discriminated from healthy forest. Areas of moderate defoliation were confused with healthy forest on northwest (NW) aspects, but were distinct from healthy forest conditions on southeast (SE)-facing slopes.

  20. Ten Years of Vegetation Change in Northern California Marshlands Detected using Landsat Satellite Image Analysis (United States)

    Potter, Christopher


    The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology was applied to detected changes in perennial vegetation cover at marshland sites in Northern California reported to have undergone restoration between 1999 and 2009. Results showed extensive contiguous areas of restored marshland plant cover at 10 of the 14 sites selected. Gains in either woody shrub cover and/or from recovery of herbaceous cover that remains productive and evergreen on a year-round basis could be mapped out from the image results. However, LEDAPS may not be highly sensitive changes in wetlands that have been restored mainly with seasonal herbaceous cover (e.g., vernal pools), due to the ephemeral nature of the plant greenness signal. Based on this evaluation, the LEDAPS methodology would be capable of fulfilling a pressing need for consistent, continual, low-cost monitoring of changes in marshland ecosystems of the Pacific Flyway.

  1. Reconstructing Historical Land Cover Type and Complexity by Synergistic Use of Landsat Multispectral Scanner and CORONA

    Directory of Open Access Journals (Sweden)

    Amir Reza Shahtahmassebi


    Full Text Available Survey data describing land cover information such as type and diversity over several decades are scarce. Therefore, our capacity to reconstruct historical land cover using field data and archived remotely sensed data over large areas and long periods of time is somewhat limited. This study explores the relationship between CORONA texture—a surrogate for actual land cover type and complexity—with spectral vegetation indices and texture variables derived from Landsat MSS under the Spectral Variation Hypothesis (SVH such as to reconstruct historical continuous land cover type and complexity. Image texture of CORONA was calculated using a mean occurrence measure while image textures of Landsat MSS were calculated by occurrence and co-occurrence measures. The relationship between these variables was evaluated using correlation and regression techniques. The reconstruction procedure was undertaken through regression kriging. The results showed that, as expected, texture based on the visible bands and corresponding indices indicated larger correlation with CORONA texture, a surrogate of land cover (correlation >0.65. In terms of prediction, the combination of the first-order mean of band green, second-order measure of tasseled cap brightness, second-order mean of Normalized Visible Index (NVI and second-order entropy of NIR yielded the best model with respect to Akaike’s Information Criterion (AIC, r-square, and variance inflation factors (VIF. The regression model was then used in regression kriging to map historical continuous land cover. The resultant maps indicated the type and degree of complexity in land cover. Moreover, the proposed methodology minimized the impacts of topographic shadow in the region. The performance of this approach was compared with two conventional classification methods: hard classifiers and continuous classifiers. In contrast to conventional techniques, the technique could clearly quantify land cover complexity and

  2. Monitoring conterminous United States (CONUS) land cover change with Web-Enabled Landsat Data (WELD) (United States)

    Hansen, M.C.; Egorov, Alexey; Potapov, P.V.; Stehman, S.V.; Tyukavina, A.; Turubanova, S.A.; Roy, David P.; Goetz, S.J.; Loveland, Thomas R.; Ju, J.; Kommareddy, A.; Kovalskyy, Valeriy; Forsyth, C.; Bents, T.


    Forest cover loss and bare ground gain from 2006 to 2010 for the conterminous United States (CONUS) were quantified at a 30 m spatial resolution using Web-Enabled Landsat Data available from the USGS Center for Earth Resources Observation and Science (EROS) ( The approach related multi-temporal WELD metrics and expert-derived training data for forest cover loss and bare ground gain through a decision tree classification algorithm. Forest cover loss was reported at state and ecoregional scales, and the identification of core forests' absent of change was made and verified using LiDAR data from the GLAS (Geoscience Laser Altimetry System) instrument. Bare ground gain correlated with population change for large metropolitan statistical areas (MSAs) outside of desert or semi-desert environments. GoogleEarth™ time-series images were used to validate the products. Mapped forest cover loss totaled 53,084 km2 and was found to be depicted conservatively, with a user's accuracy of 78% and a producer's accuracy of 68%. Excluding errors of adjacency, user's and producer's accuracies rose to 93% and 89%, respectively. Mapped bare ground gain equaled 5974 km2 and nearly matched the estimated area from the reference (GoogleEarth™) classification; however, user's (42%) and producer's (49%) accuracies were much less than those of the forest cover loss product. Excluding errors of adjacency, user's and producer's accuracies rose to 62% and 75%, respectively. Compared to recent 2001–2006 USGS National Land Cover Database validation data for forest loss (82% and 30% for respective user's and producer's accuracies) and urban gain (72% and 18% for respective user's and producer's accuracies), results using a single CONUS-scale model with WELD data are promising and point to the potential for national-scale operational mapping of key land cover transitions. However, validation results highlighted limitations, some of which can be addressed by

  3. Geological analysis of parts of the southern Arabian Shield based on Landsat imagery (United States)

    Qari, Mohammed Yousef Hedaytullah T.

