WorldWideScience

Sample records for object imagery scale

  1. Object versus spatial visual mental imagery in patients with schizophrenia

    Science.gov (United States)

    Aleman, André; de Haan, Edward H.F.; Kahn, René S.

    2005-01-01

    Objective Recent research has revealed a larger impairment of object perceptual discrimination than of spatial perceptual discrimination in patients with schizophrenia. It has been suggested that mental imagery may share processing systems with perception. We investigated whether patients with schizophrenia would show greater impairment regarding object imagery than spatial imagery. Methods Forty-four patients with schizophrenia and 20 healthy control subjects were tested on a task of object visual mental imagery and on a task of spatial visual mental imagery. Both tasks included a condition in which no imagery was needed for adequate performance, but which was in other respects identical to the imagery condition. This allowed us to adjust for nonspecific differences in individual performance. Results The results revealed a significant difference between patients and controls on the object imagery task (F1,63 = 11.8, p = 0.001) but not on the spatial imagery task (F1,63 = 0.14, p = 0.71). To test for a differential effect, we conducted a 2 (patients v. controls) х 2 (object task v. spatial task) analysis of variance. The interaction term was statistically significant (F1,62 = 5.2, p = 0.026). Conclusions Our findings suggest a differential dysfunction of systems mediating object and spatial visual mental imagery in schizophrenia. PMID:15644999

  2. Classifying objects in LWIR imagery via CNNs

    Science.gov (United States)

    Rodger, Iain; Connor, Barry; Robertson, Neil M.

    2016-10-01

    The aim of the presented work is to demonstrate enhanced target recognition and improved false alarm rates for a mid to long range detection system, utilising a Long Wave Infrared (LWIR) sensor. By exploiting high quality thermal image data and recent techniques in machine learning, the system can provide automatic target recognition capabilities. A Convolutional Neural Network (CNN) is trained and the classifier achieves an overall accuracy of > 95% for 6 object classes related to land defence. While the highly accurate CNN struggles to recognise long range target classes, due to low signal quality, robust target discrimination is achieved for challenging candidates. The overall performance of the methodology presented is assessed using human ground truth information, generating classifier evaluation metrics for thermal image sequences.

  3. Mapping dry-season tree transpiration of an oak woodland at the catchment scale, using object-attributes derived from satellite imagery and sap flow measurements

    NARCIS (Netherlands)

    Reyes-Acosta, J.L.; Lubczynski, M.

    2013-01-01

    Tree transpiration is an important plant-physiological process that influences the water cycle, thereby influencing ecosystems and even the quantity of available water resources. However, direct tree-transpiration measurements, particularly at large spatial scales, are still rare, due to the

  4. Automatic Discovery and Geotagging of Objects from Street View Imagery

    Directory of Open Access Journals (Sweden)

    Vladimir A. Krylov

    2018-04-01

    Full Text Available Many applications, such as autonomous navigation, urban planning, and asset monitoring, rely on the availability of accurate information about objects and their geolocations. In this paper, we propose the automatic detection and computation of the coordinates of recurring stationary objects of interest using street view imagery. Our processing pipeline relies on two fully convolutional neural networks: the first segments objects in the images, while the second estimates their distance from the camera. To geolocate all the detected objects coherently we propose a novel custom Markov random field model to estimate the objects’ geolocation. The novelty of the resulting pipeline is the combined use of monocular depth estimation and triangulation to enable automatic mapping of complex scenes with the simultaneous presence of multiple, visually similar objects of interest. We validate experimentally the effectiveness of our approach on two object classes: traffic lights and telegraph poles. The experiments report high object recall rates and position precision of approximately 2 m, which is approaching the precision of single-frequency GPS receivers.

  5. Visual object imagery and autobiographical memory: Object Imagers are better at remembering their personal past.

    Science.gov (United States)

    Vannucci, Manila; Pelagatti, Claudia; Chiorri, Carlo; Mazzoni, Giuliana

    2016-01-01

    In the present study we examined whether higher levels of object imagery, a stable characteristic that reflects the ability and preference in generating pictorial mental images of objects, facilitate involuntary and voluntary retrieval of autobiographical memories (ABMs). Individuals with high (High-OI) and low (Low-OI) levels of object imagery were asked to perform an involuntary and a voluntary ABM task in the laboratory. Results showed that High-OI participants generated more involuntary and voluntary ABMs than Low-OI, with faster retrieval times. High-OI also reported more detailed memories compared to Low-OI and retrieved memories as visual images. Theoretical implications of these findings for research on voluntary and involuntary ABMs are discussed.

  6. The Study of Object-Oriented Motor Imagery Based on EEG Suppression.

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    Lili Li

    Full Text Available Motor imagery is a conventional method for brain computer interface and motor learning. To avoid the great individual difference of the motor imagery ability, object-oriented motor imagery was applied, and the effects were studied. Kinesthetic motor imagery and visual observation were administered to 15 healthy volunteers. The EEG during cue-based simple imagery (SI, object-oriented motor imagery (OI, non-object-oriented motor imagery (NI and visual observation (VO was recorded. Study results showed that OI and NI presented significant contralateral suppression in mu rhythm (p 0.05. Compared with NI, OI showed significant difference (p < 0.05 in mu rhythm and weak significant difference (p = 0.0612 in beta rhythm over the contralateral hemisphere. The ability of motor imagery can be reflected by the suppression degree of mu and beta frequencies which are the motor related rhythms. Thus, greater enhancement of activation in mirror neuron system is involved in response to object-oriented motor imagery. The object-oriented motor imagery is favorable for improvement of motor imagery ability.

  7. A rat in the sewer: How mental imagery interacts with object recognition.

    Science.gov (United States)

    Karimpur, Harun; Hamburger, Kai

    2018-01-01

    The role of mental imagery has been puzzling researchers for more than two millennia. Both positive and negative effects of mental imagery on information processing have been discussed. The aim of this work was to examine how mental imagery affects object recognition and associative learning. Based on different perceptual and cognitive accounts we tested our imagery-induced interaction hypothesis in a series of two experiments. According to that, mental imagery could lead to (1) a superior performance in object recognition and associative learning if these objects are imagery-congruent (semantically) and to (2) an inferior performance if these objects are imagery-incongruent. In the first experiment, we used a static environment and tested associative learning. In the second experiment, subjects encoded object information in a dynamic environment by means of a virtual sewer system. Our results demonstrate that subjects who received a role adoption task (by means of guided mental imagery) performed better when imagery-congruent objects were used and worse when imagery-incongruent objects were used. We finally discuss our findings also with respect to alternative accounts and plead for a multi-methodological approach for future research in order to solve this issue.

  8. Estimating forest characteristics using NAIP imagery and ArcObjects

    Science.gov (United States)

    John S Hogland; Nathaniel M. Anderson; Woodam Chung; Lucas Wells

    2014-01-01

    Detailed, accurate, efficient, and inexpensive methods of estimating basal area, trees, and aboveground biomass per acre across broad extents are needed to effectively manage forests. In this study we present such a methodology using readily available National Agriculture Imagery Program imagery, Forest Inventory Analysis samples, a two stage classification and...

  9. Detection and Classification of Objects in Synthetic Aperture Radar Imagery

    National Research Council Canada - National Science Library

    Cooke, Tristrom

    2006-01-01

    .... The reports concern the detection of faint trails, and the theory and evaluation of a number of existing and novel methods for the detection and classification of ground and maritime targets with SAR imagery...

  10. Application of Object Based Classification and High Resolution Satellite Imagery for Savanna Ecosystem Analysis

    Directory of Open Access Journals (Sweden)

    Jane Southworth

    2010-12-01

    Full Text Available Savanna ecosystems are an important component of dryland regions and yet are exceedingly difficult to study using satellite imagery. Savannas are composed are varying amounts of trees, shrubs and grasses and typically traditional classification schemes or vegetation indices cannot differentiate across class type. This research utilizes object based classification (OBC for a region in Namibia, using IKONOS imagery, to help differentiate tree canopies and therefore woodland savanna, from shrub or grasslands. The methodology involved the identification and isolation of tree canopies within the imagery and the creation of tree polygon layers had an overall accuracy of 84%. In addition, the results were scaled up to a corresponding Landsat image of the same region, and the OBC results compared to corresponding pixel values of NDVI. The results were not compelling, indicating once more the problems of these traditional image analysis techniques for savanna ecosystems. Overall, the use of the OBC holds great promise for this ecosystem and could be utilized more frequently in studies of vegetation structure.

  11. Mental Imagery Scale: a new measurement tool to assess structural features of mental representations

    International Nuclear Information System (INIS)

    D'Ercole, Martina; Giannini, Anna Maria; Castelli, Paolo; Sbrilli, Antonella

    2010-01-01

    Mental imagery is a quasi-perceptual experience which resembles perceptual experience, but occurring without (appropriate) external stimuli. It is a form of mental representation and is often considered centrally involved in visuo-spatial reasoning and inventive and creative thought. Although imagery ability is assumed to be functionally independent of verbal systems, it is still considered to interact with verbal representations, enabling objects to be named and names to evoke images. In literature, most measurement tools for evaluating imagery capacity are self-report instruments focusing on differences in individuals. In the present work, we applied a Mental Imagery Scale (MIS) to mental images derived from verbal descriptions in order to assess the structural features of such mental representations. This is a key theme for those disciplines which need to turn objects and representations into words and vice versa, such as art or architectural didactics. To this aim, an MIS questionnaire was administered to 262 participants. The questionnaire, originally consisting of a 33-item 5-step Likert scale, was reduced to 28 items covering six areas: (1) Image Formation Speed, (2) Permanence/Stability, (3) Dimensions, (4) Level of Detail/Grain, (5) Distance and (6) Depth of Field or Perspective. Factor analysis confirmed our six-factor hypothesis underlying the 28 items

  12. Developing Affective Mental Imagery Stimuli with Multidimensional Scaling

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    Matthew J. Facciani

    2015-06-01

    Full Text Available The goal of this paper is to provide an example of how multidimensional scaling (MDS can be used for stimuli development. The study described in this paper illustrates this process by developing affective mental imagery stimuli using the circumplex model of affect as a guide. The circumplex model of affect argues that all emotions can be described in terms of two underlying primary dimensions: valence and arousal (Russel, 1980. We used MDS to determine if affective mental imagery stimuli obtained from verbal prompts could be separated by arousal and valence to create four distinct categories (high –positive, low-positive, high-negative, and low-negative as seen in other stimuli. 60 students from the University of South Carolina participated in the first experiment to evaluate three sets of stimuli. After being analyzed using MDS, selected stimuli were then assessed again in a second experiment to validate their robust valence and arousal distinctions. The second experiment was conducted with 34 subjects to validate 40 of the best stimuli from experiment 1. It was found that mental imagery stimuli can produce a reliable affective response for the dimensions of valence and arousal and that MDS can be an effective tool for stimuli development.

  13. Fusion of Pixel-based and Object-based Features for Road Centerline Extraction from High-resolution Satellite Imagery

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    CAO Yungang

    2016-10-01

    Full Text Available A novel approach for road centerline extraction from high spatial resolution satellite imagery is proposed by fusing both pixel-based and object-based features. Firstly, texture and shape features are extracted at the pixel level, and spectral features are extracted at the object level based on multi-scale image segmentation maps. Then, extracted multiple features are utilized in the fusion framework of Dempster-Shafer evidence theory to roughly identify the road network regions. Finally, an automatic noise removing algorithm combined with the tensor voting strategy is presented to accurately extract the road centerline. Experimental results using high-resolution satellite imageries with different scenes and spatial resolutions showed that the proposed approach compared favorably with the traditional methods, particularly in the aspect of eliminating the salt noise and conglutination phenomenon.

  14. Two Herbig-Haro objects discovered by narrow-band CCD imagery

    International Nuclear Information System (INIS)

    Ogura, Katsuo

    1990-01-01

    Two new Herbig-Haro objects, HH 132 and HH 133, have been discovered by CCD imagery behind interference filters on and just off the forbidden S II lines in the red. They are located in Puppis R2 and in Vela R2. Possible locations of their exciting sources are discussed. 12 refs

  15. Use of artificial neural networks and geographic objects for classifying remote sensing imagery

    Directory of Open Access Journals (Sweden)

    Pedro Resende Silva

    2014-06-01

    Full Text Available The aim of this study was to develop a methodology for mapping land use and land cover in the northern region of Minas Gerais state, where, in addition to agricultural land, the landscape is dominated by native cerrado, deciduous forests, and extensive areas of vereda. Using forest inventory data, as well as RapidEye, Landsat TM and MODIS imagery, three specific objectives were defined: 1 to test use of image segmentation techniques for an object-based classification encompassing spectral, spatial and temporal information, 2 to test use of high spatial resolution RapidEye imagery combined with Landsat TM time series imagery for capturing the effects of seasonality, and 3 to classify data using Artificial Neural Networks. Using MODIS time series and forest inventory data, time signatures were extracted from the dominant vegetation formations, enabling selection of the best periods of the year to be represented in the classification process. Objects created with the segmentation of RapidEye images, along with the Landsat TM time series images, were classified by ten different Multilayer Perceptron network architectures. Results showed that the methodology in question meets both the purposes of this study and the characteristics of the local plant life. With excellent accuracy values for native classes, the study showed the importance of a well-structured database for classification and the importance of suitable image segmentation to meet specific purposes.

  16. Human V4 Activity Patterns Predict Behavioral Performance in Imagery of Object Color.

    Science.gov (United States)

    Bannert, Michael M; Bartels, Andreas

    2018-04-11

    Color is special among basic visual features in that it can form a defining part of objects that are engrained in our memory. Whereas most neuroimaging research on human color vision has focused on responses related to external stimulation, the present study investigated how sensory-driven color vision is linked to subjective color perception induced by object imagery. We recorded fMRI activity in male and female volunteers during viewing of abstract color stimuli that were red, green, or yellow in half of the runs. In the other half we asked them to produce mental images of colored, meaningful objects (such as tomato, grapes, banana) corresponding to the same three color categories. Although physically presented color could be decoded from all retinotopically mapped visual areas, only hV4 allowed predicting colors of imagined objects when classifiers were trained on responses to physical colors. Importantly, only neural signal in hV4 was predictive of behavioral performance in the color judgment task on a trial-by-trial basis. The commonality between neural representations of sensory-driven and imagined object color and the behavioral link to neural representations in hV4 identifies area hV4 as a perceptual hub linking externally triggered color vision with color in self-generated object imagery. SIGNIFICANCE STATEMENT Humans experience color not only when visually exploring the outside world, but also in the absence of visual input, for example when remembering, dreaming, and during imagery. It is not known where neural codes for sensory-driven and internally generated hue converge. In the current study we evoked matching subjective color percepts, one driven by physically presented color stimuli, the other by internally generated color imagery. This allowed us to identify area hV4 as the only site where neural codes of corresponding subjective color perception converged regardless of its origin. Color codes in hV4 also predicted behavioral performance in an

  17. Object-based vegetation classification with high resolution remote sensing imagery

    Science.gov (United States)

    Yu, Qian

    Vegetation species are valuable indicators to understand the earth system. Information from mapping of vegetation species and community distribution at large scales provides important insight for studying the phenological (growth) cycles of vegetation and plant physiology. Such information plays an important role in land process modeling including climate, ecosystem and hydrological models. The rapidly growing remote sensing technology has increased its potential in vegetation species mapping. However, extracting information at a species level is still a challenging research topic. I proposed an effective method for extracting vegetation species distribution from remotely sensed data and investigated some ways for accuracy improvement. The study consists of three phases. Firstly, a statistical analysis was conducted to explore the spatial variation and class separability of vegetation as a function of image scale. This analysis aimed to confirm that high resolution imagery contains the information on spatial vegetation variation and these species classes can be potentially separable. The second phase was a major effort in advancing classification by proposing a method for extracting vegetation species from high spatial resolution remote sensing data. The proposed classification employs an object-based approach that integrates GIS and remote sensing data and explores the usefulness of ancillary information. The whole process includes image segmentation, feature generation and selection, and nearest neighbor classification. The third phase introduces a spatial regression model for evaluating the mapping quality from the above vegetation classification results. The effects of six categories of sample characteristics on the classification uncertainty are examined: topography, sample membership, sample density, spatial composition characteristics, training reliability and sample object features. This evaluation analysis answered several interesting scientific questions

  18. An Efficient Parallel Multi-Scale Segmentation Method for Remote Sensing Imagery

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    Haiyan Gu

    2018-04-01

    Full Text Available Remote sensing (RS image segmentation is an essential step in geographic object-based image analysis (GEOBIA to ultimately derive “meaningful objects”. While many segmentation methods exist, most of them are not efficient for large data sets. Thus, the goal of this research is to develop an efficient parallel multi-scale segmentation method for RS imagery by combining graph theory and the fractal net evolution approach (FNEA. Specifically, a minimum spanning tree (MST algorithm in graph theory is proposed to be combined with a minimum heterogeneity rule (MHR algorithm that is used in FNEA. The MST algorithm is used for the initial segmentation while the MHR algorithm is used for object merging. An efficient implementation of the segmentation strategy is presented using data partition and the “reverse searching-forward processing” chain based on message passing interface (MPI parallel technology. Segmentation results of the proposed method using images from multiple sensors (airborne, SPECIM AISA EAGLE II, WorldView-2, RADARSAT-2 and different selected landscapes (residential/industrial, residential/agriculture covering four test sites indicated its efficiency in accuracy and speed. We conclude that the proposed method is applicable and efficient for the segmentation of a variety of RS imagery (airborne optical, satellite optical, SAR, high-spectral, while the accuracy is comparable with that of the FNEA method.

  19. Object-oriented spatial-temporal association rules mining on ocean remote sensing imagery

    International Nuclear Information System (INIS)

    Xue, C J; Dong, Q; Ma, W X

    2014-01-01

    Using the long term marine remote sensing imagery, we develop an object-oriented spatial-temporal association rules mining framework to explore the association rules mining among marine environmental elements. Within the framework, two key issues are addressed. They are how to effectively deal with the related lattices and how to reduce the related dimensions? To deal with the first key issues, this paper develops an object-oriented method for abstracting marine sensitive objects from raster pixels and for representing them with a quadruple. To deal with the second key issues, by embedding the mutual information theory, we construct the direct association pattern tree to reduce the related elements at the first step, and then the Apriori algorithm is used to discover the spatio-temporal associated rules. Finally, Pacific Ocean is taken as a research area and multi- marine remote sensing imagery in recent three decades is used as a case study. The results show that the object-oriented spatio-temporal association rules mining can acquire the associated relationships not only among marine environmental elements in same region, also among the different regions. In addition, the information from association rules mining is much more expressive and informative in space and time than traditional spatio-temporal analysis

  20. Hierarchical Object-Based Mapping of Riverscape Units and in-Stream Mesohabitats Using LiDAR and VHR Imagery

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    Luca Demarchi

    2016-01-01

    Full Text Available In this paper, we present a new, semi-automated methodology for mapping hydromorphological indicators of rivers at a regional scale using multisource remote sensing (RS data. This novel approach is based on the integration of spectral and topographic information within a multilevel, geographic, object-based image analysis (GEOBIA. Different segmentation levels were generated based on the two sources of Remote Sensing (RS data, namely very-high spatial resolution, near-infrared imagery (VHR and high-resolution LiDAR topography. At each level, different input object features were tested with Machine Learning classifiers for mapping riverscape units and in-stream mesohabitats. The GEOBIA approach proved to be a powerful tool for analyzing the river system at different levels of detail and for coupling spectral and topographic datasets, allowing for the delineation of the natural fluvial corridor with its primary riverscape units (e.g., water channel, unvegetated sediment bars, riparian densely-vegetated units, etc. and in-stream mesohabitats with a high level of accuracy, respectively of K = 0.91 and K = 0.83. This method is flexible and can be adapted to different sources of data, with the potential to be implemented at regional scales in the future. The analyzed dataset, composed of VHR imagery and LiDAR data, is nowadays increasingly available at larger scales, notably through European Member States. At the same time, this methodology provides a tool for monitoring and characterizing the hydromorphological status of river systems continuously along the entire channel network and coherently through time, opening novel and significant perspectives to river science and management, notably for planning and targeting actions.

  1. Geographic object-based delineation of neighborhoods of Accra, Ghana using QuickBird satellite imagery.

    Science.gov (United States)

    Stow, Douglas A; Lippitt, Christopher D; Weeks, John R

    2010-08-01

    The objective was to test GEographic Object-based Image Analysis (GEOBIA) techniques for delineating neighborhoods of Accra, Ghana using QuickBird multispectral imagery. Two approaches to aggregating census enumeration areas (EAs) based on image-derived measures of vegetation objects were tested: (1) merging adjacent EAs according to vegetation measures and (2) image segmentation. Both approaches exploit readily available functions within commercial GEOBIA software. Image-derived neighborhood maps were compared to a reference map derived by spatial clustering of slum index values (from census data), to provide a relative assessment of potential map utility. A size-constrained iterative segmentation approach to aggregation was more successful than standard image segmentation or feature merge techniques. The segmentation approaches account for size and shape characteristics, enabling more realistic neighborhood boundaries to be delineated. The percentage of vegetation patches within each EA yielded more realistic delineation of potential neighborhoods than mean vegetation patch size per EA.

  2. Blanding’s Turtle (Emydoidea blandingii Potential Habitat Mapping Using Aerial Orthophotographic Imagery and Object Based Classification

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    Douglas J. King

    2012-01-01

    Full Text Available Blanding’s turtle (Emydoidea blandingii is a threatened species under Canada’s Species at Risk Act. In southern Québec, field based inventories are ongoing to determine its abundance and potential habitat. The goal of this research was to develop means for mapping of potential habitat based on primary habitat attributes that can be detected with high-resolution remotely sensed imagery. Using existing spring leaf-off 20 cm resolution aerial orthophotos of a portion of Gatineau Park where some Blanding’s turtle observations had been made, habitat attributes were mapped at two scales: (1 whole wetlands; (2 within wetland habitat features of open water, vegetation (used for camouflage and thermoregulation, and logs (used for spring sun-basking. The processing steps involved initial pixel-based classification to eliminate most areas of non-wetland, followed by object-based segmentations and classifications using a customized rule sequence to refine the wetland map and to map the within wetland habitat features. Variables used as inputs to the classifications were derived from the orthophotos and included image brightness, texture, and segmented object shape and area. Independent validation using field data and visual interpretation showed classification accuracy for all habitat attributes to be generally over 90% with a minimum of 81.5% for the producer’s accuracy of logs. The maps for each attribute were combined to produce a habitat suitability map for Blanding’s turtle. Of the 115 existing turtle observations, 92.3% were closest to a wetland of the two highest suitability classes. High-resolution imagery combined with object-based classification and habitat suitability mapping methods such as those presented provide a much more spatially explicit representation of detailed habitat attributes than can be obtained through field work alone. They can complement field efforts to document and track turtle activities and can contribute to

  3. Man-Made Object Extraction from Remote Sensing Imagery by Graph-Based Manifold Ranking

    Science.gov (United States)

    He, Y.; Wang, X.; Hu, X. Y.; Liu, S. H.

    2018-04-01

    The automatic extraction of man-made objects from remote sensing imagery is useful in many applications. This paper proposes an algorithm for extracting man-made objects automatically by integrating a graph model with the manifold ranking algorithm. Initially, we estimate a priori value of the man-made objects with the use of symmetric and contrast features. The graph model is established to represent the spatial relationships among pre-segmented superpixels, which are used as the graph nodes. Multiple characteristics, namely colour, texture and main direction, are used to compute the weights of the adjacent nodes. Manifold ranking effectively explores the relationships among all the nodes in the feature space as well as initial query assignment; thus, it is applied to generate a ranking map, which indicates the scores of the man-made objects. The man-made objects are then segmented on the basis of the ranking map. Two typical segmentation algorithms are compared with the proposed algorithm. Experimental results show that the proposed algorithm can extract man-made objects with high recognition rate and low omission rate.

  4. Detecting peatland drains with Object Based Image Analysis and Geoeye-1 imagery.

    Science.gov (United States)

    Connolly, J; Holden, N M

    2017-12-01

    Peatlands play an important role in the global carbon cycle. They provide important ecosystem services including carbon sequestration and storage. Drainage disturbs peatland ecosystem services. Mapping drains is difficult and expensive and their spatial extent is, in many cases, unknown. An object based image analysis (OBIA) was performed on a very high resolution satellite image (Geoeye-1) to extract information about drain location and extent on a blanket peatland in Ireland. Two accuracy assessment methods: Error matrix and the completeness, correctness and quality (CCQ) were used to assess the extracted data across the peatland and at several sub sites. The cost of the OBIA method was compared with manual digitisation and field survey. The drain maps were also used to assess the costs relating to blocking drains vs. a business-as-usual scenario and estimating the impact of each on carbon fluxes at the study site. The OBIA method performed well at almost all sites. Almost 500 km of drains were detected within the peatland. In the error matrix method, overall accuracy (OA) of detecting the drains was 94% and the kappa statistic was 0.66. The OA for all sub-areas, except one, was 95-97%. The CCQ was 85%, 85% and 71% respectively. The OBIA method was the most cost effective way to map peatland drains and was at least 55% cheaper than either field survey or manual digitisation, respectively. The extracted drain maps were used constrain the study area CO 2 flux which was 19% smaller than the prescribed Peatland Code value for drained peatlands. The OBIA method used in this study showed that it is possible to accurately extract maps of fine scale peatland drains over large areas in a cost effective manner. The development of methods to map the spatial extent of drains is important as they play a critical role in peatland carbon dynamics. The objective of this study was to extract data on the spatial extent of drains on a blanket bog in the west of Ireland. The

  5. Detecting peatland drains with Object Based Image Analysis and Geoeye-1 imagery

    Directory of Open Access Journals (Sweden)

    J. Connolly

    2017-03-01

    Full Text Available Abstract Background Peatlands play an important role in the global carbon cycle. They provide important ecosystem services including carbon sequestration and storage. Drainage disturbs peatland ecosystem services. Mapping drains is difficult and expensive and their spatial extent is, in many cases, unknown. An object based image analysis (OBIA was performed on a very high resolution satellite image (Geoeye-1 to extract information about drain location and extent on a blanket peatland in Ireland. Two accuracy assessment methods: Error matrix and the completeness, correctness and quality (CCQ were used to assess the extracted data across the peatland and at several sub sites. The cost of the OBIA method was compared with manual digitisation and field survey. The drain maps were also used to assess the costs relating to blocking drains vs. a business-as-usual scenario and estimating the impact of each on carbon fluxes at the study site. Results The OBIA method performed well at almost all sites. Almost 500 km of drains were detected within the peatland. In the error matrix method, overall accuracy (OA of detecting the drains was 94% and the kappa statistic was 0.66. The OA for all sub-areas, except one, was 95–97%. The CCQ was 85%, 85% and 71% respectively. The OBIA method was the most cost effective way to map peatland drains and was at least 55% cheaper than either field survey or manual digitisation, respectively. The extracted drain maps were used constrain the study area CO2 flux which was 19% smaller than the prescribed Peatland Code value for drained peatlands. Conclusions The OBIA method used in this study showed that it is possible to accurately extract maps of fine scale peatland drains over large areas in a cost effective manner. The development of methods to map the spatial extent of drains is important as they play a critical role in peatland carbon dynamics. The objective of this study was to extract data on the spatial extent of

  6. Fusion of pixel and object-based features for weed mapping using unmanned aerial vehicle imagery

    Science.gov (United States)

    Gao, Junfeng; Liao, Wenzhi; Nuyttens, David; Lootens, Peter; Vangeyte, Jürgen; Pižurica, Aleksandra; He, Yong; Pieters, Jan G.

    2018-05-01

    The developments in the use of unmanned aerial vehicles (UAVs) and advanced imaging sensors provide new opportunities for ultra-high resolution (e.g., less than a 10 cm ground sampling distance (GSD)) crop field monitoring and mapping in precision agriculture applications. In this study, we developed a strategy for inter- and intra-row weed detection in early season maize fields from aerial visual imagery. More specifically, the Hough transform algorithm (HT) was applied to the orthomosaicked images for inter-row weed detection. A semi-automatic Object-Based Image Analysis (OBIA) procedure was developed with Random Forests (RF) combined with feature selection techniques to classify soil, weeds and maize. Furthermore, the two binary weed masks generated from HT and OBIA were fused for accurate binary weed image. The developed RF classifier was evaluated by 5-fold cross validation, and it obtained an overall accuracy of 0.945, and Kappa value of 0.912. Finally, the relationship of detected weeds and their ground truth densities was quantified by a fitted linear model with a coefficient of determination of 0.895 and a root mean square error of 0.026. Besides, the importance of input features was evaluated, and it was found that the ratio of vegetation length and width was the most significant feature for the classification model. Overall, our approach can yield a satisfactory weed map, and we expect that the obtained accurate and timely weed map from UAV imagery will be applicable to realize site-specific weed management (SSWM) in early season crop fields for reducing spraying non-selective herbicides and costs.

  7. Mapping urban impervious surface using object-based image analysis with WorldView-3 satellite imagery

    Science.gov (United States)

    Iabchoon, Sanwit; Wongsai, Sangdao; Chankon, Kanoksuk

    2017-10-01

    Land use and land cover (LULC) data are important to monitor and assess environmental change. LULC classification using satellite images is a method widely used on a global and local scale. Especially, urban areas that have various LULC types are important components of the urban landscape and ecosystem. This study aims to classify urban LULC using WorldView-3 (WV-3) very high-spatial resolution satellite imagery and the object-based image analysis method. A decision rules set was applied to classify the WV-3 images in Kathu subdistrict, Phuket province, Thailand. The main steps were as follows: (1) the image was ortho-rectified with ground control points and using the digital elevation model, (2) multiscale image segmentation was applied to divide the image pixel level into image object level, (3) development of the decision ruleset for LULC classification using spectral bands, spectral indices, spatial and contextual information, and (4) accuracy assessment was computed using testing data, which sampled by statistical random sampling. The results show that seven LULC classes (water, vegetation, open space, road, residential, building, and bare soil) were successfully classified with overall classification accuracy of 94.14% and a kappa coefficient of 92.91%.

  8. Imagery of a moving object: the role of occipital cortex and human MT/V5+.

    Science.gov (United States)

    Kaas, Amanda; Weigelt, Sarah; Roebroeck, Alard; Kohler, Axel; Muckli, Lars

    2010-01-01

    Visual imagery--similar to visual perception--activates feature-specific and category-specific visual areas. This is frequently observed in experiments where the instruction is to imagine stimuli that have been shown immediately before the imagery task. Hence, feature-specific activation could be related to the short-term memory retrieval of previously presented sensory information. Here, we investigated mental imagery of stimuli that subjects had not seen before, eliminating the effects of short-term memory. We recorded brain activation using fMRI while subjects performed a behaviourally controlled guided imagery task in predefined retinotopic coordinates to optimize sensitivity in early visual areas. Whole brain analyses revealed activation in a parieto-frontal network and lateral-occipital cortex. Region of interest (ROI) based analyses showed activation in left hMT/V5+. Granger causality mapping taking left hMT/V5+ as source revealed an imagery-specific directed influence from the left inferior parietal lobule (IPL). Interestingly, we observed a negative BOLD response in V1-3 during imagery, modulated by the retinotopic location of the imagined motion trace. Our results indicate that rule-based motion imagery can activate higher-order visual areas involved in motion perception, with a role for top-down directed influences originating in IPL. Lower-order visual areas (V1, V2 and V3) were down-regulated during this type of imagery, possibly reflecting inhibition to avoid visual input from interfering with the imagery construction. This suggests that the activation in early visual areas observed in previous studies might be related to short- or long-term memory retrieval of specific sensory experiences.

  9. Selecting Appropriate Spatial Scale for Mapping Plastic-Mulched Farmland with Satellite Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    Hasituya

    2017-03-01

    Full Text Available In recent years, the area of plastic-mulched farmland (PMF has undergone rapid growth and raised remarkable environmental problems. Therefore, mapping the PMF plays a crucial role in agricultural production, environmental protection and resource management. However, appropriate data selection criteria are currently lacking. Thus, this study was carried out in two main plastic-mulching practice regions, Jizhou and Guyuan, to look for an appropriate spatial scale for mapping PMF with remote sensing. The average local variance (ALV function was used to obtain the appropriate spatial scale for mapping PMF based on the GaoFen-1 (GF-1 satellite imagery. Afterwards, in order to validate the effectiveness of the selected method and to interpret the relationship between the appropriate spatial scale derived from the ALV and the spatial scale with the highest classification accuracy, we classified the imagery with varying spatial resolution by the Support Vector Machine (SVM algorithm using the spectral features, textural features and the combined spectral and textural features respectively. The results indicated that the appropriate spatial scales from the ALV lie between 8 m and 20 m for mapping the PMF both in Jizhou and Guyuan. However, there is a proportional relation: the spatial scale with the highest classification accuracy is at the 1/2 location of the appropriate spatial scale generated from the ALV in Jizhou and at the 2/3 location of the appropriate spatial scale generated from the ALV in Guyuan. Therefore, the ALV method for quantitatively selecting the appropriate spatial scale for mapping PMF with remote sensing imagery has theoretical and practical significance.

  10. Measuring Supportive Music and Imagery Interventions: The Development of the Music Therapy Self-Rating Scale.

    Science.gov (United States)

    Meadows, Anthony; Burns, Debra S; Perkins, Susan M

    2015-01-01

    Previous research has demonstrated modest benefits from music-based interventions, specifically music and imagery interventions, during cancer care. However, little attention has been paid to measuring the benefits of music-based interventions using measurement instruments specifically designed to account for the multidimensional nature of music-imagery experiences. The purpose of this study was to describe the development of, and psychometrically evaluate, the Music Therapy Self-Rating Scale (MTSRS) as a measure for cancer patients engaged in supportive music and imagery interventions. An exploratory factor analysis using baseline data from 76 patients who consented to participate in a music-based intervention study during chemotherapy. Factor analysis of 14 items revealed four domains: Awareness of Body, Emotionally Focused, Personal Resources, and Treatment Specific. Internal reliability was excellent (Cronbach alphas ranging from 0.75 to 0.88) and construct and divergent-discriminant validity supported. The MTSRS is a psychometrically sound, brief instrument that captures essential elements of patient experience during music and imagery interventions. © the American Music Therapy Association 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  11. Algorithmic Foundation of Spectral Rarefaction for Measuring Satellite Imagery Heterogeneity at Multiple Spatial Scales

    Science.gov (United States)

    Rocchini, Duccio

    2009-01-01

    Measuring heterogeneity in satellite imagery is an important task to deal with. Most measures of spectral diversity have been based on Shannon Information theory. However, this approach does not inherently address different scales, ranging from local (hereafter referred to alpha diversity) to global scales (gamma diversity). The aim of this paper is to propose a method for measuring spectral heterogeneity at multiple scales based on rarefaction curves. An algorithmic solution of rarefaction applied to image pixel values (Digital Numbers, DNs) is provided and discussed. PMID:22389600

  12. Joint Multi-scale Convolution Neural Network for Scene Classification of High Resolution Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    ZHENG Zhuo

    2018-05-01

    Full Text Available High resolution remote sensing imagery scene classification is important for automatic complex scene recognition, which is the key technology for military and disaster relief, etc. In this paper, we propose a novel joint multi-scale convolution neural network (JMCNN method using a limited amount of image data for high resolution remote sensing imagery scene classification. Different from traditional convolutional neural network, the proposed JMCNN is an end-to-end training model with joint enhanced high-level feature representation, which includes multi-channel feature extractor, joint multi-scale feature fusion and Softmax classifier. Multi-channel and scale convolutional extractors are used to extract scene middle features, firstly. Then, in order to achieve enhanced high-level feature representation in a limit dataset, joint multi-scale feature fusion is proposed to combine multi-channel and scale features using two feature fusions. Finally, enhanced high-level feature representation can be used for classification by Softmax. Experiments were conducted using two limit public UCM and SIRI datasets. Compared to state-of-the-art methods, the JMCNN achieved improved performance and great robustness with average accuracies of 89.3% and 88.3% on the two datasets.

  13. Object-based methods for individual tree identification and tree species classification from high-spatial resolution imagery

    Science.gov (United States)

    Wang, Le

    2003-10-01

    textures occurring due to branches and twigs. As a result from the inverse wavelet transform, the tree crown boundary is enhanced while the unwanted textures are suppressed. Based on the enhanced image, an improvement is achieved when applying the two-stage methods to a high resolution aerial photograph. To improve tree species classification, we develop a new method to choose the optimal scale parameter with the aid of Bhattacharya Distance (BD), a well-known index of class separability in traditional pixel-based classification. The optimal scale parameter is then fed in the process of a region-growing-based segmentation as a break-off value. Our object classification achieves a better accuracy in separating tree species when compared to the conventional Maximum Likelihood Classification (MLC). In summary, we develop two object-based methods for identifying individual trees and classifying tree species from high-spatial resolution imagery. Both methods achieve promising results and will promote integration of Remote Sensing and GIS in forest applications.

  14. Regional snow-avalanche detection using object-based image analysis of near-infrared aerial imagery

    Directory of Open Access Journals (Sweden)

    K. Korzeniowska

    2017-10-01

    Full Text Available Snow avalanches are destructive mass movements in mountain regions that continue to claim lives and cause infrastructural damage and traffic detours. Given that avalanches often occur in remote and poorly accessible steep terrain, their detection and mapping is extensive and time consuming. Nonetheless, systematic avalanche detection over large areas could help to generate more complete and up-to-date inventories (cadastres necessary for validating avalanche forecasting and hazard mapping. In this study, we focused on automatically detecting avalanches and classifying them into release zones, tracks, and run-out zones based on 0.25 m near-infrared (NIR ADS80-SH92 aerial imagery using an object-based image analysis (OBIA approach. Our algorithm takes into account the brightness, the normalised difference vegetation index (NDVI, the normalised difference water index (NDWI, and its standard deviation (SDNDWI to distinguish avalanches from other land-surface elements. Using normalised parameters allows applying this method across large areas. We trained the method by analysing the properties of snow avalanches at three 4 km−2 areas near Davos, Switzerland. We compared the results with manually mapped avalanche polygons and obtained a user's accuracy of > 0.9 and a Cohen's kappa of 0.79–0.85. Testing the method for a larger area of 226.3 km−2, we estimated producer's and user's accuracies of 0.61 and 0.78, respectively, with a Cohen's kappa of 0.67. Detected avalanches that overlapped with reference data by > 80 % occurred randomly throughout the testing area, showing that our method avoids overfitting. Our method has potential for large-scale avalanche mapping, although further investigations into other regions are desirable to verify the robustness of our selected thresholds and the transferability of the method.

  15. Multi-class geospatial object detection based on a position-sensitive balancing framework for high spatial resolution remote sensing imagery

    Science.gov (United States)

    Zhong, Yanfei; Han, Xiaobing; Zhang, Liangpei

    2018-04-01

    Multi-class geospatial object detection from high spatial resolution (HSR) remote sensing imagery is attracting increasing attention in a wide range of object-related civil and engineering applications. However, the distribution of objects in HSR remote sensing imagery is location-variable and complicated, and how to accurately detect the objects in HSR remote sensing imagery is a critical problem. Due to the powerful feature extraction and representation capability of deep learning, the deep learning based region proposal generation and object detection integrated framework has greatly promoted the performance of multi-class geospatial object detection for HSR remote sensing imagery. However, due to the translation caused by the convolution operation in the convolutional neural network (CNN), although the performance of the classification stage is seldom influenced, the localization accuracies of the predicted bounding boxes in the detection stage are easily influenced. The dilemma between translation-invariance in the classification stage and translation-variance in the object detection stage has not been addressed for HSR remote sensing imagery, and causes position accuracy problems for multi-class geospatial object detection with region proposal generation and object detection. In order to further improve the performance of the region proposal generation and object detection integrated framework for HSR remote sensing imagery object detection, a position-sensitive balancing (PSB) framework is proposed in this paper for multi-class geospatial object detection from HSR remote sensing imagery. The proposed PSB framework takes full advantage of the fully convolutional network (FCN), on the basis of a residual network, and adopts the PSB framework to solve the dilemma between translation-invariance in the classification stage and translation-variance in the object detection stage. In addition, a pre-training mechanism is utilized to accelerate the training procedure

  16. Catchment scale multi-objective flood management

    Science.gov (United States)

    Rose, Steve; Worrall, Peter; Rosolova, Zdenka; Hammond, Gene

    2010-05-01

    Rural land management is known to affect both the generation and propagation of flooding at the local scale, but there is still a general lack of good evidence that this impact is still significant at the larger catchment scale given the complexity of physical interactions and climatic variability taking place at this level. The National Trust, in partnership with the Environment Agency, are managing an innovative project on the Holnicote Estate in south west England to demonstrate the benefits of using good rural land management practices to reduce flood risk at the both the catchment and sub-catchment scales. The Holnicote Estate is owned by the National Trust and comprises about 5,000 hectares of land, from the uplands of Exmoor to the sea, incorporating most of the catchments of the river Horner and Aller Water. There are nearly 100 houses across three villages that are at risk from flooding which could potentially benefit from changes in land management practices in the surrounding catchment providing a more sustainable flood attenuation function. In addition to the contribution being made to flood risk management there are a range of other ecosystems services that will be enhanced through these targeted land management changes. Alterations in land management will create new opportunities for wildlife and habitats and help to improve the local surface water quality. Such improvements will not only create additional wildlife resources locally but also serve the landscape response to climate change effects by creating and enhancing wildlife networks within the region. Land management changes will also restore and sustain landscape heritage resources and provide opportunities for amenity, recreation and tourism. The project delivery team is working with the National Trust from source to sea across the entire Holnicote Estate, to identify and subsequently implement suitable land management techniques to manage local flood risk within the catchments. These

  17. Mapping daily evapotranspiration at field to continental scales using geostationary and polar orbiting satellite imagery

    Directory of Open Access Journals (Sweden)

    M. C. Anderson

    2011-01-01

    Full Text Available Thermal infrared (TIR remote sensing of land-surface temperature (LST provides valuable information about the sub-surface moisture status required for estimating evapotranspiration (ET and detecting the onset and severity of drought. While empirical indices measuring anomalies in LST and vegetation amount (e.g., as quantified by the Normalized Difference Vegetation Index; NDVI have demonstrated utility in monitoring ET and drought conditions over large areas, they may provide ambiguous results when other factors (e.g., air temperature, advection are affecting plant functioning. A more physically based interpretation of LST and NDVI and their relationship to sub-surface moisture conditions can be obtained with a surface energy balance model driven by TIR remote sensing. The Atmosphere-Land Exchange Inverse (ALEXI model is a multi-sensor TIR approach to ET mapping, coupling a two-source (soil + canopy land-surface model with an atmospheric boundary layer model in time-differencing mode to routinely and robustly map daily fluxes at continental scales and 5 to 10-km resolution using thermal band imagery and insolation estimates from geostationary satellites. A related algorithm (DisALEXI spatially disaggregates ALEXI fluxes down to finer spatial scales using moderate resolution TIR imagery from polar orbiting satellites. An overview of this modeling approach is presented, along with strategies for fusing information from multiple satellite platforms and wavebands to map daily ET down to resolutions on the order of 10 m. The ALEXI/DisALEXI model has potential for global applications by integrating data from multiple geostationary meteorological satellite systems, such as the US Geostationary Operational Environmental Satellites, the European Meteosat satellites, the Chinese Fen-yung 2B series, and the Japanese Geostationary Meteorological Satellites. Work is underway to further evaluate multi-scale ALEXI implementations over the US, Europe, Africa

  18. Extraction of Terraces on the Loess Plateau from High-Resolution DEMs and Imagery Utilizing Object-Based Image Analysis

    Directory of Open Access Journals (Sweden)

    Hanqing Zhao

    2017-05-01

    Full Text Available Abstract: Terraces are typical artificial landforms on the Loess Plateau, with ecological functions in water and soil conservation, agricultural production, and biodiversity. Recording the spatial distribution of terraces is the basis of monitoring their extent and understanding their ecological effects. The current terrace extraction method mainly relies on high-resolution imagery, but its accuracy is limited due to vegetation coverage distorting the features of terraces in imagery. High-resolution topographic data reflecting the morphology of true terrace surfaces are needed. Terraces extraction on the Loess Plateau is challenging because of the complex terrain and diverse vegetation after the implementation of “vegetation recovery”. This study presents an automatic method of extracting terraces based on 1 m resolution digital elevation models (DEMs and 0.3 m resolution Worldview-3 imagery as auxiliary information used for object-based image analysis (OBIA. A multi-resolution segmentation method was used where slope, positive and negative terrain index (PN, accumulative curvature slope (AC, and slope of slope (SOS were determined as input layers for image segmentation by correlation analysis and Sheffield entropy method. The main classification features based on DEMs were chosen from the terrain features derived from terrain factors and texture features by gray-level co-occurrence matrix (GLCM analysis; subsequently, these features were determined by the importance analysis on classification and regression tree (CART analysis. Extraction rules based on DEMs were generated from the classification features with a total classification accuracy of 89.96%. The red band and near-infrared band of images were used to exclude construction land, which is easily confused with small-size terraces. As a result, the total classification accuracy was increased to 94%. The proposed method ensures comprehensive consideration of terrain, texture, shape, and

  19. An Improved Algorithm Based on Minimum Spanning Tree for Multi-scale Segmentation of Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    LI Hui

    2015-07-01

    Full Text Available As the basis of object-oriented information extraction from remote sensing imagery,image segmentation using multiple image features,exploiting spatial context information, and by a multi-scale approach are currently the research focuses. Using an optimization approach of the graph theory, an improved multi-scale image segmentation method is proposed. In this method, the image is applied with a coherent enhancement anisotropic diffusion filter followed by a minimum spanning tree segmentation approach, and the resulting segments are merged with reference to a minimum heterogeneity criterion.The heterogeneity criterion is defined as a function of the spectral characteristics and shape parameters of segments. The purpose of the merging step is to realize the multi-scale image segmentation. Tested on two images, the proposed method was visually and quantitatively compared with the segmentation method employed in the eCognition software. The results show that the proposed method is effective and outperforms the latter on areas with subtle spectral differences.

  20. Efficient Selection of Multiple Objects on a Large Scale

    DEFF Research Database (Denmark)

    Stenholt, Rasmus

    2012-01-01

    The task of multiple object selection (MOS) in immersive virtual environments is important and still largely unexplored. The diffi- culty of efficient MOS increases with the number of objects to be selected. E.g. in small-scale MOS, only a few objects need to be simultaneously selected. This may...... consuming. Instead, we have implemented and tested two of the existing approaches to 3-D MOS, a brush and a lasso, as well as a new technique, a magic wand, which automati- cally selects objects based on local proximity to other objects. In a formal user evaluation, we have studied how the performance...

  1. Fine-scale mapping of vector habitats using very high resolution satellite imagery: a liver fluke case-study.

    Science.gov (United States)

    De Roeck, Els; Van Coillie, Frieke; De Wulf, Robert; Soenen, Karen; Charlier, Johannes; Vercruysse, Jozef; Hantson, Wouter; Ducheyne, Els; Hendrickx, Guy

    2014-12-01

    The visualization of vector occurrence in space and time is an important aspect of studying vector-borne diseases. Detailed maps of possible vector habitats provide valuable information for the prediction of infection risk zones but are currently lacking for most parts of the world. Nonetheless, monitoring vector habitats from the finest scales up to farm level is of key importance to refine currently existing broad-scale infection risk models. Using Fasciola hepatica, a parasite liver fluke, as a case in point, this study illustrates the potential of very high resolution (VHR) optical satellite imagery to efficiently and semi-automatically detect detailed vector habitats. A WorldView2 satellite image capable of transmitted by freshwater snails. The vector thrives in small water bodies (SWBs), such as ponds, ditches and other humid areas consisting of open water, aquatic vegetation and/or inundated grass. These water bodies can be as small as a few m2 and are most often not present on existing land cover maps because of their small size. We present a classification procedure based on object-based image analysis (OBIA) that proved valuable to detect SWBs at a fine scale in an operational and semi-automated way. The classification results were compared to field and other reference data such as existing broad-scale maps and expert knowledge. Overall, the SWB detection accuracy reached up to 87%. The resulting fine-scale SWB map can be used as input for spatial distribution modelling of the liver fluke snail vector to enable development of improved infection risk mapping and management advice adapted to specific, local farm situations.

  2. The potential of UAS imagery for soil mapping at the agricultural plot scale

    Science.gov (United States)

    Gilliot, Jean-Marc; Michelin, Joël; Becu, Maxime; Cissé, Moustapha; Hadjar, Dalila; Vaudour, Emmanuelle

    2017-04-01

    Soil mapping is expensive and time consuming. Airborne and satellite remote sensing data have already been used to predict some soil properties but now Unmanned Aerial Systems (UAS) allow to do many images acquisitions in various field conditions in favour of developing methods for better prediction models construction. This study propose an operational method for spatial prediction of soil properties (organic carbon, clay) at the scale of the agricultural plot by using UAS imagery. An agricultural plot of 28 ha, located in the western region of Paris France, was studied from March to May 2016. An area of 3.6 ha was delimited within the plot and a total of 16 flights were completed. The UAS platforms used were the eBee fixed wing provided by Sensefly® flying at an altitude from 60m to 130m and the iris+ 3DR® Quadcopter (from 30m to 100m). Two multispectral visible near-infrared cameras were used: the AirInov® MultiSPEC 4C® and the Micasense® RedEdge®. 42 ground control points (GCP) were sampled within the 3.6 ha plot. A centimetric Trimble Geo 7x DGPS was used to determine precise GCP positions. On each GCP the soil horizons were described and the top soil were sampled for standard physico-chemical analysis. Ground spectral measurements with a Spectral Evolution® SR-3500 spectroradiometer were made synchronously with the drone flights. 22 additional GCP were placed around the 3.6 ha area in order to realize a precise georeferencing. The multispectral mosaics were calculated using the Agisoft Photoscan® software and all mapping processings were done with the ESRI ArcGIS® 10.3 software. The soil properties were estimated by partial least squares regression (PLSR) between the laboratory analyses and the multispectral information of the UAS images, with the PLS package of the R software. The objective was to establish a model that would achieve an acceptable prediction quality using minimum number of points. For this, we tested 5 models with a decreasing

  3. A methodology for producing small scale rural land use maps in semi-arid developing countries using orbital imagery

    Science.gov (United States)

    Vangenderen, J. L. (Principal Investigator); Lock, B. F.

    1976-01-01

    The author has identified the following significant results. Results have shown that it is feasible to design a methodology that can provide suitable guidelines for operational production of small scale rural land use maps of semiarid developing regions from LANDSAT MSS imagery, using inexpensive and unsophisticated visual techniques. The suggested methodology provides immediate practical benefits to map makers attempting to produce land use maps in countries with limited budgets and equipment. Many preprocessing and interpretation techniques were considered, but rejected on the grounds that they were inappropriate mainly due to the high cost of imagery and/or equipment, or due to their inadequacy for use in operational projects in the developing countries. Suggested imagery and interpretation techniques, consisting of color composites and monocular magnification proved to be the simplest, fastest, and most versatile methods.

  4. An object-oriented classification method of high resolution imagery based on improved AdaTree

    International Nuclear Information System (INIS)

    Xiaohe, Zhang; Liang, Zhai; Jixian, Zhang; Huiyong, Sang

    2014-01-01

    With the popularity of the application using high spatial resolution remote sensing image, more and more studies paid attention to object-oriented classification on image segmentation as well as automatic classification after image segmentation. This paper proposed a fast method of object-oriented automatic classification. First, edge-based or FNEA-based segmentation was used to identify image objects and the values of most suitable attributes of image objects for classification were calculated. Then a certain number of samples from the image objects were selected as training data for improved AdaTree algorithm to get classification rules. Finally, the image objects could be classified easily using these rules. In the AdaTree, we mainly modified the final hypothesis to get classification rules. In the experiment with WorldView2 image, the result of the method based on AdaTree showed obvious accuracy and efficient improvement compared with the method based on SVM with the kappa coefficient achieving 0.9242

  5. Decreased attention to object size information in scale errors performers.

    Science.gov (United States)

    Grzyb, Beata J; Cangelosi, Angelo; Cattani, Allegra; Floccia, Caroline

    2017-05-01

    Young children sometimes make serious attempts to perform impossible actions on miniature objects as if they were full-size objects. The existing explanations of these curious action errors assume (but never explicitly tested) children's decreased attention to object size information. This study investigated the attention to object size information in scale errors performers. Two groups of children aged 18-25 months (N=52) and 48-60 months (N=23) were tested in two consecutive tasks: an action task that replicated the original scale errors elicitation situation, and a looking task that involved watching on a computer screen actions performed with adequate to inadequate size object. Our key finding - that children performing scale errors in the action task subsequently pay less attention to size changes than non-scale errors performers in the looking task - suggests that the origins of scale errors in childhood operate already at the perceptual level, and not at the action level. Copyright © 2017 Elsevier Inc. All rights reserved.

  6. Current Resource Imagery Projects

    Data.gov (United States)

    Farm Service Agency, Department of Agriculture — Map showing coverage of current Resource imagery projects. High resolution/large scale Resource imagery is typically acquired for the U.S. Forest Service and other...

  7. Aerial Photography and Imagery, Ortho-Corrected, This data set contains imagery from the National Agriculture Imagery Program (NAIP). NAIP acquires digital ortho imagery during the agricultural growing seasons in the continental U.S. NAIP imagery may contain as much as 10% cloud cover per tile. This fil, Published in 2005, 1:63360 (1in=1mile) scale, University of Georgia.

    Data.gov (United States)

    NSGIC Education | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2005. This data set contains imagery from the National Agriculture Imagery Program (NAIP). NAIP...

  8. Towards large-scale mapping of urban three-dimensional structure using Landsat imagery and global elevation datasets

    Science.gov (United States)

    Wang, P.; Huang, C.

    2017-12-01

    The three-dimensional (3D) structure of buildings and infrastructures is fundamental to understanding and modelling of the impacts and challenges of urbanization in terms of energy use, carbon emissions, and earthquake vulnerabilities. However, spatially detailed maps of urban 3D structure have been scarce, particularly in fast-changing developing countries. We present here a novel methodology to map the volume of buildings and infrastructures at 30 meter resolution using a synergy of Landsat imagery and openly available global digital surface models (DSMs), including the Shuttle Radar Topography Mission (SRTM), ASTER Global Digital Elevation Map (GDEM), ALOS World 3D - 30m (AW3D30), and the recently released global DSM from the TanDEM-X mission. Our method builds on the concept of object-based height profile to extract height metrics from the DSMs and use a machine learning algorithm to predict height and volume from the height metrics. We have tested this algorithm in the entire England and assessed our result using Lidar measurements in 25 England cities. Our initial assessments achieved a RMSE of 1.4 m (R2 = 0.72) for building height and a RMSE of 1208.7 m3 (R2 = 0.69) for building volume, demonstrating the potential of large-scale applications and fully automated mapping of urban structure.

  9. Spatiotemporally enhancing time-series DMSP/OLS nighttime light imagery for assessing large-scale urban dynamics

    Science.gov (United States)

    Xie, Yanhua; Weng, Qihao

    2017-06-01

    Accurate, up-to-date, and consistent information of urban extents is vital for numerous applications central to urban planning, ecosystem management, and environmental assessment and monitoring. However, current large-scale urban extent products are not uniform with respect to definition, spatial resolution, temporal frequency, and thematic representation. This study aimed to enhance, spatiotemporally, time-series DMSP/OLS nighttime light (NTL) data for detecting large-scale urban changes. The enhanced NTL time series from 1992 to 2013 were firstly generated by implementing global inter-calibration, vegetation-based spatial adjustment, and urban archetype-based temporal modification. The dataset was then used for updating and backdating urban changes for the contiguous U.S.A. (CONUS) and China by using the Object-based Urban Thresholding method (i.e., NTL-OUT method, Xie and Weng, 2016b). The results showed that the updated urban extents were reasonably accurate, with city-scale RMSE (root mean square error) of 27 km2 and Kappa of 0.65 for CONUS, and 55 km2 and 0.59 for China, respectively. The backdated urban extents yielded similar accuracy, with RMSE of 23 km2 and Kappa of 0.63 in CONUS, while 60 km2 and 0.60 in China. The accuracy assessment further revealed that the spatial enhancement greatly improved the accuracy of urban updating and backdating by significantly reducing RMSE and slightly increasing Kappa values. The temporal enhancement also reduced RMSE, and improved the spatial consistency between estimated and reference urban extents. Although the utilization of enhanced NTL data successfully detected urban size change, relatively low locational accuracy of the detected urban changes was observed. It is suggested that the proposed methodology would be more effective for updating and backdating global urban maps if further fusion of NTL data with higher spatial resolution imagery was implemented.

  10. Object-oriented Method of Hierarchical Urban Building Extraction from High-resolution Remote-Sensing Imagery

    Directory of Open Access Journals (Sweden)

    TAO Chao

    2016-02-01

    Full Text Available An automatic urban building extraction method for high-resolution remote-sensing imagery,which combines building segmentation based on neighbor total variations with object-oriented analysis,is presented in this paper. Aimed at different extraction complexity from various buildings in the segmented image,a hierarchical building extraction strategy with multi-feature fusion is adopted. Firstly,we extract some rectangle buildings which remain intact after segmentation through shape analysis. Secondly,in order to ensure each candidate building target to be independent,multidirectional morphological road-filtering algorithm is designed which can separate buildings from the neighboring roads with similar spectrum. Finally,we take the extracted buildings and the excluded non-buildings as samples to establish probability model respectively,and Bayesian discriminating classifier is used for making judgment of the other candidate building objects to get the ultimate extraction result. The experimental results have shown that the approach is able to detect buildings with different structure and spectral features in the same image. The results of performance evaluation also support the robustness and precision of the approach developed.

  11. Object-based Morphological Building Index for Building Extraction from High Resolution Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    LIN Xiangguo

    2017-06-01

    Full Text Available Building extraction from high resolution remote sensing images is a hot research topic in the field of photogrammetry and remote sensing. In this article, an object-based morphological building index (OBMBI is constructed based on both image segmentation and graph-based top-hat reconstruction, and OBMBI is used for building extraction from high resolution remote sensing images. First, bidirectional mapping relationship between pixels, objects and graph-nodes are constructed. Second, the OBMBI image is built based on both graph-based top-hat reconstruction and the above mapping relationship. Third, a binary thresholding is performed on the OBMBI image, and the binary image is converted into vector format to derive the building polygons. Finally, the post-processing is made to optimize the extracted building polygons. Two images, including an aerial image and a panchromatic satellite image, are used to test both the proposed method and classic PanTex method. The experimental results suggest that our proposed method has a higher accuracy in building extraction than the classic PanTex method. On average, the correctness, the completeness and the quality of our method are respectively 9.49%, 11.26% and 14.11% better than those of the PanTex.

  12. M-Estimators of Roughness and Scale for -Modelled SAR Imagery

    Directory of Open Access Journals (Sweden)

    Frery Alejandro C

    2002-01-01

    Full Text Available The GA0 distribution is assumed as the universal model for multilook amplitude SAR imagery data under the multiplicative model. This distribution has two unknown parameters related to the roughness and the scale of the signal, that can be used in image analysis and processing. It can be seen that maximum likelihood and moment estimators for its parameters can be influenced by small percentages of "outliers"; hence, it is of outmost importance to find robust estimators for these parameters. One of the best-known classes of robust techniques is that of M-estimators, which are an extension of the maximum likelihood estimation method. In this work we derive the M-estimators for the parameters of the distribution, and compare them with maximum likelihood estimators with a Monte-Carlo experience. It is checked that this robust technique is superior to the classical approach under the presence of corner reflectors, a common source of contamination in SAR images. Numerical issues are addressed, and a practical example is provided.

  13. USGS Imagery Topo Large-scale Base Map Service from The National Map

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The USGS Imagery Topo Large service from The National Map (TNM) is a dynamic topographic base map service that combines the best available data (Boundaries,...

  14. Object detection based on improved color and scale invariant features

    Science.gov (United States)

    Chen, Mengyang; Men, Aidong; Fan, Peng; Yang, Bo

    2009-10-01

    A novel object detection method which combines color and scale invariant features is presented in this paper. The detection system mainly adopts the widely used framework of SIFT (Scale Invariant Feature Transform), which consists of both a keypoint detector and descriptor. Although SIFT has some impressive advantages, it is not only computationally expensive, but also vulnerable to color images. To overcome these drawbacks, we employ the local color kernel histograms and Haar Wavelet Responses to enhance the descriptor's distinctiveness and computational efficiency. Extensive experimental evaluations show that the method has better robustness and lower computation costs.

  15. HIGH RESOLUTION LANDCOVER MODELLING WITH PLÉIADES IMAGERY AND DEM DATA IN SUPPORT OF FINE SCALE LANDSCAPE THERMAL MODELLING

    Directory of Open Access Journals (Sweden)

    M. Thompson

    2017-11-01

    Full Text Available In the evaluation of air-borne thermal infrared imaging sensors, the use of simulated spectral infrared scenery is a cost-effective way to provide input to the sensor. The benefit of simulated scenes includes control over parameters governing the spectral and related thermal behaviour of the terrain as well as atmospheric conditions. Such scenes need to have a high degree of radiometric and geometric accuracy, as well as high resolution to account for small objects having different spectral and associated thermal properties. In support of this, innovative use of tri-stereo, ultra-high resolution Pléiades satellite imagery is being used to generated high detail, small scale quantitative terrain surface data to compliment comparable optical data in order to produce detailed urban and rural landscape datasets representative of different landscape features, within which spectrally defined characteristics can be subsequently matched to thermal signatures. Pléiades tri-stereo mode, acquired from the same orbit during the same pass, is particularly favourable for reaching the required metric accuracy because images are radiometrically and geometrically very homogeneous, which allows a very good radiometric matching for relief computation. The tri-stereo approach reduces noise and allows significantly enhanced relief description in landscapes where simple stereo imaging cannot see features, such as in dense urban areas or valley bottoms in steep, mountainous areas. This paper describes the datasets that have been generated for DENEL over the Hartebeespoort Dam region, west of Pretoria, South Africa. The final terrain datasets are generated by integrated modelling of both height and spectral surface characteristics within an object-based modelling environment. This approach provides an operational framework for rapid and highly accurate mapping of building and vegetation structure of wide areas, as is required in support of the evaluation of thermal

  16. Scale-adaptive Local Patches for Robust Visual Object Tracking

    Directory of Open Access Journals (Sweden)

    Kang Sun

    2014-04-01

    Full Text Available This paper discusses the problem of robustly tracking objects which undergo rapid and dramatic scale changes. To remove the weakness of global appearance models, we present a novel scheme that combines object’s global and local appearance features. The local feature is a set of local patches that geometrically constrain the changes in the target’s appearance. In order to adapt to the object’s geometric deformation, the local patches could be removed and added online. The addition of these patches is constrained by the global features such as color, texture and motion. The global visual features are updated via the stable local patches during tracking. To deal with scale changes, we adapt the scale of patches in addition to adapting the object bound box. We evaluate our method by comparing it to several state-of-the-art trackers on publicly available datasets. The experimental results on challenging sequences confirm that, by using this scale-adaptive local patches and global properties, our tracker outperforms the related trackers in many cases by having smaller failure rate as well as better accuracy.

