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...

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.

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.

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%.

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...

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.

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

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.

Normalization of satellite imagery

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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.

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.

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.

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

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.

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).

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.

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.

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.

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

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.

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.

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.

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.

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...

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...

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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 ...

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...

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...

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...

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...

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...

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...

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.

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

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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

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.

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.

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.

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...

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.

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.

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

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.

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.

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.

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...

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...

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...

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.

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...

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...

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...

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...

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.

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.

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.

[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.

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.

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.

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

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.

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

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.

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.

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

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

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...

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...

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...

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...

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...

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...

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.

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.

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.

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,...

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.

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.

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.

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.

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...

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.

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.

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...

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.

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.

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

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

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.

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.

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.

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.

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...

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.

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)

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.

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.

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.

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.

[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.

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

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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.

Multispectral image analysis for object recognition and classification

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Viau, C. R.; Payeur, P.; Cretu, A.-M.

2016-05-01

Computer and machine vision applications are used in numerous fields to analyze static and dynamic imagery in order to assist or automate decision-making processes. Advancements in sensor technologies now make it possible to capture and visualize imagery at various wavelengths (or bands) of the electromagnetic spectrum. Multispectral imaging has countless applications in various fields including (but not limited to) security, defense, space, medical, manufacturing and archeology. The development of advanced algorithms to process and extract salient information from the imagery is a critical component of the overall system performance. The fundamental objective of this research project was to investigate the benefits of combining imagery from the visual and thermal bands of the electromagnetic spectrum to improve the recognition rates and accuracy of commonly found objects in an office setting. A multispectral dataset (visual and thermal) was captured and features from the visual and thermal images were extracted and used to train support vector machine (SVM) classifiers. The SVM's class prediction ability was evaluated separately on the visual, thermal and multispectral testing datasets.

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

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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.

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

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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

Cloud cover typing from environmental satellite imagery. Discriminating cloud structure with Fast Fourier Transforms (FFT)

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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.

Single-trial effective brain connectivity patterns enhance discriminability of mental imagery tasks

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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.

USGS Imagery Only Base Map Service from The National Map

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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...

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

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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.

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

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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.

Non-Drug Pain Relief: Imagery

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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 ...

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

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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.

Kinesthetic imagery of musical performance.

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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.

Visualizing UAS-collected imagery using augmented reality

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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.

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

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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.

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

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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.

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

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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

The use of remote sensing imagery for environmental land use and flood hazard mapping

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Mouat, D. A.; Miller, D. A.; Foster, K. E.

1976-01-01

Flood hazard maps have been constructed for Graham, Yuma, and Yavapai Counties in Arizona using remote sensing techniques. Watershed maps of priority areas were selected on the basis of their interest to the county planning staff and represented areas of imminent or ongoing development and those known to be subject to inundation by storm runoff. Landsat color infrared imagery at scales of 1:1,000,000, 1:500,000, and 1:250,000 was used together with high-altitude aerial photography at scales of 1:120,000 and 1:60,000 to determine drainage patterns and erosional features, soil type, and the extent and type of ground cover. The satellite imagery was used in the form of 70 mm chips for enhancement in a color additive viewer and in all available enlargement modes. Field checking served as the main backup to the interpretations. Areas with high susceptibility to flooding were determined with a high level of confidence from the remotely sensed imagery.

The efficacy of imagery rescripting (IR) for social phobia: a randomized controlled trial.

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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.

Pornographic imagery and prevalence of paraphilia.

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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.

User Validation of VIIRS Satellite Imagery

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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.

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.

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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...

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

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.

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.

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%.

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...

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

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.

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.

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.

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.

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.

Kinesthetic imagery of musical performance

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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.

Hypnagogic imagery and EEG activity.

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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.

Alcohol imagery on New Zealand television

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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.

Motor imagery training: Kinesthetic imagery strategy and inferior parietal fMRI activation.

Science.gov (United States)

Lebon, Florent; Horn, Ulrike; Domin, Martin; Lotze, Martin

2018-04-01

Motor imagery (MI) is the mental simulation of action frequently used by professionals in different fields. However, with respect to performance, well-controlled functional imaging studies on MI training are sparse. We investigated changes in fMRI representation going along with performance changes of a finger sequence (error and velocity) after MI training in 48 healthy young volunteers. Before training, we tested the vividness of kinesthetic and visual imagery. During tests, participants were instructed to move or to imagine moving the fingers of the right hand in a specific order. During MI training, participants repeatedly imagined the sequence for 15 min. Imaging analysis was performed using a full-factorial design to assess brain changes due to imagery training. We also used regression analyses to identify those who profited from training (performance outcome and gain) with initial imagery scores (vividness) and fMRI activation magnitude during MI at pre-test (MI pre ). After training, error rate decreased and velocity increased. We combined both parameters into a common performance index. FMRI activation in the left inferior parietal lobe (IPL) was associated with MI and increased over time. In addition, fMRI activation in the right IPL during MI pre was associated with high initial kinesthetic vividness. High kinesthetic imagery vividness predicted a high performance after training. In contrast, occipital activation, associated with visual imagery strategies, showed a negative predictive value for performance. Our data echo the importance of high kinesthetic vividness for MI training outcome and consider IPL as a key area during MI and through MI training. © 2018 Wiley Periodicals, Inc.

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.

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

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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

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

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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.

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.)

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.)

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

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.

Measuring Creative Imagery Abilities

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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.

A Data Mining Approach for Sharpening Thermal Satellite Imagery over Land

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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

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

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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

Tracking Dynamic Northern Surface Water Changes with High-Frequency Planet CubeSat Imagery

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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

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...

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.

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.

Facilitating the exploitation of ERTS-1 imagery utilizing snow enhancement techniques

Science.gov (United States)

Wobber, F. J. (Principal Investigator); Martin, K. R.; Amato, R. V.

1973-01-01

The author has identified the following significant results. Snow cover in combination with low angle solar illumination has been found to provide increased tonal contrast of surface feature and is useful in the detection of bedrock fractures. Identical fracture systems were not as readily detectable in the fall due to the lack of a contrasting surface medium (snow) and a relatively high sun angle. Low angle solar illumination emphasizes topographic expressions not as apparent on imagery acquired with a higher sun angle. A strong correlation exists between the major fracture-lineament directions interpreted from multi-sensor imagery (including snow-free and snow cover ERTS) and the strike of bedrock joints recorded in the field indicating the structural origin of interpreted fracture-lineaments. A fracture-annotated ERTS-1 photo base map (1:250,000 scale) is being prepared for western Massachusetts. The map will document the utilization of ERTS-1 imagery for geological analysis in comparative snow-free and snow-covered terrain.

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...

Earthquake Damage Assessment Using Objective Image Segmentation: A Case Study of 2010 Haiti Earthquake

Science.gov (United States)

Oommen, Thomas; Rebbapragada, Umaa; Cerminaro, Daniel

2012-01-01

In this study, we perform a case study on imagery from the Haiti earthquake that evaluates a novel object-based approach for characterizing earthquake induced surface effects of liquefaction against a traditional pixel based change technique. Our technique, which combines object-oriented change detection with discriminant/categorical functions, shows the power of distinguishing earthquake-induced surface effects from changes in buildings using the object properties concavity, convexity, orthogonality and rectangularity. Our results suggest that object-based analysis holds promise in automatically extracting earthquake-induced damages from high-resolution aerial/satellite imagery.

Assessment of motor imagery ability and training

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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.

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.

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.

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.

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

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.

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.

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...

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

High Spatial Resolution Visual Band Imagery Outperforms Medium Resolution Spectral Imagery for Ecosystem Assessment in the Semi-Arid Brazilian Sertão

Directory of Open Access Journals (Sweden)

Ran Goldblatt

2017-12-01

Full Text Available Semi-arid ecosystems play a key role in global agricultural production, seasonal carbon cycle dynamics, and longer-run climate change. Because semi-arid landscapes are heterogeneous and often sparsely vegetated, repeated and large-scale ecosystem assessments of these regions have to date been impossible. Here, we assess the potential of high-spatial resolution visible band imagery for semi-arid ecosystem mapping. We use WorldView satellite imagery at 0.3–0.5 m resolution to develop a reference data set of nearly 10,000 labeled examples of three classes—trees, shrubs/grasses, and bare land—across 1000 km 2 of the semi-arid Sertão region of northeast Brazil. Using Google Earth Engine, we show that classification with low-spectral but high-spatial resolution input (WorldView outperforms classification with the full spectral information available from Landsat 30 m resolution imagery as input. Classification with high spatial resolution input improves detection of sparse vegetation and distinction between trees and seasonal shrubs and grasses, two features which are lost at coarser spatial (but higher spectral resolution input. Our total tree cover estimates for the study area disagree with recent estimates using other methods that may underestimate treecover because they confuse trees with seasonal vegetation (shrubs and grasses. This distinction is important for monitoring seasonal and long-run carbon cycle and ecosystem health. Our results suggest that newer remote sensing products that promise high frequency global coverage at high spatial but lower spectral resolution may offer new possibilities for direct monitoring of the world’s semi-arid ecosystems, and we provide methods that could be scaled to do so.

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.

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.

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)...

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)...

Utilization-based object recognition in confined spaces

Science.gov (United States)

Shirkhodaie, Amir; Telagamsetti, Durga; Chan, Alex L.

2017-05-01

Recognizing substantially occluded objects in confined spaces is a very challenging problem for ground-based persistent surveillance systems. In this paper, we discuss the ontology inference of occluded object recognition in the context of in-vehicle group activities (IVGA) and describe an approach that we refer to as utilization-based object recognition method. We examine the performance of three types of classifiers tailored for the recognition of objects with partial visibility, namely, (1) Hausdorff Distance classifier, (2) Hamming Network classifier, and (3) Recurrent Neural Network classifier. In order to train these classifiers, we have generated multiple imagery datasets containing a mixture of common objects appearing inside a vehicle with full or partial visibility and occultation. To generate dynamic interactions between multiple people, we model the IVGA scenarios using a virtual simulation environment, in which a number of simulated actors perform a variety of IVGA tasks independently or jointly. This virtual simulation engine produces the much needed imagery datasets for the verification and validation of the efficiency and effectiveness of the selected object recognizers. Finally, we improve the performance of these object recognizers by incorporating human gestural information that differentiates various object utilization or handling methods through the analyses of dynamic human-object interactions (HOI), human-human interactions (HHI), and human-vehicle interactions (HVI) in the context of IVGA.

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

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...

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...

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.

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.

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

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.

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...

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.

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.

Building a Better Urban Picture: Combining Day and Night Remote Sensing Imagery

Directory of Open Access Journals (Sweden)

Qingling Zhang

2015-09-01

Full Text Available Urban areas play a very important role in global climate change. There is increasing need to understand global urban areas with sufficient spatial details for global climate change mitigation. Remote sensing imagery, such as medium resolution Landsat daytime multispectral imagery and coarse resolution Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS nighttime light imagery, has provided a powerful tool for characterizing and mapping cities, with advantages and disadvantages. Here we propose a framework to merge cloud and cloud shadow-free Landsat Normalized Difference Vegetation Index (NDVI composite and DMSP/OLS Night Time Light (NTL to characterize global urban areas at a 30 m resolution, through a Normalized Difference Urban Index (NDUI to make full use of them while minimizing their limitations. We modify the maximum NDVI value multi-date image compositing method to generate the cloud and cloud shadow-free Landsat NDVI composite, which is critical for generating a global NDUI. Evaluation results show the NDUI can effectively increase the separability between urban areas and bare lands as well as farmland, capturing large scale urban extents and, at the same time, providing sufficient spatial details inside urban areas. With advanced cloud computing facilities and the open Landsat data archives available, NDUI has the potential for global studies at the 30 m scale.

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

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.

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.

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.

Language comprehenders retain implied shape and orientation of objects.

Science.gov (United States)

Pecher, Diane; van Dantzig, Saskia; Zwaan, Rolf A; Zeelenberg, René

2009-06-01

According to theories of embodied cognition, language comprehenders simulate sensorimotor experiences to represent the meaning of what they read. Previous studies have shown that picture recognition is better if the object in the picture matches the orientation or shape implied by a preceding sentence. In order to test whether strategic imagery may explain previous findings, language comprehenders first read a list of sentences in which objects were mentioned. Only once the complete list had been read was recognition memory tested with pictures. Recognition performance was better if the orientation or shape of the object matched that implied by the sentence, both immediately after reading the complete list of sentences and after a 45-min delay. These results suggest that previously found match effects were not due to strategic imagery and show that details of sensorimotor simulations are retained over longer periods.

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.

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."

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...

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.

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.

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%.

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…

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.

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 ...

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.

Visualising abortion: emotion discourse and fetal imagery in a contemporary abortion debate.

Science.gov (United States)

Hopkins, Nick; Zeedyk, Suzanne; Raitt, Fiona

2005-07-01

This paper presents an analysis of a recent UK anti-abortion campaign in which the use of fetal imagery--especially images of fetal remains--was a prominent issue. A striking feature of the texts produced by the group behind the campaign was the emphasis given to the emotions of those viewing such imagery. Traditionally, social scientific analyses of mass communication have problematised references to emotion and viewed them as being of significance because of their power to subvert the rational appraisal of message content. However, we argue that emotion discourse may be analysed from a different perspective. As the categorisation of the fetus is a social choice and contested, it follows that all protagonists in the abortion debate (whether pro- or anti-abortion) are faced with the task of constructing the fetus as a particular entity rather than another, and that they must seek to portray their preferred categorisation as objective and driven by an 'out-there' reality. Following this logic, we show how the emotional experience of viewing fetal imagery was represented so as to ground an anti-abortion construction of the fetus as objective. We also show how the arguments of the (pro-abortion) opposition were construed as totally discrepant with such emotions and so were invalidated as deceitful distortions of reality. The wider significance of this analysis for social scientific analyses of the abortion debate is discussed.

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…

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.

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.

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

New percepts via mental imagery?

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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.

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

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.

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.

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.

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...

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.

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…

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

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

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...

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

Tobacco imagery on New Zealand television 2002-2004.

Science.gov (United States)

McGee, Rob; Ketchel, Juanita

2006-10-01

Considerable emphasis has been placed on the importance of tobacco imagery in the movies as one of the "drivers" of smoking among young people. Findings are presented from a content analysis of 98 hours of prime-time programming on New Zealand television 2004, identifying 152 scenes with tobacco imagery, and selected characteristics of those scenes. About one in four programmes contained tobacco imagery, most of which might be regarded as "neutral or positive". This amounted to about two scenes containing such imagery for every hour of programming. A comparison with our earlier content analysis of programming in 2002 indicated little change in the level of tobacco imagery. The effect of this imagery in contributing to young viewers taking up smoking, and sustaining the addiction among those already smoking, deserves more research attention.

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

An Object-Based Machine Learning Classification Procedure for Mapping Impoundments in Brazil's Amazon-Cerrado Agricultural Frontier

Science.gov (United States)

Solvik, K.; Macedo, M.; Graesser, J.; Lathuilliere, M. J.

2017-12-01

Large-scale agriculture and cattle ranching in Brazil has driving the creation of tens of thousands of small stream impoundments to provide water for crops and livestock. These impoundments are a source of methane emissions and have significant impacts on stream temperature, connectivity, and water use over a large region. Due to their large numbers and small size, they are difficult to map using conventional methods. Here, we present a two-stage object-based supervised classification methodology for identifying man-made impoundments in Brazil. First, in Google Earth Engine pixels are classified as water or non-water using satellite data and HydroSHEDS products as predictors. Second, using Python's scikit-learn and scikit-image modules the water objects are classified as man-made or natural based on a variety of shape and spectral properties. Both classifications are performed by a random forest classifier. Training data is acquired by visually identifying impoundments and natural water bodies using high resolution satellite imagery from Google Earth.This methodology was applied to the state of Mato Grosso using a cloud-free mosaic of Sentinel 1 (10m resolution) radar and Sentinel 2 (10-20m) multispectral data acquired during the 2016 dry season. Independent test accuracy was estimated at 95% for the first stage and 93% for the second. We identified 54,294 man-made impoundments in Mato Grosso in 2016. The methodology is generalizable to other high resolution satellite data and has been tested on Landsat 5 and 8 imagery. Applying the same approach to Landsat 8 images (30 m), we identified 35,707 impoundments in the 2015 dry season. The difference in number is likely because the coarser-scale imagery fails to detect small (work will apply this approach to satellite time series for the entire Amazon-Cerrado frontier, allowing us to track changes in the number, size, and distribution of man-made impoundments. Automated impoundment mapping over large areas may help with

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...