    This thesis examines the capability and applicability of Landsat multispectral remote sensing data for geological analysis in the arid southern Arabian Shield, which is the eastern segment of the Nubian-Arabian Shield surrounding the Red Sea. The major lithologies in the study area are Proterozoic metavolcanics, metasediments, gneisses and granites. Three test-sites within the study area, located within two tectonic assemblages, the Asir Terrane and the Nabitah Mobile Belt, were selected for detailed comparison of remote sensing methods and ground geological studies. Selected digital image processing techniques were applied to full-resolution Landsat TM imagery and the results are interpreted and discussed. Methods included: image contrast improvement, edge enhancement for detecting lineaments and spectral enhancement for geological mapping. The last method was based on two principles, statistical analysis of the data and the use of arithmetical operators. New and detailed lithological and structural maps were constructed and compared with previous maps of these sites. Examples of geological relations identified using TM imagery include: recognition and mapping of migmatites for the first time in the Arabian Shield; location of the contact between the Asir Terrane and the Nabitah Mobile Belt; and mapping of lithologies, some of which were not identified on previous geological maps. These and other geological features were confirmed by field checking. Methods of lineament enhancement implemented in this study revealed structural lineaments, mostly mapped for the first time, which can be related to regional tectonics. Structural analysis showed that the southern Arabian Shield has been affected by at least three successive phases of deformation. The third phase is the most dominant and widespread. A crustal evolutionary model in the vicinity of the study area is presented showing four stages, these are: arc stage, accretion stage, collision stage and post

  4. Monitoring Changes of Ecosystem Services Supply and Demand Pattern in Central and Southern Liaoning Urban Agglomerations, China Using Landsat Images (United States)

    Li, B.; Huang, F.; Chang, S.; Qi, H.; Zhai, H.


    Indentifying the spatio-temporal patterns of ecosystem services supply and demand and the driving forces is of great significance to the regional ecological security and sustainable socio-economic development. Due to long term and high-intensity development, the ecological environment in central and southern Liaoning urban agglomerations has been greatly destroyed thereafter has restricted sustainable development in this region. Based on Landsat ETM and OLI images, land use of this urban agglomeration in 2005, 2010 and 2015 was extracted. The integrative index of multiple-ecosystem services (IMES) was used to quantify the supply (IMESs), demand (IMESd) and balance (IMESb) of multiple-ecosystem services, The spatial patterns of ecosystem services and its dynamics for the period of 2005-2015 were revealed. The multiple regression and stepwise regression analysis were used to explore relationships between ecosystem services and socioeconomic factors. The results showed that the IMESs of the region increased by 2.93 %, whereas IMESd dropped 38 %. The undersupplied area was reduced to 2. The IMESs and IMESb were mainly negatively correlated with gross domestic product (GDP), population density, foreign investment and industrial output, while GDP per capita and the number of teachers had significant positive impacts on ecosystem services supply. The positive correlation between IMESd and GDP, population density and foreign investment were found. The ecosystem services models were established. Supply and balance of multiple-ecosystem services were positively correlated with population density, but the demand was the opposite. The results can provide some reference value for the coordinately economic and ecological development in the study area.

  5. Landsat surface reflectance quality assurance extraction (version 1.7) (United States)

    Jones, J.W.; Starbuck, M.J.; Jenkerson, Calli B.


    The U.S. Geological Survey (USGS) Land Remote Sensing Program is developing an operational capability to produce Climate Data Records (CDRs) and Essential Climate Variables (ECVs) from the Landsat Archive to support a wide variety of science and resource management activities from regional to global scale. The USGS Earth Resources Observation and Science (EROS) Center is charged with prototyping systems and software to generate these high-level data products. Various USGS Geographic Science Centers are charged with particular ECV algorithm development and (or) selection as well as the evaluation and application demonstration of various USGS CDRs and ECVs. Because it is a foundation for many other ECVs, the first CDR in development is the Landsat Surface Reflectance Product (LSRP). The LSRP incorporates data quality information in a bit-packed structure that is not readily accessible without postprocessing services performed by the user. This document describes two general methods of LSRP quality-data extraction for use in image processing systems. Helpful hints for the installation and use of software originally developed for manipulation of Hierarchical Data Format (HDF) produced through the National Aeronautics and Space Administration (NASA) Earth Observing System are first provided for users who wish to extract quality data into separate HDF files. Next, steps follow to incorporate these extracted data into an image processing system. Finally, an alternative example is illustrated in which the data are extracted within a particular image processing system.

  6. Using Landsat TM and NFI data to estimate wood volume, tree biomass and stand age in Dalarna

    Energy Technology Data Exchange (ETDEWEB)

    Reese, Heather; Nilsson, Mats


    As part of the `Monitoring of forest ecosystems` project, within the MISTRA program Remote Sensing for the Environment (RESE), and also with funding from the County Administration Board of Dalarna, a demonstration project was undertaken to estimate forest stand parameters in Dalarna with the use of satellite data. Using two full scenes of Landsat Thematic Mapper data and sample plot data from the Swedish National Forest Inventory, estimations of above ground tree biomass, age, total wood volume, and separate tree species volumes were made using the `k Nearest Neighbor` method. Accuracy assessment results at the single pixel level for total wood volume are consistent with results from previous kNN estimations, with an overall relative RMSE of 75% for the western scene, and 58% overall relative RMSE for the eastern scene. Validation data show a bias of the estimate toward the mean value of the estimation data. The pixel level estimates of above ground tree biomass and age had similar validation results to those for total wood volume. Biomass estimates had a 77% relative RMSE for the western scene, and 69% for the eastern scene. Age estimates had a relative RMSE of 60% in the western scene and 57% in the eastern scene. The results may suggest the need to incorporate a geographic limitation on the plots used in the estimation, and to further investigate the co-registration between the satellite and plot data. While pixel lever errors are high, an aggregation of the estimates to larger (compartment-sized) areas could decrease the error significantly. Previous similar studies have shown that an RMSE of 10% for total wood volume can be obtained for as small areas as 100 to 450 hectares. The estimates from this study will be evaluated for use by the County Administration Board of Dalarna to find areas of ecological interest and to assist in planning 14 refs, 4 figs, 4 tabs

