Determination of turbidity patterns in Lake Chicot from LANDSAT MSS imagery

NASA Technical Reports Server (NTRS)

Lecroy, S. R. (Principal Investigator)

1982-01-01

A historical analysis of all the applicable LANDSAT imagery was conducted on the turbidity patterns of Lake Chicot, located in the southeastern corner of Arkansas. By examining the seasonal and regional turbidity patterns, a record of sediment dynamics and possible disposition can be obtained. Sketches were generated from the suitable imagery, displaying different intensities of brightness observed in bands 5 and 7 of LANDSAT's multispectral scanner data. Differences in and between bands 5 and 7 indicate variances in the levels of surface sediment concentrations. High sediment loads are revealed when distinct patterns appear in the band 7 imagery. Additionally, the upwelled signal is exponential in nature and saturates in band 5 at low wavelengths for large concentrations of suspended solids.

Analysis of optical imagery reveals regionally coherent slowdown in High Mountain Asia in response to glacier thinning

NASA Astrophysics Data System (ADS)

Dehecq, A.; Gardner, A. S.; Gourmelen, N.

2016-12-01

High Mountain Asia (HMA) glaciers play a key role in the hydrology of the region, impacting water resources. Studies focusing on HMA glaciers reveal contrasting patterns of change with rapid rates of retreat in Himalayas and near balance condition in the Karakorum, Pamir and Kunlun. Glaciers dynamics is a key variable to understand their future evolution and sensitivity to changes in atmospheric forcing. Several studies based on field measurements and remote sensing data have shown consistent slow-down of land terminating glaciers in response to ice thinning. While highly insightful, these studies have relied on the analysis of glacier velocities over small regions and/or a limited number of glaciers. Here we analyze changes in ice velocities for thousands of glaciers in HMA from optical satellite images. Applying feature-tracking algorithms to the entire Landsat 7 (SLC-ON) and 8 archives, we generated surface velocity fields over 90% of the HMA with an uncertainty of the order of 4 m/yr. The change in velocities over the last 15 years will be analyzed with reference to regional glacier elevation changes and topographic characteristics. We show that the first-order temporal evolution of glacier flow mirrors the pattern of glacier elevation changes. We observe a general decrease of ice velocity in regions of known ice mass loss, and a more complex patterns consisting of mixed acceleration and decrease of ice velocity in regions that are experiencing near-equilibrium conditions and exhibit surging behavior. To provide long-term context we analyze Landsat 4/5 to construct sparse historic velocities and Hexagon KH-9 mapping camera imagery to reconstruct historic elevations dating back as early as the 1970'. However, the older imagery is sparse due to limited downlink locations and bandwidth. In addition, sensor geometry and pointing knowledge are crude in comparison to modern imagery, imagery is often saturated (featureless) over bright snow and ice surface, and many images suffer from banding artifacts.

Brain-based decoding of mentally imagined film clips and sounds reveals experience-based information patterns in film professionals.

PubMed

de Borst, Aline W; Valente, Giancarlo; Jääskeläinen, Iiro P; Tikka, Pia

2016-04-01

In the perceptual domain, it has been shown that the human brain is strongly shaped through experience, leading to expertise in highly-skilled professionals. What has remained unclear is whether specialization also shapes brain networks underlying mental imagery. In our fMRI study, we aimed to uncover modality-specific mental imagery specialization of film experts. Using multi-voxel pattern analysis we decoded from brain activity of professional cinematographers and sound designers whether they were imagining sounds or images of particular film clips. In each expert group distinct multi-voxel patterns, specific for the modality of their expertise, were found during classification of imagery modality. These patterns were mainly localized in the occipito-temporal and parietal cortex for cinematographers and in the auditory cortex for sound designers. We also found generalized patterns across perception and imagery that were distinct for the two expert groups: they involved frontal cortex for the cinematographers and temporal cortex for the sound designers. Notably, the mental representations of film clips and sounds of cinematographers contained information that went beyond modality-specificity. We were able to successfully decode the implicit presence of film genre from brain activity during mental imagery in cinematographers. The results extend existing neuroimaging literature on expertise into the domain of mental imagery and show that experience in visual versus auditory imagery can alter the representation of information in modality-specific association cortices. Copyright © 2016 Elsevier Inc. All rights reserved.

Proceedings of the Third Annual Symposium on Mathematical Pattern Recognition and Image Analysis

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr.

1985-01-01

Topics addressed include: multivariate spline method; normal mixture analysis applied to remote sensing; image data analysis; classifications in spatially correlated environments; probability density functions; graphical nonparametric methods; subpixel registration analysis; hypothesis integration in image understanding systems; rectification of satellite scanner imagery; spatial variation in remotely sensed images; smooth multidimensional interpolation; and optimal frequency domain textural edge detection filters.

Real time system design of motor imagery brain-computer interface based on multi band CSP and SVM

NASA Astrophysics Data System (ADS)

Zhao, Li; Li, Xiaoqin; Bian, Yan

2018-04-01

Motion imagery (MT) is an effective method to promote the recovery of limbs in patients after stroke. Though an online MT brain computer interface (BCT) system, which apply MT, can enhance the patient's participation and accelerate their recovery process. The traditional method deals with the electroencephalogram (EEG) induced by MT by common spatial pattern (CSP), which is used to extract information from a frequency band. Tn order to further improve the classification accuracy of the system, information of two characteristic frequency bands is extracted. The effectiveness of the proposed feature extraction method is verified by off-line analysis of competition data and the analysis of online system.

Detecting Suspended Sediments from Remote Sensed Data in the Northern Gulf of Mexico

NASA Astrophysics Data System (ADS)

Hardin, D. M.; Graves, S. J.; Hawkins, L.; He, M.; Smith, T.; Drewry, M.; Ebersole, S.; Travis, A.; Thorn, J.; Brown, B.

2012-12-01

The Sediment Analysis Network for Decision Support (SANDS) project utilized remotely sensed data from Landsat and MODIS, both prior and following landfall, to investigate suspended sediment and sediment redistribution. The satellite imagery was enhanced by applying a combination of cluster busting and classification techniques to color and infrared bands. Results from the process show patterns associated with sediment transport and deposition related to coastal processes, storm-related sediment transport, post-storm pollutant transport, and sediment-current interactions. Imagery prior to landfall and following landfall are shown to the left for Landsat and to the right for MODIS. Scientific analysis and production of enhanced imagery was conducted by the Geological Survey of Alabama. The Information Technology and Systems Center at the University of Alabama in Huntsville was responsible for data acquisition, development of the SANDS data portal and the archive and distribution through the Global Hydrology Resource Center, one of NASA's Earth Science Data Centers . SANDs data may be obtained from the GHRC at ghrc.nsstc.nasa.gov and from the SANDS data portal at sands.itsc.uah.edu. This project was funded by the NASA Applied Sciences Division

Investigating the effects of a sensorimotor rhythm-based BCI training on the cortical activity elicited by mental imagery

NASA Astrophysics Data System (ADS)

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.

Investigating the effects of a sensorimotor rhythm-based BCI training on the cortical activity elicited by mental imagery.

PubMed

Toppi, J; Risetti, M; Quitadamo, L R; Petti, M; Bianchi, L; Salinari, S; Babiloni, F; Cincotti, F; Mattia, D; Astolfi, L

2014-06-01

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. 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. 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. 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.

Biocybernetic factors in human perception and memory

NASA Technical Reports Server (NTRS)

Lai, D. C.

1975-01-01

The objective of this research is to develop biocybernetic techniques for use in the analysis and development of skills required for the enhancement of concrete images of the 'eidetic' type. The scan patterns of the eye during inspection of scenes are treated as indicators of the brain's strategy for the intake of visual information. The authors determine the features that differentiate visual scan patterns associated with superior imagery from scan patterns associated with inferior imagery, and simultaneously differentiate the EEG features correlated with superior imagery from those correlated with inferior imagery. A closely-coupled man-machine system has been designed to generate image enhancement and to train the individual to exert greater voluntary control over his own imagery. The models for EEG signals and saccadic eye movement in the man-machine system have been completed. The report describes the details of these models and discusses their usefulness.

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

PubMed

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.

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

NASA Astrophysics Data System (ADS)

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.

Filtering high resolution hyperspectral imagery and analyzing it for quantification of water quality parameters and aquatic vegetation

NASA Astrophysics Data System (ADS)

Pande-Chhetri, Roshan

High resolution hyperspectral imagery (airborne or ground-based) is gaining momentum as a useful analytical tool in various fields including agriculture and aquatic systems. These images are often contaminated with stripes and noise resulting in lower signal-to-noise ratio, especially in aquatic regions where signal is naturally low. This research investigates effective methods for filtering high spatial resolution hyperspectral imagery and use of the imagery in water quality parameter estimation and aquatic vegetation classification. The striping pattern of the hyperspectral imagery is non-parametric and difficult to filter. In this research, a de-striping algorithm based on wavelet analysis and adaptive Fourier domain normalization was examined. The result of this algorithm was found superior to other available algorithms and yielded highest Peak Signal to Noise Ratio improvement. The algorithm was implemented on individual image bands and on selected bands of the Maximum Noise Fraction (MNF) transformed images. The results showed that image filtering in the MNF domain was efficient and produced best results. The study investigated methods of analyzing hyperspectral imagery to estimate water quality parameters and to map aquatic vegetation in case-2 waters. Ground-based hyperspectral imagery was analyzed to determine chlorophyll-a (Chl-a) concentrations in aquaculture ponds. Two-band and three-band indices were implemented and the effect of using submerged reflectance targets was evaluated. Laboratory measured values were found to be in strong correlation with two-band and three-band spectral indices computed from the hyperspectral image. Coefficients of determination (R2) values were found to be 0.833 and 0.862 without submerged targets and stronger values of 0.975 and 0.982 were obtained using submerged targets. Airborne hyperspectral images were used to detect and classify aquatic vegetation in a black river estuarine system. Image normalization for water surface reflectance and water depths was conducted and non-parametric classifiers such as ANN, SVM and SAM were tested and compared. Quality assessment indicated better classification and detection when non-parametric classifiers were applied to normalized or depth invariant transform images. Best classification accuracy of 73% was achieved when ANN is applied on normalized image and best detection accuracy of around 92% was obtained when SVM or SAM was applied on depth invariant images.

Overland Flow Analysis Using Time Series of Suas-Derived Elevation Models

NASA Astrophysics Data System (ADS)

Jeziorska, J.; Mitasova, H.; Petrasova, A.; Petras, V.; Divakaran, D.; Zajkowski, T.

2016-06-01

With the advent of the innovative techniques for generating high temporal and spatial resolution terrain models from Unmanned Aerial Systems (UAS) imagery, it has become possible to precisely map overland flow patterns. Furthermore, the process has become more affordable and efficient through the coupling of small UAS (sUAS) that are easily deployed with Structure from Motion (SfM) algorithms that can efficiently derive 3D data from RGB imagery captured with consumer grade cameras. We propose applying the robust overland flow algorithm based on the path sampling technique for mapping flow paths in the arable land on a small test site in Raleigh, North Carolina. By comparing a time series of five flights in 2015 with the results of a simulation based on the most recent lidar derived DEM (2013), we show that the sUAS based data is suitable for overland flow predictions and has several advantages over the lidar data. The sUAS based data captures preferential flow along tillage and more accurately represents gullies. Furthermore the simulated water flow patterns over the sUAS based terrain models are consistent throughout the year. When terrain models are reconstructed only from sUAS captured RGB imagery, however, water flow modeling is only appropriate in areas with sparse or no vegetation cover.

Normalization of satellite imagery

NASA Technical Reports Server (NTRS)

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.

An evaluation of Skylab (EREP) remote sensing techniques applied to investigations of crustal structure. [southwestern USA

NASA Technical Reports Server (NTRS)

Bechtold, I. C. (Principal Investigator); Reynolds, J. T.; Archer, R. L.; Wagner, C. G.

1975-01-01

The author has identified the following significant results. Film positives (70mm) from all six S190A multispectral photographic camera stations for any one scene can be registered and analyzed in a color additive viewer. Using a multispectral viewer, S190A and B films can be projected directly onto published geologic and topographic maps at scales as large as 1:62,500 and 1:24,000 without significant loss of detail. S190A films and prints permit the detection of faults, fractures, and other linear features not visible in any other space imagery. S192 MSS imagery can be useful for rock-type discrimination studies and delineation of linear patterns and arcuate anomalies. Anomalous color reflectances and arcuate color patterns revealed mineralized zones, copper deposits, vegetation, and volcanic rocks in various locations such as Panamint Range (CA), Greenwater (Death Valley), Lava Mountains (CA), northwestern Arizona, and Coso Hot Springs (CA).

Utilizing remote sensing of Thematic Mapper data to improve our understanding of estuarine processes and their influence on the productivity of estuarine-dependent fisheries

NASA Technical Reports Server (NTRS)

Browder, J. A.; May, L. N., Jr.; Rosenthal, A.; Baumann, R. H.; Gosselink, J. G.

1986-01-01

LANDSAT thematic mapper (TM) data are being used to refine and validate a stochastic spatial computer model to be applied to coastal resource management problems in Louisiana. Two major aspects of the research are: (1) the measurement of area of land (or emergent vegetation) and water and the length of the interface between land and water in TM imagery of selected coastal wetlands (sample marshes); and (2) the comparison of spatial patterns of land and water in the sample marshes of the imagery to that in marshes simulated by a computer model. In addition to activities in these two areas, the potential use of a published autocorrelation statistic is analyzed.

ERTS-1 imagery of eastern Africa: A first look at the geological structure of selected areas

NASA Technical Reports Server (NTRS)

Mohr, P. A. (Principal Investigator)

1972-01-01

The author has identified the following significant results. Imagery of the African rift system resolves the major Cainozoic faults, zones of warping, and associated volcanism. It also clearly depicts the crystal grain of the Precambrian rocks where these are exposed. New structural features, or new properties of known features such as greater extent, continuity, and linearity are revealed by ERTS-1 imagery. This applies, for example, to the NE-SW fracture zones in Yemen, the Aswa mylonite zone at the northern end of the Western Rift, the Nandi fault of western Kenya, the linear faults of the Elgeyo escarpment in the Gregory Rift, and the hemibasins of warped Tertiary lavas on the Red Sea margin of Yemen, matching those of Ethiopian plateau-Afar margin. A tentative scheme is proposed, relating the effect on the pattern of Cainozoic faulting of the degree of obliquity to Precambrian structural trend. It is particularly noteworthy that, even where the Precambrian grain determines the rift faulting to be markedly oblique to the overall trend of the rift trough, for example, in central Lake Tanganyika, the width of the trough is not significantly increased. Some ground mapped lithological boundaries are obscure on ERTS-1 imagery.

What Do Eye Gaze Metrics Tell Us about Motor Imagery?

PubMed

Poiroux, Elodie; Cavaro-Ménard, Christine; Leruez, Stéphanie; Lemée, Jean Michel; Richard, Isabelle; Dinomais, Mickael

2015-01-01

Many of the brain structures involved in performing real movements also have increased activity during imagined movements or during motor observation, and this could be the neural substrate underlying the effects of motor imagery in motor learning or motor rehabilitation. In the absence of any objective physiological method of measurement, it is currently impossible to be sure that the patient is indeed performing the task as instructed. Eye gaze recording during a motor imagery task could be a possible way to "spy" on the activity an individual is really engaged in. The aim of the present study was to compare the pattern of eye movement metrics during motor observation, visual and kinesthetic motor imagery (VI, KI), target fixation, and mental calculation. Twenty-two healthy subjects (16 females and 6 males), were required to perform tests in five conditions using imagery in the Box and Block Test tasks following the procedure described by Liepert et al. Eye movements were analysed by a non-invasive oculometric measure (SMI RED250 system). Two parameters describing gaze pattern were calculated: the index of ocular mobility (saccade duration over saccade + fixation duration) and the number of midline crossings (i.e. the number of times the subjects gaze crossed the midline of the screen when performing the different tasks). Both parameters were significantly different between visual imagery and kinesthesic imagery, visual imagery and mental calculation, and visual imagery and target fixation. For the first time we were able to show that eye movement patterns are different during VI and KI tasks. Our results suggest gaze metric parameters could be used as an objective unobtrusive approach to assess engagement in a motor imagery task. Further studies should define how oculomotor parameters could be used as an indicator of the rehabilitation task a patient is engaged in.

Comparison of EEG-Features and Classification Methods for Motor Imagery in Patients with Disorders of Consciousness

PubMed Central

Höller, Yvonne; Bergmann, Jürgen; Thomschewski, Aljoscha; Kronbichler, Martin; Höller, Peter; Crone, Julia S.; Schmid, Elisabeth V.; Butz, Kevin; Nardone, Raffaele; Trinka, Eugen

2013-01-01

Current research aims at identifying voluntary brain activation in patients who are behaviorally diagnosed as being unconscious, but are able to perform commands by modulating their brain activity patterns. This involves machine learning techniques and feature extraction methods such as applied in brain computer interfaces. In this study, we try to answer the question if features/classification methods which show advantages in healthy participants are also accurate when applied to data of patients with disorders of consciousness. A sample of healthy participants (N = 22), patients in a minimally conscious state (MCS; N = 5), and with unresponsive wakefulness syndrome (UWS; N = 9) was examined with a motor imagery task which involved imagery of moving both hands and an instruction to hold both hands firm. We extracted a set of 20 features from the electroencephalogram and used linear discriminant analysis, k-nearest neighbor classification, and support vector machines (SVM) as classification methods. In healthy participants, the best classification accuracies were seen with coherences (mean = .79; range = .53−.94) and power spectra (mean = .69; range = .40−.85). The coherence patterns in healthy participants did not match the expectation of central modulated -rhythm. Instead, coherence involved mainly frontal regions. In healthy participants, the best classification tool was SVM. Five patients had at least one feature-classifier outcome with p0.05 (none of which were coherence or power spectra), though none remained significant after false-discovery rate correction for multiple comparisons. The present work suggests the use of coherences in patients with disorders of consciousness because they show high reliability among healthy subjects and patient groups. However, feature extraction and classification is a challenging task in unresponsive patients because there is no ground truth to validate the results. PMID:24282545

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

NASA Technical Reports Server (NTRS)

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.

Determination of circulation and turbidity patterns in Kerr Lake from LANDSAT MSS imagery. [Kerr Lake, Virginia, North Carolina

NASA Technical Reports Server (NTRS)

Lecroy, S. R. (Principal Investigator)

1981-01-01

The LANDSAT imagery was historically analyzed to determine the circulation and turbidity patterns of Kerr Lake, located on the Virginia-North Carolina border. By examining the seasonal and regional turbidity and circulation patterns, a record of sediment transport and possible disposition can be obtained. Sketches were generated, displaying different intensities of brightness observed in bands 5 and 7 of LANDSAT's multispectral scanner data. Differences in and between bands 5 and 7 indicate variances in the levels of surface sediment concentrations. High sediment loads are revealed when distinct patterns appear in the band 7 imagery. The upwelled signal is exponential in nature and saturates in band 5 at low wavelengths for large concentrations of suspended solids.

A Comparison of Independent Event-Related Desynchronization Responses in Motor-Related Brain Areas to Movement Execution, Movement Imagery, and Movement Observation.

PubMed

Duann, Jeng-Ren; Chiou, Jin-Chern

2016-01-01

Electroencephalographic (EEG) event-related desynchronization (ERD) induced by movement imagery or by observing biological movements performed by someone else has recently been used extensively for brain-computer interface-based applications, such as applications used in stroke rehabilitation training and motor skill learning. However, the ERD responses induced by the movement imagery and observation might not be as reliable as the ERD responses induced by movement execution. Given that studies on the reliability of the EEG ERD responses induced by these activities are still lacking, here we conducted an EEG experiment with movement imagery, movement observation, and movement execution, performed multiple times each in a pseudorandomized order in the same experimental runs. Then, independent component analysis (ICA) was applied to the EEG data to find the common motor-related EEG source activity shared by the three motor tasks. Finally, conditional EEG ERD responses associated with the three movement conditions were computed and compared. Among the three motor conditions, the EEG ERD responses induced by motor execution revealed the alpha power suppression with highest strengths and longest durations. The ERD responses of the movement imagery and movement observation only partially resembled the ERD pattern of the movement execution condition, with slightly better detectability for the ERD responses associated with the movement imagery and faster ERD responses for movement observation. This may indicate different levels of involvement in the same motor-related brain circuits during different movement conditions. In addition, because the resulting conditional EEG ERD responses from the ICA preprocessing came with minimal contamination from the non-related and/or artifactual noisy components, this result can play a role of the reference for devising a brain-computer interface using the EEG ERD features of movement imagery or observation.

Structural lineament and pattern analysis of Missouri, using LANDSAT imagery

NASA Technical Reports Server (NTRS)

Martin, J. A.; Kisvarsanyi, G. (Principal Investigator)

1977-01-01

The author has identified the following significant results. Major linear, circular, and arcuate traces were observed on LANDSAT imagery of Missouri. Lineaments plotted within the state boundaries range from 20 to nearly 500 km in length. Several extend into adjoining states. Lineaments plots indicate a distinct pattern and in general reflect structural features of the Precambrian basement of the platform. Coincidence of lineaments traced from the imagery and known structural features in Missouri is high, thus supporting a causative relation between them. The lineament pattern apparently reveals a fundamental style of the deformation of the intracontinental craton. Dozens of heretofore unknown linear features related to epirogenic movements and deformation of this segment of the continental crust were delineated. Lineaments and mineralization are interrelated in a geometrically classifiable pattern.

Disentangling visual imagery and perception of real-world objects

PubMed Central

Lee, Sue-Hyun; Kravitz, Dwight J.; Baker, Chris I.

2011-01-01

During mental imagery, visual representations can be evoked in the absence of “bottom-up” sensory input. Prior studies have reported similar neural substrates for imagery and perception, but studies of brain-damaged patients have revealed a double dissociation with some patients showing preserved imagery in spite of impaired perception and others vice versa. Here, we used fMRI and multi-voxel pattern analysis to investigate the specificity, distribution, and similarity of information for individual seen and imagined objects to try and resolve this apparent contradiction. In an event-related design, participants either viewed or imagined individual named object images on which they had been trained prior to the scan. We found that the identity of both seen and imagined objects could be decoded from the pattern of activity throughout the ventral visual processing stream. Further, there was enough correspondence between imagery and perception to allow discrimination of individual imagined objects based on the response during perception. However, the distribution of object information across visual areas was strikingly different during imagery and perception. While there was an obvious posterior-anterior gradient along the ventral visual stream for seen objects, there was an opposite gradient for imagined objects. Moreover, the structure of representations (i.e. the pattern of similarity between responses to all objects) was more similar during imagery than perception in all regions along the visual stream. These results suggest that while imagery and perception have similar neural substrates, they involve different network dynamics, resolving the tension between previous imaging and neuropsychological studies. PMID:22040738

Remote sensing of physiographic soil units of Bennett County, South Dakota

NASA Technical Reports Server (NTRS)

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

1973-01-01

A study was conducted in Bennett County, South Dakota, to establish a rangeland test site for evaluating the usefulness of ERTS data for mapping soil resources in rangeland areas. Photographic imagery obtained in October, 1970, was analyzed to determine which type of imagery is best for mapping drainage and land use patterns. Imagery of scales ranging from 1:1,000,000 to 1.20,000 was used to delineate soil-vegetative physiographic units. The photo characteristics used to define physiographic units were texture, drainage pattern, tone pattern, land use pattern and tone. These units will be used as test data for evaluating ERTS data. The physiographic units were categorized into a land classification system. The various categories which were delineated at the different scales of imagery were designed to be useful for different levels of land use planning. The land systems are adequate only for planning of large areas for general uses. The lowest category separated was the facet. The facets have a definite soil composition and represent different soil landscapes. These units are thought to be useful for providing natural resource information needed for local planning.

Estimating spatially distributed turbulent heat fluxes from high-resolution thermal imagery acquired with a UAV system

PubMed Central

Brenner, Claire; Thiem, Christina Elisabeth; Wizemann, Hans-Dieter; Bernhardt, Matthias; Schulz, Karsten

2017-01-01

ABSTRACT In this study, high-resolution thermal imagery acquired with a small unmanned aerial vehicle (UAV) is used to map evapotranspiration (ET) at a grassland site in Luxembourg. The land surface temperature (LST) information from the thermal imagery is the key input to a one-source and two-source energy balance model. While the one-source model treats the surface as a single uniform layer, the two-source model partitions the surface temperature and fluxes into soil and vegetation components. It thus explicitly accounts for the different contributions of both components to surface temperature as well as turbulent flux exchange with the atmosphere. Contrary to the two-source model, the one-source model requires an empirical adjustment parameter in order to account for the effect of the two components. Turbulent heat flux estimates of both modelling approaches are compared to eddy covariance (EC) measurements using the high-resolution input imagery UAVs provide. In this comparison, the effect of different methods for energy balance closure of the EC data on the agreement between modelled and measured fluxes is also analysed. Additionally, the sensitivity of the one-source model to the derivation of the empirical adjustment parameter is tested. Due to the very dry and hot conditions during the experiment, pronounced thermal patterns developed over the grassland site. These patterns result in spatially variable turbulent heat fluxes. The model comparison indicates that both models are able to derive ET estimates that compare well with EC measurements under these conditions. However, the two-source model, with a more complex treatment of the energy and surface temperature partitioning between the soil and vegetation, outperformed the simpler one-source model in estimating sensible and latent heat fluxes. This is consistent with findings from prior studies. For the one-source model, a time-variant expression of the adjustment parameter (to account for the difference between aerodynamic and radiometric temperature) that depends on the surface-to-air temperature gradient yielded the best agreement with EC measurements. This study showed that the applied UAV system equipped with a dual-camera set-up allows for the acquisition of thermal imagery with high spatial and temporal resolution that illustrates the small-scale heterogeneity of thermal surface properties. The UAV-based thermal imagery therefore provides the means for analysing patterns of LST and other surface properties with a high level of detail that cannot be obtained by traditional remote sensing methods. PMID:28515537

Estimating spatially distributed turbulent heat fluxes from high-resolution thermal imagery acquired with a UAV system.

PubMed

Brenner, Claire; Thiem, Christina Elisabeth; Wizemann, Hans-Dieter; Bernhardt, Matthias; Schulz, Karsten

2017-05-19

In this study, high-resolution thermal imagery acquired with a small unmanned aerial vehicle (UAV) is used to map evapotranspiration (ET) at a grassland site in Luxembourg. The land surface temperature (LST) information from the thermal imagery is the key input to a one-source and two-source energy balance model. While the one-source model treats the surface as a single uniform layer, the two-source model partitions the surface temperature and fluxes into soil and vegetation components. It thus explicitly accounts for the different contributions of both components to surface temperature as well as turbulent flux exchange with the atmosphere. Contrary to the two-source model, the one-source model requires an empirical adjustment parameter in order to account for the effect of the two components. Turbulent heat flux estimates of both modelling approaches are compared to eddy covariance (EC) measurements using the high-resolution input imagery UAVs provide. In this comparison, the effect of different methods for energy balance closure of the EC data on the agreement between modelled and measured fluxes is also analysed. Additionally, the sensitivity of the one-source model to the derivation of the empirical adjustment parameter is tested. Due to the very dry and hot conditions during the experiment, pronounced thermal patterns developed over the grassland site. These patterns result in spatially variable turbulent heat fluxes. The model comparison indicates that both models are able to derive ET estimates that compare well with EC measurements under these conditions. However, the two-source model, with a more complex treatment of the energy and surface temperature partitioning between the soil and vegetation, outperformed the simpler one-source model in estimating sensible and latent heat fluxes. This is consistent with findings from prior studies. For the one-source model, a time-variant expression of the adjustment parameter (to account for the difference between aerodynamic and radiometric temperature) that depends on the surface-to-air temperature gradient yielded the best agreement with EC measurements. This study showed that the applied UAV system equipped with a dual-camera set-up allows for the acquisition of thermal imagery with high spatial and temporal resolution that illustrates the small-scale heterogeneity of thermal surface properties. The UAV-based thermal imagery therefore provides the means for analysing patterns of LST and other surface properties with a high level of detail that cannot be obtained by traditional remote sensing methods.

Application of LANDSAT and Skylab data for land use mapping in Italy. [emphasizing the Alps Mountains

NASA Technical Reports Server (NTRS)

Bodechtel, J.; Nithack, J.; Dibernardo, G.; Hiller, K.; Jaskolla, F.; Smolka, A.

1975-01-01

Utilizing LANDSAT and Skylab multispectral imagery of 1972 and 1973, a land use map of the mountainous regions of Italy was evaluated at a scale of 1:250,000. Seven level I categories were identified by conventional methods of photointerpretation. Images of multispectral scanner (MSS) bands 5 and 7, or equivalents were mainly used. Areas of less than 200 by 200 m were classified and standard procedures were established for interpretation of multispectral satellite imagery. Land use maps were produced for central and southern Europe indicating that the existing land use maps could be updated and optimized. The complexity of European land use patterns, the intensive morphology of young mountain ranges, and time-cost calculations are the reasons that the applied conventional techniques are superior to automatic evaluation.

Arctic and subarctic environmental analyses utilizing ERTS-1 imagery. [permafrost sediment transport, snow cover, ice conditions, and water runoff in Alaska

NASA Technical Reports Server (NTRS)

Anderson, D. M.; Mckim, H. L.; Haugen, R. K.; Gatto, L. W.; Slaughter, C. W.; Marlar, T. L. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Physiognomic landscape features were used as geologic and vegetative indicators in preparation of a surficial geology, vegetation, and permafrost map at a scale of 1:1 million using ERTS-1 band 7 imagery. The detail from this map compared favorably with USGS maps at 1:250,000 scale. Physical boundaries mapped from ERTS-1 imagery in combination with ground truth obtained from existing small maps and other sources resulted in improved and more detailed maps of permafrost terrain and vegetation for the same area. ERTS-1 imagery provides for the first time, a means of monitoring the following regional estuarine processes: daily and periodic surface water circulation patterns; changes in the relative sediment load of rivers discharging into the inlet; and, several local patterns not recognized before, such as a clockwise back eddy offshore from Clam Gulch and a counterclockwise current north of the Forelands. Comparison of ERTS-1 and Mariner imagery has revealed that the thermokarst depressions found on the Alaskan North Slope and polygonal patterns on the Yukon River Delta are possible analogs to some Martian terrain features.

A Real-Time High Performance Computation Architecture for Multiple Moving Target Tracking Based on Wide-Area Motion Imagery via Cloud and Graphic Processing Units

PubMed Central

Liu, Kui; Wei, Sixiao; Chen, Zhijiang; Jia, Bin; Chen, Genshe; Ling, Haibin; Sheaff, Carolyn; Blasch, Erik

2017-01-01

This paper presents the first attempt at combining Cloud with Graphic Processing Units (GPUs) in a complementary manner within the framework of a real-time high performance computation architecture for the application of detecting and tracking multiple moving targets based on Wide Area Motion Imagery (WAMI). More specifically, the GPU and Cloud Moving Target Tracking (GC-MTT) system applied a front-end web based server to perform the interaction with Hadoop and highly parallelized computation functions based on the Compute Unified Device Architecture (CUDA©). The introduced multiple moving target detection and tracking method can be extended to other applications such as pedestrian tracking, group tracking, and Patterns of Life (PoL) analysis. The cloud and GPUs based computing provides an efficient real-time target recognition and tracking approach as compared to methods when the work flow is applied using only central processing units (CPUs). The simultaneous tracking and recognition results demonstrate that a GC-MTT based approach provides drastically improved tracking with low frame rates over realistic conditions. PMID:28208684

A Real-Time High Performance Computation Architecture for Multiple Moving Target Tracking Based on Wide-Area Motion Imagery via Cloud and Graphic Processing Units.

PubMed

Liu, Kui; Wei, Sixiao; Chen, Zhijiang; Jia, Bin; Chen, Genshe; Ling, Haibin; Sheaff, Carolyn; Blasch, Erik

2017-02-12

This paper presents the first attempt at combining Cloud with Graphic Processing Units (GPUs) in a complementary manner within the framework of a real-time high performance computation architecture for the application of detecting and tracking multiple moving targets based on Wide Area Motion Imagery (WAMI). More specifically, the GPU and Cloud Moving Target Tracking (GC-MTT) system applied a front-end web based server to perform the interaction with Hadoop and highly parallelized computation functions based on the Compute Unified Device Architecture (CUDA©). The introduced multiple moving target detection and tracking method can be extended to other applications such as pedestrian tracking, group tracking, and Patterns of Life (PoL) analysis. The cloud and GPUs based computing provides an efficient real-time target recognition and tracking approach as compared to methods when the work flow is applied using only central processing units (CPUs). The simultaneous tracking and recognition results demonstrate that a GC-MTT based approach provides drastically improved tracking with low frame rates over realistic conditions.

Remote sensing in Iowa agriculture: Identification and classification of Iowa's crops, soils and forestry resources using ERTS-1 and complimentary underflight imagery

NASA Technical Reports Server (NTRS)

Mahlstede, J. P. (Principal Investigator); Carlson, R. E.; Fenton, T. E.; Thomson, G. W.

1974-01-01

The author has identified the following significant results. Springtime ERTS-1 imagery covering pre-selected test sites in Iowa showed considerable detail with respect to broad soil and land use patterns. Additional imagery has been incorporated into a state mosaic. The mosaic was used as a base for soil association lines transferred from an existing map. The regions of greatest contrast are between the Clarion-Nicollet-Webster soil association area and adjacent areas. Landscape characteristics in this area result in land use patterns with a high percentage of pasture, hay, and timber. The soil association areas of the state that have patterns interpreted to be associated with intensive row crop production are: Moody, Galva-Primghar-Sac, Clarion-Nicollet-Webter, Tama-Muscatine, Dinsdale-Tama, Cresco-Lourdes, Clyde, Kenyon-Floyd-Clyde, and the Luton-Onawa-Salix area on the Missouri River floodplain. Forestland estimates have been attained for an area in central Iowa using wintertime ERTS-1 imagery. Visual analysis of multispectral, temporal imagery indicates that temporal analysis for cropland identification and acreage analyses procedures may be a very useful tool. Combinations of wintertime, springtime, and summertime ERTS-1 imagery separate most vegetation types. Timing can be critical depending upon crop development and harvesting times because of the dynamic nature of agricultural production.

Automated Identification of River Hydromorphological Features Using UAV High Resolution Aerial Imagery.

PubMed

Casado, Monica Rivas; Gonzalez, Rocio Ballesteros; Kriechbaumer, Thomas; Veal, Amanda

2015-11-04

European legislation is driving the development of methods for river ecosystem protection in light of concerns over water quality and ecology. Key to their success is the accurate and rapid characterisation of physical features (i.e., hydromorphology) along the river. Image pattern recognition techniques have been successfully used for this purpose. The reliability of the methodology depends on both the quality of the aerial imagery and the pattern recognition technique used. Recent studies have proved the potential of Unmanned Aerial Vehicles (UAVs) to increase the quality of the imagery by capturing high resolution photography. Similarly, Artificial Neural Networks (ANN) have been shown to be a high precision tool for automated recognition of environmental patterns. This paper presents a UAV based framework for the identification of hydromorphological features from high resolution RGB aerial imagery using a novel classification technique based on ANNs. The framework is developed for a 1.4 km river reach along the river Dee in Wales, United Kingdom. For this purpose, a Falcon 8 octocopter was used to gather 2.5 cm resolution imagery. The results show that the accuracy of the framework is above 81%, performing particularly well at recognising vegetation. These results leverage the use of UAVs for environmental policy implementation and demonstrate the potential of ANNs and RGB imagery for high precision river monitoring and river management.

Computer mapping of turbidity and circulation patterns in Saginaw Bay, Michigan from LANDSAT data

NASA Technical Reports Server (NTRS)

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

1975-01-01

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

Proposal to evaluate the use of ERTS-A imagery in mapping and managing soil and range resources in the Sand Hills Region of Nebraska

NASA Technical Reports Server (NTRS)

Drew, J. V. (Principal Investigator)

1972-01-01

The author has identified the following significant results. Visual examination of RB-57F color infrared imagery of range sites within Test Site 313 indicates that early season imagery will show significant differences in appearance of sub-irrigated sites as compared to dry valley sites. Differences appear to be significant also when comparing the previous two sites to sands sites. Comparison of existing soil map soils delineations with vegetative growth patterns shows reasonably good agreement between the two patterns over rather broad areas. Visual examination of ERTS-1 imagery has also shown that rangeland burned by prairie fire within the last six months can be distinguished. Three confirmed fire areas have been shown on the imagery. Since only broad estimates of burned acres are available, more accurate acreage measurements will be attempted. Known acreage of burned areas will be of value to those agencies responsible for deferred grazing payments to land owners. The relative speed with which this acreage information would become available to these agencies through ERTS-1 imagery would be of much benefit.

Using QuickBird imagery to detect cover and spread of post-fire straw mulch after the 2006 Tripod Fire, Washington, USA

Treesearch

Sarah A. Lewis; Peter R. Robichaud

2011-01-01

Agricultural straw mulch is a commonly applied treatment for protecting resources at risk from runoff and erosion events after wildfires. High-resolution QuickBird satellite imagery was acquired after straw mulch was applied on the 2006 Tripod Fire in Washington. We tested whether the imagery was suitable for remotely assessing the areal coverage of the straw mulch...

An improved discriminative filter bank selection approach for motor imagery EEG signal classification using mutual information.

PubMed

Kumar, Shiu; Sharma, Alok; Tsunoda, Tatsuhiko

2017-12-28

Common spatial pattern (CSP) has been an effective technique for feature extraction in electroencephalography (EEG) based brain computer interfaces (BCIs). However, motor imagery EEG signal feature extraction using CSP generally depends on the selection of the frequency bands to a great extent. In this study, we propose a mutual information based frequency band selection approach. The idea of the proposed method is to utilize the information from all the available channels for effectively selecting the most discriminative filter banks. CSP features are extracted from multiple overlapping sub-bands. An additional sub-band has been introduced that cover the wide frequency band (7-30 Hz) and two different types of features are extracted using CSP and common spatio-spectral pattern techniques, respectively. Mutual information is then computed from the extracted features of each of these bands and the top filter banks are selected for further processing. Linear discriminant analysis is applied to the features extracted from each of the filter banks. The scores are fused together, and classification is done using support vector machine. The proposed method is evaluated using BCI Competition III dataset IVa, BCI Competition IV dataset I and BCI Competition IV dataset IIb, and it outperformed all other competing methods achieving the lowest misclassification rate and the highest kappa coefficient on all three datasets. Introducing a wide sub-band and using mutual information for selecting the most discriminative sub-bands, the proposed method shows improvement in motor imagery EEG signal classification.

Principal component greenness transformation in multitemporal agricultural Landsat data

NASA Technical Reports Server (NTRS)

Abotteen, R. A.

1978-01-01

A data compression technique for multitemporal Landsat imagery which extracts phenological growth pattern information for agricultural crops is described. The principal component greenness transformation was applied to multitemporal agricultural Landsat data for information retrieval. The transformation was favorable for applications in agricultural Landsat data analysis because of its physical interpretability and its relation to the phenological growth of crops. It was also found that the first and second greenness eigenvector components define a temporal small-grain trajectory and nonsmall-grain trajectory, respectively.

A Psychosynthesis Approach to the Use of Mental Imagery with Adult Survivors of Childhood Sexual Abuse.

ERIC Educational Resources Information Center

Brown, Michael H.

1997-01-01

States that the techniques of mental imagery can help adult survivors of childhood sexual abuse access the inner wisdom necessary to identify, understand, and creatively address issues from the past and develop new and healthier patterns of thinking and behaving. Documents the innovative ways psychosynthesis uses mental imagery with this client…

Dual Use of Image Based Tracking Techniques: Laser Eye Surgery and Low Vision Prosthesis

NASA Technical Reports Server (NTRS)

Juday, Richard D.; Barton, R. Shane

1994-01-01

With a concentration on Fourier optics pattern recognition, we have developed several methods of tracking objects in dynamic imagery to automate certain space applications such as orbital rendezvous and spacecraft capture, or planetary landing. We are developing two of these techniques for Earth applications in real-time medical image processing. The first is warping of a video image, developed to evoke shift invariance to scale and rotation in correlation pattern recognition. The technology is being applied to compensation for certain field defects in low vision humans. The second is using the optical joint Fourier transform to track the translation of unmodeled scenes. Developed as an image fixation tool to assist in calculating shape from motion, it is being applied to tracking motions of the eyeball quickly enough to keep a laser photocoagulation spot fixed on the retina, thus avoiding collateral damage.

Dual use of image based tracking techniques: Laser eye surgery and low vision prosthesis

NASA Technical Reports Server (NTRS)

Juday, Richard D.

1994-01-01

With a concentration on Fourier optics pattern recognition, we have developed several methods of tracking objects in dynamic imagery to automate certain space applications such as orbital rendezvous and spacecraft capture, or planetary landing. We are developing two of these techniques for Earth applications in real-time medical image processing. The first is warping of a video image, developed to evoke shift invariance to scale and rotation in correlation pattern recognition. The technology is being applied to compensation for certain field defects in low vision humans. The second is using the optical joint Fourier transform to track the translation of unmodeled scenes. Developed as an image fixation tool to assist in calculating shape from motion, it is being applied to tracking motions of the eyeball quickly enough to keep a laser photocoagulation spot fixed on the retina, thus avoiding collateral damage.