Applicability of Earth Observation for Identifying Small-Scale Mining Footprints in a Wet Tropical Region

Directory of Open Access Journals (Sweden)

Celso M. Isidro

2017-09-01

Full Text Available The unpredictable climate in wet tropical regions along with the spatial resolution limitations of some satellite imageries make detecting and mapping artisanal and small-scale mining (ASM challenging. The objective of this study was to test the utility of Pleiades and SPOT imagery with an object-based support vector machine (OB-SVM classifier for the multi-temporal remote sensing of ASM and other land cover including a large-scale mine in the Didipio catchment in the Philippines. Historical spatial data on location and type of ASM mines were collected from the field and were utilized as training data for the OB-SVM classifier. The classification had an overall accuracy between 87% and 89% for the three different images—Pleiades-1A for the 2013 and 2014 images and SPOT-6 for the 2016 image. The main land use features, particularly the Didipio large-scale mine, were well identified by the OB-SVM classifier, however there were greater commission errors for the mapping of small-scale mines. The lack of consistency in their shape and their small area relative to pixel sizes meant they were often not distinguished from other land clearance types (i.e., open land. To accurately estimate the total area of each land cover class, we calculated bias-adjusted surface areas based on misclassification values. The analysis showed an increase in small-scale mining areas from 91,000 m2—or 0.2% of the total catchment area—in March 2013 to 121,000 m2—or 0.3%—in May 2014, and then a decrease to 39,000 m2—or 0.1%—in January 2016.

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...

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.

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.

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.

The effects of guided imagery on comfort, depression, anxiety, and stress of psychiatric inpatients with depressive disorders.

Science.gov (United States)

Apóstolo, João Luís Alves; Kolcaba, Katharine

2009-12-01

This article describes the efficacy of a guided imagery intervention for decreasing depression, anxiety, and stress and increasing comfort in psychiatric inpatients with depressive disorders. A quasi-experimental design sampled 60 short-term hospitalized depressive patients selected consecutively. The experimental group listened to a guided imagery compact disk once a day for 10 days. The Psychiatric Inpatients Comfort Scale and the Depression, Anxiety, and Stress Scales (DASS-21) were self-administered at two time points: prior to the intervention (T1) and 10 days later (T2). Comfort and DASS-21 were also assessed in the usual care group at T1 and T2. Repeated measures revealed that the treatment group had significantly improved comfort and decreased depression, anxiety, and stress over time.

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

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...

Multi-scale 46-year remote sensing change detection of diamond mining and land cover in a conflict and post-conflict setting

Science.gov (United States)

Dewitt, Jessica D.; Chirico, Peter G.; Bergstresser, Sarah E.; Warner, Timothy A.

2017-01-01

The town of Tortiya was created in the rural northern region of Côte d′Ivoire in the late 1940s to house workers for a new diamond mine. Nearly three decades later, the closure of the industrial-scale diamond mine in 1975 did not diminish the importance of diamond profits to the region's economy, and resulted in the growth of artisanal and small-scale diamond mining (ASM) within the abandoned industrial-scale mining concession. In the early 2000s, the violent conflict that arose in Côte d′Ivoire highlighted the importance of ASM land use to the local economy, but also brought about international concerns that diamond profits were being used to fund the rebellion. In recent years, cashew plantations have expanded exponentially in the region, diversifying economic activity, but also creating the potential for conflict between diamond mining and agricultural land uses. As the government looks to address the future of Tortiya and this potential conflict, a detailed spatio-temporal understanding of the changes in these two land uses over time may assist in informing policymaking. Remotely sensed imagery presents an objective and detailed spatial record of land use/land cover (LULC), and change detection methods can provide quantitative insight regarding regional land cover trends. However, the vastly different scales of ASM and cashew orchards present a unique challenge to comprehensive understanding of land use change in the region. In this study, moderate-scale categories of LULC, including cashew orchards, uncultivated forest, urban space, mining/ bare, and mixed vegetation, were produced through supervised classification of Landsat multispectral imagery from 1984, 1991, 2000, 2007, and 2014. The fine-scale ASM land use was identified through manual interpretation of annually acquired high resolution satellite imagery. Corona imagery was also integrated into the study to extend the temporal duration of the remote sensing record back to the period of industrial-scale

Using Low Resolution Satellite Imagery for Yield Prediction and Yield Anomaly Detection

Directory of Open Access Journals (Sweden)

Oscar Rojas

2013-04-01

Full Text Available Low resolution satellite imagery has been extensively used for crop monitoring and yield forecasting for over 30 years and plays an important role in a growing number of operational systems. The combination of their high temporal frequency with their extended geographical coverage generally associated with low costs per area unit makes these images a convenient choice at both national and regional scales. Several qualitative and quantitative approaches can be clearly distinguished, going from the use of low resolution satellite imagery as the main predictor of final crop yield to complex crop growth models where remote sensing-derived indicators play different roles, depending on the nature of the model and on the availability of data measured on the ground. Vegetation performance anomaly detection with low resolution images continues to be a fundamental component of early warning and drought monitoring systems at the regional scale. For applications at more detailed scales, the limitations created by the mixed nature of low resolution pixels are being progressively reduced by the higher resolution offered by new sensors, while the continuity of existing systems remains crucial for ensuring the availability of long time series as needed by the majority of the yield prediction methods used today.

Motor experience with a sport-specific implement affects motor imagery

Science.gov (United States)

Zhu, Hua; Shen, Cheng; Zhang, Jian

2018-01-01

The present study tested whether sport-specific implements facilitate motor imagery, whereas nonspecific implements disrupt motor imagery. We asked a group of basketball players (experts) and a group of healthy controls (novices) to physically perform (motor execution) and mentally simulate (motor imagery) basketball throws. Subjects produced motor imagery when they were holding a basketball, a volleyball, or nothing. Motor imagery performance was measured by temporal congruence, which is the correspondence between imagery and execution times estimated as (imagery time minus execution time) divided by (imagery time plus execution time), as well as the vividness of motor imagery. Results showed that experts produced greater temporal congruence and vividness of kinesthetic imagery while holding a basketball compared to when they were holding nothing, suggesting a facilitation effect from sport-specific implements. In contrast, experts produced lower temporal congruence and vividness of kinesthetic imagery while holding a volleyball compared to when they were holding nothing, suggesting the interference effect of nonspecific implements. Furthermore, we found a negative correlation between temporal congruence and the vividness of kinesthetic imagery in experts while holding a basketball. On the contrary, the implement manipulation did not modulate the temporal congruence of novices. Our findings suggest that motor representation in experts is built on motor experience associated with specific-implement use and thus was subjected to modulation of the implement held. We conclude that sport-specific implements facilitate motor imagery, whereas nonspecific implements could disrupt motor representation in experts. PMID:29719738

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.

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...

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.

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.

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

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

Automated cloud screening of AVHRR imagery using split-and-merge clustering

Science.gov (United States)

Gallaudet, Timothy C.; Simpson, James J.

1991-01-01

Previous methods to segment clouds from ocean in AVHRR imagery have shown varying degrees of success, with nighttime approaches being the most limited. An improved method of automatic image segmentation, the principal component transformation split-and-merge clustering (PCTSMC) algorithm, is presented and applied to cloud screening of both nighttime and daytime AVHRR data. The method combines spectral differencing, the principal component transformation, and split-and-merge clustering to sample objectively the natural classes in the data. This segmentation method is then augmented by supervised classification techniques to screen clouds from the imagery. Comparisons with other nighttime methods demonstrate its improved capability in this application. The sensitivity of the method to clustering parameters is presented; the results show that the method is insensitive to the split-and-merge thresholds.

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.

Auditory and motor imagery modulate learning in music performance.

Science.gov (United States)

Brown, Rachel M; Palmer, Caroline

2013-01-01

Skilled performers such as athletes or musicians can improve their performance by imagining the actions or sensory outcomes associated with their skill. Performers vary widely in their auditory and motor imagery abilities, and these individual differences influence sensorimotor learning. It is unknown whether imagery abilities influence both memory encoding and retrieval. We examined how auditory and motor imagery abilities influence musicians' encoding (during Learning, as they practiced novel melodies), and retrieval (during Recall of those melodies). Pianists learned melodies by listening without performing (auditory learning) or performing without sound (motor learning); following Learning, pianists performed the melodies from memory with auditory feedback (Recall). During either Learning (Experiment 1) or Recall (Experiment 2), pianists experienced either auditory interference, motor interference, or no interference. Pitch accuracy (percentage of correct pitches produced) and temporal regularity (variability of quarter-note interonset intervals) were measured at Recall. Independent tests measured auditory and motor imagery skills. Pianists' pitch accuracy was higher following auditory learning than following motor learning and lower in motor interference conditions (Experiments 1 and 2). Both auditory and motor imagery skills improved pitch accuracy overall. Auditory imagery skills modulated pitch accuracy encoding (Experiment 1): Higher auditory imagery skill corresponded to higher pitch accuracy following auditory learning with auditory or motor interference, and following motor learning with motor or no interference. These findings suggest that auditory imagery abilities decrease vulnerability to interference and compensate for missing auditory feedback at encoding. Auditory imagery skills also influenced temporal regularity at retrieval (Experiment 2): Higher auditory imagery skill predicted greater temporal regularity during Recall in the presence of

Auditory and motor imagery modulate learning in music performance

Science.gov (United States)

Brown, Rachel M.; Palmer, Caroline

2013-01-01

Skilled performers such as athletes or musicians can improve their performance by imagining the actions or sensory outcomes associated with their skill. Performers vary widely in their auditory and motor imagery abilities, and these individual differences influence sensorimotor learning. It is unknown whether imagery abilities influence both memory encoding and retrieval. We examined how auditory and motor imagery abilities influence musicians' encoding (during Learning, as they practiced novel melodies), and retrieval (during Recall of those melodies). Pianists learned melodies by listening without performing (auditory learning) or performing without sound (motor learning); following Learning, pianists performed the melodies from memory with auditory feedback (Recall). During either Learning (Experiment 1) or Recall (Experiment 2), pianists experienced either auditory interference, motor interference, or no interference. Pitch accuracy (percentage of correct pitches produced) and temporal regularity (variability of quarter-note interonset intervals) were measured at Recall. Independent tests measured auditory and motor imagery skills. Pianists' pitch accuracy was higher following auditory learning than following motor learning and lower in motor interference conditions (Experiments 1 and 2). Both auditory and motor imagery skills improved pitch accuracy overall. Auditory imagery skills modulated pitch accuracy encoding (Experiment 1): Higher auditory imagery skill corresponded to higher pitch accuracy following auditory learning with auditory or motor interference, and following motor learning with motor or no interference. These findings suggest that auditory imagery abilities decrease vulnerability to interference and compensate for missing auditory feedback at encoding. Auditory imagery skills also influenced temporal regularity at retrieval (Experiment 2): Higher auditory imagery skill predicted greater temporal regularity during Recall in the presence of

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.

Closing the mind's eye: incoming luminance signals disrupt visual imagery.

Directory of Open Access Journals (Sweden)

Rachel Sherwood

Full Text Available Mental imagery has been associated with many cognitive functions, both high and low-level. Despite recent scientific advances, the contextual and environmental conditions that most affect the mechanisms of visual imagery remain unclear. It has been previously shown that the greater the level of background luminance the weaker the effect of imagery on subsequent perception. However, in these experiments it was unclear whether the luminance was affecting imagery generation or storage of a memory trace. Here, we report that background luminance can attenuate both mental imagery generation and imagery storage during an unrelated cognitive task. However, imagery generation was more sensitive to the degree of luminance. In addition, we show that these findings were not due to differential dark adaptation. These results suggest that afferent visual signals can interfere with both the formation and priming-memory effects associated with visual imagery. It follows that background luminance may be a valuable tool for investigating imagery and its role in various cognitive and sensory processes.

Motor imagery beyond the motor repertoire: Activity in the primary visual cortex during kinesthetic motor imagery of difficult whole body movements.

Science.gov (United States)

Mizuguchi, N; Nakata, H; Kanosue, K

2016-02-19

To elucidate the neural substrate associated with capabilities for kinesthetic motor imagery of difficult whole-body movements, we measured brain activity during a trial involving both kinesthetic motor imagery and action observation as well as during a trial with action observation alone. Brain activity was assessed with functional magnetic resonance imaging (fMRI). Nineteen participants imagined three types of whole-body movements with the horizontal bar: the giant swing, kip, and chin-up during action observation. No participant had previously tried to perform the giant swing. The vividness of kinesthetic motor imagery as assessed by questionnaire was highest for the chin-up, less for the kip and lowest for the giant swing. Activity in the primary visual cortex (V1) during kinesthetic motor imagery with action observation minus that during action observation alone was significantly greater in the giant swing condition than in the chin-up condition within participants. Across participants, V1 activity of kinesthetic motor imagery of the kip during action observation minus that during action observation alone was negatively correlated with vividness of the kip imagery. These results suggest that activity in V1 is dependent upon the capability of kinesthetic motor imagery for difficult whole-body movements. Since V1 activity is likely related to the creation of a visual image, we speculate that visual motor imagery is recruited unintentionally for the less vivid kinesthetic motor imagery of difficult whole-body movements. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

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.

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.

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

The role of mental imagery in non-clinical paranoia.

Science.gov (United States)

Bullock, Gemma; Newman-Taylor, Katherine; Stopa, Luisa

2016-03-01

Cognitive models of paranoia incorporate many of the processes implicated in the maintenance of anxiety disorders. Despite this, the role of mental imagery in paranoia remains under-researched. The current study examined the impact of a self-imagery manipulation in people with high non-clinical paranoia. We used a mixed design with one between-subjects variable (type of self-imagery) and one within-subjects variable (time--pre and post imagery manipulation). Thirty participants with high trait paranoia were allocated alternately to a positive or negative self-imagery condition. Scripts were used to elicit positive and negative self-imagery. All participants completed self-report state measures of paranoia, mood, self-esteem and self-compassion. Group by time interaction effects were found for each of the dependent variables. Positive imagery led to less state paranoia, anxiety and negative affect, and more positive affect, self-esteem and self-compassion, compared with the negative imagery group. This was a non-blind study, limited by allocation method and a brief time-frame which did not allow us to assess longevity of effects. We recruited a relatively small and predominantly female sample of people with high non-clinical paranoia. The study did not include a neutral control condition, a low paranoia comparison group, or a manipulation check following the imagery task. Self-imagery manipulations may affect paranoia, mood and self-beliefs. If the findings are replicated with clinical groups, and maintained over a longer period, this would suggest that imagery-based interventions targeting persecutory delusions might be usefully examined. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Outcome results of self-efficacy in children with sickle disease pain who were trained to use guided imagery.

Science.gov (United States)

Dobson, Cassandra

2015-11-01

The aim of this study was to describe self-efficacy as a theoretical component of behavior change in various therapeutic treatments such as the management of SCD pain. The participants were prepared to self-initiate the GI for 5 to 10 minutes three times each day regardless of pain and also during each pain episode. As part of the GI training a tape or CD with guided imagery messages was provided. Participants were monitored for 4 weeks pre and 4 weeks post intervention (GI training). Children kept a daily record of pain episodes. During this time, children continued to record as before in their personal study diary: pain episodes (intensity and treatment), school attendance, and also the frequency of GI use. At the conclusion of this 4-week period, usual pain patterns (PAT), visual imagery ability (KIAQ), and disease specific self-efficacy scale were measured again. The Sickle Cell Self-Efficacy Scale (SCSES) is a new nine-item scale measuring disease-specific perceptions of self-efficacy. The instrument's developers established internal consistency by Cronbach's alpha of 0.89. H1: Children with SCD who are trained in guided imagery will have greater disease-specific self-efficacy following the training than they had prior to learning guided imagery; the hypothesis was tested and supported using t-tests of mean interval-level scores on the SCSES. Eighteen children had positive gained scores and sixteen children raised their scores more than one standard deviation above the mean score for this sample distribution. Greater self-efficacy scores are associated with better physical and psychological functioning. Copyright © 2015 Elsevier Inc. All rights reserved.