  7. Assessing the effectiveness of Landsat 8 chlorophyll a retrieval algorithms for regional freshwater monitoring. (United States)

    Boucher, Jonah; Weathers, Kathleen C; Norouzi, Hamid; Steele, Bethel


    Predicting algal blooms has become a priority for scientists, municipalities, businesses, and citizens. Remote sensing offers solutions to the spatial and temporal challenges facing existing lake research and monitoring programs that rely primarily on high-investment, in situ measurements. Techniques to remotely measure chlorophyll a (chl a) as a proxy for algal biomass have been limited to specific large water bodies in particular seasons and narrow chl a ranges. Thus, a first step toward prediction of algal blooms is generating regionally robust algorithms using in situ and remote sensing data. This study explores the relationship between in-lake measured chl a data from Maine and New Hampshire, USA lakes and remotely sensed chl a retrieval algorithm outputs. Landsat 8 images were obtained and then processed after required atmospheric and radiometric corrections. Six previously developed algorithms were tested on a regional scale on 11 scenes from 2013 to 2015 covering 192 lakes. The best performing algorithm across data from both states had a 0.16 correlation coefficient (R 2 ) and P ≤ 0.05 when Landsat 8 images within 5 d, and improved to R 2 of 0.25 when data from Maine only were used. The strength of the correlation varied with the specificity of the time window in relation to the in-situ sampling date, explaining up to 27% of the variation in the data across several scenes. Two previously published algorithms using Landsat 8's Bands 1-4 were best correlated with chl a, and for particular late-summer scenes, they accounted for up to 69% of the variation in in-situ measurements. A sensitivity analysis revealed that a longer time difference between in situ measurements and the satellite image increased uncertainty in the models, and an effect of the time of year on several indices was demonstrated. A regional model based on the best performing remote sensing algorithm was developed and was validated using independent in situ measurements and satellite

  8. Characterizing spatiotemporal dynamics in phenology of urban ecosystems based on Landsat data

    Energy Technology Data Exchange (ETDEWEB)

    Li, Xuecao; Zhou, Yuyu; Asrar, Ghassem R.; Meng, Lin


    Seasonal phenology of vegetation plays an important role in global carbon cycle and ecosystem productivity. In urban environments, vegetation phenology is also important because of its influence on public health (e.g., allergies), and energy demand (e.g. cooling effects). In this study, we studied the potential use of remotely sensed observations (i.e. Landsat data) to derive some phenology indicators for vegetation embedded within the urban core domains in four distinctly different U.S. regions (Washington, D.C., King County in Washington, Polk County in Iowa, and Baltimore City and County in Maryland) during the past three decades. We used all available Landsat observations (circa 3000 scenes) from 1982 to 2015 and a self-adjusting double logistic model to detect and quantify the annual change of vegetation phenophases, i.e. indicators of seasonal changes in vegetation. The proposed model can capture and quantify not only phenophases of dense vegetation in rural areas, but also those of mixed vegetation in urban core domains. The derived phenology indicators show a good agreement with similar indicators derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and in situ observations, suggesting that the phenology dynamic depicted by the proposed model is reliable. The vegetation phenology and its seasonal and interannual dynamics demonstrate a distinct spatial pattern in urban domains with an earlier (9–14 days) start-of season (SOS) and a later (13–20 days) end-of season (EOS), resulting in an extended (5–30 days) growing season length (GSL) when compared to the surrounding suburban and rural areas in the four study regions. There is a general long-term trend of decreasing SOS (-0.30 day per year), and increasing EOS and GSL (0.50 and 0.90 day per year, respectively) over past three decades for these study regions. The magnitude of these trends varies among the four urban systems due to their diverse local climate conditions, vegetation

  9. Mapping Soil Salinity/Sodicity by using Landsat OLI Imagery and PLSR Algorithm over Semiarid West Jilin Province, China (United States)

    Liu, Mingyue; Du, Baojia; Zhang, Bai


    Soil salinity and sodicity can significantly reduce the value and the productivity of affected lands, posing degradation, and threats to sustainable development of natural resources on earth. This research attempted to map soil salinity/sodicity via disentangling the relationships between Landsat 8 Operational Land Imager (OLI) imagery and in-situ measurements (EC, pH) over the west Jilin of China. We established the retrieval models for soil salinity and sodicity using Partial Least Square Regression (PLSR). Spatial distribution of the soils that were subjected to hybridized salinity and sodicity (HSS) was obtained by overlay analysis using maps of soil salinity and sodicity in geographical information system (GIS) environment. We analyzed the severity and occurring sizes of soil salinity, sodicity, and HSS with regard to specified soil types and land cover. Results indicated that the models’ accuracy was improved by combining the reflectance bands and spectral indices that were mathematically transformed. Therefore, our results stipulated that the OLI imagery and PLSR method applied to mapping soil salinity and sodicity in the region. The mapping results revealed that the areas of soil salinity, sodicity, and HSS were 1.61 × 106 hm2, 1.46 × 106 hm2, and 1.36 × 106 hm2, respectively. Also, the occurring area of moderate and intensive sodicity was larger than that of salinity. This research may underpin efficiently mapping regional salinity/sodicity occurrences, understanding the linkages between spectral reflectance and ground measurements of soil salinity and sodicity, and provide tools for soil salinity monitoring and the sustainable utilization of land resources. PMID:29614727

  10. A New Automatic Method of Urban Areas Mapping in East Asia from LANDSAT Data (United States)

    XU, R.; Jia, G.