Open-source sea ice drift algorithm for Sentinel-1 SAR imagery using a combination of feature-tracking and pattern-matching

NASA Astrophysics Data System (ADS)

Muckenhuber, Stefan; Sandven, Stein

2017-04-01

An open-source sea ice drift algorithm for Sentinel-1 SAR imagery is introduced based on the combination of feature-tracking and pattern-matching. A computational efficient feature-tracking algorithm produces an initial drift estimate and limits the search area for the pattern-matching, that provides small to medium scale drift adjustments and normalised cross correlation values as quality measure. The algorithm is designed to utilise the respective advantages of the two approaches and allows drift calculation at user defined locations. The pre-processing of the Sentinel-1 data has been optimised to retrieve a feature distribution that depends less on SAR backscatter peak values. A recommended parameter set for the algorithm has been found using a representative image pair over Fram Strait and 350 manually derived drift vectors as validation. Applying the algorithm with this parameter setting, sea ice drift retrieval with a vector spacing of 8 km on Sentinel-1 images covering 400 km x 400 km, takes less than 3.5 minutes on a standard 2.7 GHz processor with 8 GB memory. For validation, buoy GPS data, collected in 2015 between 15th January and 22nd April and covering an area from 81° N to 83.5° N and 12° E to 27° E, have been compared to calculated drift results from 261 corresponding Sentinel-1 image pairs. We found a logarithmic distribution of the error with a peak at 300 m. All software requirements necessary for applying the presented sea ice drift algorithm are open-source to ensure free implementation and easy distribution.

Land utilization and ecological aspects in the Sylhet-Mymensingh Haor Region of Bangladesh: An analysis of LANDSAT data

NASA Technical Reports Server (NTRS)

Chowdhury, M. I.; Elahi, K. M.

1977-01-01

The use of remote sensing data from LANDSAT (ERTS) imageries in identifying, evaluating and mapping land use patterns of the Haor area in Bangladesh was investigated. Selected cloud free imageries of the area for the period 1972-75 were studied. Imageries in bands 4, 5 and 7 were mostly used. The method of analysis involved utilization of both human and computer services of information from ground, aerial photographs taken during this period and space imageries.

Identification of Anisomerous Motor Imagery EEG Signals Based on Complex Algorithms

PubMed Central

Zhang, Zhiwen; Duan, Feng; Zhou, Xin; Meng, Zixuan

2017-01-01

Motor imagery (MI) electroencephalograph (EEG) signals are widely applied in brain-computer interface (BCI). However, classified MI states are limited, and their classification accuracy rates are low because of the characteristics of nonlinearity and nonstationarity. This study proposes a novel MI pattern recognition system that is based on complex algorithms for classifying MI EEG signals. In electrooculogram (EOG) artifact preprocessing, band-pass filtering is performed to obtain the frequency band of MI-related signals, and then, canonical correlation analysis (CCA) combined with wavelet threshold denoising (WTD) is used for EOG artifact preprocessing. We propose a regularized common spatial pattern (R-CSP) algorithm for EEG feature extraction by incorporating the principle of generic learning. A new classifier combining the K-nearest neighbor (KNN) and support vector machine (SVM) approaches is used to classify four anisomerous states, namely, imaginary movements with the left hand, right foot, and right shoulder and the resting state. The highest classification accuracy rate is 92.5%, and the average classification accuracy rate is 87%. The proposed complex algorithm identification method can significantly improve the identification rate of the minority samples and the overall classification performance. PMID:28874909

Lateral variations in geologic structure and tectonic setting from remote sensing data

NASA Astrophysics Data System (ADS)

Alexander, S. S.

1983-05-01

The principal objective of this study was: (1) to assess the usefulness of remote sensing digital imagery, principally LANDSAT multispectral scanning (MSS) data, for inferring lateral variations in geologic structure and tectonic setting; and (2) to determine the extent to which these inferred variations correlate with observed variations in seismic excitation from underground nuclear explosion test sites in the Soviet Union. Soviet, French and U.S. test sites have been investigated to compare their geologic and tectonic responses as seen by LANDSAT. The characteristics of "granite' intrusive bodies exposed at Semipalatinsk (Degelen), North Africa (Hoggar), NTS (Climax stock), and an analog site in Maine (Mt. Katahdin), have been studied in detail. The tectonic stress field inferred from the tectonic release portion of seismic signatures of explosions in these three areas is compared with local and regional fracture patterns discernable from imagery. The usefulness of satellite synthetic aperture radar (SAR) to determine geologic conditions and delineate fault (fracture) patterns is demonstrated by the analysis of SEASAT data for an area in the eastern United States. Algorithms to enhance structural boundaries and to use textures to identify rock types were developed and applied to several test sites.

Combining self-organizing mapping and supervised affinity propagation clustering approach to investigate functional brain networks involved in motor imagery and execution with fMRI measurements.

PubMed

Zhang, Jiang; Liu, Qi; Chen, Huafu; Yuan, Zhen; Huang, Jin; Deng, Lihua; Lu, Fengmei; Zhang, Junpeng; Wang, Yuqing; Wang, Mingwen; Chen, Liangyin

2015-01-01

Clustering analysis methods have been widely applied to identifying the functional brain networks of a multitask paradigm. However, the previously used clustering analysis techniques are computationally expensive and thus impractical for clinical applications. In this study a novel method, called SOM-SAPC that combines self-organizing mapping (SOM) and supervised affinity propagation clustering (SAPC), is proposed and implemented to identify the motor execution (ME) and motor imagery (MI) networks. In SOM-SAPC, SOM was first performed to process fMRI data and SAPC is further utilized for clustering the patterns of functional networks. As a result, SOM-SAPC is able to significantly reduce the computational cost for brain network analysis. Simulation and clinical tests involving ME and MI were conducted based on SOM-SAPC, and the analysis results indicated that functional brain networks were clearly identified with different response patterns and reduced computational cost. In particular, three activation clusters were clearly revealed, which include parts of the visual, ME and MI functional networks. These findings validated that SOM-SAPC is an effective and robust method to analyze the fMRI data with multitasks.

Interpretation of geographic patterns in simulated orbital television imagery of earth resources

NASA Technical Reports Server (NTRS)

Latham, J. P.; Cross, C. I.; Kuyper, W. H.; Witmer, R. E.

1972-01-01

In order to better determine the effects of the television imagery characteristics upon the interpretation of geographic patterns obtainable from orbital television sensors, and in order to better evaluate the influences of alternative sensor system parameters such as changes in orbital altitudes or scan line rates, a team of three professional interpreters independently mapped thematically the selected geographic phenomena that they could detect in orbital television imagery produced on a fourteen inch monitor and recorded photographically for analysis. Three thematic maps were compiled by each interpreter. The maps were: (1) transportation patterns; (2) other land use; and (3) physical regions. The results from the three interpreters are compared, agreements noted, and differences analyzed for cause such as disagreement on identification of phenomenon, visual acuity, differences in interpretation techniques, and differing professional backgrounds.

Training Visual Imagery: Improvements of Metacognition, but not Imagery Strength

PubMed Central

Rademaker, Rosanne L.; Pearson, Joel

2012-01-01

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 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 2 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. PMID:22787452

Improving surface-subsurface water budgeting using high resolution satellite imagery applied on a brownfield.

PubMed

Dujardin, J; Batelaan, O; Canters, F; Boel, S; Anibas, C; Bronders, J

2011-01-15

The estimation of surface-subsurface water interactions is complex and highly variable in space and time. It is even more complex when it has to be estimated in urban areas, because of the complex patterns of the land-cover in these areas. In this research a modeling approach with integrated remote sensing analysis has been developed for estimating water fluxes in urban environments. The methodology was developed with the aim to simulate fluxes of contaminants from polluted sites. Groundwater pollution in urban environments is linked to patterns of land use and hence it is essential to characterize the land cover in a detail. An object-oriented classification approach applied on high-resolution satellite data has been adopted. To assign the image objects to one of the land-cover classes a multiple layer perceptron approach was adopted (Kappa of 0.86). Groundwater recharge has been simulated using the spatially distributed WetSpass model and the subsurface water flow using MODFLOW in order to identify and budget water fluxes. The developed methodology is applied to a brownfield case site in Vilvoorde, Brussels (Belgium). The obtained land use map has a strong impact on the groundwater recharge, resulting in a high spatial variability. Simulated groundwater fluxes from brownfield to the receiving River Zenne were independently verified by measurements and simulation of groundwater-surface water interaction based on thermal gradients in the river bed. It is concluded that in order to better quantify total fluxes of contaminants from brownfields in the groundwater, remote sensing imagery can be operationally integrated in a modeling procedure. Copyright © 2010 Elsevier B.V. All rights reserved.

Mental Imagery: Functional Mechanisms and Clinical Applications

PubMed Central

Pearson, Joel; Naselaris, Thomas; Holmes, Emily A.; Kosslyn, Stephen M.

2015-01-01

Mental imagery research has weathered both disbelief of the phenomenon and inherent methodological limitations. Here we review recent behavioral, brain imaging, and clinical research that has reshaped our understanding of mental imagery. Research supports the claim that visual mental imagery is a depictive internal representation that functions like a weak form of perception. Brain imaging work has demonstrated that neural representations of mental and perceptual images resemble one another as early as the primary visual cortex (V1). Activity patterns in V1 encode mental images and perceptual images via a common set of low-level depictive visual features. Recent translational and clinical research reveals the pivotal role that imagery plays in many mental disorders and suggests how clinicians can utilize imagery in treatment. PMID:26412097

Geomorphic analyses from space imagery

NASA Technical Reports Server (NTRS)

Morisawa, M.

1985-01-01

One of the most obvious applications of space imagery to geomorphological analyses is in the study of drainage patterns and channel networks. LANDSAT, high altitude photography and other types of remote sensing imagery are excellent for depicting stream networks on a regional scale because of their broad coverage in a single image. They offer a valuable tool for comparing and analyzing drainage patterns and channel networks all over the world. Three aspects considered in this geomorphological study are: (1) the origin, evolution and rates of development of drainage systems; (2) the topological studies of network and channel arrangements; and (3) the adjustment of streams to tectonic events and geologic structure (i.e., the mode and rate of adjustment).

Application of ERTS imagery to environmental studies of Lake Champlain

NASA Technical Reports Server (NTRS)

Lind, A. O.

1974-01-01

ERTS Imagery has provided data relating to a number of environmental and limnological concerns such as water quality, lake flooding and lake ice formation. Pollution plume data provided by ERTS was recently used in the Supreme Court case involving the States of Vermont and New York and a paper company. Flooding of lowland tracts has been a major concern due to a repetitive pattern of high lake levels over the past three years, and ERTS imagery is being used to construct the first series of flood maps of the affected areas. Lake ice development and turbidity patterns have also been studied from ERTS, since these have significance for shore erosion studies.

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

NASA Technical Reports Server (NTRS)

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.

Filter Bank Regularized Common Spatial Pattern Ensemble for Small Sample Motor Imagery Classification.

PubMed

Park, Sang-Hoon; Lee, David; Lee, Sang-Goog

2018-02-01

For the last few years, many feature extraction methods have been proposed based on biological signals. Among these, the brain signals have the advantage that they can be obtained, even by people with peripheral nervous system damage. Motor imagery electroencephalograms (EEG) are inexpensive to measure, offer a high temporal resolution, and are intuitive. Therefore, these have received a significant amount of attention in various fields, including signal processing, cognitive science, and medicine. The common spatial pattern (CSP) algorithm is a useful method for feature extraction from motor imagery EEG. However, performance degradation occurs in a small-sample setting (SSS), because the CSP depends on sample-based covariance. Since the active frequency range is different for each subject, it is also inconvenient to set the frequency range to be different every time. In this paper, we propose the feature extraction method based on a filter bank to solve these problems. The proposed method consists of five steps. First, motor imagery EEG is divided by a using filter bank. Second, the regularized CSP (R-CSP) is applied to the divided EEG. Third, we select the features according to mutual information based on the individual feature algorithm. Fourth, parameter sets are selected for the ensemble. Finally, we classify using ensemble based on features. The brain-computer interface competition III data set IVa is used to evaluate the performance of the proposed method. The proposed method improves the mean classification accuracy by 12.34%, 11.57%, 9%, 4.95%, and 4.47% compared with CSP, SR-CSP, R-CSP, filter bank CSP (FBCSP), and SR-FBCSP. Compared with the filter bank R-CSP ( , ), which is a parameter selection version of the proposed method, the classification accuracy is improved by 3.49%. In particular, the proposed method shows a large improvement in performance in the SSS.

Frequency Analysis of Modis Ndvi Time Series for Determining Hotspot of Land Degradation in Mongolia

NASA Astrophysics Data System (ADS)

Nasanbat, E.; Sharav, S.; Sanjaa, T.; Lkhamjav, O.; Magsar, E.; Tuvdendorj, B.

2018-04-01

This study examines MODIS NDVI satellite imagery time series can be used to determine hotspot of land degradation area in whole Mongolia. The trend statistical analysis of Mann-Kendall was applied to a 16-year MODIS NDVI satellite imagery record, based on 16-day composited temporal data (from May to September) for growing seasons and from 2000 to 2016. We performed to frequency analysis that resulting NDVI residual trend pattern would enable successful determined of negative and positive changes in photo synthetically health vegetation. Our result showed that negative and positive values and generated a map of significant trends. Also, we examined long-term of meteorological parameters for the same period. The result showed positive and negative NDVI trends concurred with land cover types change representing an improve or a degrade in vegetation, respectively. Also, integrated the climate parameters which were precipitation and air temperature changes in the same time period seem to have had an affecting on huge NDVI trend area. The time series trend analysis approach applied successfully determined hotspot of an improvement and a degraded area due to land degradation and desertification.

Water color and circulation southern Chesapeake Bay, part 1

NASA Technical Reports Server (NTRS)

Nichols, M. M.; Gordon, H. H.

1975-01-01

Satellite imagery from two EREP passes over the Rappahannock Estuary of the Chesapeake region is analyzed to chart colored water types, to delineate color boundaries and define circulatory patterns. Surface observations from boats and helicopters concurrent with Skylab overpass define the distributions of suspended sediment, transparency, temperature, salinity, phytoplankton, color of suspended material and optical ratio. Important features recorded by the imagery are a large-scale turbidity maximum and massive red tide blooms. Water movement is revealed by small-scale mixing patterns and tidal plumes of apparent sediment-laden water. The color patterns broadly reflect the bottom topography and the seaward gradient of suspended material between the river and the bay. Analyses of red, green and natural color photos by microdensitometry demonstrate the utility of charting water color types of potential use for managing estuarine water quality. The Skylab imagery is superior to aerial photography and surface observations for charting water color.

Forestry, geology and hydrological investigations from ERTS-1 imagery in two areas of Ecuador, South America

NASA Technical Reports Server (NTRS)

Moreno, N. V. (Principal Investigator)

1973-01-01

The author has identified the following significant results. In the Oriente area, well-drained forests containing commercially valuable hardwoods can be recognized confidently and delineated quickly on the ERTS imagery. In the tropical rainforest, ERTS can provide an abundance of inferential information about large scale geologic structures. ERTS imagery is better than normal aerial photography for recognizing linears. The imagery is particularly useful for updating maps of the distributary system of the Guagas River Basin and of any other river with a similarly rapid changing channel pattern.

Application of ERTS-1 imagery in the Vermont-New York dispute over pollution of Lake Champlain

NASA Technical Reports Server (NTRS)

Lind, A. O. (Principal Investigator)

1973-01-01

The author has identified the following significant results. ERTS-1 imagery and a composite map derived from ERTS-1 imagery were presented as evidence in a U.S. Supreme Court case involving the pollution of an interstate water body (Lake Champlain). A pollution problem generated by a large paper mill forms the basis of the suit (Vermont vs. International Paper Co. and State of New York) and ERTS-1 imagery shows the effluent pattern on the lake surface as extending into Vermont during three different times.

Imagery Rescripting for Personality Disorders

ERIC Educational Resources Information Center

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…

Evaluation of terrestrial photogrammetric point clouds derived from thermal imagery

NASA Astrophysics Data System (ADS)

Metcalf, Jeremy P.; Olsen, Richard C.

2016-05-01

Computer vision and photogrammetric techniques have been widely applied to digital imagery producing high density 3D point clouds. Using thermal imagery as input, the same techniques can be applied to infrared data to produce point clouds in 3D space, providing surface temperature information. The work presented here is an evaluation of the accuracy of 3D reconstruction of point clouds produced using thermal imagery. An urban scene was imaged over an area at the Naval Postgraduate School, Monterey, CA, viewing from above as with an airborne system. Terrestrial thermal and RGB imagery were collected from a rooftop overlooking the site using a FLIR SC8200 MWIR camera and a Canon T1i DSLR. In order to spatially align each dataset, ground control points were placed throughout the study area using Trimble R10 GNSS receivers operating in RTK mode. Each image dataset is processed to produce a dense point cloud for 3D evaluation.

ERTS-1 imagery use in reconnaissance prospecting: Evaluation of commercial utility of ERTS-1 imagery in structural reconnaissance for minerals and petroleum

NASA Technical Reports Server (NTRS)

Saunders, D. F.; Thomas, G. E. (Principal Investigator); Kinsman, F. E.; Beatty, D. F.

1973-01-01

The author has identified the following significant results. This study was performed to investigate applications of ERTS-1 imagery in commercial reconnaissance for mineral and hydrocarbon resources. ERTS-1 imagery collected over five areas in North America (Montana; Colorado; New Mexico-West Texas; Superior Province, Canada; and North Slope, Alaska) has been analyzed for data content including linears, lineaments, and curvilinear anomalies. Locations of these features were mapped and compared with known locations of mineral and hydrocarbon accumulations. Results were analyzed in the context of a simple-shear, block-coupling model. Data analyses have resulted in detection of new lineaments, some of which may be continental in extent, detection of many curvilinear patterns not generally seen on aerial photos, strong evidence of continental regmatic fracture patterns, and realization that geological features can be explained in terms of a simple-shear, block-coupling model. The conculsions are that ERTS-1 imagery is of great value in photogeologic/geomorphic interpretations of regional features, and the simple-shear, block-coupling model provides a means of relating data from ERTS imagery to structures that have controlled emplacement of ore deposits and hydrocarbon accumulations, thus providing a basis for a new approach for reconnaissance for mineral, uranium, gas, and oil deposits and structures.

Estimating wetland vegetation abundance from Landsat-8 operational land imager imagery: a comparison between linear spectral mixture analysis and multinomial logit modeling methods

NASA Astrophysics Data System (ADS)

Zhang, Min; Gong, Zhaoning; Zhao, Wenji; Pu, Ruiliang; Liu, Ke

2016-01-01

Mapping vegetation abundance by using remote sensing data is an efficient means for detecting changes of an eco-environment. With Landsat-8 operational land imager (OLI) imagery acquired on July 31, 2013, both linear spectral mixture analysis (LSMA) and multinomial logit model (MNLM) methods were applied to estimate and assess the vegetation abundance in the Wild Duck Lake Wetland in Beijing, China. To improve mapping vegetation abundance and increase the number of endmembers in spectral mixture analysis, normalized difference vegetation index was extracted from OLI imagery along with the seven reflective bands of OLI data for estimating the vegetation abundance. Five endmembers were selected, which include terrestrial plants, aquatic plants, bare soil, high albedo, and low albedo. The vegetation abundance mapping results from Landsat OLI data were finally evaluated by utilizing a WorldView-2 multispectral imagery. Similar spatial patterns of vegetation abundance produced by both fully constrained LSMA algorithm and MNLM methods were observed: higher vegetation abundance levels were distributed in agricultural and riparian areas while lower levels in urban/built-up areas. The experimental results also indicate that the MNLM model outperformed the LSMA algorithm with smaller root mean square error (0.0152 versus 0.0252) and higher coefficient of determination (0.7856 versus 0.7214) as the MNLM model could handle the nonlinear reflection phenomenon better than the LSMA with mixed pixels.

Does touch inhibit visual imagery? A case study on acquired blindness.

PubMed

von Trott Zu Solz, Jana; Paolini, Marco; Silveira, Sarita

2017-06-01

In a single-case study of acquired blindness, differential brain activation patterns for visual imagery of familiar objects with and without tactile exploration as well as of tactilely explored unfamiliar objects were observed. Results provide new insight into retrieval of visual images from episodic memory and point toward a potential tactile inhibition of visual imagery. © 2017 The Institute of Psychology, Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.

Fault pattern at the northern end of the Death Valley - Furnace Creek fault zone, California and Nevada

NASA Technical Reports Server (NTRS)

Liggett, M. A. (Principal Investigator); Childs, J. F.

1974-01-01

The author has identified the following significant results. The pattern of faulting associated with the termination of the Death Valley-Furnace Creek Fault Zone in northern Fish Lake Valley, Nevada was studied in ERTS-1 MSS color composite imagery and color IR U-2 photography. Imagery analysis was supported by field reconnaissance and low altitude aerial photography. The northwest-trending right-lateral Death Valley-Furnace Creek Fault Zone changes northward to a complex pattern of discontinuous dip slip and strike slip faults. This fault pattern terminates to the north against an east-northeast trending zone herein called the Montgomery Fault Zone. No evidence for continuation of the Death Valley-Furnace Creek Fault Zone is recognized north of the Montgomery Fault Zone. Penecontemporaneous displacement in the Death Valley-Furnace Creek Fault Zone, the complex transitional zone, and the Montgomery Fault Zone suggests that the systems are genetically related. Mercury mineralization appears to have been localized along faults recognizable in ERTS-1 imagery within the transitional zone and the Montgomery Fault Zone.

Atmospheric Correction of High-Spatial-Resolution Commercial Satellite Imagery Products Using MODIS Atmospheric Products

NASA Technical Reports Server (NTRS)

Pagnutti, Mary; Holekamp, Kara; Ryan, Robert E.; Vaughan, Ronand; Russell, Jeff; Prados, Don; Stanley, Thomas

2005-01-01

Remotely sensed ground reflectance is the foundation of any interoperability or change detection technique. Satellite intercomparisons and accurate vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), require the generation of accurate reflectance maps (NDVI is used to describe or infer a wide variety of biophysical parameters and is defined in terms of near-infrared (NIR) and red band reflectances). Accurate reflectance-map generation from satellite imagery relies on the removal of solar and satellite geometry and of atmospheric effects and is generally referred to as atmospheric correction. Atmospheric correction of remotely sensed imagery to ground reflectance has been widely applied to a few systems only. The ability to obtain atmospherically corrected imagery and products from various satellites is essential to enable widescale use of remotely sensed, multitemporal imagery for a variety of applications. An atmospheric correction approach derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) that can be applied to high-spatial-resolution satellite imagery under many conditions was evaluated to demonstrate a reliable, effective reflectance map generation method. Additional information is included in the original extended abstract.

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

NASA Astrophysics Data System (ADS)

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 imagery with potential for the implementation of multiclass (3) BCIs. Our results are consistent with the notion that frontal alpha synchronization is related with high internal processing demands, changing with the number of alternation levels during imagery. Together, these findings suggest the feasibility of pure visual motion imagery tasks as a strategy to achieve multiclass control systems with potential for BCI and in particular, neurofeedback applications in non-motor (attentional) disorders.

Analysis of GOES imagery and digitized data for the SEV-UPS period, August 1979

NASA Technical Reports Server (NTRS)

Bowley, C. J.; Burke, H. H. K.; Barnes, J. C.

1981-01-01

In support of the Southeastern Virginia Urban Plume Study (SEV-UPS), GOES satellite imagery was analyzed for the month of August 1979. The analyzed GOES images provide an additional source of meteorological input useful in the evaluation of air quality data collected during the month long period of the SEV-UPS experiment. In addition to the imagery analysis, GOES digitized data were analyzed for the period of August 6 to 11, during which a regional haze pattern was detectable in the imagery. The results of the study indicate that the observed haze patterns correspond closely with areas shown in surface based measurements to have reduced visibilities and elevated pollution levels. Moreover, the results of the analysis of digitized data indicate that digital reflectance counts can be directly related to haze intensity both over land and ocean. The model results agree closely with the observed GOES digital reflectance counts, providing further indication that satellite remote sensing can be a useful tool for monitoring regional elevated pollution episodes.

Detection, mapping and estimation of rate of spread of grass fires from southern African ERTS-1 imagery

NASA Technical Reports Server (NTRS)

Wightman, J. M.

1973-01-01

Sequential band-6 imagery of the Zambesi Basin of southern Africa recorded substantial changes in burn patterns resulting from late dry season grass fires. One example from northern Botswana, indicates that a fire consumed approximately 70 square miles of grassland over a 24-hour period. Another example from western Zambia indicates increased fire activity over a 19-day period. Other examples clearly define the area of widespread grass fires in Angola, Botswana, Rhodesia and Zambia. From the fire patterns visible on the sequential portions of the imagery, and the time intervals involved, the rates of spread of the fires are estimated and compared with estimates derived from experimental burning plots in Zambia and Canada. It is concluded that sequential ERTS-1 imagery, of the quality studied, clearly provides the information needed to detect and map grass fires and to monitor their rates of spread in this region during the late dry season.

Utilization of LANDSAT orbital imagery in the soil survey processes at Rio Grande do Norte state

NASA Technical Reports Server (NTRS)

Formaggio, A. R. (Principal Investigator)

1984-01-01

Pedologic photointerpretative criteria adapted to LANDSAT orbital imagery were used: drainage (pattern, integration degree, density and uniformity degree); relief (pattern, dissection degree and crest lines); photographic texture, photographic tonnality, and the land use (type, glebas size and intensity of use). The performance of the imagery as an auxiliar tool in the soil survey processes, at Rio Grande do Norte State was evaluated. The drainage and relief elements were easily extracted from the imagery and also ones that provided the greatest deductive possibility about pedologic boundaries. Other analyzed criteria were considered only auxiliaries, corroborating some soil limits in the evidences convergence phase. The principal pedologic dominions of the 30,000 sq km are covered by the same LANDSAT image (WRS 359/16) were delimited with good precision: (1) fluvial plains, beaches, dunes and coastal mangroves; (2) North Coast line Plateau; (3) Acu Sandstone Zone; (4) residual plateaus of the Tertiary; and (6) plains of the embasement.

Comparative evaluation of ERTS imagery for resource inventory in land use planning

NASA Technical Reports Server (NTRS)

Simonson, G. H. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Numerous previously unmapped faults in central Oregon have been distinguished on ERTS-1 imagery. Tectonic mapping of fault-controlled linears demonstrates the utility of ERTS-1 imagery as a mean of illustrating and studying the regional tectonics of the state. Soil colors observed on ERTS-1 frame 1075-18150-5 at the eastern end of the Columbia basin correlate very well with those from descriptions of soils from that area. Digital output from frame 1021-18151 has shown the enhanced ability to interpret such features as joint patterns, shadowed landslide blocks, bottomlands, and drainage patterns. Widespread use of wheat-fallow rotation in northern Umatilla County, Oregon, insures that nearly one-half of the cultivated soil is devoid of vegetation much of the time. On ERTS-1 imagery, fallow fields are only slightly darker than fields of wheat stubble at the western end of the transect. Similar climate-related contrasts in soil color are visible on ERTS-1 Imagery from several other portions of the Columbia Basin. Absence of steep topography in the area mentioned, however, minimizes the disturbing effect caused by shadows.

Applying the Notion of Metaphor Types to Enhance Counseling Protocols

ERIC Educational Resources Information Center

Tay, Dennis

2012-01-01

This article introduces the notion of metaphor types to show how the more nuanced aspects of metaphor theory can be applied to counseling practice. The author suggests that metaphor types can enhance existing interview protocols designed to help clients expand the source domain imagery of their metaphors and "bridge back" the expanded imagery to…

Structure-from-motion approach for characterization of bioerosion patterns using UAV imagery.

PubMed

Genchi, Sibila A; Vitale, Alejandro J; Perillo, Gerardo M E; Delrieux, Claudio A

2015-02-04

The aim of this work is to evaluate the applicability of the 3D model obtained through Structure-from-Motion (SFM) from unmanned aerial vehicle (UAV) imagery, in order to characterize bioerosion patterns (i.e., cavities for roosting and nesting) caused by burrowing parrots on a cliff in Bahía Blanca, Argentina. The combined use of SFM-UAV technology was successfully applied for the 3D point cloud model reconstruction. The local point density, obtained by means of a sphere of radius equal to 0.5 m, reached a mean value of 9749, allowing to build a high-resolution model (0.013 m) for resolving fine spatial details in topography. To test the model, we compared it with another point cloud dataset which was created using a low cost do-it-yourself terrestrial laser scanner; the results showed that our georeferenced model had a good accuracy. In addition, an innovative method for the detection of the bioerosion features was implemented, through the processing of data provided by SFM like color and spatial coordinates (particularly the y coordinate). From the 3D model, we also derived topographic calculations such as slope angle and surface roughness, to get associations between the surface topography and bioerosion features.

Structure-from-Motion Approach for Characterization of Bioerosion Patterns Using UAV Imagery

PubMed Central

Genchi, Sibila A.; Vitale, Alejandro J.; Perillo, Gerardo M. E.; Delrieux, Claudio A.

2015-01-01

The aim of this work is to evaluate the applicability of the 3D model obtained through Structure-from-Motion (SFM) from unmanned aerial vehicle (UAV) imagery, in order to characterize bioerosion patterns (i.e., cavities for roosting and nesting) caused by burrowing parrots on a cliff in Bahía Blanca, Argentina. The combined use of SFM-UAV technology was successfully applied for the 3D point cloud model reconstruction. The local point density, obtained by means of a sphere of radius equal to 0.5 m, reached a mean value of 9749, allowing to build a high-resolution model (0.013 m) for resolving fine spatial details in topography. To test the model, we compared it with another point cloud dataset which was created using a low cost do-it-yourself terrestrial laser scanner; the results showed that our georeferenced model had a good accuracy. In addition, an innovative method for the detection of the bioerosion features was implemented, through the processing of data provided by SFM like color and spatial coordinates (particularly the y coordinate). From the 3D model, we also derived topographic calculations such as slope angle and surface roughness, to get associations between the surface topography and bioerosion features. PMID:25658392

Spatial statistical analysis of tree deaths using airborne digital imagery

NASA Astrophysics Data System (ADS)

Chang, Ya-Mei; Baddeley, Adrian; Wallace, Jeremy; Canci, Michael

2013-04-01

High resolution digital airborne imagery offers unprecedented opportunities for observation and monitoring of vegetation, providing the potential to identify, locate and track individual vegetation objects over time. Analytical tools are required to quantify relevant information. In this paper, locations of trees over a large area of native woodland vegetation were identified using morphological image analysis techniques. Methods of spatial point process statistics were then applied to estimate the spatially-varying tree death risk, and to show that it is significantly non-uniform. [Tree deaths over the area were detected in our previous work (Wallace et al., 2008).] The study area is a major source of ground water for the city of Perth, and the work was motivated by the need to understand and quantify vegetation changes in the context of water extraction and drying climate. The influence of hydrological variables on tree death risk was investigated using spatial statistics (graphical exploratory methods, spatial point pattern modelling and diagnostics).

Cognitive Imagery and Physiological Feedback Relaxation Protocols Applied to Clinically Tense Young Adults: A Comparison of State, Trait, and Physiological Effects.

ERIC Educational Resources Information Center

Schandler, Steven L.; Dana, Edward R.

1983-01-01

Examined changes in tension behaviors and reductions in physiological tension associated with cognitive imagery and electromyographic biofeedback relaxation procedures in 45 college students. Results showed: imagery significantly reduced state anxiety. Self-rest was less effective; biofeedback greatly reduced physiological tension, but not state…

Pattern recognition of satellite cloud imagery for improved weather prediction

NASA Technical Reports Server (NTRS)

Gautier, Catherine; Somerville, Richard C. J.; Volfson, Leonid B.

1986-01-01

The major accomplishment was the successful development of a method for extracting time derivative information from geostationary meteorological satellite imagery. This research is a proof-of-concept study which demonstrates the feasibility of using pattern recognition techniques and a statistical cloud classification method to estimate time rate of change of large-scale meteorological fields from remote sensing data. The cloud classification methodology is based on typical shape function analysis of parameter sets characterizing the cloud fields. The three specific technical objectives, all of which were successfully achieved, are as follows: develop and test a cloud classification technique based on pattern recognition methods, suitable for the analysis of visible and infrared geostationary satellite VISSR imagery; develop and test a methodology for intercomparing successive images using the cloud classification technique, so as to obtain estimates of the time rate of change of meteorological fields; and implement this technique in a testbed system incorporating an interactive graphics terminal to determine the feasibility of extracting time derivative information suitable for comparison with numerical weather prediction products.

California coastal processes study: Skylab. [San Pablo and San Francisco Bays

NASA Technical Reports Server (NTRS)

Pirie, D. M.; Steller, D. D. (Principal Investigator)

1975-01-01

The author has identified the following significant results. In San Pablo Bay, the patterns of dredged sediment discharges were plotted over a three month period. It was found that lithogenous particles, kept in suspension by the fresh water from the Sacramento-San Joaquin, were transported downstream to the estuarine area at varying rates depending on the river discharge level. Skylab collected California coastal imagery at limited times and not at constant intervals. Resolution, however, helped compensate for lack of coverage. Increased spatial and spectral resolution provided details not possible utilizing Landsat imagery. The S-192 data was reformatted; band by band image density stretching was utilized to enhance sediment discharge patterns entrainment, boundaries, and eddys. The 26 January 1974 Skylab 4 imagery of San Francisco Bay was taken during an exceptionally high fresh water and suspended sediment discharge period. A three pronged surface sediment pattern was visible where the Sacramento-San Joaquin Rivers entered San Pablo Bay through Carquinez Strait.

Analysis of Impact of Tropical Cyclone Blance on Rainfall at Kupang Region Based on Atmospheric Condition and Satellite Imagery

NASA Astrophysics Data System (ADS)

Roguna, S.; Saragih, I. J. A.; Siregar, P. S.; Julius, A. M.

2018-04-01

The Tropical Depression previously identified on March 3, 2017, at Arafuru Sea has grown to Tropical Cyclone Blance on March 5, 2017. The existence of Tropical Cyclone Blance gave impacts like increasing rainfall for some regions in Indonesia until March 7, 2017, such as Kupang. The increase of rainfall cannot be separated from the atmospheric dynamics related to convection processes and the formation of clouds. Analysis of weather parameters is made such as vorticity to observe vertical motion over the study area, vertical velocity to see the speed of lift force in the atmosphere, wind to see patterns of air mass distribution and rainfall to see the increase of rainfall compared to several days before the cyclone. Analysis of satellite imagery data is used as supporting analysis to see clouds imagery and movement direction of the cyclone. The results of weather parameters analysis show strong vorticity and lift force of air mass support the growth of Cumulonimbus clouds, cyclonic patterns on wind streamline and significant increase of rainfall compared to previous days. The results of satellite imagery analysis show the convective clouds over Kupang and surrounding areas when this phenomena and cyclone pattern moved down from Arafuru Sea towards the western part of Australia.

Total variation approach for adaptive nonuniformity correction in focal-plane arrays.

PubMed

Vera, Esteban; Meza, Pablo; Torres, Sergio

2011-01-15

In this Letter we propose an adaptive scene-based nonuniformity correction method for fixed-pattern noise removal in imaging arrays. It is based on the minimization of the total variation of the estimated irradiance, and the resulting function is optimized by an isotropic total variation approach making use of an alternating minimization strategy. The proposed method provides enhanced results when applied to a diverse set of real IR imagery, accurately estimating the nonunifomity parameters of each detector in the focal-plane array at a fast convergence rate, while also forming fewer ghosting artifacts.

Evaluation of SIR-B imagery for geologic and geomorphic mapping, hydrology, and oceanography in Australia

NASA Technical Reports Server (NTRS)

Honey, F. R.; Simpson, C. J.; Huntington, J.; Horwitz, R.; Byrne, G.; Nilsson, C.

1984-01-01

The objectives of a study to evaluate the potential of Shuttle Imaging Radar-B (SIR-B) imagery for various applications are outlined. Specific goals include: the development of techniques for registration multiple acquisition, varied illumination, and incidence-angle SIR-B imagery, and a model for estimation of the relative contributions to the backscattered radiation of topography, surface roughness, and dielectric and conductivity components; (2) the evaluation of SIR-B imagery for delineation of agricultural lands affected by secondary salinity in the southwest and southeast agricultural regions of Australia; (3) the development of techniques for application of SIR-B imagery for geologic, geomorphologic and soils mapping and mineral exploration; and (4) the evaluation of the use of SIR-B imagery in determining ocean currents, current shear patterns, internal waves and bottom features for specific locations off the Australian coast.

Potential value of satellite cloud pictures in weather modification projects

NASA Technical Reports Server (NTRS)

Biswas, K. R.

1972-01-01

Satellite imagery for one project season of cloud seeding programs in the northern Great Plains has been surveyed for its probable usefulness in weather modification programs. The research projects and the meteorological information available are described. A few illustrative examples of satellite imagery analysis are cited and discussed, along with local observations of weather and the seeding decisions made in the research program. This analysis indicates a definite correlation between satellite-observed cloud patterns and the types of cloud seeding activity undertaken, and suggests a high probability of better and/or earlier decisions if the imagery is available in real time. Infrared imagery provides better estimates of cloud height which can be useful in assessing the possibility of a hail threat. The satellite imagery appears to be of more value to area-seeding projects than to single-cloud seeding experiments where the imagery is of little value except as an aid in local forecasting and analysis.

Some approaches to optimal cluster labeling of aerospace imagery

NASA Technical Reports Server (NTRS)

Chittineni, C. B.

1980-01-01

Some approaches are presented to the problem of labeling clusters using information from a given set of labeled and unlabeled aerospace imagery patterns. The assignment of class labels to the clusters is formulated as the determination of the best assignment over all possible ones with respect to some criterion. Cluster labeling is also viewed as the probability of correct labeling with a maximization of likelihood function. Results of the application of these techniques in the processing of remotely sensed multispectral scanner imagery data are presented.

The use of ERTS imagery in reservoir management and operation

NASA Technical Reports Server (NTRS)

Cooper, S. (Principal Investigator)

1973-01-01

There are no author-identified significant results in this report. Preliminary analysis of ERTS-1 imagery suggests that the configuration and areal coverage of surface waters, as well as other hydrologically related terrain features, may be obtained from ERTS-1 imagery to an extent that would be useful. Computer-oriented pattern recognition techniques are being developed to help automate the identification and analysis of hydrologic features. Considerable man-machine interaction is required while training the computer for these tasks.

Investigation of Skylab imagery for regional planning. [New York, New Jersey, and Connecticut

NASA Technical Reports Server (NTRS)

Harting, W. (Principal Investigator)

1975-01-01

The author has identified the following significant results. It is feasible to use earth terrain camera imagery to detect four land uses (vacant land, developed land, streets, and water) for general regional planning purposes. Multispectral imagery is suitable for detecting, mapping, and measuring water bodies as small as two acres. Sufficient information can be extracted to prepare graphic and pictorial representations of the general growth and development patterns, but cannot be incorporated into an inventory file for predictive models.

Mineral resources, geologic structure, and landform surveys

NASA Technical Reports Server (NTRS)

Lattman, L. H.

1973-01-01

The use of ERTS-1 imagery for mineral resources, geologic structure, and landform surveys is discussed. Four categories of ERTS imagery application are defined and explained. The types of information obtained by the various multispectral band scanners are analyzed. Samples of land use maps and tectoning and metallogenic models are developed. It is stated that the most striking features visible on ERTS imagery are regional lineaments, or linear patterns in the topography, which reflect major fracture zones extending upward from the basement of the earth.

Functional Connectivity During Exposure to Favorite-Food, Stress, and Neutral-Relaxing Imagery Differs Between Smokers and Nonsmokers.

PubMed

Garrison, Kathleen A; Sinha, Rajita; Lacadie, Cheryl M; Scheinost, Dustin; Jastreboff, Ania M; Constable, R Todd; Potenza, Marc N

2016-09-01

Tobacco-use disorder is a complex condition involving multiple brain networks and presenting with multiple behavioral correlates including changes in diet and stress. In a previous functional magnetic resonance imaging (fMRI) study of neural responses to favorite-food, stress, and neutral-relaxing imagery, smokers versus nonsmokers demonstrated blunted corticostriatal-limbic responses to favorite-food cues. Based on other recent reports of alterations in functional brain networks in smokers, the current study examined functional connectivity during exposure to favorite-food, stress, and neutral-relaxing imagery in smokers and nonsmokers, using the same dataset. The intrinsic connectivity distribution was measured to identify brain regions that differed in degree of functional connectivity between groups during each imagery condition. Resulting clusters were evaluated for seed-to-voxel connectivity to identify the specific connections that differed between groups during each imagery condition. During exposure to favorite-food imagery, smokers versus nonsmokers showed lower connectivity in the supramarginal gyrus, and differences in connectivity between the supramarginal gyrus and the corticostriatal-limbic system. During exposure to neutral-relaxing imagery, smokers versus nonsmokers showed greater connectivity in the precuneus, and greater connectivity between the precuneus and the posterior insula and rolandic operculum. During exposure to stress imagery, smokers versus nonsmokers showed lower connectivity in the cerebellum. These findings provide data-driven insights into smoking-related alterations in brain functional connectivity patterns related to appetitive, relaxing, and stressful states. This study uses a data-driven approach to demonstrate that smokers and nonsmokers show differential patterns of functional connectivity during guided imagery related to personalized favorite-food, stress, and neutral-relaxing cues, in brain regions implicated in attention, reward-related, emotional, and motivational processes. For smokers, these differences in connectivity may impact appetite, stress, and relaxation, and may interfere with smoking cessation. © The Author 2016. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Functional Connectivity During Exposure to Favorite-Food, Stress, and Neutral-Relaxing Imagery Differs Between Smokers and Nonsmokers

PubMed Central

Sinha, Rajita; Lacadie, Cheryl M.; Scheinost, Dustin; Jastreboff, Ania M.; Constable, R. Todd; Potenza, Marc N.