CHOSEN ASPECTS OF THE PRODUCTION OF THE BASIC MAP USING UAV IMAGERY

Directory of Open Access Journals (Sweden)

M. Kedzierski

2016-06-01

Full Text Available For several years there has been an increasing interest in the use of unmanned aerial vehicles in acquiring image data from a low altitude. Considering the cost-effectiveness of the flight time of UAVs vs. conventional airplanes, the use of the former is advantageous when generating large scale accurate ortophotos. Through the development of UAV imagery, we can update large-scale basic maps. These maps are cartographic products which are used for registration, economic, and strategic planning. On the basis of these maps other cartographic maps are produced, for example maps used building planning. The article presents an assessesment of the usefulness of orthophotos based on UAV imagery to upgrade the basic map. In the research a compact, non-metric camera, mounted on a fixed wing powered by an electric motor was used. The tested area covered flat, agricultural and woodland terrains. The processing and analysis of orthorectification were carried out with the INPHO UASMaster programme. Due to the effect of UAV instability on low-altitude imagery, the use of non-metric digital cameras and the low-accuracy GPS-INS sensors, the geometry of images is visibly lower were compared to conventional digital aerial photos (large values of phi and kappa angles. Therefore, typically, low-altitude images require large along- and across-track direction overlap – usually above 70 %. As a result of the research orthoimages were obtained with a resolution of 0.06 meters and a horizontal accuracy of 0.10m. Digitized basic maps were used as the reference data. The accuracy of orthoimages vs. basic maps was estimated based on the study and on the available reference sources. As a result, it was found that the geometric accuracy and interpretative advantages of the final orthoimages allow the updating of basic maps. It is estimated that such an update of basic maps based on UAV imagery reduces processing time by approx. 40%.

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)

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

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.

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.

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...

Recognition and characterization of networks of water bodies in the Arctic ice-wedge polygonal tundra using high-resolution satellite imagery

Science.gov (United States)

Skurikhin, A. N.; Gangodagamage, C.; Rowland, J. C.; Wilson, C. J.

2013-12-01

Arctic lowland landscapes underlain by permafrost are often characterized by polygon-like patterns such as ice-wedge polygons outlined by networks of ice wedges and complemented with polygon rims, troughs, shallow ponds and thermokarst lakes. Polygonal patterns and corresponding features are relatively easy to recognize in high spatial resolution satellite imagery by a human, but their automated recognition is challenging due to the variability in their spectral appearance, the irregularity of individual trough spacing and orientation within the patterns, and a lack of unique spectral response attributable to troughs with widths commonly between 1 m and 2 m. Accurate identification of fine scale elements of ice-wedge polygonal tundra is important as their imprecise recognition may bias estimates of water, heat and carbon fluxes in large-scale climate models. Our focus is on the problem of identification of Arctic polygonal tundra fine-scale landscape elements (as small as 1 m - 2 m width). The challenge of the considered problem is that while large water bodies (e.g. lakes and rivers) can be recognized based on spectral response, reliable recognition of troughs is more difficult. Troughs do not have unique spectral signature, their appearance is noisy (edges are not strong), their width is small, and they often form connected networks with ponds and lakes, and thus they have overlapping spectral response with other water bodies and surrounding non-water bodies. We present a semi-automated approach to identify and classify Arctic polygonal tundra landscape components across the range of spatial scales, such as troughs, ponds, river- and lake-like objects, using high spatial resolution satellite imagery. The novelty of the approach lies in: (1) the combined use of segmentation and shape-based classification to identify a broad range of water bodies, including troughs, and (2) the use of high-resolution WorldView-2 satellite imagery (with resolution of 0.6 m) for this

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)

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.

Collaborative real-time scheduling of multiple PTZ cameras for multiple object tracking in video surveillance

Science.gov (United States)

Liu, Yu-Che; Huang, Chung-Lin

2013-03-01

This paper proposes a multi-PTZ-camera control mechanism to acquire close-up imagery of human objects in a surveillance system. The control algorithm is based on the output of multi-camera, multi-target tracking. Three main concerns of the algorithm are (1) the imagery of human object's face for biometric purposes, (2) the optimal video quality of the human objects, and (3) minimum hand-off time. Here, we define an objective function based on the expected capture conditions such as the camera-subject distance, pan tile angles of capture, face visibility and others. Such objective function serves to effectively balance the number of captures per subject and quality of captures. In the experiments, we demonstrate the performance of the system which operates in real-time under real world conditions on three PTZ cameras.

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...

A review of supervised object-based land-cover image classification

Science.gov (United States)

Ma, Lei; Li, Manchun; Ma, Xiaoxue; Cheng, Liang; Du, Peijun; Liu, Yongxue

2017-08-01

Object-based image classification for land-cover mapping purposes using remote-sensing imagery has attracted significant attention in recent years. Numerous studies conducted over the past decade have investigated a broad array of sensors, feature selection, classifiers, and other factors of interest. However, these research results have not yet been synthesized to provide coherent guidance on the effect of different supervised object-based land-cover classification processes. In this study, we first construct a database with 28 fields using qualitative and quantitative information extracted from 254 experimental cases described in 173 scientific papers. Second, the results of the meta-analysis are reported, including general characteristics of the studies (e.g., the geographic range of relevant institutes, preferred journals) and the relationships between factors of interest (e.g., spatial resolution and study area or optimal segmentation scale, accuracy and number of targeted classes), especially with respect to the classification accuracy of different sensors, segmentation scale, training set size, supervised classifiers, and land-cover types. Third, useful data on supervised object-based image classification are determined from the meta-analysis. For example, we find that supervised object-based classification is currently experiencing rapid advances, while development of the fuzzy technique is limited in the object-based framework. Furthermore, spatial resolution correlates with the optimal segmentation scale and study area, and Random Forest (RF) shows the best performance in object-based classification. The area-based accuracy assessment method can obtain stable classification performance, and indicates a strong correlation between accuracy and training set size, while the accuracy of the point-based method is likely to be unstable due to mixed objects. In addition, the overall accuracy benefits from higher spatial resolution images (e.g., unmanned aerial

Dynamic Neuro-Cognitive Imagery Improves Mental Imagery Ability, Disease Severity, and Motor and Cognitive Functions in People with Parkinson’s Disease

Directory of Open Access Journals (Sweden)

Amit Abraham

2018-01-01

Full Text Available People with Parkinson’s disease (PD experience kinesthetic deficits, which affect motor and nonmotor functions, including mental imagery. Imagery training is a recommended, yet underresearched, approach in PD rehabilitation. Dynamic Neuro-Cognitive Imagery (DNI™ is a codified method for imagery training. Twenty subjects with idiopathic PD (Hoehn and Yahr stages I–III were randomly allocated into DNI training (experimental; n=10 or in-home learning and exercise program (control; n=10. Both groups completed at least 16 hours of training within two weeks. DNI training focused on anatomical embodiment and kinesthetic awareness. Imagery abilities, disease severity, and motor and nonmotor functions were assessed pre- and postintervention. The DNI participants improved (p<.05 in mental imagery abilities, disease severity, and motor and spatial cognitive functions. Participants also reported improvements in balance, walking, mood, and coordination, and they were more physically active. Both groups strongly agreed they enjoyed their program and were more mentally active. DNI training is a promising rehabilitation method for improving imagery ability, disease severity, and motor and nonmotor functions in people with PD. This training might serve as a complementary PD therapeutic approach. Future studies should explore the effect of DNI on motor learning and control strategies.

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

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.

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,…

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…

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...

Auditory and motor imagery modulate learning in music performance

Directory of Open Access Journals (Sweden)

Rachel M. Brown

2013-07-01

Full Text Available Skilled performers such as athletes or musicians can improve their performance by imagining the actions or sensory outcomes associated with their skill. Performers vary widely in their auditory and motor imagery abilities, and these individual differences influence sensorimotor learning. It is unknown whether imagery abilities influence both memory encoding and retrieval. We examined how auditory and motor imagery abilities influence musicians’ encoding (during Learning, as they practiced novel melodies, and retrieval (during Recall of those melodies. Pianists learned melodies by listening without performing (auditory learning or performing without sound (motor learning; following Learning, pianists performed the melodies from memory with auditory feedback (Recall. During either Learning (Experiment 1 or Recall (Experiment 2, pianists experienced either auditory interference, motor interference, or no interference. Pitch accuracy (percentage of correct pitches produced and temporal regularity (variability of quarter-note interonset intervals were measured at Recall. Independent tests measured auditory and motor imagery skills. Pianists’ pitch accuracy was higher following auditory learning than following motor learning and lower in motor interference conditions (Experiments 1 and 2. Both auditory and motor imagery skills improved pitch accuracy overall. Auditory imagery skills modulated pitch accuracy encoding (Experiment 1: Higher auditory imagery skill corresponded to higher pitch accuracy following auditory learning with auditory or motor interference, and following motor learning with motor or no interference. These findings suggest that auditory imagery abilities decrease vulnerability to interference and compensate for missing auditory feedback at encoding. Auditory imagery skills also influenced temporal regularity at retrieval (Experiment 2: Higher auditory imagery skill predicted greater temporal regularity during Recall in the

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:

A hypnotically mediated guided imagery intervention for intrusive imagery: creating ground for figure.

Science.gov (United States)

Appel, P R

1999-04-01

Intrusive imagery can be seen as a cognitive dysfunction in the assimilation and accommodation of the psychological material represented by those images. From a gestalt psychological perspective, the intrusive image represents a figure without a ground that can provide meaning and context. Hypnotically mediated guided imagery interventions can be used to create a ground for the rogue image that metaphorically is an unassimilated figure; and thus allow for the creation of a new cognitive scheme. Four case examples are presented as well as a model for the intervention.

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.

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…

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.

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.

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

Music to the inner ears: exploring individual differences in musical imagery.

Science.gov (United States)

Beaty, Roger E; Burgin, Chris J; Nusbaum, Emily C; Kwapil, Thomas R; Hodges, Donald A; Silvia, Paul J

2013-12-01

In two studies, we explored the frequency and phenomenology of musical imagery. Study 1 used retrospective reports of musical imagery to assess the contribution of individual differences to imagery characteristics. Study 2 used an experience sampling design to assess the phenomenology of musical imagery over the course of one week in a sample of musicians and non-musicians. Both studies found episodes of musical imagery to be common and positive: people rarely wanted such experiences to end and often heard music that was personally meaningful. Several variables predicted musical imagery, including personality, musical preferences, and positive mood. Musicians tended to hear musical imagery more often, but they reported less frequent episodes of deliberately-generated imagery. Taken together, the present research provides new insights into individual differences in musical imagery, and it supports the emerging view that such experiences are common, positive, and more voluntary than previously recognized. Copyright © 2013 Elsevier Inc. All rights reserved.

Analisa Spektrum Motor Imagery pada Sinyal Aktivitas Otak

Directory of Open Access Journals (Sweden)

Johan Chandra

2017-01-01

Full Text Available Otak merupakan organ vital pada tubuh manusia yang berperan sebagai pusat kendali sistem saraf manusia. Sinyal yang dikeluarkan otak (EEG mengandung berbagai informasi yang dapat dimanfaatkan pada teknologi BCI. Salah satu informasi yang dapat digunakan adalah informasi motorik baik mengenai motor execution maupung motor imagery. Pada penderita stroke yang biasanya mengalami kelumpuhan pada anggota gerak tubuhnya, informasi mengenai motor imagery dapat dimanfaatkan untuk aplikasi Brain Computer Interface terutama dalam rehabilitasi kelumpuhan anggota gerak pasien tersebut. Pada penelitian ini dirancang sebuah alat sistem EEG untuk merekam sinyal EEG pada otak untuk menganalisa spektrum motor imagery pada sinyal aktivitas otak. Sistem terdiri dari rangkaian filter pasif, rangkaian proteksi, penguat isntrumentasi, common mode rejection, amplifier, dan filter. Pengujian dilakukan dengan membandingkan sinyal EEG pada tasking motor imagery dan motor execution. Selanjutnya, informasi motorik baik motor execution dan motor imagery dapat diaplikasikan lebih lanjut pada sistem BCI terutama pada rehabilitasi medik.

EEG Topographic Mapping of Visual and Kinesthetic Imagery in Swimmers.

Science.gov (United States)

Wilson, V E; Dikman, Z; Bird, E I; Williams, J M; Harmison, R; Shaw-Thornton, L; Schwartz, G E

2016-03-01

This study investigated differences in QEEG measures between kinesthetic and visual imagery of a 100-m swim in 36 elite competitive swimmers. Background information and post-trial checks controlled for the modality of imagery, swimming skill level, preferred imagery style, intensity of image and task equality. Measures of EEG relative magnitude in theta, low (7-9 Hz) and high alpha (8-10 Hz), and low and high beta were taken from 19 scalp sites during baseline, visual, and kinesthetic imagery. QEEG magnitudes in the low alpha band during the visual and kinesthetic conditions were attenuated from baseline in low band alpha but no changes were seen in any other bands. Swimmers produced more low alpha EEG magnitude during visual versus kinesthetic imagery. This was interpreted as the swimmers having a greater efficiency at producing visual imagery. Participants who reported a strong intensity versus a weaker feeling of the image (kinesthetic) had less low alpha magnitude, i.e., there was use of more cortical resources, but not for the visual condition. These data suggest that low band (7-9 Hz) alpha distinguishes imagery modalities from baseline, visual imagery requires less cortical resources than kinesthetic imagery, and that intense feelings of swimming requires more brain activity than less intense feelings.

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

High-resolution tree canopy mapping for New York City using LIDAR and object-based image analysis

Science.gov (United States)

MacFaden, Sean W.; O'Neil-Dunne, Jarlath P. M.; Royar, Anna R.; Lu, Jacqueline W. T.; Rundle, Andrew G.

2012-01-01

Urban tree canopy is widely believed to have myriad environmental, social, and human-health benefits, but a lack of precise canopy estimates has hindered quantification of these benefits in many municipalities. This problem was addressed for New York City using object-based image analysis (OBIA) to develop a comprehensive land-cover map, including tree canopy to the scale of individual trees. Mapping was performed using a rule-based expert system that relied primarily on high-resolution LIDAR, specifically its capacity for evaluating the height and texture of aboveground features. Multispectral imagery was also used, but shadowing and varying temporal conditions limited its utility. Contextual analysis was a key part of classification, distinguishing trees according to their physical and spectral properties as well as their relationships to adjacent, nonvegetated features. The automated product was extensively reviewed and edited via manual interpretation, and overall per-pixel accuracy of the final map was 96%. Although manual editing had only a marginal effect on accuracy despite requiring a majority of project effort, it maximized aesthetic quality and ensured the capture of small, isolated trees. Converting high-resolution LIDAR and imagery into usable information is a nontrivial exercise, requiring significant processing time and labor, but an expert system-based combination of OBIA and manual review was an effective method for fine-scale canopy mapping in a complex urban environment.

Automated road network extraction from high spatial resolution multi-spectral imagery

Science.gov (United States)

Zhang, Qiaoping

For the last three decades, the Geomatics Engineering and Computer Science communities have considered automated road network extraction from remotely-sensed imagery to be a challenging and important research topic. The main objective of this research is to investigate the theory and methodology of automated feature extraction for image-based road database creation, refinement or updating, and to develop a series of algorithms for road network extraction from high resolution multi-spectral imagery. The proposed framework for road network extraction from multi-spectral imagery begins with an image segmentation using the k-means algorithm. This step mainly concerns the exploitation of the spectral information for feature extraction. The road cluster is automatically identified using a fuzzy classifier based on a set of predefined road surface membership functions. These membership functions are established based on the general spectral signature of road pavement materials and the corresponding normalized digital numbers on each multi-spectral band. Shape descriptors of the Angular Texture Signature are defined and used to reduce the misclassifications between roads and other spectrally similar objects (e.g., crop fields, parking lots, and buildings). An iterative and localized Radon transform is developed for the extraction of road centerlines from the classified images. The purpose of the transform is to accurately and completely detect the road centerlines. It is able to find short, long, and even curvilinear lines. The input image is partitioned into a set of subset images called road component images. An iterative Radon transform is locally applied to each road component image. At each iteration, road centerline segments are detected based on an accurate estimation of the line parameters and line widths. Three localization approaches are implemented and compared using qualitative and quantitative methods. Finally, the road centerline segments are grouped into a

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

Using Online Citizen Science to Assess Giant Kelp Abundances Across the Globe with Satellite Imagery

Science.gov (United States)

Byrnes, J.; Cavanaugh, K. C.; Haupt, A. J.; Trouille, L.; Rosenthal, I.; Bell, T. W.; Rassweiler, A.; Pérez-Matus, A.; Assis, J.