    Cities, as places where human activities are concentrated, account for a small percent of global land cover but are frequently cited as the chief causes of, and solutions to, climate, biogeochemistry, and hydrology processes at local, regional, and global scales. Accompanying with uncontrolled economic growth, urban sprawl has been attributed to the accelerating integration of East Asia into the world economy and involved dramatic changes in its urban form and land use. To understand the impact of urban extent on biogeophysical processes, reliable mapping of built-up areas is particularly essential in eastern cities as a result of their characteristics of smaller patches, more fragile, and a lower fraction of the urban landscape which does not have natural than in the West. Segmentation of urban land from other land-cover types using remote sensing imagery can be done by standard classification processes as well as a logic rule calculation based on spectral indices and their derivations. Efforts to establish such a logic rule with no threshold for automatically mapping are highly worthwhile. Existing automatic methods are reviewed, and then a proposed approach is introduced including the calculation of the new index and the improved logic rule. Following this, existing automatic methods as well as the proposed approach are compared in a common context. Afterwards, the proposed approach is tested separately in cities of large, medium, and small scale in East Asia selected from different LANDSAT images. The results are promising as the approach can efficiently segment urban areas, even in the presence of more complex eastern cities. Key words: Urban extraction; Automatic Method; Logic Rule; LANDSAT images; East AisaThe Proposed Approach of Extraction of Urban Built-up Areas in Guangzhou, China

  11. Analysis of land cover/use changes using Landsat 5 TM data and indices. (United States)

    Ettehadi Osgouei, Paria; Kaya, Sinasi


    Urban expansion and unprecedented rural to urban transition, along with a huge population growth, are major driving forces altering land cover/use in metropolitan areas. Many of the land cover classes such as farmlands, wetlands, forests, and bare soils have been transformed during the past years into human settlements. Identification of the city growth trends and the impact of it on the vegetation cover of an area is essential for a better understanding of the sustainability of urban development processes, both planned and unplanned. Analyzing the causes and consequences of land use dynamics helps local government, urban planners, and managers for the betterment of future plans and minimizing the negative effects.This study determined temporal changes in vegetation cover and built-up area in Istanbul (Turkey) using the normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), and built-up area index (BUAI). The temporal data were based on Landsat 5 Thematic Mapper (TM) images acquired in June of 1984, 2002, 2007, 2009, and 2011. The NDVI was applied to all the Landsat images, and the resulting NDVI images were overlaid to generate an NDVI layer stack image. The same procedure was repeated using the SAVI and BUAI images. The layer stack images revealed those areas that had changed in terms of the different indices over the years. To determine temporal change trends, the values of 150 randomly selected control points were extracted from the same locations in the NDVI, SAVI, and BUAI layer stack images. The results obtained from these control points showed that vegetation cover decreased considerably because of a remarkable increase in the built-up area.

  12. Mapping areas invaded by Prosopis juliflora in Somaliland on Landsat 8 imagery (United States)

    Rembold, Felix; Leonardi, Ugo; Ng, Wai-Tim; Gadain, Hussein; Meroni, Michele; Atzberger, Clement


    Prosopis juliflora is a fast growing tree species originating from South and Central America with a high invasion potential in semi-arid areas around the globe. It was introduced to East Africa for the stabilization of dune systems and for providing fuel wood after prolonged droughts and deforestation in the 1970s and 1980s. In many dry lands in East Africa the species has expanded rapidly and has become challenging to control. The species generally starts its colonization on deep soils with high water availability while in later stages or on poorer soils, its thorny thickets expand into drier grasslands and rangelands. Abandoned or low input farmland is also highly susceptible for invasion as P. juliflora has competitive advantages to native species and is extremely drought tolerant. In this work we describe a rapid approach to detect and map P. juliflora invasion at country level for the whole of Somaliland. Field observations were used to delineate training sites for a supervised classification of Landsat 8 imagery collected during the driest period of the year (i.e., from late February to early April). The choice of such a period allowed to maximise the spectral differences between P. juliflora and other species present in the area, as P. juliflora tends to maintain a higher vigour and canopy water content than native vegetation, when exposed to water stress. The results of our classification map the current status of invasion of Prosopis in Somaliland showing where the plant is invading natural vegetation or agricultural areas. These results have been verified for two spatial subsets of the whole study area with very high resolution (VHR) imagery, proving that Landsat 8 imagery is highly adequate to map P. juliflora. The produced map represents a baseline for understanding spatial distribution of P. juliflora across Somaliland but also for change detection and monitoring of long term dynamics in support to P. juliflora management and control activities.