2016-01-01

Introduction: Tobacco-use disorder is a complex condition involving multiple brain networks and presenting with multiple behavioral correlates including changes in diet and stress. In a previous functional magnetic resonance imaging (fMRI) study of neural responses to favorite-food, stress, and neutral-relaxing imagery, smokers versus nonsmokers demonstrated blunted corticostriatal-limbic responses to favorite-food cues. Based on other recent reports of alterations in functional brain networks in smokers, the current study examined functional connectivity during exposure to favorite-food, stress, and neutral-relaxing imagery in smokers and nonsmokers, using the same dataset. Methods: The intrinsic connectivity distribution was measured to identify brain regions that differed in degree of functional connectivity between groups during each imagery condition. Resulting clusters were evaluated for seed-to-voxel connectivity to identify the specific connections that differed between groups during each imagery condition. Results: During exposure to favorite-food imagery, smokers versus nonsmokers showed lower connectivity in the supramarginal gyrus, and differences in connectivity between the supramarginal gyrus and the corticostriatal-limbic system. During exposure to neutral-relaxing imagery, smokers versus nonsmokers showed greater connectivity in the precuneus, and greater connectivity between the precuneus and the posterior insula and rolandic operculum. During exposure to stress imagery, smokers versus nonsmokers showed lower connectivity in the cerebellum. Conclusions: These findings provide data-driven insights into smoking-related alterations in brain functional connectivity patterns related to appetitive, relaxing, and stressful states. Implications: This study uses a data-driven approach to demonstrate that smokers and nonsmokers show differential patterns of functional connectivity during guided imagery related to personalized favorite-food, stress, and neutral-relaxing cues, in brain regions implicated in attention, reward-related, emotional, and motivational processes. For smokers, these differences in connectivity may impact appetite, stress, and relaxation, and may interfere with smoking cessation. PMID:26995796

Mapping turbidity in the Charles River, Boston using a high-resolution satellite.

PubMed

Hellweger, Ferdi L; Miller, Will; Oshodi, Kehinde Sarat

2007-09-01

The usability of high-resolution satellite imagery for estimating spatial water quality patterns in urban water bodies is evaluated using turbidity in the lower Charles River, Boston as a case study. Water turbidity was surveyed using a boat-mounted optical sensor (YSI) at 5 m spatial resolution, resulting in about 4,000 data points. The ground data were collected coincidently with a satellite imagery acquisition (IKONOS), which consists of multispectral (R, G, B) reflectance at 1 m resolution. The original correlation between the raw ground and satellite data was poor (R2 = 0.05). Ground data were processed by removing points affected by contamination (e.g., sensor encounters a particle floc), which were identified visually. Also, the ground data were corrected for the memory effect introduced by the sensor's protective casing using an analytical model. Satellite data were processed to remove pixels affected by permanent non-water features (e.g., shoreline). In addition, water pixels within a certain buffer distance from permanent non-water features were removed due to contamination by the adjacency effect. To determine the appropriate buffer distance, a procedure that explicitly considers the distance of pixels to the permanent non-water features was applied. Two automatic methods for removing the effect of temporary non-water features (e.g., boats) were investigated, including (1) creating a water-only mask based on an unsupervised classification and (2) removing (filling) all local maxima in reflectance. After the various processing steps, the correlation between the ground and satellite data was significantly better (R2 = 0.70). The correlation was applied to the satellite image to develop a map of turbidity in the lower Charles River, which reveals large-scale patterns in water clarity. However, the adjacency effect prevented the application of this method to near-shore areas, where high-resolution patterns were expected (e.g., outfall plumes).

A subject-independent pattern-based Brain-Computer Interface

PubMed Central

Ray, Andreas M.; Sitaram, Ranganatha; Rana, Mohit; Pasqualotto, Emanuele; Buyukturkoglu, Korhan; Guan, Cuntai; Ang, Kai-Keng; Tejos, Cristián; Zamorano, Francisco; Aboitiz, Francisco; Birbaumer, Niels; Ruiz, Sergio

2015-01-01

While earlier Brain-Computer Interface (BCI) studies have mostly focused on modulating specific brain regions or signals, new developments in pattern classification of brain states are enabling real-time decoding and modulation of an entire functional network. The present study proposes a new method for real-time pattern classification and neurofeedback of brain states from electroencephalographic (EEG) signals. It involves the creation of a fused classification model based on the method of Common Spatial Patterns (CSPs) from data of several healthy individuals. The subject-independent model is then used to classify EEG data in real-time and provide feedback to new individuals. In a series of offline experiments involving training and testing of the classifier with individual data from 27 healthy subjects, a mean classification accuracy of 75.30% was achieved, demonstrating that the classification system at hand can reliably decode two types of imagery used in our experiments, i.e., happy emotional imagery and motor imagery. In a subsequent experiment it is shown that the classifier can be used to provide neurofeedback to new subjects, and that these subjects learn to “match” their brain pattern to that of the fused classification model in a few days of neurofeedback training. This finding can have important implications for future studies on neurofeedback and its clinical applications on neuropsychiatric disorders. PMID:26539089

Using multi-spectral imagery to detect and map stress induced by Russian wheat aphid

NASA Astrophysics Data System (ADS)

Backoulou, Georges Ferdinand

Scope and Method of Study. The rationale of this study was to assess the stress in wheat field induced by the Russian wheat aphid using multispectral imagery. The study was conducted to (a) determine the relationship between RWA and edaphic and topographic factors; (b) identify and quantify the spatial pattern of RWA infestation within wheat fields; (c) differentiate the stress induced by RWA from other stress causing factors. Data used for the analysis included RWA population density from the wheat field in, Texas, Colorado, Wyoming, and Nebraska, Digital Elevation Model from the Unites States Geological Survey (USGS), soil data from the Soil Survey Geographic database (SSURGO), and multispectral imagery acquired in the panhandle of Oklahoma. Findings and Conclusions. The study revealed that the population density of the Russian wheat aphid was related to topographic and edaphic factors. Slope and sand were predictor variables that were positively related to the density of RWA at the field level. The study has also demonstrated that stress induced by the RWA has a specific spatial pattern that can be distinguished from other stress causing factors using a combination of landscape metrics and topographic and edaphic characteristics of wheat fields. Further field-based studies using multispectral imagery and spatial pattern analysis are suggested. The suggestions require acquiring biweekly multispectral imagery and collecting RWA, topographic and edaphic data at the sampling points during the phonological growth development of wheat plants. This is an approach that may pretend to have great potential for site specific technique for the integrated pest management.

Overall evaluation of LANDSAT (ERTS) follow on imagery for cartographic application

NASA Technical Reports Server (NTRS)

Colvocoresses, A. P. (Principal Investigator)

1977-01-01

The author has identified the following significant results. LANDSAT imagery can be operationally applied to the revision of nautical charts. The imagery depicts shallow seas in a form that permits accurate planimetric image mapping of features to 20 meters of depth where the conditions of water clarity and bottom reflection are suitable. LANDSAT data also provide an excellent simulation of the earth's surface, for such applications as aeronautical charting and radar image correlation in aircraft and aircraft simulators. Radiometric enhancement, particularly edge enhancement, a technique only marginally successful with aerial photographs has proved to be high value when applied to LANDSAT data.

The functional alterations associated with motor imagery training: a comparison between motor execution and motor imagery of sequential finger tapping

NASA Astrophysics Data System (ADS)

Zhang, Hang; Yao, Li; Long, Zhiying

2011-03-01

Motor imagery training, as an effective strategy, has been more and more applied to mental disorders rehabilitation and motor skill learning. Studies on the neural mechanism underlying motor imagery have suggested that such effectiveness may be related to the functional congruence between motor execution and motor imagery. However, as compared to the studies on motor imagery, the studies on motor imagery training are much fewer. The functional alterations associated with motor imagery training and the effectiveness of motor imagery training on motor performance improvement still needs further investigation. Using fMRI, we employed a sequential finger tapping paradigm to explore the functional alterations associated with motor imagery training in both motor execution and motor imagery task. We hypothesized through 14 consecutive days motor imagery training, the motor performance could be improved and the functional congruence between motor execution and motor imagery would be sustained form pre-training phase to post-training phase. Our results confirmed the effectiveness of motor imagery training in improving motor performance and demonstrated in both pre and post-training phases, motor imagery and motor execution consistently sustained the congruence in functional neuroanatomy, including SMA (supplementary motor cortex), PMA (premotor area); M1( primary motor cortex) and cerebellum. Moreover, for both execution and imagery tasks, a similar functional alteration was observed in fusiform through motor imagery training. These findings provided an insight into the effectiveness of motor imagery training and suggested its potential therapeutic value in motor rehabilitation.

Development of a Standardized Methodology for the Use of COSI-Corr Sub-Pixel Image Correlation to Determine Surface Deformation Patterns in Large Magnitude Earthquakes.

NASA Astrophysics Data System (ADS)

Milliner, C. W. D.; Dolan, J. F.; Hollingsworth, J.; Leprince, S.; Ayoub, F.

2014-12-01

Coseismic surface deformation is typically measured in the field by geologists and with a range of geophysical methods such as InSAR, LiDAR and GPS. Current methods, however, either fail to capture the near-field coseismic surface deformation pattern where vital information is needed, or lack pre-event data. We develop a standardized and reproducible methodology to fully constrain the surface, near-field, coseismic deformation pattern in high resolution using aerial photography. We apply our methodology using the program COSI-corr to successfully cross-correlate pairs of aerial, optical imagery before and after the 1992, Mw 7.3 Landers and 1999, Mw 7.1 Hector Mine earthquakes. This technique allows measurement of the coseismic slip distribution and magnitude and width of off-fault deformation with sub-pixel precision. This technique can be applied in a cost effective manner for recent and historic earthquakes using archive aerial imagery. We also use synthetic tests to constrain and correct for the bias imposed on the result due to use of a sliding window during correlation. Correcting for artificial smearing of the tectonic signal allows us to robustly measure the fault zone width along a surface rupture. Furthermore, the synthetic tests have constrained for the first time the measurement precision and accuracy of estimated fault displacements and fault-zone width. Our methodology provides the unique ability to robustly understand the kinematics of surface faulting while at the same time accounting for both off-fault deformation and measurement biases that typically complicates such data. For both earthquakes we find that our displacement measurements derived from cross-correlation are systematically larger than the field displacement measurements, indicating the presence of off-fault deformation. We show that the Landers and Hector Mine earthquake accommodated 46% and 38% of displacement away from the main primary rupture as off-fault deformation, over a mean deformation width of 183 m and 133 m, respectively. We envisage that correlation results derived from our methodology will provide vital data for near-field deformation patterns and will be of significant use for constraining inversion solutions for fault slip at depth.

Remote sensing of soils, land forms, and land use in the northern Great Plains in preparation for ERTS applications

NASA Technical Reports Server (NTRS)

Frazee, C. J.; Westin, F. C.; Gropper, J.; Myers, V. I.

1972-01-01

Research to determine the optimum time or season for obtaining imagery to identify and map soil limitations was conducted in the proposed Oahe irrigation project area in South Dakota. The optimum time for securing photographs or imagery is when the soil surface patterns are most apparent. For cultivated areas similar to the study area, May is the optimum time. The density slicing analysis of the May image provided additional and more accurate information than did the existing soil map. The soil boundaries were more accurately located. The use of a density analysis system for an operational soil survey has not been tested, but is obviously dependent upon securing excellent photographs for interpretation. The colors or densities of photographs will have to be corrected for sun angle effects, vignetting effects, and processing to have maximum effectiveness for mapping soil limitations. Rangeland sites were established in Bennett County, South Dakota to determine the usefulness of ERTS imagery. Imagery from these areas was interpreted for land use and drainage patterns.

Thermal anomaly mapping from night MODIS imagery of USA, a tool for environmental assessment.

PubMed

Miliaresis, George Ch

2013-02-01

A method is presented for elevation, latitude and longitude decorrelation stretch of multi-temporal MODIS MYD11C3 imagery (monthly average night land surface temperature (LST) across USA and Mexico). Multiple linear regression analysis of principal components images (PCAs) quantifies the variance explained by elevation (H), latitude (LAT), and longitude (LON). The multi-temporal LST imagery is reconstructed from the residual images and selected PCAs by taking into account the portion of variance that is not related to H, LAT, LON. The reconstructed imagery presents the magnitude the standardized LST value per pixel deviates from the H, LAT, LON predicted. LST anomaly is defined as a region that presents either positive or negative reconstructed LST value. The environmental assessment of USA indicated that only for the 25 % of the study area (Mississippi drainage basin), the LST is predicted by the H, LAT, LON. Regions with milled climatic pattern were identified in the West Coast while the coldest climatic pattern is observed for Mid USA. Positive season invariant LST anomalies are identified in SW (Arizona, Sierra Nevada, etc.) and NE USA.

The effectiveness of texture analysis for mapping forest land using the panchromatic bands of Landsat 7, SPOT, and IRS imagery

Treesearch

Michael L. Hoppus; Rachel I. Riemann; Andrew J. Lister; Mark V. Finco

2002-01-01

The panchromatic bands of Landsat 7, SPOT, and IRS satellite imagery provide an opportunity to evaluate the effectiveness of texture analysis of satellite imagery for mapping of land use/cover, especially forest cover. A variety of texture algorithms, including standard deviation, Ryherd-Woodcock minimum variance adaptive window, low pass etc., were applied to moving...

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

PubMed

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 (<1 m) resolution aerial imagery, and identify social-ecological relationships of 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 cities. © 2017 by the Ecological Society of America.

Dome growth at Mount Cleveland, Aleutian Arc, quantified by time-series TerraSAR-X imagery

USGS Publications Warehouse

Wang, Teng; Poland, Michael; Lu, Zhong

2016-01-01

Synthetic aperture radar imagery is widely used to study surface deformation induced by volcanic activity; however, it is rarely applied to quantify the evolution of lava domes, which is important for understanding hazards and magmatic system characteristics. We studied dome formation associated with eruptive activity at Mount Cleveland, Aleutian Volcanic Arc, in 2011–2012 using TerraSAR-X imagery. Interferometry and offset tracking show no consistent deformation and only motion of the crater rim, suggesting that ascending magma may pass through a preexisting conduit system without causing appreciable surface deformation. Amplitude imagery has proven useful for quantifying rates of vertical and areal growth of the lava dome within the crater from formation to removal by explosive activity to rebirth. We expect that this approach can be applied at other volcanoes that host growing lava domes and where hazards are highly dependent on dome geometry and growth rates.

Snow Pattern Delineation, Scaling, Fidelity, and Landscape Factors

NASA Astrophysics Data System (ADS)

Hiemstra, C. A.; Wagner, A. M.; Deeb, E. J.; Morriss, B. F.; Sturm, M.

2014-12-01

In many snow-covered landscapes, snow tends to be shallow or deep in the same locations year after year. As snowmelt progresses in spring, areas of shallow snow become snow-free earlier than areas with deep snow. This pattern (Sturm and Wagner 2010) could likely be used to inform or improve modeled snow depth estimates where ground measurements are not collected; however, we must be certain of their utility before ingesting them into model calculations. Do patterns, as we detect them, have a relationship with earlier measured snow distributions? Second, are certain areas on the landscape likely to yield patterns that are influenced too highly by melting to be useful? Our Imnavait Creek Study Area (11 by 19 km) is on Alaska's North Slope, where we have examined a vast library of spring satellite imagery (ranging from mostly snow-covered to mostly snow-free). Landsat TM Imagery has been collected from the early 1980s-present, and the temporal and spatial resolution is roughly two weeks and 30 m, respectively. High resolution satellite imagery (WorldView 1, WorldView 2, IKONOS) has been obtained from 2010-2013 for the same area with almost daily- to monthly-temporal and at 2.5 m spatial resolutions, respectively. We found that there is a striking similarity among patterns from year to year across the span of decades and resolutions. However, the relationship of pattern with observed snow depths was strong in some areas and less clear in others. Overall, we suspect spatial scaling, spatial mismatch, sampling errors, and melt patterns explain most of the areas of pattern and depth disparity.

Utilization of ERTS-1 data in North Carolina

NASA Technical Reports Server (NTRS)

Welby, C. W. (Principal Investigator); Lammi, J. O.; Carson, R. J., III

1973-01-01

The author has identified the following significant results. A wide range of potential uses for ERTS-1 imagery is described. Special emphasis has been placed upon studies in the Coastal Plain of North Carolina. Soil groups, water quality, and suspended sediment patterns in estuaries and offshore have been studied. A phytoplankton bloom has possibly been detected. The usefulness of the imagery in coastal landform surveys has been demonstrated as has its usefulness in monitoring developmental activity in the forests. Planners appear hesitant to use the imagery because of its small scale, but it is felt that as they become familiar with the imagery they will find it useful and time-saving for many purposes.

Applicability of ERTS-1 imagery to the study of suspended sediment and aquatic fronts

NASA Technical Reports Server (NTRS)

Klemas, V.; Srna, R.; Treasure, W.; Otley, M.

1973-01-01

Imagery from three successful ERTS-1 passes over the Delaware Bay and Atlantic Coastal Region have been evaluated to determine visibility of aquatic features. Data gathered from ground truth teams before and during the overflights, in conjunction with aerial photographs taken at various altitudes, were used to interpret the imagery. The overpasses took place on August 16, October 10, 1972, and January 26, 1973, with cloud cover ranging from about zero to twenty percent. (I.D. Nos. 1024-15073, 1079-15133, and 1187-15140). Visual inspection, density slicing and multispectral analysis of the imagery revealed strong suspended sediment patterns and several distinct types of aquatic interfaces or frontal systems.

Individually adapted imagery improves brain-computer interface performance in end-users with disability.

PubMed

Scherer, Reinhold; Faller, Josef; Friedrich, Elisabeth V C; Opisso, Eloy; Costa, Ursula; Kübler, Andrea; Müller-Putz, Gernot R

2015-01-01

Brain-computer interfaces (BCIs) translate oscillatory electroencephalogram (EEG) patterns into action. Different mental activities modulate spontaneous EEG rhythms in various ways. Non-stationarity and inherent variability of EEG signals, however, make reliable recognition of modulated EEG patterns challenging. Able-bodied individuals who use a BCI for the first time achieve - on average - binary classification performance of about 75%. Performance in users with central nervous system (CNS) tissue damage is typically lower. User training generally enhances reliability of EEG pattern generation and thus also robustness of pattern recognition. In this study, we investigated the impact of mental tasks on binary classification performance in BCI users with central nervous system (CNS) tissue damage such as persons with stroke or spinal cord injury (SCI). Motor imagery (MI), that is the kinesthetic imagination of movement (e.g. squeezing a rubber ball with the right hand), is the "gold standard" and mainly used to modulate EEG patterns. Based on our recent results in able-bodied users, we hypothesized that pair-wise combination of "brain-teaser" (e.g. mental subtraction and mental word association) and "dynamic imagery" (e.g. hand and feet MI) tasks significantly increases classification performance of induced EEG patterns in the selected end-user group. Within-day (How stable is the classification within a day?) and between-day (How well does a model trained on day one perform on unseen data of day two?) analysis of variability of mental task pair classification in nine individuals confirmed the hypothesis. We found that the use of the classical MI task pair hand vs. feed leads to significantly lower classification accuracy - in average up to 15% less - in most users with stroke or SCI. User-specific selection of task pairs was again essential to enhance performance. We expect that the gained evidence will significantly contribute to make imagery-based BCI technology become accessible to a larger population of users including individuals with special needs due to CNS damage.

Individually Adapted Imagery Improves Brain-Computer Interface Performance in End-Users with Disability

PubMed Central

Scherer, Reinhold; Faller, Josef; Friedrich, Elisabeth V. C.; Opisso, Eloy; Costa, Ursula; Kübler, Andrea; Müller-Putz, Gernot R.

2015-01-01

Brain-computer interfaces (BCIs) translate oscillatory electroencephalogram (EEG) patterns into action. Different mental activities modulate spontaneous EEG rhythms in various ways. Non-stationarity and inherent variability of EEG signals, however, make reliable recognition of modulated EEG patterns challenging. Able-bodied individuals who use a BCI for the first time achieve - on average - binary classification performance of about 75%. Performance in users with central nervous system (CNS) tissue damage is typically lower. User training generally enhances reliability of EEG pattern generation and thus also robustness of pattern recognition. In this study, we investigated the impact of mental tasks on binary classification performance in BCI users with central nervous system (CNS) tissue damage such as persons with stroke or spinal cord injury (SCI). Motor imagery (MI), that is the kinesthetic imagination of movement (e.g. squeezing a rubber ball with the right hand), is the "gold standard" and mainly used to modulate EEG patterns. Based on our recent results in able-bodied users, we hypothesized that pair-wise combination of "brain-teaser" (e.g. mental subtraction and mental word association) and "dynamic imagery" (e.g. hand and feet MI) tasks significantly increases classification performance of induced EEG patterns in the selected end-user group. Within-day (How stable is the classification within a day?) and between-day (How well does a model trained on day one perform on unseen data of day two?) analysis of variability of mental task pair classification in nine individuals confirmed the hypothesis. We found that the use of the classical MI task pair hand vs. feed leads to significantly lower classification accuracy - in average up to 15% less - in most users with stroke or SCI. User-specific selection of task pairs was again essential to enhance performance. We expect that the gained evidence will significantly contribute to make imagery-based BCI technology become accessible to a larger population of users including individuals with special needs due to CNS damage. PMID:25992718

Translation of EEG Spatial Filters from Resting to Motor Imagery Using Independent Component Analysis

PubMed Central

Wang, Yijun; Wang, Yu-Te; Jung, Tzyy-Ping

2012-01-01

Electroencephalogram (EEG)-based brain-computer interfaces (BCIs) often use spatial filters to improve signal-to-noise ratio of task-related EEG activities. To obtain robust spatial filters, large amounts of labeled data, which are often expensive and labor-intensive to obtain, need to be collected in a training procedure before online BCI control. Several studies have recently developed zero-training methods using a session-to-session scenario in order to alleviate this problem. To our knowledge, a state-to-state translation, which applies spatial filters derived from one state to another, has never been reported. This study proposes a state-to-state, zero-training method to construct spatial filters for extracting EEG changes induced by motor imagery. Independent component analysis (ICA) was separately applied to the multi-channel EEG in the resting and the motor imagery states to obtain motor-related spatial filters. The resultant spatial filters were then applied to single-trial EEG to differentiate left- and right-hand imagery movements. On a motor imagery dataset collected from nine subjects, comparable classification accuracies were obtained by using ICA-based spatial filters derived from the two states (motor imagery: 87.0%, resting: 85.9%), which were both significantly higher than the accuracy achieved by using monopolar scalp EEG data (80.4%). The proposed method considerably increases the practicality of BCI systems in real-world environments because it is less sensitive to electrode misalignment across different sessions or days and does not require annotated pilot data to derive spatial filters. PMID:22666377

Patterning of pain and power with guided imagery.

PubMed

Lewandowski, Wendy A

2004-07-01

Using Martha Rogers' science of unitary human beings, changes in pain and power among 42 patients were examined in relation to the use of a guided imagery modality. Participants were randomly assigned to treatment and control groups and repeated measures MANCOVA was used to detect differences in pain and power over a 4-day period of time. The treatment group's pain decreased during the last 2 days of the study. No differences in power emerged. Guided imagery appeared to have potential as a useful nursing modality for chronic pain sufferers.

Chaotic terrain of Mars - A tectonic interpretation from Mariner 6 imagery

NASA Technical Reports Server (NTRS)

Wilson, R. C.; Harp, E. L.; Picard, M. D.; Ward, S. H.

1973-01-01

Sharp et al. (1971) define chaotic terrain as an irregular jumble of topographic forms covering a certain area within Pyrrhae Regio and adjacent regions centered at about 10 deg S., 35 deg W. This area is covered by Mariner 6 television imagery. An analysis of fracture patterns in the Martian surface from high-resolution Mariner 6 imagery suggests that the lineaments observed in both the chaotic terrain and the cratered plateau areas in Pyrrhae Regio are tectonic fractures resulting from stresses within the Martian crust.

Quantitative assessment of urban wetland dynamics using high spatial resolution satellite imagery between 2000 and 2013.

PubMed

Hu, Tangao; Liu, Jiahong; Zheng, Gang; Li, Yao; Xie, Bin

2018-05-09

Accurate and timely information describing urban wetland resources and their changes over time, especially in rapidly urbanizing areas, is becoming more important. We applied an object-based image analysis and nearest neighbour classifier to map and monitor changes in land use/cover using multi-temporal high spatial resolution satellite imagery in an urban wetland area (Hangzhou Xixi Wetland) from 2000, 2005, 2007, 2009 and 2013. The overall eight-class classification accuracies averaged 84.47% for the five years. The maps showed that between 2000 and 2013 the amount of non-wetland (urban) area increased by approximately 100%. Herbaceous (32.22%), forest (29.57%) and pond (23.85%) are the main land-cover types that changed to non-wetland, followed by cropland (6.97%), marsh (4.04%) and river (3.35%). In addition, the maps of change patterns showed that urban wetland loss is mainly distributed west and southeast of the study area due to real estate development, and the greatest loss of urban wetlands occurred from 2007 to 2013. The results demonstrate the advantages of using multi-temporal high spatial resolution satellite imagery to provide an accurate, economical means to map and analyse changes in land use/cover over time and the ability to use the results as inputs to urban wetland management and policy decisions.

Investigation of the Fractal Geometry of Tundra Lake Patterns using Historical Topographic Maps and Satellite Imagery.

NASA Astrophysics Data System (ADS)

Kariyawasam, T.; Essa, A.; Gong, M.; Sudakov, I.

2017-12-01

Greenhouse gas emissions from tundra lakes are a significant positive feedback to the atmosphere in a changing climate as a pronounced growth of the numbers of tundra lake patterns has been observed in the Arctic region. Detailed knowledge of spatial dynamics of lake patterns in a changing arctic tundra landscape and their geometrical properties is therefore potentially valuable, in order to understand and accurately model the sources of greenhouse gas emissions from boreal permafrost. Our goal is to use a collection of historical topographic maps and satellite imagery of tundra lakes to conduct computational image analyses for examining spatial dynamics of Tundra lake patterns. Our approach is based upon analyzing area-perimeter data of thousands of tundra lakes to compute the fractal dimension to study the tundra lake pattern geometry, which have been used to classify pollen grains by textual patterning (Mander, 2016), vegetation in dryland ecosystems (Mander, 2017) and melt pond patterns (Hohenegger, 2012). By analyzing area - perimeter data for over 900 lakes we find that for both historical topographic maps and current satellite imagery, the fractal dimension D is stable at 1.6 for Tundra lakes with area less than about 100km2. For Tundra lake sizes bigger than 100 km2 fractal dimension takes values close to 2 and less than one indicative of structural changes in Tundra lake pattern geometry. Furthermore the current study did not reveal any percolation transition above some critical threshold in Tundra lake evolution. The results of the study will provide scientists with new data on these aspects of tundra lakes to help characterize the geomorphology of spatial patterns in arctic tundra lakes.

Using Deep Learning for Tropical Cyclone Intensity Estimation

NASA Astrophysics Data System (ADS)

Miller, J.; Maskey, M.; Berendes, T.

2017-12-01

Satellite-based techniques are the primary approach to estimating tropical cyclone (TC) intensity. Tropical cyclone warning centers worldwide still apply variants of the Dvorak technique for such estimations that include visual inspection of the satellite images. The National Hurricane Center (NHC) estimates about 10-20% uncertainty in its post analyses when only satellite-based estimates are available. The success of the Dvorak technique proves that spatial patterns in infrared (IR) imagery strongly relate to TC intensity. With the ever-increasing quality and quantity of satellite observations of TCs, deep learning techniques designed to excel at pattern recognition have become more relevant in this area of study. In our current study, we aim to provide a fully objective approach to TC intensity estimation by utilizing deep learning in the form of a convolutional neural network trained to predict TC intensity (maximum sustained wind speed) using IR satellite imagery. Large amounts of training data are needed to train a convolutional neural network, so we use GOES IR images from historical tropical storms from the Atlantic and Pacific basins spanning years 2000 to 2015. Images are labeled using a special subset of the HURDAT2 dataset restricted to time periods with airborne reconnaissance data available in order to improve the quality of the HURDAT2 data. Results and the advantages of this technique are to be discussed.

An Analysis of Air Photo and Radar Imagery of Barro Colorado Island, Panama

DTIC Science & Technology

1989-07-01

changes (flats, hills, mountains , etc.), they cannot provide the shape information that can be obtained from stereo imagery. Referring to figure 14, one...field patterns. These are shown in figure 20. Figure 21 shows a portion of a 1979 Landsat MSS color composite scene of this alea . It has a continuous red

Water Literacy in College Freshmen: Could a Cognitive Imagery Strategy Improve Understanding?

ERIC Educational Resources Information Center

Ewing, Margaret S.; Mills, Terence J.

1994-01-01

Presents a study designed to determine whether levels of water literacy differed between (n=83) college freshman nonscience majors having one versus two years of high school science coursework, visual imagery exercises could improve understanding of the water cycle, and patterns exist in the concept of the water cycle. (Contains 23 references.)…

What do the data show? Fostering physical intuition with ClimateBits and NASA Earth Observations

NASA Astrophysics Data System (ADS)

Schollaert Uz, S.; Ward, K.

2017-12-01

Through data visualizations using global satellite imagery available in NASA Earth Observations (NEO), we explain Earth science concepts (e.g. albedo, urban heat island effect, phytoplankton). We also provide examples of ways to explore the satellite data in NEO within a new blog series. This is an ideal tool for scientists and non-scientists alike who want to quickly check satellite imagery for large scale features or patterns. NEO analysis requires no software or plug-ins; only a browser and an internet connection. You can even check imagery and perform simple analyses from your smart phone. NEO can be used to create graphics for presentations and papers or as a first step before acquiring data for more rigorous analysis. NEO has potential application to easily explore large scale environmental and climate patterns that impact operations and infrastructure. This is something we are currently exploring with end user groups.

Correlation of coastal water turbidity and current circulation with ERTS-1 and Skylab imagery

NASA Technical Reports Server (NTRS)

Klemas, V.; Otley, M.; Philpot, W.; Wethe, C.; Rogers, R.; Shah, N.

1974-01-01

The article reviews investigations of current circulation patterns, suspended sediment concentration, coastal frontal systems, and waste disposal plumes based on visual interpretation and digital analysis of ERTS-1 and Skylab/EREP imagery. Data on conditions in the Delaware Bay area were obtained from 10 ERTS-1 passes and one Skylab pass, with simultaneous surface and airborne sensing. The current patterns and sediments observed by ERTS-1 correlated well with ground-based observations. Methods are suggested which would make it possible to identify certain pollutants and sediment types from multispectral scanner data.

Dream content of Canadian males from adolescence to old age: An exploration of ontogenetic patterns.

PubMed

Dale, Allyson; Lafrenière, Alexandre; De Koninck, Joseph

2017-03-01

The present study was a first look at the ontogenetic pattern of dream content across the lifespan for men. The participants included 50 Canadian men in each of 5 age groups, from adolescence to old age including 12-17, 18-24, 25-39, 40-64, and 65-85. The last age group included 31 participants, totaling 231 males. One dream per participant was scored by two independent judges using content analysis. Trend analysis was used to determine the lifespan-developmental pattern of the dream content categories. Results demonstrated a predominance of aggressive dream imagery in the adolescent age group in line with social-developmental research. These patterns of dream imagery reflect the waking developmental patterns as proposed by social theories and recognized features of aging. Limitations and suggestions for future research, including the examining of the developmental pattern of gender differences across the lifespan, are discussed. Copyright © 2017 Elsevier Inc. All rights reserved.

Applicability of Satellite Freeze Forecasting and Cold Climate Mapping to the Other Parts of the United States

NASA Technical Reports Server (NTRS)

1981-01-01

Tasks performed to determine the value of using GOES satellite thermal imagery to enhance fruit crop production in Michigan are described. An overview is presented of the system developed for image processing and thermal image and surface environmental data bases prepared to assess the physical models developed in Florida. These data bases were used to identify correlations between satellite apparent temperatures patterns and Earth surface factors. Significant freeze events in 1981 and the physical models used to provide a perspective on how Florida models can be applied in the context of the Michigan environment are discussed.

Recognition of the geologic framework of porphyry deposits on ERTS-1 imagery

NASA Technical Reports Server (NTRS)

Wilson, J. C. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Photointerpretation methods have been most successfully applied in the less vegetated test sites where several previously unknown geologic features have been recognized and known ones extended. Northwest mid-Tertiary faults in the ELY, Nevada area are observed to offset north-trending ranges and abruptly terminate older Mesozoic structures. In the Ray, Arizona area the observed patterns of fault and fracture systems appear to be related to the locations of known porphyry copper deposits. In the Tanacross, Alaska area a number of regional circular features observed may represent near surface intrusions and, therefore, permissive environments for copper porphyries.

D Object Classification Based on Thermal and Visible Imagery in Urban Area

NASA Astrophysics Data System (ADS)

Hasani, H.; Samadzadegan, F.

2015-12-01

The spatial distribution of land cover in the urban area especially 3D objects (buildings and trees) is a fundamental dataset for urban planning, ecological research, disaster management, etc. According to recent advances in sensor technologies, several types of remotely sensed data are available from the same area. Data fusion has been widely investigated for integrating different source of data in classification of urban area. Thermal infrared imagery (TIR) contains information on emitted radiation and has unique radiometric properties. However, due to coarse spatial resolution of thermal data, its application has been restricted in urban areas. On the other hand, visible image (VIS) has high spatial resolution and information in visible spectrum. Consequently, there is a complementary relation between thermal and visible imagery in classification of urban area. This paper evaluates the potential of aerial thermal hyperspectral and visible imagery fusion in classification of urban area. In the pre-processing step, thermal imagery is resampled to the spatial resolution of visible image. Then feature level fusion is applied to construct hybrid feature space include visible bands, thermal hyperspectral bands, spatial and texture features and moreover Principle Component Analysis (PCA) transformation is applied to extract PCs. Due to high dimensionality of feature space, dimension reduction method is performed. Finally, Support Vector Machines (SVMs) classify the reduced hybrid feature space. The obtained results show using thermal imagery along with visible imagery, improved the classification accuracy up to 8% respect to visible image classification.

Looking at Earth from Space: Teacher's Guide with Activities for Earth and Space Science

NASA Technical Reports Server (NTRS)

Steele, Colleen (Editor); Steele, Colleen; Ryan, William F.

1995-01-01

The Maryland Pilot Earth Science and Technology Education Network (MAPS-NET) project was sponsored by the National Aeronautics and Space Administration (NASA) to enrich teacher preparation and classroom learning in the area of Earth system science. This publication includes a teacher's guide that replicates material taught during a graduate-level course of the project and activities developed by the teachers. The publication was developed to provide teachers with a comprehensive approach to using satellite imagery to enhance science education. The teacher's guide is divided into topical chapters and enables teachers to expand their knowledge of the atmosphere, common weather patterns, and remote sensing. Topics include: weather systems and satellite imagery including mid-latitude weather systems; wave motion and the general circulation; cyclonic disturbances and baroclinic instability; clouds; additional common weather patterns; satellite images and the internet; environmental satellites; orbits; and ground station set-up. Activities are listed by suggested grade level and include the following topics: using weather symbols; forecasting the weather; cloud families and identification; classification of cloud types through infrared Automatic Picture Transmission (APT) imagery; comparison of visible and infrared imagery; cold fronts; to ski or not to ski (imagery as a decision making tool), infrared and visible satellite images; thunderstorms; looping satellite images; hurricanes; intertropical convergence zone; and using weather satellite images to enhance a study of the Chesapeake Bay. A list of resources is also included.

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

NASA Astrophysics Data System (ADS)

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.

Proceedings of the Second Annual Symposium on Mathematical Pattern Recognition and Image Analysis Program

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr. (Principal Investigator)

1984-01-01

Several papers addressing image analysis and pattern recognition techniques for satellite imagery are presented. Texture classification, image rectification and registration, spatial parameter estimation, and surface fitting are discussed.

Assessment of Southern California environment from ERTS-1

NASA Technical Reports Server (NTRS)

Bowden, L. W.; Viellenave, J. H.

1973-01-01

ERTS-1 imagery is a useful source of data for evaluation of earth resources in Southern California. The improving quality of ERTS-1 imagery, and our increasing ability to enhance the imagery has resulted in studies of a variety of phenomena in several Southern California environments. These investigations have produced several significant results of varying detail. They include the detection and identification of macro-scale tectonic and vegetational patterns, as well as detailed analysis of urban and agricultural processes. The sequential nature of ERTS-1 imagery has allowed these studies to monitor significant changes in the environment. In addiation, some preliminary work has begun directed toward assessing the impact of expanding recreation, agriculture and urbanization into the fragile desert environment. Refinement of enhancement and mapping techniques and more intensive analysis of ERTS-1 imagery should lead to a greater capability to extract detailed information for more precise evaluations and more accurate monitoring of earth resources in Southern California.

Thermal study of the Missouri River in North Dakota using infrared imagery

NASA Technical Reports Server (NTRS)

Crosby, O. A.

1971-01-01

Studies of infrared imagery obtained from aircraft at 305- to 1,524-meter altitudes indicate the feasibility of monitoring thermal changes attributable to the operation of thermal electric plants and storage reservoirs, as well as natural phenomena such as tributary inflow and ground water seeps in large rivers. No identifiable sources of ground water inflow below the surface of the river could be found in the imagery. The thermal patterns from the generating plants and the major tributary inflow are readily apparent in imagery obtained from an altitude of 305 meters. Portions of the tape-recorded imagery were processed in a color-coded quantization to enhance the displays and to attach quantitative significance to the data. The study indicates a marked decrease in water temperature in the Missouri River prior to early fall and a moderate increase in temperature in late fall because of the Lake Sakakawea impoundment.

Influence of mental imagery on spatial presence and enjoyment assessed in different types of media.

PubMed

Weibel, David; Wissmath, Bartholomäus; Mast, Fred W

2011-10-01

Previous research studies on spatial presence point out that the users' imagery abilities are of importance. However, this influence has not yet been tested for different media. This is surprising because theoretical considerations suggest that mental imagery comes into play when a mediated environment lacks vividness. The aim of this study was to clarify the influence mental imagery abilities can have on the sensation of presence and enjoyment in different mediated environments. We presented the participants (n = 60) a narrative text, a movie sequence, and a computer game. Across all media, no effect of mental imagery abilities on presence and enjoyment was found, but imagery abilities marginally interacted with the mediated environment. Individuals with high imagery abilities experienced more presence and enjoyment in the text condition. The results were different for the film condition: here, individuals with poor imagery abilities reported marginally higher enjoyment ratings, whereas the presence ratings did not differ between the two groups. Imagery abilities had no influence on presence and enjoyment within the computer game condition. The results suggest that good imagery abilities contribute to the sensations of presence and enjoyment when reading a narrative text. The results for this study have an applied impact for media use because their effectiveness can depend on the individual mental imagery abilities.

A RESEARCH PLAN FOR THE USE OF THERMAL AVHRR IMAGERY TO STUDY ANNUAL AND SEASONAL MEAN SURFACE TEMPERATURES FOR LARGE LAKES IN NORTH AMERICA

EPA Science Inventory

Surface and vertical temperature data will be obtained from several large lakes With surface areas large enough to be effectively sampled with AVHRR imagery. Yearly and seasonal patterns of surface and whole water column thermal values will be compared to estimates of surface tem...

Utilizing ERTS imagery to detect plant diseases and nutrient deficiencies, soil types and soil moisture levels

NASA Technical Reports Server (NTRS)

Parks, W. L. (Principal Investigator); Sewell, J. I.; Hilty, J. W.; Rennie, J. C.

1973-01-01

The author has identified the following significant results. The delineation of soil associations and detection of drainage patterns, erosion and sedimentation through the use of ERTS-1 imagery are shown. Corn blight and corn virus could not be detected from ERTS-1 and detection of forest composition was at a very low probability.

Using the spatial and spectral precision of satellite imagery to predict wildlife occurrence patterns.

Treesearch

Edward J. Laurent; Haijin Shi; Demetrios Gatziolis; Joseph P. LeBouton; Michael B. Walters; Jianguo Liu

2005-01-01

We investigated the potential of using unclassified spectral data for predicting the distribution of three bird species over a -400,000 ha region of Michigan's Upper Peninsula using Landsat ETM+ imagery and 433 locations sampled for birds through point count surveys. These species, Black-throated Green Warbler, Nashville Warbler, and Ovenbird. were known to be...

Change detection in Arctic satellite imagery using clustering of sparse approximations (CoSA) over learned feature dictionaries

NASA Astrophysics Data System (ADS)

Moody, Daniela I.; Wilson, Cathy J.; Rowland, Joel C.; Altmann, Garrett L.