2017-12-01

Global scale long-term data sets that document the patterns and variability of human impacts on marine ecosystems are rare. This lack is particularly glaring for underwater species - even moreso for ecologically important ones. Here we demonstrate how online Citizen Science combined with Landsat satellite imagery can help build a picture of change in the dynamics of giant kelp, an important coastal foundation species around the globe, from the 1984 to the present. Giant kelp canopy is visible from Landsat images, but these images defy easy machine classification. To get useful data, images must be processed by hand. While academic researchers have applied this method successfully at sub-regional scales, unlocking the value of the full global dataset has not been possible until given the massive effort required. Here we present Floating Forests (http://floatingforests.org), an international collaboration between kelp forest researchers and the citizen science organization Zooniverse. Floating Forests provides an interface that allows citizen scientists to identify canopy cover of giant kelp on Landsat images, enabling us to scale up the dataset to the globe. We discuss lessons learned from the initial version of the project launched in 2014, a prototype of an image processing pipeline to bring Landsat imagery to citizen science platforms, methods of assessing accuracy of citizen scientists, and preliminary data from our relaunch of the project. Through this project we have developed generalizable tools to facilitate citizen science-based analysis of Landsat and other satellite and aerial imagery. We hope that this create a powerful dataset to unlock our understanding of how global change has altered these critically important species in the sea.

Parabolic dune reactivation and migration at Napeague, NY, USA: Insights from aerial and GPR imagery

Science.gov (United States)

Girardi, James D.; Davis, Dan M.

2010-02-01

Observations from mapping since the 19th century and aerial imagery since 1930 have been used to study changes in the aeolian geomorphology of coastal parabolic dunes over the last ~ 170 years in the Walking Dune Field, Napeague, NY. The five large parabolic dunes of the Walking Dune Field have all migrated across, or are presently interacting with, a variably forested area that has affected their migration, stabilization and morphology. This study has concentrated on a dune with a particularly complex history of stabilization, reactivation and migration. We have correlated that dune's surface evolution, as revealed by aerial imagery, with its internal structures imaged using 200 MHz and 500 MHz Ground Penetrating Radar (GPR) surveys. Both 2D (transect) and high-resolution 3D GPR imagery image downwind dipping bedding planes which can be grouped by apparent dip angle into several discrete packages of beds that reflect distinct decadal-scale episodes of dune reactivation and growth. From aerial and high resolution GPR imagery, we document a unique mode of reactivation and migration linked to upwind dune formation and parabolic dune interactions with forest trees. This study documents how dune-dune and dune-vegetation interactions have influenced a unique mode of blowout deposition that has alternated on a decadal scale between opposite sides of a parabolic dune during reactivation and migration. The pattern of recent parabolic dune reactivation and migration in the Walking Dune Field appears to be somewhat more complex, and perhaps more sensitive to subtle environmental pressures, than an idealized growth model with uniform deposition and purely on-axis migration. This pattern, believed to be prevalent among other parabolic dunes in the Walking Dune Field, may occur also in many other places where similar observational constraints are unavailable.

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.

Wavelet-based higher-order neural networks for mine detection in thermal IR imagery

Science.gov (United States)

Baertlein, Brian A.; Liao, Wen-Jiao

2000-08-01

An image processing technique is described for the detection of miens in RI imagery. The proposed technique is based on a third-order neural network, which processes the output of a wavelet packet transform. The technique is inherently invariant to changes in signature position, rotation and scaling. The well-known memory limitations that arise with higher-order neural networks are addressed by (1) the data compression capabilities of wavelet packets, (2) protections of the image data into a space of similar triangles, and (3) quantization of that 'triangle space'. Using these techniques, image chips of size 28 by 28, which would require 0(109) neural net weights, are processed by a network having 0(102) weights. ROC curves are presented for mine detection in real and simulated imagery.

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.

Effects of guided imagery on blood pressure in pregnant women with hypertension: a pilot randomized controlled trial.

Science.gov (United States)

Moffatt, Faith Wight; Hodnett, Ellen; Esplen, Mary Jane; Watt-Watson, Judy

2010-12-01

Hypertension occurs in nearly 10 percent of pregnancies, and is associated with higher risk of infant and maternal morbidity and mortality than in normal pregnancies. Previous studies have suggested that relaxation therapies reduce blood pressure in nonpregnant adults. The objectives of this pilot randomized trial were to provide preliminary evidence of whether relaxation by means of guided imagery would reduce blood pressure in hypertensive pregnant women, and to assess the feasibility of a larger trial. A total of 69 pregnant women with hypertension were randomized to periods of guided imagery or of quiet rest, twice daily for 4 weeks or until delivery, whichever came first. Daytime ambulatory mean arterial pressure, systolic and diastolic blood pressure, and anxiety were measured weekly for up to 4 weeks. Women allocated to guided imagery had lower mean arterial pressure elevations over time than those allocated to quiet rest (guided imagery: M = 1.58 mmHg, SD = 7.63; quiet rest: M = 5.93 mmHg, SD = 6.55; t = 2.36, p = 0.02). However, when adjusted for baseline mean arterial pressure and gestation, the effect was not significant (p = 0.14). Numbers of women prescribed antihypertensive medication postrandomization were similar (guided imagery: n = 16; quiet rest: n = 13, χ(2) = 0.74, p = 0.46). There was also no evidence of an effect on women's anxiety. Nearly 90 percent (n = 26) of the guided imagery group indicated that they would use it again. Further rigorous study is warranted to determine effects of guided imagery on maternal blood pressure and perinatal health outcomes. © 2010, Copyright the Authors. Journal compilation © 2010, Wiley Periodicals, Inc.

Imagery Rescripting for Body Dysmorphic Disorder: A Multiple-Baseline Single-Case Experimental Design.

Science.gov (United States)

Willson, Rob; Veale, David; Freeston, Mark

2016-03-01

Individuals with body dysmorphic disorder (BDD) often experience negative distorted images of their appearance, and research suggests these may be linked to memories of adverse events such as bullying or teasing. This study evaluates imagery rescripting (ImR) as an intervention for BDD. In this article, we present a multiple-baseline single-case experimental design testing imagery rescripting as a brief, stand-alone intervention, with six individuals with BDD that related to aversive memories. The impact of the intervention was assessed by self-reported daily measures of symptom severity (preoccupation with appearance, appearance-related checking behaviors, appearance-related distress, and strength of belief that their main problem is their appearance) and standardized clinician ratings of BDD severity (Yale-Brown Obsessive Compulsive Scale modified for BDD). Four out of six of the participants responded positively to the intervention, with clinically meaningful improvement in symptomatology. Overall response was rapid; improvements began within the first week post-ImR intervention. From a small sample it is cautiously concluded that imagery rescripting may show promise as a module in cognitive-behavioral therapy for BDD, and is worthy of further investigation. Copyright © 2015. Published by Elsevier Ltd.

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

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 ...

Do the physical and environment PETTLEP elements predict sport imagery ability?

Science.gov (United States)

Anuar, Nurwina; Williams, Sarah E; Cumming, Jennifer

2017-11-01

The present study aimed to examine whether physical and environment elements of PETTLEP imagery relate to the ability to image five types of sport imagery (i.e. skill, strategy, goal, affect and mastery). Two hundred and ninety participants (152 males, 148 females; M age  = 20.24 years, SD = 4.36) from various sports completed the Sport Imagery Ability Questionnaire (SIAQ), and a set of items designed specifically for the study to assess how frequently participants incorporate physical (e.g. 'I make small movements or gestures during the imagery') and environment (e.g. 'I image in the real training/competition environment') elements of PETTLEP imagery. Structural equation modelling tested a hypothesised model in which imagery priming (i.e. the best fitting physical and environment elements) significantly and positively predicted imagery ability of the different imagery types (skill, β = 0.38; strategy, β = 0.23; goal, β = 0.21; affect, β = 0.25; mastery, β = 0.22). The model was a good fit to the data: χ 2 (174) = 263.87, p environment elements is associated with better skill, strategy, goal, affect and mastery imagery ability. The findings extend models of imagery use by indicating that how athletes images may influence their imagery ability.

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.

Team Action Imagery and Team Cognition: Imagery of Game Situations and Required Team Actions Promotes a Functional Structure in Players' Representations of Team-Level Tactics.

Science.gov (United States)

Frank, Cornelia; Linstromberg, Gian-Luca; Hennig, Linda; Heinen, Thomas; Schack, Thomas

2018-02-01

A team's cognitions of interpersonally coordinated actions are a crucial component for successful team performance. Here, we present an approach to practice team action by way of imagery and examine its impact on team cognitions in long-term memory. We investigated the impact of a 4-week team action imagery intervention on futsal players' mental representations of team-level tactics. Skilled futsal players were assigned to either an imagery training group or a no imagery training control group. Participants in the imagery training group practiced four team-level tactics by imagining team actions in specific game situations for three times a week. Results revealed that the imagery training group's representations were more similar to that of an expert representation after the intervention compared with the control group. This study indicates that team action imagery training can have a significant impact on players' tactical skill representations and thus order formation in long-term memory.

Reflecting on imagery: a clinical perspective and overview of the special issue of memory on mental imagery and memory in psychopathology.

Science.gov (United States)

Hackmann, Ann; Holmes, Emily A

2004-07-01

The authors provide an overview of the papers in the special issue of Memory on mental imagery and memory in psychopathology. The papers address emotional, intrusive mental imagery across a range of psychological disorders including post-traumatic stress disorder (PTSD), agoraphobia, body dysmorphic disorder, mood disorders, and psychosis. They include work on information processing issues including modelling cravings, conditioning, and aversions, as well as imagery qualities such as vividness and emotionality. The overview aims to place the articles in a broader context and draw out some exciting implications of this novel work. It provides a clinical context to the recent growth in this area from a cognitive behavioural therapy (CBT) perspective. We begin with PTSD, and consider links to imagery in other disorders. The clinical implications stemming from this empirical work and from autobiographical memory theory are discussed. These include consideration of a variety of techniques for eliminating troublesome imagery, and creating healthy, realistic alternatives.

Motor imagery and swallowing: a systematic literature review

Directory of Open Access Journals (Sweden)

Ada Salvetti Cavalcanti Caldas

Full Text Available ABSTRACT Objetive: to identify, in the literature, studies that address the use of motor imagery of swallowing. Methods: a systematic review in SCOPUS databases, Science Direct and Medline, with descriptors and free terms "Motor Imagery"; "Swallow"; "Feeding"; "Stomatognathic System"; "mastication ", "Chew "; "Deglutition "; "Deglutition Disorders "; and "Mental Practice". Original articles using the motor imagery of swallowing were included, while reviews were excluded. For data analysis, at the first and second steps, the reading of titles and abstracts of the studies was carried out. In the third step, all studies that were not excluded were read in full. Results: four manuscripts were selected. The use of motor imagery in the rehabilitation of swallowing shows to be a recent proposal (2014-2015. The sample was reduced and comprised mainly healthy individuals. The EMG of the supra-hyoid muscles was used in two manuscripts. The most used neuroimaging technique was the Near-Infrared Spectroscopy, demonstrating the occurrence of hemodynamic changes during motor imagery and motor execution of swallowing. Conclusion: the motor imagery produces brain response in the motor area of the brain, suggesting that mentalization of actions related to swallowing is effective. However, further studies are needed for the application of this approach in the swallowing rehabilitation.

A Subpixel Classification of Multispectral Satellite Imagery for Interpetation of Tundra-Taiga Ecotone Vegetation (Case Study on Tuliok River Valley, Khibiny, Russia)

Science.gov (United States)

Mikheeva, A. I.; Tutubalina, O. V.; Zimin, M. V.; Golubeva, E. I.

2017-12-01

The tundra-taiga ecotone plays significant role in northern ecosystems. Due to global climatic changes, the vegetation of the ecotone is the key object of many remote-sensing studies. The interpretation of vegetation and nonvegetation objects of the tundra-taiga ecotone on satellite imageries of a moderate resolution is complicated by the difficulty of extracting these objects from the spectral and spatial mixtures within a pixel. This article describes a method for the subpixel classification of Terra ASTER satellite image for vegetation mapping of the tundra-taiga ecotone in the Tuliok River, Khibiny Mountains, Russia. It was demonstrated that this method allows to determine the position of the boundaries of ecotone objects and their abundance on the basis of quantitative criteria, which provides a more accurate characteristic of ecotone vegetation when compared to the per-pixel approach of automatic imagery interpretation.

JEarth | Analytical Remote Sensing Imagery Application for Researchers and Practitioners

Science.gov (United States)

Prashad, L.; Christensen, P. R.; Anwar, S.; Dickenshied, S.; Engle, E.; Noss, D.

2009-12-01

The ASU 100 Cities Project and the ASU Mars Space Flight Facility (MSFF) present JEarth, a set of analytical Geographic Information System (GIS) tools for viewing and processing Earth-based remote sensing imagery and vectors, including high-resolution and hyperspectral imagery such as TIMS and MASTER. JEarth is useful for a wide range of researchers and practitioners who need to access, view, and analyze remote sensing imagery. JEarth stems from existing MSFF applications: the Java application JMars (Java Mission-planning and Analysis for Remote Sensing) for viewing and analyzing remote sensing imagery and THMPROC, a web-based, interactive tool for processing imagery to create band combinations, stretches, and other imagery products. JEarth users can run the application on their desktops by installing Java-based open source software on Windows, Mac, or Linux operating systems.

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.

The Movement Imagery Questionnaire-Revised, Second Edition (MIQ-RS Is a Reliable and Valid Tool for Evaluating Motor Imagery in Stroke Populations

Directory of Open Access Journals (Sweden)

Andrew J. Butler

2012-01-01

Full Text Available Mental imagery can improve motor performance in stroke populations when combined with physical therapy. Valid and reliable instruments to evaluate the imagery ability of stroke survivors are needed to maximize the benefits of mental imagery therapy. The purposes of this study were to: examine and compare the test-retest intra-rate reliability of the Movement Imagery Questionnaire-Revised, Second Edition (MIQ-RS in stroke survivors and able-bodied controls, examine internal consistency of the visual and kinesthetic items of the MIQ-RS, determine if the MIQ-RS includes both the visual and kinesthetic dimensions of mental imagery, correlate impairment and motor imagery scores, and investigate the criterion validity of the MIQ-RS in stroke survivors by comparing the results to the KVIQ-10. Test-retest analysis indicated good levels of reliability (ICC range: .83–.99 and internal consistency (Cronbach α: .95–.98 of the visual and kinesthetic subscales in both groups. The two-factor structure of the MIQ-RS was supported by factor analysis, with the visual and kinesthetic components accounting for 88.6% and 83.4% of the total variance in the able-bodied and stroke groups, respectively. The MIQ-RS is a valid and reliable instrument in the stroke population examined and able-bodied populations and therefore useful as an outcome measure for motor imagery ability.

MULTI-TEMPORAL ASSESSMENT OF LYCHEE TREE CROP STRUCTURE USING MULTI-SPECTRAL RPAS IMAGERY

Directory of Open Access Journals (Sweden)

K. Johansen

2017-08-01

Full Text Available The lychee tree is native to China and produce small fleshy fruit up to 5 cm in diameter. Lychee production in Australia is worth > $20 million annually. Pruning of trees encourages new growth, has a positive effect on fruiting of lychee, makes fruit-picking easier, and may increase yield, as it increases light interception and tree crown surface area. The objective of this research was to assess changes in tree structure, i.e. tree crown circumference, width, height and Plant Projective Cover (PPC using multi-spectral Remotely Piloted Aircraft System (RPAS imagery collected before and after pruning of a lychee plantation. A secondary objective was to assess any variations in the results as a function of various flying heights (30, 50 and 70 m. Pre- and post-pruning results showed significant differences in all measured tree structural parameters, including an average decrease in: tree crown circumference of 1.94 m; tree crown width of 0.57 m; tree crown height of 0.62 m; and PPC of 14.8 %. The different flying heights produced similar measurements of tree crown width and PPC, whereas tree crown circumference and height measurements decreased with increasing flying height. These results show that multi-spectral RPAS imagery can provide a suitable means of assessing pruning efforts undertaken by contractors based on changes in tree structure of lychee plantations and that it is important to collect imagery in a consistent manner, as varying flying heights may cause changes to tree structural measurements.

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

Analysis on the Utility of Satellite Imagery for Detection of Agricultural Facility

Science.gov (United States)

Kang, J.-M.; Baek, S.-H.; Jung, K.-Y.