  13. An assessment of radiance in Landsat TM middle and thermal infrared wavebands for the detection of tropical forest regeneration

    International Nuclear Information System (INIS)

    Boyd, D.S.; Foody, G.M.; Curran, P.J.; Lucas, R.M.; Honzak, M.


    It has been postulated that tropical forests regenerating after deforestation constitute an unmeasured terrestrial sink of atmospheric carbon, and that the strength of this sink is a function of regeneration stage. Such regeneration stages can be characterized by biophysical properties, such as leaf and wood biomass, which influence the radiance emitted and/or reflected from the forest canopy. Remotely sensed data can therefore be used to estimate these biophysical properties and thereby determine the forest regenerative stage. Studies conducted on temperate forests have related biophysical properties successfully with red and near-infrared radiance, particularly within the Normalized Difference Vegetation Index (NDVI). However, only weak correlations have generally been observed for tropical forests and it is suggested here that the relationship between forest biophysical properties and middle and thermal infrared radiance may be stronger than that between those properties and visible and near-infrared radiance.An assessment of Landsat Thematic Mapper (TM) data revealed that radiance acquired in middle and thermal infrared wavebands contained significant information for the detection of regeneration stages in Amazonian tropical forests. It was demonstrated that tropical forest regeneration stages were most separable using middle infrared and thermal infrared wavebands and that the correlation with regeneration stage was stronger with middle infrared, thermal infrared or combinations of these wavebands than they were with visible, near infrared or combinations of these wavebands. For example, correlation coefficients increased from — 0·26 (insignificant at 95 per cent confidence level) when using the NDVI, to up to 0·93 (significant at 99 per cent confidence level) for a vegetation index containing data acquired in the middle and thermal infrared wavebands. These results point to the value of using data acquired in middle and thermal infrared wavebands for the

  14. From Landsat through SLI: Ball Aerospace Instrument Architecture for Earth Surface Monitoring (United States)

    Wamsley, P. R.; Gilmore, A. S.; Malone, K. J.; Kampe, T. U.; Good, W. S.


    The Landsat legacy spans more than forty years of moderate resolution, multi-spectral imaging of the Earth's surface. Applications for Landsat data include global environmental change, disaster planning and recovery, crop and natural resource management, and glaciology. In recent years, coastal water science has been greatly enhanced by the outstanding on-orbit performance of Landsat 8. Ball Aerospace designed and built the Operational Land Imager (OLI) instrument on Landsat 8, and is in the process of building OLI 2 for Landsat 9. Both of these instruments have the same design however improved performance is expected from OLI 2 due to greater image bit depth (14 bit on OLI 2 vs 12 bit on OLI). Ball Aerospace is currently working on two novel instrument architectures applicable to Sustainable Land Imaging for Landsat 10 and beyond. With increased budget constraints probable for future missions, technological improvements must be included in future instrument architectures to enable increased capabilities at lower cost. Ball presents the instrument architectures and associated capabilities enabling new science in past, current, and future Landsat missions.

  15. Multispectral processing of ERTS-A (LANDSAT) data for uranium exploration in the Wind River Basin, Wyoming: a visible region ratio to enhance surface alteration associated with roll-type uraium deposits. Final report, June 1974--July 1975

    International Nuclear Information System (INIS)

    Salmon, B.C.; Pillars, W.W.


    The purpose of this report is to document possible detection capabilities of the LANDSAT multispectral scanner data for use in exploration for uranium roll-type deposits. Spectral reflectivity, mineralogy, iron content, and color paramenters were measured for twenty natural surface samples collected from a semiarid region. The relationships of these properties to LANDSAT response-weighted reflectances and to reflectance ratios are discussed. It was found that the single ratio technique of multispectral processing is likely to be sensitive enough to separate hematitic stain, but not limonitic. A combination of the LANDSAT R/sub 5,4/ and R/sub 7,6/ ratios, and a processing technique sensitive to vegetative cover is recommended for detecting areas of limonitic stain. Digital level slicing of LANDSAT R/sub 5,4/ over the Wind River Basin, after geometric correction, resulted in adequate enhancement of Triassic redbeds and lighter red materials, but not for limonitic areas. No recommendations for prospects in the area were made. Information pertaining to techniques of evaluating laboratory reflectance spectra for remote sensing applications, ratio processing, and planimetric correction of LANDSAT data is presented qualitatively

  16. Five-year results from a prospective multicentre study of percutaneous pulmonary valve implantation demonstrate sustained removal of significant pulmonary regurgitation, improved right ventricular outflow tract obstruction and improved quality of life

    DEFF Research Database (Denmark)

    Hager, Alfred; Schubert, Stephan; Ewert, Peter


    . The EQ-5D quality of life utility index and visual analogue scale scores were both significantly improved six months post PPVI and remained so at five years. CONCLUSIONS: Five-year results following PPVI demonstrate resolved moderate or severe pulmonary regurgitation, improved right ventricular outflow...