  17. A method of evolving novel feature extraction algorithms for detecting buried objects in FLIR imagery using genetic programming

    Science.gov (United States)

    Paino, A.; Keller, J.; Popescu, M.; Stone, K.

    2014-06-01

    In this paper we present an approach that uses Genetic Programming (GP) to evolve novel feature extraction algorithms for greyscale images. Our motivation is to create an automated method of building new feature extraction algorithms for images that are competitive with commonly used human-engineered features, such as Local Binary Pattern (LBP) and Histogram of Oriented Gradients (HOG). The evolved feature extraction algorithms are functions defined over the image space, and each produces a real-valued feature vector of variable length. Each evolved feature extractor breaks up the given image into a set of cells centered on every pixel, performs evolved operations on each cell, and then combines the results of those operations for every cell using an evolved operator. Using this method, the algorithm is flexible enough to reproduce both LBP and HOG features. The dataset we use to train and test our approach consists of a large number of pre-segmented image "chips" taken from a Forward Looking Infrared Imagery (FLIR) camera mounted on the hood of a moving vehicle. The goal is to classify each image chip as either containing or not containing a buried object. To this end, we define the fitness of a candidate solution as the cross-fold validation accuracy of the features generated by said candidate solution when used in conjunction with a Support Vector Machine (SVM) classifier. In order to validate our approach, we compare the classification accuracy of an SVM trained using our evolved features with the accuracy of an SVM trained using mainstream feature extraction algorithms, including LBP and HOG.

  18. IKONOS imagery for the Large Scale Biosphere–Atmosphere Experiment in Amazonia (LBA).

    Science.gov (United States)

    George Hurtt; Xiangming Xiao; Michael Keller; Michael Palace; Gregory P. Asner; Rob Braswell; Brond& #305; Eduardo S. zio; Manoel Cardoso; Claudio J.R. Carvalho; Matthew G. Fearon; Liane Guild; Steve Hagen; Scott Hetrick; Berrien Moore III; Carlos Nobre; Jane M. Read; S& aacute; Tatiana NO-VALUE; Annette Schloss; George Vourlitis; Albertus J. Wickel

    2003-01-01

    The LBA-ECO program is one of several international research components under the Brazilian-led Large Scale Biosphere–Atmosphere Experiment in Amazonia (LBA). The field-oriented research activities of this study are organized along transects and include a set of primary field sites, where the major objective is to study land-use change and ecosystem dynamics, and a...

  19. Robust object tracking combining color and scale invariant features

    Science.gov (United States)

    Zhang, Shengping; Yao, Hongxun; Gao, Peipei

    2010-07-01

    Object tracking plays a very important role in many computer vision applications. However its performance will significantly deteriorate due to some challenges in complex scene, such as pose and illumination changes, clustering background and so on. In this paper, we propose a robust object tracking algorithm which exploits both global color and local scale invariant (SIFT) features in a particle filter framework. Due to the expensive computation cost of SIFT features, the proposed tracker adopts a speed-up variation of SIFT, SURF, to extract local features. Specially, the proposed method first finds matching points between the target model and target candidate, than the weight of the corresponding particle based on scale invariant features is computed as the the proportion of matching points of that particle to matching points of all particles, finally the weight of the particle is obtained by combining weights of color and SURF features with a probabilistic way. The experimental results on a variety of challenging videos verify that the proposed method is robust to pose and illumination changes and is significantly superior to the standard particle filter tracker and the mean shift tracker.

  20. Normalization of satellite imagery

    Science.gov (United States)

    Kim, Hongsuk H.; Elman, Gregory C.

    1990-01-01

    Sets of Thematic Mapper (TM) imagery taken over the Washington, DC metropolitan area during the months of November, March and May were converted into a form of ground reflectance imagery. This conversion was accomplished by adjusting the incident sunlight and view angles and by applying a pixel-by-pixel correction for atmospheric effects. Seasonal color changes of the area can be better observed when such normalization is applied to space imagery taken in time series. In normalized imagery, the grey scale depicts variations in surface reflectance and tonal signature of multi-band color imagery can be directly interpreted for quantitative information of the target.

  1. Parametric Approach in Designing Large-Scale Urban Architectural Objects

    Directory of Open Access Journals (Sweden)

    Arne Riekstiņš

    2011-04-01

    Full Text Available When all the disciplines of various science fields converge and develop, new approaches to contemporary architecture arise. The author looks towards approaching digital architecture from parametric viewpoint, revealing its generative capacity, originating from the fields of aeronautical, naval, automobile and product-design industries. The author also goes explicitly through his design cycle workflow for testing the latest methodologies in architectural design. The design process steps involved: extrapolating valuable statistical data about the site into three-dimensional diagrams, defining certain materiality of what is being produced, ways of presenting structural skin and structure simultaneously, contacting the object with the ground, interior program definition of the building with floors and possible spaces, logic of fabrication, CNC milling of the proto-type. The author’s developed tool that is reviewed in this article features enormous performative capacity and is applicable to various architectural design scales.Article in English

  2. Aerial Photography and Imagery, Ortho-Corrected, Color orthophotos of York County, SC and the municipalities flown at 400 scale, 1 foot resolution, Published in 2005, 1:4800 (1in=400ft) scale, York County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2005. Color orthophotos of York County, SC and the municipalities flown at 400 scale, 1 foot...

  3. Raft cultivation area extraction from high resolution remote sensing imagery by fusing multi-scale region-line primitive association features

    Science.gov (United States)

    Wang, Min; Cui, Qi; Wang, Jie; Ming, Dongping; Lv, Guonian

    2017-01-01

    In this paper, we first propose several novel concepts for object-based image analysis, which include line-based shape regularity, line density, and scale-based best feature value (SBV), based on the region-line primitive association framework (RLPAF). We then propose a raft cultivation area (RCA) extraction method for high spatial resolution (HSR) remote sensing imagery based on multi-scale feature fusion and spatial rule induction. The proposed method includes the following steps: (1) Multi-scale region primitives (segments) are obtained by image segmentation method HBC-SEG, and line primitives (straight lines) are obtained by phase-based line detection method. (2) Association relationships between regions and lines are built based on RLPAF, and then multi-scale RLPAF features are extracted and SBVs are selected. (3) Several spatial rules are designed to extract RCAs within sea waters after land and water separation. Experiments show that the proposed method can successfully extract different-shaped RCAs from HR images with good performance.

  4. Association between Social Anxiety and Visual Mental Imagery of Neutral Scenes: The Moderating Role of Effortful Control.

    Science.gov (United States)

    Moriya, Jun

    2017-01-01

    According to cognitive theories, verbal processing attenuates emotional processing, whereas visual imagery enhances emotional processing and contributes to the maintenance of social anxiety. Individuals with social anxiety report negative mental images in social situations. However, the general ability of visual mental imagery of neutral scenes in individuals with social anxiety is still unclear. The present study investigated the general ability of non-emotional mental imagery (vividness, preferences for imagery vs. verbal processing, and object or spatial imagery) and the moderating role of effortful control in attenuating social anxiety. The participants ( N = 231) completed five questionnaires. The results showed that social anxiety was not necessarily associated with all aspects of mental imagery. As suggested by theories, social anxiety was not associated with a preference for verbal processing. However, social anxiety was positively correlated with the visual imagery scale, especially the object imagery scale, which concerns the ability to construct pictorial images of individual objects. Further, it was negatively correlated with the spatial imagery scale, which concerns the ability to process information about spatial relations between objects. Although object imagery and spatial imagery positively and negatively predicted the degree of social anxiety, respectively, these effects were attenuated when socially anxious individuals had high effortful control. Specifically, in individuals with high effortful control, both object and spatial imagery were not associated with social anxiety. Socially anxious individuals might prefer to construct pictorial images of individual objects in natural scenes through object imagery. However, even in individuals who exhibit these features of mental imagery, effortful control could inhibit the increase in social anxiety.

  5. Association between Social Anxiety and Visual Mental Imagery of Neutral Scenes: The Moderating Role of Effortful Control

    Directory of Open Access Journals (Sweden)

    Jun Moriya

    2018-01-01

    Full Text Available According to cognitive theories, verbal processing attenuates emotional processing, whereas visual imagery enhances emotional processing and contributes to the maintenance of social anxiety. Individuals with social anxiety report negative mental images in social situations. However, the general ability of visual mental imagery of neutral scenes in individuals with social anxiety is still unclear. The present study investigated the general ability of non-emotional mental imagery (vividness, preferences for imagery vs. verbal processing, and object or spatial imagery and the moderating role of effortful control in attenuating social anxiety. The participants (N = 231 completed five questionnaires. The results showed that social anxiety was not necessarily associated with all aspects of mental imagery. As suggested by theories, social anxiety was not associated with a preference for verbal processing. However, social anxiety was positively correlated with the visual imagery scale, especially the object imagery scale, which concerns the ability to construct pictorial images of individual objects. Further, it was negatively correlated with the spatial imagery scale, which concerns the ability to process information about spatial relations between objects. Although object imagery and spatial imagery positively and negatively predicted the degree of social anxiety, respectively, these effects were attenuated when socially anxious individuals had high effortful control. Specifically, in individuals with high effortful control, both object and spatial imagery were not associated with social anxiety. Socially anxious individuals might prefer to construct pictorial images of individual objects in natural scenes through object imagery. However, even in individuals who exhibit these features of mental imagery, effortful control could inhibit the increase in social anxiety.

  6. Thermal infrared imagery as a tool for analysing the variability of surface saturated areas at various temporal and spatial scales

    Science.gov (United States)

    Glaser, Barbara; Antonelli, Marta; Pfister, Laurent; Klaus, Julian

    2017-04-01

    Surface saturated areas are important for the on- and offset of hydrological connectivity within the hillslope-riparian-stream continuum. This is reflected in concepts such as variable contributing areas or critical source areas. However, we still lack a standardized method for areal mapping of surface saturation and for observing its spatiotemporal variability. Proof-of-concept studies in recent years have shown the potential of thermal infrared (TIR) imagery to record surface saturation dynamics at various temporal and spatial scales. Thermal infrared imagery is thus a promising alternative to conventional approaches, such as the squishy boot method or the mapping of vegetation. In this study we use TIR images to investigate the variability of surface saturated areas at different temporal and spatial scales in the forested Weierbach catchment (0.45 km2) in western Luxembourg. We took TIR images of the riparian zone with a hand-held FLIR infrared camera at fortnightly intervals over 18 months at nine different locations distributed over the catchment. Not all of the acquired images were suitable for a derivation of the surface saturated areas, as various factors influence the usability of the TIR images (e.g. temperature contrasts, shadows, fog). Nonetheless, we obtained a large number of usable images that provided a good insight into the dynamic behaviour of surface saturated areas at different scales. The images revealed how diverse the evolution of surface saturated areas can be throughout the hydrologic year. For some locations with similar morphology or topography we identified diverging saturation dynamics, while other locations with different morphology / topography showed more similar behaviour. Moreover, we were able to assess the variability of the dynamics of expansion / contraction of saturated areas within the single locations, which can help to better understand the mechanisms behind surface saturation development.

  7. Optimal segmentation scale parameter selection for object-oriented ...

    African Journals Online (AJOL)

    ikkguy001

    2013-08-05

    Aug 5, 2013 ... hierarchy levels that facilitate their accurate extraction. .... digitized in ArcGIS from the available aerial photography) and image objects ..... Driven Shareholding for Knowledge-based landslide Detection by Object-based Image ...

  8. Decreased attention to object size information in scale errors performers

    NARCIS (Netherlands)

    Grzyb, B.J.; Cangelosi, A.; Cattani, A.; Floccia, C.

    2017-01-01

    Young children sometimes make serious attempts to perform impossible actions on miniature objects as if they were full-size objects. The existing explanations of these curious action errors assume (but never explicitly tested) children’s decreased attention to object size information. This study

  9. A Hierarchical Object-oriented Urban Land Cover Classification Using WorldView-2 Imagery and Airborne LiDAR data

    Science.gov (United States)

    Wu, M. F.; Sun, Z. C.; Yang, B.; Yu, S. S.

    2016-11-01

    In order to reduce the “salt and pepper” in pixel-based urban land cover classification and expand the application of fusion of multi-source data in the field of urban remote sensing, WorldView-2 imagery and airborne Light Detection and Ranging (LiDAR) data were used to improve the classification of urban land cover. An approach of object- oriented hierarchical classification was proposed in our study. The processing of proposed method consisted of two hierarchies. (1) In the first hierarchy, LiDAR Normalized Digital Surface Model (nDSM) image was segmented to objects. The NDVI, Costal Blue and nDSM thresholds were set for extracting building objects. (2) In the second hierarchy, after removing building objects, WorldView-2 fused imagery was obtained by Haze-ratio-based (HR) fusion, and was segmented. A SVM classifier was applied to generate road/parking lot, vegetation and bare soil objects. (3) Trees and grasslands were split based on an nDSM threshold (2.4 meter). The results showed that compared with pixel-based and non-hierarchical object-oriented approach, proposed method provided a better performance of urban land cover classification, the overall accuracy (OA) and overall kappa (OK) improved up to 92.75% and 0.90. Furthermore, proposed method reduced “salt and pepper” in pixel-based classification, improved the extraction accuracy of buildings based on LiDAR nDSM image segmentation, and reduced the confusion between trees and grasslands through setting nDSM threshold.

  10. Comparison of four machine learning methods for object-oriented change detection in high-resolution satellite imagery

    Science.gov (United States)

    Bai, Ting; Sun, Kaimin; Deng, Shiquan; Chen, Yan

    2018-03-01

    High resolution image change detection is one of the key technologies of remote sensing application, which is of great significance for resource survey, environmental monitoring, fine agriculture, military mapping and battlefield environment detection. In this paper, for high-resolution satellite imagery, Random Forest (RF), Support Vector Machine (SVM), Deep belief network (DBN), and Adaboost models were established to verify the possibility of different machine learning applications in change detection. In order to compare detection accuracy of four machine learning Method, we applied these four machine learning methods for two high-resolution images. The results shows that SVM has higher overall accuracy at small samples compared to RF, Adaboost, and DBN for binary and from-to change detection. With the increase in the number of samples, RF has higher overall accuracy compared to Adaboost, SVM and DBN.

  11. Monitoring Oilfield Operations and GHG Emissions Sources Using Object-based Image Analysis of High Resolution Spatial Imagery

    Science.gov (United States)

    Englander, J. G.; Brodrick, P. G.; Brandt, A. R.

    2015-12-01

    Fugitive emissions from oil and gas extraction have become a greater concern with the recent increases in development of shale hydrocarbon resources. There are significant gaps in the tools and research used to estimate fugitive emissions from oil and gas extraction. Two approaches exist for quantifying these emissions: atmospheric (or 'top down') studies, which measure methane fluxes remotely, or inventory-based ('bottom up') studies, which aggregate leakage rates on an equipment-specific basis. Bottom-up studies require counting or estimating how many devices might be leaking (called an 'activity count'), as well as how much each device might leak on average (an 'emissions factor'). In a real-world inventory, there is uncertainty in both activity counts and emissions factors. Even at the well level there are significant disagreements in data reporting. For example, some prior studies noted a ~5x difference in the number of reported well completions in the United States between EPA and private data sources. The purpose of this work is to address activity count uncertainty by using machine learning algorithms to classify oilfield surface facilities using high-resolution spatial imagery. This method can help estimate venting and fugitive emissions sources from regions where reporting of oilfield equipment is incomplete or non-existent. This work will utilize high resolution satellite imagery to count well pads in the Bakken oil field of North Dakota. This initial study examines an area of ~2,000 km2 with ~1000 well pads. We compare different machine learning classification techniques, and explore the impact of training set size, input variables, and image segmentation settings to develop efficient and robust techniques identifying well pads. We discuss the tradeoffs inherent to different classification algorithms, and determine the optimal algorithms for oilfield feature detection. In the future, the results of this work will be leveraged to be provide activity

  12. Medium - Scale Projects Selection Using Multi-Objective Decision ...

    African Journals Online (AJOL)

    Sixty (60) questionnaires were administered to experienced technically oriented personnel in the study area for evaluating objective weights attached to various projects. Forty-five responded and their values of objective weights attached to project cost, environmental effects, reliability, implementability and sustainable ...

  13. A Large-Scale 3D Object Recognition dataset

    DEFF Research Database (Denmark)

    Sølund, Thomas; Glent Buch, Anders; Krüger, Norbert

    2016-01-01

    geometric groups; concave, convex, cylindrical and flat 3D object models. The object models have varying amount of local geometric features to challenge existing local shape feature descriptors in terms of descriptiveness and robustness. The dataset is validated in a benchmark which evaluates the matching...... performance of 7 different state-of-the-art local shape descriptors. Further, we validate the dataset in a 3D object recognition pipeline. Our benchmark shows as expected that local shape feature descriptors without any global point relation across the surface have a poor matching performance with flat...

  14. Image Segmentation Parameter Optimization Considering Within- and Between-Segment Heterogeneity at Multiple Scale Levels: Test Case for Mapping Residential Areas Using Landsat Imagery

    Directory of Open Access Journals (Sweden)

    Brian A. Johnson

    2015-10-01

    Full Text Available Multi-scale/multi-level geographic object-based image analysis (MS-GEOBIA methods are becoming widely-used in remote sensing because single-scale/single-level (SS-GEOBIA methods are often unable to obtain an accurate segmentation and classification of all land use/land cover (LULC types in an image. However, there have been few comparisons between SS-GEOBIA and MS-GEOBIA approaches for the purpose of mapping a specific LULC type, so it is not well understood which is more appropriate for this task. In addition, there are few methods for automating the selection of segmentation parameters for MS-GEOBIA, while manual selection (i.e., trial-and-error approach of parameters can be quite challenging and time-consuming. In this study, we examined SS-GEOBIA and MS-GEOBIA approaches for extracting residential areas in Landsat 8 imagery, and compared naïve and parameter-optimized segmentation approaches to assess whether unsupervised segmentation parameter optimization (USPO could improve the extraction of residential areas. Our main findings were: (i the MS-GEOBIA approaches achieved higher classification accuracies than the SS-GEOBIA approach, and (ii USPO resulted in more accurate MS-GEOBIA classification results while reducing the number of segmentation levels and classification variables considerably.

  15. Algorithm and Application of Gcp-Independent Block Adjustment for Super Large-Scale Domestic High Resolution Optical Satellite Imagery

    Science.gov (United States)

    Sun, Y. S.; Zhang, L.; Xu, B.; Zhang, Y.

    2018-04-01

    The accurate positioning of optical satellite image without control is the precondition for remote sensing application and small/medium scale mapping in large abroad areas or with large-scale images. In this paper, aiming at the geometric features of optical satellite image, based on a widely used optimization method of constraint problem which is called Alternating Direction Method of Multipliers (ADMM) and RFM least-squares block adjustment, we propose a GCP independent block adjustment method for the large-scale domestic high resolution optical satellite image - GISIBA (GCP-Independent Satellite Imagery Block Adjustment), which is easy to parallelize and highly efficient. In this method, the virtual "average" control points are built to solve the rank defect problem and qualitative and quantitative analysis in block adjustment without control. The test results prove that the horizontal and vertical accuracy of multi-covered and multi-temporal satellite images are better than 10 m and 6 m. Meanwhile the mosaic problem of the adjacent areas in large area DOM production can be solved if the public geographic information data is introduced as horizontal and vertical constraints in the block adjustment process. Finally, through the experiments by using GF-1 and ZY-3 satellite images over several typical test areas, the reliability, accuracy and performance of our developed procedure will be presented and studied in this paper.

  16. Do clouds save the great barrier reef? satellite imagery elucidates the cloud-SST relationship at the local scale.

    Directory of Open Access Journals (Sweden)

    Susannah M Leahy

    Full Text Available Evidence of global climate change and rising sea surface temperatures (SSTs is now well documented in the scientific literature. With corals already living close to their thermal maxima, increases in SSTs are of great concern for the survival of coral reefs. Cloud feedback processes may have the potential to constrain SSTs, serving to enforce an "ocean thermostat" and promoting the survival of coral reefs. In this study, it was hypothesized that cloud cover can affect summer SSTs in the tropics. Detailed direct and lagged relationships between cloud cover and SST across the central Great Barrier Reef (GBR shelf were investigated using data from satellite imagery and in situ temperature and light loggers during two relatively hot summers (2005 and 2006 and two relatively cool summers (2007 and 2008. Across all study summers and shelf positions, SSTs exhibited distinct drops during periods of high cloud cover, and conversely, SST increases during periods of low cloud cover, with a three-day temporal lag between a change in cloud cover and a subsequent change in SST. Cloud cover alone was responsible for up to 32.1% of the variation in SSTs three days later. The relationship was strongest in both El Niño (2005 and La Niña (2008 study summers and at the inner-shelf position in those summers. SST effects on subsequent cloud cover were weaker and more variable among study summers, with rising SSTs explaining up to 21.6% of the increase in cloud cover three days later. This work quantifies the often observed cloud cooling effect on coral reefs. It highlights the importance of incorporating local-scale processes into bleaching forecasting models, and encourages the use of remote sensing imagery to value-add to coral bleaching field studies and to more accurately predict risks to coral reefs.

  17. Evaluating rapid ground sampling and scaling estimated plant cover using UAV imagery up to Landsat for mapping arctic vegetation

    Science.gov (United States)

    Nelson, P.; Paradis, D. P.

    2017-12-01

    The small stature and spectral diversity of arctic plant taxa presents challenges in mapping arctic vegetation. Mapping vegetation at the appropriate scale is needed to visualize effects of disturbance, directional vegetation change or mapping of specific plant groups for other applications (eg. habitat mapping). Fine spatial grain of remotely sensed data (ca. 10 cm pixels) is often necessary to resolve patches of many arctic plant groups, such as bryophytes and lichens. These groups are also spectrally different from mineral, litter and vascular plants. We sought to explore method to generate high-resolution spatial and spectral data to explore better mapping methods for arctic vegetation. We sampled ground vegetation at seven sites north or west of tree-line in Alaska, four north of Fairbanks and three northwest of Bethel, respectively. At each site, we estimated cover of plant functional types in 1m2 quadrats spaced approximately every 10 m along a 100 m long transect. Each quadrat was also scanned using a field spectroradiometer (PSR+ Spectral Evolution, 400-2500 nm range) and photographed from multiple perspectives. We then flew our small UAV with a RGB camera over the transect and at least 50 m on either side collecting on imagery of the plot, which were used to generate a image mosaic and digital surface model of the plot. We compare plant functional group cover ocular estimated in situ to post-hoc estimation, either automated or using a human observer, using the quadrat photos. We also compare interpolated lichen cover from UAV scenes to estimated lichen cover using a statistical models using Landsat data, with focus on lichens. Light and yellow lichens are discernable in the UAV imagery but certain lichens, especially dark colored lichens or those with spectral signatures similar to graminoid litter, present challenges. Future efforts will focus on integrating UAV-upscaled ground cover estimates to hyperspectral sensors (eg. AVIRIS ng) for better combined

  18. Use of multispectral satellite imagery and hyperspectral endmember libraries for urban land cover mapping at the metropolitan scale

    Science.gov (United States)

    Priem, Frederik; Okujeni, Akpona; van der Linden, Sebastian; Canters, Frank

    2016-10-01

    The value of characteristic reflectance features for mapping urban materials has been demonstrated in many experiments with airborne imaging spectrometry. Analysis of larger areas requires satellite-based multispectral imagery, which typically lacks the spatial and spectral detail of airborne data. Consequently the need arises to develop mapping methods that exploit the complementary strengths of both data sources. In this paper a workflow for sub-pixel quantification of Vegetation-Impervious-Soil urban land cover is presented, using medium resolution multispectral satellite imagery, hyperspectral endmember libraries and Support Vector Regression. A Landsat 8 Operational Land Imager surface reflectance image covering the greater metropolitan area of Brussels is selected for mapping. Two spectral libraries developed for the cities of Brussels and Berlin based on airborne hyperspectral APEX and HyMap data are used. First the combined endmember library is resampled to match the spectral response of the Landsat sensor. The library is then optimized to avoid spectral redundancy and confusion. Subsequently the spectra of the endmember library are synthetically mixed to produce training data for unmixing. Mapping is carried out using Support Vector Regression models trained with spectra selected through stratified sampling of the mixed library. Validation on building block level (mean size = 46.8 Landsat pixels) yields an overall good fit between reference data and estimation with Mean Absolute Errors of 0.06, 0.06 and 0.08 for vegetation, impervious and soil respectively. Findings of this work may contribute to the use of universal spectral libraries for regional scale land cover fraction mapping using regression approaches.

  19. Object-Based Change Detection in Urban Areas: The Effects of Segmentation Strategy, Scale, and Feature Space on Unsupervised Methods

    Directory of Open Access Journals (Sweden)

    Lei Ma

    2016-09-01

    Full Text Available Object-based change detection (OBCD has recently been receiving increasing attention as a result of rapid improvements in the resolution of remote sensing data. However, some OBCD issues relating to the segmentation of high-resolution images remain to be explored. For example, segmentation units derived using different segmentation strategies, segmentation scales, feature space, and change detection methods have rarely been assessed. In this study, we have tested four common unsupervised change detection methods using different segmentation strategies and a series of segmentation scale parameters on two WorldView-2 images of urban areas. We have also evaluated the effect of adding extra textural and Normalized Difference Vegetation Index (NDVI information instead of using only spectral information. Our results indicated that change detection methods performed better at a medium scale than at a fine scale where close to the pixel size. Multivariate Alteration Detection (MAD always outperformed the other methods tested, at the same confidence level. The overall accuracy appeared to benefit from using a two-date segmentation strategy rather than single-date segmentation. Adding textural and NDVI information appeared to reduce detection accuracy, but the magnitude of this reduction was not consistent across the different unsupervised methods and segmentation strategies. We conclude that a two-date segmentation strategy is useful for change detection in high-resolution imagery, but that the optimization of thresholds is critical for unsupervised change detection methods. Advanced methods need be explored that can take advantage of additional textural or other parameters.

  20. Non-uniform plastic deformation of micron scale objects

    DEFF Research Database (Denmark)

    Niordson, Christian Frithiof; Hutchinson, J. W.

    2003-01-01

    Significant increases in apparent flow strength are observed when non-uniform plastic deformation of metals occurs at the scale ranging from roughly one to ten microns. Several basic plane strain problems are analyzed numerically in this paper based on a new formulation of strain gradient...... plasticity. The problems are the tangential and normal loading of a finite rectangular block of material bonded to rigid platens and having traction-free ends, and the normal loading of a half-space by a flat, rigid punch. The solutions illustrate fundamental features of plasticity at the micron scale...... that are not captured by conventional plasticity theory. These include the role of material length parameters in establishing the size dependence of strength and the elevation of resistance to plastic flow resulting from constraint on plastic flow at boundaries. Details of the finite element method employed...

  1. An Automated Approach to Map Winter Cropped Area of Smallholder Farms across Large Scales Using MODIS Imagery

    Directory of Open Access Journals (Sweden)

    Meha Jain

    2017-06-01

    Full Text Available Fine-scale agricultural statistics are an important tool for understanding trends in food production and their associated drivers, yet these data are rarely collected in smallholder systems. These statistics are particularly important for smallholder systems given the large amount of fine-scale heterogeneity in production that occurs in these regions. To overcome the lack of ground data, satellite data are often used to map fine-scale agricultural statistics. However, doing so is challenging for smallholder systems because of (1 complex sub-pixel heterogeneity; (2 little to no available calibration data; and (3 high amounts of cloud cover as most smallholder systems occur in the tropics. We develop an automated method termed the MODIS Scaling Approach (MSA to map smallholder cropped area across large spatial and temporal scales using MODIS Enhanced Vegetation Index (EVI satellite data. We use this method to map winter cropped area, a key measure of cropping intensity, across the Indian subcontinent annually from 2000–2001 to 2015–2016. The MSA defines a pixel as cropped based on winter growing season phenology and scales the percent of cropped area within a single MODIS pixel based on observed EVI values at peak phenology. We validated the result with eleven high-resolution scenes (spatial scale of 5 × 5 m2 or finer that we classified into cropped versus non-cropped maps using training data collected by visual inspection of the high-resolution imagery. The MSA had moderate to high accuracies when validated using these eleven scenes across India (R2 ranging between 0.19 and 0.89 with an overall R2 of 0.71 across all sites. This method requires no calibration data, making it easy to implement across large spatial and temporal scales, with 100% spatial coverage due to the compositing of EVI to generate cloud-free data sets. The accuracies found in this study are similar to those of other studies that map crop production using automated methods

  2. Using GeoEye-1 Imagery for Multi-Temporal Object-Based Detection of Canegrub Damage in Sugarcane Fields in Queensland, Australia

    KAUST Repository

    Johansen, Kasper

    2017-12-18

    The greyback canegrub (Dermolepida albohirtum) is the main pest of sugarcane crops in all cane-growing regions between Mossman (16.5°S) and Sarina (21.5°S) in Queensland, Australia. In previous years, high infestations have cost the industry up to $40 million. However, identifying damage in the field is difficult due to the often impenetrable nature of the sugarcane crop. Satellite imagery offers a feasible means of achieving this by examining the visual characteristics of stool tipping, changed leaf color, and exposure of soil in damaged areas. The objective of this study was to use geographic object-based image analysis (GEOBIA) and high-spatial resolution GeoEye-1 satellite imagery for three years to map canegrub damage and develop two mapping approaches suitable for risk mapping. The GEOBIA mapping approach for canegrub damage detection was evaluated over three selected study sites in Queensland, covering a total of 254 km2 and included five main steps developed in the eCognition Developer software. These included: (1) initial segmentation of sugarcane block boundaries; (2) classification and subsequent omission of fallow/harvested fields, tracks, and other non-sugarcane features within the block boundaries; (3) identification of likely canegrub-damaged areas with low NDVI values and high levels of image texture within each block; (4) the further refining of canegrub damaged areas to low, medium, and high likelihood; and (5) risk classification. The validation based on field observations of canegrub damage at the time of the satellite image capture yielded producer’s accuracies between 75% and 98.7%, depending on the study site. Error of commission occurred in some cases due to sprawling, drainage issues, wind, weed, and pig damage. The two developed risk mapping approaches were based on the results of the canegrub damage detection. This research will improve decision making by growers affected by canegrub damage.

  3. Unsupervised Multi-Scale Change Detection from SAR Imagery for Monitoring Natural and Anthropogenic Disasters

    Science.gov (United States)

    Ajadi, Olaniyi A.

    increase the sampling frequency, while the developed multiscale-driven approach reliably identified changes embedded in largely stationary background scenes. With this technique, I was able to identify the extent of burn scars with high accuracy. I further applied the application of the change detection technology to oil spill mapping. The analysis highlights that the approach described in Chapter 3 can be applied to this drastically different change detection problem with only little modification. While the core of the change detection technique remained unchanged, I made modifications to the pre-processing step to enable change detection from scenes of continuously varying background. I introduced the Lipschitz regularity (LR) transformation as a technique to normalize the typically dynamic ocean surface, facilitating high performance oil spill detection independent of environmental conditions during image acquisition. For instance, I showed that LR processing reduces the sensitivity of change detection performance to variations in surface winds, which is a known limitation in oil spill detection from SAR. Finally, I applied the change detection technique to aufeis flood mapping along the Sagavanirktok River. Due to the complex nature of aufeis flooded areas, I substituted the resolution-preserving speckle filter used in Chapter 3 with curvelet filters. In addition to validating the performance of the change detection results, I also provide evidence of the wealth of information that can be extracted about aufeis flooding events once a time series of change detection information was extracted from SAR imagery. A summary of the developed change detection techniques is conducted and suggested future work is presented in Chapter 6.

  4. Implications of sensor design for coral reef detection: Upscaling ground hyperspectral imagery in spatial and spectral scales

    Science.gov (United States)

    Caras, Tamir; Hedley, John; Karnieli, Arnon

    2017-12-01

    Remote sensing offers a potential tool for large scale environmental surveying and monitoring. However, remote observations of coral reefs are difficult especially due to the spatial and spectral complexity of the target compared to sensor specifications as well as the environmental implications of the water medium above. The development of sensors is driven by technological advances and the desired products. Currently, spaceborne systems are technologically limited to a choice between high spectral resolution and high spatial resolution, but not both. The current study explores the dilemma of whether future sensor design for marine monitoring should prioritise on improving their spatial or spectral resolution. To address this question, a spatially and spectrally resampled ground-level hyperspectral image was used to test two classification elements: (1) how the tradeoff between spatial and spectral resolutions affects classification; and (2) how a noise reduction by majority filter might improve classification accuracy. The studied reef, in the Gulf of Aqaba (Eilat), Israel, is heterogeneous and complex so the local substrate patches are generally finer than currently available imagery. Therefore, the tested spatial resolution was broadly divided into four scale categories from five millimeters to one meter. Spectral resolution resampling aimed to mimic currently available and forthcoming spaceborne sensors such as (1) Environmental Mapping and Analysis Program (EnMAP) that is characterized by 25 bands of 6.5 nm width; (2) VENμS with 12 narrow bands; and (3) the WorldView series with broadband multispectral resolution. Results suggest that spatial resolution should generally be prioritized for coral reef classification because the finer spatial scale tested (pixel size mind, while the focus in this study was on the technologically limited spaceborne design, aerial sensors may presently provide an opportunity to implement the suggested setup.

  5. Fractals as objects with nontrivial structures at all scales

    International Nuclear Information System (INIS)

    Lacan, Francis; Tresser, Charles

    2015-01-01

    Toward the middle of 2001, the authors started arguing that fractals are important when discussing the operational resilience of information systems and related computer sciences issues such as artificial intelligence. But in order to argue along these lines it turned out to be indispensable to define fractals so as to let one recognize as fractals some sets that are very far from being self similar in the (usual) metric sense. This paper is devoted to define (in a loose sense at least) fractals in ways that allow for instance all the Cantor sets to be fractals and that permit to recognize fractality (the property of being fractal) in the context of the information technology issues that we had tried to comprehend. Starting from the meta-definition of a fractal as an “object with non-trivial structure at all scales” that we had used for long, we ended up taking these words seriously. Accordingly we define fractals in manners that depend both on the structures that the fractals are endowed with and the chosen sets of structure compatible maps, i.e., we approach fractals in a category-dependent manner. We expect that this new approach to fractals will contribute to the understanding of more of the fractals that appear in exact and other sciences than what can be handled presently

  6. Poverty assessment using DMSP/OLS night-time light satellite imagery at a provincial scale in China

    Science.gov (United States)

    Wang, Wen; Cheng, Hui; Zhang, Li

    2012-04-01

    All countries around the world and many international bodies, including the United Nations Development Program (UNDP), United Nations Food and Agricultural Organization (FAO), the International Fund for Agricultural Development (IFAD) and the International Labor Organization (ILO), have to eliminate rural poverty. Estimation of regional poverty level is a key issue for making strategies to eradicate poverty. Most of previous studies on regional poverty evaluations are based on statistics collected typically in administrative units. This paper has discussed the deficiencies of traditional studies, and attempted to research regional poverty evaluation issues using 3-year DMSP/OLS night-time light satellite imagery. In this study, we adopted 17 socio-economic indexes to establish an integrated poverty index (IPI) using principal component analysis (PCA), which was proven to provide a good descriptor of poverty levels in 31 regions at a provincial scale in China. We also explored the relationship between DMSP/OLS night-time average light index and the poverty index using regression analysis in SPSS and a good positive linear correlation was modelled, with R2 equal to 0.854. We then looked at provincial poverty problems in China based on this correlation. The research results indicated that the DMSP/OLS night-time light data can assist analysing provincial poverty evaluation issues.

  7. SUPPORT VECTOR MACHINE CLASSIFICATION OF OBJECT-BASED DATA FOR CROP MAPPING, USING MULTI-TEMPORAL LANDSAT IMAGERY

    Directory of Open Access Journals (Sweden)

    R. Devadas

    2012-07-01

    Full Text Available Crop mapping and time series analysis of agronomic cycles are critical for monitoring land use and land management practices, and analysing the issues of agro-environmental impacts and climate change. Multi-temporal Landsat data can be used to analyse decadal changes in cropping patterns at field level, owing to its medium spatial resolution and historical availability. This study attempts to develop robust remote sensing techniques, applicable across a large geographic extent, for state-wide mapping of cropping history in Queensland, Australia. In this context, traditional pixel-based classification was analysed in comparison with image object-based classification using advanced supervised machine-learning algorithms such as Support Vector Machine (SVM. For the Darling Downs region of southern Queensland we gathered a set of Landsat TM images from the 2010–2011 cropping season. Landsat data, along with the vegetation index images, were subjected to multiresolution segmentation to obtain polygon objects. Object-based methods enabled the analysis of aggregated sets of pixels, and exploited shape-related and textural variation, as well as spectral characteristics. SVM models were chosen after examining three shape-based parameters, twenty-three textural parameters and ten spectral parameters of the objects. We found that the object-based methods were superior to the pixel-based methods for classifying 4 major landuse/land cover classes, considering the complexities of within field spectral heterogeneity and spectral mixing. Comparative analysis clearly revealed that higher overall classification accuracy (95% was observed in the object-based SVM compared with that of traditional pixel-based classification (89% using maximum likelihood classifier (MLC. Object-based classification also resulted speckle-free images. Further, object-based SVM models were used to classify different broadacre crop types for summer and winter seasons. The influence of

  8. A methodology for small scale rural land use mapping in semi-arid developing countries using orbital imagery. Part 4: Review of land use surveys using orbital imagery outside of the USA

    Science.gov (United States)

    Vangenderen, J. L. (Principal Investigator); Lock, B. F.

    1976-01-01

    The author has identified the following significant results. Outside the U.S., various attempts were made to investigate the feasibility of utilizing orbital MSS imagery in the production of small scale land use maps. Overall, these studies are not as elaborate or extensive in their scope as the U.S. ones, and generally the non-U.S. investigators have employed nonsophisticated and less expensive techniques. A representative range of studies is presented to demonstrate the approaches and trends dealing with reprocessing, interpretation, classification, sampling, and ground truth procedures.

  9. Optimization Approach for Multi-scale Segmentation of Remotely Sensed Imagery under k-means Clustering Guidance

    Directory of Open Access Journals (Sweden)

    WANG Huixian

    2015-05-01

    Full Text Available In order to adapt different scale land cover segmentation, an optimized approach under the guidance of k-means clustering for multi-scale segmentation is proposed. At first, small scale segmentation and k-means clustering are used to process the original images; then the result of k-means clustering is used to guide objects merging procedure, in which Otsu threshold method is used to automatically select the impact factor of k-means clustering; finally we obtain the segmentation results which are applicable to different scale objects. FNEA method is taken for an example and segmentation experiments are done using a simulated image and a real remote sensing image from GeoEye-1 satellite, qualitative and quantitative evaluation demonstrates that the proposed method can obtain high quality segmentation results.

  10. Wavelet Scale Analysis of Mesoscale Convective Systems for Detecting Deep Convection From Infrared Imagery

    Science.gov (United States)

    Klein, Cornelia; Belušić, Danijel; Taylor, Christopher M.

    2018-03-01

    Mesoscale convective systems (MCSs) are frequently associated with rainfall extremes and are expected to further intensify under global warming. However, despite the significant impact of such extreme events, the dominant processes favoring their occurrence are still under debate. Meteosat geostationary satellites provide unique long-term subhourly records of cloud top temperatures, allowing to track changes in MCS structures that could be linked to rainfall intensification. Focusing on West Africa, we show that Meteosat cloud top temperatures are a useful proxy for rainfall intensities, as derived from snapshots from the Tropical Rainfall Measuring Mission 2A25 product: MCSs larger than 15,000 km2 at a temperature threshold of -40°C are found to produce 91% of all extreme rainfall occurrences in the study region, with 80% of the storms producing extreme rain when their minimum temperature drops below -80°C. Furthermore, we present a new method based on 2-D continuous wavelet transform to explore the relationship between cloud top temperature and rainfall intensity for subcloud features at different length scales. The method shows great potential for separating convective and stratiform cloud parts when combining information on temperature and scale, improving the common approach of using a temperature threshold only. We find that below -80°C, every fifth pixel is associated with deep convection. This frequency is doubled when looking at subcloud features smaller than 35 km. Scale analysis of subcloud features can thus help to better exploit cloud top temperature data sets, which provide much more spatiotemporal detail of MCS characteristics than available rainfall data sets alone.

  11. Genetic Particle Swarm Optimization–Based Feature Selection for Very-High-Resolution Remotely Sensed Imagery Object Change Detection

    Science.gov (United States)

    Chen, Qiang; Chen, Yunhao; Jiang, Weiguo

    2016-01-01

    In the field of multiple features Object-Based Change Detection (OBCD) for very-high-resolution remotely sensed images, image objects have abundant features and feature selection affects the precision and efficiency of OBCD. Through object-based image analysis, this paper proposes a Genetic Particle Swarm Optimization (GPSO)-based feature selection algorithm to solve the optimization problem of feature selection in multiple features OBCD. We select the Ratio of Mean to Variance (RMV) as the fitness function of GPSO, and apply the proposed algorithm to the object-based hybrid multivariate alternative detection model. Two experiment cases on Worldview-2/3 images confirm that GPSO can significantly improve the speed of convergence, and effectively avoid the problem of premature convergence, relative to other feature selection algorithms. According to the accuracy evaluation of OBCD, GPSO is superior at overall accuracy (84.17% and 83.59%) and Kappa coefficient (0.6771 and 0.6314) than other algorithms. Moreover, the sensitivity analysis results show that the proposed algorithm is not easily influenced by the initial parameters, but the number of features to be selected and the size of the particle swarm would affect the algorithm. The comparison experiment results reveal that RMV is more suitable than other functions as the fitness function of GPSO-based feature selection algorithm. PMID:27483285

  12. Genetic Particle Swarm Optimization-Based Feature Selection for Very-High-Resolution Remotely Sensed Imagery Object Change Detection.

    Science.gov (United States)

    Chen, Qiang; Chen, Yunhao; Jiang, Weiguo

    2016-07-30

    In the field of multiple features Object-Based Change Detection (OBCD) for very-high-resolution remotely sensed images, image objects have abundant features and feature selection affects the precision and efficiency of OBCD. Through object-based image analysis, this paper proposes a Genetic Particle Swarm Optimization (GPSO)-based feature selection algorithm to solve the optimization problem of feature selection in multiple features OBCD. We select the Ratio of Mean to Variance (RMV) as the fitness function of GPSO, and apply the proposed algorithm to the object-based hybrid multivariate alternative detection model. Two experiment cases on Worldview-2/3 images confirm that GPSO can significantly improve the speed of convergence, and effectively avoid the problem of premature convergence, relative to other feature selection algorithms. According to the accuracy evaluation of OBCD, GPSO is superior at overall accuracy (84.17% and 83.59%) and Kappa coefficient (0.6771 and 0.6314) than other algorithms. Moreover, the sensitivity analysis results show that the proposed algorithm is not easily influenced by the initial parameters, but the number of features to be selected and the size of the particle swarm would affect the algorithm. The comparison experiment results reveal that RMV is more suitable than other functions as the fitness function of GPSO-based feature selection algorithm.

  13. Object-Based Greenhouse Horticultural Crop Identification from Multi-Temporal Satellite Imagery: A Case Study in Almeria, Spain

    Directory of Open Access Journals (Sweden)

    Manuel A. Aguilar

    2015-06-01

    Full Text Available Greenhouse detection and mapping via remote sensing is a complex task, which has already been addressed in numerous studies. In this research, the innovative goal relies on the identification of greenhouse horticultural crops that were growing under plastic coverings on 30 September 2013. To this end, object-based image analysis (OBIA and a decision tree classifier (DT were applied to a set consisting of eight Landsat 8 OLI images collected from May to November 2013. Moreover, a single WorldView-2 satellite image acquired on 30 September 2013, was also used as a data source. In this approach, basic spectral information, textural features and several vegetation indices (VIs derived from Landsat 8 and WorldView-2 multi-temporal satellite data were computed on previously segmented image objects in order to identify four of the most popular autumn crops cultivated under greenhouse in Almería, Spain (i.e., tomato, pepper, cucumber and aubergine. The best classification accuracy (81.3% overall accuracy was achieved by using the full set of Landsat 8 time series. These results were considered good in the case of tomato and pepper crops, being significantly worse for cucumber and aubergine. These results were hardly improved by adding the information of the WorldView-2 image. The most important information for correct classification of different crops under greenhouses was related to the greenhouse management practices and not the spectral properties of the crops themselves.

  14. Mapping changes in the largest continuous Amazonian mangrove belt using object-based classification of multisensor satellite imagery

    Science.gov (United States)

    Nascimento, Wilson R.; Souza-Filho, Pedro Walfir M.; Proisy, Christophe; Lucas, Richard M.; Rosenqvist, Ake

    2013-01-01

    Mapping and monitoring mangrove ecosystems is a crucial objective for tropical countries, particularly where human disturbance occurs and because of uncertainties associated with sea level and climatic fluctuation. In many tropical regions, such efforts have focused largely on the use of optical data despite low capture rates because of persistent cloud cover. Recognizing the ability of Synthetic Aperture Radar (SAR) for providing cloud-free observations, this study investigated the use of JERS-1 SAR and ALOS PALSAR data, acquired in 1996 and 2008 respectively, for mapping the extent of mangroves along the Brazilian coastline, from east of the Amazon River mouth, Pará State, to the Bay of São José in Maranhão. For each year, an object-orientated classification of major land covers (mangrove, secondary vegetation, gallery and swamp forest, open water, intermittent lakes and bare areas) was performed with the resulting maps then compared to quantify change. Comparison with available ground truth data indicated a general accuracy in the 2008 image classification of all land covers of 96% (kappa = 90.6%, tau = 92.6%). Over the 12 year period, the area of mangrove increased by 718.6 km2 from 6705 m2 to 7423.60 km2, with 1931.0 km² of expansion and 1213 km² of erosion noted; 5493 km² remained unchanged in extent. The general accuracy relating to changes in mangroves was 83.3% (Kappa 66.1%; tau 66.7%). The study confirmed that these mangroves constituted the largest continuous belt globally and were experiencing significant change because of the dynamic coastal environment and the influence of sedimentation from the Amazon River along the shoreline. The study recommends continued observations using combinations of SAR and optical data to establish trends in mangrove distributions and implications for provision of ecosystem services (e.g., fish/invertebrate nurseries, carbon storage and coastal protection).

  15. Aerial Photography and Imagery, Oblique, This data set was acquired through a federal grant with Pictometry International. The imagery is either 4" or 9" resolution., Published in 2011, Not Applicable scale, Chippewa County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Oblique dataset current as of 2011. This data set was acquired through a federal grant with Pictometry International. The imagery is...

  16. Extending a field-based Sonoran desert vegetation classification to a regional scale using optical and microwave satellite imagery

    Science.gov (United States)

    Shupe, Scott Marshall

    2000-10-01

    Vegetation mapping in and regions facilitates ecological studies, land management, and provides a record to which future land changes can be compared. Accurate and representative mapping of desert vegetation requires a sound field sampling program and a methodology to transform the data collected into a representative classification system. Time and cost constraints require that a remote sensing approach be used if such a classification system is to be applied on a regional scale. However, desert vegetation may be sparse and thus difficult to sense at typical satellite resolutions, especially given the problem of soil reflectance. This study was designed to address these concerns by conducting vegetation mapping research using field and satellite data from the US Army Yuma Proving Ground (USYPG) in Southwest Arizona. Line and belt transect data from the Army's Land Condition Trend Analysis (LCTA) Program were transformed into relative cover and relative density classification schemes using cluster analysis. Ordination analysis of the same data produced two and three-dimensional graphs on which the homogeneity of each vegetation class could be examined. It was found that the use of correspondence analysis (CA), detrended correspondence analysis (DCA), and non-metric multidimensional scaling (NMS) ordination methods was superior to the use of any single ordination method for helping to clarify between-class and within-class relationships in vegetation composition. Analysis of these between-class and within-class relationships were of key importance in examining how well relative cover and relative density schemes characterize the USYPG vegetation. Using these two classification schemes as reference data, maximum likelihood and artificial neural net classifications were then performed on a coregistered dataset consisting of a summer Landsat Thematic Mapper (TM) image, one spring and one summer ERS-1 microwave image, and elevation, slope, and aspect layers

  17. Large-scale weakly supervised object localization via latent category learning.

    Science.gov (United States)

    Chong Wang; Kaiqi Huang; Weiqiang Ren; Junge Zhang; Maybank, Steve

    2015-04-01

    Localizing objects in cluttered backgrounds is challenging under large-scale weakly supervised conditions. Due to the cluttered image condition, objects usually have large ambiguity with backgrounds. Besides, there is also a lack of effective algorithm for large-scale weakly supervised localization in cluttered backgrounds. However, backgrounds contain useful latent information, e.g., the sky in the aeroplane class. If this latent information can be learned, object-background ambiguity can be largely reduced and background can be suppressed effectively. In this paper, we propose the latent category learning (LCL) in large-scale cluttered conditions. LCL is an unsupervised learning method which requires only image-level class labels. First, we use the latent semantic analysis with semantic object representation to learn the latent categories, which represent objects, object parts or backgrounds. Second, to determine which category contains the target object, we propose a category selection strategy by evaluating each category's discrimination. Finally, we propose the online LCL for use in large-scale conditions. Evaluation on the challenging PASCAL Visual Object Class (VOC) 2007 and the large-scale imagenet large-scale visual recognition challenge 2013 detection data sets shows that the method can improve the annotation precision by 10% over previous methods. More importantly, we achieve the detection precision which outperforms previous results by a large margin and can be competitive to the supervised deformable part model 5.0 baseline on both data sets.

  18. Estimation and modeling of forest attributes across large spatial scales using BiomeBGC, high-resolution imagery, LiDAR data, and inventory data

    Science.gov (United States)

    Golinkoff, Jordan Seth

    The accurate estimation of forest attributes at many different spatial scales is a critical problem. Forest landowners may be interested in estimating timber volume, forest biomass, and forest structure to determine their forest's condition and value. Counties and states may be interested to learn about their forests to develop sustainable management plans and policies related to forests, wildlife, and climate change. Countries and consortiums of countries need information about their forests to set global and national targets to deal with issues of climate change and deforestation as well as to set national targets and understand the state of their forest at a given point in time. This dissertation approaches these questions from two perspectives. The first perspective uses the process model Biome-BGC paired with inventory and remote sensing data to make inferences about a current forest state given known climate and site variables. Using a model of this type, future climate data can be used to make predictions about future forest states as well. An example of this work applied to a forest in northern California is presented. The second perspective of estimating forest attributes uses high resolution aerial imagery paired with light detection and ranging (LiDAR) remote sensing data to develop statistical estimates of forest structure. Two approaches within this perspective are presented: a pixel based approach and an object based approach. Both approaches can serve as the platform on which models (either empirical growth and yield models or process models) can be run to generate inferences about future forest state and current forest biogeochemical cycling.

  19. OBJECT-ORIENTED CHANGE DETECTION BASED ON MULTI-SCALE APPROACH

    Directory of Open Access Journals (Sweden)

    Y. Jia

    2016-06-01

    Full Text Available The change detection of remote sensing images means analysing the change information quantitatively and recognizing the change types of the surface coverage data in different time phases. With the appearance of high resolution remote sensing image, object-oriented change detection method arises at this historic moment. In this paper, we research multi-scale approach for high resolution images, which includes multi-scale segmentation, multi-scale feature selection and multi-scale classification. Experimental results show that this method has a stronger advantage than the traditional single-scale method of high resolution remote sensing image change detection.

  20. Impact of Data Placement on Resilience in Large-Scale Object Storage Systems

    Energy Technology Data Exchange (ETDEWEB)

    Carns, Philip; Harms, Kevin; Jenkins, John; Mubarak, Misbah; Ross, Robert; Carothers, Christopher

    2016-05-02

    Distributed object storage architectures have become the de facto standard for high-performance storage in big data, cloud, and HPC computing. Object storage deployments using commodity hardware to reduce costs often employ object replication as a method to achieve data resilience. Repairing object replicas after failure is a daunting task for systems with thousands of servers and billions of objects, however, and it is increasingly difficult to evaluate such scenarios at scale on realworld systems. Resilience and availability are both compromised if objects are not repaired in a timely manner. In this work we leverage a high-fidelity discrete-event simulation model to investigate replica reconstruction on large-scale object storage systems with thousands of servers, billions of objects, and petabytes of data. We evaluate the behavior of CRUSH, a well-known object placement algorithm, and identify configuration scenarios in which aggregate rebuild performance is constrained by object placement policies. After determining the root cause of this bottleneck, we then propose enhancements to CRUSH and the usage policies atop it to enable scalable replica reconstruction. We use these methods to demonstrate a simulated aggregate rebuild rate of 410 GiB/s (within 5% of projected ideal linear scaling) on a 1,024-node commodity storage system. We also uncover an unexpected phenomenon in rebuild performance based on the characteristics of the data stored on the system.

  1. Extending a prototype knowledge and object based image analysis model to coarser spatial resolution imagery: an example from the Missouri River

    Science.gov (United States)

    Strong, Laurence L.

    2012-01-01

    A prototype knowledge- and object-based image analysis model was developed to inventory and map least tern and piping plover habitat on the Missouri River, USA. The model has been used to inventory the state of sandbars annually for 4 segments of the Missouri River since 2006 using QuickBird imagery. Interpretation of the state of sandbars is difficult when images for the segment are acquired at different river stages and different states of vegetation phenology and canopy cover. Concurrent QuickBird and RapidEye images were classified using the model and the spatial correspondence of classes in the land cover and sandbar maps were analysed for the spatial extent of the images and at nest locations for both bird species. Omission and commission errors were low for unvegetated land cover classes used for nesting by both bird species and for land cover types with continuous vegetation cover and water. Errors were larger for land cover classes characterized by a mixture of sand and vegetation. Sandbar classification decisions are made using information on land cover class proportions and disagreement between sandbar classes was resolved using fuzzy membership possibilities. Regression analysis of area for a paired sample of 47 sandbars indicated an average positive bias, 1.15 ha, for RapidEye that did not vary with sandbar size. RapidEye has potential to reduce temporal uncertainty about least tern and piping plover habitat but would not be suitable for mapping sandbar erosion, and characterization of sandbar shapes or vegetation patches at fine spatial resolution.

  2. Extending a prototype knowledge- and object-based image analysis model to coarser spatial resolution imagery: an example from the Missouri River

    Science.gov (United States)

    Strong, Laurence L.

    2012-01-01

    A prototype knowledge- and object-based image analysis model was developed to inventory and map least tern and piping plover habitat on the Missouri River, USA. The model has been used to inventory the state of sandbars annually for 4 segments of the Missouri River since 2006 using QuickBird imagery. Interpretation of the state of sandbars is difficult when images for the segment are acquired at different river stages and different states of vegetation phenology and canopy cover. Concurrent QuickBird and RapidEye images were classified using the model and the spatial correspondence of classes in the land cover and sandbar maps were analysed for the spatial extent of the images and at nest locations for both bird species. Omission and commission errors were low for unvegetated land cover classes used for nesting by both bird species and for land cover types with continuous vegetation cover and water. Errors were larger for land cover classes characterized by a mixture of sand and vegetation. Sandbar classification decisions are made using information on land cover class proportions and disagreement between sandbar classes was resolved using fuzzy membership possibilities. Regression analysis of area for a paired sample of 47 sandbars indicated an average positive bias, 1.15 ha, for RapidEye that did not vary with sandbar size. RapidEye has potential to reduce temporal uncertainty about least tern and piping plover habitat but would not be suitable for mapping sandbar erosion, and characterization of sandbar shapes or vegetation patches at fine spatial resolution.

  3. Objectivity

    CERN Document Server

    Daston, Lorraine

    2010-01-01

    Objectivity has a history, and it is full of surprises. In Objectivity, Lorraine Daston and Peter Galison chart the emergence of objectivity in the mid-nineteenth-century sciences--and show how the concept differs from its alternatives, truth-to-nature and trained judgment. This is a story of lofty epistemic ideals fused with workaday practices in the making of scientific images. From the eighteenth through the early twenty-first centuries, the images that reveal the deepest commitments of the empirical sciences--from anatomy to crystallography--are those featured in scientific atlases, the compendia that teach practitioners what is worth looking at and how to look at it. Galison and Daston use atlas images to uncover a hidden history of scientific objectivity and its rivals. Whether an atlas maker idealizes an image to capture the essentials in the name of truth-to-nature or refuses to erase even the most incidental detail in the name of objectivity or highlights patterns in the name of trained judgment is a...

  4. Scaling of lifting forces in relation to object size in whole body lifting

    NARCIS (Netherlands)

    Kingma, I.; van Dieen, J.H.; Toussaint, H.M.

    2005-01-01

    Subjects prepare for a whole body lifting movement by adjusting their posture and scaling their lifting forces to the expected object weight. The expectancy is based on visual and haptic size cues. This study aimed to find out whether lifting force overshoots related to object size cues disappear or

  5. The applicability of space imagery to the small-scale topographic mapping of developing countries: A case study — the Sudan

    Science.gov (United States)

    Petrie, G.; El Niweiri, A. E. H.

    After reviewing the current status of topographic mapping in Sudan, the paper considers the possible applications of space inagery to the topographic mapping of the country at 1 : 100,000 scale. A comprehensive series of tests of the geometric accuracy and interpretability of six types of space imagery taken by the Landsat MSS, RBV and TM sensors, the MOMS scanner, the ESA Metric Camera and NASA's Large Format Camera have been conducted over a test area established in the Red Sea Hills area of Sudan supplemented by further interpretation tests carried out over the area of Khartoum and the Gezira. The results of these tests are given together with those from comparative tests carried out with other images acquired by the same sensors over test areas in developed countries (UK and USA). Further collateral information on topographic mapping at 1 : 100,000 scale from SPOT imagery has been provided by the Ordnance Survey based on its tests and experience in North Yemen. The paper concludes with an analysis of the possibilities of mapping the main (non-equatorial) area of Sudan at 1 : 100,000 scale based on the results of the extensive series of tests reported in the paper and elsewhere. Consideration is also given to the infrastructure required to support such a programme.

  6. Object-based assessment of burn severity in diseased forests using high-spatial and high-spectral resolution MASTER airborne imagery

    Science.gov (United States)

    Chen, Gang; Metz, Margaret R.; Rizzo, David M.; Dillon, Whalen W.; Meentemeyer, Ross K.

    2015-04-01

    Forest ecosystems are subject to a variety of disturbances with increasing intensities and frequencies, which may permanently change the trajectories of forest recovery and disrupt the ecosystem services provided by trees. Fire and invasive species, especially exotic disease-causing pathogens and insects, are examples of disturbances that together could pose major threats to forest health. This study examines the impacts of fire and exotic disease (sudden oak death) on forests, with an emphasis on the assessment of post-fire burn severity in a forest where trees have experienced three stages of disease progression pre-fire: early-stage (trees retaining dried foliage and fine twigs), middle-stage (trees losing fine crown fuels), and late-stage (trees falling down). The research was conducted by applying Geographic Object-Based Image Analysis (GEOBIA) to MASTER airborne images that were acquired immediately following the fire for rapid assessment and contained both high-spatial (4 m) and high-spectral (50 bands) resolutions. Although GEOBIA has gradually become a standard tool for analyzing high-spatial resolution imagery, high-spectral resolution data (dozens to hundreds of bands) can dramatically reduce computation efficiency in the process of segmentation and object-based variable extraction, leading to complicated variable selection for succeeding modeling. Hence, we also assessed two widely used band reduction algorithms, PCA (principal component analysis) and MNF (minimum noise fraction), for the delineation of image objects and the subsequent performance of burn severity models using either PCA or MNF derived variables. To increase computation efficiency, only the top 5 PCA and MNF and top 10 PCA and MNF components were evaluated, which accounted for 10% and 20% of the total number of the original 50 spectral bands, respectively. Results show that if no band reduction was applied the models developed for the three stages of disease progression had relatively

  7. Imagery Data Base Facility

    Data.gov (United States)

    Federal Laboratory Consortium — The Imagery Data Base Facility supports AFRL and other government organizations by providing imagery interpretation and analysis to users for data selection, imagery...