2012-07-01

Now that the agricultural facilities are being increase owing to development of technology and diversification of agriculture and the ratio of garden crops that are imported a lot and the crops cultivated in facilities are raised in Korea, the number of vinyl greenhouses is tending upward. So, it is important to grasp the distribution of vinyl greenhouses as much as that of rice fields, dry fields and orchards, but it is difficult to collect the information of wide areas economically and correctly. Remote sensing using satellite imagery is able to obtain data of wide area at the same time, quickly and cost-effectively collect, monitor and analyze information from every object on earth. In this study, in order to analyze the utilization of satellite imagery at detection of agricultural facility, image classification was performed about the agricultural facility, vinyl greenhouse using Formosat-2 satellite imagery. The training set of sea, vegetation, building, bare ground and vinyl greenhouse was set to monitor the agricultural facilities of the object area and the training set for the vinyl greenhouses that are main monitoring object was classified and set again into 3 types according the spectral characteristics. The image classification using 4 kinds of supervise classification methods applied by the same training set were carried out to grasp the image classification method which is effective for monitoring agricultural facilities. And, in order to minimize the misclassification appeared in the classification using the spectral information, the accuracy of classification was intended to be raised by adding texture information. The results of classification were analyzed regarding the accuracy comparing with that of naked-eyed detection. As the results of classification, the method of Mahalanobis distance was shown as more efficient than other methods and the accuracy of classification was higher when adding texture information. Hence the more effective

ANALYSIS ON THE UTILITY OF SATELLITE IMAGERY FOR DETECTION OF AGRICULTURAL FACILITY

Directory of Open Access Journals (Sweden)

J.-M. Kang

2012-07-01

Full Text Available Now that the agricultural facilities are being increase owing to development of technology and diversification of agriculture and the ratio of garden crops that are imported a lot and the crops cultivated in facilities are raised in Korea, the number of vinyl greenhouses is tending upward. So, it is important to grasp the distribution of vinyl greenhouses as much as that of rice fields, dry fields and orchards, but it is difficult to collect the information of wide areas economically and correctly. Remote sensing using satellite imagery is able to obtain data of wide area at the same time, quickly and cost-effectively collect, monitor and analyze information from every object on earth. In this study, in order to analyze the utilization of satellite imagery at detection of agricultural facility, image classification was performed about the agricultural facility, vinyl greenhouse using Formosat-2 satellite imagery. The training set of sea, vegetation, building, bare ground and vinyl greenhouse was set to monitor the agricultural facilities of the object area and the training set for the vinyl greenhouses that are main monitoring object was classified and set again into 3 types according the spectral characteristics. The image classification using 4 kinds of supervise classification methods applied by the same training set were carried out to grasp the image classification method which is effective for monitoring agricultural facilities. And, in order to minimize the misclassification appeared in the classification using the spectral information, the accuracy of classification was intended to be raised by adding texture information. The results of classification were analyzed regarding the accuracy comparing with that of naked-eyed detection. As the results of classification, the method of Mahalanobis distance was shown as more efficient than other methods and the accuracy of classification was higher when adding texture information. Hence the more

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…

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.

Exploitation of multi-temporal Earth Observation imagery for monitoring land cover change in mining sites

Science.gov (United States)

Petropoulos, G.; Partsinevelos, P.; Mitraka, Z.

2012-04-01

Surface mining has been shown to cause intensive environmental degradation in terms of landscape, vegetation and biological communities. Nowadays, the commercial availability of remote sensing imagery at high spatiotemporal scales, has improved dramatically our ability to monitor surface mining activity and evaluate its impact on the environment and society. In this study we investigate the potential use of Landsat TM imagery combined with diverse classification techniques, namely artificial neural networks and support vector machines for delineating mining exploration and assessing its effect on vegetation in various surface mining sites in the Greek island of Milos. Assessment of the mining impact in the study area is validated through the analysis of available QuickBird imagery acquired nearly concurrently to the TM overpasses. Results indicate the capability of the TM sensor combined with the image analysis applied herein as a potential economically viable solution to provide rapidly and at regular time intervals information on mining activity and its impact to the local environment. KEYWORDS: mining environmental impact, remote sensing, image classification, change detection, land reclamation, support vector machines, neural networks

Application of EREP imagery to fracture-related mine safety hazards and environmental problems in mining. [Indiana

Science.gov (United States)

Wier, C. E.; Wobber, F. J.; Amato, R. V.; Russell, O. R. (Principal Investigator)

1974-01-01

The author has identified the following significant results. All Skylab 2 imagery received to date has been analyzed manually and data related to fracture analysis and mined land inventories has been summarized on map-overlays. A comparison of the relative utility of the Skylab image products for fracture detection, soil tone/vegetation contrast mapping, and mined land mapping has been completed. Numerous fracture traces were detected on both color and black and white transparencies. Unique fracture trace data which will contribute to the investigator's mining hazards analysis were noted on the EREP imagery; these data could not be detected on ERTS-1 imagery or high altitude aircraft color infrared photography. Stream segments controlled by fractures or joint systems could be identified in more detail than with ERTS-1 imagery of comparable scale. ERTS-1 mine hazards products will be modified to demonstrate the value of this additional data. Skylab images were used successfully to update a mined land map of Indiana made in 1972. Changes in mined area as small as two acres can be identified. As the Energy Crisis increases the demand for coal, such demonstrations of the application of Skylab data to coal resources will take on new importance.

Exploring the Influence of Topographic Correction and SWIR Spectral Information Inclusion on Burnt Scars Detection From High Resolution EO Imagery: A Case Study Using ASTER imagery

Science.gov (United States)

Said, Yahia A.; Petropoulos, George; Srivastava, Prashant K.

2014-05-01

Information on burned area estimates is of key importance in environmental and ecological studies as well as in fire management including damage assessment and planning of post-fire recovery of affected areas. Earth Observation (EO) provides today the most efficient way in obtaining such information in a rapid, consistent and cost-effective manner. The present study aimed at exploring the effect of topographic correction to the burnt area delineation in conditions characteristic of a Mediterranean environment using ASTER high resolution multispectral remotely sensed imagery. A further objective was to investigate the potential added-value of the inclusion of the shortwave infrared (SWIR) bands in improving the retrievals of burned area cartography from the ASTER data. In particular the capability of the Maximum Likelihood (ML), the Support Vector Machines (SVMs) and Object-based Image Analysis (OBIA) classification techniques has been examined herein for the purposes of our study. As a case study is used a typical Mediterranean site on which a fire event occurred in Greece during the summer of 2007, for which post-fire ASTER imagery has been acquired. Our results indicated that the combination of topographic correction (ortho-rectification) with the inclusion of the SWIR bands returned the most accurate results in terms of burnt area mapping. In terms of image processing methods, OBIA showed the best results and found as the most promising approach for burned area mapping with least absolute difference from the validation polygon followed by SVM and ML. All in all, our study provides an important contribution to the understanding of the capability of high resolution imagery such as that from ASTER sensor and corroborates the usefulness particularly of the topographic correction as an image processing step when in delineating the burnt areas from such data. It also provides further evidence that use of EO technology can offer an effective practical tool for the

Fast Updating National Geo-Spatial Databases with High Resolution Imagery: China's Methodology and Experience

Science.gov (United States)

Chen, J.; Wang, D.; Zhao, R. L.; Zhang, H.; Liao, A.; Jiu, J.

2014-04-01

Geospatial databases are irreplaceable national treasure of immense importance. Their up-to-dateness referring to its consistency with respect to the real world plays a critical role in its value and applications. The continuous updating of map databases at 1:50,000 scales is a massive and difficult task for larger countries of the size of more than several million's kilometer squares. This paper presents the research and technological development to support the national map updating at 1:50,000 scales in China, including the development of updating models and methods, production tools and systems for large-scale and rapid updating, as well as the design and implementation of the continuous updating workflow. The use of many data sources and the integration of these data to form a high accuracy, quality checked product were required. It had in turn required up to date techniques of image matching, semantic integration, generalization, data base management and conflict resolution. Design and develop specific software tools and packages to support the large-scale updating production with high resolution imagery and large-scale data generalization, such as map generalization, GIS-supported change interpretation from imagery, DEM interpolation, image matching-based orthophoto generation, data control at different levels. A national 1:50,000 databases updating strategy and its production workflow were designed, including a full coverage updating pattern characterized by all element topographic data modeling, change detection in all related areas, and whole process data quality controlling, a series of technical production specifications, and a network of updating production units in different geographic places in the country.

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...

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...

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...

Improvement in spatial imagery following sight onset late in childhood.

Science.gov (United States)

Gandhi, Tapan K; Ganesh, Suma; Sinha, Pawan

2014-03-01

The factors contributing to the development of spatial imagery skills are not well understood. Here, we consider whether visual experience shapes these skills. Although differences in spatial imagery between sighted and blind individuals have been reported, it is unclear whether these differences are truly due to visual deprivation or instead are due to extraneous factors, such as reduced opportunities for the blind to interact with their environment. A direct way of assessing vision's contribution to the development of spatial imagery is to determine whether spatial imagery skills change soon after the onset of sight in congenitally blind individuals. We tested 10 children who gained sight after several years of congenital blindness and found significant improvements in their spatial imagery skills following sight-restoring surgeries. These results provide evidence of vision's contribution to spatial imagery and also have implications for the nature of internal spatial representations.

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. PMID:24623958

Application of ecological, geological and oceanographic ERTS-1 imagery to Delaware's coastal resources planning

Science.gov (United States)

Klemas, V. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Communities containing five different coastal vegetation species, developed marshlands, and fresh water impoundments have been identified in ERTS-1 images. Suspended sediment and circulation patterns in imagery from five ERTS-1 passes over Delaware Bay have been enhanced and correlated with predicted current patterns. Conclusions reached are: (1) ERTS-1 is suitable platform for observing suspended sediment patterns and water masses synoptically over large areas. (2) Suspended sediment acts as a natural tracer allowing photointerpreters to deduce gross current circulation patterns from ERTS-1 imagery. (3) Under atmospheric conditions encountered along the East Coast of the United States MSS band 5 seems to give the best representation of sediment load in upper one meter of water column. (4) In the ERTS-1 imagery the sediment patterns are delineated by three to four neighboring shades of grey. (5) Negative transparencies of the ERTS-1 images give better contrast whenever the suspended sediment tones fall within the first few steps of the grey scale. (6) Color density slicing helps delineate the suspended sediment patterns more clearly and differentiate turbidity levels.

Imagining a brighter future: the effect of positive imagery training on mood, prospective mental imagery and emotional bias in older adults.

Science.gov (United States)

Murphy, Susannah E; Clare O'Donoghue, M; Drazich, Erin H S; Blackwell, Simon E; Christina Nobre, Anna; Holmes, Emily A

2015-11-30

Positive affect and optimism play an important role in healthy ageing and are associated with improved physical and cognitive health outcomes. This study investigated whether it is possible to boost positive affect and associated positive biases in this age group using cognitive training. The effect of computerised imagery-based cognitive bias modification on positive affect, vividness of positive prospective imagery and interpretation biases in older adults was measured. 77 older adults received 4 weeks (12 sessions) of imagery cognitive bias modification or a control condition. They were assessed at baseline, post-training and at a one-month follow-up. Both groups reported decreased negative affect and trait anxiety, and increased optimism across the three assessments. Imagery cognitive bias modification significantly increased the vividness of positive prospective imagery post-training, compared with the control training. Contrary to our hypothesis, there was no difference between the training groups in negative interpretation bias. This is a useful demonstration that it is possible to successfully engage older adults in computer-based cognitive training and to enhance the vividness of positive imagery about the future in this group. Future studies are needed to assess the longer-term consequences of such training and the impact on affect and wellbeing in more vulnerable groups. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

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.

Study of the 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.

1972-01-01

The author has identified the following significant results. Various data compilation and analysis activities in support of ERTS-1 imagery interpretation are in progress or are completed. These include the compilation of mine accident data, areas of mine roof instability and the analysis of high altitude color infrared photography and low altitude color and color infrared photography which was acquired by NASA in support of the project. The photography reveals that many fracture lineaments are detectable through a varied thickness of glacial till. These data will be compiled on a series of 1:250,000 scale base maps and evaluated for a correlation between fracture zones and mine accidents and rooffalls. Due to high occurrence of cloud cover in the project area and to the delay in imagery shipments, little progress has been made in the analysis of ERTS-1 imagery.

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.

Pure visual imagery as a potential approach to achieve three classes of control for implementation of BCI in non-motor disorders

Science.gov (United States)

Sousa, Teresa; Amaral, Carlos; Andrade, João; Pires, Gabriel; Nunes, Urbano J.; Castelo-Branco, Miguel

2017-08-01

Objective. The achievement of multiple instances of control with the same type of mental strategy represents a way to improve flexibility of brain-computer interface (BCI) systems. Here we test the hypothesis that pure visual motion imagery of an external actuator can be used as a tool to achieve three classes of electroencephalographic (EEG) based control, which might be useful in attention disorders. Approach. We hypothesize that different numbers of imagined motion alternations lead to distinctive signals, as predicted by distinct motion patterns. Accordingly, a distinct number of alternating sensory/perceptual signals would lead to distinct neural responses as previously demonstrated using functional magnetic resonance imaging (fMRI). We anticipate that differential modulations should also be observed in the EEG domain. EEG recordings were obtained from twelve participants using three imagery tasks: imagery of a static dot, imagery of a dot with two opposing motions in the vertical axis (two motion directions) and imagery of a dot with four opposing motions in vertical or horizontal axes (four directions). The data were analysed offline. Main results. An increase of alpha-band power was found in frontal and central channels as a result of visual motion imagery tasks when compared with static dot imagery, in contrast with the expected posterior alpha decreases found during simple visual stimulation. The successful classification and discrimination between the three imagery tasks confirmed that three different classes of control based on visual motion imagery can be achieved. The classification approach was based on a support vector machine (SVM) and on the alpha-band relative spectral power of a small group of six frontal and central channels. Patterns of alpha activity, as captured by single-trial SVM closely reflected imagery properties, in particular the number of imagined motion alternations. Significance. We found a new mental task based on visual motion

Effects of truncal motor imagery practice on trunk performance, functional balance, and daily activities in acute stroke

Directory of Open Access Journals (Sweden)

Priyanka Shah

2016-01-01

Full Text Available Background: Motor imagery is beneficial to treat upper and lower limbs motor impairments in stroke patients, but the effects of imagery in the trunk recovery have not been reported. Hence, the aim is to test the effects of truncal motor imagery practice on trunk performance, functional balance, and daily activities in acute stroke patients. Methods: This pilot randomized clinical trial was conducted in acute stroke unit. Acute stroke patients with hemodynamic stability, aged between 30 and 70 years, first time stroke, and scoring <20 on trunk impairment scale (TIS were included in the study. Patients in the experimental group practiced trunk motor imagery in addition to physical training. Control group was given conventional physical therapy. The treatment intensity was 90 min/day, 6 days a week for 3 weeks duration. Trunk control test, TIS, brunel balance assessment (BBA, and Barthel index (BI were considered as the outcome measures. Results: Among 23 patients included in the study, 12 and 11 patients, respectively, in the control and experimental groups completed the intervention. Repeated measures ANOVA, i.e., timeFNx01 group factor analysis and effect size showed statistically significant improvements (P = 0.001 in the scores of TIS (1.64, BBA (1.83, and BI (0.67. Conclusion: Motor imagery of trunk in addition to the physical practice showed benefits in improving trunk performance, functional balance, and daily living in acute stroke.

AN EVOLUTIONARY ALGORITHM FOR FAST INTENSITY BASED IMAGE MATCHING BETWEEN OPTICAL AND SAR SATELLITE IMAGERY

Directory of Open Access Journals (Sweden)

P. Fischer

2018-04-01

Full Text Available This paper presents a hybrid evolutionary algorithm for fast intensity based matching between satellite imagery from SAR and very high-resolution (VHR optical sensor systems. The precise and accurate co-registration of image time series and images of different sensors is a key task in multi-sensor image processing scenarios. The necessary preprocessing step of image matching and tie-point detection is divided into a search problem and a similarity measurement. Within this paper we evaluate the use of an evolutionary search strategy for establishing the spatial correspondence between satellite imagery of optical and radar sensors. The aim of the proposed algorithm is to decrease the computational costs during the search process by formulating the search as an optimization problem. Based upon the canonical evolutionary algorithm, the proposed algorithm is adapted for SAR/optical imagery intensity based matching. Extensions are drawn using techniques like hybridization (e.g. local search and others to lower the number of objective function calls and refine the result. The algorithm significantely decreases the computational costs whilst finding the optimal solution in a reliable way.