2015-06-01

Advanced pattern recognition and computer vision algorithms are of great interest for landscape characterization, change detection, and change monitoring in satellite imagery, in support of global climate change science and modeling. We present results from an ongoing effort to extend neuroscience-inspired models for feature extraction to the environmental sciences, and we demonstrate our work using Worldview-2 multispectral satellite imagery. We use a Hebbian learning rule to derive multispectral, multiresolution dictionaries directly from regional satellite normalized band difference index data. These feature dictionaries are used to build sparse scene representations, from which we automatically generate land cover labels via our CoSA algorithm: Clustering of Sparse Approximations. These data adaptive feature dictionaries use joint spectral and spatial textural characteristics to help separate geologic, vegetative, and hydrologic features. Land cover labels are estimated in example Worldview-2 satellite images of Barrow, Alaska, taken at two different times, and are used to detect and discuss seasonal surface changes. Our results suggest that an approach that learns from both spectral and spatial features is promising for practical pattern recognition problems in high resolution satellite imagery.

[The Changes in the Hemodynamic Activity of the Brain during Moroe Imagery Training with the Use of Brain-Computer Interface].

PubMed

Frolov, A A; Husek, D; Silchenko, A V; Tintera, Y; Rydlo, J

2016-01-01

With the use of functional MRI (fMRI), we studied the changes in brain hemodynamic activity of healthy subjects during motor imagery training with the use brain-computer interface (BCI), which is based on the recognition of EEG patterns of imagined movements. ANOVA dispersion analysis showed there are 14 areas of the brain where statistically sgnificant changes were registered. Detailed analysis of the activity in these areas before and after training (Student's and Mann-Whitney tests) reduced the amount of areas with significantly changed activity to five; these are Brodmann areas 44 and 45, insula, middle frontal gyrus, and anterior cingulate gyrus. We suggest that these changes are caused by the formation of memory traces of those brain activity patterns which are most accurately recognized by BCI classifiers as correspondent with limb movements. We also observed a tendency of increase in the activity of motor imagery after training. The hemodynamic activity in all these 14 areas during real movements was either approximatly the same or significantly higher than during motor imagery; activity during imagined leg movements was higher that that during imagined arm movements, except for the areas of representation of arms.

Structure constrained semi-nonnegative matrix factorization for EEG-based motor imagery classification.

PubMed

Lu, Na; Li, Tengfei; Pan, Jinjin; Ren, Xiaodong; Feng, Zuren; Miao, Hongyu

2015-05-01

Electroencephalogram (EEG) provides a non-invasive approach to measure the electrical activities of brain neurons and has long been employed for the development of brain-computer interface (BCI). For this purpose, various patterns/features of EEG data need to be extracted and associated with specific events like cue-paced motor imagery. However, this is a challenging task since EEG data are usually non-stationary time series with a low signal-to-noise ratio. In this study, we propose a novel method, called structure constrained semi-nonnegative matrix factorization (SCS-NMF), to extract the key patterns of EEG data in time domain by imposing the mean envelopes of event-related potentials (ERPs) as constraints on the semi-NMF procedure. The proposed method is applicable to general EEG time series, and the extracted temporal features by SCS-NMF can also be combined with other features in frequency domain to improve the performance of motor imagery classification. Real data experiments have been performed using the SCS-NMF approach for motor imagery classification, and the results clearly suggest the superiority of the proposed method. Comparison experiments have also been conducted. The compared methods include ICA, PCA, Semi-NMF, Wavelets, EMD and CSP, which further verified the effectivity of SCS-NMF. The SCS-NMF method could obtain better or competitive performance over the state of the art methods, which provides a novel solution for brain pattern analysis from the perspective of structure constraint. Copyright © 2015 Elsevier Ltd. All rights reserved.

A multi-scale analysis of landscape statistics

Treesearch

Douglas H. Cain; Kurt H. Riitters; Kenneth Orvis

1997-01-01

It is now feasible to monitor some aspects of landscape ecological condition nationwide using remotely- sensed imagery and indicators of land cover pattern. Previous research showed redundancies among many reported pattern indicators and identified six unique dimensions of land cover pattern. This study tested the stability of those dimensions and representative...

Automated detection of slum area change in Hyderabad, India using multitemporal satellite imagery

NASA Astrophysics Data System (ADS)

Kit, Oleksandr; Lüdeke, Matthias

2013-09-01

This paper presents an approach to automated identification of slum area change patterns in Hyderabad, India, using multi-year and multi-sensor very high resolution satellite imagery. It relies upon a lacunarity-based slum detection algorithm, combined with Canny- and LSD-based imagery pre-processing routines. This method outputs plausible and spatially explicit slum locations for the whole urban agglomeration of Hyderabad in years 2003 and 2010. The results indicate a considerable growth of area occupied by slums between these years and allow identification of trends in slum development in this urban agglomeration.

Radar systems for the water resources mission, volume 2

NASA Technical Reports Server (NTRS)

Moore, R. K.; Claassen, J. P.; Erickson, R. L.; Fong, R. K. T.; Hanson, B. C.; Komen, M. J.; Mcmillan, S. B.; Parashar, S. K.

1976-01-01

The application of synthetic aperture radar (SAR) in monitoring and managing earth resources was examined. The function of spaceborne radar is to provide maps and map imagery to be used for earth resource and oceanographic applications. Spaceborne radar has the capability of mapping the entire United States regardless of inclement weather; however, the imagery must have a high degree of resolution to be meaningful. Attaining this resolution is possible with the SAR system. Imagery of the required quality must first meet mission parameters in the following areas: antenna patterns, azimuth and range ambiguities, coverage, and angle of incidence.

Effects of music on arousal during imagery in elite shooters: A pilot study.

PubMed

Kuan, Garry; Morris, Tony; Terry, Peter

2017-01-01

Beneficial effects of music on several performance-related aspects of sport have been reported, but the processes involved are not well understood. The purpose of the present study was to investigate effects of relaxing and arousing classical music on physiological indicators and subjective perceptions of arousal during imagery of a sport task. First, appropriate music excerpts were selected. Then, 12 skilled shooters performed shooting imagery while listening to the three preselected music excerpts in randomized order. Participants' galvanic skin response, peripheral temperature, and electromyography were monitored during music played concurrently with imagery. Subjective music ratings and physiological measures showed, as hypothesized, that unfamiliar relaxing music was the most relaxing and unfamiliar arousing music was the most arousing. Researchers should examine the impact of unfamiliar relaxing and arousing music played during imagery on subsequent performance in diverse sports. Practitioners can apply unfamiliar relaxing and arousing music with imagery to manipulate arousal level.

Effects of music on arousal during imagery in elite shooters: A pilot study

PubMed Central

Kuan, Garry; Morris, Tony; Terry, Peter

2017-01-01

Beneficial effects of music on several performance-related aspects of sport have been reported, but the processes involved are not well understood. The purpose of the present study was to investigate effects of relaxing and arousing classical music on physiological indicators and subjective perceptions of arousal during imagery of a sport task. First, appropriate music excerpts were selected. Then, 12 skilled shooters performed shooting imagery while listening to the three preselected music excerpts in randomized order. Participants’ galvanic skin response, peripheral temperature, and electromyography were monitored during music played concurrently with imagery. Subjective music ratings and physiological measures showed, as hypothesized, that unfamiliar relaxing music was the most relaxing and unfamiliar arousing music was the most arousing. Researchers should examine the impact of unfamiliar relaxing and arousing music played during imagery on subsequent performance in diverse sports. Practitioners can apply unfamiliar relaxing and arousing music with imagery to manipulate arousal level. PMID:28414741

The functional impact of mental imagery on conscious perception

PubMed Central

Pearson, Joel; Clifford, Colin; Tong, Frank

2008-01-01

Summary Mental imagery has been proposed to contribute to a variety of high-level cognitive functions, including memory encoding and retrieval, navigation and spatial planning, and even social communication and language comprehension [1–5]. However, it is debated whether mental imagery relies on the same sensory representations as perception [1, 6–10], and if so, what functional consequences such an overlap might have on perception itself. We report novel evidence that single instances of imagery can have a pronounced facilitatory influence on subsequent conscious perception. Either seeing or imagining a specific pattern could strongly bias which of two competing stimuli reach awareness during binocular rivalry. Effects of imagery and perception were location- and orientation-specific, accumulated in strength over time, and survived an intervening visual task lasting several seconds prior to presentation of the rivalry display. Interestingly, effects of imagery differed from those of feature-based attention. The results demonstrate that imagery, in the absence of any incoming visual signals, leads to the formation of a short-term sensory trace that can bias future perception, suggesting a means by which high-level processes that support imagination and memory retrieval may shape low-level sensory representations. PMID:18583132

Cortico-subcortical activation patterns for itch and pain imagery.

PubMed

Mochizuki, Hideki; Baumgärtner, Ulf; Kamping, Sandra; Ruttorf, Michaela; Schad, Lothar R; Flor, Herta; Kakigi, Ryusuke; Treede, Rolf-Detlef

2013-10-01

The imagery of itch and pain evokes emotional responses and covert motor responses (scratching to itch and withdrawal to pain). This suggests some similarity in cerebral mechanisms. However, itch is more socially contagious than pain, as evidenced by the fact that scratching behaviors can be easily initiated by watching itch-inducing situations, whereas withdrawal is less easily initiated by watching painful situations. Thus, we assumed that the cerebral mechanisms of itch imagery partly differ from those of pain imagery in particular with respect to motor regions. We addressed this issue in 18 healthy subjects using functional magnetic resonance imaging. The subjects were instructed to imagine itch and pain sensations in their own bodies while viewing pictures depicting stimuli associated with these sensations. Itch and pain imagery activated the anterior insular cortex (aIC) and motor-related regions such as supplementary motor area, basal ganglia, thalamus, and cerebellum. Activity in these regions was not significantly different between itch and pain imagery. However, functional connectivity between motor-related regions and the aIC showed marked differences between itch and pain imagery. Connectivity with the aIC was stronger in the primary motor and premotor cortices during pain imagery and stronger in the globus pallidus during itch imagery. These findings indicate that brain regions associated with imagery of itch are the same as those involved in imagery of pain, but their functional networks differ. These differences in brain networks may explain why motor responses to itch are more socially contagious than those related to pain. Copyright © 2013 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

Trends in Correlation-Based Pattern Recognition and Tracking in Forward-Looking Infrared Imagery

PubMed Central

Alam, Mohammad S.; Bhuiyan, Sharif M. A.

2014-01-01

In this paper, we review the recent trends and advancements on correlation-based pattern recognition and tracking in forward-looking infrared (FLIR) imagery. In particular, we discuss matched filter-based correlation techniques for target detection and tracking which are widely used for various real time applications. We analyze and present test results involving recently reported matched filters such as the maximum average correlation height (MACH) filter and its variants, and distance classifier correlation filter (DCCF) and its variants. Test results are presented for both single/multiple target detection and tracking using various real-life FLIR image sequences. PMID:25061840

Application of Geostatistical Simulation to Enhance Satellite Image Products

NASA Technical Reports Server (NTRS)

Hlavka, Christine A.; Dungan, Jennifer L.; Thirulanambi, Rajkumar; Roy, David

2004-01-01

With the deployment of Earth Observing System (EOS) satellites that provide daily, global imagery, there is increasing interest in defining the limitations of the data and derived products due to its coarse spatial resolution. Much of the detail, i.e. small fragments and notches in boundaries, is lost with coarse resolution imagery such as the EOS MODerate-Resolution Imaging Spectroradiometer (MODIS) data. Higher spatial resolution data such as the EOS Advanced Spaceborn Thermal Emission and Reflection Radiometer (ASTER), Landsat and airborne sensor imagery provide more detailed information but are less frequently available. There are, however, both theoretical and analytical evidence that burn scars and other fragmented types of land covers form self-similar or self-affine patterns, that is, patterns that look similar when viewed at widely differing spatial scales. Therefore small features of the patterns should be predictable, at least in a statistical sense, with knowledge about the large features. Recent developments in fractal modeling for characterizing the spatial distribution of undiscovered petroleum deposits are thus applicable to generating simulations of finer resolution satellite image products. We will present example EOS products, analysis to investigate self-similarity, and simulation results.

Accuracy of lineaments mapping from space

NASA Technical Reports Server (NTRS)

Short, Nicholas M.

1989-01-01

The use of Landsat and other space imaging systems for lineaments detection is analyzed in terms of their effectiveness in recognizing and mapping fractures and faults, and the results of several studies providing a quantitative assessment of lineaments mapping accuracies are discussed. The cases under investigation include a Landsat image of the surface overlying a part of the Anadarko Basin of Oklahoma, the Landsat images and selected radar imagery of major lineaments systems distributed over much of Canadian Shield, and space imagery covering a part of the East African Rift in Kenya. It is demonstrated that space imagery can detect a significant portion of a region's fracture pattern, however, significant fractions of faults and fractures recorded on a field-produced geological map are missing from the imagery as it is evident in the Kenya case.

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

NASA Astrophysics Data System (ADS)

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.

Proceedings of the NASA Symposium on Mathematical Pattern Recognition and Image Analysis

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr.

1983-01-01

The application of mathematical and statistical analyses techniques to imagery obtained by remote sensors is described by Principal Investigators. Scene-to-map registration, geometric rectification, and image matching are among the pattern recognition aspects discussed.

Choosing a DIVA: a comparison of emerging digital imagery vegetation analysis techniques

USGS Publications Warehouse

Jorgensen, Christopher F.; Stutzman, Ryan J.; Anderson, Lars C.; Decker, Suzanne E.; Powell, Larkin A.; Schacht, Walter H.; Fontaine, Joseph J.

2013-01-01

Question: What is the precision of five methods of measuring vegetation structure using ground-based digital imagery and processing techniques? Location: Lincoln, Nebraska, USA Methods: Vertical herbaceous cover was recorded using digital imagery techniques at two distinct locations in a mixed-grass prairie. The precision of five ground-based digital imagery vegetation analysis (DIVA) methods for measuring vegetation structure was tested using a split-split plot analysis of covariance. Variability within each DIVA technique was estimated using coefficient of variation of mean percentage cover. Results: Vertical herbaceous cover estimates differed among DIVA techniques. Additionally, environmental conditions affected the vertical vegetation obstruction estimates for certain digital imagery methods, while other techniques were more adept at handling various conditions. Overall, percentage vegetation cover values differed among techniques, but the precision of four of the five techniques was consistently high. Conclusions: DIVA procedures are sufficient for measuring various heights and densities of standing herbaceous cover. Moreover, digital imagery techniques can reduce measurement error associated with multiple observers' standing herbaceous cover estimates, allowing greater opportunity to detect patterns associated with vegetation structure.

Feature Selection for Motor Imagery EEG Classification Based on Firefly Algorithm and Learning Automata

PubMed Central

Liu, Aiming; Liu, Quan; Ai, Qingsong; Xie, Yi; Chen, Anqi

2017-01-01

Motor Imagery (MI) electroencephalography (EEG) is widely studied for its non-invasiveness, easy availability, portability, and high temporal resolution. As for MI EEG signal processing, the high dimensions of features represent a research challenge. It is necessary to eliminate redundant features, which not only create an additional overhead of managing the space complexity, but also might include outliers, thereby reducing classification accuracy. The firefly algorithm (FA) can adaptively select the best subset of features, and improve classification accuracy. However, the FA is easily entrapped in a local optimum. To solve this problem, this paper proposes a method of combining the firefly algorithm and learning automata (LA) to optimize feature selection for motor imagery EEG. We employed a method of combining common spatial pattern (CSP) and local characteristic-scale decomposition (LCD) algorithms to obtain a high dimensional feature set, and classified it by using the spectral regression discriminant analysis (SRDA) classifier. Both the fourth brain–computer interface competition data and real-time data acquired in our designed experiments were used to verify the validation of the proposed method. Compared with genetic and adaptive weight particle swarm optimization algorithms, the experimental results show that our proposed method effectively eliminates redundant features, and improves the classification accuracy of MI EEG signals. In addition, a real-time brain–computer interface system was implemented to verify the feasibility of our proposed methods being applied in practical brain–computer interface systems. PMID:29117100

Feature Selection for Motor Imagery EEG Classification Based on Firefly Algorithm and Learning Automata.

PubMed

Liu, Aiming; Chen, Kun; Liu, Quan; Ai, Qingsong; Xie, Yi; Chen, Anqi

2017-11-08

Motor Imagery (MI) electroencephalography (EEG) is widely studied for its non-invasiveness, easy availability, portability, and high temporal resolution. As for MI EEG signal processing, the high dimensions of features represent a research challenge. It is necessary to eliminate redundant features, which not only create an additional overhead of managing the space complexity, but also might include outliers, thereby reducing classification accuracy. The firefly algorithm (FA) can adaptively select the best subset of features, and improve classification accuracy. However, the FA is easily entrapped in a local optimum. To solve this problem, this paper proposes a method of combining the firefly algorithm and learning automata (LA) to optimize feature selection for motor imagery EEG. We employed a method of combining common spatial pattern (CSP) and local characteristic-scale decomposition (LCD) algorithms to obtain a high dimensional feature set, and classified it by using the spectral regression discriminant analysis (SRDA) classifier. Both the fourth brain-computer interface competition data and real-time data acquired in our designed experiments were used to verify the validation of the proposed method. Compared with genetic and adaptive weight particle swarm optimization algorithms, the experimental results show that our proposed method effectively eliminates redundant features, and improves the classification accuracy of MI EEG signals. In addition, a real-time brain-computer interface system was implemented to verify the feasibility of our proposed methods being applied in practical brain-computer interface systems.

Reading visually embodied meaning from the brain: Visually grounded computational models decode visual-object mental imagery induced by written text.

PubMed

Anderson, Andrew James; Bruni, Elia; Lopopolo, Alessandro; Poesio, Massimo; Baroni, Marco

2015-10-15

Embodiment theory predicts that mental imagery of object words recruits neural circuits involved in object perception. The degree of visual imagery present in routine thought and how it is encoded in the brain is largely unknown. We test whether fMRI activity patterns elicited by participants reading objects' names include embodied visual-object representations, and whether we can decode the representations using novel computational image-based semantic models. We first apply the image models in conjunction with text-based semantic models to test predictions of visual-specificity of semantic representations in different brain regions. Representational similarity analysis confirms that fMRI structure within ventral-temporal and lateral-occipital regions correlates most strongly with the image models and conversely text models correlate better with posterior-parietal/lateral-temporal/inferior-frontal regions. We use an unsupervised decoding algorithm that exploits commonalities in representational similarity structure found within both image model and brain data sets to classify embodied visual representations with high accuracy (8/10) and then extend it to exploit model combinations to robustly decode different brain regions in parallel. By capturing latent visual-semantic structure our models provide a route into analyzing neural representations derived from past perceptual experience rather than stimulus-driven brain activity. Our results also verify the benefit of combining multimodal data to model human-like semantic representations. Copyright © 2015 Elsevier Inc. All rights reserved.

Discrete cosine transform and hash functions toward implementing a (robust-fragile) watermarking scheme

NASA Astrophysics Data System (ADS)

Al-Mansoori, Saeed; Kunhu, Alavi

2013-10-01

This paper proposes a blind multi-watermarking scheme based on designing two back-to-back encoders. The first encoder is implemented to embed a robust watermark into remote sensing imagery by applying a Discrete Cosine Transform (DCT) approach. Such watermark is used in many applications to protect the copyright of the image. However, the second encoder embeds a fragile watermark using `SHA-1' hash function. The purpose behind embedding a fragile watermark is to prove the authenticity of the image (i.e. tamper-proof). Thus, the proposed technique was developed as a result of new challenges with piracy of remote sensing imagery ownership. This led researchers to look for different means to secure the ownership of satellite imagery and prevent the illegal use of these resources. Therefore, Emirates Institution for Advanced Science and Technology (EIAST) proposed utilizing existing data security concept by embedding a digital signature, "watermark", into DubaiSat-1 satellite imagery. In this study, DubaiSat-1 images with 2.5 meter resolution are used as a cover and a colored EIAST logo is used as a watermark. In order to evaluate the robustness of the proposed technique, a couple of attacks are applied such as JPEG compression, rotation and synchronization attacks. Furthermore, tampering attacks are applied to prove image authenticity.

Analysis and use of VAS satellite data

NASA Technical Reports Server (NTRS)

Fuelberg, Henry E.; Andrews, Mark J.; Beven, John L., II; Moore, Steven R.; Muller, Bradley M.

1989-01-01

Four interrelated investigations have examined the analysis and use of VAS satellite data. A case study of VAS-derived mesoscale stability parameters suggested that they would have been a useful supplement to conventional data in the forecasting of thunderstorms on the day of interest. A second investigation examined the roles of first guess and VAS radiometric data in producing sounding retrievals. Broad-scale patterns of the first guess, radiances, and retrievals frequently were similar, whereas small-scale retrieval features, especially in the dew points, were often of uncertain origin. Two research tasks considered 6.7 micron middle tropospheric water vapor imagery. The first utilized radiosonde data to examine causes for two areas of warm brightness temperature. Subsidence associated with a translating jet streak was important. The second task involving water vapor imagery investigated simulated imagery created from LAMPS output and a radiative transfer algorithm. Simulated image patterns were found to compare favorably with those actually observed by VAS. Furthermore, the mass/momentum fields from LAMPS were powerful tools for understanding causes for the image configurations.

A Ternary Hybrid EEG-NIRS Brain-Computer Interface for the Classification of Brain Activation Patterns during Mental Arithmetic, Motor Imagery, and Idle State.

PubMed

Shin, Jaeyoung; Kwon, Jinuk; Im, Chang-Hwan

2018-01-01

The performance of a brain-computer interface (BCI) can be enhanced by simultaneously using two or more modalities to record brain activity, which is generally referred to as a hybrid BCI. To date, many BCI researchers have tried to implement a hybrid BCI system by combining electroencephalography (EEG) and functional near-infrared spectroscopy (NIRS) to improve the overall accuracy of binary classification. However, since hybrid EEG-NIRS BCI, which will be denoted by hBCI in this paper, has not been applied to ternary classification problems, paradigms and classification strategies appropriate for ternary classification using hBCI are not well investigated. Here we propose the use of an hBCI for the classification of three brain activation patterns elicited by mental arithmetic, motor imagery, and idle state, with the aim to elevate the information transfer rate (ITR) of hBCI by increasing the number of classes while minimizing the loss of accuracy. EEG electrodes were placed over the prefrontal cortex and the central cortex, and NIRS optodes were placed only on the forehead. The ternary classification problem was decomposed into three binary classification problems using the "one-versus-one" (OVO) classification strategy to apply the filter-bank common spatial patterns filter to EEG data. A 10 × 10-fold cross validation was performed using shrinkage linear discriminant analysis (sLDA) to evaluate the average classification accuracies for EEG-BCI, NIRS-BCI, and hBCI when the meta-classification method was adopted to enhance classification accuracy. The ternary classification accuracies for EEG-BCI, NIRS-BCI, and hBCI were 76.1 ± 12.8, 64.1 ± 9.7, and 82.2 ± 10.2%, respectively. The classification accuracy of the proposed hBCI was thus significantly higher than those of the other BCIs ( p < 0.005). The average ITR for the proposed hBCI was calculated to be 4.70 ± 1.92 bits/minute, which was 34.3% higher than that reported for a previous binary hBCI study.

A numerical study of the ex-ROFI of the Colorado River

NASA Astrophysics Data System (ADS)

Carbajal, N.; Souza, A.; Durazo, R.

1997-08-01

The freshwater discharge of the Colorado River into the Gulf of California has been reduced to negligible quantities since the construction of the Hoover Dam in 1935. These radical anthropogenic changes in the hydrography of the Colorado River Delta had striking repercussions on both physical and biological processes. Using historical river discharge data, the changes in the flow dynamics and hydrographic patterns before and after the drastic freshwater reduction are studied numerically, using a three-dimensional nonlinear shelf model. The results are applied to assess the environmental impact of the reduction of river discharge on the area. Satellite imagery is also used to compare our results with observed fronts.

HCMM and LANDSAT imagery for geological mapping in northwest Queensland. [Australia

NASA Technical Reports Server (NTRS)

Cole, M. M.; Edmiston, D. J. (Principal Investigator)

1980-01-01

The author has identified the following significant results. Photographic prints made from negatives of day-visible and day-IR cover of selected areas were compared with enhanced color composites generated from LANDSAT computer compatible tapes and films. For geological mapping purposes, HCMM imagery is of limited value. While large scale features like the Mikadoodi anticlinorium, contrasting lithological units, and major structures may be distinguished on day-visible and day-IR cover, the spectral bands are too broad and the resolution too coarse even for regional mapping purposes. The imagery appears to be most useful for drainage studies. Where drainage is seasonal, sequential imagery permits monitoring of broad scale water movement while the day-IR imagery yields valuable information on former channels. In plains areas subject to periodic change of stream courses, comparable IR cover at a larger scale would offer considerable potential for reconstruction of former drainage patterns essential for the correct interpretation of geochemical data relative to mineral exploration.

High-resolution satellite imagery is an important yet underutilized resource in conservation biology.

PubMed

Boyle, Sarah A; Kennedy, Christina M; Torres, Julio; Colman, Karen; Pérez-Estigarribia, Pastor E; de la Sancha, Noé U

2014-01-01

Technological advances and increasing availability of high-resolution satellite imagery offer the potential for more accurate land cover classifications and pattern analyses, which could greatly improve the detection and quantification of land cover change for conservation. Such remotely-sensed products, however, are often expensive and difficult to acquire, which prohibits or reduces their use. We tested whether imagery of high spatial resolution (≤5 m) differs from lower-resolution imagery (≥30 m) in performance and extent of use for conservation applications. To assess performance, we classified land cover in a heterogeneous region of Interior Atlantic Forest in Paraguay, which has undergone recent and dramatic human-induced habitat loss and fragmentation. We used 4 m multispectral IKONOS and 30 m multispectral Landsat imagery and determined the extent to which resolution influenced the delineation of land cover classes and patch-level metrics. Higher-resolution imagery more accurately delineated cover classes, identified smaller patches, retained patch shape, and detected narrower, linear patches. To assess extent of use, we surveyed three conservation journals (Biological Conservation, Biotropica, Conservation Biology) and found limited application of high-resolution imagery in research, with only 26.8% of land cover studies analyzing satellite imagery, and of these studies only 10.4% used imagery ≤5 m resolution. Our results suggest that high-resolution imagery is warranted yet under-utilized in conservation research, but is needed to adequately monitor and evaluate forest loss and conversion, and to delineate potentially important stepping-stone fragments that may serve as corridors in a human-modified landscape. Greater access to low-cost, multiband, high-resolution satellite imagery would therefore greatly facilitate conservation management and decision-making.

Estimation of Vegetation Aerodynamic Roughness of Natural Regions Using Frontal Area Density Determined from Satellite Imagery

NASA Technical Reports Server (NTRS)

Jasinski, Michael F.; Crago, Richard

1994-01-01

Parameterizations of the frontal area index and canopy area index of natural or randomly distributed plants are developed, and applied to the estimation of local aerodynamic roughness using satellite imagery. The formulas are expressed in terms of the subpixel fractional vegetation cover and one non-dimensional geometric parameter that characterizes the plant's shape. Geometrically similar plants and Poisson distributed plant centers are assumed. An appropriate averaging technique to extend satellite pixel-scale estimates to larger scales is provided. ne parameterization is applied to the estimation of aerodynamic roughness using satellite imagery for a 2.3 sq km coniferous portion of the Landes Forest near Lubbon, France, during the 1986 HAPEX-Mobilhy Experiment. The canopy area index is estimated first for each pixel in the scene based on previous estimates of fractional cover obtained using Landsat Thematic Mapper imagery. Next, the results are incorporated into Raupach's (1992, 1994) analytical formulas for momentum roughness and zero-plane displacement height. The estimates compare reasonably well to reference values determined from measurements taken during the experiment and to published literature values. The approach offers the potential for estimating regionally variable, vegetation aerodynamic roughness lengths over natural regions using satellite imagery when there exists only limited knowledge of the vegetated surface.

Real-time image processing for passive mmW imagery

NASA Astrophysics Data System (ADS)

Kozacik, Stephen; Paolini, Aaron; Bonnett, James; Harrity, Charles; Mackrides, Daniel; Dillon, Thomas E.; Martin, Richard D.; Schuetz, Christopher A.; Kelmelis, Eric; Prather, Dennis W.

2015-05-01

The transmission characteristics of millimeter waves (mmWs) make them suitable for many applications in defense and security, from airport preflight scanning to penetrating degraded visual environments such as brownout or heavy fog. While the cold sky provides sufficient illumination for these images to be taken passively in outdoor scenarios, this utility comes at a cost; the diffraction limit of the longer wavelengths involved leads to lower resolution imagery compared to the visible or IR regimes, and the low power levels inherent to passive imagery allow the data to be more easily degraded by noise. Recent techniques leveraging optical upconversion have shown significant promise, but are still subject to fundamental limits in resolution and signal-to-noise ratio. To address these issues we have applied techniques developed for visible and IR imagery to decrease noise and increase resolution in mmW imagery. We have developed these techniques into fieldable software, making use of GPU platforms for real-time operation of computationally complex image processing algorithms. We present data from a passive, 77 GHz, distributed aperture, video-rate imaging platform captured during field tests at full video rate. These videos demonstrate the increase in situational awareness that can be gained through applying computational techniques in real-time without needing changes in detection hardware.

Guided Imagery as a Treatment Option for Fatigue

PubMed Central

Menzies, Victoria; Jallo, Nancy

2013-01-01

Purpose Fatigue is one of the most common complaints experienced among the general population. Because fatigue is recognized as a biobehavioral occurrence, a biobehavioral intervention such as guided imagery may be effective in reducing self-reported fatigue. Therefore, the purpose of this study was to explore the research literature related to the use of guided imagery as a nonpharmacological mind-body intervention for the symptom of fatigue. Method The electronic databases MEDLINE, CINAHL, PsychInfo, Psychology and Behavioral Sciences Collection and the Cochrane Library were searched from January 1980 to June 2010. Findings Of 24 articles retrieved, eight met the inclusion criteria and were included in this systematic literature review. Findings were inconsistent regarding the effectiveness of guided imagery on fatigue. Studies varied in study length, duration of the applied guided imagery intervention, dosage, and whether the images were targeted to the purpose of the intervention. Implications Guided imagery is a simple, economic intervention with the potential to effectively treat fatigue, thus further research is warranted using systematic, well-designed methodologies Standardizing guided imagery interventions according to total duration of exposure and targeted imagery in a variety of different populations adequately powered to detect changes will contribute to and strengthen nursing’s symptom-management armamentarium. PMID:21772047

Utilization of ERTS-1 data in North Carolina. [forested wetlands, water management, and land use

NASA Technical Reports Server (NTRS)

Welby, C. W. (Principal Investigator); Lammi, J. O.; Carson, R. J., III

1973-01-01

The author has identified the following significant results. ERTS-1 imagery has been used to study forested wetlands, dynamic processes off Coastal North Carolina, and land use patterns in the Wilmington, North Carolina area. The thrust of the investigation is still involvement of state and regional agencies in the use of ERTS-1 imagery in solving some of their day-to-day problems.

Landsat 8 Multispectral and Pansharpened Imagery Processing on the Study of Civil Engineering Issues

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

Decoding the direction of imagined visual motion using 7 T ultra-high field fMRI

PubMed Central

Emmerling, Thomas C.; Zimmermann, Jan; Sorger, Bettina; Frost, Martin A.; Goebel, Rainer

2016-01-01

There is a long-standing debate about the neurocognitive implementation of mental imagery. One form of mental imagery is the imagery of visual motion, which is of interest due to its naturalistic and dynamic character. However, so far only the mere occurrence rather than the specific content of motion imagery was shown to be detectable. In the current study, the application of multi-voxel pattern analysis to high-resolution functional data of 12 subjects acquired with ultra-high field 7 T functional magnetic resonance imaging allowed us to show that imagery of visual motion can indeed activate the earliest levels of the visual hierarchy, but the extent thereof varies highly between subjects. Our approach enabled classification not only of complex imagery, but also of its actual contents, in that the direction of imagined motion out of four options was successfully identified in two thirds of the subjects and with accuracies of up to 91.3% in individual subjects. A searchlight analysis confirmed the local origin of decodable information in striate and extra-striate cortex. These high-accuracy findings not only shed new light on a central question in vision science on the constituents of mental imagery, but also show for the first time that the specific sub-categorical content of visual motion imagery is reliably decodable from brain imaging data on a single-subject level. PMID:26481673

Application of multispectral radar and LANDSAT imagery to geologic mapping in death valley

NASA Technical Reports Server (NTRS)

Daily, M.; Elachi, C.; Farr, T.; Stromberg, W.; Williams, S.; Schaber, G.

1978-01-01

Side-Looking Airborne Radar (SLAR) images, acquired by JPL and Strategic Air Command Systems, and visible and near-infrared LANDSAT imagery were applied to studies of the Quaternary alluvial and evaporite deposits in Death Valley, California. Unprocessed radar imagery revealed considerable variation in microwave backscatter, generally correlated with surface roughness. For Death Valley, LANDSAT imagery is of limited value in discriminating the Quaternary units except for alluvial units distinguishable by presence or absence of desert varnish or evaporite units whose extremely rough surfaces are strongly shadowed. In contrast, radar returns are most strongly dependent on surface roughness, a property more strongly correlated with surficial geology than is surface chemistry.

Reconstruction of an infrared band of meteorological satellite imagery with abductive networks

NASA Technical Reports Server (NTRS)

Singer, Harvey A.; Cockayne, John E.; Versteegen, Peter L.

1995-01-01

As the current fleet of meteorological satellites age, the accuracy of the imagery sensed on a spectral channel of the image scanning system is continually and progressively degraded by noise. In time, that data may even become unusable. We describe a novel approach to the reconstruction of the noisy satellite imagery according to empirical functional relationships that tie the spectral channels together. Abductive networks are applied to automatically learn the empirical functional relationships between the data sensed on the other spectral channels to calculate the data that should have been sensed on the corrupted channel. Using imagery unaffected by noise, it is demonstrated that abductive networks correctly predict the noise-free observed data.

ERTS imagery for ground-water investigations

USGS Publications Warehouse

Moore, Gerald K.; Deutsch, Morris

1975-01-01

ERTS imagery offers the first opportunity to apply moderately high-resolution satellite data to the nationwide study of water resources. This imagery is both a tool and a form of basic data. Like other tools and basic data, it should be considered for use in ground-water investigations. The main advantage of its use will be to reduce the need for field work. In addition, however, broad regional features may be seen easily on ERTS imagery, whereas they would be difficult or impossible to see on the ground or on low-altitude aerial photographs. Some present and potential uses of ERTS imagery are to locate new aquifers, to study aquifer recharge and discharge, to estimate ground-water pumpage for irrigation, to predict the location and type of aquifer management problems, and to locate and monitor strip mines which commonly are sources for acid mine drainage. In many cases, boundaries which are gradational on the ground appear to be sharp on ERTS imagery. Initial results indicate that the accuracy of maps produced from ERTS imagery is completely adequate for some purposes.

[Mental Imagery: Neurophysiology and Implications in Psychiatry].

PubMed

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.

Environmental study of ERTS-1 imagery Lake Champlain Basin and Vermont

NASA Technical Reports Server (NTRS)

Lind, A. O. (Principal Investigator)

1972-01-01

The author has idenfified the following significant results. A first approximation land-type map using three categories of classification was generated for the Burlington area. The identification and mapping of a major turbidity front separating turbid waters of the southern arm of Lake Champlain from the clearer main water mass was reported on RBV 1 and 2 imagery and on subsequent MSS bands 4 and 5. Significant industrial pollution of Lake Champlain has degraded environmental quality in certain sections of the lake. Wetlands were detected and recognized using a combination of RBV bands 2 and 3. Using first-look RBV band 2 imagery, major ice marginal features were identified by using tonal patterns associated with vegetative cover. Major rivers were detected and recognized through the use of RBV band 3 imagery and MSS bands 6 and 7.

Vegetation changes caused by fire in the Florida flatwoods as observed by remote sensing

NASA Technical Reports Server (NTRS)

Mealor, W. T., Jr.; Prunty, M. C., Jr.

1969-01-01

The nature of the flatwoods and the role that ground fires have played in maintaining them are discussed. Emphasis is placed on the areal and temporal extent of burns as recorded uniformly by remote sensors. Thermal infrared, color infrared, and Ektachrome imagery were obtained from sensors flown by a NASA aircraft at 15,000 feet over a test site in Osceola County, Florida, in March 1968. The overall pattern of burning can be sequenced and mapped uniformly from the imagery. By comparing the various imagery, areal and temporal extent of burned areas can be determined. It was concluded that remote sensed imagery provides more accurate and areally comprehensive media for assessing the impact of ground fires on the landscape of the flatwoods region than are available from any other data source.

A Standardised Vocabulary for Identifying Benthic Biota and Substrata from Underwater Imagery: The CATAMI Classification Scheme

PubMed Central

Jordan, Alan; Rees, Tony; Gowlett-Holmes, Karen

2015-01-01

Imagery collected by still and video cameras is an increasingly important tool for minimal impact, repeatable observations in the marine environment. Data generated from imagery includes identification, annotation and quantification of biological subjects and environmental features within an image. To be long-lived and useful beyond their project-specific initial purpose, and to maximize their utility across studies and disciplines, marine imagery data should use a standardised vocabulary of defined terms. This would enable the compilation of regional, national and/or global data sets from multiple sources, contributing to broad-scale management studies and development of automated annotation algorithms. The classification scheme developed under the Collaborative and Automated Tools for Analysis of Marine Imagery (CATAMI) project provides such a vocabulary. The CATAMI classification scheme introduces Australian-wide acknowledged, standardised terminology for annotating benthic substrates and biota in marine imagery. It combines coarse-level taxonomy and morphology, and is a flexible, hierarchical classification that bridges the gap between habitat/biotope characterisation and taxonomy, acknowledging limitations when describing biological taxa through imagery. It is fully described, documented, and maintained through curated online databases, and can be applied across benthic image collection methods, annotation platforms and scoring methods. Following release in 2013, the CATAMI classification scheme was taken up by a wide variety of users, including government, academia and industry. This rapid acceptance highlights the scheme’s utility and the potential to facilitate broad-scale multidisciplinary studies of marine ecosystems when applied globally. Here we present the CATAMI classification scheme, describe its conception and features, and discuss its utility and the opportunities as well as challenges arising from its use. PMID:26509918

The fusion of satellite and UAV data: simulation of high spatial resolution band

NASA Astrophysics Data System (ADS)

Jenerowicz, Agnieszka; Siok, Katarzyna; Woroszkiewicz, Malgorzata; Orych, Agata

2017-10-01

Remote sensing techniques used in the precision agriculture and farming that apply imagery data obtained with sensors mounted on UAV platforms became more popular in the last few years due to the availability of low- cost UAV platforms and low- cost sensors. Data obtained from low altitudes with low- cost sensors can be characterised by high spatial and radiometric resolution but quite low spectral resolution, therefore the application of imagery data obtained with such technology is quite limited and can be used only for the basic land cover classification. To enrich the spectral resolution of imagery data acquired with low- cost sensors from low altitudes, the authors proposed the fusion of RGB data obtained with UAV platform with multispectral satellite imagery. The fusion is based on the pansharpening process, that aims to integrate the spatial details of the high-resolution panchromatic image with the spectral information of lower resolution multispectral or hyperspectral imagery to obtain multispectral or hyperspectral images with high spatial resolution. The key of pansharpening is to properly estimate the missing spatial details of multispectral images while preserving their spectral properties. In the research, the authors presented the fusion of RGB images (with high spatial resolution) obtained with sensors mounted on low- cost UAV platforms and multispectral satellite imagery with satellite sensors, i.e. Landsat 8 OLI. To perform the fusion of UAV data with satellite imagery, the simulation of the panchromatic bands from RGB data based on the spectral channels linear combination, was conducted. Next, for simulated bands and multispectral satellite images, the Gram-Schmidt pansharpening method was applied. As a result of the fusion, the authors obtained several multispectral images with very high spatial resolution and then analysed the spatial and spectral accuracies of processed images.

Imagining sex and adapting to it: different aftereffects after perceiving versus imagining faces.

PubMed

D'Ascenzo, Stefania; Tommasi, Luca; Laeng, Bruno

2014-03-01

A prolonged exposure (i.e., perceptual adaptation) to a male or a female face can produce changes (i.e., aftereffects) in the subsequent gender attribution of a neutral or average face, so that it appears respectively more female or more male. Studies using imagery adaptation and its aftereffects have yielded conflicting results. In the present study we used an adaptation paradigm with both imagined and perceived faces as adaptors, and assessed the aftereffects in judged masculinity/femininity when viewing an androgynous test face. We monitored eye movements and pupillary responses as a way to confirm whether participants did actively engage in visual imagery. The results indicated that both perceptual and imagery adaptation produce aftereffects, but that they run in opposite directions: a contrast effect with perception (e.g., after visual exposure to a female face, the androgynous appears as more male) and an assimilation effect with imagery (e.g., after imaginative exposure to a female face, the androgynous face appears as more female). The pupillary responses revealed dilations consistent with increased cognitive effort during the imagery phase, suggesting that the assimilation aftereffect occurred in the presence of an active and effortful mental imagery process, as also witnessed by the pattern of eye movements recorded during the imagery adaptation phase. Copyright © 2014 Elsevier B.V. All rights reserved.