  8. Fusion of LiDAR and aerial imagery for the estimation of downed tree volume using Support Vector Machines classification and region based object fitting

    Science.gov (United States)

    Selvarajan, Sowmya

    The study classifies 3D small footprint full waveform digitized LiDAR fused with aerial imagery to downed trees using Support Vector Machines (SVM) algorithm. Using small footprint waveform LiDAR, airborne LiDAR systems can provide better canopy penetration and very high spatial resolution. The small footprint waveform scanner system Riegl LMS-Q680 is addition with an UltraCamX aerial camera are used to measure and map downed trees in a forest. The various data preprocessing steps helped in the identification of ground points from the dense LiDAR dataset and segment the LiDAR data to help reduce the complexity of the algorithm. The haze filtering process helped to differentiate the spectral signatures of the various classes within the aerial image. Such processes, helped to better select the features from both sensor data. The six features: LiDAR height, LiDAR intensity, LiDAR echo, and three image intensities are utilized. To do so, LiDAR derived, aerial image derived and fused LiDAR-aerial image derived features are used to organize the data for the SVM hypothesis formulation. Several variations of the SVM algorithm with different kernels and soft margin parameter C are experimented. The algorithm is implemented to classify downed trees over a pine trees zone. The LiDAR derived features provided an overall accuracy of 98% of downed trees but with no classification error of 86%. The image derived features provided an overall accuracy of 65% and fusion derived features resulted in an overall accuracy of 88%. The results are observed to be stable and robust. The SVM accuracies were accompanied by high false alarm rates, with the LiDAR classification producing 58.45%, image classification producing 95.74% and finally the fused classification producing 93% false alarm rates The Canny edge correction filter helped control the LiDAR false alarm to 35.99%, image false alarm to 48.56% and fused false alarm to 37.69% The implemented classifiers provided a powerful tool for

  9. Studies on combined model based on functional objectives of large scale complex engineering

    Science.gov (United States)

    Yuting, Wang; Jingchun, Feng; Jiabao, Sun

    2018-03-01

    As various functions were included in large scale complex engineering, and each function would be conducted with completion of one or more projects, combined projects affecting their functions should be located. Based on the types of project portfolio, the relationship of projects and their functional objectives were analyzed. On that premise, portfolio projects-technics based on their functional objectives were introduced, then we studied and raised the principles of portfolio projects-technics based on the functional objectives of projects. In addition, The processes of combined projects were also constructed. With the help of portfolio projects-technics based on the functional objectives of projects, our research findings laid a good foundation for management of large scale complex engineering portfolio management.

  10. Modular, object-oriented redesign of a large-scale Monte Carlo neutron transport program

    International Nuclear Information System (INIS)

    Moskowitz, B.S.

    2000-01-01

    This paper describes the modular, object-oriented redesign of a large-scale Monte Carlo neutron transport program. This effort represents a complete 'white sheet of paper' rewrite of the code. In this paper, the motivation driving this project, the design objectives for the new version of the program, and the design choices and their consequences will be discussed. The design itself will also be described, including the important subsystems as well as the key classes within those subsystems

  11. A REGION-BASED MULTI-SCALE APPROACH FOR OBJECT-BASED IMAGE ANALYSIS

    Directory of Open Access Journals (Sweden)

    T. Kavzoglu

    2016-06-01

    Full Text Available Within the last two decades, object-based image analysis (OBIA considering objects (i.e. groups of pixels instead of pixels has gained popularity and attracted increasing interest. The most important stage of the OBIA is image segmentation that groups spectrally similar adjacent pixels considering not only the spectral features but also spatial and textural features. Although there are several parameters (scale, shape, compactness and band weights to be set by the analyst, scale parameter stands out the most important parameter in segmentation process. Estimating optimal scale parameter is crucially important to increase the classification accuracy that depends on image resolution, image object size and characteristics of the study area. In this study, two scale-selection strategies were implemented in the image segmentation process using pan-sharped Qickbird-2 image. The first strategy estimates optimal scale parameters for the eight sub-regions. For this purpose, the local variance/rate of change (LV-RoC graphs produced by the ESP-2 tool were analysed to determine fine, moderate and coarse scales for each region. In the second strategy, the image was segmented using the three candidate scale values (fine, moderate, coarse determined from the LV-RoC graph calculated for whole image. The nearest neighbour classifier was applied in all segmentation experiments and equal number of pixels was randomly selected to calculate accuracy metrics (overall accuracy and kappa coefficient. Comparison of region-based and image-based segmentation was carried out on the classified images and found that region-based multi-scale OBIA produced significantly more accurate results than image-based single-scale OBIA. The difference in classification accuracy reached to 10% in terms of overall accuracy.

  12. TrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in the Wild

    KAUST Repository

    Mü ller, Matthias; Bibi, Adel Aamer; Giancola, Silvio; Al-Subaihi, Salman; Ghanem, Bernard

    2018-01-01

    Despite the numerous developments in object tracking, further development of current tracking algorithms is limited by small and mostly saturated datasets. As a matter of fact, data-hungry trackers based on deep-learning currently rely on object detection datasets due to the scarcity of dedicated large-scale tracking datasets. In this work, we present TrackingNet, the first large-scale dataset and benchmark for object tracking in the wild. We provide more than 30K videos with more than 14 million dense bounding box annotations. Our dataset covers a wide selection of object classes in broad and diverse context. By releasing such a large-scale dataset, we expect deep trackers to further improve and generalize. In addition, we introduce a new benchmark composed of 500 novel videos, modeled with a distribution similar to our training dataset. By sequestering the annotation of the test set and providing an online evaluation server, we provide a fair benchmark for future development of object trackers. Deep trackers fine-tuned on a fraction of our dataset improve their performance by up to 1.6% on OTB100 and up to 1.7% on TrackingNet Test. We provide an extensive benchmark on TrackingNet by evaluating more than 20 trackers. Our results suggest that object tracking in the wild is far from being solved.

  13. TrackingNet: A Large-Scale Dataset and Benchmark for Object Tracking in the Wild

    KAUST Repository

    Müller, Matthias

    2018-03-28

    Despite the numerous developments in object tracking, further development of current tracking algorithms is limited by small and mostly saturated datasets. As a matter of fact, data-hungry trackers based on deep-learning currently rely on object detection datasets due to the scarcity of dedicated large-scale tracking datasets. In this work, we present TrackingNet, the first large-scale dataset and benchmark for object tracking in the wild. We provide more than 30K videos with more than 14 million dense bounding box annotations. Our dataset covers a wide selection of object classes in broad and diverse context. By releasing such a large-scale dataset, we expect deep trackers to further improve and generalize. In addition, we introduce a new benchmark composed of 500 novel videos, modeled with a distribution similar to our training dataset. By sequestering the annotation of the test set and providing an online evaluation server, we provide a fair benchmark for future development of object trackers. Deep trackers fine-tuned on a fraction of our dataset improve their performance by up to 1.6% on OTB100 and up to 1.7% on TrackingNet Test. We provide an extensive benchmark on TrackingNet by evaluating more than 20 trackers. Our results suggest that object tracking in the wild is far from being solved.

  14. A Multidimensional Scaling Approach to Developmental Dimensions in Object Permanence and Tracking Stimuli.

    Science.gov (United States)

    Townes-Rosenwein, Linda

    This paper discusses a longitudinal, exploratory study of developmental dimensions related to object permanence theory and explains how multidimensional scaling techniques can be used to identify developmental dimensions. Eighty infants, randomly assigned to one of four experimental groups and one of four counterbalanced orders of stimuli, were…

  15. Algorithm of search and track of static and moving large-scale objects

    Directory of Open Access Journals (Sweden)

    Kalyaev Anatoly

    2017-01-01

    Full Text Available We suggest an algorithm for processing of a sequence, which contains images of search and track of static and moving large-scale objects. The possible software implementation of the algorithm, based on multithread CUDA processing, is suggested. Experimental analysis of the suggested algorithm implementation is performed.

  16. Objective Scaling of Sound Quality for Normal-Hearing and Hearing-Impaired Listeners

    DEFF Research Database (Denmark)

    Nielsen, Lars Bramsløw

    ) Subjective sound quality ratings of clean and distorted speech and music signals, by normal-hearing and hearing-impaired listeners, to provide reference data, 2) An auditory model of the ear, including the effects of hearing loss, based on existing psychoacoustic knowledge, coupled to 3) An artificial neural......A new method for the objective estimation of sound quality for both normal-hearing and hearing-impaired listeners has been presented: OSSQAR (Objective Scaling of Sound Quality and Reproduction). OSSQAR is based on three main parts, which have been carried out and documented separately: 1...... network, which was trained to predict the sound quality ratings. OSSQAR predicts the perceived sound quality on two independent perceptual rating scales: Clearness and Sharpness. These two scales were shown to be the most relevant for assessment of sound quality, and they were interpreted the same way...

  17. Aerial Photography and Imagery, Ortho-Corrected, Historic 1958 black and white aerial photography for Wicomico County, Maryland. Imagery was scanned from historic hard copy images and georeferenced to current imagery. This data is available via map service., Published in 2010, 1:12000 (1in=1000ft) scale, Eastern Shore Regional GIS Cooperative.

    Data.gov (United States)

    NSGIC Regional | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2010. Historic 1958 black and white aerial photography for Wicomico County, Maryland. Imagery...

  18. An eigenfunction method for reconstruction of large-scale and high-contrast objects.

    Science.gov (United States)

    Waag, Robert C; Lin, Feng; Varslot, Trond K; Astheimer, Jeffrey P

    2007-07-01

    A multiple-frequency inverse scattering method that uses eigenfunctions of a scattering operator is extended to image large-scale and high-contrast objects. The extension uses an estimate of the scattering object to form the difference between the scattering by the object and the scattering by the estimate of the object. The scattering potential defined by this difference is expanded in a basis of products of acoustic fields. These fields are defined by eigenfunctions of the scattering operator associated with the estimate. In the case of scattering objects for which the estimate is radial, symmetries in the expressions used to reconstruct the scattering potential greatly reduce the amount of computation. The range of parameters over which the reconstruction method works well is illustrated using calculated scattering by different objects. The method is applied to experimental data from a 48-mm diameter scattering object with tissue-like properties. The image reconstructed from measurements has, relative to a conventional B-scan formed using a low f-number at the same center frequency, significantly higher resolution and less speckle, implying that small, high-contrast structures can be demonstrated clearly using the extended method.

  19. A large-scale multi-objective flights conflict avoidance approach supporting 4D trajectory operation

    OpenAIRE

    Guan, Xiangmin; Zhang, Xuejun; Lv, Renli; Chen, Jun; Weiszer, Michal

    2017-01-01

    Recently, the long-term conflict avoidance approaches based on large-scale flights scheduling have attracted much attention due to their ability to provide solutions from a global point of view. However, the current approaches which focus only on a single objective with the aim of minimizing the total delay and the number of conflicts, cannot provide the controllers with variety of optional solutions, representing different trade-offs. Furthermore, the flight track error is often overlooked i...

  20. Buoyancy limits on magnetic viscosity stress-law scalings in quasi stellar object accretion disk models

    International Nuclear Information System (INIS)

    Sakimoto, P.J.

    1985-01-01

    Quasi-Stellar Objects (QSOs) are apparently the excessively bright nuclei of distant galaxies. They are thought to be powered by accretion disks surrounding supermassive black holes: however, proof of this presumption is hampered by major uncertainties in the viscous stress necessary for accretion to occur. Models generally assume an and hoc stress law which scales the stress with the total pressure. Near the black hole, radiation pressure dominates gas pressure; scaling the stress with the radiation pressure results in disk models that are thermally unstable and optically thin. This dissertation shows that a radiation pressure scaling for the stress is not possible if the viscosity is due to turbulent magnetic Maxwell stresses. The argument is one of internal self-consistency. First, four model accretion disks that bound the reasonably expected ranges of viscous stress scalings and vertical structures are constructed. Magnetic flux tubes of various initial field strengths are then placed within these models, nd their buoyancy is modeled numerically. In disks using the radiation pressure stress law scaling, low opacities allow rapid heat flow into the flux tubes: the tubes are extremely buoyant, and magnetic fields strong enough to provide the required stress cannot be retained. If an alternative gas pressure scaling for the stress is assumed, then the disks are optically thick; flux tubes have corresponding lower buoyancy, and magnetic fields strong enough to provide the stress can be retained for dynamically significant time periods

  1. A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.

    Science.gov (United States)

    Budinich, Marko; Bourdon, Jérémie; Larhlimi, Abdelhalim; Eveillard, Damien

    2017-01-01

    Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs) for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA) and multi-objective flux variability analysis (MO-FVA). Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity) that take place at the ecosystem scale.

  2. A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.

    Directory of Open Access Journals (Sweden)

    Marko Budinich

    Full Text Available Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA and multi-objective flux variability analysis (MO-FVA. Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity that take place at the ecosystem scale.

  3. Comparison of Pixel-Based and Object-Based Classification Using Parameters and Non-Parameters Approach for the Pattern Consistency of Multi Scale Landcover

    Science.gov (United States)

    Juniati, E.; Arrofiqoh, E. N.

    2017-09-01

    Information extraction from remote sensing data especially land cover can be obtained by digital classification. In practical some people are more comfortable using visual interpretation to retrieve land cover information. However, it is highly influenced by subjectivity and knowledge of interpreter, also takes time in the process. Digital classification can be done in several ways, depend on the defined mapping approach and assumptions on data distribution. The study compared several classifiers method for some data type at the same location. The data used Landsat 8 satellite imagery, SPOT 6 and Orthophotos. In practical, the data used to produce land cover map in 1:50,000 map scale for Landsat, 1:25,000 map scale for SPOT and 1:5,000 map scale for Orthophotos, but using visual interpretation to retrieve information. Maximum likelihood Classifiers (MLC) which use pixel-based and parameters approach applied to such data, and also Artificial Neural Network classifiers which use pixel-based and non-parameters approach applied too. Moreover, this study applied object-based classifiers to the data. The classification system implemented is land cover classification on Indonesia topographic map. The classification applied to data source, which is expected to recognize the pattern and to assess consistency of the land cover map produced by each data. Furthermore, the study analyse benefits and limitations the use of methods.

  4. Critical object recognition in millimeter-wave images with robustness to rotation and scale.

    Science.gov (United States)

    Mohammadzade, Hoda; Ghojogh, Benyamin; Faezi, Sina; Shabany, Mahdi

    2017-06-01

    Locating critical objects is crucial in various security applications and industries. For example, in security applications, such as in airports, these objects might be hidden or covered under shields or secret sheaths. Millimeter-wave images can be utilized to discover and recognize the critical objects out of the hidden cases without any health risk due to their non-ionizing features. However, millimeter-wave images usually have waves in and around the detected objects, making object recognition difficult. Thus, regular image processing and classification methods cannot be used for these images and additional pre-processings and classification methods should be introduced. This paper proposes a novel pre-processing method for canceling rotation and scale using principal component analysis. In addition, a two-layer classification method is introduced and utilized for recognition. Moreover, a large dataset of millimeter-wave images is collected and created for experiments. Experimental results show that a typical classification method such as support vector machines can recognize 45.5% of a type of critical objects at 34.2% false alarm rate (FAR), which is a drastically poor recognition. The same method within the proposed recognition framework achieves 92.9% recognition rate at 0.43% FAR, which indicates a highly significant improvement. The significant contribution of this work is to introduce a new method for analyzing millimeter-wave images based on machine vision and learning approaches, which is not yet widely noted in the field of millimeter-wave image analysis.

  5. Estimating Sediment Delivery to The Rio Maranon, Peru Prior to Large-Scale Hydropower Developments Using High Resolution Imagery from Google Earth and a DJI Phantom 3 Drone

    Science.gov (United States)

    Goode, J. R.; Candelaria, T.; Kramer, N. R.; Hill, A. F.

    2016-12-01

    As global energy demands increase, generating hydroelectric power by constructing dams and reservoirs on large river systems is increasingly seen as a renewable alternative to fossil fuels, especially in emerging economies. Many large-scale hydropower projects are located in steep mountainous terrain, where environmental factors have the potential to conspire against the sustainability and success of such projects. As reservoir storage capacity decreases when sediment builds up behind dams, high sediment yields can limit project life expectancy and overall hydropower viability. In addition, episodically delivered sediment from landslides can make quantifying sediment loads difficult. These factors, combined with remote access, limit the critical data needed to effectively evaluate development decisions. In the summer of 2015, we conducted a basic survey to characterize the geomorphology, hydrology and ecology of 620 km of the Rio Maranon, Peru - a major tributary to the Amazon River, which flows north from the semi-arid Peruvian Andes - prior to its dissection by several large hydropower dams. Here we present one component of this larger study: a first order analysis of potential sediment inputs to the Rio Maranon, Peru. To evaluate sediment delivery and storage in this system, we used high resolution Google Earth imagery to delineate landslides, combined with high resolution imagery from a DJI Phantom 3 Drone, flown at alluvial fan inputs to the river in the field. Because hillslope-derived sediment inputs from headwater tributaries are important to overall ecosystem health in large river systems, our study has the potential to contribute to the understanding the impacts of large Andean dams on sediment connectivity to the Amazon basin.

  6. Characterizing, measuring, and utilizing the resolution of CT imagery for improved quantification of fine-scale features

    Energy Technology Data Exchange (ETDEWEB)

    Ketcham, Richard A., E-mail: ketcham@jsg.utexas.edu; Hildebrandt, Jordan

    2014-04-01

    Quantitative results extracted from computed tomographic (CT) data sets should be the same across resolutions and between different instruments and laboratory groups. Despite the proliferation of scanners and data processing methods and tools, and scientific studies utilizing them, relatively little emphasis has been given to ensuring that these results are comparable or reproducible. This issue is particularly pertinent when the features being imaged and measured are of the same order size as data voxels, as is often the case with fracture apertures, pore throats, and cell walls. We have created a tool that facilitates quantification of the spatial resolution of CT data via its point-spread function (PSF), in which the user draws a traverse across a sharp interface between two materials and a Gaussian PSF is fitted to the blurring across that interface. Geometric corrections account for voxel shape and the angle of the traverse to the interface, which does not need to be orthogonal. We use the tool to investigate a series of grid phantoms scanned at varying conditions and observe how the PSF varies within and between slices. The PSF increases with increasing radial distance within slices, and can increase tangentially with increasing radial distance in CT data sets acquired with relatively few projections. The PSF between CT slices is similar to that within slices when a 2-D detector is used, but is much sharper when the data are acquired one slice at a time with a collimated linear detector array. The capability described here can be used not only to calibrate processing algorithms that use deconvolution operations, but it can also help evaluate scans on a routine basis within and between CT research groups, and with respect to the features within the imagery that are being measured.

  7. Flexible feature-space-construction architecture and its VLSI implementation for multi-scale object detection

    Science.gov (United States)

    Luo, Aiwen; An, Fengwei; Zhang, Xiangyu; Chen, Lei; Huang, Zunkai; Jürgen Mattausch, Hans

    2018-04-01

    Feature extraction techniques are a cornerstone of object detection in computer-vision-based applications. The detection performance of vison-based detection systems is often degraded by, e.g., changes in the illumination intensity of the light source, foreground-background contrast variations or automatic gain control from the camera. In order to avoid such degradation effects, we present a block-based L1-norm-circuit architecture which is configurable for different image-cell sizes, cell-based feature descriptors and image resolutions according to customization parameters from the circuit input. The incorporated flexibility in both the image resolution and the cell size for multi-scale image pyramids leads to lower computational complexity and power consumption. Additionally, an object-detection prototype for performance evaluation in 65 nm CMOS implements the proposed L1-norm circuit together with a histogram of oriented gradients (HOG) descriptor and a support vector machine (SVM) classifier. The proposed parallel architecture with high hardware efficiency enables real-time processing, high detection robustness, small chip-core area as well as low power consumption for multi-scale object detection.

  8. Change Analysis and Decision Tree Based Detection Model for Residential Objects across Multiple Scales

    Directory of Open Access Journals (Sweden)

    CHEN Liyan

    2018-03-01

    Full Text Available Change analysis and detection plays important role in the updating of multi-scale databases.When overlap an updated larger-scale dataset and a to-be-updated smaller-scale dataset,people usually focus on temporal changes caused by the evolution of spatial entities.Little attention is paid to the representation changes influenced by map generalization.Using polygonal building data as an example,this study examines the changes from different perspectives,such as the reasons for their occurrence,their performance format.Based on this knowledge,we employ decision tree in field of machine learning to establish a change detection model.The aim of the proposed model is to distinguish temporal changes that need to be applied as updates to the smaller-scale dataset from representation changes.The proposed method is validated through tests using real-world building data from Guangzhou city.The experimental results show the overall precision of change detection is more than 90%,which indicates our method is effective to identify changed objects.

  9. Mapping and monitoring of sediment budgets and river change by means of UAS multi-scale, high-resolution imageries

    Science.gov (United States)

    Chang, Kuo-Jen; Tseng, Chih-Ming

    2017-04-01

    Due to the high seismicity and high annual rainfall, numerous landslides triggered every year and severe impacts affect the island Taiwan. Global warming and sea-level rise with increasing frequency and magnitude of storms and typhoons has resulted in an increase of natural hazards, and strong impacts on human life. A consequence of a change of the rainfall regime, increase of intensity and in a reduction of the duration of the events may have dramatic impacts. Heavy rainfall precipitations are one of the major triggering factors for landslides. Typhoon Morakot in 2009 brought extreme and long-time rainfall, and caused severe disasters. After 2009, numerous debris and sediment deposition increased greatly due to the severe landslides in upstream area. Detail morphological records may able to reveal the environment changes. This kind of analysis is based on the concept of DEM of difference (DoD) to evaluate the sediment budgets during climate and geo-hazard events. The aerial photographs generated digital surface models (DSMs) before and after Typhoon Morakot, and the subsequent multi-periods of imageries is thus been conducted in this study. In recent years, the remote sensing technology improves rapidly, providing a wide range of image, essential and precious information. In order quantify the hazards in different time; we try to integrate several technologies, especially by unmanned aircraft system (UAS), to decipher the consequence and the potential hazard, and the social impact. In order to monitoring the sediment budget of the study area, we integrates several methods, including, 1) Remote-sensing images gathered by UAS and by aerial photos taken in different periods; 2) field in-situ geologic investigation; 3) Differential GPS, RTK GPS in-site geomatic measurements; 4) Construct the DTMs before and after landslide, as well as the subsequent periods using UAS and aerial photos. We finally acquired 7 DEMs, prior to post-events, from 2009-2015. The precision of

  10. Spatio-Temporal Video Object Segmentation via Scale-Adaptive 3D Structure Tensor

    Directory of Open Access Journals (Sweden)

    Hai-Yun Wang

    2004-06-01

    Full Text Available To address multiple motions and deformable objects' motions encountered in existing region-based approaches, an automatic video object (VO segmentation methodology is proposed in this paper by exploiting the duality of image segmentation and motion estimation such that spatial and temporal information could assist each other to jointly yield much improved segmentation results. The key novelties of our method are (1 scale-adaptive tensor computation, (2 spatial-constrained motion mask generation without invoking dense motion-field computation, (3 rigidity analysis, (4 motion mask generation and selection, and (5 motion-constrained spatial region merging. Experimental results demonstrate that these novelties jointly contribute much more accurate VO segmentation both in spatial and temporal domains.

  11. Gravitational-wave signatures of exotic compact objects and of quantum corrections at the horizon scale

    CERN Document Server

    Cardoso, Vitor; Macedo, Caio F. B.; Palenzuela, Carlos; Pani, Paolo

    2016-01-01

    Gravitational waves from binary coalescences provide one of the cleanest signatures of the nature of compact objects. It has been recently argued that the post-merger ringdown waveform of exotic ultracompact objects is initially identical to that of a black-hole, and that putative corrections at the horizon scale will appear as secondary pulses after the main burst of radiation. Here we extend this analysis in three important directions: (i)~we show that this result applies to a large class of exotic compact objects with a photon sphere for generic orbits in the test-particle limit; (ii)~we investigate the late-time ringdown in more detail, showing that it is universally characterized by a modulated and distorted train of "echoes" of the modes of vibration associated with the photon sphere; (iii)~we study for the first time equal-mass, head-on collisions of two ultracompact boson stars and compare their gravitational-wave signal to that produced by a pair of black-holes. If the initial objects are compact eno...

  12. Data Quality Objectives For Selecting Waste Samples For Bench-Scale Reformer Treatability Studies

    International Nuclear Information System (INIS)

    Banning, D.L.

    2011-01-01

    This document describes the data quality objectives to select archived samples located at the 222-S Laboratory for Bench-Scale Reforming testing. The type, quantity, and quality of the data required to select the samples for Fluid Bed Steam Reformer testing are discussed. In order to maximize the efficiency and minimize the time to treat Hanford tank waste in the Waste Treatment and Immobilization Plant, additional treatment processes may be required. One of the potential treatment processes is the fluidized bed steam reformer. A determination of the adequacy of the fluidized bed steam reformer process to treat Hanford tank waste is required. The initial step in determining the adequacy of the fluidized bed steam reformer process is to select archived waste samples from the 222-S Laboratory that will be used in a bench scale tests. Analyses of the selected samples will be required to confirm the samples meet the shipping requirements and for comparison to the bench scale reformer (BSR) test sample selection requirements.

  13. Object-based random forest classification of Landsat ETM+ and WorldView-2 satellite imagery for mapping lowland native grassland communities in Tasmania, Australia

    Science.gov (United States)

    Melville, Bethany; Lucieer, Arko; Aryal, Jagannath

    2018-04-01

    This paper presents a random forest classification approach for identifying and mapping three types of lowland native grassland communities found in the Tasmanian Midlands region. Due to the high conservation priority assigned to these communities, there has been an increasing need to identify appropriate datasets that can be used to derive accurate and frequently updateable maps of community extent. Therefore, this paper proposes a method employing repeat classification and statistical significance testing as a means of identifying the most appropriate dataset for mapping these communities. Two datasets were acquired and analysed; a Landsat ETM+ scene, and a WorldView-2 scene, both from 2010. Training and validation data were randomly subset using a k-fold (k = 50) approach from a pre-existing field dataset. Poa labillardierei, Themeda triandra and lowland native grassland complex communities were identified in addition to dry woodland and agriculture. For each subset of randomly allocated points, a random forest model was trained based on each dataset, and then used to classify the corresponding imagery. Validation was performed using the reciprocal points from the independent subset that had not been used to train the model. Final training and classification accuracies were reported as per class means for each satellite dataset. Analysis of Variance (ANOVA) was undertaken to determine whether classification accuracy differed between the two datasets, as well as between classifications. Results showed mean class accuracies between 54% and 87%. Class accuracy only differed significantly between datasets for the dry woodland and Themeda grassland classes, with the WorldView-2 dataset showing higher mean classification accuracies. The results of this study indicate that remote sensing is a viable method for the identification of lowland native grassland communities in the Tasmanian Midlands, and that repeat classification and statistical significant testing can be

  14. GENASIS Mathematics : Object-oriented manifolds, operations, and solvers for large-scale physics simulations

    Science.gov (United States)

    Cardall, Christian Y.; Budiardja, Reuben D.

    2018-01-01

    The large-scale computer simulation of a system of physical fields governed by partial differential equations requires some means of approximating the mathematical limit of continuity. For example, conservation laws are often treated with a 'finite-volume' approach in which space is partitioned into a large number of small 'cells,' with fluxes through cell faces providing an intuitive discretization modeled on the mathematical definition of the divergence operator. Here we describe and make available Fortran 2003 classes furnishing extensible object-oriented implementations of simple meshes and the evolution of generic conserved currents thereon, along with individual 'unit test' programs and larger example problems demonstrating their use. These classes inaugurate the Mathematics division of our developing astrophysics simulation code GENASIS (Gen eral A strophysical Si mulation S ystem), which will be expanded over time to include additional meshing options, mathematical operations, solver types, and solver variations appropriate for many multiphysics applications.

  15. Real-time object tracking based on scale-invariant features employing bio-inspired hardware.

    Science.gov (United States)

    Yasukawa, Shinsuke; Okuno, Hirotsugu; Ishii, Kazuo; Yagi, Tetsuya

    2016-09-01

    We developed a vision sensor system that performs a scale-invariant feature transform (SIFT) in real time. To apply the SIFT algorithm efficiently, we focus on a two-fold process performed by the visual system: whole-image parallel filtering and frequency-band parallel processing. The vision sensor system comprises an active pixel sensor, a metal-oxide semiconductor (MOS)-based resistive network, a field-programmable gate array (FPGA), and a digital computer. We employed the MOS-based resistive network for instantaneous spatial filtering and a configurable filter size. The FPGA is used to pipeline process the frequency-band signals. The proposed system was evaluated by tracking the feature points detected on an object in a video. Copyright © 2016 Elsevier Ltd. All rights reserved.

  16. Digital holographic setups for phase object measurements in micro and macro scale

    Directory of Open Access Journals (Sweden)

    Lédl Vít

    2015-01-01

    Full Text Available The measurement of properties of so called phase objects is being solved for more than one Century starting probably with schlieren technique 1. Classical interferometry served as a great measurement tool for several decades and was replaced by holographic interferometry, which disposes with many benefits when compared to classical interferometry. Holographic interferometry undergone an enormous development in last decade when digital holography has been established as a standard technique and most of the drawbacks were solved. The paper deals with scope of the huge applicability of digital holographic interferometry in heat and mass transfer measurement from micro to macro scale and from simple 2D measurement up to complex tomographic techniques. Recently the very complex experimental setups are under development in our labs combining many techniques leading to digital holographic micro tomography methods.

  17. Everyday imagery

    DEFF Research Database (Denmark)

    Peters, Chris; Allan, Stuart

    2016-01-01

    the gradual disappearance of media from personal consciousness in a digital age. If ceaselessness is a defining characteristic of the current era, our analysis reveals that the use of smartphone cameras is indicative of people affectively and self-consciously deploying the technology to try to arrest......User-based research into the lived experiences associated with smartphone camera practices – in particular, the taking, storing, curating, and sharing of personal imagery in the digital media sphere – remains scarce, especially in contrast to their increasing ubiquity. Accordingly, this article...... social bonds, and encompass a future-oriented perspective. Relatedly, in terms of photographic composition, visual content tends to circulate around the social presence of others, boundedness of event, perceived aesthetic value, and intended shareability. Our findings question certain formulations about...

  18. Computational issues in complex water-energy optimization problems: Time scales, parameterizations, objectives and algorithms

    Science.gov (United States)

    Efstratiadis, Andreas; Tsoukalas, Ioannis; Kossieris, Panayiotis; Karavokiros, George; Christofides, Antonis; Siskos, Alexandros; Mamassis, Nikos; Koutsoyiannis, Demetris

    2015-04-01

    Modelling of large-scale hybrid renewable energy systems (HRES) is a challenging task, for which several open computational issues exist. HRES comprise typical components of hydrosystems (reservoirs, boreholes, conveyance networks, hydropower stations, pumps, water demand nodes, etc.), which are dynamically linked with renewables (e.g., wind turbines, solar parks) and energy demand nodes. In such systems, apart from the well-known shortcomings of water resources modelling (nonlinear dynamics, unknown future inflows, large number of variables and constraints, conflicting criteria, etc.), additional complexities and uncertainties arise due to the introduction of energy components and associated fluxes. A major difficulty is the need for coupling two different temporal scales, given that in hydrosystem modeling, monthly simulation steps are typically adopted, yet for a faithful representation of the energy balance (i.e. energy production vs. demand) a much finer resolution (e.g. hourly) is required. Another drawback is the increase of control variables, constraints and objectives, due to the simultaneous modelling of the two parallel fluxes (i.e. water and energy) and their interactions. Finally, since the driving hydrometeorological processes of the integrated system are inherently uncertain, it is often essential to use synthetically generated input time series of large length, in order to assess the system performance in terms of reliability and risk, with satisfactory accuracy. To address these issues, we propose an effective and efficient modeling framework, key objectives of which are: (a) the substantial reduction of control variables, through parsimonious yet consistent parameterizations; (b) the substantial decrease of computational burden of simulation, by linearizing the combined water and energy allocation problem of each individual time step, and solve each local sub-problem through very fast linear network programming algorithms, and (c) the substantial

  19. Segmentation and object-oriented classification of wetlands in a karst Florida landscape using multi-season Landsat-7 ETM+ Imagery

    Science.gov (United States)

    Segmentation and object-oriented processing of single-season and multi-season Landsat-7 ETM+ data was utilized for the classification of wetlands in a 1560 km2 study area of north central Florida. This segmentation and object-oriented classification outperformed the traditional ...

  20. Regional scale net radiation estimation by means of Landsat and TERRA/AQUA imagery and GIS modeling

    Science.gov (United States)

    Cristóbal, J.; Ninyerola, M.; Pons, X.; Llorens, P.; Poyatos, R.

    2009-04-01

    Net radiation (Rn) is one of the most important variables for the estimation of surface energy budget and is used for various applications including agricultural meteorology, climate monitoring and weather prediction. Moreover, net radiation is an essential input variable for potential as well as actual evapotranspiration modeling. Nowadays, radiometric measurements provided by Remote Sensing and GIS analysis are the technologies used to compute net radiation at regional scales in a feasible way. In this study we present a regional scale estimation of the daily Rn on clear days, (Catalonia, NE of the Iberian Peninsula), using a set of 22 Landsat images (17 Landsat-5 TM and 5 Landsat-7 ETM+) and 171 TERRA/AQUA images MODIS from 2000 to 2007 period. TERRA/AQUA MODIS images have been downloaded by means of the EOS Gateway. We have selected three different types of products which contain the remote sensing data we have used to model daily Rn: daily LST product, daily calibrated reflectances product and daily atmospheric water vapour product. Landsat-5 TM images have been corrected by means of conventional techniques based on first order polynomials taking into account the effect of land surface relief using a Digital Elevation Model, obtaining an RMS less than 30 m. Radiometric correction of Landsat non-thermal bands has been done following the methodology proposed by Pons and Solé (1994), which allows to reduce the number of undesired artifacts that are due to the effects of the atmosphere or to the differential illumination which is, in turn, due to the time of the day, the location in the Earth and the relief (zones being more illuminated than others, shadows, etc). Atmospheric correction of Landsat thermal band has been carried out by means of a single-channel algorithm improvement developed by Cristóbal et al. (2009) and the land surface emissivity computed by means of the methodology proposed by Sobrino and Raissouni (2000). Rn has been estimated through the

  1. Large-Scale Assessment of a Fully Automatic Co-Adaptive Motor Imagery-Based Brain Computer Interface.

    Directory of Open Access Journals (Sweden)

    Laura Acqualagna

    Full Text Available In the last years Brain Computer Interface (BCI technology has benefited from the development of sophisticated machine leaning methods that let the user operate the BCI after a few trials of calibration. One remarkable example is the recent development of co-adaptive techniques that proved to extend the use of BCIs also to people not able to achieve successful control with the standard BCI procedure. Especially for BCIs based on the modulation of the Sensorimotor Rhythm (SMR these improvements are essential, since a not negligible percentage of users is unable to operate SMR-BCIs efficiently. In this study we evaluated for the first time a fully automatic co-adaptive BCI system on a large scale. A pool of 168 participants naive to BCIs operated the co-adaptive SMR-BCI in one single session. Different psychological interventions were performed prior the BCI session in order to investigate how motor coordination training and relaxation could influence BCI performance. A neurophysiological indicator based on the Power Spectral Density (PSD was extracted by the recording of few minutes of resting state brain activity and tested as predictor of BCI performances. Results show that high accuracies in operating the BCI could be reached by the majority of the participants before the end of the session. BCI performances could be significantly predicted by the neurophysiological indicator, consolidating the validity of the model previously developed. Anyway, we still found about 22% of users with performance significantly lower than the threshold of efficient BCI control at the end of the session. Being the inter-subject variability still the major problem of BCI technology, we pointed out crucial issues for those who did not achieve sufficient control. Finally, we propose valid developments to move a step forward to the applicability of the promising co-adaptive methods.

  2. THE ORTHOPAEDIC REHABILITATION OF BALANCE: AN EXPERIMENTAL STUDY ON THE ROLE OF MENTAL IMAGERY AND EMOTIONAL VARIABLES.

    Directory of Open Access Journals (Sweden)

    Santo F. Di Nuovo

    2015-05-01

    Full Text Available Mental Imagery (i.e., processing of objects’ properties and spatial relations, including the ability of mentally rotating and manipulating objects in the space, is relevant for movement and its development, and particularly for rehabilitation of motor skills. Few studies aimed at assessing  the efficacy of imagery training used objective scores of Mental Imagery skills, preferring self-evaluations of these abilities reported by the subjects themselves. The aim of the paper was to explore the relevance of Mental Imagery, assessed by objective tests, in predicting the improvement of balance skills, after a standard rehabilitative training in orthopaedic settings; taking into account also emotional variables as anxiety and depression. A controlled study was conducted assessing the changes in balance skills after rehabilitative training. The sample was composed of 30 orthopaedic inpatients (females 66.7%, age range 47-91 years. To measure the dependent variable for pre-post assessment, B-scale from Performance-oriented mobility assessment test (POMA was used. Independent variables were measured using Mental Imagery Test, Mini-Mental State Examination, Hamilton Depression Rating Scale and Hamilton Anxiety Rating Scales. The best predictor of improvement in balance after rehabilitation is the Mental Imagery test, followed by age and mental efficiency. Anxiety predicts negatively the improvement, while education and depression appear to influence less the rehabilitation process. In conclusion, the study demonstrates that mental imagery is relevant in helping balance rehabilitation. A training of this function could be essential for clinical practice; the trainers should assess preliminarily the subject's attitude and ability to use mental imagery, with the aim of optimizing the rehabilitative process.

  3. A NEW FRAMEWORK FOR OBJECT-BASED IMAGE ANALYSIS BASED ON SEGMENTATION SCALE SPACE AND RANDOM FOREST CLASSIFIER

    Directory of Open Access Journals (Sweden)

    A. Hadavand

    2015-12-01

    Full Text Available In this paper a new object-based framework is developed for automate scale selection in image segmentation. The quality of image objects have an important impact on further analyses. Due to the strong dependency of segmentation results to the scale parameter, choosing the best value for this parameter, for each class, becomes a main challenge in object-based image analysis. We propose a new framework which employs pixel-based land cover map to estimate the initial scale dedicated to each class. These scales are used to build segmentation scale space (SSS, a hierarchy of image objects. Optimization of SSS, respect to NDVI and DSM values in each super object is used to get the best scale in local regions of image scene. Optimized SSS segmentations are finally classified to produce the final land cover map. Very high resolution aerial image and digital surface model provided by ISPRS 2D semantic labelling dataset is used in our experiments. The result of our proposed method is comparable to those of ESP tool, a well-known method to estimate the scale of segmentation, and marginally improved the overall accuracy of classification from 79% to 80%.

  4. Scalable multi-objective control for large scale water resources systems under uncertainty

    Science.gov (United States)

    Giuliani, Matteo; Quinn, Julianne; Herman, Jonathan; Castelletti, Andrea; Reed, Patrick

    2016-04-01

    The use of mathematical models to support the optimal management of environmental systems is rapidly expanding over the last years due to advances in scientific knowledge of the natural processes, efficiency of the optimization techniques, and availability of computational resources. However, undergoing changes in climate and society introduce additional challenges for controlling these systems, ultimately motivating the emergence of complex models to explore key causal relationships and dependencies on uncontrolled sources of variability. In this work, we contribute a novel implementation of the evolutionary multi-objective direct policy search (EMODPS) method for controlling environmental systems under uncertainty. The proposed approach combines direct policy search (DPS) with hierarchical parallelization of multi-objective evolutionary algorithms (MOEAs) and offers a threefold advantage: the DPS simulation-based optimization can be combined with any simulation model and does not add any constraint on modeled information, allowing the use of exogenous information in conditioning the decisions. Moreover, the combination of DPS and MOEAs prompts the generation or Pareto approximate set of solutions for up to 10 objectives, thus overcoming the decision biases produced by cognitive myopia, where narrow or restrictive definitions of optimality strongly limit the discovery of decision relevant alternatives. Finally, the use of large-scale MOEAs parallelization improves the ability of the designed solutions in handling the uncertainty due to severe natural variability. The proposed approach is demonstrated on a challenging water resources management problem represented by the optimal control of a network of four multipurpose water reservoirs in the Red River basin (Vietnam). As part of the medium-long term energy and food security national strategy, four large reservoirs have been constructed on the Red River tributaries, which are mainly operated for hydropower

  5. Mental imagery and the third dimension.

    Science.gov (United States)

    Pinker, S

    1980-09-01

    What sort of medium underlies imagery for three-dimensional scenes? In the present investigation, the time subjects took to scan between objects in a mental image was used to infer the sorts of geometric information that images preserve. Subjects studied an open box in which five objects were suspended, and learned to imagine this display with their eyes closed. In the first experiment, subjects scanned by tracking an imaginary point moving in a straight line between the imagined objects. Scanning times increased linearly with increasing distance between objects in three dimensions. Therefore metric 3-D information must be preserved in images, and images cannot simply be 2-D "snapshots." In a second experiment, subjects scanned across the image by "sighting" objects through an imaginary rifle sight. Here scanning times were found to increase linearly with the two-dimensional separations between objects as they appeared from the original viewing angle. Therefore metric 2-D distance information in the original perspective view must be preserved in images, and images cannot simply be 3-D "scale-models" that are assessed from any and all directions at once. In a third experiment, subjects mentally rotated the display 90 degrees and scanned between objects as they appeared in this new perspective view by tracking an imaginary rifle signt, as before. Scanning times increased linearly with the two-dimensional separations between objects as they would appear from the new relative viewing perspective. Therefore images can display metric 2-D distance information in a perspective view never actually experiences, so mental images cannot simply be "snapshot plus scale model" pairs. These results can be explained by a model in which the three-dimensional structure of objects is encoded in long-term memory in 3-D object-centered coordinate systems. When these objects are imagined, this information is then mapped onto a single 2-D "surface display" in which the perspective

  6. Synthetically chemical-electrical mechanism for controlling large scale reversible deformation of liquid metal objects

    Science.gov (United States)

    Zhang, Jie; Sheng, Lei; Liu, Jing

    2014-11-01

    Reversible deformation of a machine holds enormous promise across many scientific areas ranging from mechanical engineering to applied physics. So far, such capabilities are still hard to achieve through conventional rigid materials or depending mainly on elastomeric materials, which however own rather limited performances and require complicated manipulations. Here, we show a basic strategy which is fundamentally different from the existing ones to realize large scale reversible deformation through controlling the working materials via the synthetically chemical-electrical mechanism (SCHEME). Such activity incorporates an object of liquid metal gallium whose surface area could spread up to five times of its original size and vice versa under low energy consumption. Particularly, the alterable surface tension based on combination of chemical dissolution and electrochemical oxidation is ascribed to the reversible shape transformation, which works much more flexible than many former deformation principles through converting electrical energy into mechanical movement. A series of very unusual phenomena regarding the reversible configurational shifts are disclosed with dominant factors clarified. This study opens a generalized way to combine the liquid metal serving as shape-variable element with the SCHEME to compose functional soft machines, which implies huge potential for developing future smart robots to fulfill various complicated tasks.

  7. Infrared Imagery of Solid Rocket Exhaust Plumes

    Science.gov (United States)

    Moran, Robert P.; Houston, Janice D.

    2011-01-01

    The Ares I Scale Model Acoustic Test program consisted of a series of 18 solid rocket motor static firings, simulating the liftoff conditions of the Ares I five-segment Reusable Solid Rocket Motor Vehicle. Primary test objectives included acquiring acoustic and pressure data which will be used to validate analytical models for the prediction of Ares 1 liftoff acoustics and ignition overpressure environments. The test article consisted of a 5% scale Ares I vehicle and launch tower mounted on the Mobile Launch Pad. The testing also incorporated several Water Sound Suppression Systems. Infrared imagery was employed during the solid rocket testing to support the validation or improvement of analytical models, and identify corollaries between rocket plume size or shape and the accompanying measured level of noise suppression obtained by water sound suppression systems.

  8. High-z objects and cold dark matter cosmogonies - Constraints on the primordial power spectrum on small scales

    Science.gov (United States)

    Kashlinsky, A.

    1993-01-01

    Modified cold dark matter (CDM) models were recently suggested to account for large-scale optical data, which fix the power spectrum on large scales, and the COBE results, which would then fix the bias parameter, b. We point out that all such models have deficit of small-scale power where density fluctuations are presently nonlinear, and should then lead to late epochs of collapse of scales M between 10 exp 9 - 10 exp 10 solar masses and (1-5) x 10 exp 14 solar masses. We compute the probabilities and comoving space densities of various scale objects at high redshifts according to the CDM models and compare these with observations of high-z QSOs, high-z galaxies and the protocluster-size object found recently by Uson et al. (1992) at z = 3.4. We show that the modified CDM models are inconsistent with the observational data on these objects. We thus suggest that in order to account for the high-z objects, as well as the large-scale and COBE data, one needs a power spectrum with more power on small scales than CDM models allow and an open universe.

  9. Deep convolutional neural network training enrichment using multi-view object-based analysis of Unmanned Aerial systems imagery for wetlands classification

    Science.gov (United States)

    Liu, Tao; Abd-Elrahman, Amr

    2018-05-01

    Deep convolutional neural network (DCNN) requires massive training datasets to trigger its image classification power, while collecting training samples for remote sensing application is usually an expensive process. When DCNN is simply implemented with traditional object-based image analysis (OBIA) for classification of Unmanned Aerial systems (UAS) orthoimage, its power may be undermined if the number training samples is relatively small. This research aims to develop a novel OBIA classification approach that can take advantage of DCNN by enriching the training dataset automatically using multi-view data. Specifically, this study introduces a Multi-View Object-based classification using Deep convolutional neural network (MODe) method to process UAS images for land cover classification. MODe conducts the classification on multi-view UAS images instead of directly on the orthoimage, and gets the final results via a voting procedure. 10-fold cross validation results show the mean overall classification accuracy increasing substantially from 65.32%, when DCNN was applied on the orthoimage to 82.08% achieved when MODe was implemented. This study also compared the performances of the support vector machine (SVM) and random forest (RF) classifiers with DCNN under traditional OBIA and the proposed multi-view OBIA frameworks. The results indicate that the advantage of DCNN over traditional classifiers in terms of accuracy is more obvious when these classifiers were applied with the proposed multi-view OBIA framework than when these classifiers were applied within the traditional OBIA framework.

  10. Object-based Forest Fire Analysis for Pedrógão Grande Fire Using Landsat 8 OLI and Sentinel-2A Imagery

    Science.gov (United States)

    Tonbul, H.; Kavzoglu, T.

    2017-12-01

    Forest fires are among the most important natural disasters with the damage to the natural habitat and human-life. Mapping damaged forest fires is crucial for assessing ecological effects caused by fire, monitoring land cover changes and modeling atmospheric and climatic effects of fire. In this context, satellite data provides a great advantage to users by providing a rapid process of detecting burning areas and determining the severity of fire damage. Especially, Mediterranean ecosystems countries sets the suitable conditions for the forest fires. In this study, the determination of burnt areas of forest fire in Pedrógão Grande region of Portugal occurred in June 2017 was carried out using Landsat 8 OLI and Sentinel-2A satellite images. The Pedrógão Grande fire was one of the largest fires in Portugal, more than 60 people was killed and thousands of hectares were ravaged. In this study, four pairs of pre-fire and post-fire top of atmosphere (TOA) and atmospherically corrected images were utilized. The red and near infrared (NIR) spectral bands of pre-fire and post-fire images were stacked and multiresolution segmentation algorithm was applied. In the segmentation processes, the image objects were generated with estimated optimum homogeneity criteria. Using eCognition software, rule sets have been created to distinguish unburned areas from burned areas. In constructing the rule sets, NDVI threshold values were determined pre- and post-fire and areas where vegetation loss was detected using the NDVI difference image. The results showed that both satellite images yielded successful results for burned area discrimination with a very high degree of consistency in terms of spatial overlap and total burned area (over 93%). Object based image analysis (OBIA) was found highly effective in delineation of burnt areas.

  11. Distributed parallel cooperative coevolutionary multi-objective large-scale immune algorithm for deployment of wireless sensor networks

    DEFF Research Database (Denmark)

    Cao, Bin; Zhao, Jianwei; Yang, Po

    2018-01-01

    -objective evolutionary algorithms the Cooperative Coevolutionary Generalized Differential Evolution 3, the Cooperative Multi-objective Differential Evolution and the Nondominated Sorting Genetic Algorithm III, the proposed algorithm addresses the deployment optimization problem efficiently and effectively.......Using immune algorithms is generally a time-intensive process especially for problems with a large number of variables. In this paper, we propose a distributed parallel cooperative coevolutionary multi-objective large-scale immune algorithm that is implemented using the message passing interface...... (MPI). The proposed algorithm is composed of three layers: objective, group and individual layers. First, for each objective in the multi-objective problem to be addressed, a subpopulation is used for optimization, and an archive population is used to optimize all the objectives. Second, the large...

  12. NAIP 2015 Imagery Feedback

    Data.gov (United States)

    Farm Service Agency, Department of Agriculture — The NAIP 2015 Imagery Feedback web application allows users to make comments and observations about the quality of the 2015 National Agriculture Imagery Program...

  13. Landscape object-based analysis of wetland plant functional types: the effects of spatial scale, vegetation classes and classifier methods

    Science.gov (United States)

    Dronova, I.; Gong, P.; Wang, L.; Clinton, N.; Fu, W.; Qi, S.

    2011-12-01

    Remote sensing-based vegetation classifications representing plant function such as photosynthesis and productivity are challenging in wetlands with complex cover and difficult field access. Recent advances in object-based image analysis (OBIA) and machine-learning algorithms offer new classification tools; however, few comparisons of different algorithms and spatial scales have been discussed to date. We applied OBIA to delineate wetland plant functional types (PFTs) for Poyang Lake, the largest freshwater lake in China and Ramsar wetland conservation site, from 30-m Landsat TM scene at the peak of spring growing season. We targeted major PFTs (C3 grasses, C3 forbs and different types of C4 grasses and aquatic vegetation) that are both key players in system's biogeochemical cycles and critical providers of waterbird habitat. Classification results were compared among: a) several object segmentation scales (with average object sizes 900-9000 m2); b) several families of statistical classifiers (including Bayesian, Logistic, Neural Network, Decision Trees and Support Vector Machines) and c) two hierarchical levels of vegetation classification, a generalized 3-class set and more detailed 6-class set. We found that classification benefited from object-based approach which allowed including object shape, texture and context descriptors in classification. While a number of classifiers achieved high accuracy at the finest pixel-equivalent segmentation scale, the highest accuracies and best agreement among algorithms occurred at coarser object scales. No single classifier was consistently superior across all scales, although selected algorithms of Neural Network, Logistic and K-Nearest Neighbors families frequently provided the best discrimination of classes at different scales. The choice of vegetation categories also affected classification accuracy. The 6-class set allowed for higher individual class accuracies but lower overall accuracies than the 3-class set because

  14. The differential contributions of visual imagery constructs on autobiographical thinking.

    Science.gov (United States)

    Aydin, Cagla

    2018-02-01

    There is a growing theoretical and empirical consensus on the central role of visual imagery in autobiographical memory. However, findings from studies that explore how individual differences in visual imagery are reflected on autobiographical thinking do not present a coherent story. One reason for the mixed findings was suggested to be the treatment of visual imagery as an undifferentiated construct while evidence shows that there is more than one type of visual imagery. The present study investigates the relative contributions of different imagery constructs; namely, object and spatial imagery, on autobiographical memory processes. Additionally, it explores whether a similar relation extends to imagining the future. The results indicate that while object imagery was significantly correlated with several phenomenological characteristics, such as the level of sensory and perceptual details for past events - but not for future events - spatial imagery predicted the level of episodic specificity for both past and future events. We interpret these findings as object imagery being recruited in tasks of autobiographical memory that employ reflective processes while spatial imagery is engaged during direct retrieval of event details. Implications for the role of visual imagery in autobiographical thinking processes are discussed.

  15. Stereoscopy in cinematographic synthetic imagery

    Science.gov (United States)

    Eisenmann, Jonathan; Parent, Rick

    2009-02-01

    In this paper we present experiments and results pertaining to the perception of depth in stereoscopic viewing of synthetic imagery. In computer animation, typical synthetic imagery is highly textured and uses stylized illumination of abstracted material models by abstracted light source models. While there have been numerous studies concerning stereoscopic capabilities, conventions for staging and cinematography in stereoscopic movies have not yet been well-established. Our long-term goal is to measure the effectiveness of various cinematography techniques on the human visual system in a theatrical viewing environment. We would like to identify the elements of stereoscopic cinema that are important in terms of enhancing the viewer's understanding of a scene as well as providing guidelines for the cinematographer relating to storytelling. In these experiments we isolated stereoscopic effects by eliminating as many other visual cues as is reasonable. In particular, we aim to empirically determine what types of movement in synthetic imagery affect the perceptual depth sensing capabilities of our viewers. Using synthetic imagery, we created several viewing scenarios in which the viewer is asked to locate a target object's depth in a simple environment. The scenarios were specifically designed to compare the effectiveness of stereo viewing, camera movement, and object motion in aiding depth perception. Data were collected showing the error between the choice of the user and the actual depth value, and patterns were identified that relate the test variables to the viewer's perceptual depth accuracy in our theatrical viewing environment.

  16. Using object-based image analysis to conduct high-resolution conifer extraction at regional spatial scales

    Science.gov (United States)

    Coates, Peter S.; Gustafson, K. Benjamin; Roth, Cali L.; Chenaille, Michael P.; Ricca, Mark A.; Mauch, Kimberly; Sanchez-Chopitea, Erika; Kroger, Travis J.; Perry, William M.; Casazza, Michael L.

    2017-08-10

    imagery based on their spectral and spatial signatures. We classified conifers in 6,230 tiles and then tested for errors of omission and commission using confusion matrices. Accuracy ranged from 79.1 to 96.8, with an overall accuracy of 84.3 percent across all mapped areas. An estimated accuracy coefficient (kappa) indicated substantial to nearly perfect agreement, which varied across mapped areas. For this mapping process across the entire mapping extent, four sets of products are available at https://doi.org/10.5066/F7348HVC, including (1) a shapefile representing accuracy results linked to mapping subunits; (2) binary rasters representing conifer presence or absence at a 1 × 1 m resolution; (3) a 30 × 30 m resolution raster representing percentages of conifer canopy cover within each cell from 0 to 100; and (4) 1 × 1 m resolution canopy cover classification rasters derived from a 50-m-radius moving window analysis. The latter two products can be reclassified in a geographic information system (GIS) into user-specified bins to meet different objectives, which include approximations for phases of encroachment. These products complement, and in some cases improve upon, existing conifer maps in the Western United States, and will help facilitate sage-grouse habitat management and sagebrush ecosystem restoration.

  17. D Surface Generation from Aerial Thermal Imagery

    Science.gov (United States)

    Khodaei, B.; Samadzadegan, F.; Dadras Javan, F.; Hasani, H.

    2015-12-01

    Aerial thermal imagery has been recently applied to quantitative analysis of several scenes. For the mapping purpose based on aerial thermal imagery, high accuracy photogrammetric process is necessary. However, due to low geometric resolution and low contrast of thermal imaging sensors, there are some challenges in precise 3D measurement of objects. In this paper the potential of thermal video in 3D surface generation is evaluated. In the pre-processing step, thermal camera is geometrically calibrated using a calibration grid based on emissivity differences between the background and the targets. Then, Digital Surface Model (DSM) generation from thermal video imagery is performed in four steps. Initially, frames are extracted from video, then tie points are generated by Scale-Invariant Feature Transform (SIFT) algorithm. Bundle adjustment is then applied and the camera position and orientation parameters are determined. Finally, multi-resolution dense image matching algorithm is used to create 3D point cloud of the scene. Potential of the proposed method is evaluated based on thermal imaging cover an industrial area. The thermal camera has 640×480 Uncooled Focal Plane Array (UFPA) sensor, equipped with a 25 mm lens which mounted in the Unmanned Aerial Vehicle (UAV). The obtained results show the comparable accuracy of 3D model generated based on thermal images with respect to DSM generated from visible images, however thermal based DSM is somehow smoother with lower level of texture. Comparing the generated DSM with the 9 measured GCPs in the area shows the Root Mean Square Error (RMSE) value is smaller than 5 decimetres in both X and Y directions and 1.6 meters for the Z direction.

  18. Rendering Large-Scale Terrain Models and Positioning Objects in Relation to 3D Terrain

    National Research Council Canada - National Science Library

    Hittner, Brian

    2003-01-01

    .... Rendering large scale landscapes based on 3D geometry generally did not occur because the scenes generated tended to use up too much system memory and overburden 3D graphics cards with too many polygons...

  19. An Automated Scheme for the Large-Scale Survey of Herbig-Haro Objects

    Science.gov (United States)

    Deng, Licai; Yang, Ji; Zheng, Zhongyuan; Jiang, Zhaoji

    2001-04-01

    Owing to their spectral properties, Herbig-Haro (HH) objects can be discovered using photometric methods through a combination of filters, sampling the characteristic spectral lines and the nearby continuum. The data are commonly processed through direct visual inspection of the images. To make data reduction more efficient and the results more uniform and complete, an automated searching scheme for HH objects is developed to manipulate the images using IRAF. This approach helps to extract images with only intrinsic HH emissions. By using this scheme, the pointlike stellar sources and extended nebulous sources with continuum emission can be eliminated from the original images. The objects with only characteristic HH emission become prominent and can be easily picked up. In this paper our scheme is illustrated by a sample field and has been applied to our surveys for HH objects.

  20. Optimal unit sizing for small-scale integrated energy systems using multi-objective interval optimization and evidential reasoning approach

    International Nuclear Information System (INIS)

    Wei, F.; Wu, Q.H.; Jing, Z.X.; Chen, J.J.; Zhou, X.X.

    2016-01-01

    This paper proposes a comprehensive framework including a multi-objective interval optimization model and evidential reasoning (ER) approach to solve the unit sizing problem of small-scale integrated energy systems, with uncertain wind and solar energies integrated. In the multi-objective interval optimization model, interval variables are introduced to tackle the uncertainties of the optimization problem. Aiming at simultaneously considering the cost and risk of a business investment, the average and deviation of life cycle cost (LCC) of the integrated energy system are formulated. In order to solve the problem, a novel multi-objective optimization algorithm, MGSOACC (multi-objective group search optimizer with adaptive covariance matrix and chaotic search), is developed, employing adaptive covariance matrix to make the search strategy adaptive and applying chaotic search to maintain the diversity of group. Furthermore, ER approach is applied to deal with multiple interests of an investor at the business decision making stage and to determine the final unit sizing solution from the Pareto-optimal solutions. This paper reports on the simulation results obtained using a small-scale direct district heating system (DH) and a small-scale district heating and cooling system (DHC) optimized by the proposed framework. The results demonstrate the superiority of the multi-objective interval optimization model and ER approach in tackling the unit sizing problem of integrated energy systems considering the integration of uncertian wind and solar energies. - Highlights: • Cost and risk of investment in small-scale integrated energy systems are considered. • A multi-objective interval optimization model is presented. • A novel multi-objective optimization algorithm (MGSOACC) is proposed. • The evidential reasoning (ER) approach is used to obtain the final optimal solution. • The MGSOACC and ER can tackle the unit sizing problem efficiently.

  1. A Parameterized Pattern-Error Objective for Large-Scale Phase-Only Array Pattern Design

    Science.gov (United States)

    2016-03-21

    of 1D heuristic design approaches can be found in [6–11]. Reference [12], which proposes separate beams on interlaced subarrays, represents a 2D...and is well suited for solving with efficient quasi-Newton methods. Although deliberately simple, the objective has several heuristic parameters for...with efficient quasi-Newton methods. Although deliberately simple, the objective has several heuristic parameters for flexibility and can be used to

  2. Using MPAs to address regional-scale ecological objectives in the North Sea: modelling the effects of fishing effort displacement

    NARCIS (Netherlands)

    Greenstreet, S.P.R.; Fraser, H.M.; Piet, G.J.

    2009-01-01

    The use of Marine Protected Areas (MPAs) to address regional-scale objectives as part of an ecosystem approach to management in the North Sea is examined. Ensuring that displacement of fishing activity does not negate the ecological benefits gained from MPAs is a major concern. Two scenarios are

  3. Quantifying feedforward control: a linear scaling model for fingertip forces and object weight.

    Science.gov (United States)

    Lu, Ying; Bilaloglu, Seda; Aluru, Viswanath; Raghavan, Preeti

    2015-07-01

    The ability to predict the optimal fingertip forces according to object properties before the object is lifted is known as feedforward control, and it is thought to occur due to the formation of internal representations of the object's properties. The control of fingertip forces to objects of different weights has been studied extensively by using a custom-made grip device instrumented with force sensors. Feedforward control is measured by the rate of change of the vertical (load) force before the object is lifted. However, the precise relationship between the rate of change of load force and object weight and how it varies across healthy individuals in a population is not clearly understood. Using sets of 10 different weights, we have shown that there is a log-linear relationship between the fingertip load force rates and weight among neurologically intact individuals. We found that after one practice lift, as the weight increased, the peak load force rate (PLFR) increased by a fixed percentage, and this proportionality was common among the healthy subjects. However, at any given weight, the level of PLFR varied across individuals and was related to the efficiency of the muscles involved in lifting the object, in this case the wrist and finger extensor muscles. These results quantify feedforward control during grasp and lift among healthy individuals and provide new benchmarks to interpret data from neurologically impaired populations as well as a means to assess the effect of interventions on restoration of feedforward control and its relationship to muscular control. Copyright © 2015 the American Physiological Society.

  4. A high-level and scalable approach for generating scale-free graphs using active objects

    NARCIS (Netherlands)

    K. Azadbakht (Keyvan); N. Bezirgiannis (Nikolaos); F.S. de Boer (Frank); Aliakbary, S. (Sadegh)

    2016-01-01

    textabstractThe Barabasi-Albert model (BA) is designed to generate scale-free networks using the preferential attachment mechanism. In the preferential attachment (PA) model, new nodes are sequentially introduced to the network and they attach preferentially to existing nodes. PA is a classical

  5. Adaptive Variance Scaling in Continuous Multi-Objective Estimation-of-Distribution Algorithms

    NARCIS (Netherlands)

    P.A.N. Bosman (Peter); D. Thierens (Dirk); D. Thierens (Dirk)

    2007-01-01

    htmlabstractRecent research into single-objective continuous Estimation-of-Distribution Algorithms (EDAs) has shown that when maximum-likelihood estimations are used for parametric distributions such as the normal distribution, the EDA can easily suffer from premature convergence. In this paper we

  6. Aerial Photography and Imagery, Ortho-Corrected, This imagery was acquired through a Federal Grant with Pictometry International. The resolution is 6" in more densly populated areas and 1' in the other areas., Published in 2011, Not Applicable scale, Chippewa County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2011. This imagery was acquired through a Federal Grant with Pictometry International. The...