Land cover mapping and change detection in urban watersheds using QuickBird high spatial resolution satellite imagery

Science.gov (United States)

Hester, David Barry

The objective of this research was to develop methods for urban land cover analysis using QuickBird high spatial resolution satellite imagery. Such imagery has emerged as a rich commercially available remote sensing data source and has enjoyed high-profile broadcast news media and Internet applications, but methods of quantitative analysis have not been thoroughly explored. The research described here consists of three studies focused on the use of pan-sharpened 61-cm spatial resolution QuickBird imagery, the spatial resolution of which is the highest of any commercial satellite. In the first study, a per-pixel land cover classification method is developed for use with this imagery. This method utilizes a per-pixel classification approach to generate an accurate six-category high spatial resolution land cover map of a developing suburban area. The primary objective of the second study was to develop an accurate land cover change detection method for use with QuickBird land cover products. This work presents an efficient fuzzy framework for transforming map uncertainty into accurate and meaningful high spatial resolution land cover change analysis. The third study described here is an urban planning application of the high spatial resolution QuickBird-based land cover product developed in the first study. This work both meaningfully connects this exciting new data source to urban watershed management and makes an important empirical contribution to the study of suburban watersheds. Its analysis of residential roads and driveways as well as retail parking lots sheds valuable light on the impact of transportation-related land use on the suburban landscape. Broadly, these studies provide new methods for using state-of-the-art remote sensing data to inform land cover analysis and urban planning. These methods are widely adaptable and produce land cover products that are both meaningful and accurate. As additional high spatial resolution satellites are launched and the

Multi-disciplinary techniques for understanding time-varying space-based imagery

Science.gov (United States)

Casasent, D.; Sanderson, A.; Kanade, T.

1984-06-01

A multidisciplinary program for space-based image processing is reported. This project combines optical and digital processing techniques and pattern recognition, image understanding and artificial intelligence methodologies. Time change image processing was recognized as the key issue to be addressed. Three time change scenarios were defined based on the frame rate of the data change. This report details the recent research on: various statistical and deterministic image features, recognition of sub-pixel targets in time varying imagery, and 3-D object modeling and recognition.

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.

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

Self-imagery in individuals with high body dissatisfaction: the effect of positive and negative self-imagery on aspects of the self-concept.

Science.gov (United States)

Farrar, Stephanie; Stopa, Lusia; Turner, Hannah

2015-03-01

Cognitive behavioural models of eating disorders highlight low self-esteem as a maintaining factor. This study explored the impact of positive and negative self-imagery on aspects of the working self (implicit and explicit self-esteem and self-concept clarity) in individuals with high body dissatisfaction (an important aspect of eating disorders). The impact of these images on state body satisfaction and affect was also explored. A group of participants with high body dissatisfaction completed measures of explicit self-esteem, self-concept clarity, state body satisfaction and affect prior to completing a negative (n = 33) or positive (n = 33) self-imagery retrieval task. Following this they completed the baseline measures and a measure of implicit self-esteem. Holding a negative self-image in mind had a negative effect on explicit self-esteem, whilst holding a positive self-image had a beneficial effect. There were no effects of imagery on implicit self-esteem. Holding a negative image in mind led to a significant reduction in self-concept clarity; however, positive self-imagery did not affect self-concept clarity. Holding a negative self-image in mind led to a decrease in body satisfaction and state affect. The opposite was found for the positive self-imagery group. Implicit self-esteem was not measured at baseline. Imagery techniques which promote positive self-images may help improve aspects of the working self, body satisfaction and affect in individuals with high levels of body dissatisfaction. As such, these imagery techniques warrant further investigation in a clinical population. Copyright © 2014 Elsevier Ltd. All rights reserved.

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…

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.

Commercial Satellite Imagery Analysis for Countering Nuclear Proliferation

Science.gov (United States)

Albright, David; Burkhard, Sarah; Lach, Allison

2018-05-01

High-resolution commercial satellite imagery from a growing number of private satellite companies allows nongovernmental analysts to better understand secret or opaque nuclear programs of countries in unstable or tense regions, called proliferant states. They include North Korea, Iran, India, Pakistan, and Israel. By using imagery to make these countries’ aims and capabilities more transparent, nongovernmental groups like the Institute for Science and International Security have affected the policies of governments and the course of public debate. Satellite imagery work has also strengthened the efforts of the International Atomic Energy Agency, thereby helping this key international agency build its case to mount inspections of suspect sites and activities. This work has improved assessments of the nuclear capabilities of proliferant states. Several case studies provide insight into the use of commercial satellite imagery as a key tool to educate policy makers and affect policy.

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 ...

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....

Assessing the value of Landsat imagery: Results from a 2012 comprehensive user survey

Science.gov (United States)

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

2012-12-01

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

USING COMBINATION OF PLANAR AND HEIGHT FEATURES FOR DETECTING BUILT-UP AREAS FROM HIGH-RESOLUTION STEREO IMAGERY

Directory of Open Access Journals (Sweden)

F. Peng

2017-09-01

Full Text Available Within-class spectral variation and between-class spectral confusion in remotely sensed imagery degrades the performance of built-up area detection when using planar texture, shape, and spectral features. Terrain slope and building height are often used to optimize the results, but extracted from auxiliary data (e.g. LIDAR data, DSM. Moreover, the auxiliary data must be acquired around the same time as image acquisition. Otherwise, built-up area detection accuracy is affected. Stereo imagery incorporates both planar and height information unlike single remotely sensed images. Stereo imagery acquired by many satellites (e.g. Worldview-4, Pleiades-HR, ALOS-PRISM, and ZY-3 can be used as data source of identifying built-up areas. A new method of identifying high-accuracy built-up areas from stereo imagery is achieved by using a combination of planar and height features. The digital surface model (DSM and digital orthophoto map (DOM are first generated from stereo images. Then, height values of above-ground objects (e.g. buildings are calculated from the DSM, and used to obtain raw built-up areas. Other raw built-up areas are obtained from the DOM using Pantex and Gabor, respectively. Final high-accuracy built-up area results are achieved from these raw built-up areas using the decision level fusion. Experimental results show that accurate built-up areas can be achieved from stereo imagery. The height information used in the proposed method is derived from stereo imagery itself, with no need to require auxiliary height data (e.g. LIDAR data. The proposed method is suitable for spaceborne and airborne stereo pairs and triplets.

Using Combination of Planar and Height Features for Detecting Built-Up Areas from High-Resolution Stereo Imagery

Science.gov (United States)

Peng, F.; Cai, X.; Tan, W.

2017-09-01

Within-class spectral variation and between-class spectral confusion in remotely sensed imagery degrades the performance of built-up area detection when using planar texture, shape, and spectral features. Terrain slope and building height are often used to optimize the results, but extracted from auxiliary data (e.g. LIDAR data, DSM). Moreover, the auxiliary data must be acquired around the same time as image acquisition. Otherwise, built-up area detection accuracy is affected. Stereo imagery incorporates both planar and height information unlike single remotely sensed images. Stereo imagery acquired by many satellites (e.g. Worldview-4, Pleiades-HR, ALOS-PRISM, and ZY-3) can be used as data source of identifying built-up areas. A new method of identifying high-accuracy built-up areas from stereo imagery is achieved by using a combination of planar and height features. The digital surface model (DSM) and digital orthophoto map (DOM) are first generated from stereo images. Then, height values of above-ground objects (e.g. buildings) are calculated from the DSM, and used to obtain raw built-up areas. Other raw built-up areas are obtained from the DOM using Pantex and Gabor, respectively. Final high-accuracy built-up area results are achieved from these raw built-up areas using the decision level fusion. Experimental results show that accurate built-up areas can be achieved from stereo imagery. The height information used in the proposed method is derived from stereo imagery itself, with no need to require auxiliary height data (e.g. LIDAR data). The proposed method is suitable for spaceborne and airborne stereo pairs and triplets.

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

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…

The influence of imagery vividness on cognitive and perceptual cues in circular auditorily-induced vection

Directory of Open Access Journals (Sweden)

Aleksander eVäljamäe

2014-12-01

Full Text Available In the absence of other congruent multisensory motion cues, sound contribution to illusions of self-motion (vection is relatively weak and often attributed to purely cognitive, top-down processes. The present study addressed the influence of cognitive and perceptual factors in the experience of circular, yaw auditorily-induced vection (AIV, focusing on participants’ imagery vividness scores. We used different rotating sound sources (acoustic landmark vs. movable types and their filtered versions that provided different binaural cues (interaural time or level differences, ITD vs. ILD when delivering via loudspeaker array. The significant differences in circular vection intensity showed that 1 AIV was stronger for rotating sound fields containing auditory landmarks as compared to movable sound objects; 2 ITD based acoustic cues were more instrumental than ILD based ones for horizontal AIV; and 3 individual differences in imagery vividness significantly influenced the effects of contextual and perceptual cues. While participants with high scores of kinesthetic and visual imagery were helped by vection ``rich cues, i.e. acoustic landmarks and ITD cues, the participants from the low-vivid imagery group did not benefit from these cues automatically. Only when specifically asked to use their imagination intentionally did these external cues start influencing vection sensation in similar way to high-vivid imagers. These findings are in line with the recent fMRI work which suggested that high-vivid imagers employ automatic, almost unconscious mechanisms in imagery generation, while low-vivid imagers rely on more schematic and conscious framework. Consequently, our results provide an additional insight into the interaction between perceptual and contextual cues when experiencing purely auditorily or multisensorily induced vection.

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.)

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.

Characterizing Resident Space Object Earthshine Signature Variability

Science.gov (United States)

Van Cor, Jared D.

There are three major sources of illumination on objects in the near Earth space environment: Sunshine, Moonshine, and Earthshine. For objects in this environment (satellites, orbital debris, etc.) known as Resident Space Objects (RSOs), the sun and the moon have consistently small illuminating solid angles and can be treated as point sources; this makes their incident illumination easily modeled. The Earth on the other hand has a large illuminating solid angle, is heterogeneous, and is in a constant state of change. The objective of this thesis was to characterize the impact and variability of observed RSO Earthshine on apparent magnitude signatures in the visible optical spectral region. A key component of this research was creating Earth object models incorporating the reflectance properties of the Earth. Two Earth objects were created: a homogeneous diffuse Earth object and a time sensitive heterogeneous Earth object. The homogeneous diffuse Earth object has a reflectance equal to the average global albedo, a standard model used when modeling Earthshine. The time sensitive heterogeneous Earth object was created with two material maps representative of the dynamic reflectance of the surface of the earth, and a shell representative of the atmosphere. NASA's Moderate-resolution Imaging Spectroradiometer (MODIS) Earth observing satellite product libraries, MCD43C1 global surface BRDF map and MOD06 global fractional cloud map, were utilized to create the material maps, and a hybridized version of the Empirical Line Method (ELM) was used to create the atmosphere. This dynamic Earth object was validated by comparing simulated color imagery of the Earth to that taken by: NASAs Earth Polychromatic Imaging Camera (EPIC) located on the Deep Space Climate Observatory (DSCOVR), and by MODIS located on the Terra satellite. The time sensitive heterogeneous Earth object deviated from MODIS imagery by a spectral radiance root mean square error (RMSE) of +/-14.86 [watts/m. 2sr

GATE: computation code for medical imagery, radiotherapy and dosimetry

International Nuclear Information System (INIS)

Jan, S.

2010-01-01

The author presents the GATE code, a simulation software based on the Geant4 development environment developed by the CERN (the European organization for nuclear research) which enables Monte-Carlo type simulation to be developed for tomography imagery using ionizing radiation, and radiotherapy examinations (conventional and hadron therapy) to be simulated. The authors concentrate on the use of medical imagery in carcinology. They comment some results obtained in nuclear imagery and in radiotherapy

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.

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...

User's Self-Prediction of Performance in Motor Imagery Brain-Computer Interface.

Science.gov (United States)

Ahn, Minkyu; Cho, Hohyun; Ahn, Sangtae; Jun, Sung C

2018-01-01

Performance variation is a critical issue in motor imagery brain-computer interface (MI-BCI), and various neurophysiological, psychological, and anatomical correlates have been reported in the literature. Although the main aim of such studies is to predict MI-BCI performance for the prescreening of poor performers, studies which focus on the user's sense of the motor imagery process and directly estimate MI-BCI performance through the user's self-prediction are lacking. In this study, we first test each user's self-prediction idea regarding motor imagery experimental datasets. Fifty-two subjects participated in a classical, two-class motor imagery experiment and were asked to evaluate their easiness with motor imagery and to predict their own MI-BCI performance. During the motor imagery experiment, an electroencephalogram (EEG) was recorded; however, no feedback on motor imagery was given to subjects. From EEG recordings, the offline classification accuracy was estimated and compared with several questionnaire scores of subjects, as well as with each subject's self-prediction of MI-BCI performance. The subjects' performance predictions during motor imagery task showed a high positive correlation ( r = 0.64, p performance even without feedback information. This implies that the human brain is an active learning system and, by self-experiencing the endogenous motor imagery process, it can sense and adopt the quality of the process. Thus, it is believed that users may be able to predict MI-BCI performance and results may contribute to a better understanding of low performance and advancing BCI.

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...

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...

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.

GATE: computation code for medical imagery, radiotherapy and dosimetry; GATE: code de calcul pour l'imagerie medicale, la radiotherapie et la dosimetrie

Energy Technology Data Exchange (ETDEWEB)

Jan, S. [CEA Direction des Sciences du Vivant, Institut d ' Imagerie Bio-Medicale, Service Hospitalier Frederic Joliot, 4 pl. du Gn. Leclerc 91401 Orsay Cedex (France)

2010-07-01

The author presents the GATE code, a simulation software based on the Geant4 development environment developed by the CERN (the European organization for nuclear research) which enables Monte-Carlo type simulation to be developed for tomography imagery using ionizing radiation, and radiotherapy examinations (conventional and hadron therapy) to be simulated. The authors concentrate on the use of medical imagery in carcinology. They comment some results obtained in nuclear imagery and in radiotherapy

KOLAM: a cross-platform architecture for scalable visualization and tracking in wide-area imagery

Science.gov (United States)

Fraser, Joshua; Haridas, Anoop; Seetharaman, Guna; Rao, Raghuveer M.; Palaniappan, Kannappan

2013-05-01

KOLAM is an open, cross-platform, interoperable, scalable and extensible framework supporting a novel multi- scale spatiotemporal dual-cache data structure for big data visualization and visual analytics. This paper focuses on the use of KOLAM for target tracking in high-resolution, high throughput wide format video also known as wide-area motion imagery (WAMI). It was originally developed for the interactive visualization of extremely large geospatial imagery of high spatial and spectral resolution. KOLAM is platform, operating system and (graphics) hardware independent, and supports embedded datasets scalable from hundreds of gigabytes to feasibly petabytes in size on clusters, workstations, desktops and mobile computers. In addition to rapid roam, zoom and hyper- jump spatial operations, a large number of simultaneously viewable embedded pyramid layers (also referred to as multiscale or sparse imagery), interactive colormap and histogram enhancement, spherical projection and terrain maps are supported. The KOLAM software architecture was extended to support airborne wide-area motion imagery by organizing spatiotemporal tiles in very large format video frames using a temporal cache of tiled pyramid cached data structures. The current version supports WAMI animation, fast intelligent inspection, trajectory visualization and target tracking (digital tagging); the latter by interfacing with external automatic tracking software. One of the critical needs for working with WAMI is a supervised tracking and visualization tool that allows analysts to digitally tag multiple targets, quickly review and correct tracking results and apply geospatial visual analytic tools on the generated trajectories. One-click manual tracking combined with multiple automated tracking algorithms are available to assist the analyst and increase human effectiveness.

Enhancing voluntary imitation through attention and motor imagery.