Species classification using Unmanned Aerial Vehicle (UAV)-acquired high spatial resolution imagery in a heterogeneous grassland

NASA Astrophysics Data System (ADS)

Lu, Bing; He, Yuhong

2017-06-01

Investigating spatio-temporal variations of species composition in grassland is an essential step in evaluating grassland health conditions, understanding the evolutionary processes of the local ecosystem, and developing grassland management strategies. Space-borne remote sensing images (e.g., MODIS, Landsat, and Quickbird) with spatial resolutions varying from less than 1 m to 500 m have been widely applied for vegetation species classification at spatial scales from community to regional levels. However, the spatial resolutions of these images are not fine enough to investigate grassland species composition, since grass species are generally small in size and highly mixed, and vegetation cover is greatly heterogeneous. Unmanned Aerial Vehicle (UAV) as an emerging remote sensing platform offers a unique ability to acquire imagery at very high spatial resolution (centimetres). Compared to satellites or airplanes, UAVs can be deployed quickly and repeatedly, and are less limited by weather conditions, facilitating advantageous temporal studies. In this study, we utilize an octocopter, on which we mounted a modified digital camera (with near-infrared (NIR), green, and blue bands), to investigate species composition in a tall grassland in Ontario, Canada. Seven flight missions were conducted during the growing season (April to December) in 2015 to detect seasonal variations, and four of them were selected in this study to investigate the spatio-temporal variations of species composition. To quantitatively compare images acquired at different times, we establish a processing flow of UAV-acquired imagery, focusing on imagery quality evaluation and radiometric correction. The corrected imagery is then applied to an object-based species classification. Maps of species distribution are subsequently used for a spatio-temporal change analysis. Results indicate that UAV-acquired imagery is an incomparable data source for studying fine-scale grassland species composition, owing to its high spatial resolution. The overall accuracy is around 85% for images acquired at different times. Species composition is spatially attributed by topographical features and soil moisture conditions. Spatio-temporal variation of species composition implies the growing process and succession of different species, which is critical for understanding the evolutionary features of grassland ecosystems. Strengths and challenges of applying UAV-acquired imagery for vegetation studies are summarized at the end.

Window-based method for approximating the Hausdorff in three-dimensional range imagery

DOEpatents

Koch, Mark W [Albuquerque, NM

2009-06-02

One approach to pattern recognition is to use a template from a database of objects and match it to a probe image containing the unknown. Accordingly, the Hausdorff distance can be used to measure the similarity of two sets of points. In particular, the Hausdorff can measure the goodness of a match in the presence of occlusion, clutter, and noise. However, existing 3D algorithms for calculating the Hausdorff are computationally intensive, making them impractical for pattern recognition that requires scanning of large databases. The present invention is directed to a new method that can efficiently, in time and memory, compute the Hausdorff for 3D range imagery. The method uses a window-based approach.

Visual Imagery and Self-Questioning: Strategies to Improve Comprehension of Written Material.

ERIC Educational Resources Information Center

Clark, Frances L.; And Others

1984-01-01

Two learning strategies--visual imagery and self-questioning--designed to increase reading comprehension were taught to six learning disabled secondary students. Results indicate that LD students can learn the two strategies and can apply them in both reading ability level and grade level materials. Use of the strategies resulted in greater…

Feasibility study for automatic reduction of phase change imagery

NASA Technical Reports Server (NTRS)

Nossaman, G. O.

1971-01-01

The feasibility of automatically reducing a form of pictorial aerodynamic heating data is discussed. The imagery, depicting the melting history of a thin coat of fusible temperature indicator painted on an aerodynamically heated model, was previously reduced by manual methods. Careful examination of various lighting theories and approaches led to an experimentally verified illumination concept capable of yielding high-quality imagery. Both digital and video image processing techniques were applied to reduction of the data, and it was demonstrated that either method can be used to develop superimposed contours. Mathematical techniques were developed to find the model-to-image and the inverse image-to-model transformation using six conjugate points, and methods were developed using these transformations to determine heating rates on the model surface. A video system was designed which is able to reduce the imagery rapidly, economically and accurately. Costs for this system were estimated. A study plan was outlined whereby the mathematical transformation techniques developed to produce model coordinate heating data could be applied to operational software, and methods were discussed and costs estimated for obtaining the digital information necessary for this software.

Kinesthetic Imagery Provides Additive Benefits to Internal Visual Imagery on Slalom Task Performance.

PubMed

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.

Relating Change Patterns to Anthropogenic Processes to Assess Sustainability: A Case Study in Amazonia

Treesearch

Libia Patricia Peralta Agudelo

2006-01-01

This work focuses on identifying deforestation patterns and relating these to social processes in an extractive reserve of Acre (western Amazonia). Using multitemporal satellite imagery deforestation is observed as a series of distinctive patches against the background of forest cover. The study of patterns emphasizes the important relationships existing between...

Analysis by gender and Visual Imagery Reactivity of conventional and imagery Rorschach.

PubMed

Yanovski, A; Menduke, H; Albertson, M G

1995-06-01

Examined here are the effects of gender and Visual Imagery Reactivity in 80 consecutively selected psychiatric outpatients. The participants were grouped by gender and by the amounts of responsiveness to preceding therapy work using imagery (Imagery Nonreactors and Reactors). In the group of Imagery Nonreactors were 13 men and 22 women, and in the Reactor group were 17 men and 28 women. Compared were the responses to standard Rorschach (Conventional condition) with visual associations to memory images of Rorschach inkblots (Imagery condition). Responses were scored using the Visual Imagery Reactivity (VIR) scoring system, a general, test-nonspecific scoring method. Nonparametric statistical analysis showed that critical indicators of Imagery Reactivity encoded as High Affect/Conflict score and its derivatives associated with sexual or bizarre content were not significantly associated with gender; neither was Neutral Content score which categorizes "non-Reactivity." These results support the notion that system's criteria of Visual Imagery Reactivity can be applied equally to both men and women for the classification of Imagery Reactors and Nonreactors. Discussed are also the speculative consequences of extending the tolerance range of significance levels for the interaction between Reactivity and sex above the customary limit of p < .05 in borderline cases. The results of such an analysis may imply a trend towards more rigid defensiveness under Imagery and toward lesser verbal productivity in response to either the Conventional or the Imagery task among women who are Nonreactors. In Reactors, men produced significantly more Sexual Reference scores (in the subcategory not associated with High Affect/Conflict) than women, but this could be attributed to the effect of tester's and subjects' gender combined.

The application of satellite data in monitoring strip mines

NASA Technical Reports Server (NTRS)

Sharber, L. A.; Shahrokhi, F.

1977-01-01

Strip mines in the New River Drainage Basin of Tennessee were studied through use of Landsat-1 imagery and aircraft photography. A multilevel analysis, involving conventional photo interpretation techniques, densitometric methods, multispectral analysis and statistical testing was applied to the data. The Landsat imagery proved adequate for monitoring large-scale change resulting from active mining and land-reclamation projects. However, the spatial resolution of the satellite imagery rendered it inadequate for assessment of many smaller strip mines, in the region which may be as small as a few hectares.

Temporal coding of brain patterns for direct limb control in humans.

PubMed

Müller-Putz, Gernot R; Scherer, Reinhold; Pfurtscheller, Gert; Neuper, Christa

2010-01-01

For individuals with a high spinal cord injury (SCI) not only the lower limbs, but also the upper extremities are paralyzed. A neuroprosthesis can be used to restore the lost hand and arm function in those tetraplegics. The main problem for this group of individuals, however, is the reduced ability to voluntarily operate device controllers. A brain-computer interface provides a non-manual alternative to conventional input devices by translating brain activity patterns into control commands. We show that the temporal coding of individual mental imagery pattern can be used to control two independent degrees of freedom - grasp and elbow function - of an artificial robotic arm by utilizing a minimum number of EEG scalp electrodes. We describe the procedure from the initial screening to the final application. From eight naïve subjects participating online feedback experiments, four were able to voluntarily control an artificial arm by inducing one motor imagery pattern derived from one EEG derivation only.

California coast nearshore processes study. [nearshore currents, sediment transport, estuaries, and river discharge

NASA Technical Reports Server (NTRS)

Pirie, D. M.; Steller, D. D. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Large scale sediment plumes from intermittent streams and rivers form detectable seasonal patterns on ERTS-1 imagery. The ocean current systems, as plotted from three California coast ERTS mosaics, were identified. Offshore patterns of sediment in areas such as the Santa Barbara Channel are traceable. These patterns extend offshore to heretofore unanticipated ranges as shown on the ERTS-1 imagery. Flying spot scanner enhancements of NASA tapes resulted in details of subtle and often invisible (to the eye) nearshore features. The suspended sediments off San Francisco and in Monterey Bay are emphasized in detail. These are areas of extremely changeable offshore sediment transport patterns. Computer generated contouring of radiance levels resulted in maps that can be used in determining surface and nearsurface suspended sediment distribution. Tentative calibrations of ERTS-1 spectral brightness against sediment load have been made using shipboard measurements. Information from the combined enhancement and interpretation techniques is applicable to operational coastal engineering programs.

Towards Efficient Decoding of Multiple Classes of Motor Imagery Limb Movements Based on EEG Spectral and Time Domain Descriptors.

PubMed

Samuel, Oluwarotimi Williams; Geng, Yanjuan; Li, Xiangxin; Li, Guanglin

2017-10-28

To control multiple degrees of freedom (MDoF) upper limb prostheses, pattern recognition (PR) of electromyogram (EMG) signals has been successfully applied. This technique requires amputees to provide sufficient EMG signals to decode their limb movement intentions (LMIs). However, amputees with neuromuscular disorder/high level amputation often cannot provide sufficient EMG control signals, and thus the applicability of the EMG-PR technique is limited especially to this category of amputees. As an alternative approach, electroencephalograph (EEG) signals recorded non-invasively from the brain have been utilized to decode the LMIs of humans. However, most of the existing EEG based limb movement decoding methods primarily focus on identifying limited classes of upper limb movements. In addition, investigation on EEG feature extraction methods for the decoding of multiple classes of LMIs has rarely been considered. Therefore, 32 EEG feature extraction methods (including 12 spectral domain descriptors (SDDs) and 20 time domain descriptors (TDDs)) were used to decode multiple classes of motor imagery patterns associated with different upper limb movements based on 64-channel EEG recordings. From the obtained experimental results, the best individual TDD achieved an accuracy of 67.05 ± 3.12% as against 87.03 ± 2.26% for the best SDD. By applying a linear feature combination technique, an optimal set of combined TDDs recorded an average accuracy of 90.68% while that of the SDDs achieved an accuracy of 99.55% which were significantly higher than those of the individual TDD and SDD at p < 0.05. Our findings suggest that optimal feature set combination would yield a relatively high decoding accuracy that may improve the clinical robustness of MDoF neuroprosthesis. The study was approved by the ethics committee of Institutional Review Board of Shenzhen Institutes of Advanced Technology, and the reference number is SIAT-IRB-150515-H0077.

Area-based tests for association between spatial patterns

NASA Astrophysics Data System (ADS)

Maruca, Susan L.; Jacquez, Geoffrey M.

Edge effects pervade natural systems, and the processes that determine spatial heterogeneity (e.g. physical, geochemical, biological, ecological factors) occur on diverse spatial scales. Hence, tests for association between spatial patterns should be unbiased by edge effects and be based on null spatial models that incorporate the spatial heterogeneity characteristic of real-world systems. This paper develops probabilistic pattern association tests that are appropriate when edge effects are present, polygon size is heterogeneous, and the number of polygons varies from one classification to another. The tests are based on the amount of overlap between polygons in each of two partitions. Unweighted and area-weighted versions of the statistics are developed and verified using scenarios representing both polygon overlap and avoidance at different spatial scales and for different distributions of polygon sizes. These statistics were applied to Soda Butte Creek, Wyoming, to determine whether stream microhabitats, such as riffles, pools and glides, can be identified remotely using high spatial resolution hyperspectral imagery. These new ``spatially explicit'' techniques provide information and insights that cannot be obtained from the spectral information alone.

Vehicle detection and orientation estimation using the radon transform

NASA Astrophysics Data System (ADS)

Pelapur, Rengarajan; Bunyak, Filiz; Palaniappan, Kannappan; Seetharaman, Gunasekaran

2013-05-01

Determining the location and orientation of vehicles in satellite and airborne imagery is a challenging task given the density of cars and other vehicles and complexity of the environment in urban scenes almost anywhere in the world. We have developed a robust and accurate method for detecting vehicles using a template-based directional chamfer matching, combined with vehicle orientation estimation based on a refined segmentation, followed by a Radon transform based profile variance peak analysis approach. The same algorithm was applied to both high resolution satellite imagery and wide area aerial imagery and initial results show robustness to illumination changes and geometric appearance distortions. Nearly 80% of the orientation angle estimates for 1585 vehicles across both satellite and aerial imagery were accurate to within 15? of the ground truth. In the case of satellite imagery alone, nearly 90% of the objects have an estimated error within +/-1.0° of the ground truth.

Structural geology of the African rift system: Summary of new data from ERTS-1 imagery. [Precambrian influence

NASA Technical Reports Server (NTRS)

Mohr, P. A.

1974-01-01

ERTS imagery reveals for the first time the structural pattern of the African rift system as a whole. The strong influence of Precambrian structures on this pattern is clearly evident, especially along zones of cataclastic deformation, but the rift pattern is seen to be ultimately independent in origin and nature from Precambrian tectonism. Continuity of rift structures from one swell to another is noted. The widening of the Gregory rift as its northern end reflects an underlying Precambrian structural divergence, and is not a consequence of reaching the swell margin. Although the Western Rift is now proven to terminate at the Aswa Mylonite Zone, in southern Sudan, lineaments extend northeastwards from Lake Albert to the Eastern Rift at Lake Stefanie. The importance of en-echelon structures in the African rifts is seen to have been exaggerated.

Computer image processing in marine resource exploration

NASA Technical Reports Server (NTRS)

Paluzzi, P. R.; Normark, W. R.; Hess, G. R.; Hess, H. D.; Cruickshank, M. J.

1976-01-01

Pictographic data or imagery is commonly used in marine exploration. Pre-existing image processing techniques (software) similar to those used on imagery obtained from unmanned planetary exploration were used to improve marine photography and side-scan sonar imagery. Features and details not visible by conventional photo processing methods were enhanced by filtering and noise removal on selected deep-sea photographs. Information gained near the periphery of photographs allows improved interpretation and facilitates construction of bottom mosaics where overlapping frames are available. Similar processing techniques were applied to side-scan sonar imagery, including corrections for slant range distortion, and along-track scale changes. The use of digital data processing and storage techniques greatly extends the quantity of information that can be handled, stored, and processed.

Trial-by-trial adaptation of movements during mental practice under force field.

PubMed

Anwar, Muhammad Nabeel; Khan, Salman Hameed

2013-01-01

Human nervous system tries to minimize the effect of any external perturbing force by bringing modifications in the internal model. These modifications affect the subsequent motor commands generated by the nervous system. Adaptive compensation along with the appropriate modifications of internal model helps in reducing human movement errors. In the current study, we studied how motor imagery influences trial-to-trial learning in a robot-based adaptation task. Two groups of subjects performed reaching movements with or without motor imagery in a velocity-dependent force field. The results show that reaching movements performed with motor imagery have relatively a more focused generalization pattern and a higher learning rate in training direction.

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

NASA Technical Reports Server (NTRS)

Wier, C. E. (Principal Investigator); Powell, R. L.; Amato, R. V.; Russell, O. R.; Martin, K. R.

1975-01-01

The author has identified the following significant results. This investigation evaluated the applicability of a variety of sensor types, formats, and resolution capabilities to the study of both fuel and nonfuel mined lands. The image reinforcement provided by stereo viewing of the EREP images proved useful for identifying lineaments and for mined lands mapping. Skylab S190B color and color infrared transparencies were the most useful EREP imagery. New information on lineament and fracture patterns in the bedrock of Indiana and Illinois extracted from analysis of the Skylab imagery has contributed to furthering the geological understanding of this portion of the Illinois basin.

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

NASA Astrophysics Data System (ADS)

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 how much users would pay to replace Landsat imagery in the event of a data gap. Overall willingness to pay as well as willingness to pay by sector and citizenship will be reported. The results from this survey indicate that the value of Landsat imagery is substantial for the majority of users and that the loss of Landsat would negatively impact many users.

Performance of Scattering Matrix Decomposition and Color Spaces for Synthetic Aperture Radar Imagery

DTIC Science & Technology

2010-03-01

Color Spaces and Synthetic Aperture Radar (SAR) Multicolor Imaging. 15 2.3.1 Colorimetry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.3.2...III. Decomposition Techniques on SAR Polarimetry and Colorimetry applied to SAR Imagery...space polarimetric SAR systems. Colorimetry is also introduced in this chapter, presenting the fundamentals of the RGB and CMY color spaces, defined for

A summary of selected early results from the ERTS-1 menhaden experiment

NASA Technical Reports Server (NTRS)

Stevenson, W. H. (Principal Investigator); Kemmerer, A. J.; Benigno, J. A.; Reese, G. B.; Minkler, F. C.

1973-01-01

The author has identified the following significant results. Imagery from ERTS-1 satellite was used in conjunction with aerial photographically-sensed menhaden distribution information, sea truth oceanographic measurements, and commercial fishing information from a 8685 square kilometer study area in the north-central portion of the Gulf of Mexico to demonstrate relationships between selected oceanographic parameters and menhaden distribution, ERTS-1 imagery and menhaden distribution, and ERTS-1 imagery and oceanographic parameters. ERTS-1, MSS band 5 imagery density levels correlated with photographically detected menhaden distribution patterns and could be explained based on sea truth Secchi disc transparency and water depth measurements. These two parameters, together with surface salinity, Forel-Ule color, and chlorophyll-a also were found to correlate significantly with menhaden distribution. Eight empirical models were developed which provided menhaden distribution predictions for the study area on combinations of Secchi disc transparency, water depth, surface salinity, and Forel-Ule color measurements.

Analysis of EEG signals related to artists and nonartists during visual perception, mental imagery, and rest using approximate entropy.

PubMed

Shourie, Nasrin; Firoozabadi, Mohammad; Badie, Kambiz

2014-01-01

In this paper, differences between multichannel EEG signals of artists and nonartists were analyzed during visual perception and mental imagery of some paintings and at resting condition using approximate entropy (ApEn). It was found that ApEn is significantly higher for artists during the visual perception and the mental imagery in the frontal lobe, suggesting that artists process more information during these conditions. It was also observed that ApEn decreases for the two groups during the visual perception due to increasing mental load; however, their variation patterns are different. This difference may be used for measuring progress in novice artists. In addition, it was found that ApEn is significantly lower during the visual perception than the mental imagery in some of the channels, suggesting that visual perception task requires more cerebral efforts.

The application of airborne imaging radars (L and X-band) to earth resources problems

NASA Technical Reports Server (NTRS)

Drake, B.; Shuchman, R. A.; Bryan, M. L.; Larson, R. W.; Liskow, C. L.; Rendleman, R. A.

1974-01-01

A multiplexed synthetic aperture Side-Looking Airborne Radar (SLAR) that simultaneously images the terrain with X-band (3.2 cm) and L-band (23.0 cm) radar wavelengths was developed. The Feasibility of using multiplexed SLAR to obtain useful information for earth resources purposes. The SLAR imagery, aerial photographs, and infrared imagery are examined to determine the qualitative tone and texture of many rural land-use features imaged. The results show that: (1) Neither X- nor L-band SLAR at moderate and low depression angles can directly or indirectly detect pools of water under standing vegetation. (2) Many of the urban and rural land-use categories present in the test areas can be identified and mapped on the multiplexed SLAR imagery. (3) Water resources management can be done using multiplexed SLAR. (4) Drainage patterns can be determined on both the X- and L-band imagery.

Comparison between wavelet transform and moving average as filter method of MODIS imagery to recognize paddy cropping pattern in West Java

NASA Astrophysics Data System (ADS)

Dwi Nugroho, Kreshna; Pebrianto, Singgih; Arif Fatoni, Muhammad; Fatikhunnada, Alvin; Liyantono; Setiawan, Yudi

2017-01-01

Information on the area and spatial distribution of paddy field are needed to support sustainable agricultural and food security program. Mapping or distribution of cropping pattern paddy field is important to obtain sustainability paddy field area. It can be done by direct observation and remote sensing method. This paper discusses remote sensing for paddy field monitoring based on MODIS time series data. In time series MODIS data, difficult to direct classified of data, because of temporal noise. Therefore wavelet transform and moving average are needed as filter methods. The Objective of this study is to recognize paddy cropping pattern with wavelet transform and moving average in West Java using MODIS imagery (MOD13Q1) from 2001 to 2015 then compared between both of methods. The result showed the spatial distribution almost have the same cropping pattern. The accuracy of wavelet transform (75.5%) is higher than moving average (70.5%). Both methods showed that the majority of the cropping pattern in West Java have pattern paddy-fallow-paddy-fallow with various time planting. The difference of the planting schedule was occurs caused by the availability of irrigation water.

Variation in the Mississippi River Plume from Data Synthesis of Model Outputs and MODIS Imagery

NASA Astrophysics Data System (ADS)

Fitzpatrick, C.; Kolker, A.; Chu, P. Y.

2017-12-01

Understanding the Mississippi River (MR) plume's interaction with the open ocean is crucial for understanding many processes in the Gulf of Mexico. Though the Mississippi River and its delta and plume have been studied extensively, recent archives of model products and satellite imagery have allowed us to highlight patterns in plume behavior over the last two decades through large scale data synthesis. Using 8 years of USGS discharge data and Landsat imagery, we identified the spatial extent, geographic patterns, depth, and freshwater concentration of the MR plume across seasons and years. Using 20 years of HYCOM (HYbrid Coordinate Ocean Model) analysis and reanalysis model output, and several years of NGOFS FVCOM model outputs, we mapped the minimum and maximum spatial area of the MR plume, and its varied extent east and west. From the synthesis and analysis of these data, the statistical probability of the MR plume's spatial area and geographical extent were computed. Measurements of the MR plume and its response to river discharge may predict future behavior and provide a path forward to understanding MR plume influence on nearby ecosystems.

Evaluation of commercial utility of ERTS-A imagery in structural reconnaissance for minerals and petroleum

NASA Technical Reports Server (NTRS)

Saunders, D. F.; Thomas, G. E.

1973-01-01

Five areas in North America (North Slope-Alaska, Superior Province-Canada, Williston Basin-Montana, Colorado and New Mexico-West Texas) are being studied for discernibility of geological evidence on ERTS-1 imagery, Evidence mapped is compared with known mineral/hydrocarbon accumulations to determine the value of the imagery in commercial exploration programs. Evaluation has proceeded in the New Mexico-West Texas area while awaiting imagery in the other areas. To date, results have been better than expected. Clearly discernible structural lineaments in New Mexico-West Texas are evident on the photographs. Comparison of this evidence with known major mining localities in New Mexico indicates a clear pattern of coincidence between the lineaments and mining localities. In West Texas, lineament and geomorphological evidence obtainable from the photographs define the petroleum-productive Central Basin Platform. Based on evaluation results in the New Mexico-West Texas area and on cursory results in the other four areas of North America, ERTS-1 imagery will be extremely valuable in defining the regional and local structure in any commercial exploration program.

Kansas environmental and resource study: A Great Plains model, tasks 1-6

NASA Technical Reports Server (NTRS)

Haralick, R. M.; Kanemasu, E. T.; Morain, S. A.; Yarger, H. L. (Principal Investigator); Ulaby, F. T.; Shanmugam, K. S.; Williams, D. L.; Mccauley, J. R.; Mcnaughton, J. L.

1972-01-01

There are no author identified significant results in this report. Environmental and resources investigations in Kansas utilizing ERTS-1 imagery are summarized for the following areas: (1) use of feature extraction techniqued for texture context information in ERTS imagery; (2) interpretation and automatic image enhancement; (3) water use, production, and disease detection and predictions for wheat; (4) ERTS-1 agricultural statistics; (5) monitoring fresh water resources; and (6) ground pattern analysis in the Great Plains.

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

NASA Astrophysics Data System (ADS)

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 monitoring of agricultural facilities is expected to be available if the characteristics such as texture information including satellite images or spatial pattern are studied in detail.

Processing of SeaMARC swath sonar imagery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pratson, L.; Malinverno, A.; Edwards, M.

1990-05-01

Side-scan swath sonar systems have become an increasingly important means of mapping the sea floor. Two such systems are the deep-towed, high-resolution SeaMARC I sonar, which has a variable swath width of up to 5 km, and the shallow-towed, lower-resolution SeaMARC II sonar, which has a swath width of 10 km. The sea-floor imagery of acoustic backscatter output by the SeaMARC sonars is analogous to aerial photographs and airborne side-looking radar images of continental topography. Geologic interpretation of the sea-floor imagery is greatly facilitated by image processing. Image processing of the digital backscatter data involves removal of noise by medianmore » filtering, spatial filtering to remove sonar scans of anomalous intensity, across-track corrections to remove beam patterns caused by nonuniform response of the sonar transducers to changes in incident angle, and contrast enhancement by histogram equalization to maximize the available dynamic range. Correct geologic interpretation requires submarine structural fabrics to be displayed in their proper locations and orientations. Geographic projection of sea-floor imagery is achieved by merging the enhanced imagery with the sonar vehicle navigation and correcting for vehicle attitude. Co-registration of bathymetry with sonar imagery introduces sea-floor relief and permits the imagery to be displayed in three-dimensional perspectives, furthering the ability of the marine geologist to infer the processes shaping formerly hidden subsea terrains.« less

Virtual and Actual Humanoid Robot Control with Four-Class Motor-Imagery-Based Optical Brain-Computer Interface

PubMed Central

Kim, Youngmoo E.

2017-01-01

Motor-imagery tasks are a popular input method for controlling brain-computer interfaces (BCIs), partially due to their similarities to naturally produced motor signals. The use of functional near-infrared spectroscopy (fNIRS) in BCIs is still emerging and has shown potential as a supplement or replacement for electroencephalography. However, studies often use only two or three motor-imagery tasks, limiting the number of available commands. In this work, we present the results of the first four-class motor-imagery-based online fNIRS-BCI for robot control. Thirteen participants utilized upper- and lower-limb motor-imagery tasks (left hand, right hand, left foot, and right foot) that were mapped to four high-level commands (turn left, turn right, move forward, and move backward) to control the navigation of a simulated or real robot. A significant improvement in classification accuracy was found between the virtual-robot-based BCI (control of a virtual robot) and the physical-robot BCI (control of the DARwIn-OP humanoid robot). Differences were also found in the oxygenated hemoglobin activation patterns of the four tasks between the first and second BCI. These results corroborate previous findings that motor imagery can be improved with feedback and imply that a four-class motor-imagery-based fNIRS-BCI could be feasible with sufficient subject training. PMID:28804712

The influence of smoking imagery on the smoking intentions of young people: testing a media interpretation model.

PubMed

McCool, Judith P; Cameron, Linda D; Petrie, Keith J

2005-06-01

To assess a theoretical model of adolescents' exposure to films, perceptions of smoking imagery in film, and smoking intentions. A structured questionnaire was completed by 3041 Year 8 (aged 12 years) and Year 12 (aged 16 years) students from 25 schools in Auckland, New Zealand. The survey assessed the relationships among exposure to films, attitudes about smoking imagery, perceptions of smoking prevalence and its acceptability, and expectations of smoking in the future. Measures included exposure to films, perceived pervasiveness of, and nonchalant attitudes about smoking imagery, identification of positive smoker stereotypes in films, perceived smoking prevalence, judgment of smoking acceptability, and smoking expectations. Path analytic techniques, using multiple regression analyses, were used to test the pattern of associations identified by the media interpretation model. Hierarchical regression analyses revealed that film exposure predicted higher levels of perceived smoking prevalence, perceived imagery pervasiveness, and nonchalant attitudes about smoking imagery. Nonchalant attitudes, identification of positive smoker stereotypes, and perceived smoking prevalence predicted judgments of smoking acceptability. Acceptability judgments, identification of positive stereotypes, and perceived smoking prevalence were all positively associated with smoking expectations. The media interpretation model accounted for 24% of the variance in smoking expectations within the total sample. Smoking imagery in film may play a role in the development of smoking intentions through inflating the perception of smoking prevalence and presenting socially attractive images.

Virtual and Actual Humanoid Robot Control with Four-Class Motor-Imagery-Based Optical Brain-Computer Interface.

PubMed

Batula, Alyssa M; Kim, Youngmoo E; Ayaz, Hasan

2017-01-01

Motor-imagery tasks are a popular input method for controlling brain-computer interfaces (BCIs), partially due to their similarities to naturally produced motor signals. The use of functional near-infrared spectroscopy (fNIRS) in BCIs is still emerging and has shown potential as a supplement or replacement for electroencephalography. However, studies often use only two or three motor-imagery tasks, limiting the number of available commands. In this work, we present the results of the first four-class motor-imagery-based online fNIRS-BCI for robot control. Thirteen participants utilized upper- and lower-limb motor-imagery tasks (left hand, right hand, left foot, and right foot) that were mapped to four high-level commands (turn left, turn right, move forward, and move backward) to control the navigation of a simulated or real robot. A significant improvement in classification accuracy was found between the virtual-robot-based BCI (control of a virtual robot) and the physical-robot BCI (control of the DARwIn-OP humanoid robot). Differences were also found in the oxygenated hemoglobin activation patterns of the four tasks between the first and second BCI. These results corroborate previous findings that motor imagery can be improved with feedback and imply that a four-class motor-imagery-based fNIRS-BCI could be feasible with sufficient subject training.

Cubesat-Derived Detection of Seagrasses Using Planet Imagery Following Unmixing-Based Denoising: is Small the Next Big?

NASA Astrophysics Data System (ADS)

Traganos, D.; Cerra, D.; Reinartz, P.

2017-05-01

Seagrasses are one of the most productive and widespread yet threatened coastal ecosystems on Earth. Despite their importance, they are declining due to various threats, which are mainly anthropogenic. Lack of data on their distribution hinders any effort to rectify this decline through effective detection, mapping and monitoring. Remote sensing can mitigate this data gap by allowing retrospective quantitative assessment of seagrass beds over large and remote areas. In this paper, we evaluate the quantitative application of Planet high resolution imagery for the detection of seagrasses in the Thermaikos Gulf, NW Aegean Sea, Greece. The low Signal-to-noise Ratio (SNR), which characterizes spectral bands at shorter wavelengths, prompts the application of the Unmixing-based denoising (UBD) as a pre-processing step for seagrass detection. A total of 15 spectral-temporal patterns is extracted from a Planet image time series to restore the corrupted blue and green band in the processed Planet image. Subsequently, we implement Lyzenga's empirical water column correction and Support Vector Machines (SVM) to evaluate quantitative benefits of denoising. Denoising aids detection of Posidonia oceanica seagrass species by increasing its producer and user accuracy by 31.7 % and 10.4 %, correspondingly, with a respective increase in its Kappa value from 0.3 to 0.48. In the near future, our objective is to improve accuracies in seagrass detection by applying more sophisticated, analytical water column correction algorithms to Planet imagery, developing time- and cost-effective monitoring of seagrass distribution that will enable in turn the effective management and conservation of these highly valuable and productive ecosystems.

A study of image quality for radar image processing. [synthetic aperture radar imagery

NASA Technical Reports Server (NTRS)

King, R. W.; Kaupp, V. H.; Waite, W. P.; Macdonald, H. C.

1982-01-01

Methods developed for image quality metrics are reviewed with focus on basic interpretation or recognition elements including: tone or color; shape; pattern; size; shadow; texture; site; association or context; and resolution. Seven metrics are believed to show promise as a way of characterizing the quality of an image: (1) the dynamic range of intensities in the displayed image; (2) the system signal-to-noise ratio; (3) the system spatial bandwidth or bandpass; (4) the system resolution or acutance; (5) the normalized-mean-square-error as a measure of geometric fidelity; (6) the perceptual mean square error; and (7) the radar threshold quality factor. Selective levels of degradation are being applied to simulated synthetic radar images to test the validity of these metrics.

Landscape pattern and car use: Linking household data with satellite imagery

NASA Astrophysics Data System (ADS)

Keller, R.; Vance, C.

2013-12-01

Landscape pattern has long been hypothesized to influence automobile dependency. Because choices about land development tend to have long-lasting impacts that span over decades, understanding the magnitude of this influence is critical to the design of policies to reduce emissions and other negative externalities associated with car use. Combining household survey data from Germany with satellite imagery and other geo-referenced data sources, we undertake an econometric analysis of the relation between landscape pattern and automobile dependency. Specifically, we employ a two-part model to investigate two dimensions of car use, the discrete decision to own a car and, conditional upon ownership, the continuous decision of how far to drive. Results indicate that landscape pattern, as captured by measures of both land cover (e.g. the extent of open space and landscape diversity) and land use (e.g. the density of regional businesses) are important predictors of car ownership and use. Other policy-relevant variables, such as fuel prices and public transit infrastructure, are also identified as correlates. Based on the magnitude of our estimates, we conclude that carefully considered land development and zoning measures - ones that encourage dense development, diverse land cover and mixed land use - can have beneficial impacts in reducing car dependency that extend far into the future. Key terms: Landscape pattern, Satellite imagery, Germany, Two-part model Figure 1. Distribution of Elasticities of Landscape and Social Effects on German Household Weekly Car Use Results from Two Part Model N = 13,089 (probit) N = 10,987 (OLS)Robust standard errors in parentheses***, **, and *, denotes significance at the 0.01, 0.05, and 0.1 levels

Material Characterization using Passive Multispectral Polarimetric Imagery

DTIC Science & Technology

2013-03-01

least intuitive RS technique is undoubtedly polarimetry . Polarization is a property of all TEM waves, so its applications are not limited to any...Shaw. “Review of passive imaging polarimetry for remote sensing applications”. Applied Optics, 45(22):5453–5469, 2006. [48] Vanderbilt, V.C. and...refractive index; polarimetry ; multispectral; polarization; polarisation; polarimetric imagery; dispersion; Drude model; Cauchy equation; remote

Regressive Imagery in Creative Problem-Solving: Comparing Verbal Protocols of Expert and Novice Visual Artists and Computer Programmers

ERIC Educational Resources Information Center

Kozbelt, Aaron; Dexter, Scott; Dolese, Melissa; Meredith, Daniel; Ostrofsky, Justin

2015-01-01

We applied computer-based text analyses of regressive imagery to verbal protocols of individuals engaged in creative problem-solving in two domains: visual art (23 experts, 23 novices) and computer programming (14 experts, 14 novices). Percentages of words involving primary process and secondary process thought, plus emotion-related words, were…

Improvement in estimation of soil water deficit by integrating airborne imagery data into a soil water balance modelents into a soil water

USDA-ARS?s Scientific Manuscript database

In this paper, an approach that integrates airborne imagery data as inputs was used to improve the estimation of soil water deficit (SWD) for maize and sunflower grown under full and deficit irrigation treatments. The proposed model was applied to optimize the maximum total available soil water (TAW...

Experience modulates motor imagery-based brain activity.

PubMed

Kraeutner, Sarah N; McWhinney, Sean R; Solomon, Jack P; Dithurbide, Lori; Boe, Shaun G

2018-05-01

Whether or not brain activation during motor imagery (MI), the mental rehearsal of movement, is modulated by experience (i.e. skilled performance, achieved through long-term practice) remains unclear. Specifically, MI is generally associated with diffuse activation patterns that closely resemble novice physical performance, which may be attributable to a lack of experience with the task being imagined vs. being a distinguishing feature of MI. We sought to examine how experience modulates brain activity driven via MI, implementing a within- and between-group design to manipulate experience across tasks as well as expertise of the participants. Two groups of 'experts' (basketball/volleyball athletes) and 'novices' (recreational controls) underwent magnetoencephalography (MEG) while performing MI of four multi-articular tasks, selected to ensure that the degree of experience that participants had with each task varied. Source-level analysis was applied to MEG data and linear mixed effects modelling was conducted to examine task-related changes in activity. Within- and between-group comparisons were completed post hoc and difference maps were plotted. Brain activation patterns observed during MI of tasks for which participants had a low degree of experience were more widespread and bilateral (i.e. within-groups), with limited differences observed during MI of tasks for which participants had similar experience (i.e. between-groups). Thus, we show that brain activity during MI is modulated by experience; specifically, that novice performance is associated with the additional recruitment of regions across both hemispheres. Future investigations of the neural correlates of MI should consider prior experience when selecting the task to be performed. © 2018 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Satellite-derived attributes of cloud vortex systems and their application to climate studies

NASA Technical Reports Server (NTRS)

Carleton, Andrew M.

1987-01-01

Defense Meteorological Satellite Program (DMSP) visible and infrared mosaics are analyzed in conjunction with synoptic meteorological observations of sea level pressure (SLP) and upper-air height to derive composite patterns of cyclonic cloud vortices for the Northern Hemisphere. The patterns reveal variations in the structure and implied dynamics of cyclonic systems at different stages of development that include: (1) increasing vertical symmetry of the lower-level and upper-air circulations and (2) decreasing lower-tropospheric thicknesses and temperature advection, associated with increasing age of the vortex. Cloud vortices are more intense in winter than in summer and typically reach maximum intensity in the short-lived prespiral signature stage. There are major structural differences among frontal wave, polar air, and 'instant occlusion' cyclogenesis types. Cyclones in the dissipation stage may reintensify (deepen), as denoted by the appearance in the imagery of an asymmetric cloud band or a tightened spiral vortex. The satellite-derived statistics on cloud vortex intensity, which are seasonal- and latitude- as well as type-dependent, are applied to a preliminary examination of the synoptic manifestations of seasonal climate variability. An apparently close relationship is found, for two winter and spring seasons, between Northern Hemisphere cyclonic activity and variations in cryosphere variables, particularly the extent of Arctic sea ice. The results may indicate that increased snow and ice extent accompany a southward displacement of cyclonic activity and/or a predominance of deeper systems. However, there is also a strong regional dependence to the ice-synoptics feedback. This study demonstrates the utility of high resolution meteorological satellite imagery for studies of climate variations (climate dynamics).

An Evaluation of Data Fusion Products for the Analysis of Dryland Forest Phenology

NASA Astrophysics Data System (ADS)

Walker, J. J.; de Beurs, K.; Wynne, R. H.; Gao, F.

2010-12-01

Semi-arid forest areas cover a significant proportion of the world’s land surface; in the interior western U.S. alone, dryland forests extend across more than 56 million hectares. The scarcity of water in these systems makes them acutely sensitive to sustained weather fluctuations, such as the higher temperatures and altered water regimes predicted under most climate change scenarios. To understand, monitor, and predict the anticipated spatial and temporal changes in these areas, it is vital to characterize current phenological patterns. Phenological analysis of western U.S. drylands is complicated by patchy land cover and mosaics of plant phenology states at a variety of spatial scales. Our aim is to use complementary satellite sensors to mitigate these difficulties and gain greater insight into phenological patterns in dryland forests. In this study we applied the spatial and temporal adaptive reflectance model (STARFM; Gao et al. 2006) to fuse Landsat and MODIS imagery to create synthetic images at Landsat spatial resolution and MODIS temporal resolution. To determine which MODIS dataset is most appropriate for the creation of synthetic images intended for the analysis of dryland forest phenology, we examined the effect of temporal compositing and BRDF function adjustment on the accuracy of STARFM imagery. We assembled seven Landsat 5 scenes (path/row 37/36) and temporally-coincident 500m MODIS datasets (seven daily (MOD09GA), seven 8-day composite (MOD09A1), and fourteen 16-day nadir BRDF-adjusted composite (MCD43A4) images) spanning the 2006 April - October growing season in northern Arizona, which is characterized by large tracts of dryland forest. The STARFM algorithm was applied to each MODIS data series to produce four synthetic images (one daily; one 8-day composite; and two 16-day composites) corresponding to each Landsat image. Validation of the accuracy of the synthetic images was achieved by comparing the reflectance values of a random sample of the identified dryland forest pixels in both images. Preliminary data analysis of the effect of the temporal resolution and dataset parameters indicates that the MODIS 8-day composite image may be a suitable and sufficient dataset for phenological analysis in this dryland forest ecosystem. Overall, this work demonstrates the feasibility of using data fusion products to assemble an imagery dataset at sufficiently high temporal and spatial scales to permit a more detailed examination of the underlying phenological processes and trends in dryland forest areas.

Citizen science land cover classification based on ground and satellite imagery: Case study Day River in Vietnam

NASA Astrophysics Data System (ADS)

Nguyen, Son Tung; Minkman, Ellen; Rutten, Martine

2016-04-01

Citizen science is being increasingly used in the context of environmental research, thus there are needs to evaluate cognitive ability of humans in classifying environmental features. With the focus on land cover, this study explores the extent to which citizen science can be applied in sensing and measuring the environment that contribute to the creation and validation of land cover data. The Day Basin in Vietnam was selected to be the study area. Different methods to examine humans' ability to classify land cover were implemented using different information sources: ground based photos - satellite images - field observation and investigation. Most of the participants were solicited from local people and/or volunteers. Results show that across methods and sources of information, there are similar patterns of agreement and disagreement on land cover classes among participants. Understanding these patterns is critical to create a solid basis for implementing human sensors in earth observation. Keywords: Land cover, classification, citizen science, Landsat 8

The results of initial analysis of OSTA-1/Ocean Color Experiment (OCE) imagery

NASA Technical Reports Server (NTRS)

Kim, H. H.; Hart, W. D.

1982-01-01

Ocean view images from the Ocean Color Experiment (OCE) were produced at three widely separated locations on the Earth. Digital computer enhancement and band ratioing techniques were applied to radiometrically corrected OCE spectral data to emphasize patterns of chlorophyll distribution and, in one shallow, clear water case, bottom topography. The chlorophyll pattern in the Yellow Sea between China and Korea was evident in a scene produced from Shuttle Orbit 24. The effects of the discharge from the Yangtze and other rivers were also observed. Two scenes from orbits 30 and 32 revealed the movement of patches of plankton in the Gulf of Cadiz. Geometrical corrections to these images permitted the existing ocean current velocities in the vicinity to be deduced. The variability in water depth over the Grand Bahama Bank was estimated by using the blue-green OCE channel. The very clear water conditions in the area caused bottom reflected sunlight to produce a sensor signal which was related inversely to the depth of the water.