  7. Aerial Photography and Imagery, Ortho-Corrected, This dataset contains imagery of Prince George's County in RGB format. The primary goal was to acquire Countywide Digital Orthoimagery at 6" ground pixel resolution., Published in 2009, 1:1200 (1in=100ft) scale, Maryland National Capital Park and Planning Commission.

    Data.gov (United States)

    NSGIC Non-Profit | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2009. This dataset contains imagery of Prince George's County in RGB format. The primary goal...

  8. Aerial Photography and Imagery, Ortho-Corrected, We have new imagery from Pictometry's AccuPlus flown in March 2010 and to be delivered in October 2010., Published in 2010, 1:600 (1in=50ft) scale, Augusta-Richmond County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2010. We have new imagery from Pictometry's AccuPlus flown in March 2010 and to be delivered in...

  9. iLab 20M: A Large-scale Controlled Object Dataset to Investigate Deep Learning

    Science.gov (United States)

    2016-07-01

    models to be tolerant to identity - preserving image variations (e.g., variation in position, scale, pose, illumination, occlusion). To probe this, some...regular- izer and adopted it for CNNs. Another classic example is Siamese Networks [5] which are two identical copies of the same network, with the same...holds a camera (Microsoft LifeCam Cinema , 1280×720, YUYV) which can be placed and oriented at any location and pose reachable by the arm. A second arm

  10. Automatically Determining Scale Within Unstructured Point Clouds

    Science.gov (United States)

    Kadamen, Jayren; Sithole, George

    2016-06-01

    Three dimensional models obtained from imagery have an arbitrary scale and therefore have to be scaled. Automatically scaling these models requires the detection of objects in these models which can be computationally intensive. Real-time object detection may pose problems for applications such as indoor navigation. This investigation poses the idea that relational cues, specifically height ratios, within indoor environments may offer an easier means to obtain scales for models created using imagery. The investigation aimed to show two things, (a) that the size of objects, especially the height off ground is consistent within an environment, and (b) that based on this consistency, objects can be identified and their general size used to scale a model. To test the idea a hypothesis is first tested on a terrestrial lidar scan of an indoor environment. Later as a proof of concept the same test is applied to a model created using imagery. The most notable finding was that the detection of objects can be more readily done by studying the ratio between the dimensions of objects that have their dimensions defined by human physiology. For example the dimensions of desks and chairs are related to the height of an average person. In the test, the difference between generalised and actual dimensions of objects were assessed. A maximum difference of 3.96% (2.93cm) was observed from automated scaling. By analysing the ratio between the heights (distance from the floor) of the tops of objects in a room, identification was also achieved.

  11. Multicontroller: an object programming approach to introduce advanced control algorithms for the GCS large scale project

    CERN Document Server

    Cabaret, S; Coppier, H; Rachid, A; Barillère, R; CERN. Geneva. IT Department

    2007-01-01

    The GCS (Gas Control System) project team at CERN uses a Model Driven Approach with a Framework - UNICOS (UNified Industrial COntrol System) - based on PLC (Programming Language Controller) and SCADA (Supervisory Control And Data Acquisition) technologies. The first' UNICOS versions were able to provide a PID (Proportional Integrative Derivative) controller whereas the Gas Systems required more advanced control strategies. The MultiController is a new UNICOS object which provides the following advanced control algorithms: Smith Predictor, PFC (Predictive Function Control), RST* and GPC (Global Predictive Control). Its design is based on a monolithic entity with a global structure definition which is able to capture the desired set of parameters of any specific control algorithm supported by the object. The SCADA system -- PVSS - supervises the MultiController operation. The PVSS interface provides users with supervision faceplate, in particular it links any MultiController with recipes: the GCS experts are ab...

  12. Aerial Photography and Imagery, Ortho-Corrected - 2009 Digital Orthophotos - Bradford County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This metadata describes the digital ortho imagery covering Bradford County, FL. This 1"=200' scale imagery is comprised of natural color orthophotography with a GSD...

  13. Aerial Photography and Imagery, Ortho-Corrected - 2010 Digital Orthophotos - Union County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This metadata describes the digital ortho imagery covering Union County, FL. This 1"=200' scale imagery is comprised of natural color orthophotography with a GSD...

  14. Aerial Photography and Imagery, Ortho-Corrected - 2013 Digital Orthophotos - Calhoun County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This metadata describes the digital ortho imagery covering Calhoun and Gulf Counties, FL. This 1"=200' scale imagery is comprised of natural color orthoimagery with...

  15. Aerial Photography and Imagery, Ortho-Corrected - 2013 Digital Orthophotos - Liberty County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This metadata describes the digital ortho imagery covering Liberty County, FL. This 1"=200' scale imagery is comprised of 24 bit natural color orthophotography with...

  16. Aerial Photography and Imagery, Ortho-Corrected - 2010 Digital Orthophotos - Franklin County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This metadata describes the digital ortho imagery covering Franklin County, FL. This 1"=200' scale imagery is comprised of natural color orthophotography with a GSD...

  17. Applications of UAS-SfM for coastal vulnerability assessment: Geomorphic feature extraction and land cover classification from fine-scale elevation and imagery data

    Science.gov (United States)

    Sturdivant, E. J.; Lentz, E. E.; Thieler, E. R.; Remsen, D.; Miner, S.

    2016-12-01

    Characterizing the vulnerability of coastal systems to storm events, chronic change and sea-level rise can be improved with high-resolution data that capture timely snapshots of biogeomorphology. Imagery acquired with unmanned aerial systems (UAS) coupled with structure from motion (SfM) photogrammetry can produce high-resolution topographic and visual reflectance datasets that rival or exceed lidar and orthoimagery. Here we compare SfM-derived data to lidar and visual imagery for their utility in a) geomorphic feature extraction and b) land cover classification for coastal habitat assessment. At a beach and wetland site on Cape Cod, Massachusetts, we used UAS to capture photographs over a 15-hectare coastal area with a resulting pixel resolution of 2.5 cm. We used standard SfM processing in Agisoft PhotoScan to produce an elevation point cloud, an orthomosaic, and a digital elevation model (DEM). The SfM-derived products have a horizontal uncertainty of +/- 2.8 cm. Using the point cloud in an extraction routine developed for lidar data, we determined the position of shorelines, dune crests, and dune toes. We used the output imagery and DEM to map land cover with a pixel-based supervised classification. The dense and highly precise SfM point cloud enabled extraction of geomorphic features with greater detail than with lidar. The feature positions are reported with near-continuous coverage and sub-meter accuracy. The orthomosaic image produced with SfM provides visual reflectance with higher resolution than those available from aerial flight surveys, which enables visual identification of small features and thus aids the training and validation of the automated classification. We find that the high-resolution and correspondingly high density of UAS data requires some simple modifications to existing measurement techniques and processing workflows, and that the types of data and the quality provided is equivalent to, and in some cases surpasses, that of data

  18. Assessing Communication Skills of Medical Students in Objective Structured Clinical Examinations (OSCE)--A Systematic Review of Rating Scales.

    Science.gov (United States)

    Cömert, Musa; Zill, Jördis Maria; Christalle, Eva; Dirmaier, Jörg; Härter, Martin; Scholl, Isabelle

    2016-01-01

    Teaching and assessment of communication skills have become essential in medical education. The Objective Structured Clinical Examination (OSCE) has been found as an appropriate means to assess communication skills within medical education. Studies have demonstrated the importance of a valid assessment of medical students' communication skills. Yet, the validity of the performance scores depends fundamentally on the quality of the rating scales used in an OSCE. Thus, this systematic review aimed at providing an overview of existing rating scales, describing their underlying definition of communication skills, determining the methodological quality of psychometric studies and the quality of psychometric properties of the identified rating scales. We conducted a systematic review to identify psychometrically tested rating scales, which have been applied in OSCE settings to assess communication skills of medical students. Our search strategy comprised three databases (EMBASE, PsycINFO, and PubMed), reference tracking and consultation of experts. We included studies that reported psychometric properties of communication skills assessment rating scales used in OSCEs by examiners only. The methodological quality of included studies was assessed using the COnsensus based Standards for the selection of health status Measurement INstruments (COSMIN) checklist. The quality of psychometric properties was evaluated using the quality criteria of Terwee and colleagues. Data of twelve studies reporting on eight rating scales on communication skills assessment in OSCEs were included. Five of eight rating scales were explicitly developed based on a specific definition of communication skills. The methodological quality of studies was mainly poor. The psychometric quality of the eight rating scales was mainly intermediate. Our results reveal that future psychometric evaluation studies focusing on improving the methodological quality are needed in order to yield psychometrically

  19. Assessing Communication Skills of Medical Students in Objective Structured Clinical Examinations (OSCE) - A Systematic Review of Rating Scales

    Science.gov (United States)

    Cömert, Musa; Zill, Jördis Maria; Christalle, Eva; Dirmaier, Jörg; Härter, Martin; Scholl, Isabelle

    2016-01-01

    Background Teaching and assessment of communication skills have become essential in medical education. The Objective Structured Clinical Examination (OSCE) has been found as an appropriate means to assess communication skills within medical education. Studies have demonstrated the importance of a valid assessment of medical students’ communication skills. Yet, the validity of the performance scores depends fundamentally on the quality of the rating scales used in an OSCE. Thus, this systematic review aimed at providing an overview of existing rating scales, describing their underlying definition of communication skills, determining the methodological quality of psychometric studies and the quality of psychometric properties of the identified rating scales. Methods We conducted a systematic review to identify psychometrically tested rating scales, which have been applied in OSCE settings to assess communication skills of medical students. Our search strategy comprised three databases (EMBASE, PsycINFO, and PubMed), reference tracking and consultation of experts. We included studies that reported psychometric properties of communication skills assessment rating scales used in OSCEs by examiners only. The methodological quality of included studies was assessed using the COnsensus based Standards for the selection of health status Measurement INstruments (COSMIN) checklist. The quality of psychometric properties was evaluated using the quality criteria of Terwee and colleagues. Results Data of twelve studies reporting on eight rating scales on communication skills assessment in OSCEs were included. Five of eight rating scales were explicitly developed based on a specific definition of communication skills. The methodological quality of studies was mainly poor. The psychometric quality of the eight rating scales was mainly intermediate. Discussion Our results reveal that future psychometric evaluation studies focusing on improving the methodological quality are needed

  20. 2.5D change detection from satellite imagery to monitor small-scale mining activities in the Democratic Republic of the Congo

    Science.gov (United States)

    Kranz, Olaf; Lang, Stefan; Schoepfer, Elisabeth

    2017-09-01

    Mining natural resources serve fundamental societal needs or commercial interests, but it may well turn into a driver of violence and regional instability. In this study, very high resolution (VHR) optical stereo satellite data are analysed to monitor processes and changes in one of the largest artisanal and small-scale mining sites in the Democratic Republic of the Congo, which is among the world's wealthiest countries in exploitable minerals To identify the subtle structural changes, the applied methodological framework employs object-based change detection (OBCD) based on optical VHR data and generated digital surface models (DSM). Results prove the DSM-based change detection approach enhances the assessment gained from sole 2D analyses by providing valuable information about changes in surface structure or volume. Land cover changes as analysed by OBCD reveal an increase in bare soil area by a rate of 47% between April 2010 and September 2010, followed by a significant decrease of 47.5% until March 2015. Beyond that, DSM differencing enabled the characterisation of small-scale features such as pits and excavations. The presented Earth observation (EO)-based monitoring of mineral exploitation aims at a better understanding of the relations between resource extraction and conflict, and thus providing relevant information for potential mitigation strategies and peace building.

  1. Drive for Consumption, Craving, and Connectivity in the Visual Cortex during the Imagery of Desired Food

    Directory of Open Access Journals (Sweden)

    Jessica eBullins

    2013-11-01

    Full Text Available There is considerable interest in understanding food cravings given the obesogenic environment of Western Society. In this paper we examine how the imagery of palatable foods affects cravings and functional connectivity in the visual cortex for people who differ on the power of food scale (PFS. Fourteen older, overweight/obese adults came to our laboratory on two different occasions. Both times they ate a controlled breakfast meal and then were restricted from eating for 2.5 hours prior to scanning. On one day they consumed a BOOST® liquid meal after the period of food restriction, whereas on the other day they only consumed water (NO BOOST® condition. After these manipulations, they had an fMRI scan in which they were asked to image both neutral objects and their favorite snack foods; they also completed visual analogue scales for craving, hunger, and the vividness of the imagery experiences. Irrespective of the BOOST® manipulation, we observed marked increases in food cravings when older, overweight/obese adults created images of favorite foods in their minds as opposed to creating an image of neutral objects; however, the increase in food craving following the imagery of desired food was more pronounced among those scoring high than low on the PFS. Furthermore, local efficiency within the visual cortex when imaging desired food was higher for those scoring high as compared to low on the PFS. The active imagery of desired foods seemed to have overpowered the BOOST® manipulation when evaluating connectivity in the visual cortex.

  2. Radiography with cosmic-ray and compact accelerator muons; Exploring inner-structure of large-scale objects and landforms.

    Science.gov (United States)

    Nagamine, Kanetada

    2016-01-01

    Cosmic-ray muons (CRM) arriving from the sky on the surface of the earth are now known to be used as radiography purposes to explore the inner-structure of large-scale objects and landforms, ranging in thickness from meter to kilometers scale, such as volcanic mountains, blast furnaces, nuclear reactors etc. At the same time, by using muons produced by compact accelerators (CAM), advanced radiography can be realized for objects with a thickness in the sub-millimeter to meter range, with additional exploration capability such as element identification and bio-chemical analysis. In the present report, principles, methods and specific research examples of CRM transmission radiography are summarized after which, principles, methods and perspective views of the future CAM radiography are described.

  3. Multi-objective optimization and exergetic-sustainability of an irreversible nano scale Braysson cycle operating with Ma

    Directory of Open Access Journals (Sweden)

    Mohammad H. Ahmadi

    2016-06-01

    Full Text Available Nano technology is developed in this decade and changes the way of life. Moreover, developing nano technology has effect on the performance of the materials and consequently improves the efficiency and robustness of them. So, nano scale thermal cycles will be probably engaged in the near future. In this paper, a nano scale irreversible Braysson cycle is studied thermodynamically for optimizing the performance of the Braysson cycle. In the aforementioned cycle an ideal Maxwell–Boltzmann gas is used as a working fluid. Furthermore, three different plans are used for optimizing with multi-objectives; though, the outputs of the abovementioned plans are assessed autonomously. Throughout the first plan, with the purpose of maximizing the ecological coefficient of performance and energy efficiency of the system, multi-objective optimization algorithms are used. Furthermore, in the second plan, two objective functions containing the ecological coefficient of performance and the dimensionless Maximum available work are maximized synchronously by utilizing multi-objective optimization approach. Finally, throughout the third plan, three objective functions involving the dimensionless Maximum available work, the ecological coefficient of performance and energy efficiency of the system are maximized synchronously by utilizing multi-objective optimization approach. The multi-objective evolutionary approach based on the non-dominated sorting genetic algorithm approach is used in this research. Making a decision is performed by three different decision makers comprising linear programming approaches for multidimensional analysis of preference and an approach for order of preference by comparison with ideal answer and Bellman–Zadeh. Lastly, analysis of error is employed to determine deviation of the outcomes gained from each plan.

  4. Contrast and Strength of Visual Memory and Imagery Differentially Affect Visual Perception

    OpenAIRE

    Saad, Elyana; Silvanto, Juha

    2013-01-01

    Visual short-term memory (VSTM) and visual imagery have been shown to modulate visual perception. However, how the subjective experience of VSTM/imagery and its contrast modulate this process has not been investigated. We addressed this issue by asking participants to detect brief masked targets while they were engaged either in VSTM or visual imagery. Subjective experience of memory/imagery (strength scale), and the visual contrast of the memory/mental image (contrast scale) were assessed on...

  5. Landslide mapping with multi-scale object-based image analysis – a case study in the Baichi watershed, Taiwan

    Directory of Open Access Journals (Sweden)

    T. Lahousse

    2011-10-01

    Full Text Available We developed a multi-scale OBIA (object-based image analysis landslide detection technique to map shallow landslides in the Baichi watershed, Taiwan, after the 2004 Typhoon Aere event. Our semi-automated detection method selected multiple scales through landslide size statistics analysis for successive classification rounds. The detection performance achieved a modified success rate (MSR of 86.5% with the training dataset and 86% with the validation dataset. This performance level was due to the multi-scale aspect of our methodology, as the MSR for single scale classification was substantially lower, even after spectral difference segmentation, with a maximum of 74%. Our multi-scale technique was capable of detecting landslides of varying sizes, including very small landslides, up to 95 m2. The method presented certain limitations: the thresholds we established for classification were specific to the study area, to the landslide type in the study area, and to the spectral characteristics of the satellite image. Because updating site-specific and image-specific classification thresholds is easy with OBIA software, our multi-scale technique is expected to be useful for mapping shallow landslides at watershed level.

  6. Comparison of vocal tract discomfort scale results with objective and instrumental phoniatric parameters among teacher rehabilitees from voice disorders

    Directory of Open Access Journals (Sweden)

    Ewelina Woźnicka

    2013-04-01

    Full Text Available Background: Diagnostic and therapeutic procedures of occupational dysphonia play a major role in voice self-assessment, which is one of the elements of a comprehensive evaluation of voice disorders. The aim of the study was to assess the applicability of the Vocal Tract Discomfort (VTD scale to monitor the effectiveness of voice rehabilitation and compare the VTD results with objective and instrumental methods of phoniatric diagnosis. Materials and Methods: The study included 55 teachers (mean age, 47.2 with occupational dysphonia. A comprehensive diagnosis took into account self-assessment by VTD scale, phoniatric examination, including laryngovideostroboscopy (LVSS and objective measurements of the aerodynamic parameter - the maximum phonation time (MPT. After 4 months of intense rehabilitation, post-therapy examination was performed using the methods specified above. Results: After the treatment, a significant improvement was obtained in the subjective symptoms measured on a VTD scale - assessed both for the frequency (p = 0.000 and the severity (p = 0.000 subscales. Positive effects of the therapy were also observed for the parameters evaluated in the phoniatric study (p < 0.01 and laryngovideostroboscopy (p < 0.01. After voice therapy, there was also an improvement in the objective parameter MCF, which was about 5 seconds longer. Studies have shown that the VTD scale is characterized by high reliability - Cronbach's alpha coefficient in the preliminary test was as follows: for the frequency subscale symptoms - 0.826, and severity - 0.845; similarly high reliability was achieved in the control test, 0.908 and 0.923, respectively. Conclusions: Vocal Tract Discomfort scale can be a valuable tool for assessing voice, and can also be used to monitor the effectiveness of therapy of the occupational dysphonia. Med Pr 2013;64(2:199–206

  7. A fully convolutional network for weed mapping of unmanned aerial vehicle (UAV) imagery.

    Science.gov (United States)

    Huang, Huasheng; Deng, Jizhong; Lan, Yubin; Yang, Aqing; Deng, Xiaoling; Zhang, Lei

    2018-01-01

    Appropriate Site Specific Weed Management (SSWM) is crucial to ensure the crop yields. Within SSWM of large-scale area, remote sensing is a key technology to provide accurate weed distribution information. Compared with satellite and piloted aircraft remote sensing, unmanned aerial vehicle (UAV) is capable of capturing high spatial resolution imagery, which will provide more detailed information for weed mapping. The objective of this paper is to generate an accurate weed cover map based on UAV imagery. The UAV RGB imagery was collected in 2017 October over the rice field located in South China. The Fully Convolutional Network (FCN) method was proposed for weed mapping of the collected imagery. Transfer learning was used to improve generalization capability, and skip architecture was applied to increase the prediction accuracy. After that, the performance of FCN architecture was compared with Patch_based CNN algorithm and Pixel_based CNN method. Experimental results showed that our FCN method outperformed others, both in terms of accuracy and efficiency. The overall accuracy of the FCN approach was up to 0.935 and the accuracy for weed recognition was 0.883, which means that this algorithm is capable of generating accurate weed cover maps for the evaluated UAV imagery.

  8. Digging up your dirt. High school students combine small-scale respiration and soil carbon measurements with satellite imagery in hands-on inquiry activities.

    Science.gov (United States)

    Kemper, K.; Throop, H.

    2015-12-01

    One of the greatest impacts on the global carbon cycle is changes in land use. Making this concept relevant and inquiry-based for high school students is challenging. Many are familiar with reconstructing paleo-climate from ice core data, but few have a connection to current climate research. Many students ask questions like 'What will our area be like in 20 years?' or 'How much does planting trees help?' while few have the scientific language to engage in a discussion to answer these questions. Our work connects students to climate change research in several ways: first, teacher Keska Kemper engaged in field research with Dr. Heather Throop creating a 'teacher in the field' perspective for students in the classroom. Dr. Throop met with Keska Kemper's students several times to develop an inquiry-based field study. Students predicted and then measured rates of respiration between different soil types in an urban park close to their school. Students then could compare their results from Portland, Oregon to Throop's work across a rain gradient in Australia. Discussions about percent tree cover and soil carbon helped students see connections between land use changes and changes in carbon cycling. Last, students examined satellite imagery to determine percent tree cover and numberss of trees to compare to soil carbon in the same region. Students were able to examine imagery over the last 30 years to visualize land use changes in the greater Portland area.

  9. HackaMol: An Object-Oriented Modern Perl Library for Molecular Hacking on Multiple Scales.

    Science.gov (United States)

    Riccardi, Demian; Parks, Jerry M; Johs, Alexander; Smith, Jeremy C

    2015-04-27

    HackaMol is an open source, object-oriented toolkit written in Modern Perl that organizes atoms within molecules and provides chemically intuitive attributes and methods. The library consists of two components: HackaMol, the core that contains classes for storing and manipulating molecular information, and HackaMol::X, the extensions that use the core. The core is well-tested, well-documented, and easy to install across computational platforms. The goal of the extensions is to provide a more flexible space for researchers to develop and share new methods. In this application note, we provide a description of the core classes and two extensions: HackaMol::X::Calculator, an abstract calculator that uses code references to generalize interfaces with external programs, and HackaMol::X::Vina, a structured class that provides an interface with the AutoDock Vina docking program.

  10. Combining soft decision algorithms and scale-sequential hypotheses pruning for object recognition

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, V.P.; Manolakos, E.S. [Northeastern Univ., Boston, MA (United States)

    1996-12-31

    This paper describes a system that exploits the synergy of Hierarchical Mixture Density (HMD) estimation with multiresolution decomposition based hypothesis pruning to perform efficiently joint segmentation and labeling of partially occluded objects in images. First we present the overall structure of the HMD estimation algorithm in the form of a recurrent neural network which generates the posterior probabilities of the various hypotheses associated with the image. Then in order to reduce the large memory and computation requirement we propose a hypothesis pruning scheme making use of the orthonormal discrete wavelet transform for dimensionality reduction. We provide an intuitive justification for the validity of this scheme and present experimental results and performance analysis on real and synthetic images to verify our claims.

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

    Science.gov (United States)

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

    2011-01-01

    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.

  12. Coarse-coded higher-order neural networks for PSRI object recognition. [position, scale, and rotation invariant

    Science.gov (United States)

    Spirkovska, Lilly; Reid, Max B.

    1993-01-01

    A higher-order neural network (HONN) can be designed to be invariant to changes in scale, translation, and inplane rotation. Invariances are built directly into the architecture of a HONN and do not need to be learned. Consequently, fewer training passes and a smaller training set are required to learn to distinguish between objects. The size of the input field is limited, however, because of the memory required for the large number of interconnections in a fully connected HONN. By coarse coding the input image, the input field size can be increased to allow the larger input scenes required for practical object recognition problems. We describe a coarse coding technique and present simulation results illustrating its usefulness and its limitations. Our simulations show that a third-order neural network can be trained to distinguish between two objects in a 4096 x 4096 pixel input field independent of transformations in translation, in-plane rotation, and scale in less than ten passes through the training set. Furthermore, we empirically determine the limits of the coarse coding technique in the object recognition domain.

  13. An objective and parsimonious approach for classifying natural flow regimes at a continental scale

    Science.gov (United States)

    Archfield, S. A.; Kennen, J.; Carlisle, D.; Wolock, D.

    2013-12-01

    Hydroecological stream classification--the process of grouping streams by similar hydrologic responses and, thereby, similar aquatic habitat--has been widely accepted and is often one of the first steps towards developing ecological flow targets. Despite its importance, the last national classification of streamgauges was completed about 20 years ago. A new classification of 1,534 streamgauges in the contiguous United States is presented using a novel and parsimonious approach to understand similarity in ecological streamflow response. This new classification approach uses seven fundamental daily streamflow statistics (FDSS) rather than winnowing down an uncorrelated subset from 200 or more ecologically relevant streamflow statistics (ERSS) commonly used in hydroecological classification studies. The results of this investigation demonstrate that the distributions of 33 tested ERSS are consistently different among the classes derived from the seven FDSS. It is further shown that classification based solely on the 33 ERSS generally does a poorer job in grouping similar streamgauges than the classification based on the seven FDSS. This new classification approach has the additional advantages of overcoming some of the subjectivity associated with the selection of the classification variables and provides a set of robust continental-scale classes of US streamgauges.

  14. The deployment of a large scale object store at the RAL Tier-1

    Science.gov (United States)

    Dewhurst, A.; Johnson, I.; Adams, J.; Canning, B.; Vasilakakos, G.; Packer, A.

    2017-10-01

    Since 2014, the RAL Tier-1 has been working on deploying a Ceph backed object store. The aim is to replace Castor for disk-only storage. This new service must be scalable to meet the data demands of the LHC to 2020 and beyond. As well as offering access protocols the LHC experiments currently use, it must also provide industry standard access protocols. In order to keep costs down the service must use erasure coding rather than replication to ensure data reliability. This paper will present details of the storage service setup, which has been named Echo, as well as the experience gained from running it. The RAL Tier-1 has also been developing XrootD and GridFTP plugins for Ceph. Both plugins are built on top of the same libraries that write striped data into Ceph and therefore data written by one protocol will be accessible by the other. In the long term we hope the LHC experiments will migrate to industry standard protocols, therefore these plugins will only provide the features needed by the LHC experiments. This paper will report on the development and testing of these plugins.

  15. Verification of micro-scale photogrammetry for smooth three-dimensional object measurement

    Science.gov (United States)

    Sims-Waterhouse, Danny; Piano, Samanta; Leach, Richard

    2017-05-01

    By using sub-millimetre laser speckle pattern projection we show that photogrammetry systems are able to measure smooth three-dimensional objects with surface height deviations less than 1 μm. The projection of laser speckle patterns allows correspondences on the surface of smooth spheres to be found, and as a result, verification artefacts with low surface height deviations were measured. A combination of VDI/VDE and ISO standards were also utilised to provide a complete verification method, and determine the quality parameters for the system under test. Using the proposed method applied to a photogrammetry system, a 5 mm radius sphere was measured with an expanded uncertainty of 8.5 μm for sizing errors, and 16.6 μm for form errors with a 95 % confidence interval. Sphere spacing lengths between 6 mm and 10 mm were also measured by the photogrammetry system, and were found to have expanded uncertainties of around 20 μm with a 95 % confidence interval.

  16. Increase of Universality in Human Brain during Mental Imagery from Visual Perception

    OpenAIRE

    Bhattacharya, Joydeep

    2009-01-01

    BACKGROUND: Different complex systems behave in a similar way near their critical points of phase transitions which leads to an emergence of a universal scaling behaviour. Universality indirectly implies a long-range correlation between constituent subsystems. As the distributed correlated processing is a hallmark of higher complex cognition, I investigated a measure of universality in human brain during perception and mental imagery of complex real-life visual object like visual art. METHODO...

  17. An Autonomous Sensor Tasking Approach for Large Scale Space Object Cataloging

    Science.gov (United States)

    Linares, R.; Furfaro, R.

    The field of Space Situational Awareness (SSA) has progressed over the last few decades with new sensors coming online, the development of new approaches for making observations, and new algorithms for processing them. Although there has been success in the development of new approaches, a missing piece is the translation of SSA goals to sensors and resource allocation; otherwise known as the Sensor Management Problem (SMP). This work solves the SMP using an artificial intelligence approach called Deep Reinforcement Learning (DRL). Stable methods for training DRL approaches based on neural networks exist, but most of these approaches are not suitable for high dimensional systems. The Asynchronous Advantage Actor-Critic (A3C) method is a recently developed and effective approach for high dimensional systems, and this work leverages these results and applies this approach to decision making in SSA. The decision space for the SSA problems can be high dimensional, even for tasking of a single telescope. Since the number of SOs in space is relatively high, each sensor will have a large number of possible actions at a given time. Therefore, efficient DRL approaches are required when solving the SMP for SSA. This work develops a A3C based method for DRL applied to SSA sensor tasking. One of the key benefits of DRL approaches is the ability to handle high dimensional data. For example DRL methods have been applied to image processing for the autonomous car application. For example, a 256x256 RGB image has 196608 parameters (256*256*3=196608) which is very high dimensional, and deep learning approaches routinely take images like this as inputs. Therefore, when applied to the whole catalog the DRL approach offers the ability to solve this high dimensional problem. This work has the potential to, for the first time, solve the non-myopic sensor tasking problem for the whole SO catalog (over 22,000 objects) providing a truly revolutionary result.

  18. An Improved SIFT Algorithm for Unmanned Aerial Vehicle Imagery

    International Nuclear Information System (INIS)

    Li, J M; Yan, D M; Wang, G; Zhang, L

    2014-01-01

    The Unmanned Aerial Vehicle (UAV) platform has the benefits of low cost and convenience compared with satellites. Recently, UAVs have shown a wide range of applications such as land use change, mineral resources management and local topographic mapping. Because of the instability of the UAV air gesture, an image matching method is necessary to match different images of an object or scene. Scale Invariant Feature Transform (SIFT) features are invariant to image scaling, rotation and translation. However, the main drawback of a SIFT algorithm is its significant memory consumption and low computational speed, particularly in the case of high-resolution imagery. In this study, in order to overcome these drawbacks, we have analysed the construction of the scale-space in the SIFT algorithm and selected new parameters to construct the SIFT scale-space to improve the memory consumption and computational speed for the processing of UAV imagery. Here, we propose a restriction on the number of octaves and levels for Gaussian image pyramids. Our experiment shows that the proposed algorithm effectively reduces memory consumption and significantly improves the operational efficiency of the feature point extraction and matching under the premise of maintaining the precision of the extracted feature points

  19. The UNH Earth Systems Observatory: A Regional Application in Support of GEOSS Global-Scale Objectives

    Science.gov (United States)

    Vorosmarty, C. J.; Braswell, B.; Fekete, B.; Glidden, S.; Hartmann, H.; Magill, A.; Prusevich, A.; Wollheim, W.; Blaha, D.; Justice, D.; Hurtt, G.; Jacobs, J.; Ollinger, S.; McDowell, W.; Rock, B.; Rubin, F.; Schloss, A.

    2006-12-01

    The Northeast corridor of the US is emblematic of the many changes taking place across the nation's and indeed the world's watersheds. Because ecosystem and watershed change occurs over many scales and is so multifaceted, transferring scientific knowledge to applications as diverse as remediation of local ground water pollution, setting State-wide best practices for non-point source pollution control, enforcing regional carbon sequestration treaties, or creating public/private partnerships for protecting ecosystem services requires a new generation of integrative environmental surveillance systems, information technology, and information transfer to the user community. Geographically complex ecosystem interactions justify moving toward more integrative, regionally-based management strategies to deal with issues affecting land, inland waterways, and coastal waterways. A unified perspective that considers the full continuum of processes which link atmospheric forcings, terrestrial responses, watershed exports along drainage networks, and the final delivery to the coastal zone, nearshore, and off shore waters is required to adequately support the management challenge. A recent inventory of NOAA-supported environmental surveillance systems, IT resources, new sensor technologies, and management-relevant decision support systems shows the community poised to formulate an integrated and operational picture of the environment of New England. This paper presents the conceptual framework and early products of the newly-created UNH Earth Systems Observatory. The goal of the UNH Observatory is to serve as a regionally-focused yet nationally-prominent platform for observation-based, integrative science and management of the New England/Gulf of Maine's land, air, and ocean environmental systems. Development of the UNH Observatory is being guided by the principles set forth under the Global Earth Observation System of Systems and is cast as an end-to-end prototype for GEOSS

  20. Users, uses, and value of Landsat satellite imagery: results from the 2012 survey of users

    Science.gov (United States)

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

    2013-01-01

    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.

  1. The applied model of imagery use: Examination of moderation and mediation effects.

    Science.gov (United States)

    Koehn, S; Stavrou, N A M; Young, J A; Morris, T

    2016-08-01

    The applied model of mental imagery use proposed an interaction effect between imagery type and imagery ability. This study had two aims: (a) the examination of imagery ability as a moderating variable between imagery type and dispositional flow, and (b) the testing of alternative mediation models. The sample consisted of 367 athletes from Scotland and Australia, who completed the Sport Imagery Questionnaire, Sport Imagery Ability Questionnaire, and Dispositional Flow Scale-2. Hierarchical regression analysis showed direct effects of imagery use and imagery ability on flow, but no significant interaction. Mediation analysis revealed a significant indirect path, indicating a partially mediated relationship (P = 0.002) between imagery use, imagery ability, and flow. Partial mediation was confirmed when the effect of cognitive imagery use and cognitive imagery ability was tested, and a full mediation model was found between motivational imagery use, motivational imagery ability, and flow. The results are discussed in conjunction with potential future research directions on advancing theory and applications. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  2. [Comparison of vocal tract discomfort scale results with objective and instrumental phoniatric parameters among teacher rehabilitees from voice disorders].

    Science.gov (United States)

    Woźnicka, Ewelina; Niebudek-Bogusz, Ewa; Wiktorowicz, Justyna; Sliwińska-Kowalska, Mariola

    2013-01-01

    Diagnostic and therapeutic procedures of occupational dysphonia play a major role in voice self-assessment, which is one of the elements of a comprehensive evaluation of voice disorders. The aim of the study was to assess the applicability of the Vocal Tract Discomfort (VTD) scale to monitor the effectiveness of voice rehabilitation and compare the VTD results with objective and instrumental methods of phoniatric diagnosis. The study included 55 teachers (mean age, 47.2) with occupational dysphonia. A comprehensive diagnosis took into account self-assessment by VTD scale, phoniatric examination, including laryngovideostroboscopy (LVSS) and objective measurements of the aerodynamic parameter - the maximum phonation time (MPT). After 4 months of intense rehabilitation, post-therapy examination was performed using the methods specified above. After the treatment, a significant improvement was obtained in the subjective symptoms measured on a VTD scale - assessed both for the frequency (p = 0.000) and the severity (p = 0.000) subscales. Positive effects of the therapy were also observed for the parameters evaluated in the phoniatric study (p dysphonia.

  3. MM-MDS: a multidimensional scaling database with similarity ratings for 240 object categories from the Massive Memory picture database.

    Directory of Open Access Journals (Sweden)

    Michael C Hout

    Full Text Available Cognitive theories in visual attention and perception, categorization, and memory often critically rely on concepts of similarity among objects, and empirically require measures of "sameness" among their stimuli. For instance, a researcher may require similarity estimates among multiple exemplars of a target category in visual search, or targets and lures in recognition memory. Quantifying similarity, however, is challenging when everyday items are the desired stimulus set, particularly when researchers require several different pictures from the same category. In this article, we document a new multidimensional scaling database with similarity ratings for 240 categories, each containing color photographs of 16-17 exemplar objects. We collected similarity ratings using the spatial arrangement method. Reports include: the multidimensional scaling solutions for each category, up to five dimensions, stress and fit measures, coordinate locations for each stimulus, and two new classifications. For each picture, we categorized the item's prototypicality, indexed by its proximity to other items in the space. We also classified pairs of images along a continuum of similarity, by assessing the overall arrangement of each MDS space. These similarity ratings will be useful to any researcher that wishes to control the similarity of experimental stimuli according to an objective quantification of "sameness."

  4. MM-MDS: a multidimensional scaling database with similarity ratings for 240 object categories from the Massive Memory picture database.

    Science.gov (United States)

    Hout, Michael C; Goldinger, Stephen D; Brady, Kyle J

    2014-01-01

    Cognitive theories in visual attention and perception, categorization, and memory often critically rely on concepts of similarity among objects, and empirically require measures of "sameness" among their stimuli. For instance, a researcher may require similarity estimates among multiple exemplars of a target category in visual search, or targets and lures in recognition memory. Quantifying similarity, however, is challenging when everyday items are the desired stimulus set, particularly when researchers require several different pictures from the same category. In this article, we document a new multidimensional scaling database with similarity ratings for 240 categories, each containing color photographs of 16-17 exemplar objects. We collected similarity ratings using the spatial arrangement method. Reports include: the multidimensional scaling solutions for each category, up to five dimensions, stress and fit measures, coordinate locations for each stimulus, and two new classifications. For each picture, we categorized the item's prototypicality, indexed by its proximity to other items in the space. We also classified pairs of images along a continuum of similarity, by assessing the overall arrangement of each MDS space. These similarity ratings will be useful to any researcher that wishes to control the similarity of experimental stimuli according to an objective quantification of "sameness."

  5. Imagery Integration Team

    Science.gov (United States)

    Calhoun, Tracy; Melendrez, Dave

    2014-01-01

    The Human Exploration Science Office (KX) provides leadership for NASA's Imagery Integration (Integration 2) Team, an affiliation of experts in the use of engineering-class imagery intended to monitor the performance of launch vehicles and crewed spacecraft in flight. Typical engineering imagery assessments include studying and characterizing the liftoff and ascent debris environments; launch vehicle and propulsion element performance; in-flight activities; and entry, landing, and recovery operations. Integration 2 support has been provided not only for U.S. Government spaceflight (e.g., Space Shuttle, Ares I-X) but also for commercial launch providers, such as Space Exploration Technologies Corporation (SpaceX) and Orbital Sciences Corporation, servicing the International Space Station. The NASA Integration 2 Team is composed of imagery integration specialists from JSC, the Marshall Space Flight Center (MSFC), and the Kennedy Space Center (KSC), who have access to a vast pool of experience and capabilities related to program integration, deployment and management of imagery assets, imagery data management, and photogrammetric analysis. The Integration 2 team is currently providing integration services to commercial demonstration flights, Exploration Flight Test-1 (EFT-1), and the Space Launch System (SLS)-based Exploration Missions (EM)-1 and EM-2. EM-2 will be the first attempt to fly a piloted mission with the Orion spacecraft. The Integration 2 Team provides the customer (both commercial and Government) with access to a wide array of imagery options - ground-based, airborne, seaborne, or vehicle-based - that are available through the Government and commercial vendors. The team guides the customer in assembling the appropriate complement of imagery acquisition assets at the customer's facilities, minimizing costs associated with market research and the risk of purchasing inadequate assets. The NASA Integration 2 capability simplifies the process of securing one

  6. Estimating pinyon and juniper cover across Utah using NAIP imagery

    Directory of Open Access Journals (Sweden)

    Darrell B. Roundy

    2016-11-01

    Full Text Available Expansion of Pinus L. (pinyon and Juniperus L. (juniper (P-J trees into sagebrush (Artemisia L. steppe communities can lead to negative effects on hydrology, loss of wildlife habitat, and a decrease in desirable understory vegetation. Tree reduction treatments are often implemented to mitigate these negative effects. In order to prioritize and effectively plan these treatments, rapid, accurate, and inexpensive methods are needed to estimate tree canopy cover at the landscape scale. We used object based image analysis (OBIA software (Feature AnalystTM for ArcMap 10.1®, ENVI Feature Extraction®, and Trimble eCognition Developer 8.2® to extract tree canopy cover using NAIP (National Agricultural Imagery Program imagery. We then compared our extractions with ground measured tree canopy cover (crown diameter and line point intercept on 309 plots across 44 sites in Utah. Extraction methods did not consistently over- or under-estimate ground measured P-J canopy cover except where tree cover was >45%. Estimates of tree canopy cover using OBIA techniques were strongly correlated with estimates using the crown diameter method (r = 0.93 for ENVI, 0.91 for Feature AnalystTM, and 0.92 for eCognition. Tree cover estimates using OBIA techniques had lower correlations with tree cover measurements using the line-point intercept method (r = 0.85 for ENVI, 0.83 for Feature AnalystTM, and 0.83 for eCognition. All software packages accurately and inexpensively extracted P-J canopy cover from NAIP imagery when the imagery was not blurred, and when P-J cover was not mixed with Amelanchier alnifolia (Utah serviceberry and Quercus gambelii (Gambel’s oak, which had similar spectral values as P-J.

  7. Brain networks underlying mental imagery of auditory and visual information.

    Science.gov (United States)

    Zvyagintsev, Mikhail; Clemens, Benjamin; Chechko, Natalya; Mathiak, Krystyna A; Sack, Alexander T; Mathiak, Klaus

    2013-05-01

    Mental imagery is a complex cognitive process that resembles the experience of perceiving an object when this object is not physically present to the senses. It has been shown that, depending on the sensory nature of the object, mental imagery also involves correspondent sensory neural mechanisms. However, it remains unclear which areas of the brain subserve supramodal imagery processes that are independent of the object modality, and which brain areas are involved in modality-specific imagery processes. Here, we conducted a functional magnetic resonance imaging study to reveal supramodal and modality-specific networks of mental imagery for auditory and visual information. A common supramodal brain network independent of imagery modality, two separate modality-specific networks for imagery of auditory and visual information, and a common deactivation network were identified. The supramodal network included brain areas related to attention, memory retrieval, motor preparation and semantic processing, as well as areas considered to be part of the default-mode network and multisensory integration areas. The modality-specific networks comprised brain areas involved in processing of respective modality-specific sensory information. Interestingly, we found that imagery of auditory information led to a relative deactivation within the modality-specific areas for visual imagery, and vice versa. In addition, mental imagery of both auditory and visual information widely suppressed the activity of primary sensory and motor areas, for example deactivation network. These findings have important implications for understanding the mechanisms that are involved in generation of mental imagery. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  8. Portable devices for delivering imagery and modelling interventions ...

    African Journals Online (AJOL)

    The main objective of this study was to investigate the effectiveness of portable devices (MP4) and a stationary device (DVD and fixed point stationary computer) in delivering imagery and modelling training among female netball players, examining the effect on imagery adherence, performance, self-efficacy, and the relative ...

  9. Forward looking anomaly detection via fusion of infrared and color imagery

    Science.gov (United States)

    Stone, K.; Keller, J. M.; Popescu, M.; Havens, T. C.; Ho, K. C.

    2010-04-01

    This paper develops algorithms for the detection of interesting and abnormal objects in color and infrared imagery taken from cameras mounted on a moving vehicle, observing a fixed scene. The primary purpose of detection is to cue a human-in-the-loop detection system. Algorithms for direct detection and change detection are investigated, as well as fusion of the two. Both methods use temporal information to reduce the number of false alarms. The direct detection algorithm uses image self-similarity computed between local neighborhoods to determine interesting, or unique, parts of an image. Neighborhood similarity is computed using Euclidean distance in CIELAB color space for the color imagery, and Euclidean distance between grey levels in the infrared imagery. The change detection algorithm uses the affine scale-invariant feature transform (ASIFT) to transform multiple background frames into the current image space. Each transformed image is then compared to the current image, and the multiple outputs are fused to produce a single difference image. Changes in lighting and contrast between the background run and the current run are adjusted for in both color and infrared imagery. Frame-to-frame motion is modeled using a perspective transformation, the parameters of which are computed using scale-invariant feature transform (SIFT) keypoint correspondences. This information is used to perform temporal accumulation of single frame detections for both the direct detection and change detection algorithms. Performance of the proposed algorithms is evaluated on multiple lanes from a data collection at a US Army test site.

  10. The Achievement of Therapeutic Objectives Scale: Interrater Reliability and Sensitivity to Change in Short-Term Dynamic Psychotherapy and Cognitive Therapy

    Science.gov (United States)

    Valen, Jakob; Ryum, Truls; Svartberg, Martin; Stiles, Tore C.; McCullough, Leigh

    2011-01-01

    This study examined interrater reliability and sensitivity to change of the Achievement of Therapeutic Objectives Scale (ATOS; McCullough, Larsen, et al., 2003) in short-term dynamic psychotherapy (STDP) and cognitive therapy (CT). The ATOS is a process scale originally developed to assess patients' achievements of treatment objectives in STDP,…

  11. Mapping Spatial Distribution of Larch Plantations from Multi-Seasonal Landsat-8 OLI Imagery and Multi-Scale Textures Using Random Forests

    Directory of Open Access Journals (Sweden)

    Tian Gao

    2015-02-01

    Full Text Available The knowledge about spatial distribution of plantation forests is critical for forest management, monitoring programs and functional assessment. This study demonstrates the potential of multi-seasonal (spring, summer, autumn and winter Landsat-8 Operational Land Imager imageries with random forests (RF modeling to map larch plantations (LP in a typical plantation forest landscape in North China. The spectral bands and two types of textures were applied for creating 675 input variables of RF. An accuracy of 92.7% for LP, with a Kappa coefficient of 0.834, was attained using the RF model. A RF-based importance assessment reveals that the spectral bands and bivariate textural features calculated by pseudo-cross variogram (PC strongly promoted forest class-separability, whereas the univariate textural features influenced weakly. A feature selection strategy eliminated 93% of variables, and then a subset of the 47 most essential variables was generated. In this subset, PC texture derived from summer and winter appeared the most frequently, suggesting that this variability in growing peak season and non-growing season can effectively enhance forest class-separability. A RF classifier applied to the subset led to 91.9% accuracy for LP, with a Kappa coefficient of 0.829. This study provides an insight into approaches for discriminating plantation forests with phenological behaviors.

  12. Coastal California Digital Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This digital ortho-imagery dataset is a survey of coastal California. The project area consists of approximately 3774 square miles. The project design of the digital...

  13. NOAA Emergency Response Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The imagery posted on this site is in response to natural disasters. The aerial photography missions were conducted by the NOAA Remote Sensing Division. The majority...

  14. TEMPORAL VEGETATION DYNAMICS IN PEAT SWAMP AREA USING MODIS TIME-SERIES IMAGERY: A MONITORING APPROACH OF HIGH-SENSITIVE ECOSYSTEM IN REGIONAL SCALE

    Directory of Open Access Journals (Sweden)

    Yudi Setiawan

    2016-10-01

    Full Text Available Peat swamp area is an essential ecosystem due to high vulnerability of functions and services. As the change of forest cover in peat swamp area has increased considerably, many studies on peat swamp have focused on forest conversion or forest degradation. Meanwhile, in the context of changes in the forestlands are the sum of several processes such as deforestation, reforestation/afforestation, regeneration of previously deforested areas, and the changing spatial location of the forest boundary. Remote sensing technology seems to be a powerful tool to provide information required following that concerns. A comparison imagery taken at the different dates over the same locations for assessing those changes tends to be limited by the vegetation phenology and land-management practices. Consequently, the simultaneous analysis seems to be a way to deal with the issues above, as a means for better understanding of the dynamics changes in peat swamp area. In this study, we examined the feasibility of using MODIS images during the last 14 years for detecting and monitoring the changes in peat swamp area. We identified several significant patterns that have been assigned as the specific peat swamp ecosystem. The results indicate that a different type of ecosystem and its response to the environmental changes can be portrayed well by the significant patterns. In understanding the complex situations of each pattern, several vegetation dynamics patterns were characterized by physical land characteristics, such as peat depth, land use, concessions and others. Characterizing the pathways of dynamics change in peat swamp area will allow further identification for the range of proximate and underlying factors of the forest cover change that can help to develop useful policy interventions in peatland management.

  15. Analysis of Decadal-Scale Shoreline Change along the Hamlet of Paulatuk (Canadian Arctic), using Landsat Satellite Imagery and GIS techniques from 1984 to 2014.

    Science.gov (United States)

    Sankar, R. D.; Murray, M. S.; Wells, P.

    2016-12-01

    Increased accuracy in estimating coastal change along localized segments of the Canadian Arctic coast is essential, in order to identify plausible adaptation initiatives to deal with the effects of climate change. This paper quantifies rates of shoreline movement along an 11 km segment of the Hamlet of Paulatuk (Northwest Territories, Canada), using an innovative modelling technique - Analyzing Moving Boundaries Using R (AMBUR). Approximately two dozen shorelines, obtained from high-resolution Landsat satellite imagery were analyzed. Shorelines were extracted using the band ratio method and compiled in ArcMapTM to determine decadal trends of coastal change. The unique geometry of Paulatuk facilitated an independent analysis of the western and eastern sections of the study area. Long-term (1984-2014) and short-term (1984-2003) erosion and accretion rates were calculated using the Linear Regression and End Point Rate methods respectively. Results reveal an elevated rate of erosion for the western section of the hamlet over the long-term (-1.1 m/yr), compared to the eastern portion (-0.92 m/yr). The study indicates a significant alongshore increase in the rates of erosion on both portions of the study area, over the short-term period 1984 to 2003. Mean annual erosion rates increased over the short-term along the western segment (-1.4 m/yr), while the eastern shoreline retreated at a rate of -1.3 m/yr over the same period. The analysis indicates that an amalgamation of factors may be responsible for the patterns of land loss experienced along Paulatuk. These include increased sea-surface temperature coupled with dwindling arctic ice and elevated storm hydrodynamics. The analysis further reveals that the coastline along the eastern portion of the hamlet, where the majority of the population reside, is vulnerable to a high rate of shoreline erosion.

  16. USGS Imagery Only Base Map Service from The National Map

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — USGS Imagery Only is a tile cache base map of orthoimagery in The National Map visible to the 1:18,000 scale. Orthoimagery data are typically high resolution images...

  17. Massachusetts Bay - Internal wave packets digitized from SAR imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This feature class contains internal wave packets digitized from SAR imagery at 1:350,000 scale in Massachusetts Bay. Internal waves are nonsinusoidal waves that...

  18. Improved regional-scale Brazilian cropping systems' mapping based on a semi-automatic object-based clustering approach

    Science.gov (United States)

    Bellón, Beatriz; Bégué, Agnès; Lo Seen, Danny; Lebourgeois, Valentine; Evangelista, Balbino Antônio; Simões, Margareth; Demonte Ferraz, Rodrigo Peçanha

    2018-06-01

    Cropping systems' maps at fine scale over large areas provide key information for further agricultural production and environmental impact assessments, and thus represent a valuable tool for effective land-use planning. There is, therefore, a growing interest in mapping cropping systems in an operational manner over large areas, and remote sensing approaches based on vegetation index time series analysis have proven to be an efficient tool. However, supervised pixel-based approaches are commonly adopted, requiring resource consuming field campaigns to gather training data. In this paper, we present a new object-based unsupervised classification approach tested on an annual MODIS 16-day composite Normalized Difference Vegetation Index time series and a Landsat 8 mosaic of the State of Tocantins, Brazil, for the 2014-2015 growing season. Two variants of the approach are compared: an hyperclustering approach, and a landscape-clustering approach involving a previous stratification of the study area into landscape units on which the clustering is then performed. The main cropping systems of Tocantins, characterized by the crop types and cropping patterns, were efficiently mapped with the landscape-clustering approach. Results show that stratification prior to clustering significantly improves the classification accuracies for underrepresented and sparsely distributed cropping systems. This study illustrates the potential of unsupervised classification for large area cropping systems' mapping and contributes to the development of generic tools for supporting large-scale agricultural monitoring across regions.

  19. Design, experimental investigation and multi-objective optimization of a small-scale radial compressor for heat pump applications

    Energy Technology Data Exchange (ETDEWEB)

    Schiffmann, J. [Fischer Engineering Solutions AG, Birkenweg 3, CH-3360 Herzogenbuchsee (Switzerland); Favrat, D. [Ecole Polytechnique Federale de Lausanne, EPFL STI IGM LENI, Station 9, CH-1015 Lausanne (Switzerland)

    2010-01-15

    The main driver for small scale turbomachinery in domestic heat pumps is the potential for reaching higher efficiencies than volumetric compressors currently used and the potential for making the compressor oil-free, bearing a considerable advantage in the design of advanced multi-stage heat pump cycles. An appropriate turbocompressor for driving domestic heat pumps with a high temperature lift requires the ability to operate on a wide range of pressure ratios and mass flows, confronting the designer with the necessity of a compromise between range and efficiency. The present publication shows a possible way to deal with that difficulty, by coupling an appropriate modeling tool to a multi-objective optimizer. The optimizer manages to fit the compressor design into the possible specifications field while keeping the high efficiency on a wide operational range. The 1D-tool used for the compressor stage modeling has been validated by experimentally testing an initial impeller design. The excellent experimental results, the agreement with the model and the linking of the model to a multi-objective optimizer will allow to design radial compressor stages managing to fit the wide operational range of domestic heat pumps while keeping the high efficiency level. (author)

  20. OrthoImagery submittal for Allen County, Indiana

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Digital orthographic imagery datasets contain georeferenced images of the Earth?s surface, collected by a sensor in which object displacement has been removed for...

  1. OrthoImagery Submission for Moultrie County, Illinois, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Digital orthographic imagery datasets contain georeferenced images of the Earth's surface, collected by a sensor in which object displacement has beeen removed for...

  2. OrthoImagery submittal for Clinton County, Indiana

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Digital orthographic imagery datasets contain georeferenced images of the Earth?s surface, collected by a sensor in which object displacement has been removed for...

  3. OrthoImagery Submission for Christian County, Illinois, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Digital orthographic imagery datasets contain georeferenced images of the Earth's surface, collected by a sensor in which object displacement has beeen removed for...

  4. OrthoImagery Submission for Colfax County NE

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Digital orthographic imagery datasets contain georeferenced images of the surface of the Earth, collected by a sensor in which object displacement has been removed...

  5. OrthoImagery Submission for Monmouth County, New Jersey

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Digital orthographic imagery datasets contain georeferenced images of the Earth's surface, collected by a sensor in which object displacement has been removed for...

  6. OrthoImagery submittal for Scott County, Indiana

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Digital orthographic imagery datasets contain georeferenced images of the Earth's surface, collected by a sensor in which object displacement has been removed for...

  7. OrthoImagery submittal for Switzerland County, Indiana

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Digital orthographic imagery datasets contain georeferenced images of the Earth's surface, collected by a sensor in which object displacement has been removed for...

  8. OrthoImagery submittal for Gibson County, Indiana

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Digital orthographic imagery datasets contain georeferenced images of the Earth?s surface, collected by a sensor in which object displacement has been removed for...

  9. OrthoImagery Submission for Douglas County, Illinois, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Digital orthographic imagery datasets contain georeferenced images of the Earth's surface, collected by a sensor in which object displacement has beeen removed for...

  10. OrthoImagery Submission for Albany County, New York

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Digital orthographic imagery datasets contain georeferenced images of the Earth's surface, collected by a sensor in which object displacement has been removed for...

  11. OrthoImagery Submission for Putnam County, New York

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — Digital orthographic imagery datasets contain georeferenced images of the Earth's surface, collected by a sensor in which object displacement has been removed for...

  12. Large-Scale Laboratory Experiments of Initiation of Motion and Burial of Objects under Currents and Waves

    Science.gov (United States)

    Landry, B. J.; Wu, H.; Wenzel, S. P.; Gates, S. J.; Fytanidis, D. K.; Garcia, M. H.

    2017-12-01

    Unexploded ordnances (UXOs) can be found at the bottom of coastal areas as the residue of military wartime activities, training or accidents. These underwater objects are hazards for humans and the coastal environment increasing the need for addressing the knowledge gaps regarding the initiation of motion, fate and transport of UXOs under currents and wave conditions. Extensive experimental analysis was conducted for the initiation of motion of UXOs under various rigid bed roughness conditions (smooth PVC, pitted steel, marbles, gravels and bed of spherical particles) for both unidirectional and oscillatory flows. Particle image velocimetry measurements were conducted under both flow conditions to resolve the flow structure estimate the critical flow conditions for initiation of motion of UXOs. Analysis of the experimental observations shows that the geometrical characteristics of the UXOs, their properties (i.e. volume, mass) and their orientation with respect to the mean flow play an important role on the reorientation and mobility of the examined objects. A novel unified initiation of motion diagram is proposed using an effective/unified hydrodynamic roughness and a new length scale which includes the effect of the projected area and the bed-UXO contact area. Both unidirectional and oscillatory critical flow conditions collapsed into a single dimensionless diagram highlighting the importance and practical applicability of the proposed work. In addition to the rigid bed experiments, the burial dynamics of proud UXOs on a mobile sand bed were also examined. The complex flow-bedform-UXOs interactions were evaluated which highlighted the effect of munition density on burial rate and final burial depth. Burial dynamics and mechanisms for motion were examined for various UXOs types, and results show that, for the case of the low density UXOs under energetic conditions, lateral transport coexists with burial. Prior to burial, UXO re-orientation was also observed

  13. Acquisition of airborne imagery in support of Deepwater Horizon oil spill recovery assessments

    Science.gov (United States)

    Bostater, Charles R., Jr.; Muller-Karger, Frank E.

    2012-09-01

    Remote sensing imagery was collected from a low flying aircraft along the near coastal waters of the Florida Panhandle and northern Gulf of Mexico and into Barataria Bay, Louisiana, USA, during March 2011. Imagery was acquired from an aircraft that simultaneously collected traditional photogrammetric film imagery, digital video, digital still images, and digital hyperspectral imagery. The original purpose of the project was to collect airborne imagery to support assessment of weathered oil in littoral areas influenced by the Deepwater Horizon oil and gas spill that occurred during the spring and summer of 2010. This paper describes the data acquired and presents information that demonstrates the utility of small spatial scale imagery to detect the presence of weathered oil along littoral areas in the northern Gulf of Mexico. Flight tracks and examples of imagery collected are presented and methods used to plan and acquire the imagery are described. Results suggest weathered oil in littoral areas after the spill was contained at the source.

  14. Measuring Creative Imagery Abilities

    Directory of Open Access Journals (Sweden)

    Dorota M. Jankowska

    2015-10-01

    Full Text Available Over the decades, creativity and imagination research developed in parallel, but they surprisingly rarely intersected. This paper introduces a new theoretical model of creative imagination, which bridges creativity and imagination research, as well as presents a new psychometric instrument, called the Test of Creative Imagery Abilities (TCIA, developed to measure creative imagery abilities understood in accordance with this model. Creative imagination is understood as constituted by three interrelated components: vividness (the ability to create images characterized by a high level of complexity and detail, originality (the ability to produce unique imagery, and transformativeness (the ability to control imagery. TCIA enables valid and reliable measurement of these three groups of abilities, yielding the general score of imagery abilities and at the same time making profile analysis possible. We present the results of eight studies on a total sample of more than 1,700 participants, showing the factor structure of TCIA using confirmatory factor analysis, as well as provide data confirming this instrument’s validity and reliability. The availability of TCIA for interested researchers may result in new insights and possibilities of integrating the fields of creativity and imagination science.

  15. NAIP 2015 Imagery Feedback Map

    Data.gov (United States)

    Farm Service Agency, Department of Agriculture — The NAIP 2015 Imagery Feedback map allows users to make comments and observations about the quality of the 2015 National Agriculture Imagery Program (NAIP)...

  16. NAIP 2017 Imagery Feedback Map

    Data.gov (United States)

    Farm Service Agency, Department of Agriculture — The NAIP 2017 Imagery Feedback map allows users to make comments and observations about the quality of the 2017 National Agriculture Imagery Program (NAIP)...

  17. Gestures maintain spatial imagery.

    Science.gov (United States)

    Wesp, R; Hesse, J; Keutmann, D; Wheaton, K

    2001-01-01

    Recent theories suggest alternatives to the commonly held belief that the sole role of gestures is to communicate meaning directly to listeners. Evidence suggests that gestures may serve a cognitive function for speakers, possibly acting as lexical primes. We observed that participants gestured more often when describing a picture from memory than when the picture was present and that gestures were not influenced by manipulating eye contact of a listener. We argue that spatial imagery serves a short-term memory function during lexical search and that gestures may help maintain spatial images. When spatial imagery is not necessary, as in conditions of direct visual stimulation, reliance on gestures is reduced or eliminated.

  18. Rain Characteristics and Large-Scale Environments of Precipitation Objects with Extreme Rain Volumes from TRMM Observations

    Science.gov (United States)

    Zhou, Yaping; Lau, William K M.; Liu, Chuntao

    2013-01-01

    This study adopts a "precipitation object" approach by using 14 years of Tropical Rainfall Measuring Mission (TRMM) Precipitation Feature (PF) and National Centers for Environmental Prediction (NCEP) reanalysis data to study rainfall structure and environmental factors associated with extreme heavy rain events. Characteristics of instantaneous extreme volumetric PFs are examined and compared to those of intermediate and small systems. It is found that instantaneous PFs exhibit a much wider scale range compared to the daily gridded precipitation accumulation range. The top 1% of the rainiest PFs contribute over 55% of total rainfall and have 2 orders of rain volume magnitude greater than those of the median PFs. We find a threshold near the top 10% beyond which the PFs grow exponentially into larger, deeper, and colder rain systems. NCEP reanalyses show that midlevel relative humidity and total precipitable water increase steadily with increasingly larger PFs, along with a rapid increase of 500 hPa upward vertical velocity beyond the top 10%. This provides the necessary moisture convergence to amplify and sustain the extreme events. The rapid increase in vertical motion is associated with the release of convective available potential energy (CAPE) in mature systems, as is evident in the increase in CAPE of PFs up to 10% and the subsequent dropoff. The study illustrates distinct stages in the development of an extreme rainfall event including: (1) a systematic buildup in large-scale temperature and moisture, (2) a rapid change in rain structure, (3) explosive growth of the PF size, and (4) a release of CAPE before the demise of the event.

  19. Hypnagogic imagery and EEG activity.

    Science.gov (United States)

    Hayashi, M; Katoh, K; Hori, T

    1999-04-01

    The relationships between hypnagogic imagery and EEG activity were studied. 7 subjects (4 women and 3 men) reported the content of hypnagogic imagery every minute and the hypnagogic EEGs were classified into 5 stages according to Hori's modified criteria. The content of the hypnagogic imagery changed as a function of the hypnagogic EEG stages.