  17. Landsat-based trend analysis of lake dynamics across northern permafrost regions (United States)

    Nitze, Ingmar; Grosse, Guido; Jones, Benjamin M.; Arp, Christopher D.; Ulrich, Mathias; Federov, Alexander; Veremeeva, Alexandra


    Lakes are a ubiquitous landscape feature in northern permafrost regions. They have a strong impact on carbon, energy and water fluxes and can be quite responsive to climate change. The monitoring of lake change in northern high latitudes, at a sufficiently accurate spatial and temporal resolution, is crucial for understanding the underlying processes driving lake change. To date, lake change studies in permafrost regions were based on a variety of different sources, image acquisition periods and single snapshots, and localized analysis, which hinders the comparison of different regions. Here we present, a methodology based on machine-learning based classification of robust trends of multi-spectral indices of Landsat data (TM,ETM+, OLI) and object-based lake detection, to analyze and compare the individual, local and regional lake dynamics of four different study sites (Alaska North Slope, Western Alaska, Central Yakutia, Kolyma Lowland) in the northern permafrost zone from 1999 to 2014. Regional patterns of lake area change on the Alaska North Slope (-0.69%), Western Alaska (-2.82%), and Kolyma Lowland (-0.51%) largely include increases due to thermokarst lake expansion, but more dominant lake area losses due to catastrophic lake drainage events. In contrast, Central Yakutia showed a remarkable increase in lake area of 48.48%, likely resulting from warmer and wetter climate conditions over the latter half of the study period. Within all study regions, variability in lake dynamics was associated with differences in permafrost characteristics, landscape position (i.e. upland vs. lowland), and surface geology. With the global availability of Landsat data and a consistent methodology for processing the input data derived from robust trends of multi-spectral indices, we demonstrate a transferability, scalability and consistency of lake change analysis within the northern permafrost region.

  18. Influence of Ecological Factors on Estimation of Impervious Surface Area Using Landsat 8 Imagery

    Directory of Open Access Journals (Sweden)

    Yuqiu Jia


    Full Text Available Estimation of impervious surface area is important to the study of urban environments and social development, but surface characteristics, as well as the temporal, spectral, and spatial resolutions of remote sensing images, influence the estimation accuracy. To investigate the effects of regional environmental characteristics on the estimation of impervious surface area, we divided China into seven sub-regions based on climate, soil type, feature complexity, and vegetation phenology: arid and semi-arid areas, Huang-Huai-Hai winter wheat production areas, typical temperate regions, the Pearl River Delta, the middle and lower reaches of the Yangtze River, typical tropical and subtropical regions, and the Qinghai Tibet Plateau. Impervious surface area was estimated from Landsat 8 images of five typical cities, including Yinchuan, Shijiazhuang, Shenyang, Ningbo, and Kunming. Using the linear spectral unmixing method, impervious and permeable surface areas were determined at the pixel-scale based on end-member proportions. We calculated the producer’s accuracy, user’s accuracy, and overall accuracy to assess the estimation accuracy, and compared the accuracies among images acquired from different seasons and locations. In tropical and subtropical regions, vegetation canopies can confound the identification of impervious surfaces and, thus, images acquired in winter, early spring, and autumn are most suitable; estimations in the Pearl River Delta, the middle and lower reaches of the Yangtze River are influenced by soil, vegetation phenology, vegetation canopy, and water, and images acquired in spring, summer, and autumn provide the best results; in typical temperate areas, images acquired from spring to autumn are most effective for estimations; in winter wheat-growing areas, images acquired throughout the year are suitable; and in arid and semi-arid areas, summer and early autumn, during which vegetation is abundant, are the optimal seasons for

  19. Vegetation pattern of Istanbul from the Landsat data and the relationship with meteorological parameters

    Directory of Open Access Journals (Sweden)

    Z. Aslan


    Full Text Available This paper discusses the preliminary results of a study on the vegetation pattern and its relationship with meteorological parameters in and around Istanbul. The study covers an area of over 6800 km2 consisting of urban and suburban centers, and uses the visible and near-infrared bands of Landsat. The spatial variation of the Normalized Difference Vegetation Index (NDVI and meteorological parameters such as sensible heat flux, momentum flux, relative humidity, moist static energy, rainfall rate and temperature have been investigated based on observations in ten stations in the European (Thracian and Anatolian parts of Istanbul. NDVI values have been evaluated from the Landsat data for a single day, viz. 24 October 1986, using ERDAS in ten different classes. The simultaneous spatial variations of sensible heat and momentum fluxes have been computed from the wind and temperature profiles using the Monin-Obukhov similarity theory. The static energy variations are based on the surface meteorological observations. There is very good correlation between NDVI and rainfall rate. Good correlation also exists between: NDVI and relative humidity; NDVI, sensible heat flux and relative humidity; NDVI, momentum flux and emissivity; and NDVI, sensible heat flux and emissivity. The study suggests that the momentum flux has only marginal impact on NDVI. Due to rapid urbanization,the coastal belt is characterized by reduced NDVI compared to the interior areas, suggesting that thermodynamic discontinuities considerably influence the vegetation pattern. This study is useful for the investigation of small-scale circulation models, especially in urban and suburban areas where differential heating leads to the formation of heat islands. In the long run, such studies on a global scale are vital to gain accurate, timely information on the distribution of vegetation on the earth's surface. This may lead to an understanding of how changes in land cover affect phenomena as

  20. Forest cover of North America in the 1970s mapped using Landsat MSS data (United States)

    Feng, M.; Sexton, J. O.; Channan, S.; Townshend, J. R.