Science.gov (United States)

Bek, Judith; Poliakoff, Ellen; Marshall, Hannah; Trueman, Sophie; Gowen, Emma

2016-07-01

Action observation activates brain areas involved in performing the same action and has been shown to increase motor learning, with potential implications for neurorehabilitation. Recent work indicates that the effects of action observation on movement can be increased by motor imagery or by directing attention to observed actions. In voluntary imitation, activation of the motor system during action observation is already increased. We therefore explored whether imitation could be further enhanced by imagery or attention. Healthy participants observed and then immediately imitated videos of human hand movement sequences, while movement kinematics were recorded. Two blocks of trials were completed, and after the first block participants were instructed to imagine performing the observed movement (Imagery group, N = 18) or attend closely to the characteristics of the movement (Attention group, N = 15), or received no further instructions (Control group, N = 17). Kinematics of the imitated movements were modulated by instructions, with both Imagery and Attention groups being closer in duration, peak velocity and amplitude to the observed model compared with controls. These findings show that both attention and motor imagery can increase the accuracy of imitation and have implications for motor learning and rehabilitation. Future work is required to understand the mechanisms by which these two strategies influence imitation accuracy.

Effects of kinesthetic versus visual imagery practice on two technical dance movements: a pilot study.

Science.gov (United States)

Girón, Elizabeth Coker; McIsaac, Tara; Nilsen, Dawn

2012-03-01

Motor imagery is a type of mental practice that involves imagining the body performing a movement in the absence of motor output. Dance training traditionally incorporates mental practice techniques, but quantitative effects of motor imagery on the performance of dance movements are largely unknown. This pilot study compared the effects of two different imagery modalities, external visual imagery and kinesthetic imagery, on pelvis and hip kinematics during two technical dance movements, plié and sauté. Each of three female dance students (mean age = 19.7 years, mean years of training = 10.7) was assigned to use a type of imagery practice: visual imagery, kinesthetic imagery, or no imagery. Effects of motor imagery on peak external hip rotation varied by both modality and task. Kinesthetic imagery increased peak external hip rotation for pliés, while visual imagery increased peak external hip rotation for sautés. Findings suggest that the success of motor imagery in improving performance may be task-specific. Dancers may benefit from matching imagery modality to technical tasks in order to improve alignment and thereby avoid chronic injury.

Visual imaging capacity and imagery control in Fine Arts students.

Science.gov (United States)

Pérez-Fabello, Maria José; Campos, Alfredo; Gómez-Juncal, Rocío

2007-06-01

This study investigated relationships between visual imaging abilities (imaging capacity and imagery control) and academic performance in 146 Fine Arts students (31 men, 115 women). Mean age was 22.3 yr. (SD= 1.9; range 20-26 yr.). All of the participants who volunteered for the experiment regularly attended classes and were first, second, or third year students. For evaluation of imaging abilities, the Spanish versions of the Gordon Test of Visual Imagery Control, the Vividness of Visual Imagery Questionnaire, the Verbalizer-Visualizer Questionnaire, and Betts' Questionnaire Upon Mental Imagery were used. Academic performance was assessed in four areas, Drawing, Painting, Sculpture, and Complementary Subjects, over a three-year period. The results indicate that imagery control was associated with academic performance in Fine Arts. These findings are discussed in the context of previous studies, and new lines of research are proposed.

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.

Support vector machine as a binary classifier for automated object detection in remotely sensed data

International Nuclear Information System (INIS)

Wardaya, P D

2014-01-01

In the present paper, author proposes the application of Support Vector Machine (SVM) for the analysis of satellite imagery. One of the advantages of SVM is that, with limited training data, it may generate comparable or even better results than the other methods. The SVM algorithm is used for automated object detection and characterization. Specifically, the SVM is applied in its basic nature as a binary classifier where it classifies two classes namely, object and background. The algorithm aims at effectively detecting an object from its background with the minimum training data. The synthetic image containing noises is used for algorithm testing. Furthermore, it is implemented to perform remote sensing image analysis such as identification of Island vegetation, water body, and oil spill from the satellite imagery. It is indicated that SVM provides the fast and accurate analysis with the acceptable result

Support vector machine as a binary classifier for automated object detection in remotely sensed data

Science.gov (United States)

Wardaya, P. D.

2014-02-01

In the present paper, author proposes the application of Support Vector Machine (SVM) for the analysis of satellite imagery. One of the advantages of SVM is that, with limited training data, it may generate comparable or even better results than the other methods. The SVM algorithm is used for automated object detection and characterization. Specifically, the SVM is applied in its basic nature as a binary classifier where it classifies two classes namely, object and background. The algorithm aims at effectively detecting an object from its background with the minimum training data. The synthetic image containing noises is used for algorithm testing. Furthermore, it is implemented to perform remote sensing image analysis such as identification of Island vegetation, water body, and oil spill from the satellite imagery. It is indicated that SVM provides the fast and accurate analysis with the acceptable result.

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.

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.

Polar bears from space: Assessing satellite imagery as a tool to track Arctic wildlife

Science.gov (United States)

Stapleton, Seth P.; LaRue, Michelle A.; Lecomte, Nicolas; Atkinson, Stephen N.; Garshelis, David L.; Porter, Claire; Atwood, Todd C.

2014-01-01

Development of efficient techniques for monitoring wildlife is a priority in the Arctic, where the impacts of climate change are acute and remoteness and logistical constraints hinder access. We evaluated high resolution satellite imagery as a tool to track the distribution and abundance of polar bears. We examined satellite images of a small island in Foxe Basin, Canada, occupied by a high density of bears during the summer ice-free season. Bears were distinguished from other light-colored spots by comparing images collected on different dates. A sample of ground-truthed points demonstrated that we accurately classified bears. Independent observers reviewed images and a population estimate was obtained using mark- recapture models. This estimate (N: 94; 95% Confidence Interval: 92-105) was remarkably similar to an abundance estimate derived from a line transect aerial survey conducted a few days earlier (N: 102; 95% CI: 69-152). Our findings suggest that satellite imagery is a promising tool for monitoring polar bears on land, with implications for use with other Arctic wildlife. Large scale applications may require development of automated detection processes to expedite review and analysis. Future research should assess the utility of multi-spectral imagery and examine sites with different environmental characteristics.

Polar bears from space: assessing satellite imagery as a tool to track Arctic wildlife.

Directory of Open Access Journals (Sweden)

Seth Stapleton

Full Text Available Development of efficient techniques for monitoring wildlife is a priority in the Arctic, where the impacts of climate change are acute and remoteness and logistical constraints hinder access. We evaluated high resolution satellite imagery as a tool to track the distribution and abundance of polar bears. We examined satellite images of a small island in Foxe Basin, Canada, occupied by a high density of bears during the summer ice-free season. Bears were distinguished from other light-colored spots by comparing images collected on different dates. A sample of ground-truthed points demonstrated that we accurately classified bears. Independent observers reviewed images and a population estimate was obtained using mark-recapture models. This estimate (N: 94; 95% Confidence Interval: 92-105 was remarkably similar to an abundance estimate derived from a line transect aerial survey conducted a few days earlier (N: 102; 95% CI: 69-152. Our findings suggest that satellite imagery is a promising tool for monitoring polar bears on land, with implications for use with other Arctic wildlife. Large scale applications may require development of automated detection processes to expedite review and analysis. Future research should assess the utility of multi-spectral imagery and examine sites with different environmental characteristics.

Polar bears from space: assessing satellite imagery as a tool to track Arctic wildlife.

Science.gov (United States)

Stapleton, Seth; LaRue, Michelle; Lecomte, Nicolas; Atkinson, Stephen; Garshelis, David; Porter, Claire; Atwood, Todd

2014-01-01

Development of efficient techniques for monitoring wildlife is a priority in the Arctic, where the impacts of climate change are acute and remoteness and logistical constraints hinder access. We evaluated high resolution satellite imagery as a tool to track the distribution and abundance of polar bears. We examined satellite images of a small island in Foxe Basin, Canada, occupied by a high density of bears during the summer ice-free season. Bears were distinguished from other light-colored spots by comparing images collected on different dates. A sample of ground-truthed points demonstrated that we accurately classified bears. Independent observers reviewed images and a population estimate was obtained using mark-recapture models. This estimate (N: 94; 95% Confidence Interval: 92-105) was remarkably similar to an abundance estimate derived from a line transect aerial survey conducted a few days earlier (N: 102; 95% CI: 69-152). Our findings suggest that satellite imagery is a promising tool for monitoring polar bears on land, with implications for use with other Arctic wildlife. Large scale applications may require development of automated detection processes to expedite review and analysis. Future research should assess the utility of multi-spectral imagery and examine sites with different environmental characteristics.

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...

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...

Integrating High-Resolution Taskable Imagery into a Sensorweb for Automatic Space-Based Monitoring of Flooding in Thailand

Science.gov (United States)

Chien, Steve; Mclaren, David; Doubleday, Joshua; Tran, Daniel; Tanpipat, Veerachai; Chitradon, Royol; Boonya-aroonnet, Surajate; Thanapakpawin, Porranee; Mandl, Daniel

2012-01-01

Several space-based assets (Terra, Aqua, Earth Observing One) have been integrated into a sensorweb to monitor flooding in Thailand. In this approach, the Moderate Imaging Spectrometer (MODIS) data from Terra and Aqua is used to perform broad-scale monitoring to track flooding at the regional level (250m/pixel) and EO-1 is autonomously tasked in response to alerts to acquire higher resolution (30m/pixel) Advanced Land Imager (ALI) data. This data is then automatically processed to derive products such as surface water extent and volumetric water estimates. These products are then automatically pushed to organizations in Thailand for use in damage estimation, relief efforts, and damage mitigation. More recently, this sensorweb structure has been used to request imagery, access imagery, and process high-resolution (several m to 30m), targetable asset imagery from commercial assets including Worldview-2, Ikonos, Radarsat-2, Landsat-7, and Geo-Eye-1. We describe the overall sensorweb framework as well as new workflows and products made possible via these extensions.

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...

Perception-oriented fusion of multi-sensor imagery: visible, IR, and SAR

Science.gov (United States)

Sidorchuk, D.; Volkov, V.; Gladilin, S.

2018-04-01

This paper addresses the problem of image fusion of optical (visible and thermal domain) data and radar data for the purpose of visualization. These types of images typically contain a lot of complimentary information, and their joint visualization can be useful and more convenient for human user than a set of individual images. To solve the image fusion problem we propose a novel algorithm that utilizes some peculiarities of human color perception and based on the grey-scale structural visualization. Benefits of presented algorithm are exemplified by satellite imagery.

Scrubbing Up: Multi-Scale Investigation of Woody Encroachment in a Southern African Savannah

Directory of Open Access Journals (Sweden)

Christopher G. Marston

2017-04-01

Full Text Available Changes in the extent of woody vegetation represent a major conservation question in many savannah systems around the globe. To address the problem of the current lack of broad-scale cost-effective tools for land cover monitoring in complex savannah environments, we use a multi-scale approach to quantifying vegetation change in Kruger National Park (KNP, South Africa. We test whether medium spatial resolution satellite data (Landsat, existing back to the 1970s, which have pixel sizes larger than typical vegetation patches, can nevertheless capture the thematic detail required to detect woody encroachment in savannahs. We quantify vegetation change over a 13-year period in KNP, examine the changes that have occurred, assess the drivers of these changes, and compare appropriate remote sensing data sources for monitoring change. We generate land cover maps for three areas of southern KNP using very high resolution (VHR and medium resolution satellite sensor imagery from February 2001 to 2014. Considerable land cover change has occurred, with large increases in shrubs replacing both trees and grassland. Examination of exclosure areas and potential environmental driver data suggests two mechanisms: elephant herbivory removing trees and at least one separate mechanism responsible for conversion of grassland to shrubs, theorised to be increasing atmospheric CO2. Thus, the combination of these mechanisms causes the novel two-directional shrub encroachment that we observe (tree loss and grassland conversion. Multi-scale comparison of classifications indicates that although spatial detail is lost when using medium resolution rather than VHR imagery for land cover classification (e.g., Landsat imagery cannot readily distinguish between tree and shrub classes, while VHR imagery can, the thematic detail contained within both VHR and medium resolution classifications is remarkably congruent. This suggests that medium resolution imagery contains sufficient

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.

A Neuroscientific Review of Imagery and Observation Use in Sport

OpenAIRE

Holmes , Paul; Calmels , Claire

2008-01-01

International audience; Imagery and observation are multicomponential, involving individual difference characteristics that modify the processes. The authors propose that both imagery and observation function by offering effective routes to access and reinforce neural networks for skilled performance. The neural isomor-phism with overt behaviors offers a tempting mechanism to explain the beneficial outcomes of the 2 processes. However, several limitations related to imagery indicate the possi...

Kinesthetic but not visual imagery assists in normalizing the CNV in Parkinson's disease.

Science.gov (United States)

Lim, Vanessa K; Polych, Melody A; Holländer, Antje; Byblow, Winston D; Kirk, Ian J; Hamm, Jeff P

2006-10-01

This study investigated whether kinesthetic and/or visual imagery could alter the contingent negative variation (CNV) for patients with Parkinson's disease (PD). The CNV was recorded in six patients with PD and seven controls before and after a 10min block of imagery. There were two types of imagery employed: kinesthetic and visual, which were evaluated on separate days. The global field power (GFP) of the late CNV did not change after the visual imagery for either group, nor was there a significant difference between the groups. In contrast, kinesthetic imagery resulted in significant group differences pre-, versus post-imagery GFPs, which was not present prior to performing the kinesthetic imagery task. In patients with PD, the CNV amplitudes post-, relative to pre-kinesthetic imagery, increased over the dorsolateral prefrontal regions and decreased in the ipsilateral parietal regions. There were no such changes in controls. A 10-min session of kinesthetic imagery enhanced the GFP amplitude of the late CNV for patients but not for controls. While the study needs to be replicated with a greater number of participants, the results suggest that kinesthetic imagery may be a promising tool for investigations into motor changes, and may potentially be employed therapeutically, in patients with Parkinson's disease.

Studying Action Representation in Children via Motor Imagery

Science.gov (United States)

Gabbard, Carl

2009-01-01

The use of motor imagery is a widely used experimental paradigm for the study of cognitive aspects of action planning and control in adults. Furthermore, there are indications that motor imagery provides a window into the process of action representation. These notions complement internal model theory suggesting that such representations allow…

Detection and Characterization of Hedgerows Using TerraSAR-X Imagery

Directory of Open Access Journals (Sweden)

Julie Betbeder

2014-04-01

Full Text Available Whilst most hedgerow functions depend upon hedgerow structure and hedgerow network patterns, in many ecological studies information on the fragmentation of hedgerows network and canopy structure is often retrieved in the field in small areas using accurate ground surveys and estimated over landscapes in a semi-quantitative manner. This paper explores the use of radar SAR imagery to (i detect hedgerow networks; and (ii describe the hedgerow canopy heterogeneity using TerraSAR-X imagery. The extraction of hedgerow networks was achieved using an object-oriented method using two polarimetric parameters: the Single Bounce and the Shannon Entropy derived from one TerraSAR-X image. The hedgerow canopy heterogeneity estimated from field measurements was compared with two backscattering coefficients and three polarimetric parameters derived from the same image. The results show that the hedgerow network and its fragmentation can be identified with a very good accuracy (Kappa index: 0.92. This study also reveals the high correlation between one polarimetric parameter, the Shannon entropy, and the canopy fragmentation measured in the field. Therefore, VHSR radar images can both precisely detect the presence of wooded hedgerow networks and characterize their structure, which cannot be achieved with optical images.

VERTICAL ACCURACY COMPARISON OF DIGITAL ELEVATION MODEL FROM LIDAR AND MULTITEMPORAL SATELLITE IMAGERY

Directory of Open Access Journals (Sweden)

J. Octariady

2017-05-01

Full Text Available Digital elevation model serves to illustrate the appearance of the earth's surface. DEM can be produced from a wide variety of data sources including from radar data, LiDAR data, and stereo satellite imagery. Making the LiDAR DEM conducted using point cloud data from LiDAR sensor. Making a DEM from stereo satellite imagery can be done using same temporal or multitemporal stereo satellite imagery. How much the accuracy of DEM generated from multitemporal stereo stellite imagery and LiDAR data is not known with certainty. The study was conducted using LiDAR DEM data and multitemporal stereo satellite imagery DEM. Multitemporal stereo satellite imagery generated semi-automatically by using 3 scene stereo satellite imagery with acquisition 2013–2014. The high value given each of DEM serve as the basis for calculating high accuracy DEM respectively. The results showed the high value differences in the fraction of the meter between LiDAR DEM and multitemporal stereo satellite imagery DEM.