  20. Study on dynamic multi-objective approach considering coal and water conflict in large scale coal group

    Science.gov (United States)

    Feng, Qing; Lu, Li

    2018-01-01

    In the process of coal mining, destruction and pollution of groundwater in has reached an imminent time, and groundwater is not only related to the ecological environment, but also affect the health of human life. Similarly, coal and water conflict is still one of the world's problems in large scale coal mining regions. Based on this, this paper presents a dynamic multi-objective optimization model to deal with the conflict of the coal and water in the coal group with multiple subordinate collieries and arrive at a comprehensive arrangement to achieve environmentally friendly coal mining strategy. Through calculation, this paper draws the output of each subordinate coal mine. And on this basis, we continue to adjust the environmental protection parameters to compare the coal production at different collieries at different stages under different attitude of the government. At last, the paper conclude that, in either case, it is the first arrangement to give priority to the production of low-drainage, high-yield coal mines.

  1. Solar Imagery - Chromosphere - Calcium

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset consists of full-disk images of the sun in Calcium (Ca) II K wavelength (393.4 nm). Ca II K imagery reveal magnetic structures of the sun from about 500...

  2. Drive for consumption, craving, and connectivity in the visual cortex during the imagery of desired food.

    Science.gov (United States)

    Bullins, Jessica; Laurienti, Paul J; Morgan, Ashley R; Norris, James; Paolini, Brielle M; Rejeski, W Jack

    2013-01-01

    There is considerable interest in understanding food cravings given the obesogenic environment of Western Society. In this paper we examine how the imagery of palatable foods affects cravings and functional connectivity in the visual cortex for people who differ on the power of food scale (PFS). Fourteen older, overweight/obese adults came to our laboratory on two different occasions. Both times they ate a controlled breakfast meal and then were restricted from eating for 2.5 h prior to scanning. On 1 day they consumed a BOOST(®) liquid meal after the period of food restriction, whereas on the other day they only consumed water (NO BOOST(®) condition). After these manipulations, they had an fMRI scan in which they were asked to image both neutral objects and their favorite snack foods; they also completed visual analog scales for craving, hunger, and the vividness of the imagery experiences. Irrespective of the BOOST(®) manipulation, we observed marked increases in food cravings when older, overweight/obese adults created images of favorite foods in their minds as opposed to creating an image of neutral objects; however, the increase in food craving following the imagery of desired food was more pronounced among those scoring high than low on the PFS. Furthermore, local efficiency within the visual cortex when imaging desired food was higher for those scoring high as compared to low on the PFS. The active imagery of desired foods seemed to have overpowered the BOOST(®) manipulation when evaluating connectivity in the visual cortex.

  3. Aerial Photography and Imagery, Ortho-Corrected, Washington County, NC true color orthophotography - 1 foot resolution in the remainder of the county, Published in 2009, 1:4800 (1in=400ft) scale, Washington County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2009. Washington County, NC true color orthophotography - 1 foot resolution in the remainder of...

  4. Aerial Photography and Imagery, Ortho-Corrected, Washington County, NC true color orthophotography - 1/4 foot resolution over selected areas, Published in 2009, 1:1200 (1in=100ft) scale, Washington County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2009. Washington County, NC true color orthophotography - 1/4 foot resolution over selected...

  5. Aerial Photography and Imagery, Ortho-Corrected, Washington County, NC true color orhophotography - 1/2 foot resolution over selected areas, Published in 2009, 1:2400 (1in=200ft) scale, Washington County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2009. Washington County, NC true color orhophotography - 1/2 foot resolution over selected areas.

  6. Aerial Photography and Imagery, Ortho-Corrected, Washburn County had ortho/oblique photography flight done in April of 2009. Pictometry was contracted for the project., Published in 2009, 1:4800 (1in=400ft) scale, Washburn County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2009. Washburn County had ortho/oblique photography flight done in April of 2009. Pictometry...

  7. Aerial Photography and Imagery, Ortho-Corrected, Spring 2006 - natural color - countywide 12 inch pixel orthophotography - County of Polk, Wisconsin, Published in 2006, 1:2400 (1in=200ft) scale, Polk County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2006. Spring 2006 - natural color - countywide 12 inch pixel orthophotography - County of Polk,...

  8. Aerial Photography and Imagery, Ortho-Corrected, 4 inch aerial photography (color, infrared, and color oblique) in urban areas, 1 foot in national forest, Published in 2006, 1:600 (1in=50ft) scale, Los Angeles County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2006. 4 inch aerial photography (color, infrared, and color oblique) in urban areas, 1 foot in...

  9. Training visual imagery: Improvements of metacognition, but not imagery strength

    Directory of Open Access Journals (Sweden)

    Rosanne Lynn Rademaker

    2012-07-01

    Full Text Available Visual imagery has been closely linked to brain mechanisms involved in perception. Can visual imagery, like visual perception, improve by means of training? Previous research has demonstrated that people can reliably evaluate the vividness of single episodes of sensory imagination – might the metacognition of imagery also improve over the course of training? We had participants imagine colored Gabor patterns for an hour a day, over the course of five consecutive days, and again two weeks after training. Participants rated the subjective vividness and effort of their mental imagery on each trial. The influence of imagery on subsequent binocular rivalry dominance was taken as our measure of imagery strength. We found no overall effect of training on imagery strength. Training did, however, improve participant’s metacognition of imagery. Trial-by-trial ratings of vividness gained predictive power on subsequent rivalry dominance as a function of training. These data suggest that, while imagery strength might be immune to training in the current context, people’s metacognitive understanding of mental imagery can improve with practice.

  10. Guilt, Shame and Compassionate Imagery in War: Traumatized German Soldiers with PTSD, a Pilot Study

    Directory of Open Access Journals (Sweden)

    Christina Alliger-Horn

    2016-10-01

    Full Text Available Background: The consideration of specific trauma-associated emotions poses a challenge for the differential treatment planning in trauma therapy. Soldiers experiencing deployment-related posttraumatic stress disorder often struggle with emotions of guilt and shame as a central component of their PTSD. Objective: The purpose of this study was to examine the extent to which soldiers’ PTSD symptoms and their trauma-related guilt and shame may be affected as a function of their ability to develop compassionate imagery between their CURRENT SELF (today and their TRAUMATIZED SELF (back then. Method: The sample comprised 24 male German soldiers diagnosed with PTSD who were examined on the Posttraumatic Diagnostic Scale (PDS and two additional measures: the Emotional Distress Inventory (EIBE and the Quality of Interaction between the CURRENT SELF and the TRAUMATIZED SELF (QUI-HD: Qualität der Interaktion zwischen HEUTIGEN ICH und DAMALIGEN ICH at pre- and post-treatment and again at follow-up. The treatment used was imagery rescripting and reprocessing therapy (IRRT. Results: Eighteen of the 24 soldiers showed significant improvement in their PTSD symptoms at post-treatment and at follow-up (on their reliable change index. A significant change in trauma-associated guilt and shame emerged when compassionate imagery was developed towards one’s TRAUMATIZED SELF. The degree and intensity of the guilt and shame felt at the beginning of treatment and the degree of compassionate imagery developed toward the TRAUMATIZED SELF were predictors for change on the PDS scores. Conclusions: For soldiers suffering from specific war-related trauma involving PTSD, the use of self-nurturing, compassionate imagery that fosters reconciling with the traumatized part of the self can effectively diminish trauma-related symptoms, especially when guilt and shame are central emotions.

  11. Sea-Ice Feature Mapping using JERS-1 Imagery

    Science.gov (United States)

    Maslanik, James; Heinrichs, John

    1994-01-01

    JERS-1 SAR and OPS imagery are examined in combination with other data sets to investigate the utility of the JERS-1 sensors for mapping fine-scale sea ice conditions. Combining ERS-1 C band and JERS-1 L band SAR aids in discriminating multiyear and first-year ice. Analysis of OPS imagery for a field site in the Canadian Archipelago highlights the advantages of OPS's high spatial and spectral resolution for mapping ice structure, melt pond distribution, and surface albedo.

  12. Time scales of pattern evolution from cross-spectrum analysis of advanced very high resolution radiometer and coastal zone color scanner imagery

    Science.gov (United States)

    Denman, Kenneth L.; Abbott, Mark R.

    1994-01-01

    We have selected square subareas (110 km on a side) from coastal zone color scanner (CZCS) and advanced very high resolution radiometer (AVHRR) images for 1981 in the California Current region off northern California for which we could identify sequences of cloud-free data over periods of days to weeks. We applied a two-dimensional fast Fourier transformation to images after median filtering, (x, y) plane removal, and cosine tapering. We formed autospectra and coherence spectra as functions of a scalar wavenumber. Coherence estimates between pairs of images were plotted against time separation between images for several wide wavenumber bands to provide a temporal lagged coherence function. The temporal rate of loss of correlation (decorrelation time scale) in surface patterns provides a measure of the rate of pattern change or evolution as a function of spatial dimension. We found that patterns evolved (or lost correlation) approximately twice as rapidly in upwelling jets as in the 'quieter' regions between jets. The rapid evolution of pigment patterns (lifetime of about 1 week or less for scales of 50-100 km) ought to hinder biomass transfer to zooplankton predators compared with phytoplankton patches that persist for longer times. We found no significant differences between the statistics of CZCS and AVHRR images (spectral shape or rate of decorrelation). In addition, in two of the three areas studied, the peak correlation between AVHRR and CZCS images from the same area occurred at zero lag, indicating that the patterns evolved simutaneously. In the third area, maximum coherence between thermal and pigment patterns occurred when pigment images lagged thermal images by 1-2 days, mirroring the expected lag of high pigment behind low temperatures (and high nutrients) in recently upwelled water. We conclude that in dynamic areas such as coastal upwelling systems, the phytoplankton cells (identified by pigment color patterns) behave largely as passive scalars at the

  13. Automated analysis of autoradiographic imagery

    International Nuclear Information System (INIS)

    Bisignani, W.T.; Greenhouse, S.C.

    1975-01-01

    A research programme is described which has as its objective the automated characterization of neurological tissue regions from autoradiographs by utilizing hybrid-resolution image processing techniques. An experimental system is discussed which includes raw imagery, scanning an digitizing equipments, feature-extraction algorithms, and regional characterization techniques. The parameters extracted by these algorithms are presented as well as the regional characteristics which are obtained by operating on the parameters with statistical sampling techniques. An approach is presented for validating the techniques and initial experimental results are obtained from an anlysis of an autoradiograph of a region of the hypothalamus. An extension of these automated techniques to other biomedical research areas is discussed as well as the implications of applying automated techniques to biomedical research problems. (author)

  14. Up-scaling of multi-variable flood loss models from objects to land use units at the meso-scale

    Directory of Open Access Journals (Sweden)

    H. Kreibich

    2016-05-01

    Full Text Available Flood risk management increasingly relies on risk analyses, including loss modelling. Most of the flood loss models usually applied in standard practice have in common that complex damaging processes are described by simple approaches like stage-damage functions. Novel multi-variable models significantly improve loss estimation on the micro-scale and may also be advantageous for large-scale applications. However, more input parameters also reveal additional uncertainty, even more in upscaling procedures for meso-scale applications, where the parameters need to be estimated on a regional area-wide basis. To gain more knowledge about challenges associated with the up-scaling of multi-variable flood loss models the following approach is applied: Single- and multi-variable micro-scale flood loss models are up-scaled and applied on the meso-scale, namely on basis of ATKIS land-use units. Application and validation is undertaken in 19 municipalities, which were affected during the 2002 flood by the River Mulde in Saxony, Germany by comparison to official loss data provided by the Saxon Relief Bank (SAB.In the meso-scale case study based model validation, most multi-variable models show smaller errors than the uni-variable stage-damage functions. The results show the suitability of the up-scaling approach, and, in accordance with micro-scale validation studies, that multi-variable models are an improvement in flood loss modelling also on the meso-scale. However, uncertainties remain high, stressing the importance of uncertainty quantification. Thus, the development of probabilistic loss models, like BT-FLEMO used in this study, which inherently provide uncertainty information are the way forward.

  15. Up-scaling of multi-variable flood loss models from objects to land use units at the meso-scale

    Science.gov (United States)

    Kreibich, Heidi; Schröter, Kai; Merz, Bruno

    2016-05-01

    Flood risk management increasingly relies on risk analyses, including loss modelling. Most of the flood loss models usually applied in standard practice have in common that complex damaging processes are described by simple approaches like stage-damage functions. Novel multi-variable models significantly improve loss estimation on the micro-scale and may also be advantageous for large-scale applications. However, more input parameters also reveal additional uncertainty, even more in upscaling procedures for meso-scale applications, where the parameters need to be estimated on a regional area-wide basis. To gain more knowledge about challenges associated with the up-scaling of multi-variable flood loss models the following approach is applied: Single- and multi-variable micro-scale flood loss models are up-scaled and applied on the meso-scale, namely on basis of ATKIS land-use units. Application and validation is undertaken in 19 municipalities, which were affected during the 2002 flood by the River Mulde in Saxony, Germany by comparison to official loss data provided by the Saxon Relief Bank (SAB).In the meso-scale case study based model validation, most multi-variable models show smaller errors than the uni-variable stage-damage functions. The results show the suitability of the up-scaling approach, and, in accordance with micro-scale validation studies, that multi-variable models are an improvement in flood loss modelling also on the meso-scale. However, uncertainties remain high, stressing the importance of uncertainty quantification. Thus, the development of probabilistic loss models, like BT-FLEMO used in this study, which inherently provide uncertainty information are the way forward.

  16. Neural decoding of visual imagery during sleep.

    Science.gov (United States)

    Horikawa, T; Tamaki, M; Miyawaki, Y; Kamitani, Y

    2013-05-03

    Visual imagery during sleep has long been a topic of persistent speculation, but its private nature has hampered objective analysis. Here we present a neural decoding approach in which machine-learning models predict the contents of visual imagery during the sleep-onset period, given measured brain activity, by discovering links between human functional magnetic resonance imaging patterns and verbal reports with the assistance of lexical and image databases. Decoding models trained on stimulus-induced brain activity in visual cortical areas showed accurate classification, detection, and identification of contents. Our findings demonstrate that specific visual experience during sleep is represented by brain activity patterns shared by stimulus perception, providing a means to uncover subjective contents of dreaming using objective neural measurement.

  17. ASPECTS OF DEM GENERATION FROM UAS IMAGERY

    Directory of Open Access Journals (Sweden)

    A. Greiwe

    2013-08-01

    Full Text Available Since a few years, micro UAS (unmanned aerial systems with vertical take off and landing capabilities like quadro- or octocopter are used as sensor platform for Aerophotogrammetry. Since the restricted payload of micro UAS with a total weight up of 5 kg (payload only up to 1.5 kg, these systems are often equipped with small format cameras. These cameras can be classified as amateur cameras and it is often the case, that these systems do not meet the requirements of a geometric stable camera for photogrammetric measurement purposes. However, once equipped with a suitable camera system, an UAS is an interesting alternative to expensive manned flights for small areas. The operating flight height of the above described UAS is about 50 up to 150 meters above ground level. This low flight height lead on the one hand to a very high spatial resolution of the aerial imagery. Depending on the cameras focal length and the sensor's pixel size, the ground sampling distance (GSD is usually about 1 up to 5 cm. This high resolution is useful especially for the automatic generation of homologous tie-points, which are a precondition for the image alignment (bundle block adjustment. On the other hand, the image scale depends on the object's height and the UAV operating height. Objects like mine heaps or construction sites show high variations of the object's height. As a result, operating the UAS with a constant flying height will lead to high variations in the image scale. For some processing approaches this will lead to problems e.g. the automatic tie-point generation in stereo image pairs. As precondition to all DEM generating approaches, first of all a geometric stable camera, sharp images are essentially. Well known calibration parameters are necessary for the bundle adjustment, to control the exterior orientations. It can be shown, that a simultaneous on site camera calibration may lead to misaligned aerial images. Also, the success rate of an automatic tie

  18. Contrast and strength of visual memory and imagery differentially affect visual perception.

    Directory of Open Access Journals (Sweden)

    Elyana Saad

    Full Text Available Visual short-term memory (VSTM and visual imagery have been shown to modulate visual perception. However, how the subjective experience of VSTM/imagery and its contrast modulate this process has not been investigated. We addressed this issue by asking participants to detect brief masked targets while they were engaged either in VSTM or visual imagery. Subjective experience of memory/imagery (strength scale, and the visual contrast of the memory/mental image (contrast scale were assessed on a trial-by-trial basis. For both VSTM and imagery, contrast of the memory/mental image was positively associated with reporting target presence. Consequently, at the sensory level, both VSTM and imagery facilitated visual perception. However, subjective strength of VSTM was positively associated with visual detection whereas the opposite pattern was found for imagery. Thus the relationship between subjective strength of memory/imagery and visual detection are qualitatively different for VSTM and visual imagery, although their impact at the sensory level appears similar. Our results furthermore demonstrate that imagery and VSTM are partly dissociable processes.

  19. Contrast and strength of visual memory and imagery differentially affect visual perception.

    Science.gov (United States)

    Saad, Elyana; Silvanto, Juha

    2013-01-01

    Visual short-term memory (VSTM) and visual imagery have been shown to modulate visual perception. However, how the subjective experience of VSTM/imagery and its contrast modulate this process has not been investigated. We addressed this issue by asking participants to detect brief masked targets while they were engaged either in VSTM or visual imagery. Subjective experience of memory/imagery (strength scale), and the visual contrast of the memory/mental image (contrast scale) were assessed on a trial-by-trial basis. For both VSTM and imagery, contrast of the memory/mental image was positively associated with reporting target presence. Consequently, at the sensory level, both VSTM and imagery facilitated visual perception. However, subjective strength of VSTM was positively associated with visual detection whereas the opposite pattern was found for imagery. Thus the relationship between subjective strength of memory/imagery and visual detection are qualitatively different for VSTM and visual imagery, although their impact at the sensory level appears similar. Our results furthermore demonstrate that imagery and VSTM are partly dissociable processes.

  20. Kinesthetic imagery of musical performance.

    Science.gov (United States)

    Lotze, Martin

    2013-01-01

    Musicians use different kinds of imagery. This review focuses on kinesthetic imagery, which has been shown to be an effective complement to actively playing an instrument. However, experience in actual movement performance seems to be a requirement for a recruitment of those brain areas representing movement ideation during imagery. An internal model of movement performance might be more differentiated when training has been more intense or simply performed more often. Therefore, with respect to kinesthetic imagery, these strategies are predominantly found in professional musicians. There are a few possible reasons as to why kinesthetic imagery is used in addition to active training; one example is the need for mental rehearsal of the technically most difficult passages. Another reason for mental practice is that mental rehearsal of the piece helps to improve performance if the instrument is not available for actual training as is the case for professional musicians when they are traveling to various appearances. Overall, mental imagery in musicians is not necessarily specific to motor, somatosensory, auditory, or visual aspects of imagery, but integrates them all. In particular, the audiomotor loop is highly important, since auditory aspects are crucial for guiding motor performance. All these aspects result in a distinctive representation map for the mental imagery of musical performance. This review summarizes behavioral data, and findings from functional brain imaging studies of mental imagery of musical performance.

  1. Imagery encoding and false recognition errors: Examining the role of imagery process and imagery content on source misattributions.

    Science.gov (United States)

    Foley, Mary Ann; Foy, Jeffrey; Schlemmer, Emily; Belser-Ehrlich, Janna

    2010-11-01

    Imagery encoding effects on source-monitoring errors were explored using the Deese-Roediger-McDermott paradigm in two experiments. While viewing thematically related lists embedded in mixed picture/word presentations, participants were asked to generate images of objects or words (Experiment 1) or to simply name the items (Experiment 2). An encoding task intended to induce spontaneous images served as a control for the explicit imagery instruction conditions (Experiment 1). On the picture/word source-monitoring tests, participants were much more likely to report "seeing" a picture of an item presented as a word than the converse particularly when images were induced spontaneously. However, this picture misattribution error was reversed after generating images of words (Experiment 1) and was eliminated after simply labelling the items (Experiment 2). Thus source misattributions were sensitive to the processes giving rise to imagery experiences (spontaneous vs deliberate), the kinds of images generated (object vs word images), and the ways in which materials were presented (as pictures vs words).

  2. Automated Generation of the Alaska Coastline Using High-Resolution Satellite Imagery

    Science.gov (United States)

    Roth, G.; Porter, C. C.; Cloutier, M. D.; Clementz, M. E.; Reim, C.; Morin, P. J.

    2015-12-01

    Previous campaigns to map Alaska's coast at high resolution have relied on airborne, marine, or ground-based surveying and manual digitization. The coarse temporal resolution, inability to scale geographically, and high cost of field data acquisition in these campaigns is inadequate for the scale and speed of recent coastal change in Alaska. Here, we leverage the Polar Geospatial Center (PGC) archive of DigitalGlobe, Inc. satellite imagery to produce a state-wide coastline at 2 meter resolution. We first select multispectral imagery based on time and quality criteria. We then extract the near-infrared (NIR) band from each processed image, and classify each pixel as water or land with a pre-determined NIR threshold value. Processing continues with vectorizing the water-land boundary, removing extraneous data, and attaching metadata. Final coastline raster and vector products maintain the original accuracy of the orthorectified satellite data, which is often within the local tidal range. The repeat frequency of coastline production can range from 1 month to 3 years, depending on factors such as satellite capacity, cloud cover, and floating ice. Shadows from trees or structures complicate the output and merit further data cleaning. The PGC's imagery archive, unique expertise, and computing resources enabled us to map the Alaskan coastline in a few months. The DigitalGlobe archive allows us to update this coastline as new imagery is acquired, and facilitates baseline data for studies of coastal change and improvement of topographic datasets. Our results are not simply a one-time coastline, but rather a system for producing multi-temporal, automated coastlines. Workflows and tools produced with this project can be freely distributed and utilized globally. Researchers and government agencies must now consider how they can incorporate and quality-control this high-frequency, high-resolution data to meet their mapping standards and research objectives.

  3. Non-Drug Pain Relief: Imagery

    Science.gov (United States)

    PATIENT EDUCATION patienteducation.osumc.edu Non-Drug Pain Relief: Imagery Relaxation helps lessen tension. One way to help decrease pain is to use imagery. Imagery is using your imagination to create a ...

  4. Benchmark Imagery FY11 Technical Report

    Energy Technology Data Exchange (ETDEWEB)

    Roberts, R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Pope, P. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2011-06-14

    This report details the work performed in FY11 under project LL11-GS-PD06, “Benchmark Imagery for Assessing Geospatial Semantic Extraction Algorithms.” The original LCP for the Benchmark Imagery project called for creating a set of benchmark imagery for verifying and validating algorithms that extract semantic content from imagery. More specifically, the first year was slated to deliver real imagery that had been annotated, the second year to deliver real imagery that had composited features, and the final year was to deliver synthetic imagery modeled after the real imagery.

  5. Imagery Rescripting for Personality Disorders

    Science.gov (United States)

    Arntz, Arnoud

    2011-01-01

    Imagery rescripting is a powerful technique that can be successfully applied in the treatment of personality disorders. For personality disorders, imagery rescripting is not used to address intrusive images but to change the implicational meaning of schemas and childhood experiences that underlie the patient's problems. Various mechanisms that may…

  6. Testing methods for using high-resolution satellite imagery to monitor polar bear abundance and distribution

    Science.gov (United States)

    LaRue, Michelle A.; Stapleton, Seth P.; Porter, Claire; Atkinson, Stephen N.; Atwood, Todd C.; Dyck, Markus; Lecomte, Nicolas

    2015-01-01

    High-resolution satellite imagery is a promising tool for providing coarse information about polar species abundance and distribution, but current applications are limited. With polar bears (Ursus maritimus), the technique has only proven effective on landscapes with little topographic relief that are devoid of snow and ice, and time-consuming manual review of imagery is required to identify bears. Here, we evaluated mechanisms to further develop methods for satellite imagery by examining data from Rowley Island, Canada. We attempted to automate and expedite detection via a supervised spectral classification and image differencing to expedite image review. We also assessed what proportion of a region should be sampled to obtain reliable estimates of density and abundance. Although the spectral signature of polar bears differed from nontarget objects, these differences were insufficient to yield useful results via a supervised classification process. Conversely, automated image differencing—or subtracting one image from another—correctly identified nearly 90% of polar bear locations. This technique, however, also yielded false positives, suggesting that manual review will still be required to confirm polar bear locations. On Rowley Island, bear distribution approximated a Poisson distribution across a range of plot sizes, and resampling suggests that sampling >50% of the site facilitates reliable estimation of density (CV in certain areas, but large-scale applications remain limited because of the challenges in automation and the limited environments in which the method can be effectively applied. Improvements in resolution may expand opportunities for its future uses.

  7. Testing methods for using high-resolution satellite imagery to monitor polar bear abundance and distribution

    Science.gov (United States)

    LaRue, Michelle A.; Stapleton, Seth P.; Porter, Claire; Atkinson, Stephen N.; Atwood, Todd C.; Dyck, Markus; Lecomte, Nicolas

    2015-01-01

    High-resolution satellite imagery is a promising tool for providing coarse information about polar species abundance and distribution, but current applications are limited. With polar bears (Ursus maritimus), the technique has only proven effective on landscapes with little topographic relief that are devoid of snow and ice, and time-consuming manual review of imagery is required to identify bears. Here, we evaluated mechanisms to further develop methods for satellite imagery by examining data from Rowley Island, Canada. We attempted to automate and expedite detection via a supervised spectral classification and image differencing to expedite image review. We also assessed what proportion of a region should be sampled to obtain reliable estimates of density and abundance. Although the spectral signature of polar bears differed from nontarget objects, these differences were insufficient to yield useful results via a supervised classification process. Conversely, automated image differencing—or subtracting one image from another—correctly identified nearly 90% of polar bear locations. This technique, however, also yielded false positives, suggesting that manual review will still be required to confirm polar bear locations. On Rowley Island, bear distribution approximated a Poisson distribution across a range of plot sizes, and resampling suggests that sampling >50% of the site facilitates reliable estimation of density (CV large-scale applications remain limited because of the challenges in automation and the limited environments in which the method can be effectively applied. Improvements in resolution may expand opportunities for its future uses.

  8. Scales

    Science.gov (United States)

    Scales are a visible peeling or flaking of outer skin layers. These layers are called the stratum ... Scales may be caused by dry skin, certain inflammatory skin conditions, or infections. Examples of disorders that ...

  9. Unified Modeling Language description of the object-oriented multi-scale adaptive finite element method for Step-and-Flash Imprint Lithography Simulations

    International Nuclear Information System (INIS)

    Paszynski, Maciej; Gurgul, Piotr; Sieniek, Marcin; Pardo, David

    2010-01-01

    In the first part of the paper we present the multi-scale simulation of the Step-and-Flash Imprint Lithography (SFIL), a modern patterning process. The simulation utilizes the hp adaptive Finite Element Method (hp-FEM) coupled with Molecular Statics (MS) model. Thus, we consider the multi-scale problem, with molecular statics applied in the areas of the mesh where the highest accuracy is required, and the continuous linear elasticity with thermal expansion coefficient applied in the remaining part of the domain. The degrees of freedom from macro-scale element's nodes located on the macro-scale side of the interface have been identified with particles from nano-scale elements located on the nano-scale side of the interface. In the second part of the paper we present Unified Modeling Language (UML) description of the resulting multi-scale application (hp-FEM coupled with MS). We investigated classical, procedural codes from the point of view of the object-oriented (O-O) programming paradigm. The discovered hierarchical structure of classes and algorithms makes the UML project as independent on the spatial dimension of the problem as possible. The O-O UML project was defined at an abstract level, independent on the programming language used.

  10. Mental imagery for musical changes in loudness

    Directory of Open Access Journals (Sweden)

    Freya eBailes

    2012-12-01

    Full Text Available Musicians imagine music during mental rehearsal, when reading from a score, and while composing. An important characteristic of music is its temporality. Among the parameters that vary through time is sound intensity, perceived as patterns of loudness. Studies of mental imagery for melodies (i.e. pitch and rhythm show interference from concurrent musical pitch and verbal tasks, but how we represent musical changes in loudness is unclear. Theories suggest that our perceptions of loudness change relate to our perceptions of force or effort, implying a motor representation. An experiment was conducted to investigate the modalities that contribute to imagery for loudness change. Musicians performed a within-subjects loudness change recall task, comprising 48 trials. First, participants heard a musical scale played with varying patterns of loudness, which they were asked to remember. There followed an empty interval of 8 seconds (nil distractor control, or the presentation of a series of 4 sine tones, or 4 visual letters or 3 conductor gestures, also to be remembered. Participants then saw an unfolding score of the notes of the scale, during which they were to imagine the corresponding scale in their mind while adjusting a slider to indicate the imagined changes in loudness. Finally, participants performed a recognition task of the tone, letter or gesture sequence. Based on the motor hypothesis, we predicted that observing and remembering conductor gestures would impair loudness change scale recall, while observing and remembering tone or letter string stimuli would not. Results support this prediction, with loudness change recalled less accurately in the gestures condition than in the control condition. An effect of musical training suggests that auditory and motor imagery ability may be closely related to domain expertise.

  11. Vividness of Visual Imagery Depends on the Neural Overlap with Perception in Visual Areas.

    Science.gov (United States)

    Dijkstra, Nadine; Bosch, Sander E; van Gerven, Marcel A J

    2017-02-01

    Research into the neural correlates of individual differences in imagery vividness point to an important role of the early visual cortex. However, there is also great fluctuation of vividness within individuals, such that only looking at differences between people necessarily obscures the picture. In this study, we show that variation in moment-to-moment experienced vividness of visual imagery, within human subjects, depends on the activity of a large network of brain areas, including frontal, parietal, and visual areas. Furthermore, using a novel multivariate analysis technique, we show that the neural overlap between imagery and perception in the entire visual system correlates with experienced imagery vividness. This shows that the neural basis of imagery vividness is much more complicated than studies of individual differences seemed to suggest. Visual imagery is the ability to visualize objects that are not in our direct line of sight: something that is important for memory, spatial reasoning, and many other tasks. It is known that the better people are at visual imagery, the better they can perform these tasks. However, the neural correlates of moment-to-moment variation in visual imagery remain unclear. In this study, we show that the more the neural response during imagery is similar to the neural response during perception, the more vivid or perception-like the imagery experience is. Copyright © 2017 the authors 0270-6474/17/371367-07$15.00/0.

  12. The Effects of Guided Imagery on Heart Rate Variability in Simulated Spaceflight Emergency Tasks Performers

    Directory of Open Access Journals (Sweden)

    Zhang Yijing

    2015-01-01

    Full Text Available Objectives. The present study aimed to investigate the effects of guided imagery training on heart rate variability in individuals while performing spaceflight emergency tasks. Materials and Methods. Twenty-one student subjects were recruited for the experiment and randomly divided into two groups: imagery group (n=11 and control group (n=10. The imagery group received instructor-guided imagery (session 1 and self-guided imagery training (session 2 consecutively, while the control group only received conventional training. Electrocardiograms of the subjects were recorded during their performance of nine spaceflight emergency tasks after imagery training. Results. In both of the sessions, the root mean square of successive differences (RMSSD, the standard deviation of all normal NN (SDNN, the proportion of NN50 divided by the total number of NNs (PNN50, the very low frequency (VLF, the low frequency (LF, the high frequency (HF, and the total power (TP in the imagery group were significantly higher than those in the control group. Moreover, LF/HF of the subjects after instructor-guided imagery training was lower than that after self-guided imagery training. Conclusions. Guided imagery was an effective regulator for HRV indices and could be a potential stress countermeasure in performing spaceflight tasks.

  13. The Effects of Guided Imagery on Heart Rate Variability in Simulated Spaceflight Emergency Tasks Performers

    Science.gov (United States)

    Yijing, Zhang; Xiaoping, Du; Fang, Liu; Xiaolu, Jing; Bin, Wu

    2015-01-01

    Objectives. The present study aimed to investigate the effects of guided imagery training on heart rate variability in individuals while performing spaceflight emergency tasks. Materials and Methods. Twenty-one student subjects were recruited for the experiment and randomly divided into two groups: imagery group (n = 11) and control group (n = 10). The imagery group received instructor-guided imagery (session 1) and self-guided imagery training (session 2) consecutively, while the control group only received conventional training. Electrocardiograms of the subjects were recorded during their performance of nine spaceflight emergency tasks after imagery training. Results. In both of the sessions, the root mean square of successive differences (RMSSD), the standard deviation of all normal NN (SDNN), the proportion of NN50 divided by the total number of NNs (PNN50), the very low frequency (VLF), the low frequency (LF), the high frequency (HF), and the total power (TP) in the imagery group were significantly higher than those in the control group. Moreover, LF/HF of the subjects after instructor-guided imagery training was lower than that after self-guided imagery training. Conclusions. Guided imagery was an effective regulator for HRV indices and could be a potential stress countermeasure in performing spaceflight tasks. PMID:26137491

  14. Integration of aerial oblique imagery and terrestrial imagery for optimized 3D modeling in urban areas

    Science.gov (United States)

    Wu, Bo; Xie, Linfu; Hu, Han; Zhu, Qing; Yau, Eric

    2018-05-01

    Photorealistic three-dimensional (3D) models are fundamental to the spatial data infrastructure of a digital city, and have numerous potential applications in areas such as urban planning, urban management, urban monitoring, and urban environmental studies. Recent developments in aerial oblique photogrammetry based on aircraft or unmanned aerial vehicles (UAVs) offer promising techniques for 3D modeling. However, 3D models generated from aerial oblique imagery in urban areas with densely distributed high-rise buildings may show geometric defects and blurred textures, especially on building façades, due to problems such as occlusion and large camera tilt angles. Meanwhile, mobile mapping systems (MMSs) can capture terrestrial images of close-range objects from a complementary view on the ground at a high level of detail, but do not offer full coverage. The integration of aerial oblique imagery with terrestrial imagery offers promising opportunities to optimize 3D modeling in urban areas. This paper presents a novel method of integrating these two image types through automatic feature matching and combined bundle adjustment between them, and based on the integrated results to optimize the geometry and texture of the 3D models generated from aerial oblique imagery. Experimental analyses were conducted on two datasets of aerial and terrestrial images collected in Dortmund, Germany and in Hong Kong. The results indicate that the proposed approach effectively integrates images from the two platforms and thereby improves 3D modeling in urban areas.

  15. Full-scale vibration tests of Atucha II N.P.P. Part I: objectives, instrumentation and test description

    International Nuclear Information System (INIS)

    Konno, T.; Tsugawa, T.; Sala, G.; Friebe, T.M.; Prato, C.A.; Godoy, A.R.

    1995-01-01

    The main purpose of the tests was to provide experimental data on the dynamic characteristics of the main reactor building and adjacent structures of a full-scale nuclear power plant built on deep Quaternary soil deposits. Test results were intended to provide a benchmark case for control and calibration of state-of-the-art numerical techniques used for engineering design of new plants and assessment of existing facilities. Interpretation of test results and calibration of numerical analyses are described in other associated papers. (author). 5 figs

  16. Creation and validation of a visual macroscopic hematuria scale for optimal communication and an objective hematuria index.

    Science.gov (United States)

    Wong, Lih-Ming; Chum, Jia-Min; Maddy, Peter; Chan, Steven T F; Travis, Douglas; Lawrentschuk, Nathan

    2010-07-01

    Macroscopic hematuria is a common symptom and sign that is challenging to quantify and describe. The degree of hematuria communicated is variable due to health worker experience combined with lack of a reliable grading tool. We produced a reliable, standardized visual scale to describe hematuria severity. Our secondary aim was to validate a new laboratory test to quantify hemoglobin in hematuria specimens. Nurses were surveyed to ascertain current hematuria descriptions. Blood and urine were titrated at varying concentrations and digitally photographed in catheter bag tubing. Photos were processed and printed on transparency paper to create a prototype swatch or card showing light, medium, heavy and old hematuria. Using the swatch 60 samples were rated by nurses and laymen. Interobserver variability was reported using the generalized kappa coefficient of agreement. Specimens were analyzed for hemolysis by measuring optical density at oxyhemoglobin absorption peaks. Interobserver agreement between nurses and laymen was good (kappa = 0.51, p visual scale to grade and communicate hematuria with adequate interobserver agreement is feasible. The test for optical density at oxyhemoglobin absorption peaks is a new method, validated in our study, to quantify hemoglobin in a hematuria specimen. Copyright (c) 2010 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

  17. Mental Representation and Motor Imagery Training

    Directory of Open Access Journals (Sweden)

    Thomas eSchack

    2014-05-01

    Full Text Available Research in sports, dance and rehabilitation has shown that Basic Action Concepts (BACs are fundamental building blocks of mental action representations. BACs are based on chunked body postures related to common functions for realizing action goals. In this paper, we outline issues in research methodology and an experimental method, SDA-M (structural dimensional analysis of mental representation, to assess action-relevant representational structures that reflect the organization of BACs. The SDA-M reveals a strong relationship between cognitive representation and performance if complex actions are performed. We show how the SDA-M can improve motor imagery training and how it contributes to our understanding of coaching processes. The SDA-M capitalizes on the objective measurement of individual mental movement representations before training and the integration of these results into the motor imagery training. Such motor imagery training based on mental representations has been applied successfully in professional sports such as golf, volleyball, gymnastics, windsurfing, and recently in the rehabilitation of patients who have suffered a stroke.

  18. Optimization of airfoil-type PCHE for the recuperator of small scale brayton cycle by cost-based objective function

    International Nuclear Information System (INIS)

    Kwon, Jin Gyu; Kim, Tae Ho; Park, Hyun Sun; Cha, Jae Eun; Kim, Moo Hwan

    2016-01-01

    Highlights: • Suggest the Nusselt number and Fanning friction factor correlation for airfoil-type PCHE. • Show that cost-based optimization is available to airfoil-type PCHE. • Suggest the recuperator design for SCIEL test loop at KAERI by cost-based objective function with correlations from numerical analysis. - Abstract: Supercritical carbon dioxide (SCO_2) Brayton cycle gives high efficiency of power cycle with small size. Printed circuit heat exchangers (PCHE) are proper selection for the Brayton cycle because their operability at high temperature and high pressure with small size. Airfoil fin PCHE was suggested by Kim et al. (2008b), it can provide high heat transfer-like zigzag channel PCHE with low pressure drop-like straight channel PCHE. Optimization of the airfoil fin PCHE was not performed like the zigzag channel PCHE. For optimization of the airfoil fin PCHE, the operating condition of the recuperator of SCO_2 Integral Experiment Loop (SCIEL) Brayton cycle test loop at Korea Atomic Energy Research Institute (KAERI) was used. We performed CFD analysis for various airfoil fin configurations using ANSYS CFX 15.0, and made correlations for predicting the Nusselt number and the Fanning friction factor. The recuperator was designed by the simple energy balance code with our correlations. Using the cost-based objective function with production cost and operation cost from size and pressure drop of the recuperator, we evaluated airfoil fin configuration by using total cost and suggested the optimization configuration of the airfoil fin PCHE.

  19. Does objective cluster analysis serve as a useful precursor to seasonal precipitation prediction at local scale? Application to western Ethiopia

    Science.gov (United States)

    Zhang, Ying; Moges, Semu; Block, Paul

    2018-01-01

    Prediction of seasonal precipitation can provide actionable information to guide management of various sectoral activities. For instance, it is often translated into hydrological forecasts for better water resources management. However, many studies assume homogeneity in precipitation across an entire study region, which may prove ineffective for operational and local-level decisions, particularly for locations with high spatial variability. This study proposes advancing local-level seasonal precipitation predictions by first conditioning on regional-level predictions, as defined through objective cluster analysis, for western Ethiopia. To our knowledge, this is the first study predicting seasonal precipitation at high resolution in this region, where lives and livelihoods are vulnerable to precipitation variability given the high reliance on rain-fed agriculture and limited water resources infrastructure. The combination of objective cluster analysis, spatially high-resolution prediction of seasonal precipitation, and a modeling structure spanning statistical and dynamical approaches makes clear advances in prediction skill and resolution, as compared with previous studies. The statistical model improves versus the non-clustered case or dynamical models for a number of specific clusters in northwestern Ethiopia, with clusters having regional average correlation and ranked probability skill score (RPSS) values of up to 0.5 and 33 %, respectively. The general skill (after bias correction) of the two best-performing dynamical models over the entire study region is superior to that of the statistical models, although the dynamical models issue predictions at a lower resolution and the raw predictions require bias correction to guarantee comparable skills.

  20. Optimization of airfoil-type PCHE for the recuperator of small scale brayton cycle by cost-based objective function

    Energy Technology Data Exchange (ETDEWEB)

    Kwon, Jin Gyu [Division of Advanced Nuclear Engineering, POSTECH, Pohang 790-784 (Korea, Republic of); Kim, Tae Ho [Department of Mechanical Engineering, POSTECH, Pohang 790-784 (Korea, Republic of); Park, Hyun Sun, E-mail: hejsunny@postech.ac.kr [Division of Advanced Nuclear Engineering, POSTECH, Pohang 790-784 (Korea, Republic of); Cha, Jae Eun [Korea Atomic Energy Research Institute, Daejeon 305-353 (Korea, Republic of); Kim, Moo Hwan [Division of Advanced Nuclear Engineering, POSTECH, Pohang 790-784 (Korea, Republic of); Korea Institute of Nuclear Safety, Daejeon 305-338 (Korea, Republic of)

    2016-03-15

    Highlights: • Suggest the Nusselt number and Fanning friction factor correlation for airfoil-type PCHE. • Show that cost-based optimization is available to airfoil-type PCHE. • Suggest the recuperator design for SCIEL test loop at KAERI by cost-based objective function with correlations from numerical analysis. - Abstract: Supercritical carbon dioxide (SCO{sub 2}) Brayton cycle gives high efficiency of power cycle with small size. Printed circuit heat exchangers (PCHE) are proper selection for the Brayton cycle because their operability at high temperature and high pressure with small size. Airfoil fin PCHE was suggested by Kim et al. (2008b), it can provide high heat transfer-like zigzag channel PCHE with low pressure drop-like straight channel PCHE. Optimization of the airfoil fin PCHE was not performed like the zigzag channel PCHE. For optimization of the airfoil fin PCHE, the operating condition of the recuperator of SCO{sub 2} Integral Experiment Loop (SCIEL) Brayton cycle test loop at Korea Atomic Energy Research Institute (KAERI) was used. We performed CFD analysis for various airfoil fin configurations using ANSYS CFX 15.0, and made correlations for predicting the Nusselt number and the Fanning friction factor. The recuperator was designed by the simple energy balance code with our correlations. Using the cost-based objective function with production cost and operation cost from size and pressure drop of the recuperator, we evaluated airfoil fin configuration by using total cost and suggested the optimization configuration of the airfoil fin PCHE.

  1. Conditioned pain modulation is minimally influenced by cognitive evaluation or imagery of the conditioning stimulus

    Directory of Open Access Journals (Sweden)

    Bernaba M

    2014-11-01

    Full Text Available Mario Bernaba, Kevin A Johnson, Jiang-Ti Kong, Sean MackeyStanford Systems Neuroscience and Pain Laboratory, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USAPurpose: Conditioned pain modulation (CPM is an experimental approach for probing endogenous analgesia by which one painful stimulus (the conditioning stimulus may inhibit the perceived pain of a subsequent stimulus (the test stimulus. Animal studies suggest that CPM is mediated by a spino–bulbo–spinal loop using objective measures such as neuronal firing. In humans, pain ratings are often used as the end point. Because pain self-reports are subject to cognitive influences, we tested whether cognitive factors would impact on CPM results in healthy humans.Methods: We conducted a within-subject, crossover study of healthy adults to determine the extent to which CPM is affected by 1 threatening and reassuring evaluation and 2 imagery alone of a cold conditioning stimulus. We used a heat stimulus individualized to 5/10 on a visual analog scale as the testing stimulus and computed the magnitude of CPM by subtracting the postconditioning rating from the baseline pain rating of the heat stimulus.Results: We found that although evaluation can increase the pain rating of the conditioning stimulus, it did not significantly alter the magnitude of CPM. We also found that imagery of cold pain alone did not result in statistically significant CPM effect.Conclusion: Our results suggest that CPM is primarily dependent on sensory input, and that the cortical processes of evaluation and imagery have little impact on CPM. These findings lend support for CPM as a useful tool for probing endogenous analgesia through subcortical mechanisms.Keywords: conditioned pain modulation, endogenous analgesia, evaluation, imagery, cold presser test, CHEPS, contact heat-evoked potential stimulator

  2. Kinesthetic imagery of musical performance

    Directory of Open Access Journals (Sweden)

    Martin eLotze

    2013-06-01

    Full Text Available Musicians use different kinds of imagery. This review focuses on kinesthetic imagery, which has been shown to be an effective complement to actively playing an instrument. However, experience in actual movement performance seems to be a requirement for a recruitment of those brain areas representing movement ideation during imagery. An internal model of movement performance might be more differentiated when training has been more intense or simply performed more often. Therefore, with respect to kinesthetic imagery, these strategies are predominantly found in professional musicians. There are a few possible reasons as to why kinesthetic imagery is used in addition to active training; one example is the need for mental rehearsal of the technically most difficult passages. Training difficult passages repeatedly has the potential to induce fatigue in tendons and muscles and can ultimately result in the development of dystonia. Another reason for mental practice is that mental rehearsal of the piece helps to improve performance if the instrument is not available for actual training as is the case for professional musicians when they are travelling to various appearances. Overall, mental imagery in musicians is not necessarily specific to motor, somatosensory, auditory or visual aspects of imagery, but integrates them all. In particular, the audiomotor loop is highly important, since auditory aspects are crucial for guiding motor performance. Furthermore, slight co-movement, for instance of the fingers, usually occurs when imagining musical performance, a situation different to the laboratory condition where movement execution is strictly controlled. All these aspects result in a distinctive representation map for the mental imagery of musical performance. This review summarizes behavioral data, and findings from functional brain imaging studies of mental imagery of musical performance.

  3. Adequate managment of patients with dystrophinopathies (muscular dystrophy Duchenne/Becker: objective scales and additional diagnostic methods

    Directory of Open Access Journals (Sweden)

    A. S. Nosko

    2014-01-01

    Full Text Available There are still no guidlines on managment of Duchenne/Becker myodystrophy in domestic medical practice. It leads to decrease of quality of life and, what is more important, lifespan of patients. In this article we have described our Western coleagues lаst decade experience, including consensus guidelines published in 2010 on mаnаgment of Duchenne myodystrophy, supplemented with our practicle experience. We have described standardized motor development scale and muscle tone score for patients with MDD/MDB, and algorithm of multidiscipline care with focus on prevention, diagnosis and treatment of main disease and steroid therapy complications: cardiovascular, orthopedics, respirator etc. These recommendations not only improve quality of live and extend lifespan of MDD/MDB patients, but allow to take part in multicentre trials on searching of pathognomonic and symptomatic treatment.

  4. Grey relational and neural network approach for multi-objective optimization in small scale resistance spot welding of titanium alloy

    Energy Technology Data Exchange (ETDEWEB)

    Wan, Xiaodong; Wang, Yuanxun; Zhao, Dawei [Huazhong University of Science and Technology, Wuhan (China)

    2016-06-15

    The prediction and optimization of weld quality characteristics in small scale resistance spot welding of TC2 titanium alloy were investigated. Grey relational analysis, neural network and genetic algorithm were applied separately. Quality characteristics were selected as nugget diameter, failure load, failure displacement and failure energy. Welding parameters to be optimized were set as electrode force, welding current and welding time. Grey relational analysis was conducted for a rough estimation of the optimum welding parameters. Results showed that welding current played a key role in weld quality improvement. Different back propagation neural network architectures were then arranged to predict multiple quality characteristics. Interaction effects of welding parameters were analyzed with the proposed neural network. Failure load was found more sensitive to the change of welding parameters than nugget diameter. Optimum welding parameters were determined by genetic algorithm. The predicted responses showed good agreement with confirmation experiments.

  5. Imagery mismatch negativity in musicians.

    Science.gov (United States)

    Herholz, Sibylle C; Lappe, Claudia; Knief, Arne; Pantev, Christo

    2009-07-01

    The present study investigated musical imagery in musicians and nonmusicians by means of magnetoencephalography (MEG). We used a new paradigm in which subjects had to continue familiar melodies in their mind and then judged if a further presented tone was a correct continuation of the melody. Incorrect tones elicited an imagery mismatch negativity (iMMN) in musicians but not in nonmusicians. This finding suggests that the MMN component can be based on an imagined instead of a sensory memory trace and that imagery of music is modulated by musical expertise.

  6. Does objective cluster analysis serve as a useful precursor to seasonal precipitation prediction at local scale? Application to western Ethiopia

    Directory of Open Access Journals (Sweden)

    Y. Zhang

    2018-01-01

    Full Text Available Prediction of seasonal precipitation can provide actionable information to guide management of various sectoral activities. For instance, it is often translated into hydrological forecasts for better water resources management. However, many studies assume homogeneity in precipitation across an entire study region, which may prove ineffective for operational and local-level decisions, particularly for locations with high spatial variability. This study proposes advancing local-level seasonal precipitation predictions by first conditioning on regional-level predictions, as defined through objective cluster analysis, for western Ethiopia. To our knowledge, this is the first study predicting seasonal precipitation at high resolution in this region, where lives and livelihoods are vulnerable to precipitation variability given the high reliance on rain-fed agriculture and limited water resources infrastructure. The combination of objective cluster analysis, spatially high-resolution prediction of seasonal precipitation, and a modeling structure spanning statistical and dynamical approaches makes clear advances in prediction skill and resolution, as compared with previous studies. The statistical model improves versus the non-clustered case or dynamical models for a number of specific clusters in northwestern Ethiopia, with clusters having regional average correlation and ranked probability skill score (RPSS values of up to 0.5 and 33 %, respectively. The general skill (after bias correction of the two best-performing dynamical models over the entire study region is superior to that of the statistical models, although the dynamical models issue predictions at a lower resolution and the raw predictions require bias correction to guarantee comparable skills.

  7. Future distributed generation: An operational multi-objective optimization model for integrated small scale urban electrical, thermal and gas grids

    International Nuclear Information System (INIS)

    Lo Cascio, Ermanno; Borelli, Davide; Devia, Francesco; Schenone, Corrado

    2017-01-01

    Highlights: • Multi-objective optimization model for retrofitted and integrated natural gas pressure regulation stations. • Comparison of different incentive mechanisms for recovered energy based on the characteristics of preheating process. • Control strategies comparison: performances achieved with optimal control vs. ones obtained by thermal load tracking. - Abstract: A multi-objective optimization model for urban integrated electrical, thermal and gas grids is presented. The main system consists of a retrofitted natural gas pressure regulation station where a turbo-expander allows to recover energy from the process. Here, the natural gas must be preheated in order to avoid methane hydrates. The preheating phase could be based on fossil fuels, renewable or on a thermal mix. Depending on the system configuration, the proposed optimization model enables a proper differentiation based on how the natural gas preheating process is expected to be accomplished. This differentiation is addressed by weighting the electricity produced by the turbo-expander and linking it to proper remuneration tariffs. The effectiveness of the model has been tested on an existing plant located in the city of Genoa. Here, the thermal energy is provided by means of two redundant gas-fired boilers and a cogeneration unit. Furthermore, the whole system is thermally integrated with a district heating network. Numerical simulation results, obtained with the commercial proprietary software Honeywell UniSim Design Suite, have been compared with the optimal solutions achieved. The effectiveness of the model, in terms of economic and environmental performances, is finally quantified. For specific conditions, the model allows achieving an operational costs reduction of about 17% with the respect to thermal-load-tracking control logic.

  8. Automatic orientation and 3D modelling from markerless rock art imagery

    Science.gov (United States)

    Lerma, J. L.; Navarro, S.; Cabrelles, M.; Seguí, A. E.; Hernández, D.

    2013-02-01

    This paper investigates the use of two detectors and descriptors on image pyramids for automatic image orientation and generation of 3D models. The detectors and descriptors replace manual measurements and are used to detect, extract and match features across multiple imagery. The Scale-Invariant Feature Transform (SIFT) and the Speeded Up Robust Features (SURF) will be assessed based on speed, number of features, matched features, and precision in image and object space depending on the adopted hierarchical matching scheme. The influence of applying in addition Area Based Matching (ABM) with normalised cross-correlation (NCC) and least squares matching (LSM) is also investigated. The pipeline makes use of photogrammetric and computer vision algorithms aiming minimum interaction and maximum accuracy from a calibrated camera. Both the exterior orientation parameters and the 3D coordinates in object space are sequentially estimated combining relative orientation, single space resection and bundle adjustment. The fully automatic image-based pipeline presented herein to automate the image orientation step of a sequence of terrestrial markerless imagery is compared with manual bundle block adjustment and terrestrial laser scanning (TLS) which serves as ground truth. The benefits of applying ABM after FBM will be assessed both in image and object space for the 3D modelling of a complex rock art shelter.

  9. APFO Historical Availability of Imagery

    Data.gov (United States)

    Farm Service Agency, Department of Agriculture — The APFO Historical Availability ArcGIS Online web map provides an easy to use reference of what historical imagery is available by county from the Aerial...

  10. New percepts via mental imagery?

    Directory of Open Access Journals (Sweden)

    Fred Walter Mast

    2012-10-01

    Full Text Available We are able to extract detailed information from mental images that we were not explicitly aware of during encoding. For example, we can discover a new figure when we rotate a previously seen image in our mind. However, such discoveries are not really new but just new interpretations. In two recent publications, we have shown that mental imagery can lead to perceptual learning (Tartaglia et al., 2009, 2012. Observers imagined the central line of a bisection stimulus for thousands of trials. This training enabled observers to perceive bisection offsets that were invisible before training. Hence, it seems that perceptual learning via mental imagery leads to new percepts. We will argue, however, that these new percepts can occur only within known models. In this sense, perceptual learning via mental imagery exceeds new discoveries in mental images. Still, the effects of mental imagery on perceptual learning are limited. Only perception can lead to really new perceptual experience.

  11. Image Segmentation of Hyperspectral Imagery

    National Research Council Canada - National Science Library

    Wellman, Mark

    2003-01-01

    .... Army tactical applications. An important tactical application of infrared (IR) hyperspectral imagery is the detection of low-contrast targets, including those targets that may employ camouflage, concealment, and deception (CCD) techniques 1, 2...

  12. Capturing change: the duality of time-lapse imagery to acquire data and depict ecological dynamics

    Science.gov (United States)

    Brinley Buckley, Emma M.; Allen, Craig R.; Forsberg, Michael; Farrell, Michael; Caven, Andrew J.

    2017-01-01

    We investigate the scientific and communicative value of time-lapse imagery by exploring applications for data collection and visualization. Time-lapse imagery has a myriad of possible applications to study and depict ecosystems and can operate at unique temporal and spatial scales to bridge the gap between large-scale satellite imagery projects and observational field research. Time-lapse data sequences, linking time-lapse imagery with data visualization, have the ability to make data come alive for a wider audience by connecting abstract numbers to images that root data in time and place. Utilizing imagery from the Platte Basin Timelapse Project, water inundation and vegetation phenology metrics are quantified via image analysis and then paired with passive monitoring data, including streamflow and water chemistry. Dynamic and interactive time-lapse data sequences elucidate the visible and invisible ecological dynamics of a significantly altered yet internationally important river system in central Nebraska.

  13. Capturing change: the duality of time-lapse imagery to acquire data and depict ecological dynamics

    Directory of Open Access Journals (Sweden)

    Emma M. Brinley Buckley

    2017-09-01

    Full Text Available We investigate the scientific and communicative value of time-lapse imagery by exploring applications for data collection and visualization. Time-lapse imagery has a myriad of possible applications to study and depict ecosystems and can operate at unique temporal and spatial scales to bridge the gap between large-scale satellite imagery projects and observational field research. Time-lapse data sequences, linking time-lapse imagery with data visualization, have the ability to make data come alive for a wider audience by connecting abstract numbers to images that root data in time and place. Utilizing imagery from the Platte Basin Timelapse Project, water inundation and vegetation phenology metrics are quantified via image analysis and then paired with passive monitoring data, including streamflow and water chemistry. Dynamic and interactive time-lapse data sequences elucidate the visible and invisible ecological dynamics of a significantly altered yet internationally important river system in central Nebraska.

  14. Spectral Difference in the Image Domain for Large Neighborhoods, a GEOBIA Pre-Processing Step for High Resolution Imagery

    Directory of Open Access Journals (Sweden)

    Roeland de Kok

    2012-08-01

    Full Text Available Contrast plays an important role in the visual interpretation of imagery. To mimic visual interpretation and using contrast in a Geographic Object Based Image Analysis (GEOBIA environment, it is useful to consider an analysis for single pixel objects. This should be done before applying homogeneity criteria in the aggregation of pixels for the construction of meaningful image objects. The habit or “best practice” to start GEOBIA with pixel aggregation into homogeneous objects should come with the awareness that feature attributes for single pixels are at risk of becoming less accessible for further analysis. Single pixel contrast with image convolution on close neighborhoods is a standard technique, also applied in edge detection. This study elaborates on the analysis of close as well as much larger neighborhoods inside the GEOBIA domain. The applied calculations are limited to the first segmentation step for single pixel objects in order to produce additional feature attributes for objects of interest to be generated in further aggregation processes. The equation presented functions at a level that is considered an intermediary product in the sequential processing of imagery. The procedure requires intensive processor and memory capacity. The resulting feature attributes highlight not only contrasting pixels (edges but also contrasting areas of local pixel groups. The suggested approach can be extended and becomes useful in classifying artificial areas at national scales using high resolution satellite mosaics.

  15. Professional Success and Gender in Family Medicine: Design of Scales and Examination of Gender Differences in Subjective and Objective Success Among Family Physicians.

    Science.gov (United States)

    Delgado, Ana; Saletti-Cuesta, Lorena; López-Fernández, Luis Andrés; Toro-Cárdenas, Silvia; Luna del Castillo, Juan de Dios

    2016-03-01

    Two components of professional success have been defined: objective career success (OCS) and subjective career success (SCS). Despite the increasing number of women practicing medicine, gender inequalities persist. The objectives of this descriptive, cross-sectional, and multicenter study were (a) to construct and validate OCS and SCS scales, (b) to determine the relationships between OCS and SCS and between each scale and professional/family characteristics, and (c) to compare these associations between male and female family physicians (FPs). The study sample comprised 250 female and 250 male FPs from urban health centers in Andalusia (Spain). Data were gathered over 6 months on gender, age, care load, professional/family variables, and family-work balance, using a self-administered questionnaire. OSC and SCS scales were examined by using exploratory factorial analysis and Cronbach's α, and scores were compared by gender-stratified bivariate and multiple regression analyses. Intraclass correlation coefficients were calculated using a multilevel analysis. The response rate was 73.6%. We identified three OCS factors and two SCS factors. Lower scores were obtained by female versus male FPs in the OCS dimensions, but there were no gender differences in either SCS dimension. © The Author(s) 2014.

  16. Knowledge deficit, attitude and behavior scales association to objective measures of sun exposure and sunburn in a Danish population based sample.

    Science.gov (United States)

    Køster, Brian; Søndergaard, Jens; Nielsen, Jesper Bo; Christensen, Karl Bang; Allen, Martin; Olsen, Anja; Bentzen, Joan

    2017-01-01

    The objective of this study was to develop new scales measuring knowledge and attitude about UVR and sun related behavior, and to examine their association to sun related behavior objectively measured by personal dosimetry. During May-August 2013, 664 Danes wore a personal electronic UV-dosimeter for one week that measured their UVR exposure. Afterwards, they answered a questionnaire on sun-related items. We applied descriptive analysis, linear and logistic regression analysis to evaluate the associations between the questionnaire scales and objective UVR measures. Perceiving protection as routine and important were positively correlated with protective behavior. Knowledge deficit of UV and risk of melanoma, perceived benefits and importance of protection behavior was also correlated with use of protection. 'Knowledge deficit of UV and risk of melanoma and Perceived barrier towards sun avoidance between 12 and 15' were both associated with increased risk of sunburn. Attitude towards tan was associated to both outdoor time and exposure as well as use of protection, but not to sunburn. The results regarding Knowledge deficit of UV and risk of melanoma associated to UVR exposure and Perceived barrier towards sun avoidance between 12 and 15 emphasize the importance of awareness of melanoma risk and the priority of the skin cancer prevention advice. Shifting activities to outside the suns peak-hours could be an approach for structural and campaign preventive measures. Knowledge of items predicting exposure to UVR, use of protection and sunburn are important for planning of preventive interventions and melanoma research.

  17. Aerial Photography and Imagery, Ortho-Corrected, Digital orthophographs (DOPs) were derived from black and white aerial photographs taken in the spring of 2000. The DOP scale is 1:4800 (1" = 400') rectified to 18" pixels., Published in 2000, 1:4800 (1in=400ft) scale, Manitowoc County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2000. Digital orthophographs (DOPs) were derived from black and white aerial photographs taken...

  18. VHF/UHF imagery and RCS measurements of ground targets in forested terrain

    Science.gov (United States)

    Gatesman, Andrew J.; Beaudoin, Christopher J.; Giles, Robert H.; Waldman, Jerry; Nixon, William E.

    2002-08-01

    The monostatic VV and HH-polarized radar signatures of several targets and trees have been measured at foliage penetration frequencies (VHF/UHF) by using 1/35th scale models and an indoor radar range operating at X-band. An array of high-fidelity scale model ground vehicles and test objects as well as scaled ground terrain and trees have been fabricated for the study. Radar measurement accuracy has been confirmed by comparing the signature of a test object with a method of moments radar cross section prediction code. In addition to acquiring signatures of targets located on a smooth, dielectric ground plane, data have also been acquired with targets located in simulated wooded terrain that included scaled tree trunks and tree branches. In order to assure the correct backscattering behavior, all dielectric properties of live tree wood and moist soil were scaled properly to match the complex dielectric constant of the full-scale materials. The impact of the surrounding tree clutter on the VHF/UHF radar signatures of ground vehicles was accessed. Data were processed into high-resolution, polar-formatted ISAR imagery and signature comparisons are made between targets in open-field and forested scenarios.