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

NASA Astrophysics Data System (ADS)

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.

Detection Of Tornado Damage Tracks With EOS Data

NASA Technical Reports Server (NTRS)

Jedlovec, Gary J.; Nair, Udaysankar; Haines, Stephanie L.

2005-01-01

The damage surveys conducted by the NWS in the aftermath of a reported tornadic event are used to document the location of the tornado ground damage track (path length and width) and an estimation of the tornado intensity. This study explored the possibility of using near real-time medium and high-resolution satellite imagery from the NASA EOS satellites to provide additional information for the surveys. MODIS and ASTER data were used to study the damage tracks from three tornadic storms; the La Plata, Maryland storm of 28 April 2002 and the Carter-Butler Counties and Madison County Missouri storms of 24 April 2002. These storms varied in intensity (from F0-F4) and occurred over regions with different land use. It was found that, depending on the nature of land use, tornado damage tracks from intense storms (F2 or greater) may be evident in both ASTER and MODIS satellite imagery. In areas of dense vegetation the scar patterns show up very clearly, while in areas of grassland and regions with few trees, scar patterns are not at all obvious in the satellite imagery. The detection of previously unidentified segments of a damage track caused by the 24 April 2004 Madison County, Missouri tornado demonstrates the utility of satellite imagery for damage surveys. However, the capability to detect tornado tracks in satellite imagery appears to be as much dependent on the nature of the underlying surface and land use as on the severity of the tornadic storm. The imaging sensors on the NPOESS operational satellites to be launched in 2006 will continue the unique observing capabilities of the EOS instruments.

Mental steps: Differential activation of internal pacemakers in motor imagery and in mental imitation of gait.

PubMed

Sacheli, Lucia Maria; Zapparoli, Laura; De Santis, Carlo; Preti, Matteo; Pelosi, Catia; Ursino, Nicola; Zerbi, Alberto; Banfi, Giuseppe; Paulesu, Eraldo

2017-10-01

Gait imagery and gait observation can boost the recovery of locomotion dysfunctions; yet, a neurologically justified rationale for their clinical application is lacking as much as a direct comparison of their neural correlates. Using functional magnetic resonance imaging, we measured the neural correlates of explicit motor imagery of gait during observation of in-motion videos shot in a park with a steady cam (Virtual Walking task). In a 2 × 2 factorial design, we assessed the modulatory effect of gait observation and of foot movement execution on the neural correlates of the Virtual Walking task: in half of the trials, the participants were asked to mentally imitate a human model shown while walking along the same route (mental imitation condition); moreover, for half of all the trials, the participants also performed rhythmic ankle dorsiflexion as a proxy for stepping movements. We found that, beyond the areas associated with the execution of lower limb movements (the paracentral lobule, the supplementary motor area, and the cerebellum), gait imagery also recruited dorsal premotor and posterior parietal areas known to contribute to the adaptation of walking patterns to environmental cues. When compared with mental imitation, motor imagery recruited a more extensive network, including a brainstem area compatible with the human mesencephalic locomotor region (MLR). Reduced activation of the MLR in mental imitation indicates that this more visually guided task poses less demand on subcortical structures crucial for internally generated gait patterns. This finding may explain why patients with subcortical degeneration benefit from rehabilitation protocols based on gait observation. Hum Brain Mapp 38:5195-5216, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Detection of Storm Damage Tracks with EOS Data

NASA Technical Reports Server (NTRS)

Jedlovec, Gary J.; Nair, Udaysankar; Haines, Stephanie L.

2006-01-01

The damage surveys conducted by the NWS in the aftermath of a reported tornadic event are used to document the location of the tornado ground damage track (pathlength and width) and an estimation of the tornado intensity. This study explores the possibility of using near-real-time medium and high spatial resolution satellite imagery from the NASA Earth Observing System satellites to provide additional information for the surveys. Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data were used to study the damage tracks from three tornadic storms: the La Plata, Maryland, storm of 28 April 2002 and the Ellsinore and Marquand, Missouri, storms of 24 April 2002. These storms varied in intensity and occurred over regions with significantly different land cover. It was found that, depending on the nature of the land cover, tornado damage tracks from intense storms (F1 or greater) and hail storms may be evident in ASTER, Landsat, and MODIS satellite imagery. In areas where the land cover is dominated by forests, the scar patterns can show up very clearly, while in areas of grassland and regions with few trees, scar patterns are not as obvious or cannot be seen at all in the satellite imagery. The detection of previously unidentified segments of a damage track caused by the 24 April 2002 Marquand, Missouri, tornado demonstrates the utility of satellite imagery for damage surveys. However, the capability to detect tornado tracks in satellite imagery depends on the ability to observe the ground without obstruction from space and appears to be as much dependent on the nature of the underlying surface and land cover as on the severity of the tornadic storm.

Dissecting hemisphere-specific contributions to visual spatial imagery using parametric brain mapping.

PubMed

Bien, Nina; Sack, Alexander T

2014-07-01

In the current study we aimed to empirically test previously proposed accounts of a division of labour between the left and right posterior parietal cortices during visuospatial mental imagery. The representation of mental images in the brain has been a topic of debate for several decades. Although the posterior parietal cortex is involved bilaterally, previous studies have postulated that hemispheric specialisation might result in a division of labour between the left and right parietal cortices. In the current fMRI study, we used an elaborated version of a behaviourally-controlled spatial imagery paradigm, the mental clock task, which involves mental image generation and a subsequent spatial comparison between two angles. By systematically varying the difference between the two angles that are mentally compared, we induced a symbolic distance effect: smaller differences between the two angles result in higher task difficulty. We employed parametrically weighed brain imaging to reveal brain areas showing a graded activation pattern in accordance with the induced distance effect. The parametric difficulty manipulation influenced behavioural data and brain activation patterns in a similar matter. Moreover, since this difficulty manipulation only starts to play a role from the angle comparison phase onwards, it allows for a top-down dissociation between the initial mental image formation, and the subsequent angle comparison phase of the spatial imagery task. Employing parametrically weighed fMRI analysis enabled us to top-down disentangle brain activation related to mental image formation, and activation reflecting spatial angle comparison. The results provide first empirical evidence for the repeatedly proposed division of labour between the left and right posterior parietal cortices during spatial imagery. Copyright © 2014 Elsevier Inc. All rights reserved.

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

PubMed

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.

Unique digital imagery interface between a silicon graphics computer and the kinetic kill vehicle hardware-in-the-loop simulator (KHILS) wideband infrared scene projector (WISP)

NASA Astrophysics Data System (ADS)

Erickson, Ricky A.; Moren, Stephen E.; Skalka, Marion S.

1998-07-01

Providing a flexible and reliable source of IR target imagery is absolutely essential for operation of an IR Scene Projector in a hardware-in-the-loop simulation environment. The Kinetic Kill Vehicle Hardware-in-the-Loop Simulator (KHILS) at Eglin AFB provides the capability, and requisite interfaces, to supply target IR imagery to its Wideband IR Scene Projector (WISP) from three separate sources at frame rates ranging from 30 - 120 Hz. Video can be input from a VCR source at the conventional 30 Hz frame rate. Pre-canned digital imagery and test patterns can be downloaded into stored memory from the host processor and played back as individual still frames or movie sequences up to a 120 Hz frame rate. Dynamic real-time imagery to the KHILS WISP projector system, at a 120 Hz frame rate, can be provided from a Silicon Graphics Onyx computer system normally used for generation of digital IR imagery through a custom CSA-built interface which is available for either the SGI/DVP or SGI/DD02 interface port. The primary focus of this paper is to describe our technical approach and experience in the development of this unique SGI computer and WISP projector interface.

Effect of biased feedback on motor imagery learning in BCI-teleoperation system.

PubMed

Alimardani, Maryam; Nishio, Shuichi; Ishiguro, Hiroshi

2014-01-01

Feedback design is an important issue in motor imagery BCI systems. Regardless, to date it has not been reported how feedback presentation can optimize co-adaptation between a human brain and such systems. This paper assesses the effect of realistic visual feedback on users' BCI performance and motor imagery skills. We previously developed a tele-operation system for a pair of humanlike robotic hands and showed that BCI control of such hands along with first-person perspective visual feedback of movements can arouse a sense of embodiment in the operators. In the first stage of this study, we found that the intensity of this ownership illusion was associated with feedback presentation and subjects' performance during BCI motion control. In the second stage, we probed the effect of positive and negative feedback bias on subjects' BCI performance and motor imagery skills. Although the subject specific classifier, which was set up at the beginning of experiment, detected no significant change in the subjects' online performance, evaluation of brain activity patterns revealed that subjects' self-regulation of motor imagery features improved due to a positive bias of feedback and a possible occurrence of ownership illusion. Our findings suggest that in general training protocols for BCIs, manipulation of feedback can play an important role in the optimization of subjects' motor imagery skills.

Effectiveness of PETTLEP imager on performance of passing skill in volleyball.

PubMed

Afrouzeh, M; Sohrabi, E; Haghkhan, A; Rowshani, F; Goharrokhi, S

2015-01-01

This study was conducted to compare the effectiveness of PETTLEP-based imagery, and traditional imagery interventions, on performance of passing skill in volleyball. 36 beginners male volleyball players (Mage =13.5 years, SD=0.55 years) with 5-6 months practice experience were randomly assigned to one of three groups: physical practice + PETTLEP imagery (PP+PI) (N.=15), physical practice + traditional imagery (N.=15), and physical practice only (PP; N.=15). Subjects in the PP+PI group applied the seven components of PETTLEP imagery training; whereas subjects in the PP+TI engaged in a relaxation session before imagery and used response laden motor imagery scripts. The two groups completed 15 minutes of imagery training followed immediately by 13 minutes of "passing" practice three times per week. The PP group completed only 13 minutes of "passing" practice three times per week. Each group performed its respective tasks for 7 weeks. A pre-test took place during the first practice session in which "passing" was assessed. After the 7-week practice program, a post-test took place followed by a retention test, one "no-practice" week later. All groups improved significantly (P<0.05) from pre- to post-test and retention test. However, as hypothesised the PP+PI group improved more (P<0.05) than the PP+TI and PP groups. The findings, therefore, support the effectiveness of PETTLEP imagery in enhancing performance of passing skill in volleyball when combined with physical practice.

Bridging the gap between motor imagery and motor execution with a brain-robot interface.

PubMed

Bauer, Robert; Fels, Meike; Vukelić, Mathias; Ziemann, Ulf; Gharabaghi, Alireza

2015-03-01

According to electrophysiological studies motor imagery and motor execution are associated with perturbations of brain oscillations over spatially similar cortical areas. By contrast, neuroimaging and lesion studies suggest that at least partially distinct cortical networks are involved in motor imagery and execution. We sought to further disentangle this relationship by studying the role of brain-robot interfaces in the context of motor imagery and motor execution networks. Twenty right-handed subjects performed several behavioral tasks as indicators for imagery and execution of movements of the left hand, i.e. kinesthetic imagery, visual imagery, visuomotor integration and tonic contraction. In addition, subjects performed motor imagery supported by haptic/proprioceptive feedback from a brain-robot-interface. Principal component analysis was applied to assess the relationship of these indicators. The respective cortical resting state networks in the α-range were investigated by electroencephalography using the phase slope index. We detected two distinct abilities and cortical networks underlying motor control: a motor imagery network connecting the left parietal and motor areas with the right prefrontal cortex and a motor execution network characterized by transmission from the left to right motor areas. We found that a brain-robot-interface might offer a way to bridge the gap between these networks, opening thereby a backdoor to the motor execution system. This knowledge might promote patient screening and may lead to novel treatment strategies, e.g. for the rehabilitation of hemiparesis after stroke. Copyright © 2014 Elsevier Inc. All rights reserved.

Seismically active structural lineaments in south-central Alaska as seen on ERTS-1 imagery

NASA Technical Reports Server (NTRS)

Gedney, L. (Principal Investigator); Vanwormer, J. D.

1973-01-01

The author has identified the following significant results. A mosaic of south-central Alaska composed of 19 ERTS-1 images, when compared with the seismicity pattern of the area, reveals that the larger earthquakes tend to fall on lineaments which are easily recognizable on the imagery. In most cases, these lineaments have not been mapped as faults. One particular lineament, which was the scene of three earthquakes of magnitude 4 or greater during 1972, passes very close to Anchorage.

The use of ERTS-1 multispectral imagery for crop identification in a semi-arid climate

NASA Technical Reports Server (NTRS)

Stockton, J. G.; Bauer, M. E.; Blair, B. O.; Baumgardner, M. F.

1975-01-01

Crop identification using multispectral satellite imagery and multivariate pattern recognition was used to identify wheat accurately in Greeley County, Kansas. A classification accuracy of 97 percent was found for wheat and the wheat estimate in hectares was within 5 percent of the USDA's Statistical Reporting Service estimate for 1973. The multispectral response of cotton and sorghum in Texas was not unique enough to distinguish between them nor to separate them from other cultivated crops.

Investigations using data from LANDSAT-2

NASA Technical Reports Server (NTRS)

Hossain, A. (Principal Investigator)

1977-01-01

The author has identified the following significant results. LANDSAT imageries of Mirpur area of Dacca district were used in connection with surveys for black plastic clay. The imageries showed the broad pattern of small valleys cutting into Madhupur clay. Land use maps of Haor areas of Sylhet and Mymensingh districts were prepared. As a test case, two thana areas, namely Nickley and Astogram, were classified in different categories such as crop, settlement, and water. It does not show much agreement with the Agriculture Dept.'s statistics.

Applications of satellite image processing to the analysis of Amazonian cultural ecology

NASA Technical Reports Server (NTRS)

Behrens, Clifford A.

1991-01-01

This paper examines the application of satellite image processing towards identifying and comparing resource exploitation among indigenous Amazonian peoples. The use of statistical and heuristic procedures for developing land cover/land use classifications from Thematic Mapper satellite imagery will be discussed along with actual results from studies of relatively small (100 - 200 people) settlements. Preliminary research indicates that analysis of satellite imagery holds great potential for measuring agricultural intensification, comparing rates of tropical deforestation, and detecting changes in resource utilization patterns over time.

Atmospheric water distribution in a midlatitude cyclone observed by the Seasat Scanning Multichannel Microwave Radiometer

NASA Technical Reports Server (NTRS)

Mcmurdie, L. A.; Katsaros, K. B.

1985-01-01

Patterns in the horizontal distribution of integrated water vapor, integrated liquid water and rainfall rate derived from the Seasat Scanning Multichannel Microwave Radiometer (SMMR) during a September 10-12, 1978 North Pacific cyclone are studied. These patterns are compared with surface analyses, ship reports, radiosonde data, and GOES-West infrared satellite imagery. The SMMR data give a unique view of the large mesoscale structure of a midlatitude cyclone. The water vapor distribution is found to have characteristic patterns related to the location of the surface fronts throughout the development of the cyclone. An example is given to illustrate that SMMR data could significantly improve frontal analysis over data-sparse oceanic regions. The distribution of integrated liquid water agrees qualitatively well with corresponding cloud patterns in satellite imagery and appears to provide a means to distinguish where liquid water clouds exist under a cirrus shield. Ship reports of rainfall intensity agree qualitatively very well with SMMR-derived rainrates. Areas of mesoscale rainfall, on the order of 50 km x 50 km or greater are detected using SMMR derived rainrates.

Google Haul Out: Earth Observation Imagery and Digital Aerial Surveys in Coastal Wildlife Management and Abundance Estimation

PubMed Central

Moxley, Jerry H.; Bogomolni, Andrea; Hammill, Mike O.; Moore, Kathleen M. T.; Polito, Michael J.; Sette, Lisa; Sharp, W. Brian; Waring, Gordon T.; Gilbert, James R.; Halpin, Patrick N.; Johnston, David W.

2017-01-01

Abstract As the sampling frequency and resolution of Earth observation imagery increase, there are growing opportunities for novel applications in population monitoring. New methods are required to apply established analytical approaches to data collected from new observation platforms (e.g., satellites and unmanned aerial vehicles). Here, we present a method that estimates regional seasonal abundances for an understudied and growing population of gray seals (Halichoerus grypus) in southeastern Massachusetts, using opportunistic observations in Google Earth imagery. Abundance estimates are derived from digital aerial survey counts by adapting established correction-based analyses with telemetry behavioral observation to quantify survey biases. The result is a first regional understanding of gray seal abundance in the northeast US through opportunistic Earth observation imagery and repurposed animal telemetry data. As species observation data from Earth observation imagery become more ubiquitous, such methods provide a robust, adaptable, and cost-effective solution to monitoring animal colonies and understanding species abundances. PMID:29599542

Infrared photography and imagery in water resources research

USGS Publications Warehouse

Robinove, Charles J.

1965-01-01

Infrared photography has restricted usefulness in general water resources studies but is particularly useful in special problems such as shoreline mapping. Infrared imagery is beginning to be used in water resources studies for the identification of surface and sub surface thermal anomalies as expressed at the surface and the measurement of apparent water surface temperatures. It will attain its maximum usefulness only when interpretation criteria for infrared imagery are fully developed. Several important hydrologic problems to which infrared imagery may be applied are: (1) determination of circulation and cooling of water in power plant cooling ponds, (2) measurement of river temperature and temperature decline downstream from power plants discharging heated water, (3) identification of submarine springs along coasts, and (4) measurement of temperature differences along streams as indicators of effluent seepage of ground water. Although it is possible at this time to identify many features of importance to hydrology by the use of infrared imagery, the task remaining is to develop criteria to show the hydrologic significance of the features.

Google Haul Out: Earth Observation Imagery and Digital Aerial Surveys in Coastal Wildlife Management and Abundance Estimation.

PubMed

Moxley, Jerry H; Bogomolni, Andrea; Hammill, Mike O; Moore, Kathleen M T; Polito, Michael J; Sette, Lisa; Sharp, W Brian; Waring, Gordon T; Gilbert, James R; Halpin, Patrick N; Johnston, David W

2017-08-01

As the sampling frequency and resolution of Earth observation imagery increase, there are growing opportunities for novel applications in population monitoring. New methods are required to apply established analytical approaches to data collected from new observation platforms (e.g., satellites and unmanned aerial vehicles). Here, we present a method that estimates regional seasonal abundances for an understudied and growing population of gray seals (Halichoerus grypus) in southeastern Massachusetts, using opportunistic observations in Google Earth imagery. Abundance estimates are derived from digital aerial survey counts by adapting established correction-based analyses with telemetry behavioral observation to quantify survey biases. The result is a first regional understanding of gray seal abundance in the northeast US through opportunistic Earth observation imagery and repurposed animal telemetry data. As species observation data from Earth observation imagery become more ubiquitous, such methods provide a robust, adaptable, and cost-effective solution to monitoring animal colonies and understanding species abundances.

Improving the TAMI for use with athletes.

PubMed

Madan, Christopher R; Singhal, Anthony

2014-01-01

Athletes have been shown to have greater movement imagery abilities than non-athletes. However, since these differences were observed using questionnaires where participants subjectively judged the vividness of performing imagined movements, it is possible that responses could be biased by other factors such as social desirability. One possible solution is to use an objective test, such as the Test of Ability in Movement Imagery (TAMI; Madan, C. R., & Singhal, A. (2013). Introducing TAMI: An objective test of ability in movement imagery. Journal of Motor Behavior, 45, 153-166.). Unfortunately, young adults perform relatively well on the TAMI, leaving little room for statistical sensitivity in observing higher scores. Here we propose an alternate scoring method for the TAMI that resolves this limitation by weighing items according to their difficulty. We apply this scoring method to existing data and show that this improves the TAMI's selectivity to measuring ability in movement imagery, rather than related imagery processes. Thus, we have successfully improved the TAMI to be more suited for use with athletic populations.

The Effect of Underwater Imagery Radiometry on 3d Reconstruction and Orthoimagery

NASA Astrophysics Data System (ADS)

Agrafiotis, P.; Drakonakis, G. I.; Georgopoulos, A.; Skarlatos, D.

2017-02-01

The work presented in this paper investigates the effect of the radiometry of the underwater imagery on automating the 3D reconstruction and the produced orthoimagery. Main aim is to investigate whether pre-processing of the underwater imagery improves the 3D reconstruction using automated SfM - MVS software or not. Since the processing of images either separately or in batch is a time-consuming procedure, it is critical to determine the necessity of implementing colour correction and enhancement before the SfM - MVS procedure or directly to the final orthoimage when the orthoimagery is the deliverable. Two different test sites were used to capture imagery ensuring different environmental conditions, depth and complexity. Three different image correction methods are applied: A very simple automated method using Adobe Photoshop, a developed colour correction algorithm using the CLAHE (Zuiderveld, 1994) method and an implementation of the algorithm described in Bianco et al., (2015). The produced point clouds using the initial and the corrected imagery are then being compared and evaluated.

Investigations of severe/tornadic thunderstorm development and evolution based on satellite and AVE/SESAME/VAS data

NASA Technical Reports Server (NTRS)

Vonderhaar, T. H.; Purdom, J. F. W.

1984-01-01

The use of rapid scan satellite imagery to investigate the local environment of severe thunderstorms is discussed. Mesoscale cloud tracking and vertical wind shear as it affects thunderstorm relative flow are mentioned. The role of pre-existing low level cloud cover in the outbreak of tornadoes was investigated. Applying visible atmospheric sounding imagery to mesoscale phenomena is also addressed.

Topography from shading and stereo

NASA Technical Reports Server (NTRS)

Horn, Berthold K. P.

1994-01-01

Methods exploiting photometric information in images that have been developed in machine vision can be applied to planetary imagery. Integrating shape from shading, binocular stereo, and photometric stereo yields a robust system for recovering detailed surface shape and surface reflectance information. Such a system is useful in producing quantitative information from the vast volume of imagery being received, as well as in helping visualize the underlying surface.

Assessment of Antarctic moss health from multi-sensor UAS imagery with Random Forest Modelling

NASA Astrophysics Data System (ADS)

Turner, Darren; Lucieer, Arko; Malenovský, Zbyněk; King, Diana; Robinson, Sharon A.

2018-06-01

Moss beds are one of very few terrestrial vegetation types that can be found on the Antarctic continent and as such mapping their extent and monitoring their health is important to environmental managers. Across Antarctica, moss beds are experiencing changes in health as their environment changes. As Antarctic moss beds are spatially fragmented with relatively small extent they require very high resolution remotely sensed imagery to monitor their distribution and dynamics. This study demonstrates that multi-sensor imagery collected by an Unmanned Aircraft System (UAS) provides a novel data source for assessment of moss health. In this study, we train a Random Forest Regression Model (RFM) with long-term field quadrats at a study site in the Windmill Islands, East Antarctica and apply it to UAS RGB and 6-band multispectral imagery, derived vegetation indices, 3D topographic data, and thermal imagery to predict moss health. Our results suggest that moss health, expressed as a percentage between 0 and 100% healthy, can be estimated with a root mean squared error (RMSE) between 7 and 12%. The RFM also quantifies the importance of input variables for moss health estimation showing the multispectral sensor data was important for accurate health prediction, such information being essential for planning future field investigations. The RFM was applied to the entire moss bed, providing an extrapolation of the health assessment across a larger spatial area. With further validation the resulting maps could be used for change detection of moss health across multiple sites and seasons.

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

NASA Astrophysics Data System (ADS)

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.

Differential Contribution of Bilateral Supplementary Motor Area to the Effective Connectivity Networks Induced by Task Conditions Using Dynamic Causal Modeling

PubMed Central

Tao, Zhongping; Zhang, Mu

2014-01-01

Abstract Functional imaging studies have indicated hemispheric asymmetry of activation in bilateral supplementary motor area (SMA) during unimanual motor tasks. However, the hemispherically special roles of bilateral SMAs on primary motor cortex (M1) in the effective connectivity networks (ECN) during lateralized tasks remain unclear. Aiming to study the differential contribution of bilateral SMAs during the motor execution and motor imagery tasks, and the hemispherically asymmetric patterns of ECN among regions involved, the present study used dynamic causal modeling to analyze the functional magnetic resonance imaging data of the unimanual motor execution/imagery tasks in 12 right-handed subjects. Our results demonstrated that distributions of network parameters underlying motor execution and motor imagery were significantly different. The variation was mainly induced by task condition modulations of intrinsic coupling. Particularly, regardless of the performing hand, the task input modulations of intrinsic coupling from the contralateral SMA to contralateral M1 were positive during motor execution, while varied to be negative during motor imagery. The results suggested that the inhibitive modulation suppressed the overt movement during motor imagery. In addition, the left SMA also helped accomplishing left hand tasks through task input modulation of left SMA→right SMA connection, implying that hemispheric recruitment occurred when performing nondominant hand tasks. The results specified differential and altered contributions of bilateral SMAs to the ECN during unimanual motor execution and motor imagery, and highlighted the contributions induced by the task input of motor execution/imagery. PMID:24606178

Reliability and Validity of Digital Imagery Methodology for Measuring Starting Portions and Plate Waste from School Salad Bars.

PubMed

Bean, Melanie K; Raynor, Hollie A; Thornton, Laura M; Sova, Alexandra; Dunne Stewart, Mary; Mazzeo, Suzanne E

2018-04-12

Scientifically sound methods for investigating dietary consumption patterns from self-serve salad bars are needed to inform school policies and programs. To examine the reliability and validity of digital imagery for determining starting portions and plate waste of self-serve salad bar vegetables (which have variable starting portions) compared with manual weights. In a laboratory setting, 30 mock salads with 73 vegetables were made, and consumption was simulated. Each component (initial and removed portion) was weighed; photographs of weighed reference portions and pre- and post-consumption mock salads were taken. Seven trained independent raters visually assessed images to estimate starting portions to the nearest ¼ cup and percentage consumed in 20% increments. These values were converted to grams for comparison with weighed values. Intraclass correlations between weighed and digital imagery-assessed portions and plate waste were used to assess interrater reliability and validity. Pearson's correlations between weights and digital imagery assessments were also examined. Paired samples t tests were used to evaluate mean differences (in grams) between digital imagery-assessed portions and measured weights. Interrater reliabilities were excellent for starting portions and plate waste with digital imagery. For accuracy, intraclass correlations were moderate, with lower accuracy for determining starting portions of leafy greens compared with other vegetables. However, accuracy of digital imagery-assessed plate waste was excellent. Digital imagery assessments were not significantly different from measured weights for estimating overall vegetable starting portions or waste; however, digital imagery assessments slightly underestimated starting portions (by 3.5 g) and waste (by 2.1 g) of leafy greens. This investigation provides preliminary support for use of digital imagery in estimating starting portions and plate waste from school salad bars. Results might inform methods used in empirical investigations of dietary intake in schools with self-serve salad bars. Copyright © 2018 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

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

NASA Technical Reports Server (NTRS)

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.

Toward a visuospatial developmental account of sequence-space synesthesia

PubMed Central

Price, Mark C.; Pearson, David G.

2013-01-01

Sequence-space synesthetes experience some sequences (e.g., numbers, calendar units) as arranged in spatial forms, i.e., spatial patterns in their mind's eye or even outside their body. Various explanations have been offered for this phenomenon. Here we argue that these spatial forms are continuous with varieties of non-synesthetic visuospatial imagery and share their central characteristics. This includes their dynamic and elaborative nature, their involuntary feel, and consistency over time. Drawing from literatures on mental imagery and working memory, we suggest how the initial acquisition and subsequent elaboration of spatial forms could be accounted for in terms of the known developmental trajectory of visuospatial representations. This extends from the formation of image-based representations of verbal material in childhood to the later maturation of dynamic control of imagery. Individual differences in the development of visuospatial style also account for variation in the character of spatial forms, e.g., in terms of distinctions such as visual versus spatial imagery, or ego-centric versus object-based transformations. PMID:24187538

Utilizing ERTS-A imagery for tectonic analysis through study of the Bighorn Mountains Region

NASA Technical Reports Server (NTRS)

Hoppin, R. A. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Preliminary vegetation analysis has been undertaken on MSS scene 1085-17294, Oct. 16, 1973 in the Bighorn region. Forest Service maps showing detailed distribution of dominant forest types have been compared with MSS bands 5 and 7 positive transparencies, enlarged positive prints, and color imagery produced on an Addcol viewer. Patterns on the ERTS imagery match those on the Forest Service maps quite well. A tectonic map ovearlay of MSS band 7 of the Bighorn region reveals a strong concentration of linears in the uplift as compared to basins. Folds in the Bighorn Basin are visible where not covered by post-Paleocene deposits. In regions where far less is known of the geology than in this area, it might be possible to predict the subsurface occurrence of folds and lineaments on the basis of imagery analysis and more confidently explore covered areas for concealed oil structures and mineral deposits.

Spline function approximation techniques for image geometric distortion representation. [for registration of multitemporal remote sensor imagery

NASA Technical Reports Server (NTRS)

Anuta, P. E.

1975-01-01

Least squares approximation techniques were developed for use in computer aided correction of spatial image distortions for registration of multitemporal remote sensor imagery. Polynomials were first used to define image distortion over the entire two dimensional image space. Spline functions were then investigated to determine if the combination of lower order polynomials could approximate a higher order distortion with less computational difficulty. Algorithms for generating approximating functions were developed and applied to the description of image distortion in aircraft multispectral scanner imagery. Other applications of the techniques were suggested for earth resources data processing areas other than geometric distortion representation.

Remote sensing of soils, land forms, and land use in the northern great plains in preparation for ERTS applications

NASA Technical Reports Server (NTRS)

Frazee, C. J.; Westin, F. C.; Gropper, J.; Myers, V. I.

1972-01-01

Research to determine the optimum time or season for obtaining imagery to identify and map soil limitations was conducted in the proposed Oahe irrigation project area in South Dakota. The optimum time for securing photographs or imagery is when the soil surface patterns are most apparent. For cultivated areas similar to the study area, May is the optimum time. The fields are cultivated or the planted crop has not yet masked soil surface features. Soil limitations in 59 percent of the field of the flight line could be mapped using the above criteria. The remaining fields cannot be mapped because the vegetation or growing crops do not express features related to soil differences. This suggests that imagery from more than one year is necessary to map completely the soil limitations of Oahe area by remote sensing techniques. Imagery from the other times studied is not suitable for identifying and mapping soil limitations of Oahe area by remote sensing techniques. Imagery from the other times studied is not suitable for identifying and mapping soil limitations because the vegetative cover masked the soil surface and does not reflect soil differences.

ERTS-1 imagery use in reconnaissance prospecting: Evaluation of commercial utility of ERTS-1 imagery in structural reconnaissance for minerals and petroleum

NASA Technical Reports Server (NTRS)

Saunders, D. F. (Principal Investigator); Thomas, G. L.; Kinsman, F. E.

1973-01-01

The author has identified the following significant results. Five areas in North America (North Slope-Alaska, Superior Province-Canada, Williston Basin-Montana, Colorado, and New Mexico-West Texas) are being studied for discernibility of geological evidence on ERTS-1 imagery. Evidence mapped is compared with known mineral/hydrocarbon accumulations to determine the value of the imagery in commercial exploration programs. Evaluation has proceeded in the New Mexico-Texas area, and to date, results have been better than expected. Clearly discernible structural lineaments in this area are evident on the photographs. Comparison of this evidence with known major mining localities in New Mexico indicates a clear pattern of coincidence between the lineaments and mining localities. In West Texas, lineament and geomorphological evidence obtainable from the photographs define the petroleum-productive Central Basin Platform. Based on evaluation of results in the New Mexico-West Texas area and on cursory results in the other four areas of North America, it is concluded that ERTS-1 imagery will be extremely valuable in defining the regional and local structure in any commercial exploration program.

An Adaptive Ship Detection Scheme for Spaceborne SAR Imagery

PubMed Central

Leng, Xiangguang; Ji, Kefeng; Zhou, Shilin; Xing, Xiangwei; Zou, Huanxin

2016-01-01

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. PMID:27563902

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

PubMed

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.

Speckle noise reduction of 1-look SAR imagery

NASA Technical Reports Server (NTRS)

Nathan, Krishna S.; Curlander, John C.

1987-01-01

Speckle noise is inherent to synthetic aperture radar (SAR) imagery. Since the degradation of the image due to this noise results in uncertainties in the interpretation of the scene and in a loss of apparent resolution, it is desirable to filter the image to reduce this noise. In this paper, an adaptive algorithm based on the calculation of the local statistics around a pixel is applied to 1-look SAR imagery. The filter adapts to the nonstationarity of the image statistics since the size of the blocks is very small compared to that of the image. The performance of the filter is measured in terms of the equivalent number of looks (ENL) of the filtered image and the resulting resolution degradation. The results are compared to those obtained from different techniques applied to similar data. The local adaptive filter (LAF) significantly increases the ENL of the final image. The associated loss of resolution is also lower than that for other commonly used speckle reduction techniques.

Plumes and Blooms: Observations, Analysis and Modeling for SIMBIOS

NASA Technical Reports Server (NTRS)

Maritorena, S.; Siegel, D. A.; Nelson, N. B.

2004-01-01

The goal of the Plumes and Blooms (PnB) project is to develop, validate and apply to imagery state-of-the-art ocean color algorithms for quantifying sediment plumes and phytoplankton blooms for the Case II environment of the Santa Barbara Channel. We conduct monthly to twice-monthly transect observations across the Santa Barbara Channel to develop an algorithm development and product validation data set. A primary goal is the use the PnB field data set to objectively tune semi-analytical models of ocean color for this site and apply them using available satellite imagery (SeaWiFS and MODIS). However, the comparison between PnB field observations and satellite estimates of primary products has been disappointing. We find that field estimates of water-leaving radiance correspond poorly to satellite estimates for both SeaWiFS and MODIS local area coverage imagery. We believe this is due to poor atmospheric correction due to complex mixtures of aerosol types found in these near-coastal regions.

A reconnaissance space sensing investigation of crustal structure for a strip from the eastern Sierra Nevada to the Colorado Plateau

NASA Technical Reports Server (NTRS)

Bechtold, I. C. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Analysis of ERTS-1 MSS imagery over the sourthern Basin-Range Province of California, Nevada, and Arizona has led to recognition of regional tectonic control of volcanism, plutonism, mineralization, and fault patterns. This conclusion is the result of geologic reconnaissance of anomalies observed in ERTS-1 and Apollo-9 data, guided by intermediate scale U-2 photography, SLAR, and relevant geologic literature. In addition to regional tectonic studies, the ERTS-1 imagery provides a basis for detailed research of relatively small geologic features. Interpretation of ERTS-1 and Apollo-9 space imagery and intermediate scale X-15 and U-2 photography indicates the presence of a major fault zone along the California-Nevada state line, here named the Pahrump fault zone. Field mapping confirms previously unreported evidence of fault breaks in bedrock, along range fronts and in Quaternary alluvium and lake sediments. Regional gravity lows and fault traces within the Pahrump fault zone from a general left stepping en echelon pattern. The trend and postulated diplacement for this fault are similar to other major strike slip fault zones in the southern Basin-Range Province.

Mapping tropical dry forest habitats integrating landsat NDVI, Ikonos imagery, and topographic information in the Caribbean island of Mona.

PubMed

Martinuzzi, Sebastiáin; Gould, William A; Ramos Gonzalez, Olga M; Martinez Robles, Alma; Calle Maldonado, Paulina; Pérez-Buitrago, Néstor; Fumero Caban, José J

2008-06-01

Assessing the status of tropical dry forest habitats using remote sensing technologies is one of the research priorities for Neotropical forests. We developed a simple method for mapping vegetation and habitats in a tropical dry forest reserve, Mona Island, Puerto Rico, by integrating the Normalized Difference Vegetation Index (NDVI) from Landsat, topographic information, and high-resolution Ikonos imagery. The method was practical for identifying vegetation types in areas with a great variety of plant communities and complex relief, and can be adapted to other dry forest habitats of the Caribbean Islands. NDVI was useful for identifying the distribution of forests, woodlands, and shrubland, providing a natural representation of the vegetation patterns on the island. The use of Ikonos imagery allowed increasing the number of land cover classes. As a result, sixteen land-cover types were mapped over the 5500 ha area, with a kappa coefficient of accuracy equal to 79%. This map is a central piece for modeling vertebrate species distribution and biodiversity patterns by the Puerto Rico Gap Analysis Project, and it is of great value for assisting research and management actions in the island.

Improved Volitional Recall of Motor-Imagery-Related Brain Activation Patterns Using Real-Time Functional MRI-Based Neurofeedback.

PubMed

Bagarinao, Epifanio; Yoshida, Akihiro; Ueno, Mika; Terabe, Kazunori; Kato, Shohei; Isoda, Haruo; Nakai, Toshiharu

2018-01-01

Motor imagery (MI), a covert cognitive process where an action is mentally simulated but not actually performed, could be used as an effective neurorehabilitation tool for motor function improvement or recovery. Recent approaches employing brain-computer/brain-machine interfaces to provide online feedback of the MI during rehabilitation training have promising rehabilitation outcomes. In this study, we examined whether participants could volitionally recall MI-related brain activation patterns when guided using neurofeedback (NF) during training. The participants' performance was compared to that without NF. We hypothesized that participants would be able to consistently generate the relevant activation pattern associated with the MI task during training with NF compared to that without NF. To assess activation consistency, we used the performance of classifiers trained to discriminate MI-related brain activation patterns. Our results showed significantly higher predictive values of MI-related activation patterns during training with NF. Additionally, this improvement in the classification performance tends to be associated with the activation of middle temporal gyrus/inferior occipital gyrus, a region associated with visual motion processing, suggesting the importance of performance monitoring during MI task training. Taken together, these findings suggest that the efficacy of MI training, in terms of generating consistent brain activation patterns relevant to the task, can be enhanced by using NF as a mechanism to enable participants to volitionally recall task-related brain activation patterns.

In Situ 3D Coherent X-ray Diffraction Imaging of Shock Experiments: Possible?

NASA Astrophysics Data System (ADS)

Barber, John

2011-03-01

In traditional coherent X-ray diffraction imaging (CXDI), a 2D or quasi-2D object is illuminated by a beam of coherent X-rays to produce a diffraction pattern, which is then manipulated via a process known as iterative phase retrieval to reconstruct an image of the original 2D sample. Recently, there have been dramatic advances in methods for performing fully 3D CXDI of a sample from a single diffraction pattern [Raines et al, Nature 463 214-7 (2010)], and these methods have been used to image samples tens of microns in size using soft X-rays. In this work, I explore the theoretical possibility of applying 3D CXDI techniques to the in situ imaging of the interaction between a shock front and a polycrystal, a far more stringent problem. A delicate trade-off is required between photon energy, spot size, imaging resolution, and the dimensions of the experimental setup. In this talk, I will outline the experimental and computational requirements for performing such an experiment, and I will present images and movies from simulations of one such hypothetical experiment, including both the time-resolved X-ray diffraction patterns and the time-resolved sample imagery.

Discussion of CoSA: Clustering of Sparse Approximations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Armstrong, Derek Elswick

2017-03-07

The purpose of this talk is to discuss the possible applications of CoSA (Clustering of Sparse Approximations) to the exploitation of HSI (HyperSpectral Imagery) data. CoSA is presented by Moody et al. in the Journal of Applied Remote Sensing (“Land cover classification in multispectral imagery using clustering of sparse approximations over learned feature dictionaries”, Vol. 8, 2014) and is based on machine learning techniques.

The application of remote sensing to the development and formulation of hydrologic planning models

NASA Technical Reports Server (NTRS)

Fowler, T. R.; Castruccio, P. A.; Loats, H. L., Jr.

1977-01-01

The development of a remote sensing model and its efficiency in determining parameters of hydrologic models are reviewed. Procedures for extracting hydrologic data from LANDSAT imagery, and the visual analysis of composite imagery are presented. A hydrologic planning model is developed and applied to determine seasonal variations in watershed conditions. The transfer of this technology to a user community and contract arrangements are discussed.

Dynamics and pattern of a managed coniferous forest landscape in Oregon.

Treesearch

T.A. Spies; W.J. Ripple; G.A. Bradshaw

1994-01-01

We examined the process of fragmentation in a managed forest landscape by comparing rates and patterns of disturbance (primarily clear-cutting) and regrowth between 1972 and 1988 using Landsat imagery. A 2589-km2 managed forest landscape in western Oregon was classified into two forest types, closed-canopy conifer forest (CF) (typically, > 60% conifer cover) and...

Use of LANDSAT imagery for soil survey

NASA Technical Reports Server (NTRS)

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

1977-01-01

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

Riverbed formation

NASA Technical Reports Server (NTRS)

Skinner, M.

1972-01-01

The general fluvial processes that work to form a riverbed and produce the characteristic pattern of either meandering, braided, or straight are reviewed. A method for quantification of river pattern and correlation, with the basic hydraulic characteristics of discharge and slope, is presented. Additional characteristics of a river system may be deduced from high-quality photography and imagery obtained from either aircraft or space platforms.

Geographic techniques and recent applications of remote sensing to landscape-water quality studies

USGS Publications Warehouse

Griffith, J.A.