    The distribution and changes in Earth's forests impact hydrological, biogeochemical, and energy fluxes, as well as ecosystems' capacity to support biodiversity and human economies. Long-term records of forest cover are needed across a broad range of investigation, including climate and carbon-cycle modeling, hydrological studies, habitat analyzes, biological conservation, and land-use planning. Satellite-based observations enable mapping and monitoring of forests at ecologically and economically relevant resolutions and continental or even global extents. Following early forest-mapping efforts using coarser resolution remote sensing data such as the Advanced Very High Resolution Radiometer (AVHRR) and MODerate-resolution Imaging Spectroradiometer (MODIS), forests have been mapped regionally at developed by the Global Land Cover Facility (GLCF) as reference, we developed an automated approach to detect forests using MSS data by leveraging the multispectral and phenological characteristics of forests observed in MSS time-series. The forest-cover map is produced with layers representing the year of observation, detection of forest-cover change relative to 1990, and the uncertainty of forest-cover and -change layers. The approach has been implemented with open-source libraries to facilitate processing large volumes of Landsat MSS images on high-performance computing machines. As the first result of our global mapping effort, we present the forest cover for North America. More than 25,000 Landsat MSS scenes were processed to provide a 120-meter resolution forest cover for North America, which will be made publicly available on the GLCF website (

  1. Combining lake and watershed characteristics with Landsat TM data for remote estimation of regional lake clarity (United States)

    McCullough, Ian M.; Loftin, Cyndy; Sader, Steven A.


    Water clarity is a reliable indicator of lake productivity and an ideal metric of regional water quality. Clarity is an indicator of other water quality variables including chlorophyll-a, total phosphorus and trophic status; however, unlike these metrics, clarity can be accurately and efficiently estimated remotely on a regional scale. Remote sensing is useful in regions containing a large number of lakes that are cost prohibitive to monitor regularly using traditional field methods. Field-assessed lakes generally are easily accessible and may represent a spatially irregular, non-random sample of a region. We developed a remote monitoring program for Maine lakes >8 ha (1511 lakes) to supplement existing field monitoring programs. We combined Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) brightness values for TM bands 1 (blue) and 3 (red) to estimate water clarity (secchi disk depth) during 1990–2010. Although similar procedures have been applied to Minnesota and Wisconsin lakes, neither state incorporates physical lake variables or watershed characteristics that potentially affect clarity into their models. Average lake depth consistently improved model fitness, and the proportion of wetland area in lake watersheds also explained variability in clarity in some cases. Nine regression models predicted water clarity (R2 = 0.69–0.90) during 1990–2010, with separate models for eastern (TM path 11; four models) and western Maine (TM path 12; five models that captured differences in topography and landscape disturbance. Average absolute difference between model-estimated and observed secchi depth ranged 0.65–1.03 m. Eutrophic and mesotrophic lakes consistently were estimated more accurately than oligotrophic lakes. Our results show that TM bands 1 and 3 can be used to estimate regional lake water clarity outside the Great Lakes Region and that the accuracy of estimates is improved with additional model variables that reflect

  2. Modeling and Mapping of Soil Salinity with Reflectance Spectroscopy and Landsat Data Using Two Quantitative Methods (PLSR and MARS

    Directory of Open Access Journals (Sweden)

    Said Nawar


    Full Text Available The monitoring of soil salinity levels is necessary for the prevention and mitigation of land degradation in arid environments. To assess the potential of remote sensing in estimating and mapping soil salinity in the El-Tina Plain, Sinai, Egypt, two predictive models were constructed based on the measured soil electrical conductivity (ECe and laboratory soil reflectance spectra resampled to Landsat sensor’s resolution. The models used were partial least squares regression (PLSR and multivariate adaptive regression splines (MARS. The results indicated that a good prediction of the soil salinity can be made based on the MARS model (R2 = 0.73, RMSE = 6.53, and ratio of performance to deviation (RPD = 1.96, which performed better than the PLSR model (R2 = 0.70, RMSE = 6.95, and RPD = 1.82. The models were subsequently applied on a pixel-by-pixel basis to the reflectance values derived from two Landsat images (2006 and 2012 to generate quantitative maps of the soil salinity. The resulting maps were validated successfully for 37 and 26 sampling points for 2006 and 2012, respectively, with R2 = 0.72 and 0.74 for 2006 and 2012, respectively, for the MARS model, and R2 = 0.71 and 0.73 for 2006 and 2012, respectively, for the PLSR model. The results indicated that MARS is a more suitable technique than PLSR for the estimation and mapping of soil salinity, especially in areas with high levels of salinity. The method developed in this paper can be used for other satellite data, like those provided by Landsat 8, and can be applied in other arid and semi-arid environments.

  3. Predicting lake trophic state by relating Secchi-disk transparency measurements to Landsat-satellite imagery for Michigan inland lakes, 2003-05 and 2007-08 (United States)

    Fuller, L.M.; Jodoin, R.S.; Minnerick, R.J.