  19. Satellite Imagery Analysis for Automated Global Food Security Forecasting

    Science.gov (United States)

    Moody, D.; Brumby, S. P.; Chartrand, R.; Keisler, R.; Mathis, M.; Beneke, C. M.; Nicholaeff, D.; Skillman, S.; Warren, M. S.; Poehnelt, J.

    2017-12-01

    The recent computing performance revolution has driven improvements in sensor, communication, and storage technology. Multi-decadal remote sensing datasets at the petabyte scale are now available in commercial clouds, with new satellite constellations generating petabytes/year of daily high-resolution global coverage imagery. Cloud computing and storage, combined with recent advances in machine learning, are enabling understanding of the world at a scale and at a level of detail never before feasible. We present results from an ongoing effort to develop satellite imagery analysis tools that aggregate temporal, spatial, and spectral information and that can scale with the high-rate and dimensionality of imagery being collected. We focus on the problem of monitoring food crop productivity across the Middle East and North Africa, and show how an analysis-ready, multi-sensor data platform enables quick prototyping of satellite imagery analysis algorithms, from land use/land cover classification and natural resource mapping, to yearly and monthly vegetative health change trends at the structural field level.

  20. Exploring effect of segmentation scale on orient-based crop identification using HJ CCD data in Northeast China

    International Nuclear Information System (INIS)

    Cao, Xin; Zheng, Xinqi; Li, Qiangzi; Du, Xin; Zhang, Miao

    2014-01-01

    Crop identification and acreage estimation with remote sensing were the main issues for crop production estimation. Object-oriented classification has been involved in crop extraction from high spatial resolution images. However, different imagery segmentation scales for object-oriented classification always yield quite different crop identification accuracy. In this paper, multi-scale image segmentation was conducted to carry out crop identification using HJ CCD imagery in Red Star Farm in Heilongjiang province. Corn, soybean and wheat were identified as the final crop classes. Crop identification features at different segmentation scale were generated. Crop separability based on different feature-combinations was evaluated using class separation distance. Nearest Neighbour classifier (NN) was then used for crop identification. The results showed that the best segmentation scale was 8, and the overall crop identification accuracy was about 0.969 at that scale

  1. Objective structured assessment of nontechnical skills: Reliability of a global rating scale for the in-training assessment in the operating room.

    Science.gov (United States)

    Dedy, Nicolas J; Szasz, Peter; Louridas, Marisa; Bonrath, Esther M; Husslein, Heinrich; Grantcharov, Teodor P

    2015-06-01

    Nontechnical skills are critical for patient safety in the operating room (OR). As a result, regulatory bodies for accreditation and certification have mandated the integration of these competencies into postgraduate education. A generally accepted approach to the in-training assessment of nontechnical skills, however, is lacking. The goal of the present study was to develop an evidence-based and reliable tool for the in-training assessment of residents' nontechnical performance in the OR. The Objective Structured Assessment of Nontechnical Skills tool was designed as a 5-point global rating scale with descriptive anchors for each item, based on existing evidence-based frameworks of nontechnical skills, as well as resident training requirements. The tool was piloted on scripted videos and refined in an iterative process. The final version was used to rate residents' performance in recorded OR crisis simulations and during live observations in the OR. A total of 37 simulations and 10 live procedures were rated. Interrater agreement was good for total mean scores, both in simulation and in the real OR, with intraclass correlation coefficients >0.90 in all settings for average and single measures. Internal consistency of the scale was high (Cronbach's alpha = 0.80). The Objective Structured Assessment of Nontechnical Skills global rating scale was developed as an evidence-based tool for the in-training assessment of residents' nontechnical performance in the OR. Unique descriptive anchors allow for a criterion-referenced assessment of performance. Good reliability was demonstrated in different settings, supporting applications in research and education. Copyright © 2015 Elsevier Inc. All rights reserved.

  2. Essential climatic variables estimation with satellite imagery

    Science.gov (United States)

    Kolotii, A.; Kussul, N.; Shelestov, A.; Lavreniuk, M. S.

    2016-12-01

    According to Sendai Framework for Disaster Risk Reduction 2015 - 2030 Leaf Area Index (LAI) is considered as one of essential climatic variables. This variable represents the amount of leaf material in ecosystems and controls the links between biosphere and atmosphere through various processes and enables monitoring and quantitative assessment of vegetation state. LAI has added value for such important global resources monitoring tasks as drought mapping and crop yield forecasting with use of data from different sources [1-2]. Remote sensing data from space can be used to estimate such biophysical parameter at regional and national scale. High temporal satellite imagery is usually required to capture main parameters of crop growth [3]. Sentinel-2 mission launched in 2015 be ESA is a source of high spatial and temporal resolution satellite imagery for mapping biophysical parameters. Products created with use of automated Sen2-Agri system deployed during Sen2-Agri country level demonstration project for Ukraine will be compared with our independent results of biophysical parameters mapping. References Shelestov, A., Kolotii, A., Camacho, F., Skakun, S., Kussul, O., Lavreniuk, M., & Kostetsky, O. (2015, July). Mapping of biophysical parameters based on high resolution EO imagery for JECAM test site in Ukraine. In 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 1733-1736 Kolotii, A., Kussul, N., Shelestov, A., Skakun, S., Yailymov, B., Basarab, R., ... & Ostapenko, V. (2015). Comparison of biophysical and satellite predictors for wheat yield forecasting in Ukraine. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 40(7), 39-44. Kussul, N., Lemoine, G., Gallego, F. J., Skakun, S. V., Lavreniuk, M., & Shelestov, A. Y. Parcel-Based Crop Classification in Ukraine Using Landsat-8 Data and Sentinel-1A Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 9 (6), 2500-2508.

  3. [A study on the individual differences of the experience of hypnagogic imagery].

    Science.gov (United States)

    Watanabe, T

    1998-02-01

    Having defined the distinction between hypnagogic imagery and dreams, a preliminary study on the individual differences in the experience of visual hypnagogic imagery was conducted. (1) A questionnaire on visual hypnagogic experience was administered to 796 students. The results suggested that previous researches on the incidence of this experience might have suffered from ambiguous definitions. (2) The Scale of Mental Imagery (Hasegawa, 1992) was administered to 330 of the same students, Eysenck Personality Questionnaire to 305 students, and S-A Creativity Test (Sozosei-shinri-kenkyukai, 1969) to 221 students. The frequency of hypnagogic experiences was significantly associated with the scores of "the vividness of mental imagery", "neuroticism", and "creativity". (3) Based on these results, a proposed research problem on hypnagogic imagery was discussed.

  4. AgSat Imagery Collection Footprints

    Data.gov (United States)

    Farm Service Agency, Department of Agriculture — The AgSat Imagery Collection Footprints map shows the imagery footprints which have been collected under the USDA satellite blanket purchase agreement. Click on a...

  5. Concepts are not represented by conscious imagery

    NARCIS (Netherlands)

    D. Pecher (Diane); S. van Dantzig (Saskia); H.N.J. Schifferstien (Hendrik)

    2009-01-01

    textabstractAccording to theories of grounded cognition, conceptual representation and perception share processing mechanisms. We investigated whether this overlap is due to conscious perceptual imagery. Participants filled out questionnaires to assess the vividness of their imagery (Questionnaire

  6. Information mining in remote sensing imagery

    Science.gov (United States)

    Li, Jiang

    The volume of remotely sensed imagery continues to grow at an enormous rate due to the advances in sensor technology, and our capability for collecting and storing images has greatly outpaced our ability to analyze and retrieve information from the images. This motivates us to develop image information mining techniques, which is very much an interdisciplinary endeavor drawing upon expertise in image processing, databases, information retrieval, machine learning, and software design. This dissertation proposes and implements an extensive remote sensing image information mining (ReSIM) system prototype for mining useful information implicitly stored in remote sensing imagery. The system consists of three modules: image processing subsystem, database subsystem, and visualization and graphical user interface (GUI) subsystem. Land cover and land use (LCLU) information corresponding to spectral characteristics is identified by supervised classification based on support vector machines (SVM) with automatic model selection, while textural features that characterize spatial information are extracted using Gabor wavelet coefficients. Within LCLU categories, textural features are clustered using an optimized k-means clustering approach to acquire search efficient space. The clusters are stored in an object-oriented database (OODB) with associated images indexed in an image database (IDB). A k-nearest neighbor search is performed using a query-by-example (QBE) approach. Furthermore, an automatic parametric contour tracing algorithm and an O(n) time piecewise linear polygonal approximation (PLPA) algorithm are developed for shape information mining of interesting objects within the image. A fuzzy object-oriented database based on the fuzzy object-oriented data (FOOD) model is developed to handle the fuzziness and uncertainty. Three specific applications are presented: integrated land cover and texture pattern mining, shape information mining for change detection of lakes, and

  7. Agency Video, Audio and Imagery Library

    Science.gov (United States)

    Grubbs, Rodney

    2015-01-01

    The purpose of this presentation was to inform the ISS International Partners of the new NASA Agency Video, Audio and Imagery Library (AVAIL) website. AVAIL is a new resource for the public to search for and download NASA-related imagery, and is not intended to replace the current process by which the International Partners receive their Space Station imagery products.

  8. Media, Mental Imagery, and Memory.

    Science.gov (United States)

    Clark, Robert L.

    1978-01-01

    Thirty-two students at the University of Oregon were tested to determine the effects of media on mental imagery and memory. The model incorporates a dual coding hypothesis, and five single and multiple channel treatments were used. (Author/JEG)

  9. Dialectical Imagery and Postmodern Research

    Science.gov (United States)

    Davison, Kevin G.

    2006-01-01

    This article suggests utilizing dialectical imagery, as understood by German social philosopher Walter Benjamin, as an additional qualitative data analysis strategy for research into the postmodern condition. The use of images mined from research data may offer epistemological transformative possibilities that will assist in the demystification of…

  10. Illustrating and Designing Quranic Imagery

    Science.gov (United States)

    Almenoar, Lubna

    2009-01-01

    Selected verses from Abdullah Yusuf Ali's English language translation of the meaning of the Quran have been used as a literary text to teach both descriptive and figurative imagery (including similes, metaphors and symbols) to students at the undergraduate level in an Islamic institution. The technique--Illustrating and Designing for teaching…

  11. Classification of radiation-hazardous objects by the ecological risk rate, based on the concept of the International Nuclear Event Scale (INES)

    International Nuclear Information System (INIS)

    Vetrov, V.A.

    2003-01-01

    The principal categories of the radiation-hazardous objects (RHO) (nuclear fuel cycle plants (NFC including NPP); ships with nuclear engine units and appropriate service facilities; units related with nuclear weapons (design, manufacture, storage, etc.); contaminated territories in the result nuclear accidents and nuclear facilities tests; civil enterprises using the radioactive sources) with real accident risk from radioactive substances (RS) release into environment are considered. For assessment of the ecological risk rate from RHO the International Nuclear Event Scale implemented by IAEA for NPP use is suggested. By opinion of the specialists the INES criteria could be used for radiation events assessment to other RHO that gives possibility for RHO arrangement by the potential hazard rate for environment in the case of accident. For RHO qualitative classification the main parameters assessment influencing on radioactive release risk (amount (total activity) of radioactive substances; possibility of chain reaction development; strength of technological parameters, etc.) was suggested. On the base of the INES all above-listed RHO kinds in the case of accident could be conditionally separated into three categories: 1. most radiation dangerous objects, on which could be severe and serious radiation accidents (corresponding to 4-7 INES levels); 2. RHO on which there is risk for accidents accompanying with RS release (accidents up to 4 INES level). 3. RHO without practical possibility for event (incidents - not higher 3 INES level). Introduction of suggested classification gives possibility for RHO safety control requirements rationalizing to radiation monitoring purposes for both RHO and the local systems

  12. Social scaling of extrapersonal space: target objects are judged as closer when the reference frame is a human agent with available movement potentialities.

    Science.gov (United States)

    Fini, C; Brass, M; Committeri, G

    2015-01-01

    effect was simply due to a line-of-sight mechanism (visual perspective taking) we compared the human agent free to move with the same agent tied to a pole with a rope, thus reducing movement potentialities while maintaining equal visual accessibility. The "Near space extension" disappeared when this manipulation was introduced, showing that movement potentialities are the relevant factor for such an effect. Our results demonstrate for the first time that during allocentric distance judgments within extrapersonal space, we implicitly process the movement potentialities of the RF. A target object is perceived as being closer when the allocentric RF is a human with available movement potentialities, suggesting a mechanism of social scaling of extrapersonal space processing. Copyright © 2014. Published by Elsevier B.V.

  13. Change detection on LOD 2 building models with very high resolution spaceborne stereo imagery

    Science.gov (United States)

    Qin, Rongjun

    2014-10-01

    Due to the fast development of the urban environment, the need for efficient maintenance and updating of 3D building models is ever increasing. Change detection is an essential step to spot the changed area for data (map/3D models) updating and urban monitoring. Traditional methods based on 2D images are no longer suitable for change detection in building scale, owing to the increased spectral variability of the building roofs and larger perspective distortion of the very high resolution (VHR) imagery. Change detection in 3D is increasingly being investigated using airborne laser scanning data or matched Digital Surface Models (DSM), but rare study has been conducted regarding to change detection on 3D city models with VHR images, which is more informative but meanwhile more complicated. This is due to the fact that the 3D models are abstracted geometric representation of the urban reality, while the VHR images record everything. In this paper, a novel method is proposed to detect changes directly on LOD (Level of Detail) 2 building models with VHR spaceborne stereo images from a different date, with particular focus on addressing the special characteristics of the 3D models. In the first step, the 3D building models are projected onto a raster grid, encoded with building object, terrain object, and planar faces. The DSM is extracted from the stereo imagery by hierarchical semi-global matching (SGM). In the second step, a multi-channel change indicator is extracted between the 3D models and stereo images, considering the inherent geometric consistency (IGC), height difference, and texture similarity for each planar face. Each channel of the indicator is then clustered with the Self-organizing Map (SOM), with "change", "non-change" and "uncertain change" status labeled through a voting strategy. The "uncertain changes" are then determined with a Markov Random Field (MRF) analysis considering the geometric relationship between faces. In the third step, buildings are

  14. Object and Objective Lost?

    DEFF Research Database (Denmark)

    Lopdrup-Hjorth, Thomas

    2015-01-01

    This paper explores the erosion and problematization of ‘the organization’ as a demarcated entity. Utilizing Foucault's reflections on ‘state-phobia’ as a source of inspiration, I show how an organization-phobia has gained a hold within Organization Theory (OT). By attending to the history...... of this organization-phobia, the paper argues that OT has become increasingly incapable of speaking about its core object. I show how organizations went from being conceptualized as entities of major importance to becoming theoretically deconstructed and associated with all kinds of ills. Through this history......, organizations as distinct entities have been rendered so problematic that they have gradually come to be removed from the center of OT. The costs of this have been rather significant. Besides undermining the grounds that gave OT intellectual credibility and legitimacy to begin with, the organization-phobia...

  15. Photogrammetry of the Viking Lander imagery

    Science.gov (United States)

    Wu, S. S. C.; Schafer, F. J.

    1982-01-01

    The problem of photogrammetric mapping which uses Viking Lander photography as its basis is solved in two ways: (1) by converting the azimuth and elevation scanning imagery to the equivalent of a frame picture, using computerized rectification; and (2) by interfacing a high-speed, general-purpose computer to the analytical plotter employed, so that all correction computations can be performed in real time during the model-orientation and map-compilation process. Both the efficiency of the Viking Lander cameras and the validity of the rectification method have been established by a series of pre-mission tests which compared the accuracy of terrestrial maps compiled by this method with maps made from aerial photographs. In addition, 1:10-scale topographic maps of Viking Lander sites 1 and 2 having a contour interval of 1.0 cm have been made to test the rectification method.

  16. Mental Imagery in Depression: Phenomenology, Potential Mechanisms, and Treatment Implications.

    Science.gov (United States)

    Holmes, Emily A; Blackwell, Simon E; Burnett Heyes, Stephanie; Renner, Fritz; Raes, Filip

    2016-01-01

    Mental imagery is an experience like perception in the absence of a percept. It is a ubiquitous feature of human cognition, yet it has been relatively neglected in the etiology, maintenance, and treatment of depression. Imagery abnormalities in depression include an excess of intrusive negative mental imagery; impoverished positive imagery; bias for observer perspective imagery; and overgeneral memory, in which specific imagery is lacking. We consider the contribution of imagery dysfunctions to depressive psychopathology and implications for cognitive behavioral interventions. Treatment advances capitalizing on the representational format of imagery (as opposed to its content) are reviewed, including imagery rescripting, positive imagery generation, and memory specificity training. Consideration of mental imagery can contribute to clinical assessment and imagery-focused psychological therapeutic techniques and promote investigation of underlying mechanisms for treatment innovation. Research into mental imagery in depression is at an early stage. Work that bridges clinical psychology and neuroscience in the investigation of imagery-related mechanisms is recommended.

  17. A signature correlation study of ground target VHF/UHF ISAR imagery

    Science.gov (United States)

    Gatesman, Andrew J.; Beaudoin, Christopher J.; Giles, Robert H.; Kersey, William T.; Waldman, Jerry; Carter, Steve; Nixon, William E.

    2003-09-01

    VV and HH-polarized radar signatures of several ground targets were acquired in the VHF/UHF band (171-342 MHz) by using 1/35th scale models and an indoor radar range operating from 6 to 12 GHz. Data were processed into medianized radar cross sections as well as focused, ISAR imagery. Measurement validation was confirmed by comparing the radar cross section of a test object with a method of moments radar cross section prediction code. The signatures of several vehicles from three vehicle classes (tanks, trunks, and TELs) were measured and a signature cross-correlation study was performed. The VHF/UHF band is currently being exploited for its foliage penetration ability, however, the coarse image resolution which results from the relatively long radar wavelengths suggests a more challenging target recognition problem. One of the study's goals was to determine the amount of unique signature content in VHF/UHF ISAR imagery of military ground vehicles. Open-field signatures are compared with each other as well as with simplified shapes of similar size. Signatures were also acquired on one vehicle in a variety of configurations to determine the impact of monitor target variations on the signature content at these frequencies.

  18. Advanced Ecosystem Mapping Techniques for Large Arctic Study Domains Using Calibrated High-Resolution Imagery

    Science.gov (United States)

    Macander, M. J.; Frost, G. V., Jr.

    2015-12-01

    Regional-scale mapping of vegetation and other ecosystem properties has traditionally relied on medium-resolution remote sensing such as Landsat (30 m) and MODIS (250 m). Yet, the burgeoning availability of high-resolution (environments has not been previously evaluated. Image segmentation, or object-based image analysis, automatically partitions high-resolution imagery into homogeneous image regions that can then be analyzed based on spectral, textural, and contextual information. We applied eCognition software to delineate waterbodies and vegetation classes, in combination with other techniques. Texture metrics were evaluated to determine the feasibility of using high-resolution imagery to algorithmically characterize periglacial surface forms (e.g., ice-wedge polygons), which are an important physical characteristic of permafrost-dominated regions but which cannot be distinguished by medium-resolution remote sensing. These advanced mapping techniques provide products which can provide essential information supporting a broad range of ecosystem science and land-use planning applications in northern Alaska and elsewhere in the circumpolar Arctic.

  19. Calibrating EEG-based motor imagery brain-computer interface from passive movement.

    Science.gov (United States)

    Ang, Kai Keng; Guan, Cuntai; Wang, Chuanchu; Phua, Kok Soon; Tan, Adrian Hock Guan; Chin, Zheng Yang

    2011-01-01

    EEG data from performing motor imagery are usually collected to calibrate a subject-specific model for classifying the EEG data during the evaluation phase of motor imagery Brain-Computer Interface (BCI). However, there is no direct objective measure to determine if a subject is performing motor imagery correctly for proper calibration. Studies have shown that passive movement, which is directly observable, induces Event-Related Synchronization patterns that are similar to those induced from motor imagery. Hence, this paper investigates the feasibility of calibrating EEG-based motor imagery BCI from passive movement. EEG data of 12 healthy subjects were collected during motor imagery and passive movement of the hand by a haptic knob robot. The calibration models using the Filter Bank Common Spatial Pattern algorithm on the EEG data from motor imagery were compared against using the EEG data from passive movement. The performances were compared based on the 10×10-fold cross-validation accuracies of the calibration data, and off-line session-to-session transfer kappa values to other sessions of motor imagery performed on another day. The results showed that the calibration performed using passive movement yielded higher model accuracy and off-line session-to-session transfer (73.6% and 0.354) than the calibration performed using motor imagery (71.3% and 0.311), and no significant differences were observed between the two groups (p=0.20, 0.23). Hence, this study shows that it is feasible to calibrate EEG-based motor imagery BCI from passive movement.

  20. Impact spacecraft imagery and comparative morphology of craters

    International Nuclear Information System (INIS)

    Moutsoulas, M.; Piteri, S.

    1979-01-01

    The use of hard-landing 'simple' missions for wide-scale planetary exploration is considered. As an example of their imagery potentialities, Ranger VII data are used for the study of the morphological characteristics of 16 Mare Cognitum craters. The morphological patterns of lunar craters, expressed in terms of the Depth/Diameter ratios appear to be in most cases independent of the crater location or size. (Auth.)

  1. Electrophysiological potentials reveal cortical mechanisms for mental imagery, mental simulation, and grounded (embodied cognition

    Directory of Open Access Journals (Sweden)

    Haline E. Schendan

    2012-09-01

    Full Text Available Grounded cognition theory proposes that cognition, including meaning, is grounded in sensorimotor processing. The mechanism for grounding cognition is mental simulation, which is a type of mental imagery that re-enacts modal processing. To reveal top-down, cortical mechanisms for mental simulation of shape, event-related potentials were recorded to face and object pictures preceded by mental imagery of a picture. Mental imagery of the identical face or object (congruous condition facilitated not only categorical perception (VPP/N170 but also later visual knowledge (N3[00] complex and linguistic knowledge (N400 for faces more than objects, and strategic semantic analysis (late positive complex between 200 and 700 ms. The later effects resembled semantic congruity effects with pictures. Mental imagery also facilitated category decisions, as a P3(00 peaked earlier for congruous than incongruous (other category pictures, resembling the case when identical pictures repeat immediately. Thus mental imagery mimics semantic congruity and immediate repetition priming processes with pictures. Perception control results showed the opposite for faces and were in the same direction for objects: Perceptual repetition adapts (and so impairs processing of perceived faces from categorical perception onwards, but primes processing of objects during categorical perception, visual knowledge processes, and strategic semantic analysis. For both imagery and perception, differences between faces and objects support domain-specificity and indicate that cognition is grounded in modal processing. Altogether, this direct neural evidence reveals that top-down processes of mental imagery sustain an imagistic representation that mimics perception well enough to prime subsequent perception and cognition. This also suggests that automatic mental simulation of the visual shape of faces and objects operates between 200 and 400 ms, and strategic mental simulation operates between

  2. Bistatic SAR: Imagery & Image Products.

    Energy Technology Data Exchange (ETDEWEB)

    Yocky, David A.; Wahl, Daniel E.; Jakowatz, Charles V,

    2014-10-01

    While typical SAR imaging employs a co-located (monostatic) RADAR transmitter and receiver, bistatic SAR imaging separates the transmitter and receiver locations. The transmitter and receiver geometry determines if the scattered signal is back scatter, forward scatter, or side scatter. The monostatic SAR image is backscatter. Therefore, depending on the transmitter/receiver collection geometry, the captured imagery may be quite different that that sensed at the monostatic SAR. This document presents imagery and image products formed from captured signals during the validation stage of the bistatic SAR research. Image quality and image characteristics are discussed first. Then image products such as two-color multi-view (2CMV) and coherent change detection (CCD) are presented.

  3. Resolution Enhancement of Multilook Imagery

    Energy Technology Data Exchange (ETDEWEB)

    Galbraith, Amy E. [Univ. of Arizona, Tucson, AZ (United States)

    2004-07-01

    This dissertation studies the feasibility of enhancing the spatial resolution of multi-look remotely-sensed imagery using an iterative resolution enhancement algorithm known as Projection Onto Convex Sets (POCS). A multi-angle satellite image modeling tool is implemented, and simulated multi-look imagery is formed to test the resolution enhancement algorithm. Experiments are done to determine the optimal con guration and number of multi-angle low-resolution images needed for a quantitative improvement in the spatial resolution of the high-resolution estimate. The important topic of aliasing is examined in the context of the POCS resolution enhancement algorithm performance. In addition, the extension of the method to multispectral sensor images is discussed and an example is shown using multispectral confocal fluorescence imaging microscope data. Finally, the remote sensing issues of atmospheric path radiance and directional reflectance variations are explored to determine their effect on the resolution enhancement performance.

  4. Visuospatial imagery and working memory in schizophrenia.

    Science.gov (United States)

    Matthews, Natasha L; Collins, Kathleen P; Thakkar, Katharine N; Park, Sohee

    2014-01-01

    The ability to form mental images that reconstruct former perceptual experiences is closely related to working memory (WM) ability. However, whereas WM deficits are established as a core feature of schizophrenia, an independent body of work suggests that mental imagery ability is enhanced in the disorder. Across two experiments we investigated mental imagery in schizophrenia and its relationship with WM. In Experiment 1, individuals with schizophrenia (SZ: n=15) and matched controls (CO: n=14) completed a mental imagery generation and inspection task and a spatial delayed-response WM task. In Experiment 2, SZ (n=16) and CO (n=16) completed a novel version of the mental imagery task modified to increase WM maintenance demand. In Experiment 1, SZ demonstrated enhanced mental imagery performance, as evidenced by faster response times relative to CO, with preserved accuracy. However, enhanced mental imagery in SZ was accompanied by impaired WM as assessed by the delayed-response task. In Experiment 2, when WM maintenance load was increased, SZ no longer showed superior imagery performance. We found evidence for enhanced imagery manipulation in SZ despite their WM maintenance deficit. However, this imagery enhancement was abolished when WM maintenance demands were increased. This profile of enhanced imagery manipulation but impaired maintenance could be used to implement novel remediation strategies in the disorder.

  5. User Validation of VIIRS Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Don Hillger

    2015-12-01

    Full Text Available Visible/Infrared Imaging Radiometer Suite (VIIRS Imagery from the Suomi National Polar-orbiting Partnership (S-NPP satellite is the finest spatial resolution (375 m multi-spectral imagery of any operational meteorological satellite to date. The Imagery environmental data record (EDR has been designated as a Key Performance Parameter (KPP for VIIRS, meaning that its performance is vital to the success of a series of Joint Polar Satellite System (JPSS satellites that will carry this instrument. Because VIIRS covers the high-latitude and Polar Regions especially well via overlapping swaths from adjacent orbits, the Alaska theatre in particular benefits from VIIRS more than lower-latitude regions. While there are no requirements that specifically address the quality of the EDR Imagery aside from the VIIRS SDR performance requirements, the value of VIIRS Imagery to operational users is an important consideration in the Cal/Val process. As such, engaging a wide diversity of users constitutes a vital part of the Imagery validation strategy. The best possible image quality is of utmost importance. This paper summarizes the Imagery Cal/Val Team’s quality assessment in this context. Since users are a vital component to the validation of VIIRS Imagery, specific examples of VIIRS imagery applied to operational needs are presented as an integral part of the post-checkout Imagery validation.

  6. Landsat imagery: a unique resource

    Science.gov (United States)

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

    2011-01-01

    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).

  7. Radio-marking and in vivo imagery of oligonucleotides

    International Nuclear Information System (INIS)

    Kuehnast, Bertrand

    2000-01-01

    This research thesis is part of activities aimed at the development of new molecules like oligonucleotides. Its first objective was the development and validation of a marking method with fluorine-18 of oligonucleotides for their in-vivo pharmacological assessment with positron emission tomography (PET). Further investigations addressed the use of iodine-125 for oligonucleotide marking purpose. This radio-marking, and in vivo and ex vivo imagery techniques are described, and their potential is highlighted for the pharmacological assessment of different oligonucleotides

  8. Information fusion performance evaluation for motion imagery data using mutual information: initial study

    Science.gov (United States)

    Grieggs, Samuel M.; McLaughlin, Michael J.; Ezekiel, Soundararajan; Blasch, Erik

    2015-06-01

    As technology and internet use grows at an exponential rate, video and imagery data is becoming increasingly important. Various techniques such as Wide Area Motion imagery (WAMI), Full Motion Video (FMV), and Hyperspectral Imaging (HSI) are used to collect motion data and extract relevant information. Detecting and identifying a particular object in imagery data is an important step in understanding visual imagery, such as content-based image retrieval (CBIR). Imagery data is segmented and automatically analyzed and stored in dynamic and robust database. In our system, we seek utilize image fusion methods which require quality metrics. Many Image Fusion (IF) algorithms have been proposed based on different, but only a few metrics, used to evaluate the performance of these algorithms. In this paper, we seek a robust, objective metric to evaluate the performance of IF algorithms which compares the outcome of a given algorithm to ground truth and reports several types of errors. Given the ground truth of a motion imagery data, it will compute detection failure, false alarm, precision and recall metrics, background and foreground regions statistics, as well as split and merge of foreground regions. Using the Structural Similarity Index (SSIM), Mutual Information (MI), and entropy metrics; experimental results demonstrate the effectiveness of the proposed methodology for object detection, activity exploitation, and CBIR.

  9. Open-source algorithm for detecting sea ice surface features in high-resolution optical imagery

    Directory of Open Access Journals (Sweden)

    N. C. Wright

    2018-04-01

    Full Text Available Snow, ice, and melt ponds cover the surface of the Arctic Ocean in fractions that change throughout the seasons. These surfaces control albedo and exert tremendous influence over the energy balance in the Arctic. Increasingly available meter- to decimeter-scale resolution optical imagery captures the evolution of the ice and ocean surface state visually, but methods for quantifying coverage of key surface types from raw imagery are not yet well established. Here we present an open-source system designed to provide a standardized, automated, and reproducible technique for processing optical imagery of sea ice. The method classifies surface coverage into three main categories: snow and bare ice, melt ponds and submerged ice, and open water. The method is demonstrated on imagery from four sensor platforms and on imagery spanning from spring thaw to fall freeze-up. Tests show the classification accuracy of this method typically exceeds 96 %. To facilitate scientific use, we evaluate the minimum observation area required for reporting a representative sample of surface coverage. We provide an open-source distribution of this algorithm and associated training datasets and suggest the community consider this a step towards standardizing optical sea ice imagery processing. We hope to encourage future collaborative efforts to improve the code base and to analyze large datasets of optical sea ice imagery.

  10. Open-source algorithm for detecting sea ice surface features in high-resolution optical imagery

    Science.gov (United States)

    Wright, Nicholas C.; Polashenski, Chris M.

    2018-04-01

    Snow, ice, and melt ponds cover the surface of the Arctic Ocean in fractions that change throughout the seasons. These surfaces control albedo and exert tremendous influence over the energy balance in the Arctic. Increasingly available meter- to decimeter-scale resolution optical imagery captures the evolution of the ice and ocean surface state visually, but methods for quantifying coverage of key surface types from raw imagery are not yet well established. Here we present an open-source system designed to provide a standardized, automated, and reproducible technique for processing optical imagery of sea ice. The method classifies surface coverage into three main categories: snow and bare ice, melt ponds and submerged ice, and open water. The method is demonstrated on imagery from four sensor platforms and on imagery spanning from spring thaw to fall freeze-up. Tests show the classification accuracy of this method typically exceeds 96 %. To facilitate scientific use, we evaluate the minimum observation area required for reporting a representative sample of surface coverage. We provide an open-source distribution of this algorithm and associated training datasets and suggest the community consider this a step towards standardizing optical sea ice imagery processing. We hope to encourage future collaborative efforts to improve the code base and to analyze large datasets of optical sea ice imagery.

  11. Three-dimensional imagery by encoding sources of X rays

    International Nuclear Information System (INIS)

    Magnin, Isabelle

    1987-01-01

    This research thesis addresses the theoretical and practical study of X ray coded sources, and thus notably aims at exploring whether it would be possible to transform a standard digital radiography apparatus (as those operated in radiology hospital departments) into a low cost three-dimensional imagery system. The author first recalls the principle of conventional tomography and improvement attempts, and describes imagery techniques based on the use of encoding openings and source encoding. She reports the modelling of an imagery system based on encoded sources of X ray, and addresses the original notion of three-dimensional response for such a system. The author then addresses the reconstruction method by considering the reconstruction of a plane object, of a multi-plane object, and of real three-dimensional object. The frequency properties and the tomographic capacities of various types of source codes are analysed. She describes a prototype tomography apparatus, and presents and discusses three-dimensional actual phantom reconstructions. She finally introduces a new principle of dynamic three-dimensional radiography which implements an acquisition technique by 'gating code'. The acquisition principle should allow the reconstruction of volumes animated by periodic deformations, such as the heart for example [fr

  12. A question of intention in motor imagery.

    Science.gov (United States)

    Gabbard, Carl; Cordova, Alberto; Lee, Sunghan

    2009-03-01

    We examined the question-is the intention of completing a simulated motor action the same as the intention used in processing overt actions? Participants used motor imagery to estimate distance reachability in two conditions: Imagery-Only (IO) and Imagery-Execution (IE). With IO (red target) only a verbal estimate using imagery was given. With IE (green target) participants knew that they would actually reach after giving a verbal estimate and be judged on accuracy. After measuring actual maximum reach, used for the comparison, imagery targets were randomly presented across peripersonal- (within reach) and extrapersonal (beyond reach) space. Results indicated no difference in overall accuracy by condition, however, there was a significant distinction by space; participants were more accurate in peripersonal space. Although more research is needed, these findings support an increasing body of evidence suggesting that the neurocognitive processes (in this case, intention) driving motor imagery and overt actions are similar.

  13. Pornographic imagery and prevalence of paraphilia.

    Science.gov (United States)

    Dietz, P E; Evans, B

    1982-11-01

    The authors classified 1,760 heterosexual pornographic magazines according to the imagery of the cover photographs. Covers depicting only a woman posed alone predominated in 1970 but constituted only 10.7% of the covers in 1981. Bondage and domination imagery was the most prevalent nonormative imagery and was featured in 17.2% of the magazines. Smaller proportions of material were devoted to group sexual activity (9.8%), tranvestism and transsexualism (4.4%), and other nonnormative imagery. The authors suggest that pornographic imagery is an unobtrusive measure of the relative prevalence of those paraphilias associated with preferences for specific types of visual imagery and for which better data are lacking.

  14. NOAA GOES-R Series Advanced Baseline Imager (ABI) Level 2+ Cloud and Moisture Imagery Products (CMIP)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Cloud and Moisture Imagery product contains one or more Earth-view images with pixel values identifying brightness values that are scaled to support visual...

  15. ACCURACY COMPARISON OF VHR SYSTEMATIC-ORTHO SATELLITE IMAGERIES AGAINST VHR ORTHORECTIFIED IMAGERIES USING GCP

    Directory of Open Access Journals (Sweden)

    E. Widyaningrum

    2016-06-01

    Full Text Available The Very High Resolution (VHR satellite imageries such us Pleiades, WorldView-2, GeoEye-1 used for precise mapping purpose must be corrected from any distortion to achieve the expected accuracy. Orthorectification is performed to eliminate geometric errors of the VHR satellite imageries. Orthorectification requires main input data such as Digital Elevation Model (DEM and Ground Control Point (GCP. The VHR systematic-ortho imageries were generated using SRTM 30m DEM without using any GCP data. The accuracy value differences of VHR systematic-ortho imageries and VHR orthorectified imageries using GCP currently is not exactly defined. This study aimed to identified the accuracy comparison of VHR systematic-ortho imageries against orthorectified imageries using GCP. Orthorectified imageries using GCP created by using Rigorous model. Accuracy evaluation is calculated by using several independent check points.

  16. Monitoring Areal Snow Cover Using NASA Satellite Imagery

    Science.gov (United States)

    Harshburger, Brian J.; Blandford, Troy; Moore, Brandon

    2011-01-01

    The objective of this project is to develop products and tools to assist in the hydrologic modeling process, including tools to help prepare inputs for hydrologic models and improved methods for the visualization of streamflow forecasts. In addition, this project will facilitate the use of NASA satellite imagery (primarily snow cover imagery) by other federal and state agencies with operational streamflow forecasting responsibilities. A GIS software toolkit for monitoring areal snow cover extent and producing streamflow forecasts is being developed. This toolkit will be packaged as multiple extensions for ArcGIS 9.x and an opensource GIS software package. The toolkit will provide users with a means for ingesting NASA EOS satellite imagery (snow cover analysis), preparing hydrologic model inputs, and visualizing streamflow forecasts. Primary products include a software tool for predicting the presence of snow under clouds in satellite images; a software tool for producing gridded temperature and precipitation forecasts; and a suite of tools for visualizing hydrologic model forecasting results. The toolkit will be an expert system designed for operational users that need to generate accurate streamflow forecasts in a timely manner. The Remote Sensing of Snow Cover Toolbar will ingest snow cover imagery from multiple sources, including the MODIS Operational Snowcover Data and convert them to gridded datasets that can be readily used. Statistical techniques will then be applied to the gridded snow cover data to predict the presence of snow under cloud cover. The toolbar has the ability to ingest both binary and fractional snow cover data. Binary mapping techniques use a set of thresholds to determine whether a pixel contains snow or no snow. Fractional mapping techniques provide information regarding the percentage of each pixel that is covered with snow. After the imagery has been ingested, physiographic data is attached to each cell in the snow cover image. This data

  17. Unconscious Imagination and the Mental Imagery Debate

    Directory of Open Access Journals (Sweden)

    Berit Brogaard

    2017-05-01

    Full Text Available Traditionally, philosophers have appealed to the phenomenological similarity between visual experience and visual imagery to support the hypothesis that there is significant overlap between the perceptual and imaginative domains. The current evidence, however, is inconclusive: while evidence from transcranial brain stimulation seems to support this conclusion, neurophysiological evidence from brain lesion studies (e.g., from patients with brain lesions resulting in a loss of mental imagery but not a corresponding loss of perception and vice versa indicates that there are functional and anatomical dissociations between mental imagery and perception. Assuming that the mental imagery and perception do not overlap, at least, to the extent traditionally assumed, then the question arises as to what exactly mental imagery is and whether it parallels perception by proceeding via several functionally distinct mechanisms. In this review, we argue that even though there may not be a shared mechanism underlying vision for perception and conscious imagery, there is an overlap between the mechanisms underlying vision for action and unconscious visual imagery. On the basis of these findings, we propose a modification of Kosslyn’s model of imagery that accommodates unconscious imagination and explore possible explanations of the quasi-pictorial phenomenology of conscious visual imagery in light of the fact that its underlying neural substrates and mechanisms typically are distinct from those of visual experience.

  18. Sensory Substitution and Multimodal Mental Imagery.

    Science.gov (United States)

    Nanay, Bence

    2017-09-01

    Many philosophers use findings about sensory substitution devices in the grand debate about how we should individuate the senses. The big question is this: Is "vision" assisted by (tactile) sensory substitution really vision? Or is it tactile perception? Or some sui generis novel form of perception? My claim is that sensory substitution assisted "vision" is neither vision nor tactile perception, because it is not perception at all. It is mental imagery: visual mental imagery triggered by tactile sensory stimulation. But it is a special form of mental imagery that is triggered by corresponding sensory stimulation in a different sense modality, which I call "multimodal mental imagery."

  19. Kinesthetic motor imagery modulates body sway.

    Science.gov (United States)

    Rodrigues, E C; Lemos, T; Gouvea, B; Volchan, E; Imbiriba, L A; Vargas, C D

    2010-08-25

    The aim of this study was to investigate the effect of imagining an action implicating the body axis in the kinesthetic and visual motor imagery modalities upon the balance control system. Body sway analysis (measurement of center of pressure, CoP) together with electromyography (EMG) recording and verbal evaluation of imagery abilities were obtained from subjects during four tasks, performed in the upright position: to execute bilateral plantar flexions; to imagine themselves executing bilateral plantar flexions (kinesthetic modality); to imagine someone else executing the same movement (visual modality), and to imagine themselves singing a song (as a control imagery task). Body sway analysis revealed that kinesthetic imagery leads to a general increase in CoP oscillation, as reflected by an enhanced area of displacement. This effect was also verified for the CoP standard deviation in the medial-lateral direction. An increase in the trembling displacement (equivalent to center of pressure minus center of gravity) restricted to the anterior-posterior direction was also observed to occur during kinesthetic imagery. The visual imagery task did not differ from the control (sing) task for any of the analyzed parameters. No difference in the subjects' ability to perform the imagery tasks was found. No modulation of EMG data were observed across imagery tasks, indicating that there was no actual execution during motor imagination. These results suggest that motor imagery performed in the kinesthetic modality evokes motor representations involved in balance control. Copyright (c)10 IBRO. Published by Elsevier Ltd. All rights reserved.

  20. Assessment of motor imagery ability and training

    Directory of Open Access Journals (Sweden)

    André Luiz Felix Rodacki

    2010-09-01

    Full Text Available The aim of this study was to evaluate changes in motor imagery ability in response to a specific dart throwing training. Twelve subjects (17-22 years with no previous experience in dart throwing or imagery agreed to participate. Changes in imagery ability were assessed using the Sports Imagery Questionnaire before (pretreatment and after (post-treatment an imagery training program consisting of 10 sessions. Retention (RET was assessed 2 weeks after training. The program included mental exercises designed to develop vivid images, to control one’s own images, and to increase perception about performance. Comparison of the imagery training conditions (training alone, training accompanied, observing a colleague, and during assessment showed no differences between the pretreatment, post-treatment and RET evaluations. Although imagery ability did not respond to training, significant differences between imagery domains (visual, auditory, kinesthetic, and animic were found (p<0.05, except between the visual and animic domains (p=0.58. These differences might be related to subject’s domain preference subject during the imagery process and to the nature of the task in which the skill technique used seems to be a relevant aspect.

  1. Integration of Synthetic Aperture Radar (SAR) Imagery and Derived Products into Severe Weather Disaster Response

    Science.gov (United States)

    Schultz, L. A.; Molthan, A.; Nicoll, J. B.; Bell, J. R.; Gens, R.; Meyer, F. J.

    2017-12-01

    Disaster response efforts leveraging imagery from NASA, USGS, NOAA, and the European Space Agency (ESA) have continued to expand as satellite imagery and derived products offer an enhanced overview of the affected areas, especially in remote areas where terrain and the scale of the damage can inhibit response efforts. NASA's Short-term Prediction Research and Transition (SPoRT) Center has been supporting the NASA Earth Science Disaster Response Program by providing both optical and SAR imagery products to the NWS and FEMA to assist during domestic response efforts. Although optical imagery has dominated, the availability of ESA's Synthetic Aperture Radar (SAR) data from the Sentinel 1-A/B satellites offers a unique perspective to the damage response community as SAR imagery can be collected regardless of the time of day or the presence of clouds, two major hindrances to the use of satellite optical imagery. Through a partnership with the University of Alaska Fairbanks (UAF) and the collocated Alaska Satellite Facility (ASF), NASA's SAR Distributed Active Archive Center (DAAC), SPoRT has been investigating the use of SAR imagery products to support storm damage surveys conducted by the National Weather Service after any severe weather event. Additionally, products are also being developed and tested for FEMA and the National Guard Bureau. This presentation will describe how SAR data from the Sentinel 1A/B satellites are processed and developed into products. Examples from multiple tornado and hail events will be presented highlighting both the strengths and weaknesses of SAR imagery and how it integrates and compliments more traditional optical imagery collected post-event. Specific case study information from a large hail event in South Dakota and a long track tornado near Clear Lake, Wisconsin will be discussed as well as an overview of the work being done to support FEMA and the National Guard.

  2. The influence of multi-season imagery on models of canopy cover: A case study

    Science.gov (United States)

    John W. Coulston; Dennis M. Jacobs; Chris R. King; Ivey C. Elmore

    2013-01-01

    Quantifying tree canopy cover in a spatially explicit fashion is important for broad-scale monitoring of ecosystems and for management of natural resources. Researchers have developed empirical models of tree canopy cover to produce geospatial products. For subpixel models, percent tree canopy cover estimates (derived from fine-scale imagery) serve as the response...

  3. Vegetation cover in relation to socioeconomic factors in a tropical city assessed from sub-meter resolution imagery.

    Science.gov (United States)

    Martinuzzi, Sebastián; Ramos-González, Olga M; Muñoz-Erickson, Tischa A; Locke, Dexter H; Lugo, Ariel E; Radeloff, Volker C

    2018-04-01

    Fine-scale information about urban vegetation and social-ecological relationships is crucial to inform both urban planning and ecological research, and high spatial resolution imagery is a valuable tool for assessing urban areas. However, urban ecology and remote sensing have largely focused on cities in temperate zones. Our goal was to characterize urban vegetation cover with sub-meter (urban vegetation patterns in a tropical city, the San Juan Metropolitan Area, Puerto Rico. Our specific objectives were to (1) map vegetation cover using sub-meter spatial resolution (0.3-m) imagery, (2) quantify the amount of residential and non-residential vegetation, and (3) investigate the relationship between patterns of urban vegetation vs. socioeconomic and environmental factors. We found that 61% of the San Juan Metropolitan Area was green and that our combination of high spatial resolution imagery and object-based classification was highly successful for extracting vegetation cover in a moist tropical city (97% accuracy). In addition, simple spatial pattern analysis allowed us to separate residential from non-residential vegetation with 76% accuracy, and patterns of residential and non-residential vegetation varied greatly across the city. Both socioeconomic (e.g., population density, building age, detached homes) and environmental variables (e.g., topography) were important in explaining variations in vegetation cover in our spatial regression models. However, important socioeconomic drivers found in cities in temperate zones, such as income and home value, were not important in San Juan. Climatic and cultural differences between tropical and temperate cities may result in different social-ecological relationships. Our study provides novel information for local land use planners, highlights the value of high spatial resolution remote sensing data to advance ecological research and urban planning in tropical cities, and emphasizes the need for more studies in tropical

  4. [French norms of imagery for pictures, for concrete and abstract words].

    Science.gov (United States)

    Robin, Frédérique

    2006-09-01

    This paper deals with French norms for mental image versus picture agreement for 138 pictures and the imagery value for 138 concrete words and 69 abstract words. The pictures were selected from Snodgrass et Vanderwart's norms (1980). The concrete words correspond to the dominant naming response to the pictorial stimuli. The abstract words were taken from verbal associative norms published by Ferrand (2001). The norms were established according to two variables: 1) mental image vs. picture agreement, and 2) imagery value of words. Three other variables were controlled: 1) picture naming agreement; 2) familiarity of objects referred to in the pictures and the concrete words, and 3) subjective verbal frequency of words. The originality of this work is to provide French imagery norms for the three kinds of stimuli usually compared in research on dual coding. Moreover, these studies focus on figurative and verbal stimuli variations in visual imagery processes.

  5. OrthoImagery Submission for Isabella county, MI

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — This data set contains 1-meter resolution imagery derived from the 2005 National Agriculture Imagery Program (NAIP) statewide aerial imagery acquisition. Data have...

  6. Visual memory and visual mental imagery recruit common control and sensory regions of the brain.

    Science.gov (United States)

    Slotnick, Scott D; Thompson, William L; Kosslyn, Stephen M

    2012-01-01

    Separate lines of research have shown that visual memory and visual mental imagery are mediated by frontal-parietal control regions and can rely on occipital-temporal sensory regions of the brain. We used fMRI to assess the degree to which visual memory and visual mental imagery rely on the same neural substrates. During the familiarization/study phase, participants studied drawings of objects. During the test phase, words corresponding to old and new objects were presented. In the memory test, participants responded "remember," "know," or "new." In the imagery test, participants responded "high vividness," "moderate vividness," or "low vividness." Visual memory (old-remember) and visual imagery (old-high vividness) were commonly associated with activity in frontal-parietal control regions and occipital-temporal sensory regions. In addition, visual memory produced greater activity than visual imagery in parietal and occipital-temporal regions. The present results suggest that visual memory and visual imagery rely on highly similar--but not identical--cognitive processes.

  7. Advances in the Processing of VHR Optical Imagery in Support of Safeguards Verification

    International Nuclear Information System (INIS)

    Niemeyer, I.; Listner, C.; Canty, M.

    2015-01-01

    Under the Additional Protocol of the Non-Proliferation Treaty (NPT) complementing the safeguards agreements between States and the International Atomic Energy Agency, commercial satellite imagery, preferably acquired by very high-resolution (VHR) satellite sensors, is an important source of safeguards-relevant information. Satellite imagery can assist in the evaluation of site declarations, design information verification, the detection of undeclared nuclear facilities, and the preparation of inspections or other visits. With the IAEA's Geospatial Exploitation System (GES), satellite imagery and other geospatial information such as site plans of nuclear facilities are available for a broad range of inspectors, analysts and country officers. The demand for spatial information and new tools to analyze this data is growing, together with the rising number of nuclear facilities under safeguards worldwide. Automated computer-driven processing of satellite imagery could therefore add a big value in the safeguards verification process. These could be, for example, satellite imagery pre-processing algorithms specially developed for new sensors, tools for pixel or object-based image analysis, or geoprocessing tools that generate additional safeguards-relevant information. In the last decade procedures for automated (pre-) processing of satellite imagery have considerably evolved. This paper aims at testing some pixel-based and object-based procedures for automated change detection and classification in support of safeguards verification. Taking different nuclear sites as examples, these methods will be evaluated and compared with regard to their suitability to (semi-) automatically extract safeguards-relevant information. (author)

  8. Can motor imagery and hypnotic susceptibility explain Conversion Disorder with motor symptoms?

    Science.gov (United States)

    Srzich, Alexander J; Byblow, Winston D; Stinear, James W; Cirillo, John; Anson, J Greg

    2016-08-01

    Marked distortions in sense of agency can be induced by hypnosis in susceptible individuals, including alterations in subjective awareness of movement initiation and control. These distortions, with associated disability, are similar to those experienced with Conversion Disorder (CD), an observation that has led to the hypothesis that hypnosis and CD share causal mechanisms. The purpose of this review is to explore the relationships among motor imagery (MI), hypnotic susceptibility, and CD, then to propose how MI ability may contribute to hypnotic responding and CD. Studies employing subjective assessments of mental imagery have found little association between imagery abilities and hypnotic susceptibility. A positive association between imagery abilities and hypnotic susceptibility becomes apparent when objective measures of imagery ability are employed. A candidate mechanism to explain motor responses during hypnosis is kinaesthetic MI, which engages a strategy that involves proprioception or the "feel" of movement when no movement occurs. Motor suppression imagery (MSI), a strategy involving inhibition of movement, may provide an alternate objective measurable phenomenon that underlies both hypnotic susceptibility and CD. Evidence to date supports the idea that there may be a positive association between kinaesthetic MI ability and hypnotic susceptibility. Additional evidence supports a positive association between hypnotic susceptibility and CD. Disturbances in kinaesthetic MI performance in CD patients indicate that MI mechanisms may also underlie CD symptoms. Further investigation of the above relationships is warranted to explain these phenomena, and establish theoretical explanations underlying sense of agency. Copyright © 2016. Published by Elsevier Ltd.

  9. Thematic mapping from satellite imagery

    CERN Document Server

    Denègre, J

    2013-01-01

    Thematic Mapping from Satellite Imagery: A Guidebook discusses methods in producing maps using satellite images. The book is comprised of five chapters; each chapter covers one stage of the process. Chapter 1 tackles the satellite remote sensing imaging and its cartographic significance. Chapter 2 discusses the production processes for extracting information from satellite data. The next chapter covers the methods for combining satellite-derived information with that obtained from conventional sources. Chapter 4 deals with design and semiology for cartographic representation, and Chapter 5 pre

  10. An approach for flood monitoring by the combined use of Landsat 8 optical imagery and COSMO-SkyMed radar imagery

    Science.gov (United States)

    Tong, Xiaohua; Luo, Xin; Liu, Shuguang; Xie, Huan; Chao, Wei; Liu, Shuang; Liu, Shijie; Makhinov, A. N.; Makhinova, A. F.; Jiang, Yuying

    2018-02-01

    Remote sensing techniques offer potential for effective flood detection with the advantages of low-cost, large-scale, and real-time surface observations. The easily accessible data sources of optical remote sensing imagery provide abundant spectral information for accurate surface water body extraction, and synthetic aperture radar (SAR) systems represent a powerful tool for flood monitoring because of their all-weather capability. This paper introduces a new approach for flood monitoring by the combined use of both Landsat 8 optical imagery and COSMO-SkyMed radar imagery. Specifically, the proposed method applies support vector machine and the active contour without edges model for water extent determination in the periods before and during the flood, respectively. A map difference method is used for the flood inundation analysis. The proposed approach is particularly suitable for large-scale flood monitoring, and it was tested on a serious flood that occurred in northeastern China in August 2013, which caused immense loss of human lives and properties. High overall accuracies of 97.46% for the optical imagery and 93.70% for the radar imagery are achieved by the use of the techniques presented in this study. The results show that about 12% of the whole study area was inundated, corresponding to 5466 km2 of land surface.

  11. Biomass burning: Combustion emissions, satellite imagery, and biogenic emissions

    International Nuclear Information System (INIS)

    Levine, J.S.; Cofer, W.R III; Rhinehart, R.P.; Cahoon, D.R. J.; Winstead, E.L.; Sebacher, S.; Sebacher, D.I.; Stocks, B.J.

    1991-01-01

    This chapter deals with two different, but related, aspects of biomass burning. The first part of the chapter deals with a technique to estimate the instantaneous emissions of trace gases produced by biomass burning using satellite imagery. The second part of the chapter concerns the recent discovery that burning results in significantly enhanced biogenic emissions of N 2 O, NO, and CH 4 . Hence, biomass burning has both an immediate and long-term impact on the production of trace gases to the atmosphere. The objective of this research is to better assess and quantify the role of this research is to better assess and quantify the role and impact of biomass as a driver for global change. It will be demonstrated that satellite imagery of fires may be used to estimate combustion emissions and may in the future be used to estimate the long-term postburn biogenic emissions of trace gases to the atmosphere

  12. Fully Convolutional Network Based Shadow Extraction from GF-2 Imagery

    Science.gov (United States)

    Li, Z.; Cai, G.; Ren, H.

    2018-04-01

    There are many shadows on the high spatial resolution satellite images, especially in the urban areas. Although shadows on imagery severely affect the information extraction of land cover or land use, they provide auxiliary information for building extraction which is hard to achieve a satisfactory accuracy through image classification itself. This paper focused on the method of building shadow extraction by designing a fully convolutional network and training samples collected from GF-2 satellite imagery in the urban region of Changchun city. By means of spatial filtering and calculation of adjacent relationship along the sunlight direction, the small patches from vegetation or bridges have been eliminated from the preliminary extracted shadows. Finally, the building shadows were separated. The extracted building shadow information from the proposed method in this paper was compared with the results from the traditional object-oriented supervised classification algorihtms. It showed that the deep learning network approach can improve the accuracy to a large extent.

  13. Alcohol imagery on New Zealand television

    Directory of Open Access Journals (Sweden)

    Reeder Anthony I

    2007-02-01

    Full Text Available Abstract Background To examine the extent and nature of alcohol imagery on New Zealand (NZ television, a content analysis of 98 hours of prime-time television programs and advertising was carried out over 7 consecutive days' viewing in June/July 2004. The main outcome measures were number of scenes in programs, trailers and advertisements depicting alcohol imagery; the extent of critical versus neutral and promotional imagery; and the mean number of scenes with alcohol per hour, and characteristics of scenes in which alcohol featured. Results There were 648 separate depictions of alcohol imagery across the week, with an average of one scene every nine minutes. Scenes depicting uncritical imagery outnumbered scenes showing possible adverse health consequences of drinking by 12 to 1. Conclusion The evidence points to a large amount of alcohol imagery incidental to storylines in programming on NZ television. Alcohol is also used in many advertisements to market non-alcohol goods and services. More attention needs to be paid to the extent of alcohol imagery on television from the industry, the government and public health practitioners. Health education with young people could raise critical awareness of the way alcohol imagery is presented on television.

  14. Imagery, Music, Cognitive Style and Memory.

    Science.gov (United States)

    Stratton, Valerie N.; Zalanowski, Annette

    Paired associate memory was tested with imagery and repetition instructions, with and without background music. Subjects were 64 students enrolled in an introductory psychology course. Music was found to have no effect with imagery instructions, but significantly improved performance with the repetition instructions. Music had different effects on…

  15. Mental Imagery in Creative Problem Solving.

    Science.gov (United States)

    Polland, Mark J.

    In order to investigate the relationship between mental imagery and creative problem solving, a study of 44 separate accounts reporting mental imagery experiences associated with creative discoveries were examined. The data included 29 different scientists, among them Albert Einstein and Stephen Hawking, and 9 artists, musicians, and writers,…

  16. Mental Imagery and Visual Working Memory

    Science.gov (United States)

    Keogh, Rebecca; Pearson, Joel

    2011-01-01

    Visual working memory provides an essential link between past and future events. Despite recent efforts, capacity limits, their genesis and the underlying neural structures of visual working memory remain unclear. Here we show that performance in visual working memory - but not iconic visual memory - can be predicted by the strength of mental imagery as assessed with binocular rivalry in a given individual. In addition, for individuals with strong imagery, modulating the background luminance diminished performance on visual working memory and imagery tasks, but not working memory for number strings. This suggests that luminance signals were disrupting sensory-based imagery mechanisms and not a general working memory system. Individuals with poor imagery still performed above chance in the visual working memory task, but their performance was not affected by the background luminance, suggesting a dichotomy in strategies for visual working memory: individuals with strong mental imagery rely on sensory-based imagery to support mnemonic performance, while those with poor imagery rely on different strategies. These findings could help reconcile current controversy regarding the mechanism and location of visual mnemonic storage. PMID:22195024

  17. Mental imagery and visual working memory.

    Directory of Open Access Journals (Sweden)

    Rebecca Keogh

    Full Text Available Visual working memory provides an essential link between past and future events. Despite recent efforts, capacity limits, their genesis and the underlying neural structures of visual working memory remain unclear. Here we show that performance in visual working memory--but not iconic visual memory--can be predicted by the strength of mental imagery as assessed with binocular rivalry in a given individual. In addition, for individuals with strong imagery, modulating the background luminance diminished performance on visual working memory and imagery tasks, but not working memory for number strings. This suggests that luminance signals were disrupting sensory-based imagery mechanisms and not a general working memory system. Individuals with poor imagery still performed above chance in the visual working memory task, but their performance was not affected by the background luminance, suggesting a dichotomy in strategies for visual working memory: individuals with strong mental imagery rely on sensory-based imagery to support mnemonic performance, while those with poor imagery rely on different strategies. These findings could help reconcile current controversy regarding the mechanism and location of visual mnemonic storage.

  18. Mental imagery and visual working memory.

    Science.gov (United States)

    Keogh, Rebecca; Pearson, Joel

    2011-01-01

    Visual working memory provides an essential link between past and future events. Despite recent efforts, capacity limits, their genesis and the underlying neural structures of visual working memory remain unclear. Here we show that performance in visual working memory--but not iconic visual memory--can be predicted by the strength of mental imagery as assessed with binocular rivalry in a given individual. In addition, for individuals with strong imagery, modulating the background luminance diminished performance on visual working memory and imagery tasks, but not working memory for number strings. This suggests that luminance signals were disrupting sensory-based imagery mechanisms and not a general working memory system. Individuals with poor imagery still performed above chance in the visual working memory task, but their performance was not affected by the background luminance, suggesting a dichotomy in strategies for visual working memory: individuals with strong mental imagery rely on sensory-based imagery to support mnemonic performance, while those with poor imagery rely on different strategies. These findings could help reconcile current controversy regarding the mechanism and location of visual mnemonic storage.

  19. Toward automated face detection in thermal and polarimetric thermal imagery

    Science.gov (United States)

    Gordon, Christopher; Acosta, Mark; Short, Nathan; Hu, Shuowen; Chan, Alex L.

    2016-05-01

    Visible spectrum face detection algorithms perform pretty reliably under controlled lighting conditions. However, variations in illumination and application of cosmetics can distort the features used by common face detectors, thereby degrade their detection performance. Thermal and polarimetric thermal facial imaging are relatively invariant to illumination and robust to the application of makeup, due to their measurement of emitted radiation instead of reflected light signals. The objective of this work is to evaluate a government off-the-shelf wavelet based naïve-Bayes face detection algorithm and a commercial off-the-shelf Viola-Jones cascade face detection algorithm on face imagery acquired in different spectral bands. New classifiers were trained using the Viola-Jones cascade object detection framework with preprocessed facial imagery. Preprocessing using Difference of Gaussians (DoG) filtering reduces the modality gap between facial signatures across the different spectral bands, thus enabling more correlated histogram of oriented gradients (HOG) features to be extracted from the preprocessed thermal and visible face images. Since the availability of training data is much more limited in the thermal spectrum than in the visible spectrum, it is not feasible to train a robust multi-modal face detector using thermal imagery alone. A large training dataset was constituted with DoG filtered visible and thermal imagery, which was subsequently used to generate a custom trained Viola-Jones detector. A 40% increase in face detection rate was achieved on a testing dataset, as compared to the performance of a pre-trained/baseline face detector. Insights gained in this research are valuable in the development of more robust multi-modal face detectors.

  20. Observer perspective imagery with stuttering.

    Science.gov (United States)

    Lowe, Robyn; Menzies, Ross; Packman, Ann; O'Brian, Sue; Onslow, Mark

    2015-01-01

    Adults who stutter are at risk of developing a range of psychological conditions. Social anxiety disorder is the most common anxiety disorder associated with stuttering. Observer perspective imagery is one cognitive process involved in the maintenance of some anxiety disorders. This involves viewing images as if looking at the self from the perspective of another. In contrast, the field perspective involves looking out from the self at the surrounding environment. The purpose of this study was to assess the presence of observer perspective imagery with stuttering. The authors administered the Hackmann, Surawy and Clark (1998) semi-structured interview to 30 adults who stutter and 30 controls. Group images and impressions were compared for frequency, perspective recalled and emotional valence. The stuttering group was significantly more likely than controls to recall images and impressions from an observer rather than a field perspective for anxious situations. It is possible the present results could reflect the same attentional processing bias that occurs with anxiety disorders in the non-stuttering population. These preliminary results provide an explanation for the persistence of conditions such as social anxiety disorder with stuttering. Clinical implications are discussed.