2002-01-01

This article overviews recent advances in studies of landscape-water quality relationships using remote sensing techniques. With the increasing feasibility of using remotely-sensed data, landscape-water quality studies can now be more easily performed on regional, multi-state scales. The traditional method of relating land use and land cover to water quality has been extended to include landscape pattern and other landscape information derived from satellite data. Three items are focused on in this article: 1) the increasing recognition of the importance of larger-scale studies of regional water quality that require a landscape perspective; 2) the increasing importance of remotely sensed data, such as the imagery-derived normalized difference vegetation index (NDVI) and vegetation phenological metrics derived from time-series NDVI data; and 3) landscape pattern. In some studies, using landscape pattern metrics explained some of the variation in water quality not explained by land use/cover. However, in some other studies, the NDVI metrics were even more highly correlated to certain water quality parameters than either landscape pattern metrics or land use/cover proportions. Although studies relating landscape pattern metrics to water quality have had mixed results, this recent body of work applying these landscape measures and satellite-derived metrics to water quality analysis has demonstrated their potential usefulness in monitoring watershed conditions across large regions.

Object Recognition in Mental Representations: Directions for Exploring Diagnostic Features through Visual Mental Imagery.

PubMed

Roldan, Stephanie M

2017-01-01

One of the fundamental goals of object recognition research is to understand how a cognitive representation produced from the output of filtered and transformed sensory information facilitates efficient viewer behavior. Given that mental imagery strongly resembles perceptual processes in both cortical regions and subjective visual qualities, it is reasonable to question whether mental imagery facilitates cognition in a manner similar to that of perceptual viewing: via the detection and recognition of distinguishing features. Categorizing the feature content of mental imagery holds potential as a reverse pathway by which to identify the components of a visual stimulus which are most critical for the creation and retrieval of a visual representation. This review will examine the likelihood that the information represented in visual mental imagery reflects distinctive object features thought to facilitate efficient object categorization and recognition during perceptual viewing. If it is the case that these representational features resemble their sensory counterparts in both spatial and semantic qualities, they may well be accessible through mental imagery as evaluated through current investigative techniques. In this review, methods applied to mental imagery research and their findings are reviewed and evaluated for their efficiency in accessing internal representations, and implications for identifying diagnostic features are discussed. An argument is made for the benefits of combining mental imagery assessment methods with diagnostic feature research to advance the understanding of visual perceptive processes, with suggestions for avenues of future investigation.

Object Recognition in Mental Representations: Directions for Exploring Diagnostic Features through Visual Mental Imagery

PubMed Central

Roldan, Stephanie M.

2017-01-01

One of the fundamental goals of object recognition research is to understand how a cognitive representation produced from the output of filtered and transformed sensory information facilitates efficient viewer behavior. Given that mental imagery strongly resembles perceptual processes in both cortical regions and subjective visual qualities, it is reasonable to question whether mental imagery facilitates cognition in a manner similar to that of perceptual viewing: via the detection and recognition of distinguishing features. Categorizing the feature content of mental imagery holds potential as a reverse pathway by which to identify the components of a visual stimulus which are most critical for the creation and retrieval of a visual representation. This review will examine the likelihood that the information represented in visual mental imagery reflects distinctive object features thought to facilitate efficient object categorization and recognition during perceptual viewing. If it is the case that these representational features resemble their sensory counterparts in both spatial and semantic qualities, they may well be accessible through mental imagery as evaluated through current investigative techniques. In this review, methods applied to mental imagery research and their findings are reviewed and evaluated for their efficiency in accessing internal representations, and implications for identifying diagnostic features are discussed. An argument is made for the benefits of combining mental imagery assessment methods with diagnostic feature research to advance the understanding of visual perceptive processes, with suggestions for avenues of future investigation. PMID:28588538

Combining Imagery and Models to Understand River Dynamics

NASA Astrophysics Data System (ADS)

Blain, C. A.; Mied, R. P.; Linzell, R. S.

2014-12-01

Rivers pose one of the most challenging environments to characterize. Their geometric complexity and continually changing position and character are difficult to measure under optimal circumstances. Further compounding the problem is the often inaccessibility of these areas around the globe. Yet details of the river bank position and bed elevation are essential elements in the construction of accurate predictive river models. To meet this challenge, remote sensing imagery is first used to initialize the construction of advanced high resolution river circulation models. In turn, such models are applied to dynamically interpret remotely-sensed surface features. A method has been developed to automatically extract water and shoreline locations from arbitrarily sourced high resolution (~1m gsd) visual spectrum imagery without recourse to the spectral or color information. The approach relies on quantifying the difference in image texture between the relatively smooth water surface and the comparatively rough surface of surrounding land. Processing the segmented land/water interface results in ordered, continuous shoreline coordinates that bound river model construction. In the absence of observed bed elevations, one of several available analytic bathymetry cross-sectional relations are applied to complete the river model configuration. Successful application of this approach to the Snohomish River, WA and the Pearl River, MS are demonstrated. Once constructed, a hydrodynamic model of the river model can also be applied to unravel the dynamics responsible for observed surface features in the imagery. At a creek-river confluence in the Potomac River, MD, an ebb tide front observed in the imagery is analyzed using the model. The result is knowledge that an ebb shoal located just outside of the creek must be present and is essential for front formation. Furthermore, the front is found to be persistent throughout the tidal cycle, although it changes sign between ebb and flood phases. The presence of the creek only minimally modifies the underlying currents.

Satellite geological and geophysical remote sensing of Iceland: Preliminary results of geologic, hydrologic, oceanographic, and agricultural studies with ERTS-1 imagery

NASA Technical Reports Server (NTRS)

Williams, R. S., Jr. (Principal Investigator); Boeovarsson, A.; Frioriksson, S.; Palmason, G.; Rist, S.; Sigtryggsson, H.; Saemundsson, K.; Thorarinsson, S.; Thorsteinsson, I.

1973-01-01

The author has identified the following significant results. The wide variety of geological and geophysical phenomena which can be observed in Iceland, and particularly their very direct relation to the management of the country's natural resources, has provided great impetus to the use of ERTS-1 imagery to measure and map the dynamic natural phenomena in Iceland. MSS imagery is being used to study a large variety of geological and geophysical eruptive products, geologic structure, volcanic geomorphology, hydrologic, oceanographic, and agricultural phenomena of Iceland. Some of the preliminary results from this research projects are: (1) a large number of geological and volcanic features can be studied from ERTS-1 imagery, particularly imagery acquired at low sun angle, which had not previously been recognized; (2) under optimum conditions the ERTS-1 satellite can discern geothermal areas by their snow melt pattern or warm spring discharge into frozen lakes; (3) various maps at scales of 1:1 million and 1:500,000 can be updated and made more accurate with ERTS-1 imagery; (4) the correlation of water reserves with snowcover can improve the basis for planning electrical production in the management of water resources; (5) false-color composites (MSS) permitted the mapping of four types of vegetation: forested; grasslands, reclaimed, and cultivated areas, and the seasonal change of the vegetation, all of high value to rangeland management.

NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE): Changing patterns in the use of NRT satellite imagery

NASA Astrophysics Data System (ADS)

Davies, D.; Michael, K.; Schmaltz, J. E.; Harrison, S.; Ding, F.; Durbin, P. B.; Boller, R. A.; Cechini, M. F.; Rinsland, P. L.; Ye, G.; Mauoka, E.

2015-12-01

NASA's Land, Atmosphere Near real-time Capability for EOS (Earth Observing System) (LANCE) provides data and imagery approximately 3 hours from satellite observation, to monitor natural events globally and to meet the needs of the near real-time (NRT) applications community. This article describes LANCE, and how the use of NRT data and imagery has evolved. Since 2010 there has been a four-fold increase in both the volume of data and the number of files downloaded. Over the last year there has been a marked shift in the way in which users are accessing NRT imagery; users are gravitating towards Worldview and the Global Imagery Browse Services (GIBS) and away from MODIS Rapid Response, in part due to the increased exposure through social media. In turn this is leading to a broader range of users viewing NASA NRT imagery. This article also describes new, and planned, product enhancements to LANCE. Over the last year, LANCE has expanded to support NRT products from the Advanced Microwave Scanning Radiometer 2 (AMSR2), and the Multi-angle Imaging SpectroRadiometer (MISR). LANCE elements are also planning to ingest and process NRT data from the Visible Infrared Imager Radiometer Suite (VIIRS), and the advanced Ozone Mapping and Profiler Suite (OMPS) instruments onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite in the near future.

Automated cloud and shadow detection and filling using two-date Landsat imagery in the United States

USGS Publications Warehouse

Jin, Suming; Homer, Collin G.; Yang, Limin; Xian, George; Fry, Joyce; Danielson, Patrick; Townsend, Philip A.

2013-01-01

A simple, efficient, and practical approach for detecting cloud and shadow areas in satellite imagery and restoring them with clean pixel values has been developed. Cloud and shadow areas are detected using spectral information from the blue, shortwave infrared, and thermal infrared bands of Landsat Thematic Mapper or Enhanced Thematic Mapper Plus imagery from two dates (a target image and a reference image). These detected cloud and shadow areas are further refined using an integration process and a false shadow removal process according to the geometric relationship between cloud and shadow. Cloud and shadow filling is based on the concept of the Spectral Similarity Group (SSG), which uses the reference image to find similar alternative pixels in the target image to serve as replacement values for restored areas. Pixels are considered to belong to one SSG if the pixel values from Landsat bands 3, 4, and 5 in the reference image are within the same spectral ranges. This new approach was applied to five Landsat path/rows across different landscapes and seasons with various types of cloud patterns. Results show that almost all of the clouds were captured with minimal commission errors, and shadows were detected reasonably well. Among five test scenes, the lowest producer's accuracy of cloud detection was 93.9% and the lowest user's accuracy was 89%. The overall cloud and shadow detection accuracy ranged from 83.6% to 99.3%. The pixel-filling approach resulted in a new cloud-free image that appears seamless and spatially continuous despite differences in phenology between the target and reference images. Our methods offer a straightforward and robust approach for preparing images for the new 2011 National Land Cover Database production.

Relationships between remotely sensed fisheries distribution information and selected oceanographic parameters in the Mississippi Sound

NASA Technical Reports Server (NTRS)

Kemmerer, A. J.; Benigno, J. A.

1973-01-01

The author has identified the following significant results. A feasibility study to demonstrate the potential of satellites for providing fisheries significant information was conducted in the Mississippi Sound and adjacent offshore waters. Attempts were made to relate satellite acquired imagery to selected oceanographic parameters and then to relate these parameters to aircraft remotely sensed distribution patterns of resident surface schooling fishes. Initial results suggest that this approach is valid and that the satellite acquired imagery may have important fisheries resource assessment implications.

Archeological/Environmental Research

NASA Technical Reports Server (NTRS)

1991-01-01

Landsat/Seasat remote sensing was used by Ames Research Center to evaluate environmental influence on ancient Mayan civilization. Over 35 archeological sites were imaged and valuable information concerning Maya settlement patterns, environment, and resource usage resulted. The imagery was also used by Mexican authorities to develop coastal management plans, establish Biosphere Reserves and assess damage from the 1988 Hurricane Gilbert. Imagery showed evidence of ancient coastlines, changes in sea level, an ancient river plain and Mayan canal systems. Previously unknown Mayan reservoirs were discovered. The project is considered a pioneering effort combining remote sensing, environmental studies and archeology.

Investigation using data from ERTS to develop and implement utilization of living marine resources

NASA Technical Reports Server (NTRS)

Stevenson, W. H. (Principal Investigator); Pastula, E. J., Jr.

1973-01-01

The author has identified the following significant results. A feasibility study to demonstrate the potential of satellites for providing fisheries significant information was conducted in the Mississippi Sound and adjacent offshore waters. Attempts were made to relate satellite acquired imagery to selected oceanographic parameters and then to relate these parameters to aircraft remotely sensed distribution patterns of resident surface schooling fishes. Initial results suggest that this approach is valid and that the satellite acquired imagery may have important fisheries resource assessment implications.

Regional Land Use Mapping: the Phoenix Pilot Project

NASA Technical Reports Server (NTRS)

Anderson, J. R.; Place, J. L.

1971-01-01

The Phoenix Pilot Program has been designed to make effective use of past experience in making land use maps and collecting land use information. Conclusions reached from the project are: (1) Land use maps and accompanying statistical information of reasonable accuracy and quality can be compiled at a scale of 1:250,000 from orbital imagery. (2) Orbital imagery used in conjunction with other sources of information when available can significantly enhance the collection and analysis of land use information. (3) Orbital imagery combined with modern computer technology will help resolve the problem of obtaining land use data quickly and on a regular basis, which will greatly enhance the usefulness of such data in regional planning, land management, and other applied programs. (4) Agreement on a framework or scheme of land use classification for use with orbital imagery will be necessary for effective use of land use data.

Boundaries of ERTS and aircraft data within which useful water quality information can be obtained

NASA Technical Reports Server (NTRS)

Egan, W. G.

1974-01-01

Calibration procedures have been devised and applied to ERTS-1, multispectral, true color, and false color imagery. The results indicate that the ERTS and multispectral imagery are correlated with optical in situ measurements of the harbor water. Correlation is extended to true and false color imagery through in situ optical measurements of the harbor water. The best photometric accuracy is achieved with multispectral aerial imagery and the use of bulk MSS tape. The aircraft green photographic and ERTS-1 MSS-4 bands have been found most suitable for monitoring the scattered light levels under the conditions of this investigation. The application of satellite or aircraft for optical remote sensing depends upon the physical scale and frequency of sensing since both sensor systems generally have sufficient photometric sensitivity. The chemical parameters of the harbor water were found to be correlated to the optical properties for two stations investigated in detail.

Radar and infrared remote sensing of terrain, water resources, arctic sea ice, and agriculture

NASA Technical Reports Server (NTRS)

Biggs, A. W.

1983-01-01

Radar range measurements, basic waveforms of radar systems, and radar displays are initially described. These are followed by backscatter from several types of terrain and vegetation as a function of frequency and grazing angle. Analytical models for this backscatter include the facet models of radar return, with range-angle, velocity-range, velocity-angle, range, velocity, and angular only discriminations. Several side-looking airborne radar geometries are presented. Radar images of Arctic sea ice, fresh water lake ice, cloud-covered terrain, and related areas are presented to identify applications of radar imagery. Volume scatter models are applied to radar imagery from alpine snowfields. Short pulse ice thickness radar for subsurface probes is discussed in fresh-water ice and sea ice detection. Infrared scanners, including multispectral, are described. Diffusion of cold water into a river, Arctic sea ice, power plant discharges, volcanic heat, and related areas are presented in thermal imagery. Multispectral radar and infrared imagery are discussed, with comparisons of photographic, infrared, and radar imagery of the same terrain or subjects.

A comparison of LANDSAT TM to MSS imagery for detecting submerged aquatic vegetation in lower Chesapeake Bay

NASA Technical Reports Server (NTRS)

Ackleson, S. G.; Klemas, V.

1985-01-01

LANDSAT Thematic Mapper (TM) and Multispectral Scanner (MSS) imagery generated simultaneously over Guinea Marsh, Virginia, are assessed in the ability to detect submerged aquatic, bottom-adhering plant canopies (SAV). An unsupervised clustering algorithm is applied to both image types and the resulting classifications compared to SAV distributions derived from color aerial photography. Class confidence and accuracy are first computed for all water areas and then only shallow areas where water depth is less than 6 feet. In both the TM and MSS imagery, masking water areas deeper than 6 ft. resulted in greater classification accuracy at confidence levels greater than 50%. Both systems perform poorly in detecting SAV with crown cover densities less than 70%. On the basis of the spectral resolution, radiometric sensitivity, and location of visible bands, TM imagery does not offer a significant advantage over MSS data for detecting SAV in Lower Chesapeake Bay. However, because the TM imagery represents a higher spatial resolution, smaller SAV canopies may be detected than is possible with MSS data.

Investigation of the environmental change pattern of Japan

NASA Technical Reports Server (NTRS)

Maruyasu, T. (Principal Investigator)

1973-01-01

The author has identified the following significant results. ERTS-1 imagery clearly identifies the relationships between the status of erosion, effluent patterns affected by the coastal current, and the cultural construction activities. Simple photographic techniques can be used for detecting water mass distribution separately from cloud cover and also noise caused by reflected sunlight from wave surfaces. Polluted water does not diffuse continuously into the oceanic water, but forms masses in the water in the Kuroshio area. The polluted or turbid water in the area just north of the Tomogashima Channel, the south outlet of the Osaka Bay, shows that the northward tidal current runs in a clockwise eddy at the tidal period when the imagery was taken. Such an eddy-like pattern of tidal current had never been revealed by conventional oceanographic data. A front between an oceanic water mass and a polluted water mass runs in a NW-SE direction in the central part of the Osaka Bay. The patterns of turbid water discharged from the Kii River and Yoshino River show a northward tidal current in the North Kii Straits. The pattern of lighter turbid or polluted water located in the northwest region of the North Kii straits suggests the existence of a clockwise eddy in the straits.

Electromagnetic correlates of musical expertise in processing of tone patterns.

PubMed

Kuchenbuch, Anja; Paraskevopoulos, Evangelos; Herholz, Sibylle C; Pantev, Christo

2012-01-01

Using magnetoencephalography (MEG), we investigated the influence of long term musical training on the processing of partly imagined tone patterns (imagery condition) compared to the same perceived patterns (perceptual condition). The magnetic counterpart of the mismatch negativity (MMNm) was recorded and compared between musicians and non-musicians in order to assess the effect of musical training on the detection of deviants to tone patterns. The results indicated a clear MMNm in the perceptual condition as well as in a simple pitch oddball (control) condition in both groups. However, there was no significant mismatch response in either group in the imagery condition despite above chance behavioral performance in the task of detecting deviant tones. The latency and the laterality of the MMNm in the perceptual condition differed significantly between groups, with an earlier MMNm in musicians, especially in the left hemisphere. In contrast the MMNm amplitudes did not differ significantly between groups. The behavioral results revealed a clear effect of long-term musical training in both experimental conditions. The obtained results represent new evidence that the processing of tone patterns is faster and more strongly lateralized in musically trained subjects, which is consistent with other findings in different paradigms of enhanced auditory neural system functioning due to long-term musical training.

Relationships among vegetation structure, canopy composition, and avian richness patterns across an aspen-conifer forest gradient

Treesearch

Charles E. Swift; Kerri T. Vierling; Andrew T. Hudak; Lee A. Vierling

2017-01-01

Ecologists have a long-term interest in understanding the relative influence of vegetation composition and vegetation structure on avian diversity. LiDAR remote sensing is useful in studying local patterns of avian diversity because it characterizes fine-scale vegetation structure across broad extents. We used LiDAR, aerial and satellite imagery, and avian field data...

Map misclassifications can cause large errors in landscape pattern indices: examples from habitat fragmentation.

Treesearch

William T. Langford; Sarah E. Gergel; Thomas G. Dietterich; Warren Cohen

2006-01-01

Although habitat fragmentation is one of the greatest threats to biodiversity worldwide, virtually no attention has been paid to the quantification of error in fragmentation statistics. Landscape pattern indices (LPIs), such as mean patch size and number of patches, are routinely used to quantify fragmentation and are often calculated using remote sensing imagery that...

Spatial Analysis of Post-Hurricane Katrina Thermal Pattern and Intensity in Greater New Orleans: Implications for Urban Heat Island Phenomenon

NASA Astrophysics Data System (ADS)

Lief, Aram Parrish

In 2005, Hurricane Katrina's diverse impacts on the Greater New Orleans area included damaged and destroyed trees, and other despoiled vegetation, which also increased the exposure of artificial and bare surfaces, known factors that contribute to the climatic phenomenon known as the urban heat island (UHI). This is an investigation of UHI in the aftermath of Hurricane Katrina, which entails the analysis of pre and post-hurricane Katrina thermal imagery of the study area, including changes to surface heat patterns and vegetative cover. Imagery from Landsat TM was used to show changes to the pattern and intensity of the UHI effect, caused by an extreme weather event. Using remote sensing visualization methods, in situ data, and local knowledge, the author found there was a measurable change in the pattern and intensity of the New Orleans UHI effect, as well as concomitant changes to vegetative land cover. This finding may be relevant for urban planners and citizens, especially in the context of recovery from a large-scale disaster of a coastal city, regarding future weather events, and other natural and human impacts.

Electrode channel selection based on backtracking search optimization in motor imagery brain-computer interfaces.

PubMed

Dai, Shengfa; Wei, Qingguo

2017-01-01

Common spatial pattern algorithm is widely used to estimate spatial filters in motor imagery based brain-computer interfaces. However, use of a large number of channels will make common spatial pattern tend to over-fitting and the classification of electroencephalographic signals time-consuming. To overcome these problems, it is necessary to choose an optimal subset of the whole channels to save computational time and improve the classification accuracy. In this paper, a novel method named backtracking search optimization algorithm is proposed to automatically select the optimal channel set for common spatial pattern. Each individual in the population is a N-dimensional vector, with each component representing one channel. A population of binary codes generate randomly in the beginning, and then channels are selected according to the evolution of these codes. The number and positions of 1's in the code denote the number and positions of chosen channels. The objective function of backtracking search optimization algorithm is defined as the combination of classification error rate and relative number of channels. Experimental results suggest that higher classification accuracy can be achieved with much fewer channels compared to standard common spatial pattern with whole channels.

Evaluation of Ocean Color Scanner (OCS) photographic and digital data: Santa Barbara Channel test site, 29 October 1975 overflight

NASA Technical Reports Server (NTRS)

Kraus, S. P.; Estes, J. E.; Kronenberg, M. R.; Hajic, E. J.

1977-01-01

A summary of Ocean Color Scanner data was examined to evaluate detection and discrimination capabilities of the system for marine resources, oil pollution and man-made sea surface targets of opportunity in the Santa Barbara Channel. Assessment of the utility of OCS for the determination of sediment transport patterns along the coastal zone was a secondary goal. Data products provided 1975 overflight were in digital and analog formats. In evaluating the OCS data, automated and manual procedures were employed. A total of four channels of data in digital format were analyzed, as well as three channels of color combined imagery, and four channels of black and white imagery. In addition, 1:120,000 scale color infrared imagery acquired simultaneously with the OCS data were provided for comparative analysis purposes.

Spatial Metadata for Global Change Investigations Using Remote Sensing

NASA Technical Reports Server (NTRS)

Emerson, Charles W.; Quattrochi, Dale A.; Lam, Nina Siu-Ngan; Arnold, James E. (Technical Monitor)

2002-01-01

Satellite and aircraft-borne remote sensors have gathered petabytes of data over the past 30+ years. These images are an important resource for establishing cause and effect relationships between human-induced land cover changes and alterations in climate and other biophysical patterns at local to global scales. However, the spatial, temporal, and spectral characteristics of these datasets vary, thus complicating long-term studies involving several types of imagery. As the geographical and temporal coverage, the spectral and spatial resolution, and the number of individual sensors increase, the sheer volume and complexity of available data sets will complicate management and use of the rapidly growing archive of earth imagery. Mining this vast data resource for images that provide the necessary information for climate change studies becomes more difficult as more sensors are launched and more imagery is obtained.

Detection of people in military and security context imagery

NASA Astrophysics Data System (ADS)

Shannon, Thomas M. L.; Spier, Emmet H.; Wiltshire, Ben

2014-10-01

A high level of manual visual surveillance of complex scenes is dependent solely on the awareness of human operators whereas an autonomous person detection solution could assist by drawing their attention to potential issues, in order to reduce cognitive burden and achieve more with less manpower. Our research addressed the challenge of the reliable identification of persons in a scene who may be partially obscured by structures or by handling weapons or tools. We tested the efficacy of a recently published computer vision approach based on the construction of cascaded, non-linear classifiers from part-based deformable models by assessing performance using imagery containing infantrymen in the open or when obscured, undertaking low level tactics or acting as civilians using tools. Results were compared with those obtained from published upright pedestrian imagery. The person detector yielded a precision of approximately 65% for a recall rate of 85% for military context imagery as opposed to a precision of 85% for the upright pedestrian image cases. These results compared favorably with those reported by the authors when applied to a range of other on-line imagery databases. Our conclusion is that the deformable part-based model method may be a potentially useful people detection tool in the challenging environment of military and security context imagery.

Point Cloud and Digital Surface Model Generation from High Resolution Multiple View Stereo Satellite Imagery

NASA Astrophysics Data System (ADS)

Gong, K.; Fritsch, D.

2018-05-01

Nowadays, multiple-view stereo satellite imagery has become a valuable data source for digital surface model generation and 3D reconstruction. In 2016, a well-organized multiple view stereo publicly benchmark for commercial satellite imagery has been released by the John Hopkins University Applied Physics Laboratory, USA. This benchmark motivates us to explore the method that can generate accurate digital surface models from a large number of high resolution satellite images. In this paper, we propose a pipeline for processing the benchmark data to digital surface models. As a pre-procedure, we filter all the possible image pairs according to the incidence angle and capture date. With the selected image pairs, the relative bias-compensated model is applied for relative orientation. After the epipolar image pairs' generation, dense image matching and triangulation, the 3D point clouds and DSMs are acquired. The DSMs are aligned to a quasi-ground plane by the relative bias-compensated model. We apply the median filter to generate the fused point cloud and DSM. By comparing with the reference LiDAR DSM, the accuracy, the completeness and the robustness are evaluated. The results show, that the point cloud reconstructs the surface with small structures and the fused DSM generated by our pipeline is accurate and robust.

Utilizing ERTS-1 imagery for tectonic analysis through study of the Bighorn Mountains region

NASA Technical Reports Server (NTRS)

Hoppin, R. A. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Comparisons of imagery of three seasons, late summer-fall, winter, and spring indicate that for this region fall imagery is the best for overall geologic analysis. Winter scenes with light to moderate snow cover provide excellent topographic detail owing to snow enhancement, lower sun angle, and clarity of the atmosphere. Spring imagery has considerable reduction of tonal contrast owing to the low reflecting heavy green grass cover which subdues lithologic effects; heavy snow cover in the uplands masks topography. Mapping of geologic formations is impractical in most cases. Separation into tonal units can provide some general clues on structure. A given tonal unit can include parts of several geologic formations and different stratigraphic units can have the same tonal signature. Drainage patterns and anomalies provide the most consistent clues for detecting folds, monoclines, and homoclines. Vegetation only locally reflects lithology and structure. False color infrared 9 x 9 transparencies are the most valuable single imagery. Where these can be supplemented by U-2 color infrared for more detailed work, a tremendous amount of information is available. Adequately field checking such a large area just in one scene is the major logistic problem even in a fairly well known region.

Comparison of Hyperspectral and Multispectral Satellites for Discriminating Land Cover in Northern California

NASA Astrophysics Data System (ADS)

Clark, M. L.; Kilham, N. E.

2015-12-01

Land-cover maps are important science products needed for natural resource and ecosystem service management, biodiversity conservation planning, and assessing human-induced and natural drivers of land change. Most land-cover maps at regional to global scales are produced with remote sensing techniques applied to multispectral satellite imagery with 30-500 m pixel sizes (e.g., Landsat, MODIS). Hyperspectral, or imaging spectrometer, imagery measuring the visible to shortwave infrared regions (VSWIR) of the spectrum have shown impressive capacity to map plant species and coarser land-cover associations, yet techniques have not been widely tested at regional and greater spatial scales. The Hyperspectral Infrared Imager (HyspIRI) mission is a VSWIR hyperspectral and thermal satellite being considered for development by NASA. The goal of this study was to assess multi-temporal, HyspIRI-like satellite imagery for improved land cover mapping relative to multispectral satellites. We mapped FAO Land Cover Classification System (LCCS) classes over 22,500 km2 in the San Francisco Bay Area, California using 30-m HyspIRI, Landsat 8 and Sentinel-2 imagery simulated from data acquired by NASA's AVIRIS airborne sensor. Random Forests (RF) and Multiple-Endmember Spectral Mixture Analysis (MESMA) classifiers were applied to the simulated images and accuracies were compared to those from real Landsat 8 images. The RF classifier was superior to MESMA, and multi-temporal data yielded higher accuracy than summer-only data. With RF, hyperspectral data had overall accuracy of 72.2% and 85.1% with full 20-class and reduced 12-class schemes, respectively. Multispectral imagery had lower accuracy. For example, simulated and real Landsat data had 7.5% and 4.6% lower accuracy than HyspIRI data with 12 classes, respectively. In summary, our results indicate increased mapping accuracy using HyspIRI multi-temporal imagery, particularly in discriminating different natural vegetation types, such as spectrally-mixed woodlands and forests.

Airborne Hyperspectral Imagery for the Detection of Agricultural Crop Stress

NASA Technical Reports Server (NTRS)

Cassady, Philip E.; Perry, Eileen M.; Gardner, Margaret E.; Roberts, Dar A.

2001-01-01

Multispectral digital imagery from aircraft or satellite is presently being used to derive basic assessments of crop health for growers and others involved in the agricultural industry. Research indicates that narrow band stress indices derived from hyperspectral imagery should have improved sensitivity to provide more specific information on the type and cause of crop stress, Under funding from the NASA Earth Observation Commercial Applications Program (EOCAP) we are identifying and evaluating scientific and commercial applications of hyperspectral imagery for the remote characterization of agricultural crop stress. During the summer of 1999 a field experiment was conducted with varying nitrogen treatments on a production corn-field in eastern Nebraska. The AVIRIS (Airborne Visible-Infrared Imaging Spectrometer) hyperspectral imager was flown at two critical dates during crop development, at two different altitudes, providing images with approximately 18m pixels and 3m pixels. Simultaneous supporting soil and crop characterization included spectral reflectance measurements above the canopy, biomass characterization, soil sampling, and aerial photography. In this paper we describe the experiment and results, and examine the following three issues relative to the utility of hyperspectral imagery for scientific study and commercial crop stress products: (1) Accuracy of reflectance derived stress indices relative to conventional measures of stress. We compare reflectance-derived indices (both field radiometer and AVIRIS) with applied nitrogen and with leaf level measurement of nitrogen availability and chlorophyll concentrations over the experimental plots (4 replications of 5 different nitrogen levels); (2) Ability of the hyperspectral sensors to detect sub-pixel areas under crop stress. We applied the stress indices to both the 3m and 18m AVIRIS imagery for the entire production corn field using several sub-pixel areas within the field to compare the relative sensitivity of each stress index; and (3) Comparative sensitivity of stress indices to realistic measurement uncertainties. We compare the stress indices calculated with several levels of spectral uncertainty (by shifting the wavelengths) and reflectance uncertainty (by systematically varying the reflectance retrieval code initialization).

Identification and interpretation of tectonic features from ERTS-1 imagery

NASA Technical Reports Server (NTRS)

Abdel-Gawad, M. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Many criteria of active or recent fault movements are observable in the imagery. It was observed that where earthquake epicenter clusters occur, evidence of recent fault movements is generally observed. The opposite was not necessarily true as there are areas where evidence of recent faulting is observed, often along major known faults which are peculiarly devoid of significant seismicity. A tentative conclusion is that the seismicity pattern alone can often be a misleading criteria for potential earthquake hazards. The feasibility of recognizing geomorphic criteria of recent fault movement from ERTS-1 imagery suggests that ERTS imagery should be used to map potentially active faults and utilize this data to develop better criteria for the identification of areas prone to future earthquakes. An apparent correlation was observed between the distribution of mercury deposits in the California Coast Range Province and transverse fault zones trending west-northwest oblique to the trend of the San Andreas system. The significance of this correlation and the full extent of its implication on mercury exploration is under study.

Religion's support for the domination of women--breaking the cycle.

PubMed

LaChat, M R

1988-01-01

Throughout history, certain religious images and symbols often have been uncritically used to legitimate the dominance of men over women. This uncritical use has had lasting effects upon our culture, and these images and symbols often continue to be used as rationale for subordinating women today. Since the nursing profession has been, and continues to be, a predominantly female occupation, nurses are especially impacted by this inherited imagery. In their role as primary health care givers, nurse practitioners often care for women who have been victimized by a pattern of male domination that culturally is bound up in and perpetuated by certain religious imagery. This article describes and analyzes the power of religious sex-role imagery to maintain the public and professional order of female subordination to the male. Practical ideas are suggested for the nursing profession that will help to reconstruct this imagery along more equitable and humane lines. Through such efforts, nurses can justly achieve more reciprocity and equality for themselves, and can take active steps to prevent the victimization of many of the women they care for.

To evaluate ERTS-1 data for the usefulness as a geological sensor in the diverse geological terranes of New York State

NASA Technical Reports Server (NTRS)

Isachsen, Y. W. (Principal Investigator)

1973-01-01

The author has identified the following significant results. The straight NNE-trending escarpment that marks the easternmost extent of the Catskill Mountains appears, from ERTS-1 imagery (1079-15124) to be related to a set of parallel topographic lineaments which occur over a distance of 40 km to the west. The October 11 imagery of the Adirondacks (1080-15174) displays the pre-Paleozoic erosion surface along the western and northern margin of the Adirondack Mountains dome. The northern portion of this paleoplain is terminated to the southeast by an escarpment following an ENE topographic linear to produce a pseudo-cuesta. The snow covered terrain in the Mohawk Valley between Albany and Rome (1170-15182 and 1169-15123) displays with sculptural clarity a drumlin field having a cloud-free area of about 2600 sq km; glacial flow directions can be plotted readily because the stoss and lee sides of the drumlins can be distinguished. In the imagery of summer and fall, agricultural patterns obscured the detail which is visible in the winter imagery.

Using satellite remote sensing to model and map the distribution of Bicknell's thrush (Catharus bicknelli) in the White Mountains of New Hampshire

NASA Astrophysics Data System (ADS)

Hale, Stephen Roy

Landsat-7 Enhanced Thematic Mapper satellite imagery was used to model Bicknell's Thrush (Catharus bicknelli) distribution in the White Mountains of New Hampshire. The proof-of-concept was established for using satellite imagery in species-habitat modeling, where for the first time imagery spectral features were used to estimate a species-habitat model variable. The model predicted rising probabilities of thrush presence with decreasing dominant vegetation height, increasing elevation, and decreasing distance to nearest Fir Sapling cover type. To solve the model at all locations required regressor estimates at every pixel, which were not available for the dominant vegetation height and elevation variables. Topographically normalized imagery features Normalized Difference Vegetation Index and Band 1 (blue) were used to estimate dominant vegetation height using multiple linear regression; and a Digital Elevation Model was used to estimate elevation. Distance to nearest Fir Sapling cover type was obtained for each pixel from a land cover map specifically constructed for this project. The Bicknell's Thrush habitat model was derived using logistic regression, which produced the probability of detecting a singing male based on the pattern of model covariates. Model validation using Bicknell's Thrush data not used in model calibration, revealed that the model accurately estimated thrush presence at probabilities ranging from 0 to <0.40 and from 0.50 to <0.60. Probabilities from 0.40 to <0.50 and greater than 0.60 significantly underestimated and overestimated presence, respectively. Applying the model to the study area illuminated an important implication for Bicknell's Thrush conservation. The model predicted increasing numbers of presences and increasing relative density with rising elevation, with which exists a concomitant decrease in land area. Greater land area of lower density habitats may account for more total individuals and reproductive output than higher density less abundant land area. Efforts to conserve areas of highest individual density under the assumption that density reflects habitat quality could target the smallest fraction of the total population.

Observing the Earth from an Astronaut's View - Applied Remote Sensing in Schools

NASA Astrophysics Data System (ADS)

Rienow, Andreas; Hodam, Henryk; Menz, Gunter; Kerstin, Voß

2015-04-01

Since spring 2014, NASA conducts the High Definition Earth Viewing (HDEV) mission at the International Space Station (ISS). HDEV consists of four cameras mounted at ESA's Columbus laboratory. They continuously observe our earth in three different perspectives. Hence, they provide not only footage showing the Sun and the Moon rising and setting but also regular images of landscapes that are difficult to access, such as mountain ranges, deserts, and tropical rainforests. The German educational project "Columbus Eye", which is executed by the University of Bonn and is funded by the German Aerospace Center (DLR), aims at the implementation of the HDEV imagery and videos in a teaching portal: www.columbuseye.uni-bonn.de. Pupils should be motivated to work with the footage in order to learn about pattern and processes of the coupled human-environment system like volcano eruptions or deforestation. The material is developed on the experiences of the FIS (German abbreviation for "Remote Sensing in Schools") project and its learning portal (www.fis.uni-bonn.de/en). Recognizing that in-depth use of satellite imagery can only be achieved by the means of computer aided learning methods, a sizeable number of e-Learning contents in German and English have been created throughout the last 7 years since FIS' kickoff. The talk presents the educational valorization of ISS and satellite borne imagery data as well as their interactive implementation for teachers and pupils in both learning portals. It will be shown which possibilities the topic of earth observation from space holds ready for teaching the regular STEM curricula. A report of first experiences of a nationwide road show accompanying the mission of the ESA astronaut Alexander Gerst will be given. Among others it involved an event during which pupils from a secondary school in North Rhine-Westphalia have talked to the astronaut via ham radio. Accordingly, the presentation addresses the question of how synergies of human space travels can be used to enhance the fascination of earth observation imagery in the light of problem-based learning in everyday school lessons.

Inferring diagnosis and trajectory of wet age-related macular degeneration from OCT imagery of retina

NASA Astrophysics Data System (ADS)

Irvine, John M.; Ghadar, Nastaran; Duncan, Steve; Floyd, David; O'Dowd, David; Lin, Kristie; Chang, Tom

2017-03-01

Quantitative biomarkers for assessing the presence, severity, and progression of age-related macular degeneration (AMD) would benefit research, diagnosis, and treatment. This paper explores development of quantitative biomarkers derived from OCT imagery of the retina. OCT images for approximately 75 patients with Wet AMD, Dry AMD, and no AMD (healthy eyes) were analyzed to identify image features indicative of the patients' conditions. OCT image features provide a statistical characterization of the retina. Healthy eyes exhibit a layered structure, whereas chaotic patterns indicate the deterioration associated with AMD. Our approach uses wavelet and Frangi filtering, combined with statistical features that do not rely on image segmentation, to assess patient conditions. Classification analysis indicates clear separability of Wet AMD from other conditions, including Dry AMD and healthy retinas. The probability of correct classification of was 95.7%, as determined from cross validation. Similar classification analysis predicts the response of Wet AMD patients to treatment, as measured by the Best Corrected Visual Acuity (BCVA). A statistical model predicts BCVA from the imagery features with R2 = 0.846. Initial analysis of OCT imagery indicates that imagery-derived features can provide useful biomarkers for characterization and quantification of AMD: Accurate assessment of Wet AMD compared to other conditions; image-based prediction of outcome for Wet AMD treatment; and features derived from the OCT imagery accurately predict BCVA; unlike many methods in the literature, our techniques do not rely on segmentation of the OCT image. Next steps include larger scale testing and validation.

Remote sensing of soybean stress as an indicator of chemical concentration of biosolid amended surface soils

NASA Astrophysics Data System (ADS)

Sridhar, B. B. Maruthi; Vincent, Robert K.; Roberts, Sheila J.; Czajkowski, Kevin

2011-08-01

The accumulation of heavy metals in the biosolid amended soils and the risk of their uptake into different plant parts is a topic of great concern. This study examines the accumulation of several heavy metals and nutrients in soybeans grown on biosolid applied soils and the use of remote sensing to monitor the metal uptake and plant stress. Field and greenhouse studies were conducted with soybeans grown on soils applied with biosolids at varying rates. The plant growth was monitored using Landsat TM imagery and handheld spectroradiometer in field and greenhouse studies, respectively. Soil and plant samples were collected and then analyzed for several elemental concentrations. The chemical concentrations in soils and roots increased significantly with increase in applied biosolid concentrations. Copper (Cu) and Molybdenum (Mo) accumulated significantly in the shoots of the metal-treated plants. Our spectral and Landsat TM image analysis revealed that the Normalized Difference Vegetative Index (NDVI) can be used to distinguish the metal stressed plants. The NDVI showed significant negative correlation with increase in soil Cu concentrations followed by other elements. This study suggests the use of remote sensing to monitor soybean stress patterns and thus indirectly assess soil chemical characteristics.

Diffractive optical element in materials testing

NASA Astrophysics Data System (ADS)

Silvennoinen, Raimo V. J.; Peiponen, Kai-Erik

1998-09-01

The object of this paper is to present a sensor based on diffractive optics that can be applied for the materials testing. The present sensor, which is based on the use of a computer-generated hologram (CGH) exploits the holographic imagery. The CGH-sensor was introduced for inspection of surface roughness and flatness of metal surfaces. The results drawn out by the present sensor are observed to be in accordance with the experimental data. Together with the double exposure holographic interferometry (DEHI) and digital electronic speckle pattern interferometry (DSPI) in elasticity inspection, the sensor was applied for the investigations of surface quality of opaque fragile materials, which are pharmaceutical compacts. The optical surface quality was observed to be related to the porosity of the pharmaceutical tablets. The CGH-sensor was also applied for investigations of optical quality of thin films as PLZT ceramics and coating of pharmaceutical compacts. The surfaces of PLZT samples showed fluctuations in optical curvature, and wedgeness for all the cases studied. For pharmaceutical compacts, the optical signals were observed to depend to a great extent on the optical constants of the coatings and the substrates, and in addition to the surface porosity under the coating.