An Object-Based Image Analysis Approach for Detecting Penguin Guano in very High Spatial Resolution Satellite Images

Directory of Open Access Journals (Sweden)

Chandi Witharana

2016-04-01

Full Text Available 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 knowledge-based GEOBIA rules across different study sites focusing on the same semantic class. We systematically gauged the segmentation quality, classification accuracy, and the reproducibility of fuzzy rules. A master ruleset was developed based on one study site and it was re-tasked “without adaptation” and “with adaptation” on candidate image scenes comprising guano stains. Our results suggest that object-based methods incorporating the spectral, textural, spatial, and contextual characteristics of guano are capable of successfully detecting guano stains. Reapplication of the master ruleset on candidate scenes without modifications produced inferior classification results, while adapted rules produced comparable or superior results compared to the reference image. This work provides a road map to an operational “image-to-assessment pipeline” that will enable Antarctic wildlife researchers to seamlessly integrate VHSR imagery into on-demand penguin population census.

6883 Maintenance Training Simulator Development Utilizing Imagery Techniques.

Science.gov (United States)

1980-05-01

increased motivation (as by its game-like setting), etc. These questions are left for future inquiry. 26 CONCLUSIONS AND RECOMMENDATIONS The imagery training...the output of power supply PS4 ." 46. 46 ; 20b. Read instructions (imagery group only). "To ready the board, take the one drawing that is titled

Task-dependent engagements of the primary visual cortex during kinesthetic and visual motor imagery.

Science.gov (United States)

Mizuguchi, Nobuaki; Nakamura, Maiko; Kanosue, Kazuyuki

2017-01-01

Motor imagery can be divided into kinesthetic and visual aspects. In the present study, we investigated excitability in the corticospinal tract and primary visual cortex (V1) during kinesthetic and visual motor imagery. To accomplish this, we measured motor evoked potentials (MEPs) and probability of phosphene occurrence during the two types of motor imageries of finger tapping. The MEPs and phosphenes were induced by transcranial magnetic stimulation to the primary motor cortex and V1, respectively. The amplitudes of MEPs and probability of phosphene occurrence during motor imagery were normalized based on the values obtained at rest. Corticospinal excitability increased during both kinesthetic and visual motor imagery, while excitability in V1 was increased only during visual motor imagery. These results imply that modulation of cortical excitability during kinesthetic and visual motor imagery is task dependent. The present finding aids in the understanding of the neural mechanisms underlying motor imagery and provides useful information for the use of motor imagery in rehabilitation or motor imagery training. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

An Adaptive Ship Detection Scheme for Spaceborne SAR Imagery

Directory of Open Access Journals (Sweden)

Xiangguang Leng

2016-08-01

Full Text Available With the rapid development of spaceborne synthetic aperture radar (SAR and the increasing need of ship detection, research on adaptive ship detection in spaceborne SAR imagery is of great importance. Focusing on practical problems of ship detection, this paper presents a highly adaptive ship detection scheme for spaceborne SAR imagery. It is able to process a wide range of sensors, imaging modes and resolutions. Two main stages are identified in this paper, namely: ship candidate detection and ship discrimination. Firstly, this paper proposes an adaptive land masking method using ship size and pixel size. Secondly, taking into account the imaging mode, incidence angle, and polarization channel of SAR imagery, it implements adaptive ship candidate detection in spaceborne SAR imagery by applying different strategies to different resolution SAR images. Finally, aiming at different types of typical false alarms, this paper proposes a comprehensive ship discrimination method in spaceborne SAR imagery based on confidence level and complexity analysis. Experimental results based on RADARSAT-1, RADARSAT-2, TerraSAR-X, RS-1, and RS-3 images demonstrate that the adaptive scheme proposed in this paper is able to detect ship targets in a fast, efficient and robust way.

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,…

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...

Imitation and matching of meaningless gestures: distinct involvement from motor and visual imagery.

Science.gov (United States)

Lesourd, Mathieu; Navarro, Jordan; Baumard, Josselin; Jarry, Christophe; Le Gall, Didier; Osiurak, François

2017-05-01

The aim of the present study was to understand the underlying cognitive processes of imitation and matching of meaningless gestures. Neuropsychological evidence obtained in brain damaged patients, has shown that distinct cognitive processes supported imitation and matching of meaningless gestures. Left-brain damaged (LBD) patients failed to imitate while right-brain damaged (RBD) patients failed to match meaningless gestures. Moreover, other studies with brain damaged patients showed that LBD patients were impaired in motor imagery while RBD patients were impaired in visual imagery. Thus, we hypothesize that imitation of meaningless gestures might rely on motor imagery, whereas matching of meaningless gestures might be based on visual imagery. In a first experiment, using a correlational design, we demonstrated that posture imitation relies on motor imagery but not on visual imagery (Experiment 1a) and that posture matching relies on visual imagery but not on motor imagery (Experiment 1b). In a second experiment, by manipulating directly the body posture of the participants, we demonstrated that such manipulation evokes a difference only in imitation task but not in matching task. In conclusion, the present study provides direct evidence that the way we imitate or we have to compare postures depends on motor imagery or visual imagery, respectively. Our results are discussed in the light of recent findings about underlying mechanisms of meaningful and meaningless gestures.

What makes an ad a cigarette ad? Commercial tobacco imagery in the lesbian, gay, and bisexual press

Science.gov (United States)

Smith, E.; Offen, N.; Malone, R.

2005-01-01

Objectives: To determine the extent of commercial tobacco imagery in the lesbian, gay, and bisexual (LGB) press. Methods: Content analysis of all advertising containing tobacco related text or imagery in 20 LGB community periodicals, published between January 1990 and December 2000. Results: 3428 ads were found: 689 tobacco product ads, 1607 ads for cessation products or services, 99 ads with a political message about tobacco, and 1033 non-tobacco ads that showed tobacco (NAST). Although cessation ads were numerically dominant, tobacco product ads and NAST occupied more space and were more likely to use images. NAST almost never had an anti-tobacco message. Formal sponsorship between tobacco and other companies was very rare. Lesbian periodicals had proportionally more NAST and fewer cessation ads. Conclusions: Cigarette ads were outnumbered by NAST. Although these ads do not usually show brands, and are unlikely to be the result of formal sponsorship agreements, they may be "selling" smoking. Tobacco control advocates should persuade editors to refuse tobacco product ads and those with gratuitous tobacco imagery. PMID:16286500

[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.

Negative mental imagery in public speaking anxiety: Forming cognitive resistance by taxing visuospatial working memory.

Science.gov (United States)

Homer, Sophie R; Deeprose, Catherine; Andrade, Jackie

2016-03-01

This study sought to reconcile two lines of research. Previous studies have identified a prevalent and causal role of negative imagery in social phobia and public speaking anxiety; others have demonstrated that lateral eye movements during visualisation of imagery reduce its vividness, most likely by loading the visuospatial sketchpad of working memory. It was hypothesised that using eye movements to reduce the intensity of negative imagery associated with public speaking may reduce anxiety resulting from imagining a public speaking scenario compared to an auditory control task. Forty undergraduate students scoring high in anxiety on the Personal Report of Confidence as a Speaker scale took part. A semi-structured interview established an image that represented the participant's public speaking anxiety, which was then visualised during an eye movement task or a matched auditory task. Reactions to imagining a hypothetical but realistic public speaking scenario were measured. As hypothesised, representative imagery was established and reduced in vividness more effectively by the eye movement task than the auditory task. The public speaking scenario was then visualised less vividly and generated less anxiety when imagined after performing the eye movement task than after the auditory task. Self-report measures and a hypothetical scenario rather than actual public speaking were used. Replication is required in larger as well as clinical samples. Visuospatial working memory tasks may preferentially reduce anxiety associated with personal images of feared events, and thus provide cognitive resistance which reduces emotional reactions to imagined, and potentially real-life future stressful experiences. Copyright © 2015 Elsevier Ltd. All rights reserved.

Emergency Response Imagery Related to Hurricanes Harvey, Irma, and Maria

Science.gov (United States)

Worthem, A. V.; Madore, B.; Imahori, G.; Woolard, J.; Sellars, J.; Halbach, A.; Helmricks, D.; Quarrick, J.

2017-12-01

NOAA's National Geodetic Survey (NGS) and Remote Sensing Division acquired and rapidly disseminated emergency response imagery related to the three recent hurricanes Harvey, Irma, and Maria. Aerial imagery was collected using a Trimble Digital Sensor System, a high-resolution digital camera, by means of NOAA's King Air 350ER and DeHavilland Twin Otter (DHC-6) Aircraft. The emergency response images are used to assess the before and after effects of the hurricanes' damage. The imagery aids emergency responders, such as FEMA, Coast Guard, and other state and local governments, in developing recovery strategies and efforts by prioritizing areas most affected and distributing appropriate resources. Collected imagery is also used to provide damage assessment for use in long-term recovery and rebuilding efforts. Additionally, the imagery allows for those evacuated persons to see images of their homes and neighborhoods remotely. Each of the individual images are processed through ortho-rectification and merged into a uniform mosaic image. These remotely sensed datasets are publically available, and often used by web-based map servers as well as, federal, state, and local government agencies. This poster will show the imagery collected for these three hurricanes and the processes involved in getting data quickly into the hands of those that need it most.

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.

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...

Brain activation profiles during kinesthetic and visual imagery: An fMRI study.

Science.gov (United States)

Kilintari, Marina; Narayana, Shalini; Babajani-Feremi, Abbas; Rezaie, Roozbeh; Papanicolaou, Andrew C

2016-09-01

The aim of this study was to identify brain regions involved in motor imagery and differentiate two alternative strategies in its implementation: imagining a motor act using kinesthetic or visual imagery. Fourteen adults were precisely instructed and trained on how to imagine themselves or others perform a movement sequence, with the aim of promoting kinesthetic and visual imagery, respectively, in the context of an fMRI experiment using block design. We found that neither modality of motor imagery elicits activation of the primary motor cortex and that each of the two modalities involves activation of the premotor area which is also activated during action execution and action observation conditions, as well as of the supplementary motor area. Interestingly, the visual and the posterior cingulate cortices show reduced BOLD signal during both imagery conditions. Our results indicate that the networks of regions activated in kinesthetic and visual imagery of motor sequences show a substantial, while not complete overlap, and that the two forms of motor imagery lead to a differential suppression of visual areas. Copyright © 2016 Elsevier B.V. All rights reserved.

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

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...

Representations and Techniques for 3D Object Recognition and Scene Interpretation

CERN Document Server

Hoiem, Derek

2011-01-01

One of the grand challenges of artificial intelligence is to enable computers to interpret 3D scenes and objects from imagery. This book organizes and introduces major concepts in 3D scene and object representation and inference from still images, with a focus on recent efforts to fuse models of geometry and perspective with statistical machine learning. The book is organized into three sections: (1) Interpretation of Physical Space; (2) Recognition of 3D Objects; and (3) Integrated 3D Scene Interpretation. The first discusses representations of spatial layout and techniques to interpret physi

North-American Conference Highlights the Treatment of Trauma Utilizing Guided Imagery and Music

DEFF Research Database (Denmark)

Scott-Montcrieff, Suzannah; Beck, Bolette Daniels; Montgomery, Erin

2015-01-01

A report on the 2015 Association for Music and Imagery conference highlights papers that address clinical practice and research using Guided Imagery and Music for the treatment of trauma.......A report on the 2015 Association for Music and Imagery conference highlights papers that address clinical practice and research using Guided Imagery and Music for the treatment of trauma....

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

Automated Soil Physical Parameter Assessment Using Smartphone and Digital Camera Imagery

Directory of Open Access Journals (Sweden)

Matt Aitkenhead

2016-12-01

Full Text Available Here we present work on using different types of soil profile imagery (topsoil profiles captured with a smartphone camera and full-profile images captured with a conventional digital camera to estimate the structure, texture and drainage of the soil. The method is adapted from earlier work on developing smartphone apps for estimating topsoil organic matter content in Scotland and uses an existing visual soil structure assessment approach. Colour and image texture information was extracted from the imagery. This information was linked, using geolocation information derived from the smartphone GPS system or from field notes, with existing collections of topography, land cover, soil and climate data for Scotland. A neural network model was developed that was capable of estimating soil structure (on a five-point scale, soil texture (sand, silt, clay, bulk density, pH and drainage category using this information. The model is sufficiently accurate to provide estimates of these parameters from soils in the field. We discuss potential improvements to the approach and plans to integrate the model into a set of smartphone apps for estimating health and fertility indicators for Scottish soils.

The effect of motor imagery with specific implement in expert badminton player.

Science.gov (United States)

Wang, Z; Wang, S; Shi, F-Y; Guan, Y; Wu, Y; Zhang, L-L; Shen, C; Zeng, Y-W; Wang, D-H; Zhang, J

2014-09-05

Motor skill can be improved with mental simulation. Implements are widely used in daily life and in various sports. However, it is unclear whether the utilization of implements enhances the effect of mental simulation. The present study was designed to investigate the different effects of motor imagery in athletes and novices when they handled a specific implement. We hypothesize that athletes have better motor imagery ability than novices when they hold a specific implement for the sport. This is manifested as higher motor cortical excitability in athletes than novices during motor imagery with the specific implement. Sixteen expert badminton players and 16 novices were compared when they held a specific implement such as a badminton racket and a non-specific implement such as a a plastic bar. Motor imagery ability was measured with a self-evaluation questionnaire. Transcranial magnetic stimulation was used to test the motor cortical excitability during motor imagery. Motor-evoked potentials (MEPs) in the first dorsal interosseous (FDI) and extensor carpi radialis muscles were recorded. Athletes reported better motor imagery than novices when they held a specific implement. Athletes exhibited more MEP facilitation than novices in the FDI muscle with the specific implement applied during motor imagery. The MEP facilitation is correlated with motor imagery ability in athletes. We conclude that the effects of motor imagery with a specific implement are enhanced in athletes compared to novices and the difference between two groups is caused by long-term physical training of athletes with the specific implement. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

Learning multiscale and deep representations for classifying remotely sensed imagery

Science.gov (United States)

Zhao, Wenzhi; Du, Shihong

2016-03-01

It is widely agreed that spatial features can be combined with spectral properties for improving interpretation performances on very-high-resolution (VHR) images in urban areas. However, many existing methods for extracting spatial features can only generate low-level features and consider limited scales, leading to unpleasant classification results. In this study, multiscale convolutional neural network (MCNN) algorithm was presented to learn spatial-related deep features for hyperspectral remote imagery classification. Unlike traditional methods for extracting spatial features, the MCNN first transforms the original data sets into a pyramid structure containing spatial information at multiple scales, and then automatically extracts high-level spatial features using multiscale training data sets. Specifically, the MCNN has two merits: (1) high-level spatial features can be effectively learned by using the hierarchical learning structure and (2) multiscale learning scheme can capture contextual information at different scales. To evaluate the effectiveness of the proposed approach, the MCNN was applied to classify the well-known hyperspectral data sets and compared with traditional methods. The experimental results shown a significant increase in classification accuracies especially for urban areas.

Research of building information extraction and evaluation based on high-resolution remote-sensing imagery

Science.gov (United States)

Cao, Qiong; Gu, Lingjia; Ren, Ruizhi; Wang, Lang

2016-09-01

Building extraction currently is important in the application of high-resolution remote sensing imagery. At present, quite a few algorithms are available for detecting building information, however, most of them still have some obvious disadvantages, such as the ignorance of spectral information, the contradiction between extraction rate and extraction accuracy. The purpose of this research is to develop an effective method to detect building information for Chinese GF-1 data. Firstly, the image preprocessing technique is used to normalize the image and image enhancement is used to highlight the useful information in the image. Secondly, multi-spectral information is analyzed. Subsequently, an improved morphological building index (IMBI) based on remote sensing imagery is proposed to get the candidate building objects. Furthermore, in order to refine building objects and further remove false objects, the post-processing (e.g., the shape features, the vegetation index and the water index) is employed. To validate the effectiveness of the proposed algorithm, the omission errors (OE), commission errors (CE), the overall accuracy (OA) and Kappa are used at final. The proposed method can not only effectively use spectral information and other basic features, but also avoid extracting excessive interference details from high-resolution remote sensing images. Compared to the original MBI algorithm, the proposed method reduces the OE by 33.14% .At the same time, the Kappa increase by 16.09%. In experiments, IMBI achieved satisfactory results and outperformed other algorithms in terms of both accuracies and visual inspection

Alcohol imagery on popularly viewed television in the UK.

Science.gov (United States)

Lyons, Ailsa; McNeill, Ann; Britton, John