  1. Guided Imagery and Stress in Pregnant Adolescents.

    Science.gov (United States)

    Flynn, Theresa A; Jones, Brittney A; Ausderau, Karla K

    2016-01-01

    We examined the effects of a guided imagery intervention on perceived stress in pregnant adolescents. Thirty-five pregnant adolescents recruited from a local alternative education program participated in a guided imagery intervention. Participants listened to a pregnancy-specific guided imagery recording on four separate occasions during their pregnancies. Perceived stress was measured immediately before and after each session using the Perceived Stress Measure-9 (PSM-9). Participants' pre- and postsession PSM-9 scores for three of the four sessions demonstrated a significant reduction in stress. Participants' baseline stress levels also decreased significantly across the four listening sessions. The greatest reductions in stress within and between sessions occurred in the early sessions, with effects diminishing over time. Pregnant teens experienced initial short- and long-term stress reduction during a guided imagery intervention, supporting the use of guided imagery to reduce stress in pregnant adolescents. Copyright © 2016 by the American Occupational Therapy Association, Inc.

  2. Coded aperture imagery filtered autocorrelation decoding; Imagerie par ouverture de codage decodage par autocorrelation filtree

    Energy Technology Data Exchange (ETDEWEB)

    Rouyer, A. [CEA Bruyeres-le-Chatel, 91 (France)

    2005-10-15

    Coded aperture imagery is particularly suited for imaging objects emitting penetrating radiation (hard X rays, gamma, neutrons), or for particles with rectilinear trajectories (electrons, protons, alpha particles, etc.). It is used when methods based on classical optical principles (reflection, refraction, diffraction), are invalid, or when the source emission is too weak for the well known pinhole method to give a usable image. The optical system consists in an aperture through an absorbing screen, named coding aperture, whose transmission is calculated in such a way that the spatial resolution is similar to that of a simple pinhole device, but with a far superior radiation collecting efficiency. We present a new decoding method,, called filtered autocorrelation, and illustrate its performances on images obtained with various coding apertures. (author)

  3. Enhanced processing of SPOT multispectral satellite imagery for environmental monitoring and modelling

    Energy Technology Data Exchange (ETDEWEB)

    Clark, B.

    2010-07-01

    acquisition were available. The proposed historical empirical line method (HELM) for absolute atmospheric correction was found to be the only applied technique that could derive (rho{sub s}) within an RMSE of < 0.02 (rho{sub s}) in the SPOT visible and near-infrared bands; an accuracy level identified as a benchmark for successful atmospheric correction. A multi-scale segmentation/object relationship modelling (MSS/ORM) approach was applied to map LULC in the Taita Hills from the multi-temporal SPOT imagery. This object-based procedure was shown to derive significant improvements over a uni-scale maximum-likelihood technique. The derived LULC data was used in combination with low cost GIS geospatial layers describing elevation, rainfall and soil type, to model degradation in the Taita Hills in the form of potential soil loss, utilizing the simple universal soil loss equation (USLE). Furthermore, human population distribution and abundance were modelled with satisfactory results using only SPOT and GIS derived data and non-Gaussian predictive modelling techniques. The SPOT derived LULC data was found to be unnecessary as a predictor because the first and second order image texture measurements had greater power to explain variation in dwelling unit occurrence and abundance. The ability of the procedures to be implemented locally in the developing world using low-cost or freely available data and software was considered. The techniques discussed in this thesis are considered equally applicable to other medium and high-resolution optical satellite imagery, as well the utilized SPOT data. (orig.)

  4. Phenomenological Reliving and Visual Imagery During Autobiographical Recall in Alzheimer's Disease.

    Science.gov (United States)

    El Haj, Mohamad; Kapogiannis, Dimitrios; Antoine, Pascal

    2016-03-16

    Multiple studies have shown compromise of autobiographical memory and phenomenological reliving in Alzheimer's disease (AD). We investigated various phenomenological features of autobiographical memory to determine their relative vulnerability in AD. To this aim, participants with early AD and cognitively normal older adult controls were asked to retrieve an autobiographical event and rate on a five-point scale metacognitive judgments (i.e., reliving, back in time, remembering, and realness), component processes (i.e., visual imagery, auditory imagery, language, and emotion), narrative properties (i.e., rehearsal and importance), and spatiotemporal specificity (i.e., spatial details and temporal details). AD participants showed lower general autobiographical recall than controls, and poorer reliving, travel in time, remembering, realness, visual imagery, auditory imagery, language, rehearsal, and spatial detail-a decrease that was especially pronounced for visual imagery. Yet, AD participants showed high rating for emotion and importance. Early AD seems to compromise many phenomenological features, especially visual imagery, but also seems to preserve some other features.

  5. Phase 2 Final Report. IAEA Safeguards: Implementation blueprint of commercial satellite imagery

    Energy Technology Data Exchange (ETDEWEB)

    Andersson, Christer [SSC Satellitbild AB, Solna (Sweden)

    2000-01-01

    This document - IAEA Safeguards: Implementation Blueprint of Commercial Satellite Imagery - constitutes the second report from SSC Satellitbild giving a structured view and solid guidelines on how to proceed with a conceivable implementation of satellite imagery to support Safeguards activities of the Agency. This Phase 2 report presents a large number of concrete recommendations regarding suggested management issues, work organisation, imagery purchasing and team building. The study has also resulted in several lists of actions and preliminary project plans with GANT schedules concerning training, hardware and software, as well as for the initial pilot studies. In both the Phase 1 and Phase 2 studies it is confirmed that the proposed concept of a relatively small Imagery Unit using high-resolution data will be a sound and feasible undertaking. Such a unit capable of performing advanced image processing as a tool for various safeguard tasks will give the Agency an effective instrument for reference, monitoring, verification, and detection of declared and undeclared activities. The total cost for implementing commercial satellite imagery at the Department for Safeguards, as simulated in these studies, is approximately MUSD 1,5 per year. This cost is founded on an activity scenario with a staff of 4 experts working in an IAEA Imagery Unit with a workload of three dossiers or issues per week. The imagery unit is built around an advanced PC image processing system capable of handling several hundreds of pre-processed images per year. Alternatively a Reduced Scenario with a staff of 3 would need a budget of approximately MUSD 0,9 per year, whereas an Enhanced Imagery Unit including 5 experts and a considerably enlarged capacity would cost MUSD 1,7 per year. The Imagery Unit should be organised so it clearly reflects the objectives and role as set by the Member States and the management of the Agency. We recommend the Imagery Unit to be organised into four main work

  6. Phase 2 Final Report. IAEA Safeguards: Implementation blueprint of commercial satellite imagery

    International Nuclear Information System (INIS)

    Andersson, Christer

    2000-01-01

    This document - IAEA Safeguards: Implementation Blueprint of Commercial Satellite Imagery - constitutes the second report from SSC Satellitbild giving a structured view and solid guidelines on how to proceed with a conceivable implementation of satellite imagery to support Safeguards activities of the Agency. This Phase 2 report presents a large number of concrete recommendations regarding suggested management issues, work organisation, imagery purchasing and team building. The study has also resulted in several lists of actions and preliminary project plans with GANT schedules concerning training, hardware and software, as well as for the initial pilot studies. In both the Phase 1 and Phase 2 studies it is confirmed that the proposed concept of a relatively small Imagery Unit using high-resolution data will be a sound and feasible undertaking. Such a unit capable of performing advanced image processing as a tool for various safeguard tasks will give the Agency an effective instrument for reference, monitoring, verification, and detection of declared and undeclared activities. The total cost for implementing commercial satellite imagery at the Department for Safeguards, as simulated in these studies, is approximately MUSD 1,5 per year. This cost is founded on an activity scenario with a staff of 4 experts working in an IAEA Imagery Unit with a workload of three dossiers or issues per week. The imagery unit is built around an advanced PC image processing system capable of handling several hundreds of pre-processed images per year. Alternatively a Reduced Scenario with a staff of 3 would need a budget of approximately MUSD 0,9 per year, whereas an Enhanced Imagery Unit including 5 experts and a considerably enlarged capacity would cost MUSD 1,7 per year. The Imagery Unit should be organised so it clearly reflects the objectives and role as set by the Member States and the management of the Agency. We recommend the Imagery Unit to be organised into four main work

  7. Colors in mind: a novel paradigm to investigate pure color imagery.

    Science.gov (United States)

    Wantz, Andrea L; Borst, Grégoire; Mast, Fred W; Lobmaier, Janek S

    2015-07-01

    Mental color imagery abilities are commonly measured using paradigms that involve naming, judging, or comparing the colors of visual mental images of well-known objects (e.g., "Is a sunflower darker yellow than a lemon"?). Although this approach is widely used in patient studies, differences in the ability to perform such color comparisons might simply reflect participants' general knowledge of object colors rather than their ability to generate accurate visual mental images of the colors of the objects. The aim of the present study was to design a new color imagery paradigm. Participants were asked to visualize a color for 3 s and then to determine a visually presented color by pressing 1 of 6 keys. We reasoned that participants would react faster when the imagined and perceived colors were congruent than when they were incongruent. In Experiment 1, participants were slower in incongruent than congruent trials but only when they were instructed to visualize the colors. The results in Experiment 2 demonstrate that the congruency effect reported in Experiment 1 cannot be attributed to verbalization of the color that had to be visualized. Finally, in Experiment 3, the congruency effect evoked by mental imagery correlated with performance in a perceptual version of the task. We discuss these findings with respect to the mechanisms that underlie mental imagery and patients suffering from color imagery deficits. (c) 2015 APA, all rights reserved.

  8. Conventional Microscopy vs. Computer Imagery in Chiropractic Education.

    Science.gov (United States)

    Cunningham, Christine M; Larzelere, Elizabeth D; Arar, Ilija

    2008-01-01

    As human tissue pathology slides become increasingly difficult to obtain, other methods of teaching microscopy in educational laboratories must be considered. The purpose of this study was to evaluate our students' satisfaction with newly implemented computer imagery based laboratory instruction and to obtain input from their perspective on the advantages and disadvantages of computerized vs. traditional microscope laboratories. This undertaking involved the creation of a new computer laboratory. Robbins and Cotran Pathologic Basis of Disease, 7(th)ed, was chosen as the required text which gave students access to the Robbins Pathology website, including complete content of text, Interactive Case Study Companion, and Virtual Microscope. Students had experience with traditional microscopes in their histology and microbiology laboratory courses. Student satisfaction with computer based learning was assessed using a 28 question survey which was administered to three successive trimesters of pathology students (n=193) using the computer survey website Zoomerang. Answers were given on a scale of 1-5 and statistically analyzed using weighted averages. The survey data indicated that students were satisfied with computer based learning activities during pathology laboratory instruction. The most favorable aspect to computer imagery was 24-7 availability (weighted avg. 4.16), followed by clarification offered by accompanying text and captions (weighted avg. 4.08). Although advantages and disadvantages exist in using conventional microscopy and computer imagery, current pathology teaching environments warrant investigation of replacing traditional microscope exercises with computer applications. Chiropractic students supported the adoption of computer-assisted instruction in pathology laboratories.

  9. A cross-modal perspective on the relationships between imagery and working memory

    Directory of Open Access Journals (Sweden)

    Lora T Likova

    2013-01-01

    Full Text Available Mapping the distinctions and interrelationships between imagery and working memory remains challenging. Although each of these major cognitive constructs is defined and treated in various ways across studies, most accept that both imagery and working memory involve a form of internal representation available to our awareness. In working memory, there is a further emphasis on active maintenance and use of this conscious representation to guide voluntary action. Multicomponent working memory models incorporate representational buffers, such as the visuo-spatial sketchpad, plus central executive functions. If there is a visuo-spatial ‘sketchpad’ for working memory, does imagery involve the same representational buffer? Alternatively, does working memory employ an imagery-specific representational mechanism to occupy our awareness? Or do both constructs utilize a more generic ‘projection screen’ of an amodal nature? In a cross-modal fMRI study a novel memory paradigm is introduced based on drawing, which may be conceptualized as a complex behaviour adaptable to learning in the tactile modality. Blindfolded participants were trained to draw complex objects guided purely by the memory of felt tactile images. If this working memory task had been mediated by transfer of the felt spatial configuration to the visual imagery mechanism, the response profile in visual cortex would be predicted to have the ‘top-down’ signature of propagation of the imagery signal downwards through the visual hierarchy. Remarkably, the pattern of cross-modal occipital activation generated by the non-visual memory drawing was essentially the inverse of this typical ‘imagery signature’, with the sole visual hierarchy activation occurring in V1, accompanied by deactivation of the entire extrastriate part of the hierarchy. The implications of these findings for the debate on the interrelationships between the core cognitive constructs of working memory and imagery

  10. On Picturing a Candle: The Prehistory of Imagery Science.

    Science.gov (United States)

    MacKisack, Matthew; Aldworth, Susan; Macpherson, Fiona; Onians, John; Winlove, Crawford; Zeman, Adam

    2016-01-01

    The past 25 years have seen a rapid growth of knowledge about brain mechanisms involved in visual mental imagery. These advances have largely been made independently of the long history of philosophical - and even psychological - reckoning with imagery and its parent concept 'imagination'. We suggest that the view from these empirical findings can be widened by an appreciation of imagination's intellectual history, and we seek to show how that history both created the conditions for - and presents challenges to - the scientific endeavor. We focus on the neuroscientific literature's most commonly used task - imagining a concrete object - and, after sketching what is known of the neurobiological mechanisms involved, we examine the same basic act of imagining from the perspective of several key positions in the history of philosophy and psychology. We present positions that, firstly, contextualize and inform the neuroscientific account, and secondly, pose conceptual and methodological challenges to the scientific analysis of imagery. We conclude by reflecting on the intellectual history of visualization in the light of contemporary science, and the extent to which such science may resolve long-standing theoretical debates.

  11. Vehicle classification in WAMI imagery using deep network

    Science.gov (United States)

    Yi, Meng; Yang, Fan; Blasch, Erik; Sheaff, Carolyn; Liu, Kui; Chen, Genshe; Ling, Haibin

    2016-05-01

    Humans have always had a keen interest in understanding activities and the surrounding environment for mobility, communication, and survival. Thanks to recent progress in photography and breakthroughs in aviation, we are now able to capture tens of megapixels of ground imagery, namely Wide Area Motion Imagery (WAMI), at multiple frames per second from unmanned aerial vehicles (UAVs). WAMI serves as a great source for many applications, including security, urban planning and route planning. These applications require fast and accurate image understanding which is time consuming for humans, due to the large data volume and city-scale area coverage. Therefore, automatic processing and understanding of WAMI imagery has been gaining attention in both industry and the research community. This paper focuses on an essential step in WAMI imagery analysis, namely vehicle classification. That is, deciding whether a certain image patch contains a vehicle or not. We collect a set of positive and negative sample image patches, for training and testing the detector. Positive samples are 64 × 64 image patches centered on annotated vehicles. We generate two sets of negative images. The first set is generated from positive images with some location shift. The second set of negative patches is generated from randomly sampled patches. We also discard those patches if a vehicle accidentally locates at the center. Both positive and negative samples are randomly divided into 9000 training images and 3000 testing images. We propose to train a deep convolution network for classifying these patches. The classifier is based on a pre-trained AlexNet Model in the Caffe library, with an adapted loss function for vehicle classification. The performance of our classifier is compared to several traditional image classifier methods using Support Vector Machine (SVM) and Histogram of Oriented Gradient (HOG) features. While the SVM+HOG method achieves an accuracy of 91.2%, the accuracy of our deep

  12. Mental imagery of gravitational motion.

    Science.gov (United States)

    Gravano, Silvio; Zago, Myrka; Lacquaniti, Francesco

    2017-10-01

    There is considerable evidence that gravitational acceleration is taken into account in the interaction with falling targets through an internal model of Earth gravity. Here we asked whether this internal model is accessed also when target motion is imagined rather than real. In the main experiments, naïve participants grasped an imaginary ball, threw it against the ceiling, and caught it on rebound. In different blocks of trials, they had to imagine that the ball moved under terrestrial gravity (1g condition) or under microgravity (0g) as during a space flight. We measured the speed and timing of the throwing and catching actions, and plotted ball flight duration versus throwing speed. Best-fitting duration-speed curves estimate the laws of ball motion implicit in the participant's performance. Surprisingly, we found duration-speed curves compatible with 0g for both the imaginary 0g condition and the imaginary 1g condition, despite the familiarity with Earth gravity effects and the added realism of performing the throwing and catching actions. In a control experiment, naïve participants were asked to throw the imaginary ball vertically upwards at different heights, without hitting the ceiling, and to catch it on its way down. All participants overestimated ball flight durations relative to the durations predicted by the effects of Earth gravity. Overall, the results indicate that mental imagery of motion does not have access to the internal model of Earth gravity, but resorts to a simulation of visual motion. Because visual processing of accelerating/decelerating motion is poor, visual imagery of motion at constant speed or slowly varying speed appears to be the preferred mode to perform the tasks. Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. Learning target masks in infrared linescan imagery

    Science.gov (United States)

    Fechner, Thomas; Rockinger, Oliver; Vogler, Axel; Knappe, Peter

    1997-04-01

    In this paper we propose a neural network based method for the automatic detection of ground targets in airborne infrared linescan imagery. Instead of using a dedicated feature extraction stage followed by a classification procedure, we propose the following three step scheme: In the first step of the recognition process, the input image is decomposed into its pyramid representation, thus obtaining a multiresolution signal representation. At the lowest three levels of the Laplacian pyramid a neural network filter of moderate size is trained to indicate the target location. The last step consists of a fusion process of the several neural network filters to obtain the final result. To perform this fusion we use a belief network to combine the various filter outputs in a statistical meaningful way. In addition, the belief network allows the integration of further knowledge about the image domain. By applying this multiresolution recognition scheme, we obtain a nearly scale- and rotational invariant target recognition with a significantly decreased false alarm rate compared with a single resolution target recognition scheme.

  14. Distributed solar photovoltaic array location and extent dataset for remote sensing object identification

    Science.gov (United States)

    Bradbury, Kyle; Saboo, Raghav; L. Johnson, Timothy; Malof, Jordan M.; Devarajan, Arjun; Zhang, Wuming; M. Collins, Leslie; G. Newell, Richard

    2016-12-01

    Earth-observing remote sensing data, including aerial photography and satellite imagery, offer a snapshot of the world from which we can learn about the state of natural resources and the built environment. The components of energy systems that are visible from above can be automatically assessed with these remote sensing data when processed with machine learning methods. Here, we focus on the information gap in distributed solar photovoltaic (PV) arrays, of which there is limited public data on solar PV deployments at small geographic scales. We created a dataset of solar PV arrays to initiate and develop the process of automatically identifying solar PV locations using remote sensing imagery. This dataset contains the geospatial coordinates and border vertices for over 19,000 solar panels across 601 high-resolution images from four cities in California. Dataset applications include training object detection and other machine learning algorithms that use remote sensing imagery, developing specific algorithms for predictive detection of distributed PV systems, estimating installed PV capacity, and analysis of the socioeconomic correlates of PV deployment.

  15. The Sport Imagery Questionnaire for Children (SIQ-C)

    Science.gov (United States)

    Hall, C. R.; Munroe-Chandler, K. J.; Fishburne, G. J.; Hall, N. D.

    2009-01-01

    Athletes of all ages report using imagery extensively to enhance their sport performance. The Sport Imagery Questionnaire (Hall, Mack, Paivio, & Hausenblas, 1998) was developed to assess cognitive and motivational imagery used by adult athletes. No such instrument currently exists to measure the use of imagery by young athletes. The aim of the…

  16. Cloud Detection by Fusing Multi-Scale Convolutional Features

    Science.gov (United States)

    Li, Zhiwei; Shen, Huanfeng; Wei, Yancong; Cheng, Qing; Yuan, Qiangqiang

    2018-04-01

    Clouds detection is an important pre-processing step for accurate application of optical satellite imagery. Recent studies indicate that deep learning achieves best performance in image segmentation tasks. Aiming at boosting the accuracy of cloud detection for multispectral imagery, especially for those that contain only visible and near infrared bands, in this paper, we proposed a deep learning based cloud detection method termed MSCN (multi-scale cloud net), which segments cloud by fusing multi-scale convolutional features. MSCN was trained on a global cloud cover validation collection, and was tested in more than ten types of optical images with different resolution. Experiment results show that MSCN has obvious advantages over the traditional multi-feature combined cloud detection method in accuracy, especially when in snow and other areas covered by bright non-cloud objects. Besides, MSCN produced more detailed cloud masks than the compared deep cloud detection convolution network. The effectiveness of MSCN make it promising for practical application in multiple kinds of optical imagery.

  17. Processing Satellite Imagery To Detect Waste Tire Piles

    Science.gov (United States)

    Skiles, Joseph; Schmidt, Cynthia; Wuinlan, Becky; Huybrechts, Catherine

    2007-01-01

    A methodology for processing commercially available satellite spectral imagery has been developed to enable identification and mapping of waste tire piles in California. The California Integrated Waste Management Board initiated the project and provided funding for the method s development. The methodology includes the use of a combination of previously commercially available image-processing and georeferencing software used to develop a model that specifically distinguishes between tire piles and other objects. The methodology reduces the time that must be spent to initially survey a region for tire sites, thereby increasing inspectors and managers time available for remediation of the sites. Remediation is needed because millions of used tires are discarded every year, waste tire piles pose fire hazards, and mosquitoes often breed in water trapped in tires. It should be possible to adapt the methodology to regions outside California by modifying some of the algorithms implemented in the software to account for geographic differences in spectral characteristics associated with terrain and climate. The task of identifying tire piles in satellite imagery is uniquely challenging because of their low reflectance levels: Tires tend to be spectrally confused with shadows and deep water, both of which reflect little light to satellite-borne imaging systems. In this methodology, the challenge is met, in part, by use of software that implements the Tire Identification from Reflectance (TIRe) model. The development of the TIRe model included incorporation of lessons learned in previous research on the detection and mapping of tire piles by use of manual/ visual and/or computational analysis of aerial and satellite imagery. The TIRe model is a computational model for identifying tire piles and discriminating between tire piles and other objects. The input to the TIRe model is the georeferenced but otherwise raw satellite spectral images of a geographic region to be surveyed

  18. Methodology for the assessment of the impacts of climate change on land degradation at multiple scales: Use of high resolution satellite imagery, modelling, and ground measurements for the assessment in Ethiopia

    Science.gov (United States)

    Ahmed, Oumer

    In this study, a new multi-scalar methodology for assessing land degradation response to climate change is presented by analyzing 22 years of both climatic data and satellite observations, together with future projections from modelling, for Ethiopia. A comprehensive analysis of the impacts of climate change on land degradation was performed as evidenced from the integration of a host of land degradation indicators, namely: normalized difference vegetation Index (NDVI), net primary productivity (NPP), crop yield, biomass, length of growing period (LGP), rainfall use efficiency (RUE), energy use efficiency (EUE) and aridity index (AI). The results from the national level assessment indicate that over the period of 1984-2006, NPP decreased overall. Degrading areas occupy 30% of the country and suffer an average loss of NPP 10.3 kg C ha-1 y-1. The crop yield prediction results indicate a wide range of outcomes is to be expected for the country, due to the heterogeneity of the agro-climatic resources as well as of projected climate change. The results of the sub-national level assessment show that about 29% of the Awash watershed is degrading, and these degrading areas experience an average loss of NPP 4.6 kg C ha-1 y-1. Further, about 33.8% of the degrading area in the watershed is associated with bare land and 25% with agricultural land. Finally, since remotely sensed estimates are frequently used to assess land degradation at multiple scales, scale transfer methods are evaluated in this study to provide a tool to rank both upscaling and downscaling procedures.

  19. Aerial Photography and Imagery, Ortho-Corrected, This data set includes georectified, 4 -band digital orthophotos for 213.7 square miles of the Blackwater National Wildlife Refuge and Fishing Bay WMA in Dorchester County, MD., Published in 2010, 1:2400 (1in=200ft) scale, Eastern Shore Regional GIS Cooperative.

    Data.gov (United States)

    NSGIC Regional | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2010. This data set includes georectified, 4 -band digital orthophotos for 213.7 square miles...

  20. Aerial Photography and Imagery, Ortho-Corrected, April 2012, color and b/w and NIR, tiff and MrSID, section tiles or countywide mosaic- plan to refly in 2017 at same resolution (6" pixel), Published in 2012, 1:1200 (1in=100ft) scale, Dodge County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2012. April 2012, color and b/w and NIR, tiff and MrSID, section tiles or countywide mosaic-...

  1. Aerial Photography and Imagery, Ortho-Corrected, Polk County retained Ayres Associates to acquire digital aerial photography during the spring of 2010 suitable for the production of color orthophotography at a 12-inch ground pixel resolution (approximately 956 sq. miles). The photography was obtained du, Published in 2010, 1:2400 (1in=200ft) scale, Polk County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2010. Polk County retained Ayres Associates to acquire digital aerial photography during the...

  2. The World Health Organisation Disability Assessment Scale (WHODAS II: Links between self-rated health and objectively defined and clinical parameters in the population of spinal cord injury

    Directory of Open Access Journals (Sweden)

    Steinerte V.

    2016-01-01

    Full Text Available There are many clinical and objectively defined parameters that are used to evaluate a person's disability. Since the World Health Organisation has presented the WHODAS II as a means of objectively measuring subjectively defined functions, greater attention has been focused on self-rated health. Only a few studies, however, have been conducted about differences between self-rated health and objectively defined parameters. The survey for this study was conducted on the basis of WHODAS II and the population in Latvia with spinal cord injury. Respondents were between 18 and 65, and 98 questionnaires were analysed. The results show that people with spinal cord injury on average rate their functioning as limited (33–40 points of 100. Most respondents have been declared to be disabled, which is defined as very serious or severe functional disorders. More than 40% have paid jobs, while one-third do not work for reasons of health. The research shows that there is a close coherence (p< 0.05 between individual, objectively and clinically defined indicators on the one hand and the aspects of the questionnaire in which physical functioning was an important factor on the other hand. In order to understand the real functional abilities of patients and the individual factors that influence those abilities, it is necessary to define functional self-rated health in addition to objectively defined indicators.

  3. Crown-level tree species classification from AISA hyperspectral imagery using an innovative pixel-weighting approach

    Science.gov (United States)

    Liu, Haijian; Wu, Changshan

    2018-06-01

    Crown-level tree species classification is a challenging task due to the spectral similarity among different tree species. Shadow, underlying objects, and other materials within a crown may decrease the purity of extracted crown spectra and further reduce classification accuracy. To address this problem, an innovative pixel-weighting approach was developed for tree species classification at the crown level. The method utilized high density discrete LiDAR data for individual tree delineation and Airborne Imaging Spectrometer for Applications (AISA) hyperspectral imagery for pure crown-scale spectra extraction. Specifically, three steps were included: 1) individual tree identification using LiDAR data, 2) pixel-weighted representative crown spectra calculation using hyperspectral imagery, with which pixel-based illuminated-leaf fractions estimated using a linear spectral mixture analysis (LSMA) were employed as weighted factors, and 3) representative spectra based tree species classification was performed through applying a support vector machine (SVM) approach. Analysis of results suggests that the developed pixel-weighting approach (OA = 82.12%, Kc = 0.74) performed better than treetop-based (OA = 70.86%, Kc = 0.58) and pixel-majority methods (OA = 72.26, Kc = 0.62) in terms of classification accuracy. McNemar tests indicated the differences in accuracy between pixel-weighting and treetop-based approaches as well as that between pixel-weighting and pixel-majority approaches were statistically significant.

  4. MULTIPLE OBJECTS

    Directory of Open Access Journals (Sweden)

    A. A. Bosov

    2015-04-01

    Full Text Available Purpose. The development of complicated techniques of production and management processes, information systems, computer science, applied objects of systems theory and others requires improvement of mathematical methods, new approaches for researches of application systems. And the variety and diversity of subject systems makes necessary the development of a model that generalizes the classical sets and their development – sets of sets. Multiple objects unlike sets are constructed by multiple structures and represented by the structure and content. The aim of the work is the analysis of multiple structures, generating multiple objects, the further development of operations on these objects in application systems. Methodology. To achieve the objectives of the researches, the structure of multiple objects represents as constructive trio, consisting of media, signatures and axiomatic. Multiple object is determined by the structure and content, as well as represented by hybrid superposition, composed of sets, multi-sets, ordered sets (lists and heterogeneous sets (sequences, corteges. Findings. In this paper we study the properties and characteristics of the components of hybrid multiple objects of complex systems, proposed assessments of their complexity, shown the rules of internal and external operations on objects of implementation. We introduce the relation of arbitrary order over multiple objects, we define the description of functions and display on objects of multiple structures. Originality.In this paper we consider the development of multiple structures, generating multiple objects.Practical value. The transition from the abstract to the subject of multiple structures requires the transformation of the system and multiple objects. Transformation involves three successive stages: specification (binding to the domain, interpretation (multiple sites and particularization (goals. The proposed describe systems approach based on hybrid sets

  5. 2012 Oconee County, Georgia ADS80 Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — All imagery was collected during the 2012 Spring flying season during leaf-off conditions for deciduous vegetation in the State of Georgia. The sun angle was at...

  6. Competence imagery: a case study treating emetophobia.

    Science.gov (United States)

    Moran, Daniel J; O'Brien, Richard M

    2005-06-01

    An emetophobic child is nonresponsive to conventional systematic desensitization and has her anxiety responses counterconditioned by using Competence Imagery instead of physical relaxation responses while progressing through her fear hierarchy.

  7. Mental imagery boosts music compositional creativity.

    Science.gov (United States)

    Wong, Sarah Shi Hui; Lim, Stephen Wee Hun

    2017-01-01

    We empirically investigated the effect of mental imagery on young children's music compositional creativity. Children aged 5 to 8 years participated in two music composition sessions. In the control session, participants based their composition on a motif that they had created using a sequence of letter names. In the mental imagery session, participants were given a picture of an animal and instructed to imagine the animal's sounds and movements, before incorporating what they had imagined into their composition. Six expert judges independently rated all music compositions on creativity based on subjective criteria (consensual assessment). Reliability analyses indicated that the expert judges demonstrated a high level of agreement in their ratings. The mental imagery compositions received significantly higher creativity ratings by the expert judges than did the control compositions. These results provide evidence for the effectiveness of mental imagery in enhancing young children's music compositional creativity.

  8. Mental imagery boosts music compositional creativity

    Science.gov (United States)

    Lim, Stephen Wee Hun

    2017-01-01

    We empirically investigated the effect of mental imagery on young children’s music compositional creativity. Children aged 5 to 8 years participated in two music composition sessions. In the control session, participants based their composition on a motif that they had created using a sequence of letter names. In the mental imagery session, participants were given a picture of an animal and instructed to imagine the animal’s sounds and movements, before incorporating what they had imagined into their composition. Six expert judges independently rated all music compositions on creativity based on subjective criteria (consensual assessment). Reliability analyses indicated that the expert judges demonstrated a high level of agreement in their ratings. The mental imagery compositions received significantly higher creativity ratings by the expert judges than did the control compositions. These results provide evidence for the effectiveness of mental imagery in enhancing young children’s music compositional creativity. PMID:28296965

  9. Guided Imagery and Music - And Beyond?

    DEFF Research Database (Denmark)

    Bonde, Lars Ole

    4 original research articles, one essay, a classical article and two clinical papers documenting the development of theory, research and clinical practice within the receptive music therapy model [The Bonny Method of] Guided Imagery and Music.......4 original research articles, one essay, a classical article and two clinical papers documenting the development of theory, research and clinical practice within the receptive music therapy model [The Bonny Method of] Guided Imagery and Music....

  10. Mental Imagery and Visual Working Memory

    OpenAIRE

    Keogh, Rebecca; Pearson, Joel

    2011-01-01

    Visual working memory provides an essential link between past and future events. Despite recent efforts, capacity limits, their genesis and the underlying neural structures of visual working memory remain unclear. Here we show that performance in visual working memory - but not iconic visual memory - can be predicted by the strength of mental imagery as assessed with binocular rivalry in a given individual. In addition, for individuals with strong imagery, modulating the background luminance ...

  11. Damage to the surface of the small intestinal villus: an objective scale of assessment of the effects of single and fractionated radiation doses

    Energy Technology Data Exchange (ETDEWEB)

    Carr, K.E.; Watt, C. (Glasgow Univ. (UK). Dept. of Anatomy); Hamlet, R.; Nias, A.H.W. (Glasgow Inst. of Radiotherapeutics and Oncology (UK))

    1983-07-01

    Scanning electron microscopy has been used to compare damage to mouse small intestinal mucosa after irradiation with different doses of photons and neutrons. Various stages of the collapse of villous structure seen after radiation include the production of conical and rudimentary villi and a flattened mucosa. A scale is proposed to relate radiation to villous damage. Points from this scale are taken to produce comparative ratios for equivalent damage produced by different radiation conditions. RBE values are quoted for neutron, X and gamma radiation given as single or fractionated irradiation doses and as whole or partial body irradiation. The relationship between the stroma in intravillous pegs and that of the pericryptal compartment is explored.

  12. Damage to the surface of the small intestinal villus: an objective scale of assessment of the effects of single and fractionated radiation doses

    International Nuclear Information System (INIS)

    Carr, K.E.; Watt, C.

    1983-01-01

    Scanning electron microscopy has been used to compare damage to mouse small intestinal mucosa after irradiation with different doses of photons and neutrons. Various stages of the collapse of villous structure seen after radiation include the production of conical and rudimentary villi and a flattened mucosa. A scale is proposed to relate radiation to villous damage. Points from this scale are taken to produce comparative ratios for equivalent damage produced by different radiation conditions. RBE values are quoted for neutron, X and gamma radiation given as single or fractionated irradiation doses and as whole or partial body irradiation. The relationship between the stroma in intravillous pegs and that of the pericryptal compartment is explored. (author)

  13. Mental imagery in emotion and emotional disorders.

    Science.gov (United States)

    Holmes, Emily A; Mathews, Andrew

    2010-04-01

    Mental imagery has been considered relevant to psychopathology due to its supposed special relationship with emotion, although evidence for this assumption has been conspicuously lacking. The present review is divided into four main sections: (1) First, we review evidence that imagery can evoke emotion in at least three ways: a direct influence on emotional systems in the brain that are responsive to sensory signals; overlap between processes involved in mental imagery and perception which can lead to responding "as if" to real emotion-arousing events; and the capacity of images to make contact with memories for emotional episodes in the past. (2) Second, we describe new evidence confirming that imagery does indeed evoke greater emotional responses than verbal representation, although the extent of emotional response depends on the image perspective adopted. (3) Third, a heuristic model is presented that contrasts the generation of language-based representations with imagery and offers an account of their differing effects on emotion, beliefs and behavior. (4) Finally, based on the foregoing review, we discuss the role of imagery in maintaining emotional disorders, and its uses in psychological treatment. Copyright 2010 Elsevier Ltd. All rights reserved.

  14. Teachers as Learners Examine Land-Use Change in the Local Environment Using Remote Sensing Imagery

    Science.gov (United States)

    Klagges, Hope; Harbor, Jon; Shepardson, Daniel; Bell, Cheryl; Meyer, Jason; Burgess, Willie; Leuenberger, Ted

    2002-01-01

    In environmental science education, learners are exposed to earth phenomena that occur across a wide range of spatial and temporal scales. However, it is challenging for learners to grasp the significance of spatial and temporal change because they have limited perspectives of the Earth. Within the scientific community, remotely sensed imagery is…

  15. A geologic analysis of the Side-Looking Airborne Radar imagery of southern New England

    Science.gov (United States)

    Banks, Paul T.

    1975-01-01

    Analysis of the side looking airborn radar imagery of Massachusetts, Connecticut and Rhode Island indicates that radar shows the topography in great detail. Since bedrock geologic features are frequently expressed in the topography the radar lends itself to geologic interpretation. The radar was studied by comparisons with field mapped geologic data first at a scale of approximately 1:125,000 and then at a scale of 1:500,000. The larger scale comparison revealed that faults, minor faults, joint sets, bedding and foliation attitudes, lithology and lithologic contacts all have a topographic expression interpretable on the imagery. Surficial geologic features were far less visible on the imagery over most of the area studied. The smaller scale comparisons revealed a pervasive, near orthogonal fracture set cutting all types and ages of rock and trending roughly N40?E and N30?W. In certain places the strike of bedding and foliation attitudes and some lithologic Contacts were visible in addition to the fractures. Fracturing in southern New England is apparently far more important than has been previously recognized. This new information, together with the visibility of many bedding and foliation attitudes and lithologic contacts, indicates the importance of radar imagery in improving the geologic interpretation of an area.

  16. Real-time people and vehicle detection from UAV imagery

    Science.gov (United States)

    Gaszczak, Anna; Breckon, Toby P.; Han, Jiwan

    2011-01-01

    A generic and robust approach for the real-time detection of people and vehicles from an Unmanned Aerial Vehicle (UAV) is an important goal within the framework of fully autonomous UAV deployment for aerial reconnaissance and surveillance. Here we present an approach for the automatic detection of vehicles based on using multiple trained cascaded Haar classifiers with secondary confirmation in thermal imagery. Additionally we present a related approach for people detection in thermal imagery based on a similar cascaded classification technique combining additional multivariate Gaussian shape matching. The results presented show the successful detection of vehicle and people under varying conditions in both isolated rural and cluttered urban environments with minimal false positive detection. Performance of the detector is optimized to reduce the overall false positive rate by aiming at the detection of each object of interest (vehicle/person) at least once in the environment (i.e. per search patter flight path) rather than every object in each image frame. Currently the detection rate for people is ~70% and cars ~80% although the overall episodic object detection rate for each flight pattern exceeds 90%.

  17. Elegant objects

    CERN Document Server

    Bugayenko, Yegor

    2017-01-01

    There are 23 practical recommendations for object-oriented programmers. Most of them are completely against everything you've read in other books. For example, static methods, NULL references, getters, setters, and mutable classes are called evil. Compound variable names, validators, private static literals, configurable objects, inheritance, annotations, MVC, dependency injection containers, reflection, ORM and even algorithms are our enemies.

  18. Objective lens

    Science.gov (United States)

    Olczak, Eugene G. (Inventor)

    2011-01-01

    An objective lens and a method for using same. The objective lens has a first end, a second end, and a plurality of optical elements. The optical elements are positioned between the first end and the second end and are at least substantially symmetric about a plane centered between the first end and the second end.

  19. Impact of self-administered relaxation and guided imagery techniques during final trimester and birth.

    Science.gov (United States)

    Gedde-Dahl, Merete; Fors, Egil A

    2012-02-01

    The objective of this study was to test if and how self-administered practice of relaxation techniques, positive affirmation and guided imagery, in the final part of pregnancy had an impact on giving birth. Further to see if the use of a simple method, a CD with a booklet, with no previous training or specific support of the participants (neither required nor delivered), affected the birth experience. Outcome measures were monitored both during and after delivery: During delivery, pain and anxiety were measured at different stages of birth. Post-delivery Wellbeing (Edmonton Scale 0-10, where 10 is the worst possible feeling of Wellbeing), pain, anxiety, Apgar score, duration of birth, complications and anesthesia/analgesic were recorded. Those in the CD-intervention group also reported how many times they had practiced the techniques. The study employed a randomized controlled trial. Results show that the CD-intervention group had a significantly better score on total Wellbeing, as measured by the ESAS (0-10) Edmonton Scale. Copyright © 2011 Elsevier Ltd. All rights reserved.

  20. Histopathology reconstruction on digital imagery

    Science.gov (United States)

    Li, Wenjing; Lieberman, Rich W.; Nie, Sixiang; Xie, Yihua; Eldred, Michael; Oyama, Jody

    2009-02-01

    Diagnosing cervical cancer in a woman is a multi-step procedure involving examination of the cervix, possible biopsy and follow-up. It is open to subjective interpretation and highly dependent upon the skills of cytologists, colposcopists, and pathologists. In an effort to reduce the subjectiveness of the colposcopist-directed biopsy and to improve the diagnostic accuracy of colposcopy, we have developed new colposcopic imaging systems with accompanying computer aided diagnostic (CAD) techniques to guide a colposcopist in deciding if and where to biopsy. If the biopsy's histopathology, the identification of the disease state at the cellular and near-cellular level, is to be used as the gold standard for CAD, then the location of the histopathologic analysis must match exactly to the location of the biopsy tissue in the digital image. Otherwise, no matter how perfect the histopathology and the quality of the digital imagery, the two data sets cannot be matched and the true sensitivity and specificity of the CAD cannot be ascertained. We report here on new approaches to preserving, continuously, the location and orientation of a biopsy sample with respect to its location in the digital image of the cervix so as to preserve the exact spatial relationship throughout the mechanical aspects of the histopathologic analysis. This new approach will allow CAD to produce a linear diagnosis and pinpoint the location of the tissue under examination.

  1. Rehabilitation of the elbow extension with motor imagery in a patient with quadriplegia after tendon transfer.

    Science.gov (United States)

    Grangeon, Murielle; Guillot, Aymeric; Sancho, Pierre-Olivier; Picot, Marion; Revol, Patrice; Rode, Gilles; Collet, Christian

    2010-07-01

    To test the effect of a postsurgical motor imagery program in the rehabilitation of a patient with quadriplegia. Crossover design with kinematic analysis. Rehabilitation Hospital of Lyon. Study approved by the local Human Research Ethics Committee. C6-level injured patient (American Spinal Injury Association Impairment Scale grade A) with no voluntary elbow extension (triceps brachialis score 1). The surgical procedure was to transfer the distal insertion of the biceps brachii onto the triceps tendon of both arms. The postsurgical intervention on the left arm included 10 sessions of physical rehabilitation followed by 10 motor imagery sessions of 30 minutes each. The patient underwent 5 sessions a week during 2 consecutive weeks. The motor imagery content included mental representations based on elbow extension involved in goal-directed movements. The rehabilitation period of the right arm was reversed, with motor imagery performed first, followed by physical therapy. The kinematics of upper-limb movements was recorded (movement time and variability) before and after each type of rehabilitation period. A long-term retention test was performed 1 month later. Motor imagery training enhanced motor recovery by reducing hand trajectory variability-that is, improving smoothness. Motor performance then remained stable over 1 month. Motor imagery improved motor recovery when associated with physical therapy, with motor performance remaining stable over the 1-month period. We concluded that motor imagery should be successfully associated with classic rehabilitation procedure after tendon transfer. Physical sessions may thus be shortened if too stressful or painful. Copyright 2010 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

  2. Colors in Mind: A Novel Paradigm to Investigate Pure Color Imagery

    Science.gov (United States)

    Wantz, Andrea L.; Borst, Grégoire; Mast, Fred W.; Lobmaier, Janek S.

    2015-01-01

    Mental color imagery abilities are commonly measured using paradigms that involve naming, judging, or comparing the colors of visual mental images of well-known objects (e.g., "Is a sunflower darker yellow than a lemon"?). Although this approach is widely used in patient studies, differences in the ability to perform such color…

  3. The Perpetuation of Subtle Prejudice: Race and Gender Imagery in 1990s Television Advertising.

    Science.gov (United States)

    Coltrane, Scott; Messineo, Melinda

    2000-01-01

    Analyzed television commercials aired on programs with high ratings for specific target audiences from 1992-94 to investigate how advertising imagery simultaneously constructed racial and gender stereotypes. Results indicated that 1990s television commercials portrayed white men as powerful, white women as sex objects, African American men as…

  4. Imagery rescripting as a clinical intervention for aversive memories : A meta-analysis

    NARCIS (Netherlands)

    Morina, N.; Lancee, J.; Arntz, A.

    Background and objectives Literature suggests that imagery rescripting (ImRs) is an effective psychological intervention. Methods We conducted a meta-analysis of ImRs for psychological complaints that are associated with aversive memories. Relevant publications were collected from the databases

  5. Using Brief Guided Imagery to Reduce Math Anxiety and Improve Math Performance: A Pilot Study

    Science.gov (United States)

    Henslee, Amber M.; Klein, Brandi A.

    2017-01-01

    The objective of this study was to investigate whether brief guided imagery could provide a short-term reduction in math anxiety and improve math performance. Undergraduates (N = 581) were screened for math anxiety, and the highest and lowest quartiles were recruited to participate in a lab-based study. Participants were assigned to a brief guided…

  6. Tactile acuity is disrupted in osteoarthritis but is unrelated to disruptions in motor imagery performance.

    NARCIS (Netherlands)

    Stanton, T.R.; Lin, C.W.; Bray, H.; Smeets, R.J.P.; Taylor, D.; Law, R.Y.; Moseley, G.L.

    2013-01-01

    OBJECTIVE: To determine whether tactile acuity is disrupted in people with knee OA and to determine whether tactile acuity, a clinical signature of primary sensory cortex representation, is related to motor imagery performance (MIP; evaluates working body schema) and pain. METHODS: Experiment 1:

  7. Infrastructure assessment for disaster management using multi-sensor and multi-temporal remote sensing imagery

    DEFF Research Database (Denmark)

    Butenuth, Matthias; Frey, Daniel; Nielsen, Allan Aasbjerg

    2011-01-01

    In this paper, a new assessment system is presented to evaluate infrastructure objects such as roads after natural disasters in near-realtime. A particular aim is the exploitation of multi-sensorial and multi-temporal imagery together with further {GIS-}data in a comprehensive assessment framewor...

  8. Spatially defined disruption of motor imagery performance in people with osteoarthritis

    NARCIS (Netherlands)

    Stanton, T.R.; Lin, C.W.; Smeets, R.J.P.; Taylor, D.; Law, R.; Lorimer Moseley, G.

    2012-01-01

    OBJECTIVES: To determine whether motor imagery performance is disrupted in patients with painful knee OA and if this disruption is specific to the location of the pain. METHODS: Twenty patients with painful knee OA, 20 patients with arm pain and 20 healthy pain-free controls undertook a motor

  9. Visualizing UAS-collected imagery using augmented reality

    Science.gov (United States)

    Conover, Damon M.; Beidleman, Brittany; McAlinden, Ryan; Borel-Donohue, Christoph C.

    2017-05-01

    One of the areas where augmented reality will have an impact is in the visualization of 3-D data. 3-D data has traditionally been viewed on a 2-D screen, which has limited its utility. Augmented reality head-mounted displays, such as the Microsoft HoloLens, make it possible to view 3-D data overlaid on the real world. This allows a user to view and interact with the data in ways similar to how they would interact with a physical 3-D object, such as moving, rotating, or walking around it. A type of 3-D data that is particularly useful for military applications is geo-specific 3-D terrain data, and the visualization of this data is critical for training, mission planning, intelligence, and improved situational awareness. Advances in Unmanned Aerial Systems (UAS), photogrammetry software, and rendering hardware have drastically reduced the technological and financial obstacles in collecting aerial imagery and in generating 3-D terrain maps from that imagery. Because of this, there is an increased need to develop new tools for the exploitation of 3-D data. We will demonstrate how the HoloLens can be used as a tool for visualizing 3-D terrain data. We will describe: 1) how UAScollected imagery is used to create 3-D terrain maps, 2) how those maps are deployed to the HoloLens, 3) how a user can view and manipulate the maps, and 4) how multiple users can view the same virtual 3-D object at the same time.

  10. Extended objects

    International Nuclear Information System (INIS)

    Creutz, M.

    1976-01-01

    After some disconnected comments on the MIT bag and string models for extended hadrons, I review current understanding of extended objects in classical conventional relativistic field theories and their quantum mechanical interpretation

  11. Trusted Objects

    International Nuclear Information System (INIS)

    CAMPBELL, PHILIP L.; PIERSON, LYNDON G.; WITZKE, EDWARD L.

    1999-01-01

    In the world of computers a trusted object is a collection of possibly-sensitive data and programs that can be allowed to reside and execute on a computer, even on an adversary's machine. Beyond the scope of one computer we believe that network-based agents in high-consequence and highly reliable applications will depend on this approach, and that the basis for such objects is what we call ''faithful execution.''

  12. Photogrammetric Processing Using ZY-3 Satellite Imagery

    Science.gov (United States)

    Kornus, W.; Magariños, A.; Pla, M.; Soler, E.; Perez, F.

    2015-03-01

    detected covering an area of 4691ha, corresponding to less than 2% of the imaged area. Most of the artifacts are caused by clouds (4614ha). A minor part (77ha) is affected by colour patch, stripping or blooming effects. For the final qualitative analysis on the usability of the ZY-3 imagery for stereo plotting purposes stereo combinations of the nadir and an oblique image are discarded, mainly due to the different pixel size, which produces difficulties in the stereoscopic vision and poor accuracy in positioning and measuring. With the two oblique images a level of detail equivalent to 1:25.000 scale is achieved for transport network, hydrography, vegetation and elements to model the terrain as break lines. For settlement, including buildings and other constructions a lower level of detail is achieved equivalent to 1:50.000 scale.

  13. Satellite Imagery Production and Processing Using Apache Hadoop

    Science.gov (United States)

    Hill, D. V.; Werpy, J.

    2011-12-01

    The United States Geological Survey's (USGS) Earth Resources Observation and Science (EROS) Center Land Science Research and Development (LSRD) project has devised a method to fulfill its processing needs for Essential Climate Variable (ECV) production from the Landsat archive using Apache Hadoop. Apache Hadoop is the distributed processing technology at the heart of many large-scale, processing solutions implemented at well-known companies such as Yahoo, Amazon, and Facebook. It is a proven framework and can be used to process petabytes of data on thousands of processors concurrently. It is a natural fit for producing satellite imagery and requires only a few simple modifications to serve the needs of science data processing. This presentation provides an invaluable learning opportunity and should be heard by anyone doing large scale image processing today. The session will cover a description of the problem space, evaluation of alternatives, feature set overview, configuration of Hadoop for satellite image processing, real-world performance results, tuning recommendations and finally challenges and ongoing activities. It will also present how the LSRD project built a 102 core processing cluster with no financial hardware investment and achieved ten times the initial daily throughput requirements with a full time staff of only one engineer. Satellite Imagery Production and Processing Using Apache Hadoop is presented by David V. Hill, Principal Software Architect for USGS LSRD.

  14. A Brazilian-Portuguese version of the Kinesthetic and Visual Motor Imagery Questionnaire.

    Science.gov (United States)

    Demanboro, Alan; Sterr, Annette; Anjos, Sarah Monteiro Dos; Conforto, Adriana Bastos

    2018-01-01

    Motor imagery has emerged as a potential rehabilitation tool in stroke. The goals of this study were: 1) to develop a translated and culturally-adapted Brazilian-Portugese version of the Kinesthetic and Visual Motor Imagery Questionnaire (KVIQ20-P); 2) to evaluate the psychometric characteristics of the scale in a group of patients with stroke and in an age-matched control group; 3) to compare the KVIQ20 performance between the two groups. Test-retest, inter-rater reliabilities, and internal consistencies were evaluated in 40 patients with stroke and 31 healthy participants. In the stroke group, ICC confidence intervals showed excellent test-retest and inter-rater reliabilities. Cronbach's alpha also indicated excellent internal consistency. Results for controls were comparable to those obtained in persons with stroke. The excellent psychometric properties of the KVIQ20-P should be considered during the design of studies of motor imagery interventions for stroke rehabilitation.

  15. Pixel-Wise Classification Method for High Resolution Remote Sensing Imagery Using Deep Neural Networks

    Directory of Open Access Journals (Sweden)

    Rui Guo

    2018-03-01

    Full Text Available Considering the classification of high spatial resolution remote sensing imagery, this paper presents a novel classification method for such imagery using deep neural networks. Deep learning methods, such as a fully convolutional network (FCN model, achieve state-of-the-art performance in natural image semantic segmentation when provided with large-scale datasets and respective labels. To use data efficiently in the training stage, we first pre-segment training images and their labels into small patches as supplements of training data using graph-based segmentation and the selective search method. Subsequently, FCN with atrous convolution is used to perform pixel-wise classification. In the testing stage, post-processing with fully connected conditional random fields (CRFs is used to refine results. Extensive experiments based on the Vaihingen dataset demonstrate that our method performs better than the reference state-of-the-art networks when applied to high-resolution remote sensing imagery classification.

  16. Large-scale hydropower system optimization using dynamic programming and object-oriented programming: the case of the Northeast China Power Grid.

    Science.gov (United States)

    Li, Ji-Qing; Zhang, Yu-Shan; Ji, Chang-Ming; Wang, Ai-Jing; Lund, Jay R

    2013-01-01

    This paper examines long-term optimal operation using dynamic programming for a large hydropower system of 10 reservoirs in Northeast China. Besides considering flow and hydraulic head, the optimization explicitly includes time-varying electricity market prices to maximize benefit. Two techniques are used to reduce the 'curse of dimensionality' of dynamic programming with many reservoirs. Discrete differential dynamic programming (DDDP) reduces the search space and computer memory needed. Object-oriented programming (OOP) and the ability to dynamically allocate and release memory with the C++ language greatly reduces the cumulative effect of computer memory for solving multi-dimensional dynamic programming models. The case study shows that the model can reduce the 'curse of dimensionality' and achieve satisfactory results.

  17. Real-time changes in corticospinal excitability related to motor imagery of a force control task

    DEFF Research Database (Denmark)

    Tatemoto, Tsuyoshi; Tsuchiya, Junko; Numata, Atsuki

    2017-01-01

    Objective To investigate real-time excitability changes in corticospinal pathways related to motor imagery in a changing force control task, using transcranial magnetic stimulation (TMS). Methods Ten healthy volunteers learnt to control the contractile force of isometric right wrist dorsiflexion...... in order to track an on-screen sine wave form. Participants performed the trained task 40 times with actual muscle contraction in order to construct the motor image. They were then instructed to execute the task without actual muscle contraction, but by imagining contraction of the right wrist...... in dorsiflexion. Motor evoked potentials (MEPs), induced by TMS in the right extensor carpi radialis muscle (ECR) and flexor carpi radialis muscle (FCR), were measured during motor imagery. MEPs were induced at five time points: prior to imagery, during the gradual generation of the imaged wrist dorsiflexion...

  18. Tracking Dynamic Northern Surface Water Changes with High-Frequency Planet CubeSat Imagery

    Directory of Open Access Journals (Sweden)

    Sarah W. Cooley

    2017-12-01

    Full Text Available Recent deployments of CubeSat imagers by companies such as Planet may advance hydrological remote sensing by providing an unprecedented combination of high temporal and high spatial resolution imagery at the global scale. With approximately 170 CubeSats orbiting at full operational capacity, the Planet CubeSat constellation currently offers an average revisit time of <1 day for the Arctic and near-daily revisit time globally at 3 m spatial resolution. Such data have numerous potential applications for water resource monitoring, hydrologic modeling and hydrologic research. Here we evaluate Planet CubeSat imaging capabilities and potential scientific utility for surface water studies in the Yukon Flats, a large sub-Arctic wetland in north central Alaska. We find that surface water areas delineated from Planet imagery have a normalized root mean square error (NRMSE of <11% and geolocation accuracy of <10 m as compared with manual delineations from high resolution (0.3–0.5 m WorldView-2/3 panchromatic satellite imagery. For a 625 km2 subarea of the Yukon Flats, our time series analysis reveals that roughly one quarter of 268 lakes analyzed responded to changes in Yukon River discharge over the period 23 June–1 October 2016, one half steadily contracted, and one quarter remained unchanged. The spatial pattern of observed lake changes is heterogeneous. While connections to Yukon River control the hydrologically connected lakes, the behavior of other lakes is complex, likely driven by a combination of intricate flow paths, underlying geology and permafrost. Limitations of Planet CubeSat imagery include a lack of an automated cloud mask, geolocation inaccuracies, and inconsistent radiometric calibration across multiple platforms. Although these challenges must be addressed before Planet CubeSat imagery can achieve its full potential for large-scale hydrologic research, we conclude that CubeSat imagery offers a powerful new tool for the study and

  19. Scaling of Thermal Images at Different Spatial Resolution: The Mixed Pixel Problem

    Directory of Open Access Journals (Sweden)

    Hamlyn G. Jones

    2014-07-01

    Full Text Available The consequences of changes in spatial resolution for application of thermal imagery in plant phenotyping in the field are discussed. Where image pixels are significantly smaller than the objects of interest (e.g., leaves, accurate estimates of leaf temperature are possible, but when pixels reach the same scale or larger than the objects of interest, the observed temperatures become significantly biased by the background temperature as a result of the presence of mixed pixels. Approaches to the estimation of the true leaf temperature that apply both at the whole-pixel level and at the sub-pixel level are reviewed and discussed.

  20. Satellite imagery in a nuclear age

    International Nuclear Information System (INIS)

    Baines, P.J.

    1998-01-01

    Increasingly, high resolution satellite imaging systems are becoming available from multiple and diverse sources with capabilities useful for answering security questions. With increased supply, data availability and data authenticity may be assured. In a commercial market a supplier can ill afford the loss in market share that would result from any falsification of data. Similarly rising competitors willing to sell imagery of national security sites will decrease the tendency to endure self-imposed restrictions on sales of those sites. International organizations operating in the security interests of all nations might also gain preferential access. Costa for imagery will also fall to the point were individuals can afford purchases of satellite images. International organizations will find utility in exploiting imagery for solving international security problems. Housed within international organizations possessing competent staff, procedures, and 'shared destiny' stakes in resolving compliance discrepancies, the use of satellite imagery may provide a degree of stability in a world in which individuals, non-governmental organizations and governments may choose to exploit the available information for political gain. The use of satellite imagery outside these international organizations might not necessarily be aimed at seeking mutually beneficial solutions for international problems

  1. Satellite imagery in safeguards: progress and prospects

    International Nuclear Information System (INIS)

    Niemeyer, I.; Listner, C.

    2013-01-01

    The use of satellite imagery has become very important for the verification of the safeguards implementation under the Nuclear Non-Proliferation Treaty (NPT). The main applications of satellite imagery are to verify the correctness and completeness of the member states' declarations, and to provide preparatory information for inspections, complimentary access and other technical visits. If the area of interest is not accessible, remote sensing sensors provide one of the few opportunities of gathering data for nuclear monitoring, as for example in Iraq between 1998 and 2002 or currently in North Korea. Satellite data of all available sensor types contains a considerable amount of safeguard-relevant information. Very high-resolution optical satellite imagery provides the most detailed spatial information on nuclear sites and activities up to 0.41 m resolution, together with up to 8 spectral bands from the visible light and near infrared. Thermal infrared (TIR) images can indicate the operational status of nuclear facilities and help to identify undeclared activities. Hyper-spectral imagery allows a quantitative estimation of geophysical, geochemical and biochemical characteristics of the earth's surface and is therefore useful for assessing, for example, surface cover changes due to drilling, mining and milling activities. Synthetic Aperture Radar (SAR) image data up to 1 m spatial resolution provides an all-weather, day and night monitoring capability. However, the absence (or existence) of nuclear activities can never be confirmed completely based on satellite imagery. (A.C.)

  2. An Object-Based Image Analysis Approach for Detecting Penguin Guano in very High Spatial Resolution Satellite Images

    OpenAIRE

    Chandi Witharana; Heather J. Lynch

    2016-01-01

    The logistical challenges of Antarctic field work and the increasing availability of very high resolution commercial imagery have driven an interest in more efficient search and classification of remotely sensed imagery. This exploratory study employed geographic object-based analysis (GEOBIA) methods to classify guano stains, indicative of chinstrap and Adélie penguin breeding areas, from very high spatial resolution (VHSR) satellite imagery and closely examined the transferability of knowle...

  3. From sixty-two interviews on 'the worst and the best episode of your life'. Relationships between internal working models and a grammatical scale of subject-object affective connections.

    Science.gov (United States)

    Seganti, A; Carnevale, G; Mucelli, R; Solano, L; Target, M

    2000-06-01

    The authors address the issue of inferring unconscious internal working models of interaction through language. After reviewing Main's seminal work of linguistic assessment through the 'adult attachment interview', they stress the idea of adults' internal working models (IWMs) as information-processing devices, which give moment-to-moment sensory orientation in the face of any past or present, animate or inanimate object. They propose that a selective perception of the objects could match expected with actual influence of objects on the subject's self, through very simple 'parallel-processed' categories of internal objects. They further hypothesise that the isomorphism between internal working models of interaction and grammatical connections between subjects and objects within a clause could be a key to tracking positive and negative images of self and other during discourse. An experiment is reported applying the authors' 'scale of subject/object affective connection' to the narratives of sixty-two subjects asked to write about the 'worst' and 'best' episodes of their lives. Participants had previously been classified using Hazan & Shaver's self-reported 'attachment types' (avoidant, anxious and secure) categorising individuals' general expectations in relation to others. The findings were that the subject/object distribution of positive and negative experience, through verbs defined for this purpose as either performative or state verbs, did significantly differ between groups. In addition, different groups tended, during the best episodes, significantly to invert the trend of positive/negative subject/object distribution shown during the worst episode. Results are discussed in terms of a psychoanalytic theory of improvement through co-operative elaboration of negative relational issues.

  4. Continental-shelf Scale Passive Ocean AcousticWaveguide Remote Sensing of Marine Mammals and other Submerged Objects including Detection, Localization, and Classification

    Science.gov (United States)

    Wang, Delin

    In this thesis, we develop the basics of the Passive Ocean Acoustic Waveguide Remote Sensing (POAWRS) technique for the instantaneous continental-shelf scale detection, localization and species classification of marine mammal vocalizations. POAWRS uses a large-aperture, densely sampled coherent hydrophone array system with orders of magnitude higher array gain to enhance signal-to-noise ratios (SNR) by coherent beamforming, enabling detection of underwater acoustic signals either two orders of magnitude more distant in range or lower in SNR than a single hydrophone. The ability to employ coherent spatial processing of signals with the POAWRS technology significantly improves areal coverage, enabling detection of oceanic sound sources over instantaneous wide areas spanning 100 km or more in diameter. The POAWRS approach was applied to analyze marine mammal vocalizations from diverse species received on a 160-element Office Naval Research Five Octave Research Array (ONR-FORA) deployed during their feeding season in Fall 2006 in the Gulf of Maine. The species-dependent temporal-spatial distribution of marine mammal vocalizations and correlation to the prey fish distributions have been determined. Furthermore, the probability of detection regions, source level distributions and pulse compression gains of the vocalization signals from diverse marine mammal species have been estimated. We also develop an approach for enhancing the angular resolution and improving bearing estimates of acoustic signals received on a coherent hydrophone array with multiple-nested uniformly-spaced subapertures, such as the ONR-FORA, by nonuniform array beamforming. Finally we develop a low-cost non-oil-filled towable prototype hydrophone array that consists of eight hydrophone elements with real-time data acquisition and 100 m tow cable. The approach demonstrated here will be applied in the development of a full 160 element POAWRS-type low-cost coherent hydrophone array system in the future.