    Inland lakes are an important economic and environmental resource for Michigan. The U.S. Geological Survey and the Michigan Department of Natural Resources and Environment have been cooperatively monitoring the quality of selected lakes in Michigan through the Lake Water Quality Assessment program. Sampling for this program began in 2001; by 2010, 730 of Michigan’s 11,000 inland lakes are expected to have been sampled once. Volunteers coordinated by the Michigan Department of Natural Resources and Environment began sampling lakes in 1974 and continue to sample (in 2010) approximately 250 inland lakes each year through the Michigan Cooperative Lakes Monitoring Program. Despite these sampling efforts, it still is impossible to physically collect measurements for all Michigan inland lakes; however, Landsat-satellite imagery has been used successfully in Minnesota, Wisconsin, Michigan, and elsewhere to predict the trophic state of unsampled inland lakes greater than 20 acres by producing regression equations relating in-place Secchi-disk measurements to Landsat bands. This study tested three alternatives to methods previously used in Michigan to improve results for predicted statewide Trophic State Index (TSI) computed from Secchi-disk transparency (TSI (SDT)). The alternative methods were used on 14 Landsat-satellite scenes with statewide TSI (SDT) for two time periods (2003– 05 and 2007–08). Specifically, the methods were (1) satellitedata processing techniques to remove areas affected by clouds, cloud shadows, haze, shoreline, and dense vegetation for inland lakes greater than 20 acres in Michigan; (2) comparison of the previous method for producing a single open-water predicted TSI (SDT) value (which was based on an area of interest (AOI) and lake-average approach) to an alternative Gethist method for identifying open-water areas in inland lakes (which follows the initial satellite-data processing and targets the darkest pixels, representing the deepest water

  4. A Hybrid Color Mapping Approach to Fusing MODIS and Landsat Images for Forward Prediction


    Chiman Kwan; Bence Budavari; Feng Gao; Xiaolin Zhu


    We present a new, simple, and efficient approach to fusing MODIS and Landsat images. It is well known that MODIS images have high temporal resolution and low spatial resolution, whereas Landsat images are just the opposite. Similar to earlier approaches, our goal is to fuse MODIS and Landsat images to yield high spatial and high temporal resolution images. Our approach consists of two steps. First, a mapping is established between two MODIS images, where one is at an earlier time, t1, and the...

  5. Use of LANDSAT data to define soil boundaries in Carroll County, Missouri (United States)

    Davidson, S. E.


    Bands 4, 5 and 7 false color composite photographs were prepared using data from LANDSAT scenes acquired during April 1977 and April 1981 on computer compatible tapes, and these color composites were compared with band 7 black and white photographs prepared for the entire county. Delineations of soil boundaries at the soil association level were achieved using LANDSAT spectral reflectance data and slope maps for a portion of Carroll County, Missouri. Forty two spectral reflectance classes from April 1977 LANDSAT data were overlaid on digitized slope maps of nine USGS 7.5 minute series topographic quadrangle slope maps to achieve boundary delineations of the soil associations.

  6. Comparative analysis of different sensor data (Landsat-TM and MOMS) for earth observation and impact on future sensor development

    International Nuclear Information System (INIS)

    Bodechtel, J.; Zilger, J.; Salomonson, V.V.


    The missions of the German Modular Optoelectronic Multispectral Scanner (MOMS) aboard two flights of the United States Space Transportation System STS demonstrated the feasibility of a novel concept with regard to both technical and scientific objectives. On account of the successful missions a cooperative study was instituted for comparing MOMS observations with the more familiar operational Landsat-Thematic Mapper data over selected testsites as a means of obtaining some relative measure of performance. This paper summarizes the results obtained and presents the MOMS-02

  7. Analysis of conifer forest regeneration using Landsat Thematic Mapper data (United States)

    Fiorella, Maria; Ripple, William J.


    Landsat Thematic Mapper (TM) data were used to evaluate young conifer stands in the western Cascade Mountains of Oregon. Regression and correlation analyses were used to describe the relationships between TM band values and age of young Douglas-fir stands (2 to 35 years old). Spectral data from well regenerated Douglas-fir stands were compared to those of poorly regenerated conifer stands. TM bands 1, 2, 3, 5, 6, and 7 were inversely correlated with the age (r greater than or equal to -0.80) of well regenerated Douglas-fir stands. Overall, the 'structural index' (TM 4/5 ratio) had the highest correlation to age of Douglas-fir stands (r = 0.96). Poorly regenerated stands were spectrally distinct from well regenerated Douglas-fir stands after the stands reached an age of approximately 15 years.

  8. A fully redundant power hinge for LANDSAT-D appendages (United States)

    Mamrol, F. E.; Matteo, D. N.


    The configuration and testing of a power driven hinge for deployment of the solar array and antenna boom for the LANDSAT-D spacecraft is discussed. The hinge is fully mechanically and electrically redundant and, thereby, can sustain a single point failure of any one motor (or its power supply), speed reducer, or bearing set without loss of its ability to function. This design utilizes the capability of the stepper motor drive to remove the flexibility of the drive train from the joint stiffness equation when the hinge is loaded against its stop. This feature precludes gapping of the joint under spacecraft maneuver loads even in the absence of a latching feature. Thus, retraction is easily accomplished by motor reversal without the need for a solenoid function to remove the latch.

  9. Forest cover change and fragmentation using Landsat data in Maçka State Forest Enterprise in Turkey. (United States)

    Cakir, Günay; Sivrikaya, Fatih; Keleş, Sedat


    Monitoring forest cover change and understanding the dynamic of forest cover is increasingly important in sustainable development and management of forest ecosystems. This paper uses remote sensing (RS) techniques to monitor forest cover change in Maçka State Forest Enterprise (MSFE) located in NE of Turkey through 1975 to 2000 and then analyses spatial and temporal changes in