  5. [Mental Imagery: Neurophysiology and Implications in Psychiatry].

    Science.gov (United States)

    Martínez, Nathalie Tamayo

    2014-03-01

    To provide an explanation about what mental imagery is and some implications in psychiatry. This article is a narrative literature review. There are many terms in which imagery representations are described in different fields of research. They are defined as perceptions in the absence of an external stimulus, and can be created in any sensory modality. Their neurophysiological substrate is almost the same as the one activated during sensory perception. There is no unified theory about its function, but it is possibly the way that our brain uses and manipulates the information to respond to the environment. Mental imagery is an everyday phenomenon, and when it occurs in specific patterns it can be a sign of mental disorders. Copyright © 2014 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.

  6. Colors in Mind: A Novel Paradigm to Investigate Pure Color Imagery

    OpenAIRE

    Wantz, Andrea Laura; Borst, Grégoire; Mast, Fred; Lobmaier, Janek

    2015-01-01

    Mental color imagery abilities are commonly measured using paradigms that involve naming, judging, or comparing the colors of visual mental images of well-known objects (e.g., “Is a sunflower darker yellow than a lemon”?). Although this approach is widely used in patient studies, differences in the ability to perform such color comparisons might simply reflect participants’ general knowledge of object colors rather than their ability to generate accurate visual mental images of the colors of ...

  7. Fearful imagery in social phobia: generalization, comorbidity, and physiological reactivity.

    Science.gov (United States)

    McTeague, Lisa M; Lang, Peter J; Laplante, Marie-Claude; Cuthbert, Bruce N; Strauss, Cyd C; Bradley, Margaret M

    2009-03-01

    Social phobia has been characterized as a disorder of exaggerated fear of social threat and heightened sensitivity to imagery of social failure. To assess the physiological basis of this description, social phobia patients (n=75) and demographically matched control participants (n=75) imagined neutral and fearful events while acoustic startle probes were occasionally presented and eye-blink responses (orbicularis occuli) recorded. Changes in heart rate, skin conductance level, and facial expressivity were also indexed. In addition to comparing control participants and social phobia patients, the influences of diagnostic subtype (circumscribed, generalized), comorbid depression, and chronicity were assessed. Patients exceeded control participants in startle reflex and autonomic responding during imagery of social threat, whereas the groups evinced commensurate reactivity to contents depicting commonly shared fears (survival threat). Individuals with circumscribed performance phobia were similar to control participants, with the exception of more robust reactions to idiographic, performance fear imagery. In contrast, generalized phobic patients were characterized by longer disorder chronicity and demonstrated heightened sensitivity to a broader range of fear contents. Those with generalized phobia plus comorbid depression showed attenuation of fear-potentiated startle and reported the most protracted social anxiety. Subtypes of social phobia can be objectively distinguished in patterns of physiological reactivity. Furthermore, subtypes vary systematically in chronicity and defensive engagement with the shortest disorder duration (circumscribed phobia) associated with the most robust and focal physiological reactivity, followed by broader defensive sensitivity in more chronic generalized phobia, and finally attenuation of the formerly exaggerated fear potentiation in the comorbidly depressed, the most chronic form.

  8. Aerial Photography and Imagery, Ortho-Corrected - FDOT 2009 Orthophotography

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — This Imagery was provided by Florida Department of Transportation to the Volusia County Property Appraiser. 1 Foot Color Pixel Orthophotography. This imagery was...

  9. USDA/FSA Imagery Programs - Public Map Gallery

    Data.gov (United States)

    Farm Service Agency, Department of Agriculture — Imagery programs are an important part of maintaining, creating and updating geospatial data at the USDA Farm Service Agency. Imagery acquisition is provided by the...

  10. The impact of ageing and gender on visual mental imagery processes: A study of performance on tasks from the Complete Visual Mental Imagery Battery (CVMIB).

    Science.gov (United States)

    Palermo, Liana; Piccardi, Laura; Nori, Raffaella; Giusberti, Fiorella; Guariglia, Cecilia

    2016-09-01

    In this study we aim to evaluate the impact of ageing and gender on different visual mental imagery processes. Two hundred and fifty-one participants (130 women and 121 men; age range = 18-77 years) were given an extensive neuropsychological battery including tasks probing the generation, maintenance, inspection, and transformation of visual mental images (Complete Visual Mental Imagery Battery, CVMIB). Our results show that all mental imagery processes with the exception of the maintenance are affected by ageing, suggesting that other deficits, such as working memory deficits, could account for this effect. However, the analysis of the transformation process, investigated in terms of mental rotation and mental folding skills, shows a steeper decline in mental rotation, suggesting that age could affect rigid transformations of objects and spare non-rigid transformations. Our study also adds to previous ones in showing gender differences favoring men across the lifespan in the transformation process, and, interestingly, it shows a steeper decline in men than in women in inspecting mental images, which could partially account for the mixed results about the effect of ageing on this specific process. We also discuss the possibility to introduce the CVMIB in clinical assessment in the context of theoretical models of mental imagery.

  11. Fashion Objects

    DEFF Research Database (Denmark)

    Andersen, Bjørn Schiermer

    2009-01-01

    -- an outline which at the same time indicates the need for transformations of the Durkheimian model on decisive points. Thus, thirdly, it returns to Durkheim and undertakes to develop his concepts in a direction suitable for a sociological theory of fashion. Finally, it discusses the theoretical implications......This article attempts to create a framework for understanding modern fashion phenomena on the basis of Durkheim's sociology of religion. It focuses on Durkheim's conception of the relation between the cult and the sacred object, on his notion of 'exteriorisation', and on his theory of the social...... symbol in an attempt to describe the peculiar attraction of the fashion object and its social constitution. However, Durkheim's notions of cult and ritual must undergo profound changes if they are to be used in an analysis of fashion. The article tries to expand the Durkheimian cult, radically enlarging...

  12. Lehrbuch Guided Imagery in Music (GIM)

    DEFF Research Database (Denmark)

    Maack, Carola; Geiger, Edith Maria

    Guided Imagery in Music (GIM) ist eine musikpsychotherapeutische Methode, bei welcher der Patient eine Auswahl meist klassischer Musik in einem entspannten Zustand hört und sein Erleben (= Imaginationen) der Therapeutin mitteilt. Theoretische Hintergründe, klinische Anwendung, sowie methodenspezi......Guided Imagery in Music (GIM) ist eine musikpsychotherapeutische Methode, bei welcher der Patient eine Auswahl meist klassischer Musik in einem entspannten Zustand hört und sein Erleben (= Imaginationen) der Therapeutin mitteilt. Theoretische Hintergründe, klinische Anwendung, sowie...

  13. Utilities objectives

    International Nuclear Information System (INIS)

    Cousin, Y.; Fabian, H.U.

    1996-01-01

    The policy of French and german utilities is to make use of nuclear energy as a long term, competitive and environmentally friendly power supply. The world electricity generation is due to double within the next 30 years. In the next 20 to 30 years the necessity of nuclear energy will be broadly recognized. More than for most industries, to deal properly with nuclear energy requires the combination of a consistent political will, of a proper institutional framework, of strong and legitimate control authorities, of a sophisticated industry and of operators with skilled management and human resources. One of the major risk facing nuclear energy is the loss of competitiveness. This can be achieved only through the combination of an optimized design, a consistent standardization, a proper industrial partnership and a stable long term strategy. Although the existing plants in Western Europe are already very safe, the policy is clearly to enhance the safety of the next generation of nuclear plants which are designing today. The French and German utilities have chosen an evolutionary approach based on experience and proven technologies, with an enhanced defense in depth and an objective of easier operation and maintenance. The cost objective is to maintain and improve what has been achieved in the best existing power plants in both countries. This calls for rational choices and optimized design to meet the safety objectives, a strong standardization policy, short construction times, high availability and enough flexibility to enable optimization of the fuel cycle throughout the lifetime of the plants. The conceptual design phase has proven that the French and German teams from industry and from the utilities are able to pursue both the safety and the cost objectives, basing their decision on a rational approach which could be accepted by the safety authorities. (J.S.)

  14. Olfactory dreams, olfactory interest, and imagery : Relationships to olfactory memory

    OpenAIRE

    Arshamian, Artin

    2007-01-01

    Existing evidence for olfactory imagery is mixed and mainly based on reports from hallucinations and volitional imagery. Using a questionnaire, Stevenson and Case (2005) showed that olfactory dreams provided a good source for olfactory imagery studies. This study applied an extended version of the same questionnaire and examined olfactory dreams and their relation to real-life experienced odors, volitional imagery, and olfactory interest. Results showed that olfactory dreams were similar to r...

  15. Visualisation, imagery, and the development of geometrical reasoning

    OpenAIRE

    Jones, Keith; Bills, Chris

    1998-01-01

    This report focuses on some aspects of the nature and role of visualisation and imagery in the teaching and learning of mathematics, particularly as a component in the development of geometrical reasoning. Issues briefly addressed include the relationship between imagery and perception, imagery and memory, the nature of dynamic images, and the interaction between imagery and concept development. The report concludes with a series of questions that may provide a suitable programme for research...

  16. Scaled signal intensity of uterine fibroids based on T2-weighted MR images: a potential objective method to determine the suitability for magnetic resonance-guided focused ultrasound surgery of uterine fibroids.

    Science.gov (United States)

    Park, Hyun; Yoon, Sang-Wook; Sokolov, Amit

    2015-12-01

    Magnetic Resonance-guided Focused Ultrasound Surgery (MRgFUS) is a non-invasive method to treat uterine fibroids. To help determine the patient suitability for MRgFUS, we propose a new objective measure: the scaled signal intensity (SSI) of uterine fibroids in T2 weighted MR images (T2WI). Forty three uterine fibroids in 40 premenopausal women were included in this retrospective study. SSI of each fibroid was measured from the screening T2WI by standardizing its mean signal intensity to a 0-100 scale, using reference intensities of rectus abdominis muscle (0) and subcutaneous fat (100). Correlation between the SSI and the non-perfused volume (NPV) ratio (a measure for treatment success) was calculated. Pre-treatment SSI showed a significant inverse-correlation with post treatment NPV ratio (p < 0.05). When dichotomizing NPV ratio at 45 %, the optimal cut off value of the SSI was found to be 16.0. A fibroid with SSI value 16.0 or less can be expected to have optimal responses. The SSI of uterine fibroids in T2WI can be suggested as an objective parameter to help in patient selection for MRgFUS. • Signal intensity of fibroid in MR images predicts treatment response to MRgFUS. • Signal intensity is standardized into scaled form using adjacent tissues as references. • Fibroids with SSI less than 16.0 are expected to have optimal responses.

  17. Cloud cover typing from environmental satellite imagery. Discriminating cloud structure with Fast Fourier Transforms (FFT)

    Science.gov (United States)

    Logan, T. L.; Huning, J. R.; Glackin, D. L.

    1983-01-01

    The use of two dimensional Fast Fourier Transforms (FFTs) subjected to pattern recognition technology for the identification and classification of low altitude stratus cloud structure from Geostationary Operational Environmental Satellite (GOES) imagery was examined. The development of a scene independent pattern recognition methodology, unconstrained by conventional cloud morphological classifications was emphasized. A technique for extracting cloud shape, direction, and size attributes from GOES visual imagery was developed. These attributes were combined with two statistical attributes (cloud mean brightness, cloud standard deviation), and interrogated using unsupervised clustering amd maximum likelihood classification techniques. Results indicate that: (1) the key cloud discrimination attributes are mean brightness, direction, shape, and minimum size; (2) cloud structure can be differentiated at given pixel scales; (3) cloud type may be identifiable at coarser scales; (4) there are positive indications of scene independence which would permit development of a cloud signature bank; (5) edge enhancement of GOES imagery does not appreciably improve cloud classification over the use of raw data; and (6) the GOES imagery must be apodized before generation of FFTs.

  18. USGS Imagery Applications During Disaster Response After Recent Earthquakes

    Science.gov (United States)

    Hudnut, K. W.; Brooks, B. A.; Glennie, C. L.; Finnegan, D. C.

    2015-12-01

    It is not only important to rapidly characterize surface fault rupture and related ground deformation after an earthquake, but also to repeatedly make observations following an event to forecast fault afterslip. These data may also be used by other agencies to monitor progress on damage repairs and restoration efforts by emergency responders and the public. Related requirements include repeatedly obtaining reference or baseline imagery before a major disaster occurs, as well as maintaining careful geodetic control on all imagery in a time series so that absolute georeferencing may be applied to the image stack through time. In addition, repeated post-event imagery acquisition is required, generally at a higher repetition rate soon after the event, then scaled back to less frequent acquisitions with time, to capture phenomena (such as fault afterslip) that are known to have rates that decrease rapidly with time. For example, lidar observations acquired before and after the South Napa earthquake of 2014, used in our extensive post-processing work that was funded primarily by FEMA, aided in the accurate forecasting of fault afterslip. Lidar was used to independently validate and verify the official USGS afterslip forecast. In order to keep pace with rapidly evolving technology, a development pipeline must be established and maintained to continually test and incorporate new sensors, while adapting these new components to the existing platform and linking them to the existing base software system, and then sequentially testing the system as it evolves. Improvements in system performance by incremental upgrades of system components and software are essential. Improving calibration parameters and thereby progressively eliminating artifacts requires ongoing testing, research and development. To improve the system, we have formed an interdisciplinary team with common interests and diverse sources of support. We share expertise and leverage funding while effectively and

  19. Botswana team sport players' perception of cohesion and imagery ...

    African Journals Online (AJOL)

    Perception of cohesion and imagery use among 45 elite team sport players in Botswana were assessed with the Group Environment Questionnaire (Carron et al., 1985) and the Sport Imagery Questionnaire (Hall et al., 1998) to determine whether a relationship exists between the variables, and whether imagery use will ...

  20. 7 CFR 611.22 - Availability of satellite imagery.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 6 2010-01-01 2010-01-01 false Availability of satellite imagery. 611.22 Section 611... § 611.22 Availability of satellite imagery. Cloud-free maps of the United States based on imagery received from a satellite are prepared and released to the pubic by NRCS. The maps offer the first image of...

  1. Geographic Object-Based Image Analysis - Towards a new paradigm.

    Science.gov (United States)

    Blaschke, Thomas; Hay, Geoffrey J; Kelly, Maggi; Lang, Stefan; Hofmann, Peter; Addink, Elisabeth; Queiroz Feitosa, Raul; van der Meer, Freek; van der Werff, Harald; van Coillie, Frieke; Tiede, Dirk

    2014-01-01

    The amount of scientific literature on (Geographic) Object-based Image Analysis - GEOBIA has been and still is sharply increasing. These approaches to analysing imagery have antecedents in earlier research on image segmentation and use GIS-like spatial analysis within classification and feature extraction approaches. This article investigates these development and its implications and asks whether or not this is a new paradigm in remote sensing and Geographic Information Science (GIScience). We first discuss several limitations of prevailing per-pixel methods when applied to high resolution images. Then we explore the paradigm concept developed by Kuhn (1962) and discuss whether GEOBIA can be regarded as a paradigm according to this definition. We crystallize core concepts of GEOBIA, including the role of objects, of ontologies and the multiplicity of scales and we discuss how these conceptual developments support important methods in remote sensing such as change detection and accuracy assessment. The ramifications of the different theoretical foundations between the ' per-pixel paradigm ' and GEOBIA are analysed, as are some of the challenges along this path from pixels, to objects, to geo-intelligence. Based on several paradigm indications as defined by Kuhn and based on an analysis of peer-reviewed scientific literature we conclude that GEOBIA is a new and evolving paradigm.

  2. Automatic digital surface model (DSM) generation from aerial imagery data

    Science.gov (United States)

    Zhou, Nan; Cao, Shixiang; He, Hongyan; Xing, Kun; Yue, Chunyu

    2018-04-01

    Aerial sensors are widely used to acquire imagery for photogrammetric and remote sensing application. In general, the images have large overlapped region, which provide a lot of redundant geometry and radiation information for matching. This paper presents a POS supported dense matching procedure for automatic DSM generation from aerial imagery data. The method uses a coarse-to-fine hierarchical strategy with an effective combination of several image matching algorithms: image radiation pre-processing, image pyramid generation, feature point extraction and grid point generation, multi-image geometrically constraint cross-correlation (MIG3C), global relaxation optimization, multi-image geometrically constrained least squares matching (MIGCLSM), TIN generation and point cloud filtering. The image radiation pre-processing is used in order to reduce the effects of the inherent radiometric problems and optimize the images. The presented approach essentially consists of 3 components: feature point extraction and matching procedure, grid point matching procedure and relational matching procedure. The MIGCLSM method is used to achieve potentially sub-pixel accuracy matches and identify some inaccurate and possibly false matches. The feasibility of the method has been tested on different aerial scale images with different landcover types. The accuracy evaluation is based on the comparison between the automatic extracted DSMs derived from the precise exterior orientation parameters (EOPs) and the POS.

  3. Single-trial effective brain connectivity patterns enhance discriminability of mental imagery tasks

    Science.gov (United States)

    Rathee, Dheeraj; Cecotti, Hubert; Prasad, Girijesh

    2017-10-01

    Objective. The majority of the current approaches of connectivity based brain-computer interface (BCI) systems focus on distinguishing between different motor imagery (MI) tasks. Brain regions associated with MI are anatomically close to each other, hence these BCI systems suffer from low performances. Our objective is to introduce single-trial connectivity feature based BCI system for cognition imagery (CI) based tasks wherein the associated brain regions are located relatively far away as compared to those for MI. Approach. We implemented time-domain partial Granger causality (PGC) for the estimation of the connectivity features in a BCI setting. The proposed hypothesis has been verified with two publically available datasets involving MI and CI tasks. Main results. The results support the conclusion that connectivity based features can provide a better performance than a classical signal processing framework based on bandpass features coupled with spatial filtering for CI tasks, including word generation, subtraction, and spatial navigation. These results show for the first time that connectivity features can provide a reliable performance for imagery-based BCI system. Significance. We show that single-trial connectivity features for mixed imagery tasks (i.e. combination of CI and MI) can outperform the features obtained by current state-of-the-art method and hence can be successfully applied for BCI applications.

  4. Landsat and agriculture—Case studies on the uses and benefits of Landsat imagery in agricultural monitoring and production

    Science.gov (United States)

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

    2017-03-29

    production. The USDA has been using Landsat imagery to monitor global agricultural production since the launch of Landsat 1 in 1972. Landsat imagery provides objective, global input for a number of USDA agricultural programs and plays an important role in economic and food security forecasting.U.S. Department of Agriculture—Satellite Imagery Archive.—Highlights a number of the experiences of the USDA in acquiring, sharing, and managing moderate resolution imagery to support the diversity of USDA operational programs. Private sector applications using Landsat imagery for agricultural management are discussed in the Landsat Imagery Use and Benefits in Field-Level Agricultural Production Management section of the report in the following subsections:Field-Level Management.—Provides an introduction to what field-level production management is and how it can be applied to agricultural management. This section explores the concept of zone mapping and how Landsat imagery can be used to identify different conditions within a field. The section also provides a case study of zone-mapping software, developed by GK Technology, Inc., that is used by numerous agricultural consultants.Putting Zone Maps to Work.—Highlights several case studies of private agricultural consultants who have been using Landsat imagery to develop zone maps for farmers. Landsat imagery is helping consultants and farmers optimize agricultural inputs, including fertilizer and seed, which leads to higher yield and economic return for the farmer.Increasing Yield.—Highlights the primary benefit of zone mapping using Landsat imagery. Using 5-year market average prices for a number of commodities, this section provides examples of how yield increases translate into higher returns for farmers.

  5. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Suwannee County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  6. Kinesthetic Imagery Provides Additive Benefits to Internal Visual Imagery on Slalom Task Performance.

    Science.gov (United States)

    Callow, Nichola; Jiang, Dan; Roberts, Ross; Edwards, Martin G

    2017-02-01

    Recent brain imaging research demonstrates that the use of internal visual imagery (IVI) or kinesthetic imagery (KIN) activates common and distinct brain areas. In this paper, we argue that combining the imagery modalities (IVI and KIN) will lead to a greater cognitive representation (with more brain areas activated), and this will cause a greater slalom-based motor performance compared with using IVI alone. To examine this assertion, we randomly allocated 56 participants to one of the three groups: IVI, IVI and KIN, or a math control group. Participants performed a slalom-based driving task in a driving simulator, with average lap time used as a measure of performance. Results revealed that the IVI and KIN group achieved significantly quicker lap times than the IVI and the control groups. The discussion includes a theoretical advancement on why the combination of imagery modalities might facilitate performance, with links made to the cognitive neuroscience literature and applied practice.

  7. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Sumter County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  8. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Alachua County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  9. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Putnam County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  10. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Lake County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  11. Aerial Photography and Imagery, Ortho-Corrected - FL Bay Ortho Imagery Project Spring 2013

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This file references a single orthogonal imagery tile produced from nadir images captured by Pictometry International during the period of December 30th, 2012 and...

  12. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Taylor County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  13. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Okeechobee County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  14. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Baker County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  15. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Palm Beach County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  16. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Leon County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  17. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Volusia County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  18. National Geospatial Data Asset (NGDA) National Agriculture Imagery Program (NAIP) Imagery - 2017 Planned Acquisition

    Data.gov (United States)

    Farm Service Agency, Department of Agriculture — NAIP imagery is acquired annually with the total coverage being determined by available funds from FSA and funding partners, considering FSA priorities. The NAIP...

  19. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Lee County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  20. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Nassau County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  1. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Duval County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  2. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Indian River County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  3. Aerial Photography and Imagery, Ortho-Corrected - 2010 NAIP Imagery - Gadsden County

    Data.gov (United States)

    NSGIC Education | GIS Inventory — This data set contains polygons delineating the seams boundary between acquired imagery used in the creation of DOQQs and compressed county mosaic (CCM). The DOQQ...

  4. VHR satellite imagery for humanitarian crisis management: a case study

    Science.gov (United States)

    Bitelli, Gabriele; Eleias, Magdalena; Franci, Francesca; Mandanici, Emanuele

    2017-09-01

    During the last years, remote sensing data along with GIS have been largely employed for supporting emergency management activities. In this context, the use of satellite images and derived map products has become more common also in the different phases of humanitarian crisis response. In this work very high resolution satellite imagery was processed to assess the evolution of Za'atari Refugee Camp, built in Jordan in 2012 by the UN Refugee Agency to host Syrian refugees. Multispectral satellite scenes of the Za'atari area were processed by means of object-based classifications. The main aim of the present work is the development of a semiautomated procedure for multi-temporal camp monitoring with particular reference to the dwellings detection. Whilst in the emergency mapping domain automation of feature extraction is widely investigated, in the field of humanitarian missions the information is often extracted by means of photointerpretation of the satellite data. This approach requires time for the interpretation; moreover, it is not reliable enough in complex situations, where features of interest are often small, heterogeneous and inconsistent. Therefore, the present paper discusses a methodology to obtain information for assisting humanitarian crisis management, using a semi-automatic classification approach applied to satellite imagery.

  5. Delineating wetland catchments and modeling hydrologic connectivity using lidar data and aerial imagery

    Directory of Open Access Journals (Sweden)

    Q. Wu

    2017-07-01

    Full Text Available In traditional watershed delineation and topographic modeling, surface depressions are generally treated as spurious features and simply removed from a digital elevation model (DEM to enforce flow continuity of water across the topographic surface to the watershed outlets. In reality, however, many depressions in the DEM are actual wetland landscape features with seasonal to permanent inundation patterning characterized by nested hierarchical structures and dynamic filling–spilling–merging surface-water hydrological processes. Differentiating and appropriately processing such ecohydrologically meaningful features remains a major technical terrain-processing challenge, particularly as high-resolution spatial data are increasingly used to support modeling and geographic analysis needs. The objectives of this study were to delineate hierarchical wetland catchments and model their hydrologic connectivity using high-resolution lidar data and aerial imagery. The graph-theory-based contour tree method was used to delineate the hierarchical wetland catchments and characterize their geometric and topological properties. Potential hydrologic connectivity between wetlands and streams were simulated using the least-cost-path algorithm. The resulting flow network delineated potential flow paths connecting wetland depressions to each other or to the river network on scales finer than those available through the National Hydrography Dataset. The results demonstrated that our proposed framework is promising for improving overland flow simulation and hydrologic connectivity analysis.

  6. Imagery Rescripting in Posttraumatic Stress Disorder

    Science.gov (United States)

    Hackmann, Anne

    2011-01-01

    This article provides an overview of methods of working with imagery to change meanings and ameliorate posttraumatic stress disorder (PTSD). It opens with a description of phenomenology in this disorder, usually characterized by a small number of recurrent images of the trauma, each representing a moment that warned of a threat to the physical or…

  7. Imagery for Disaster Response and Recovery

    Science.gov (United States)

    Bethel, G. R.

    2011-12-01

    Exposing the remotely sensed imagery for disaster response and recovery can provide the basis for an unbiased understanding of current conditions. Having created consolidated remotely sensed and geospatial data sources documents for US and Foreign disasters over the past six years, availability and usability are continuing to evolve. By documenting all existing sources of imagery and value added products, the disaster response and recovery community can develop actionable information. The past two years have provided unique situations to use imagery including a major humanitarian disaster and response effort in Haiti, a major environmental disaster in the Gulf of Mexico, a killer tornado in Joplin Missouri and long-term flooding in the Midwest. Each disaster presents different challenges and requires different spatial resolutions, spectral properties and/or multi-temporal collections. The community of data providers continues to expand with organized actives such as the International Charter for Space and Major Disasters and acquisitions by the private sector for the public good rather than for profit. However, data licensing, the lack of cross-calibration and inconsistent georeferencing hinder optimal use. Recent pre-event imagery is a critial component to any disaster response.

  8. Paris Commune Imagery in China's Mass Media.

    Science.gov (United States)

    Meiss, Guy T.

    The role of ideology in mass media practices is explored in an analysis of the relation between the Paris Commune of 1871 and the Shanghai Commune of 1967, two attempts to translate the philosophical concept of dictatorship of the proletariat into some political form. A review of the use of Paris Commune imagery by the Chinese to mobilize the…

  9. Changes of hypnagogic imagery and EEG stages

    OpenAIRE

    Hayashi, Mitsuo; Katoh, Kohichi; Hori, Tadao

    1998-01-01

    The aim of this study is to investigate the relationships between hypnagogic imagery and EEG stages. According to Hori, et al. (1994), the hypnagogic EEGs was classified into 9 stages, those were 1) alpha wave train, 2) alpha wave intermittent (>50%), 3) alpha wave intermittent (

  10. Placebo-like analgesia via response imagery

    NARCIS (Netherlands)

    Peerdeman, K.J.; Laarhoven, A.I.M. van; Bartels, D.J.P.; Peters, M.L.; Evers, A.W.M.

    2017-01-01

    BACKGROUND: Placebo effects on pain are reliably observed in the literature. A core mechanism of these effects is response expectancies. Response expectancies can be formed by instructions, prior experiences and observation of others. Whether mental imagery of a response can also induce placebo-like

  11. Satellite imagery and the Department of Safeguards

    International Nuclear Information System (INIS)

    Chitumbo, K.; Bunney, J.; Leve, G.; Robb, S.

    2001-01-01

    Full text: The presentation examines some of the challenges the Satellite Imagery and Analysis Laboratory (SIAL) is facing in supporting Strengthened Safeguards. It focuses on the analytical process, starting with specifying initial tasking and continuing through to end products that are a direct result of in-house analysis. In addition it also evaluates the advantages and disadvantages of SIAL's mission and introduces external forces that the agency must consider, but cannot itself, predict or control. Although SIAL's contribution to tasks relating to Article 2a(iii) of the Additional Protocol are known and are presently of great benefit to operations areas, this is only one aspect of its work. SIAL's ability to identify and analyze historical satellite imagery data has the advantage of permitting operations to take a more in depth view of a particular area of interest's (AOI) development, and thus may permit operations to confirm or refute specific assertions relating to the AOI's function or abilities. These assertions may originate in-house or may be open source reports the agency feels it is obligated to explore. SIAL's mission is unique in the world of imagery analysis. Its aim is to support all operations areas equally and in doing so it must maintain global focus. The task is tremendous, but the resultant coverage and concentration of unique expertise will allow SIAL to develop and provide operations with datasets that can be exploited in standalone mode or be incorporated into new cutting edge tools to be developed in SGIT. At present SIAL relies on two remote sensors, IKONOS-2 and EROS-AI, for present high- resolution imagery data and is using numerous sources for historical, pre 1999, data. A multiplicity of sources for high-resolution data is very important to SIAL, but is something that it cannot influence. It is hoped that the planned launch of two new sensors by Summer 2002 will be successful and will offer greater flexibility for image collection

  12. Investigating the effects of a sensorimotor rhythm-based BCI training on the cortical activity elicited by mental imagery

    Science.gov (United States)

    Toppi, J.; Risetti, M.; Quitadamo, L. R.; Petti, M.; Bianchi, L.; Salinari, S.; Babiloni, F.; Cincotti, F.; Mattia, D.; Astolfi, L.

    2014-06-01

    Objective. It is well known that to acquire sensorimotor (SMR)-based brain-computer interface (BCI) control requires a training period before users can achieve their best possible performances. Nevertheless, the effect of this training procedure on the cortical activity related to the mental imagery ability still requires investigation to be fully elucidated. The aim of this study was to gain insights into the effects of SMR-based BCI training on the cortical spectral activity associated with the performance of different mental imagery tasks. Approach. Linear cortical estimation and statistical brain mapping techniques were applied on high-density EEG data acquired from 18 healthy participants performing three different mental imagery tasks. Subjects were divided in two groups, one of BCI trained subjects, according to their previous exposure (at least six months before this study) to motor imagery-based BCI training, and one of subjects who were naive to any BCI paradigms. Main results. Cortical activation maps obtained for trained and naive subjects indicated different spectral and spatial activity patterns in response to the mental imagery tasks. Long-term effects of the previous SMR-based BCI training were observed on the motor cortical spectral activity specific to the BCI trained motor imagery task (simple hand movements) and partially generalized to more complex motor imagery task (playing tennis). Differently, mental imagery with spatial attention and memory content could elicit recognizable cortical spectral activity even in subjects completely naive to (BCI) training. Significance. The present findings contribute to our understanding of BCI technology usage and might be of relevance in those clinical conditions when training to master a BCI application is challenging or even not possible.

  13. Mapping Sub-Antarctic Cushion Plants Using Random Forests to Combine Very High Resolution Satellite Imagery and Terrain Modelling

    Science.gov (United States)

    Bricher, Phillippa K.; Lucieer, Arko; Shaw, Justine; Terauds, Aleks; Bergstrom, Dana M.

    2013-01-01

    Monitoring changes in the distribution and density of plant species often requires accurate and high-resolution baseline maps of those species. Detecting such change at the landscape scale is often problematic, particularly in remote areas. We examine a new technique to improve accuracy and objectivity in mapping vegetation, combining species distribution modelling and satellite image classification on a remote sub-Antarctic island. In this study, we combine spectral data from very high resolution WorldView-2 satellite imagery and terrain variables from a high resolution digital elevation model to improve mapping accuracy, in both pixel- and object-based classifications. Random forest classification was used to explore the effectiveness of these approaches on mapping the distribution of the critically endangered cushion plant Azorella macquariensis Orchard (Apiaceae) on sub-Antarctic Macquarie Island. Both pixel- and object-based classifications of the distribution of Azorella achieved very high overall validation accuracies (91.6–96.3%, κ = 0.849–0.924). Both two-class and three-class classifications were able to accurately and consistently identify the areas where Azorella was absent, indicating that these maps provide a suitable baseline for monitoring expected change in the distribution of the cushion plants. Detecting such change is critical given the threats this species is currently facing under altering environmental conditions. The method presented here has applications to monitoring a range of species, particularly in remote and isolated environments. PMID:23940805

  14. Motion/imagery secure cloud enterprise architecture analysis

    Science.gov (United States)

    DeLay, John L.

    2012-06-01

    Cloud computing with storage virtualization and new service-oriented architectures brings a new perspective to the aspect of a distributed motion imagery and persistent surveillance enterprise. Our existing research is focused mainly on content management, distributed analytics, WAN distributed cloud networking performance issues of cloud based technologies. The potential of leveraging cloud based technologies for hosting motion imagery, imagery and analytics workflows for DOD and security applications is relatively unexplored. This paper will examine technologies for managing, storing, processing and disseminating motion imagery and imagery within a distributed network environment. Finally, we propose areas for future research in the area of distributed cloud content management enterprises.

  15. Photogrammetric Measurements in Fixed Wing Uav Imagery

    Science.gov (United States)

    Gülch, E.

    2012-07-01

    Several flights have been undertaken with PAMS (Photogrammetric Aerial Mapping System) by Germap, Germany, which is briefly introduced. This system is based on the SmartPlane fixed-wing UAV and a CANON IXUS camera system. The plane is equipped with GPS and has an infrared sensor system to estimate attitude values. A software has been developed to link the PAMS output to a standard photogrammetric processing chain built on Trimble INPHO. The linking of the image files and image IDs and the handling of different cases with partly corrupted output have to be solved to generate an INPHO project file. Based on this project file the software packages MATCH-AT, MATCH-T DSM, OrthoMaster and OrthoVista for digital aerial triangulation, DTM/DSM generation and finally digital orthomosaik generation are applied. The focus has been on investigations on how to adapt the "usual" parameters for the digital aerial triangulation and other software to the UAV flight conditions, which are showing high overlaps, large kappa angles and a certain image blur in case of turbulences. It was found, that the selected parameter setup shows a quite stable behaviour and can be applied to other flights. A comparison is made to results from other open source multi-ray matching software to handle the issue of the described flight conditions. Flights over the same area at different times have been compared to each other. The major objective was here to see, on how far differences occur relative to each other, without having access to ground control data, which would have a potential for applications with low requirements on the absolute accuracy. The results show, that there are influences of weather and illumination visible. The "unusual" flight pattern, which shows big time differences for neighbouring strips has an influence on the AT and DTM/DSM generation. The results obtained so far do indicate problems in the stability of the camera calibration. This clearly requests a usage of GCPs for all

  16. Neuropsychological Component of Imagery Processing

    Science.gov (United States)

    1991-01-25

    and von Bonin, G. (1951). The Isocortex of Man. Urbana, IL: University of Illinois Press. Bauer, R. M., and Rubens, A. B. (1985). Agnosia . In K. M...Apperceptive agnosia : the specification and description of constructs. In Humphreys, G. W., and Riddoch, M. J. (1987a) (Eds.). Visual Object Processing: A...visual processing: agnosias , achromatopsia, Balint’s syndrome and related difficulties of orientation and construction. In M.-M. Mesulam (Ed

  17. Scaled signal intensity of uterine fibroids based on T2-weighted MR images: a potential objective method to determine the suitability for magnetic resonance-guided focused ultrasound surgery of uterine fibroids

    Energy Technology Data Exchange (ETDEWEB)

    Park, Hyun [CHA University, Comprehensive Gynecologic Cancer Center, CHA Bundang Medical Center, Gyunggi-do (Korea, Republic of); Yoon, Sang-Wook [CHA University, Department of Diagnostic Radiology, CHA Bundang Medical Center, Sungnam-si, Gyunggi-do (Korea, Republic of); Sokolov, Amit [InSightec Ltd., Haifa (Israel)

    2015-12-15

    Magnetic Resonance-guided Focused Ultrasound Surgery (MRgFUS) is a non-invasive method to treat uterine fibroids. To help determine the patient suitability for MRgFUS, we propose a new objective measure: the scaled signal intensity (SSI) of uterine fibroids in T2 weighted MR images (T2WI). Forty three uterine fibroids in 40 premenopausal women were included in this retrospective study. SSI of each fibroid was measured from the screening T2WI by standardizing its mean signal intensity to a 0-100 scale, using reference intensities of rectus abdominis muscle (0) and subcutaneous fat (100). Correlation between the SSI and the non-perfused volume (NPV) ratio (a measure for treatment success) was calculated. Pre-treatment SSI showed a significant inverse-correlation with post treatment NPV ratio (p < 0.05). When dichotomizing NPV ratio at 45 %, the optimal cut off value of the SSI was found to be 16.0. A fibroid with SSI value 16.0 or less can be expected to have optimal responses. The SSI of uterine fibroids in T2WI can be suggested as an objective parameter to help in patient selection for MRgFUS. (orig.)

  18. Gamifying Video Object Segmentation.

    Science.gov (United States)

    Spampinato, Concetto; Palazzo, Simone; Giordano, Daniela

    2017-10-01

    Video object segmentation can be considered as one of the most challenging computer vision problems. Indeed, so far, no existing solution is able to effectively deal with the peculiarities of real-world videos, especially in cases of articulated motion and object occlusions; limitations that appear more evident when we compare the performance of automated methods with the human one. However, manually segmenting objects in videos is largely impractical as it requires a lot of time and concentration. To address this problem, in this paper we propose an interactive video object segmentation method, which exploits, on one hand, the capability of humans to identify correctly objects in visual scenes, and on the other hand, the collective human brainpower to solve challenging and large-scale tasks. In particular, our method relies on a game with a purpose to collect human inputs on object locations, followed by an accurate segmentation phase achieved by optimizing an energy function encoding spatial and temporal constraints between object regions as well as human-provided location priors. Performance analysis carried out on complex video benchmarks, and exploiting data provided by over 60 users, demonstrated that our method shows a better trade-off between annotation times and segmentation accuracy than interactive video annotation and automated video object segmentation approaches.

  19. A Data Mining Approach for Sharpening Thermal Satellite Imagery over Land

    Directory of Open Access Journals (Sweden)

    Feng Gao

    2012-10-01

    Full Text Available Thermal infrared (TIR imagery is normally acquired at coarser pixel resolution than that of shortwave sensors on the same satellite platform and often the TIR resolution is not suitable for monitoring crop conditions of individual fields or the impacts of land cover changes that are at significantly finer spatial scales. Consequently, thermal sharpening techniques have been developed to sharpen TIR imagery to shortwave band pixel resolutions, which are often fine enough for field-scale applications. A classic thermal sharpening technique, TsHARP, uses a relationship between land surface temperature (LST and Normalized Difference Vegetation Index (NDVI developed empirically at the TIR pixel resolution and applied at the NDVI pixel resolution. However, recent studies show that unique relationships between temperature and NDVI may only exist for a limited class of landscapes, with mostly green vegetation and homogeneous air and soil conditions. To extend application of thermal sharpening to more complex conditions, a new data mining sharpener (DMS technique is developed. The DMS approach builds regression trees between TIR band brightness temperatures and shortwave spectral reflectances based on intrinsic sample characteristics. A comparison of sharpening techniques applied over a rainfed agricultural area in central Iowa, an irrigated agricultural region in the Texas High Plains, and a heterogeneous naturally vegetated landscape in Alaska indicates that the DMS outperformed TsHARP in all cases. The artificial box-like patterns in LST generated by the TsHARP approach are greatly reduced using the DMS scheme, especially for areas containing irrigated crops, water bodies, thin clouds or terrain. While the DMS technique can provide fine resolution TIR imagery, there are limits to the sharpening ratios that can be reasonably implemented. Consequently, sharpening techniques cannot replace actual thermal band imagery at fine resolutions or missions that

  20. The efficacy of imagery rescripting (IR) for social phobia: a randomized controlled trial.

    Science.gov (United States)

    Lee, Seung Won; Kwon, Jung-Hye

    2013-12-01

    There is a need for brief effective treatment of social phobia and Imagery Rescripting (IR) is a potential candidate. The purpose of this study was to examine the efficacy of IR preceded by cognitive restructuring as a stand-alone brief treatment using a randomized controlled design. Twenty-three individuals with social phobia were randomly assigned to an IR group or to a control group. Participants in the IR group were provided with one session of imagery interviewing and two sessions of cognitive restructuring and Imagery Rescripting. Those in the control group had one session of clinical interviewing and two sessions of supportive therapy. Outcome measures including the Korean version of the social avoidance and distress scale (K-SADS) were administered before and after treatment, and at three-month follow-up. The short version of the Questionnaire upon Mental Imagery and the Traumatic Experience Scale were also administered before treatment. Participants in the IR group improved significantly on K-SADS and other outcome measures, compared to the control group. The beneficial effects of IR were maintained at three-month follow-up. It was also found that mental imagery ability and the severity of the traumatic experience did not moderate the outcome of IR. Further studies are needed to replicate the findings of our study using a large sample. The efficacy of IR as a stand-alone brief treatment was demonstrated for social phobia. The findings indicate that IR could be utilized as a cost-effective intervention for social phobia. Copyright © 2013 Elsevier Ltd. All rights reserved.

  1. Selective effect of physical fatigue on motor imagery accuracy.

    Directory of Open Access Journals (Sweden)

    Franck Di Rienzo

    Full Text Available While the use of motor imagery (the mental representation of an action without overt execution during actual training sessions is usually recommended, experimental studies examining the effect of physical fatigue on subsequent motor imagery performance are sparse and yielded divergent findings. Here, we investigated whether physical fatigue occurring during an intense sport training session affected motor imagery ability. Twelve swimmers (nine males, mean age 15.5 years conducted a 45 min physically-fatiguing protocol where they swam from 70% to 100% of their maximal aerobic speed. We tested motor imagery ability immediately before and after fatigue state. Participants randomly imagined performing a swim turn using internal and external visual imagery. Self-reports ratings, imagery times and electrodermal responses, an index of alertness from the autonomic nervous system, were the dependent variables. Self-reports ratings indicated that participants did not encounter difficulty when performing motor imagery after fatigue. However, motor imagery times were significantly shortened during posttest compared to both pretest and actual turn times, thus indicating reduced timing accuracy. Looking at the selective effect of physical fatigue on external visual imagery did not reveal any difference before and after fatigue, whereas significantly shorter imagined times and electrodermal responses (respectively 15% and 48% decrease, p<0.001 were observed during the posttest for internal visual imagery. A significant correlation (r=0.64; p<0.05 was observed between motor imagery vividness (estimated through imagery questionnaire and autonomic responses during motor imagery after fatigue. These data support that unlike local muscle fatigue, physical fatigue occurring during intense sport training sessions is likely to affect motor imagery accuracy. These results might be explained by the updating of the internal representation of the motor sequence, due to

  2. Guided Imagery Improves Mood, Fatigue, and Quality of Life in Individuals With Multiple Sclerosis: An Exploratory Efficacy Trial of Healing Light Guided Imagery.

    Science.gov (United States)

    Case, Laura K; Jackson, Paula; Kinkel, Revere; Mills, Paul J

    2018-01-01

    Multiple sclerosis is a disabling and progressive neurological disease that has significant negative effects on health-related quality of life. This exploratory efficacy study examined the effects of Healing Light Guided Imagery (HLGI), a novel variant of guided imagery, compared with a wait-list control in patients with relapsing-remitting multiple sclerosis. Changes in the Beck Depression Inventory, Fatigue Severity Scale, and Multiple Sclerosis Quality of Life instrument (physical and mental components) were compared between groups. Patients who completed HLGI (N = 9) showed significant reductions in depressed mood ( P mental ( P journaling (N = 8). Our results suggest that HLGI can improve self-reported physical and mental well-being in patients with relapsing-remitting multiple sclerosis. Further research is needed to study the effectiveness of this therapy, as well as its mind-body mechanisms of action.

  3. The Bonny Method of Guided Imagery and Music (BMGIM) with Cancer Survivors

    DEFF Research Database (Denmark)

    Bonde, Lars Ole

    . Subquestions 4-8 are addressed in a qualitative investigation in three parts: 1. with focus on the participants’ experience of the BMGIM therapy, 2. with focus on the imagery, 3. with focus on the interrelationship between music and imagery. METHOD The quantitative investigation: Clinical trial......SHORT SUMMARY MAIN RESEARCH QUESTION: What is the influence of ten individual BMGIM sessions on mood and quality of life in cancer survivors? - The investigation addresses the following sub-questions: 1) Can ten BMGIM sessions improve the mood of the participants? 2) Can ten BMGIM sessions improve....../self reports were used: (a) Hospital Anxiety and Depression Scale (HADS) + (a1) Four specific MT/GIM questions (b) European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30), (c) Antonovsky's Sense of Coherence Scale (SOC) After every session questionnaires (a...

  4. Spatial representations elicit dual-coding effects in mental imagery.

    Science.gov (United States)

    Verges, Michelle; Duffy, Sean

    2009-08-01

    Spatial aspects of words are associated with their canonical locations in the real world. Yet little research has tested whether spatial associations denoted in language comprehension generalize to their corresponding images. We directly tested the spatial aspects of mental imagery in picture and word processing (Experiment 1). We also tested whether spatial representations of motion words produce similar perceptual-interference effects as demonstrated by object words (Experiment 2). Findings revealed that words denoting an upward spatial location produced slower responses to targets appearing at the top of the display, whereas words denoting a downward spatial location produced slower responses to targets appearing at the bottom of the display. Perceptual-interference effects did not obtain for pictures or for words lacking a spatial relation. These findings provide greater empirical support for the perceptual-symbols system theory (Barsalou, 1999, 2008). Copyright © 2009 Cognitive Science Society, Inc.

  5. Performance improvements from imagery:evidence that internal visual imagery is superior to external visual imagery for slalom performance

    Directory of Open Access Journals (Sweden)

    Nichola eCallow

    2013-10-01

    Full Text Available We report three experiments investigating the hypothesis that use of internal visual imagery (IVI would be superior to external visual imagery (EVI for the performance of different slalom-based motor tasks. In Experiment 1, three groups of participants (IVI, EVI, and a control group performed a driving-simulation slalom task. The IVI group achieved significantly quicker lap times than EVI and the control group. In Experiment 2, participants performed a downhill running slalom task under both IVI and EVI conditions. Performance was again quickest in the IVI compared to EVI condition, with no differences in accuracy. Experiment 3 used the same group design as Experiment 1, but with participants performing a downhill ski-slalom task. Results revealed the IVI group to be significantly more accurate than the control group, with no significant differences in time taken to complete the task. These results support the beneficial effects of IVI for slalom-based tasks, and significantly advances our knowledge related to the differential effects of visual imagery perspectives on motor performance.

  6. ESTIMATION OF SEAGRASS COVERAGE BY DEPTH INVARIANT INDICES ON QUICKBIRD IMAGERY

    Directory of Open Access Journals (Sweden)

    Muhammad Anshar Amran

    2010-01-01

    Full Text Available Management of seagrass ecosystem requires availability of information on the actual condition of seagrass coverage. Remote sensing technology for seagrass mapping has been used to detect the presence of seagrass coverage, but so far no information on the condition of seagrass could be obtained. Therefore, a research is required using remote sensing imagery to obtain information on the condition of seagrass coverage.The aim of this research is to formulate mathematical relationship between seagrass coverage and depth invariant indices on Quickbird imagery. Transformation was done on multispectral bands which could detect sea floor objects that are in the region of blue, green and red bands.The study areas covered are the seas around Barranglompo Island and Barrangcaddi Island, westward of Makassar city, Indonesia. Various seagrass coverages were detected within the region under study.Mathematical relationship between seagrass coverage and depth invariant indices was obtained by multiple linear regression method. Percentage of seagrass coverage (C was obtained by transformation of depth invariant indices (Xij on Quickbird imagery, with transformation equation as follows:C = 19.934 – 63.347 X12 + 23.239 X23.A good accuracy of 75% for the seagrass coverage was obtained by transformation of depth invariant indices (Xij on Quickbird imagery.

  7. ESIAC: A data products system for ERTS imagery (time-lapse viewing and measuring)

    Science.gov (United States)

    Evans, W. E.; Serebreny, S. M.

    1974-01-01

    An Electronic Satellite Image Analysis Console (ESIAC) has been developed for visual analysis and objective measurement of earth resources imagery. The system is being employed to process imagery for use by USGS investigators in several different disciplines studying dynamic hydrologic conditions. The ESIAC provides facilities for storing registered image sequences in a magnetic video disc memory for subsequent recall, enhancement, and animated display in monochrome or color. The unique feature of the system is the capability to time-lapse the ERTS imagery and/or analytic displays of the imagery. Data products have included quantitative measurements of distances and areas, brightness profiles, and movie loops of selected themes. The applications of these data products are identified and include such diverse problem areas as measurement of snowfield extent, sediment plumes from estuary dicharge, playa inventory, phreatophyte and other vegetation changes. A comparative ranking of the electronic system in terms of accuracy, cost effectiveness and data output shows it to be a viable means of data analysis.

  8. Building change detection via a combination of CNNs using only RGB aerial imageries

    Science.gov (United States)

    Nemoto, Keisuke; Hamaguchi, Ryuhei; Sato, Masakazu; Fujita, Aito; Imaizumi, Tomoyuki; Hikosaka, Shuhei

    2017-10-01

    Building change information extracted from remote sensing imageries is important for various applications such as urban management and marketing planning. The goal of this work is to develop a methodology for automatically capturing building changes from remote sensing imageries. Recent studies have addressed this goal by exploiting 3-D information as a proxy for building height. In contrast, because in practice it is expensive or impossible to prepare 3-D information, we do not rely on 3-D data but focus on using only RGB aerial imageries. Instead, we employ deep convolutional neural networks (CNNs) to extract effective features, and improve change detection accuracy in RGB remote sensing imageries. We consider two aspects of building change detection, building detection and subsequent change detection. Our proposed methodology was tested on several areas, which has some differences such as dominant building characteristics and varying brightness values. On all over the tested areas, the proposed method provides good results for changed objects, with recall values over 75 % with a strict overlap requirement of over 50% in intersection-over-union (IoU). When the IoU threshold was relaxed to over 10%, resulting recall values were over 81%. We conclude that use of CNNs enables accurate detection of building changes without employing 3-D information.

  9. Remote sensing object-oriented approaches coupled with ...

    African Journals Online (AJOL)

    Hence the combined use of new generation sensor imagery and the employment of object-oriented image classification techniques provided more accurate information on Melia invasion in the study area. This is an encouraging result given the high degree of intermingling of Melia with other plants at the study site.

  10. Geographic Object-Based Image Analysis: Towards a new paradigm

    NARCIS (Netherlands)

    Blaschke, T.; Hay, G.J.; Kelly, M.; Lang, S.; Hofmann, P.; Addink, E.A.|info:eu-repo/dai/nl/224281216; Queiroz Feitosa, R.; van der Meer, F.D.|info:eu-repo/dai/nl/138940908; van der Werff, H.M.A.; van Coillie, F.; Tiede, A.

    2014-01-01

    The amount of scientific literature on (Geographic) Object-based Image Analysis – GEOBIA has been and still is sharply increasing. These approaches to analysing imagery have antecedents in earlier research on image segmentation and use GIS-like spatial analysis within classification and feature

  11. Image classification independent of orientation and scale

    Science.gov (United States)

    Arsenault, Henri H.; Parent, Sebastien; Moisan, Sylvain

    1998-04-01

    The recognition of targets independently of orientation has become fairly well developed in recent years for in-plane rotation. The out-of-plane rotation problem is much less advanced. When both out-of-plane rotations and changes of scale are present, the problem becomes very difficult. In this paper we describe our research on the combined out-of- plane rotation problem and the scale invariance problem. The rotations were limited to rotations about an axis perpendicular to the line of sight. The objects to be classified were three kinds of military vehicles. The inputs used were infrared imagery and photographs. We used a variation of a method proposed by Neiberg and Casasent, where a neural network is trained with a subset of the database and a minimum distances from lines in feature space are used for classification instead of nearest neighbors. Each line in the feature space corresponds to one class of objects, and points on one line correspond to different orientations of the same target. We found that the training samples needed to be closer for some orientations than for others, and that the most difficult orientations are where the target is head-on to the observer. By means of some additional training of the neural network, we were able to achieve 100% correct classification for 360 degree rotation and a range of scales over a factor of five.

  12. Internal and External Imagery Effects on Tennis Skills Among Novices.

    Science.gov (United States)

    Dana, Amir; Gozalzadeh, Elmira

    2017-10-01

    The purpose of this study was to determine the effects of internal and external visual imagery perspectives on performance accuracy of open and closed tennis skills (i.e., serve, forehand, and backhand) among novices. Thirty-six young male novices, aged 15-18 years, from a summer tennis program participated. Following initial skill acquisition (12 sessions), baseline assessments of imagery ability and imagery perspective preference were used to assign participants to one of three groups: internal imagery ( n = 12), external imagery ( n = 12), or a no-imagery (mental math exercise) control group ( n = 12). The experimental interventions of 15 minutes of mental imagery (internal or external) or mental math exercises followed by 15 minutes of physical practice were held three times a week for six weeks. The performance accuracy of the groups on the serve, forehand, and backhand strokes was measured at pre- and post-test using videotaping. Results showed significant increases in the performance accuracy of all three tennis strokes in all three groups, but serve accuracy in the internal imagery group and forehand accuracy in the external imagery group showed greater improvements, while backhand accuracy was similarly improved in all three groups. These findings highlight differential efficacy of internal and external visual imagery for performance improvement on complex sport skills in early stage motor learning.

  13. Assessing mental imagery in clinical psychology: A review of imagery measures and a guiding framework

    Science.gov (United States)

    Pearson, David G.; Deeprose, Catherine; Wallace-Hadrill, Sophie M.A.; Heyes, Stephanie Burnett; Holmes, Emily A.

    2013-01-01

    Mental imagery is an under-explored field in clinical psychology research but presents a topic of potential interest and relevance across many clinical disorders, including social phobia, schizophrenia, depression, and post-traumatic stress disorder. There is currently a lack of a guiding framework from which clinicians may select the domains or associated measures most likely to be of appropriate use in mental imagery research. We adopt an interdisciplinary approach and present a review of studies across experimental psychology and clinical psychology in order to highlight the key domains and measures most likely to be of relevance. This includes a consideration of methods for experimentally assessing the generation, maintenance, inspection and transformation of mental images; as well as subjective measures of characteristics such as image vividness and clarity. We present a guiding framework in which we propose that cognitive, subjective and clinical aspects of imagery should be explored in future research. The guiding framework aims to assist researchers in the selection of measures for assessing those aspects of mental imagery that are of most relevance to clinical psychology. We propose that a greater understanding of the role of mental imagery in clinical disorders will help drive forward advances in both theory and treatment. PMID:23123567

  14. Transferring Deep Convolutional Neural Networks for the Scene Classification of High-Resolution Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    Fan Hu

    2015-11-01

    Full Text Available Learning efficient image representations is at the core of the scene classification task of remote sensing imagery. The existing methods for solving the scene classification task, based on either feature coding approaches with low-level hand-engineered features or unsupervised feature learning, can only generate mid-level image features with limited representative ability, which essentially prevents them from achieving better performance. Recently, the deep convolutional neural networks (CNNs, which are hierarchical architectures trained on large-scale datasets, have shown astounding performance in object recognition and detection. However, it is still not clear how to use these deep convolutional neural networks for high-resolution remote sensing (HRRS scene classification. In this paper, we investigate how to transfer features from these successfully pre-trained CNNs for HRRS scene classification. We propose two scenarios for generating image features via extracting CNN features from different layers. In the first scenario, the activation vectors extracted from fully-connected layers are regarded as the final image features; in the second scenario, we extract dense features from the last convolutional layer at multiple scales and then encode the dense features into global image features through commonly used feature coding approaches. Extensive experiments on two public scene classification datasets demonstrate that the image features obtained by the two proposed scenarios, even with a simple linear classifier, can result in remarkable performance and improve the state-of-the-art by a significant margin. The results reveal that the features from pre-trained CNNs generalize well to HRRS datasets and are more expressive than the low- and mid-level features. Moreover, we tentatively combine features extracted from different CNN models for better performance.

  15. Active training paradigm for motor imagery BCI.

    Science.gov (United States)

    Li, Junhua; Zhang, Liqing

    2012-06-01

    Brain-computer interface (BCI) allows the use of brain activities for people to directly communicate with the external world or to control external devices without participation of any peripheral nerves and muscles. Motor imagery is one of the most popular modes in the research field of brain-computer interface. Although motor imagery BCI has some advantages compared with other modes of BCI, such as asynchronization, it is necessary to require training sessions before using it. The performance of trained BCI system depends on the quality of training samples or the subject engagement. In order to improve training effect and decrease training time, we proposed a new paradigm where subjects participated in training more actively than in the traditional paradigm. In the traditional paradigm, a cue (to indicate what kind of motor imagery should be imagined during the current trial) is given to the subject at the beginning of a trial or during a trial, and this cue is also used as a label for this trial. It is usually assumed that labels for trials are accurate in the traditional paradigm, although subjects may not have performed the required or correct kind of motor imagery, and trials may thus be mislabeled. And then those mislabeled trials give rise to interference during model training. In our proposed paradigm, the subject is required to reconfirm the label and can correct the label when necessary. This active training paradigm may generate better training samples with fewer inconsistent labels because it overcomes mistakes when subject's motor imagination does not match the given cues. The experiments confirm that our proposed paradigm achieves better performance; the improvement is significant according to statistical analysis.

  16. Imagery helps in the treatment of epilepsy

    International Nuclear Information System (INIS)

    Mauguiere, F.; Merlet, I.; Ryvlin, P.; Le Bars, D.

    1996-01-01

    The cerebral imagery (NMR imaging, single photon emission computed tomography, positron computed tomography) can be useful in the therapeutic treatment of the epilepsy. Indeed, it allows to delimit the brain part which, in becoming hyper excitable after a cerebral injury is the source of epileptic crises. The surgical ablation is a possible solution to suppress the crises when the anti epileptic drugs are useless. (O.M.)

  17. Study of application of ERTS-A imagery to fracture related mine safety hazards in the coal mining industry

    Science.gov (United States)

    Wier, C. E.; Wobber, F. J. (Principal Investigator); Russell, O. R.; Amato, R. V.

    1973-01-01

    The author has identified the following significant results. The utility of ERTS-1/high altitude aircraft imagery to detect underground mine hazards is strongly suggested. A 1:250,000 scale mined lands map of the Vincennes Quadrangle, Indiana has been prepared. This map is a prototype for a national mined lands inventory and will be distributed to State and Federal offices.

  18. Mental imagery affects subsequent automatic defense responses

    Directory of Open Access Journals (Sweden)

    Muriel A Hagenaars

    2015-06-01

    Full Text Available Automatic defense responses promote survival and appropriate action under threat. They have also been associated with the development of threat-related psychiatric syndromes. Targeting such automatic responses during threat may be useful in populations with frequent threat exposure. Here, two experiments explored whether mental imagery as a pre-trauma manipulation could influence fear bradycardia (a core characteristic of freezing during subsequent analogue trauma (affective picture viewing. Image-based interventions have proven successful in the treatment of threat-related disorders, and are easily applicable. In Experiment 1 43 healthy participants were randomly assigned to an imagery script condition. Participants executed a passive viewing task with blocks of neutral, pleasant and unpleasant pictures after listening to an auditory script that was either related (with a positive or a negative outcome or unrelated to the unpleasant pictures from the passive viewing task. Heart rate was assessed during script listening and during passive viewing. Imagining negative related scripts resulted in greater bradycardia (neutral-unpleasant contrast than imagining positive scripts, especially unrelated. This effect was replicated in Experiment 2 (N = 51, again in the neutral-unpleasant contrast. An extra no-script condition showed that bradycardia was not induced by the negative related script, but rather that a positive script attenuated bradycardia. These preliminary results might indicate reduced vigilance after unrelated positive events. Future research should replicate these findings using a larger sample. Either way, the findings show that highly automatic defense behavior can be influenced by relatively simple mental imagery manipulations.

  19. Effect of Guided Imagery on Maternal Fetal Attachment in Nulliparous Women with Unplanned Pregnancy

    OpenAIRE

    Masoumeh Kordi; Maryam Fasanghari; Negar Asgharipour; Habibollah Esmaily

    2016-01-01

    Introduction and Objectives: Nulliparous women with unplanned pregnancy experience high levels of anxiety, which may adversely affect maternal-fetal attachment. Therefore, in this study, we aimed to determine the effect of guided imagery on maternal-fetal attachment in nulliparous women with unplanned pregnancy. Materials and Methods: In this clinical trial, 67 nulliparous women with unplanned pregnancy were randomly divided into two groups of intervention (n=35) and control (n=32) in 2015. D...

  20. Geovisualisation of relief in a virtual reality system on the basis of low-level aerial imagery

    Science.gov (United States)

    Halik, Łukasz; Smaczyński, Maciej

    2017-12-01

    The aim of the following paper was to present the geomatic process of transforming low-level aerial imagery obtained with unmanned aerial vehicles (UAV) into a digital terrain model (DTM) and implementing the model into a virtual reality system (VR). The object of the study was a natural aggretage heap of an irregular shape and denivelations up to 11 m. Based on the obtained photos, three point clouds (varying in the level of detail) were generated for the 20,000-m2-area. For further analyses, the researchers selected the point cloud with the best ratio of accuracy to output file size. This choice was made based on seven control points of the heap surveyed in the field and the corresponding points in the generated 3D model. The obtained several-centimetre differences between the control points in the field and the ones from the model might testify to the usefulness of the described algorithm for creating large-scale DTMs for engineering purposes. Finally, the chosen model was implemented into the VR system, which enables the most lifelike exploration of 3D terrain plasticity in real time, thanks to the first person view mode (FPV). In this mode, the user observes an object with the aid of a Head- mounted display (HMD), experiencing the geovisualisation from the inside, and virtually analysing the terrain as a direct animator of the observations.