Noise tolerant dendritic lattice associative memories

NASA Astrophysics Data System (ADS)

Ritter, Gerhard X.; Schmalz, Mark S.; Hayden, Eric; Tucker, Marc

2011-09-01

Linear classifiers based on computation over the real numbers R (e.g., with operations of addition and multiplication) denoted by (R, +, x), have been represented extensively in the literature of pattern recognition. However, a different approach to pattern classification involves the use of addition, maximum, and minimum operations over the reals in the algebra (R, +, maximum, minimum) These pattern classifiers, based on lattice algebra, have been shown to exhibit superior information storage capacity, fast training and short convergence times, high pattern classification accuracy, and low computational cost. Such attributes are not always found, for example, in classical neural nets based on the linear inner product. In a special type of lattice associative memory (LAM), called a dendritic LAM or DLAM, it is possible to achieve noise-tolerant pattern classification by varying the design of noise or error acceptance bounds. This paper presents theory and algorithmic approaches for the computation of noise-tolerant lattice associative memories (LAMs) under a variety of input constraints. Of particular interest are the classification of nonergodic data in noise regimes with time-varying statistics. DLAMs, which are a specialization of LAMs derived from concepts of biological neural networks, have successfully been applied to pattern classification from hyperspectral remote sensing data, as well as spatial object recognition from digital imagery. The authors' recent research in the development of DLAMs is overviewed, with experimental results that show utility for a wide variety of pattern classification applications. Performance results are presented in terms of measured computational cost, noise tolerance, classification accuracy, and throughput for a variety of input data and noise levels.

Partial Least Square Discriminant Analysis Based on Normalized Two-Stage Vegetation Indices for Mapping Damage from Rice Diseases Using PlanetScope Datasets.

PubMed

Shi, Yue; Huang, Wenjiang; Ye, Huichun; Ruan, Chao; Xing, Naichen; Geng, Yun; Dong, Yingying; Peng, Dailiang

2018-06-11

In recent decades, rice disease co-epidemics have caused tremendous damage to crop production in both China and Southeast Asia. A variety of remote sensing based approaches have been developed and applied to map diseases distribution using coarse- to moderate-resolution imagery. However, the detection and discrimination of various disease species infecting rice were seldom assessed using high spatial resolution data. The aims of this study were (1) to develop a set of normalized two-stage vegetation indices (VIs) for characterizing the progressive development of different diseases with rice; (2) to explore the performance of combined normalized two-stage VIs in partial least square discriminant analysis (PLS-DA); and (3) to map and evaluate the damage caused by rice diseases at fine spatial scales, for the first time using bi-temporal, high spatial resolution imagery from PlanetScope datasets at a 3 m spatial resolution. Our findings suggest that the primary biophysical parameters caused by different disease (e.g., changes in leaf area, pigment contents, or canopy morphology) can be captured using combined normalized two-stage VIs. PLS-DA was able to classify rice diseases at a sub-field scale, with an overall accuracy of 75.62% and a Kappa value of 0.47. The approach was successfully applied during a typical co-epidemic outbreak of rice dwarf (Rice dwarf virus, RDV), rice blast ( Magnaporthe oryzae ), and glume blight ( Phyllosticta glumarum ) in Guangxi Province, China. Furthermore, our approach highlighted the feasibility of the method in capturing heterogeneous disease patterns at fine spatial scales over the large spatial extents.

Analysing spatio-temporal land degradation dynamics in dry rangelands using landscape metrics and satellite time series data

NASA Astrophysics Data System (ADS)

von Keyserlingk, Jennifer; Paton, Eva Nora; Förster, Saskia; Bronstert, Axel

2017-04-01

Many of the dry rangelands of Southern Europe are threatened by land degradation. This process not only reduces the land's ecological functioning, but also its capacity to provide ecosystem goods and services for local land users. In rangelands, one important aspect is vegetation degradation, which reduces the land's capacity to support livestock. Thus, there is an urgent need to understand the complex dynamics and drivers of land degradation. In the past, both have been difficult to study due to the extensive spatial and temporal scales involved. In the last decade, a large number of remotely sensed imageries has become available for free, which enables a new approach to this topic. The aim of this research is to study land degradation as a multidimensional process incorporating its spatial and temporal components. We developed a methodological approach that makes use of long-term satellite Landsat data. Here, we use imagery of a typical degraded Mediterranean rangeland in Southern Cyprus (Randi Forest) for the years 1998-2015. We have chosen the NDVI as a proxy for vegetation greenness and applied different spatial landscape metrics to calculate changes in vegetation patterns over time. Further, we applied a time-series based approach (BFAST) on selected pixels, to look for sudden changes and trends in the vegetation dynamics. The results promoted our knowledge on how land degradation dynamics in Mediterranean rangelands can be captured through spatio-temporal vegetation dynamics and allowed us to select the most suitable metrics for further analysis. In the long-term, we aim at using Landsat satellite data covering 30 years. To gain a functional understanding of land degradation, we want to overlay our results from the remotely sensed data with results of an eco-hydrological model (SWAT).

The effect of radar azimuth angle on cultural data. [urban scene analysis and land use studies

NASA Technical Reports Server (NTRS)

Bryan, M. L.

1979-01-01

Emphasis is placed on the role that the orientation of observed features has on the grey tone of the resulting positive image. As an example it is shown that in the Los Angeles urbanized region, large areas have significantly lower grey tones than adjacent areas having similar land cover. It is determined that this effect is the result of the angle difference between the radar azimuth and the street pattern and especially the orientation of the walls of the structures imaged. Therefore, knowledge of this information is essential in order to ensure accurate interpretation of radar imagery. It is concluded that for radar systems operated from platforms which have fixed azimuth angles (e.g., satellite systems such as Seasat-A), an interpretation methodology, which considers street patterns, is considered especially critical for proper and accurate SAR imagery.

An ecologic study of peat landforms in Canada and Alaska

NASA Technical Reports Server (NTRS)

Glaser, P. H.

1986-01-01

The role of groundwater and surface runoff in controlling the water chemistry and development of peat landforms in northern Minnesota are described. The LANDSAT imagery taken duing spring break-up are particularly valuable in identifying potential zones of groundwater discharge. The vascular floras of raised bogs in eastern North Americas demonstrating the remarkabe uniformity of the ombrotrophic flora over broad geographic regions are described. The evolution of peat landforms in the major boreal peatlands of eastern America is examined. The LANDSAT imagery is used to determine the area of patterned to featureless peatlands, the area of ombrotrophic bog relative to minerotrophic fen, and the relative size and degree of streamlining of island landforms entirely composed of peat. Such measurements can be used to assess the role of climate, time, and hydrology in controlling the formation of peatland patterns across broad geographic regions.

Separation of man-made and natural patterns in high-altitude imagery of agricultural areas

NASA Technical Reports Server (NTRS)

Samulon, A. S.

1975-01-01

A nonstationary linear digital filter is designed and implemented which extracts the natural features from high-altitude imagery of agricultural areas. Essentially, from an original image a new image is created which displays information related to soil properties, drainage patterns, crop disease, and other natural phenomena, and contains no information about crop type or row spacing. A model is developed to express the recorded brightness in a narrow-band image in terms of man-made and natural contributions and which describes statistically the spatial properties of each. The form of the minimum mean-square error linear filter for estimation of the natural component of the scene is derived and a suboptimal filter is implemented. Nonstationarity of the two-dimensional random processes contained in the model requires a unique technique for deriving the optimum filter. Finally, the filter depends on knowledge of field boundaries. An algorithm for boundary location is proposed, discussed, and implemented.

Aerial Observations of Symmetric Instability at the North Wall of the Gulf Stream

NASA Astrophysics Data System (ADS)

Savelyev, I.; Thomas, L. N.; Smith, G. B.; Wang, Q.; Shearman, R. K.; Haack, T.; Christman, A. J.; Blomquist, B.; Sletten, M.; Miller, W. D.; Fernando, H. J. S.

2018-01-01

An unusual spatial pattern on the ocean surface was captured by thermal airborne swaths taken across a strong sea surface temperature front at the North Wall of the Gulf Stream. The thermal pattern on the cold side of the front resembles a staircase consisting of tens of steps, each up to ˜200 m wide and up to ˜0.3°C warm. The steps are well organized, clearly separated by sharp temperature gradients, mostly parallel and aligned with the primary front. The interpretation of the airborne imagery is aided by oceanographic measurements from two research vessels. Analysis of the in situ observations indicates that the front was unstable to symmetric instability, a type of overturning instability that can generate coherent structures with similar dimensions to the temperature steps seen in the airborne imagery. It is concluded that the images capture, for the first time, the surface temperature field of symmetric instability turbulence.

Pattern recognition analysis of polar clouds during summer and winter

NASA Technical Reports Server (NTRS)

Ebert, Elizabeth E.

1992-01-01

A pattern recognition algorithm is demonstrated which classifies eighteen surface and cloud types in high-latitude AVHRR imagery based on several spectral and textural features, then estimates the cloud properties (fractional coverage, albedo, and brightness temperature) using a hybrid histogram and spatial coherence technique. The summertime version of the algorithm uses both visible and infrared data (AVHRR channels 1-4), while the wintertime version uses only infrared data (AVHRR channels 3-5). Three days of low-resolution AVHRR imagery from the Arctic and Antarctic during January and July 1984 were analyzed for cloud type and fractional coverage. The analysis showed significant amounts of high cloudiness in the Arctic during one day in winter. The Antarctic summer scene was characterized by heavy cloud cover in the southern ocean and relatively clear conditions in the continental interior. A large region of extremely low brightness temperatures in East Antarctica during winter suggests the presence of polar stratospheric cloud.

Estimation of Cirrus and Stratus Cloud Heights Using Landsat Imagery

NASA Technical Reports Server (NTRS)

Inomata, Yasushi; Feind, R. E.; Welch, R. M.

1996-01-01

A new method based upon high-spatial-resolution imagery is presented that matches cloud and shadow regions to estimate cirrus and stratus cloud heights. The distance between the cloud and the matching shadow pattern is accomplished using the 2D cross-correlation function from which the cloud height is derived. The distance between the matching cloud-shadow patterns is verified manually. The derived heights also are validated through comparison with a temperature-based retrieval of cloud height. It is also demonstrated that an estimate of cloud thickness can be retrieved if both the sunside and anti-sunside of the cloud-shadow pair are apparent. The technique requires some intepretation to determine the cloud height level retrieved (i.e., the top, base, or mid-level). It is concluded that the method is accurate to within several pixels, equivalent to cloud height variations of about +/- 250 m. The results show that precise placement of the templates is unnecessary, so that the development of a semi-automated procedure is possible. Cloud templates of about 64 pixels on a side or larger produce consistent results. The procedure was repeated for imagery degraded to simulate lower spatial resolutions. The results suggest that spatial resolution of 150-200 m or better is necessary in order to obtain stable cloud height retrievals.

Investigation of relationships between linears, total and hazy areas, and petroleum production in the Williston Basin: An ERTS approach

NASA Technical Reports Server (NTRS)

Erickson, J. M.; Street, J. S. (Principal Investigator); Munsell, C. J.; Obrien, D. E.

1975-01-01

The author has identified the following significant results. ERTS-1 imagery in a variety of formats was used to locate linear, tonal, and hazy features and to relate them to areas of hydrocarbon production in the Williston Basin of North Dakota, eastern Montana, and northern South Dakota. Derivative maps of rectilinear, curvilinear, tonal, and hazy features were made using standard laboratory techniques. Mapping of rectilinears on both bands 5 and 7 over the entire region indicated the presence of a northeast-southwest and a northwest-southeast regional trend which is indicative of the bedrock fracture pattern in the basin. Curved lines generally bound areas of unique tone, maps of tonal patterns repeat many of the boundaries seen on curvilinear maps. Tones were best analyzed on spring and fall imagery in the Williston Basin. It is postulated that hazy areas are caused by atmospheric phenomena. The ability to use ERTS imagery as an exploration tool was examined where petroleum and gas are presently produced (Bottineau Field, Nesson and Antelope anticlines, Redwing Creek, and Cedar Creek anticline). It is determined that some tonal and linear features coincide with location of present production in Redwing and Cedar Creeks. In the remaining cases, targets could not be sufficiently well defined to justify this method.

Application of remote sensing in the study of vegetation and soils in Idaho

NASA Technical Reports Server (NTRS)

Tisdale, E. W. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Comparison of ERTS-1 imagery and USGS 1:250,000 scale maps of study areas with known ground points revealed significant map errors. These errors were sufficient to render impractical the projection of ERTS-1 imagery directly onto maps of the area. Marked differences were found in the delineation of ground features by different MSS bands. Generally, Band 4 was least useful, while Band 5 proved valuable for indicating patterns of native vegetation, cultivated areas - both dry and irrigated, lava fields, drainage basins, and deep bodies of water. Band 6 was better for landforms and drainages and for shallow bodies of water than Band 5 but inferior for indicating patterns in native vegetation and most types of cultivated land. Band 7 was best of all for indicating lava flows, water bodies, and landform features. Use of a additive color viewer-projector aided greatly in separation of images. A combination of Bands 5 and 7 with appropriate color filters proved best for separating most types of native vegetation and cultivated crops. Landform features and water bodies also showed well with this combination. The addition of Band 4 imagery to these further enhanced the identification of semi-dormant vegetation.

Insensitivity of visual short-term memory to irrelevant visual information.

PubMed

Andrade, Jackie; Kemps, Eva; Werniers, Yves; May, Jon; Szmalec, Arnaud

2002-07-01

Several authors have hypothesized that visuo-spatial working memory is functionally analogous to verbal working memory. Irrelevant background speech impairs verbal short-term memory. We investigated whether irrelevant visual information has an analogous effect on visual short-term memory, using a dynamic visual noise (DVN) technique known to disrupt visual imagery (Quinn & McConnell, 1996b). Experiment I replicated the effect of DVN on pegword imagery. Experiments 2 and 3 showed no effect of DVN on recall of static matrix patterns, despite a significant effect of a concurrent spatial tapping task. Experiment 4 showed no effect of DVN on encoding or maintenance of arrays of matrix patterns, despite testing memory by a recognition procedure to encourage visual rather than spatial processing. Serial position curves showed a one-item recency effect typical of visual short-term memory. Experiment 5 showed no effect of DVN on short-term recognition of Chinese characters, despite effects of visual similarity and a concurrent colour memory task that confirmed visual processing of the characters. We conclude that irrelevant visual noise does not impair visual short-term memory. Visual working memory may not be functionally analogous to verbal working memory, and different cognitive processes may underlie visual short-term memory and visual imagery.

Variability of Basal Melt Beneath the Pine Island Glacier Ice Shelf, West Antarctica

NASA Technical Reports Server (NTRS)

Bindschadler, Robert; Vaughan, David G.; Vornberger, Patricia

2011-01-01

Observations from satellite and airborne platforms are combined with model calculations to infer the nature and efficiency of basal melting of the Pine Island Glacier ice shelf, West Antarctica, by ocean waters. Satellite imagery shows surface features that suggest ice-shelf-wide changes to the ocean s influence on the ice shelf as the grounding line retreated. Longitudinal profiles of ice surface and bottom elevations are analyzed to reveal a spatially dependent pattern of basal melt with an annual melt flux of 40.5 Gt/a. One profile captures a persistent set of surface waves that correlates with quasi-annual variations of atmospheric forcing of Amundsen Sea circulation patterns, establishing a direct connection between atmospheric variability and sub-ice-shelf melting. Ice surface troughs are hydrostatically compensated by ice-bottom voids up to 150m deep. Voids form dynamically at the grounding line, triggered by enhanced melting when warmer-than-average water arrives. Subsequent enlargement of the voids is thermally inefficient (4% or less) compared with an overall melting efficiency beneath the ice shelf of 22%. Residual warm water is believed to cause three persistent polynyas at the ice-shelf front seen in Landsat imagery. Landsat thermal imagery confirms the occurrence of warm water at the same locations.

Region-based automatic building and forest change detection on Cartosat-1 stereo imagery

NASA Astrophysics Data System (ADS)

Tian, J.; Reinartz, P.; d'Angelo, P.; Ehlers, M.

2013-05-01

In this paper a novel region-based method is proposed for change detection using space borne panchromatic Cartosat-1 stereo imagery. In the first step, Digital Surface Models (DSMs) from two dates are generated by semi-global matching. The geometric lateral resolution of the DSMs is 5 m × 5 m and the height accuracy is in the range of approximately 3 m (RMSE). In the second step, mean-shift segmentation is applied on the orthorectified images of two dates to obtain initial regions. A region intersection following a merging strategy is proposed to get minimum change regions and multi-level change vectors are extracted for these regions. Finally change detection is achieved by combining these features with weighted change vector analysis. The result evaluations demonstrate that the applied DSM generation method is well suited for Cartosat-1 imagery, and the extracted height values can largely improve the change detection accuracy, moreover it is shown that the proposed change detection method can be used robustly for both forest and industrial areas.

Balancing a simulated inverted pendulum through motor imagery: an EEG-based real-time control paradigm.

PubMed

Yue, Jingwei; Zhou, Zongtan; Jiang, Jun; Liu, Yadong; Hu, Dewen

2012-08-30

Most brain-computer interfaces (BCIs) are non-time-restraint systems. However, the method used to design a real-time BCI paradigm for controlling unstable devices is still a challenging problem. This paper presents a real-time feedback BCI paradigm for controlling an inverted pendulum on a cart (IPC). In this paradigm, sensorimotor rhythms (SMRs) were recorded using 15 active electrodes placed on the surface of the subject's scalp. Subsequently, common spatial pattern (CSP) was used as the basic filter to extract spatial patterns. Finally, linear discriminant analysis (LDA) was used to translate the patterns into control commands that could stabilize the simulated inverted pendulum. Offline trainings were employed to teach the subjects to execute corresponding mental tasks, such as left/right hand motor imagery. Five subjects could successfully balance the online inverted pendulum for more than 35s. The results demonstrated that BCIs are able to control nonlinear unstable devices. Furthermore, the demonstration and extension of real-time continuous control might be useful for the real-life application and generalization of BCI. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

How feedback, motor imagery, and reward influence brain self-regulation using real-time fMRI.

PubMed

Sepulveda, Pradyumna; Sitaram, Ranganatha; Rana, Mohit; Montalba, Cristian; Tejos, Cristian; Ruiz, Sergio

2016-09-01

The learning process involved in achieving brain self-regulation is presumed to be related to several factors, such as type of feedback, reward, mental imagery, duration of training, among others. Explicitly instructing participants to use mental imagery and monetary reward are common practices in real-time fMRI (rtfMRI) neurofeedback (NF), under the assumption that they will enhance and accelerate the learning process. However, it is still not clear what the optimal strategy is for improving volitional control. We investigated the differential effect of feedback, explicit instructions and monetary reward while training healthy individuals to up-regulate the blood-oxygen-level dependent (BOLD) signal in the supplementary motor area (SMA). Four groups were trained in a two-day rtfMRI-NF protocol: GF with NF only, GF,I with NF + explicit instructions (motor imagery), GF,R with NF + monetary reward, and GF,I,R with NF + explicit instructions (motor imagery) + monetary reward. Our results showed that GF increased significantly their BOLD self-regulation from day-1 to day-2 and GF,R showed the highest BOLD signal amplitude in SMA during the training. The two groups who were instructed to use motor imagery did not show a significant learning effect over the 2 days. The additional factors, namely motor imagery and reward, tended to increase the intersubject variability in the SMA during the course of training. Whole brain univariate and functional connectivity analyses showed common as well as distinct patterns in the four groups, representing the varied influences of feedback, reward, and instructions on the brain. Hum Brain Mapp 37:3153-3171, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Sex moderates stress reactivity in heavy drinkers.

PubMed

Hartwell, Emily E; Ray, Lara A

2013-11-01

Psychological stress and alcohol use disorders have a well-known connection. Individual differences in stress reactivity have been an area of interest in alcohol research, particularly given the relationship between craving and stress reactivity to later relapse. The present study examines the role of sex on stress-induced alcohol craving and emotional reactivity using a guided imagery stress paradigm. Participants were 64 non-treatment seeking heavy drinkers from the community who completed a two-session protocol that included two guided imagery exposures, Stress and Neutral. Participants reported their mood and craving before and after each exposure using the Differential Emotions Scale and the Alcohol Urge Questionnaire respectively. Analyses revealed a significant Stress × Sex × Trial effect on craving [F (1,61) = 5.35; p < .05] after controlling for AUDIT scores [F (1,61) = 8.16; p < .01] such that females reported greater increases in craving from baseline to post-imagery during the stress imagery versus the neutral imagery condition, than did males. Mood reactivity analysis showed similar patterns. Specifically, there was a significant Stress × Sex × Trial effect on the anxiety subscale of the DES [F (1,61) = 15.81; p < .001] such that females reported greater increases in anxiety from baseline to post-imagery during the stress imagery versus the neutral conditions, than did males. These results suggest that female heavy drinkers were more sensitive to the effects of the stress-induction on alcohol craving and mood reactivity than males. If supported by future studies, these initial findings may help advance understanding of the mechanisms of stress and mood regulation as central to alcoholism liability and recovery in females. © 2013 Elsevier Ltd. All rights reserved.

Investigation of LANDSAT imagery on correlations between ore deposits and major shield structures in Finland. [Baltic Shield

NASA Technical Reports Server (NTRS)

Tuominen, H. V. (Principal Investigator); Kuosmanen, V.

1975-01-01

The author has identified the following significant results. On the central Baltic Shield, the concept of drainage patterns can be extended to smaller scales in which case many cultural features become involved to the spatial patterns influenced by bedrock structure. Features resulting from agriculture activity and timbering often exaggerate the influence of the bedrock on the image texture.

Recce imagery compression options

NASA Astrophysics Data System (ADS)

Healy, Donald J.

1995-09-01

The errors introduced into reconstructed RECCE imagery by ATARS DPCM compression are compared to those introduced by the more modern DCT-based JPEG compression algorithm. For storage applications in which uncompressed sensor data is available JPEG provides better mean-square-error performance while also providing more flexibility in the selection of compressed data rates. When ATARS DPCM compression has already been performed, lossless encoding techniques may be applied to the DPCM deltas to achieve further compression without introducing additional errors. The abilities of several lossless compression algorithms including Huffman, Lempel-Ziv, Lempel-Ziv-Welch, and Rice encoding to provide this additional compression of ATARS DPCM deltas are compared. It is shown that the amount of noise in the original imagery significantly affects these comparisons.

Topological anomaly detection performance with multispectral polarimetric imagery

NASA Astrophysics Data System (ADS)

Gartley, M. G.; Basener, W.,

2009-05-01

Polarimetric imaging has demonstrated utility for increasing contrast of manmade targets above natural background clutter. Manual detection of manmade targets in multispectral polarimetric imagery can be challenging and a subjective process for large datasets. Analyst exploitation may be improved utilizing conventional anomaly detection algorithms such as RX. In this paper we examine the performance of a relatively new approach to anomaly detection, which leverages topology theory, applied to spectral polarimetric imagery. Detection results for manmade targets embedded in a complex natural background will be presented for both the RX and Topological Anomaly Detection (TAD) approaches. We will also present detailed results examining detection sensitivities relative to: (1) the number of spectral bands, (2) utilization of Stoke's images versus intensity images, and (3) airborne versus spaceborne measurements.

National project for the evaluation of ERTS imagery applications to various earth resources problems of Turkey

NASA Technical Reports Server (NTRS)

Alpan, S. (Principal Investigator)

1976-01-01

The author has identified the following significant results. It is observed that LANDSAT images can be used in preparing an accurate tectonic map of the study areas. These images are most useful in geological mapping areas where vegetation cover is sparse. LANDSAT images can be used to identify and separate evergreens and trees with leaves, and they can successfully delineate boundaries of forestry areas. Water holding capacity of the soil, internal and external drainage, vegetation pattern, irrigated and nonirrigated land, and fallow and planted fields are also detected on the LANDSAT imagery.

Utilizing remote sensing of thematic mapper data to improve our understanding of estuarine processes and their influence on the productivity of estuarine-dependent fisheries

NASA Technical Reports Server (NTRS)

Browder, Joan A.; May, L. Nelson, Jr.; Rosenthal, Alan; Baumann, Robert H.; Gosselink, James G.

1987-01-01

A stochastic spatial computer model addressing coastal resource problems in Lousiana is being refined and validated using thematic mapper (TM) imagery. The TM images of brackish marsh sites were processed and data were tabulated on spatial parameters from TM images of the salt marsh sites. The Fisheries Image Processing Systems (FIPS) was used to analyze the TM scene. Activities were concentrated on improving the structure of the model and developing a structure and methodology for calibrating the model with spatial-pattern data from the TM imagery.

Image Processor

NASA Technical Reports Server (NTRS)

1989-01-01

Texas Instruments Programmable Remapper is a research tool used to determine how to best utilize the part of a patient's visual field still usable by mapping onto his field of vision with manipulated imagery. It is an offshoot of a NASA program for speeding up, improving the accuracy of pattern recognition in video imagery. The Remapper enables an image to be "pushed around" so more of it falls into the functional portions in the retina of a low vision person. It works at video rates, and researchers hope to significantly reduce its size and cost, creating a wearable prosthesis for visually impaired people.

Different atmospheric effects in remote sensing of uniform and nonuniform surfaces

NASA Technical Reports Server (NTRS)

Kaufman, Y. J.; Fraser, R. S.

1982-01-01

The atmospheric effect on the radiance of sunlight scattered from the earth-atmosphere system is greatly dependent on the surface reflectance pattern, the contrast between adjacent fields, and the optical properties of the atmosphere. In addition, the atmospheric effect is described by the range and magnitude of the adjacency effects, the atmospheric modulation transfer function, and the apparent spatial resolution of remotely sensed imagery. This paper discusses the atmospheric effect on classification of surface features and shows that surface nonuniformity can be used for developing procedures to remove the atmospheric effect from the satellite imagery.

Remote sensing inputs to landscape models which predict future spatial land use patterns for hydrologic models

NASA Technical Reports Server (NTRS)

Miller, L. D.; Tom, C.; Nualchawee, K.

1977-01-01

A tropical forest area of Northern Thailand provided a test case of the application of the approach in more natural surroundings. Remote sensing imagery subjected to proper computer analysis has been shown to be a very useful means of collecting spatial data for the science of hydrology. Remote sensing products provide direct input to hydrologic models and practical data bases for planning large and small-scale hydrologic developments. Combining the available remote sensing imagery together with available map information in the landscape model provides a basis for substantial improvements in these applications.

Novel wavelength diversity technique for high-speed atmospheric turbulence compensation

NASA Astrophysics Data System (ADS)

Arrasmith, William W.; Sullivan, Sean F.

2010-04-01

The defense, intelligence, and homeland security communities are driving a need for software dominant, real-time or near-real time atmospheric turbulence compensated imagery. The development of parallel processing capabilities are finding application in diverse areas including image processing, target tracking, pattern recognition, and image fusion to name a few. A novel approach to the computationally intensive case of software dominant optical and near infrared imaging through atmospheric turbulence is addressed in this paper. Previously, the somewhat conventional wavelength diversity method has been used to compensate for atmospheric turbulence with great success. We apply a new correlation based approach to the wavelength diversity methodology using a parallel processing architecture enabling high speed atmospheric turbulence compensation. Methods for optical imaging through distributed turbulence are discussed, simulation results are presented, and computational and performance assessments are provided.

Automatic tissue characterization from ultrasound imagery

NASA Astrophysics Data System (ADS)

Kadah, Yasser M.; Farag, Aly A.; Youssef, Abou-Bakr M.; Badawi, Ahmed M.

1993-08-01

In this work, feature extraction algorithms are proposed to extract the tissue characterization parameters from liver images. Then the resulting parameter set is further processed to obtain the minimum number of parameters representing the most discriminating pattern space for classification. This preprocessing step was applied to over 120 pathology-investigated cases to obtain the learning data for designing the classifier. The extracted features are divided into independent training and test sets and are used to construct both statistical and neural classifiers. The optimal criteria for these classifiers are set to have minimum error, ease of implementation and learning, and the flexibility for future modifications. Various algorithms for implementing various classification techniques are presented and tested on the data. The best performance was obtained using a single layer tensor model functional link network. Also, the voting k-nearest neighbor classifier provided comparably good diagnostic rates.

Sensing Urban Land-Use Patterns by Integrating Google Tensorflow and Scene-Classification Models

NASA Astrophysics Data System (ADS)

Yao, Y.; Liang, H.; Li, X.; Zhang, J.; He, J.

2017-09-01

With the rapid progress of China's urbanization, research on the automatic detection of land-use patterns in Chinese cities is of substantial importance. Deep learning is an effective method to extract image features. To take advantage of the deep-learning method in detecting urban land-use patterns, we applied a transfer-learning-based remote-sensing image approach to extract and classify features. Using the Google Tensorflow framework, a powerful convolution neural network (CNN) library was created. First, the transferred model was previously trained on ImageNet, one of the largest object-image data sets, to fully develop the model's ability to generate feature vectors of standard remote-sensing land-cover data sets (UC Merced and WHU-SIRI). Then, a random-forest-based classifier was constructed and trained on these generated vectors to classify the actual urban land-use pattern on the scale of traffic analysis zones (TAZs). To avoid the multi-scale effect of remote-sensing imagery, a large random patch (LRP) method was used. The proposed method could efficiently obtain acceptable accuracy (OA = 0.794, Kappa = 0.737) for the study area. In addition, the results show that the proposed method can effectively overcome the multi-scale effect that occurs in urban land-use classification at the irregular land-parcel level. The proposed method can help planners monitor dynamic urban land use and evaluate the impact of urban-planning schemes.

BCI Competition IV – Data Set I: Learning Discriminative Patterns for Self-Paced EEG-Based Motor Imagery Detection

PubMed Central

Zhang, Haihong; Guan, Cuntai; Ang, Kai Keng; Wang, Chuanchu

2012-01-01

Detecting motor imagery activities versus non-control in brain signals is the basis of self-paced brain-computer interfaces (BCIs), but also poses a considerable challenge to signal processing due to the complex and non-stationary characteristics of motor imagery as well as non-control. This paper presents a self-paced BCI based on a robust learning mechanism that extracts and selects spatio-spectral features for differentiating multiple EEG classes. It also employs a non-linear regression and post-processing technique for predicting the time-series of class labels from the spatio-spectral features. The method was validated in the BCI Competition IV on Dataset I where it produced the lowest prediction error of class labels continuously. This report also presents and discusses analysis of the method using the competition data set. PMID:22347153

Summary of an integrated ERTS-1 project and its results at the Missouri Geological Survey

NASA Technical Reports Server (NTRS)

Martin, J. A.; Allen, W. H.; Rath, D. L.; Rueff, A.

1974-01-01

Use of the ERTS imagery involved the recognition and interpretation of various ground patterns. Analysis and application are tied to ongoing programs. Specific studies utilizing the imagery and NASA aircraft photography are: a statewide lake and dam inventory; assessment of flooding and floodprone areas along the Missouri portion of the Mississippi and Missouri Rivers; land-use classification for several counties; structural features in selected areas; and Pleistocene features in northern Missouri. Though it has been suggested that repetitive coverage is not necessary for geologic studies, it is this specific feature along with the synoptic view of large portions of the State that provided the potential for the utilization of the ERTS imagery in Missouri. Other State agencies, Departments of Conservation, Agriculture, and Community Affairs, have expressed interest in the potential application of ERTS data in their respective fields.

Mapping Atlantic coastal marshlands, Maryland, Georgia, using ERTS-1 imagery

NASA Technical Reports Server (NTRS)

Anderson, R. R.; Carter, V. L.; Mcginness, J. W., Jr.

1973-01-01

Eastern coastal marshes are the most extensive and productive in the United States. A relatively low cost, moderately accurate method is needed to map these areas for management and protection. Groundbased and low-altitude aircraft methods for mapping are time-consuming and quite expensive. The launch of NASA's Earth Resources Technology Satellite has provided an opportunity to test the feasibility of mapping wetlands using small scale imagery. The test sites selected were in Chesapeake Bay, Maryland, and Ossabaw Island, Georgia. Results of the investigation indicate that the following may be ascertained from ERTS imagery, enlarged to 1:250,000: (1) upper wetland boundary; (2) drainage pattern in the wetland; (3) plant communities; (4) ditching activities associated with agriculture; and (5) lagooning for water-side home development. Conclusions are that ERTS will be an excellent tool for many types of coastal wetland mapping.

Compiling Techniques for East Antarctic Ice Velocity Mapping Based on Historical Optical Imagery

NASA Astrophysics Data System (ADS)

Li, X.; Li, R.; Qiao, G.; Cheng, Y.; Ye, W.; Gao, T.; Huang, Y.; Tian, Y.; Tong, X.

2018-05-01

Ice flow velocity over long time series in East Antarctica plays a vital role in estimating and predicting the mass balance of Antarctic Ice Sheet and its contribution to global sea level rise. However, there is no Antarctic ice velocity product with large space scale available showing the East Antarctic ice flow velocity pattern before the 1990s. We proposed three methods including parallax decomposition, grid-based NCC image matching, feature and gird-based image matching with constraints for estimation of surface velocity in East Antarctica based on ARGON KH-5 and LANDSAT imagery, showing the feasibility of using historical optical imagery to obtain Antarctic ice motion. Based on these previous studies, we presented a set of systematic method for developing ice surface velocity product for the entire East Antarctica from the 1960s to the 1980s in this paper.

Arctic and subarctic environmental analyses utilizing ERTS-1 imagery

NASA Technical Reports Server (NTRS)

Anderson, D. M. (Principal Investigator); Mckim, H. L.; Gatto, L. W.; Haugen, R. K.; Crowder, W. K.; Slaughter, C. W.; Marlar, T. L.

1974-01-01

The author has identified the following significant results. ERTS-1 imagery provides a means of distinguishing and monitoring estuarine surface water circulation patterns and changes in the relative sediment load of discharging rivers on a regional basis. Physical boundaries mapped from ERTS-1 imagery in combination with ground truth obtained from existing small scale maps and other sources resulted in improved and more detailed maps of permafrost terrain and vegetation for the same area. Snowpack cover within a research watershed has been analyzed and compared to ground data. Large river icings along the proposed Alaska pipeline route from Prudhoe Bay to the Brooks Range have been monitored. Sea ice deformation and drift northeast of Point Barrow, Alaska have been measured during a four day period in March and shore-fast ice accumulation and ablation along the west coast of Alaska have been mapped for the spring and early summer seasons.

Advances in image compression and automatic target recognition; Proceedings of the Meeting, Orlando, FL, Mar. 30, 31, 1989

NASA Technical Reports Server (NTRS)

Tescher, Andrew G. (Editor)

1989-01-01

Various papers on image compression and automatic target recognition are presented. Individual topics addressed include: target cluster detection in cluttered SAR imagery, model-based target recognition using laser radar imagery, Smart Sensor front-end processor for feature extraction of images, object attitude estimation and tracking from a single video sensor, symmetry detection in human vision, analysis of high resolution aerial images for object detection, obscured object recognition for an ATR application, neural networks for adaptive shape tracking, statistical mechanics and pattern recognition, detection of cylinders in aerial range images, moving object tracking using local windows, new transform method for image data compression, quad-tree product vector quantization of images, predictive trellis encoding of imagery, reduced generalized chain code for contour description, compact architecture for a real-time vision system, use of human visibility functions in segmentation coding, color texture analysis and synthesis using Gibbs random fields.

Evaluation of the capabilities of satellite imagery for monitoring regional air pollution episodes

NASA Technical Reports Server (NTRS)

Barnes, J. C.; Bowley, C. J.; Burke, H. H. K.

1979-01-01

A comparative analysis of satellite visible channel imagery and ground based aerosol measurements is carried out for three cases representing a significant pollution episodes based on low surface visibility and high sulfate levels. The feasibility of detecting pollution episodes from space is also investigated using a simulation model. The model results are compared to quantitative information derived from digitized satellite data. The results show that when levels are or = 30 micrograms/cu, a haze pattern that correlates closely with the area of reported low surface visibilities and high micrograms sulfate levels can be detected in satellite visible channel imagery. The model simulation demonstrates the potential of the satellite to monitor the magnitude and areal extent of pollution episodes. Quantitative information on total aerosol amount derived from the satellite digitized data using the atmospheric radiative transfer model agrees well with the results obtained from the ground based measurements.

Emotion regulation through execution, observation, and imagery of emotional movements

PubMed Central

Shafir, Tal; Taylor, Stephan F.; Atkinson, Anthony P.; Langenecker, Scott A.; Zubieta, Jon-Kar

2014-01-01

According to Damasio’s somatic marker hypothesis, emotions are generated by conveying the current state of the body to the brain through interoceptive and proprioceptive afferent input. The resulting brain activation patterns represent unconscious emotions and correlate with subjective feelings. This proposition implies a corollary that the deliberate control of motor behavior could regulate feelings. We tested this possibility, hypothesizing that engaging in movements associated with a certain emotion would enhance that emotion and/or the corresponding valence. Furthermore, because motor imagery and observation are thought to activate the same mirror-neuron network engaged during motor execution, they might also activate the same emotional processing circuits, leading to similar emotional effects. Therefore, we measured the effects of motor execution, motor imagery and observation of whole-body dynamic expressions of emotions (happiness, sadness, fear) on affective state. All three tasks enhanced the corresponding affective state, indicating their potential to regulate emotions. PMID:23561915

A reduction in ag/residential signature conflict using principal components analysis of LANDSAT temporal data

NASA Technical Reports Server (NTRS)

Williams, D. L.; Borden, F. Y.

1977-01-01

Methods to accurately delineate the types of land cover in the urban-rural transition zone of metropolitan areas were considered. The application of principal components analysis to multidate LANDSAT imagery was investigated as a means of reducing the overlap between residential and agricultural spectral signatures. The statistical concepts of principal components analysis were discussed, as well as the results of this analysis when applied to multidate LANDSAT imagery of the Washington, D.C. metropolitan area.

GOES-R Proving Ground Activities at the NASA Short-Term Prediction Research and Transition (SPoRT) Center

NASA Technical Reports Server (NTRS)

Molthan, Andrew

2011-01-01

SPoRT is actively involved in GOES-R Proving Ground activities in a number of ways: (1) Applying the paradigm of product development, user training, and interaction to foster interaction with end users at NOAA forecast offices national centers. (2) Providing unique capabilities in collaboration with other GOES-R Proving Ground partners (a) Hybrid GOES-MODIS imagery (b) Pseudo-GLM via regional lightning mapping arrays (c) Developing new RGB imagery from EUMETSAT guidelines

Kansas environmental and resource study: A Great Plains model. [land use, image enhancement, winter wheat, agriculture, water resources, and pattern recognition

NASA Technical Reports Server (NTRS)

Haralick, R. M.; Kanemasu, E. T.; Morain, S. A.; Yarger, H. L.; Ulaby, F. T.; Davis, J. C. (Principal Investigator); Bosley, R. J.; Williams, D. L.; Mccauley, J. R.; Mcnaughton, J. L.

1973-01-01

The author has identified the following significant results. Improvement in the land use classification accuracy of ERTS-1 MSS multi-images over Kansas can be made using two distances between neighboring grey tone N-tuples instead of one distance. Much more information is contained texturally than spectrally on the Kansas image. Ground truth measurements indicate that reflectance ratios of the 545 and 655 nm wavebands provide an index of plant development and possibly physiological stress. Preliminary analysis of MSS 4 and 5 channels substantiate the ground truth interpretation. Results of the land use mapping experiment indicate that ERTS-1 imagery has major potential in regionalization. The ways in which land is utilized within these regions may then be studied more effectively than if no adequate regionalization is available. A model for estimating wheat yield per acre has been applied to acreage estimates derived from ERTS-1 imagery to project the 1973 wheat yields for a ten county area in southwest Kansas. The results are within 3% of the preharvest estimates for the same area prepared by the USDA. Visual identification of winter wheat is readily achieved by using a temporal sequence of images. Identification can be improve by stratifying the project area into subregions having more or less homogeneous agricultural practices and crop mixes.

Infrared Cephalic-Vein to Assist Blood Extraction Tasks: Automatic Projection and Recognition

NASA Astrophysics Data System (ADS)

Lagüela, S.; Gesto, M.; Riveiro, B.; González-Aguilera, D.

2017-05-01

Thermal infrared band is not commonly used in photogrammetric and computer vision algorithms, mainly due to the low spatial resolution of this type of imagery. However, this band captures sub-superficial information, increasing the capabilities of visible bands regarding applications. This fact is especially important in biomedicine and biometrics, allowing the geometric characterization of interior organs and pathologies with photogrammetric principles, as well as the automatic identification and labelling using computer vision algorithms. This paper presents advances of close-range photogrammetry and computer vision applied to thermal infrared imagery, with the final application of Augmented Reality in order to widen its application in the biomedical field. In this case, the thermal infrared image of the arm is acquired and simultaneously projected on the arm, together with the identification label of the cephalic-vein. This way, blood analysts are assisted in finding the vein for blood extraction, especially in those cases where the identification by the human eye is a complex task. Vein recognition is performed based on the Gaussian temperature distribution in the area of the vein, while the calibration between projector and thermographic camera is developed through feature extraction and pattern recognition. The method is validated through its application to a set of volunteers, with different ages and genres, in such way that different conditions of body temperature and vein depth are covered for the applicability and reproducibility of the method.

Improving the Accuracy and Training Speed of Motor Imagery Brain-Computer Interfaces Using Wavelet-Based Combined Feature Vectors and Gaussian Mixture Model-Supervectors.

PubMed

Lee, David; Park, Sang-Hoon; Lee, Sang-Goog

2017-10-07

In this paper, we propose a set of wavelet-based combined feature vectors and a Gaussian mixture model (GMM)-supervector to enhance training speed and classification accuracy in motor imagery brain-computer interfaces. The proposed method is configured as follows: first, wavelet transforms are applied to extract the feature vectors for identification of motor imagery electroencephalography (EEG) and principal component analyses are used to reduce the dimensionality of the feature vectors and linearly combine them. Subsequently, the GMM universal background model is trained by the expectation-maximization (EM) algorithm to purify the training data and reduce its size. Finally, a purified and reduced GMM-supervector is used to train the support vector machine classifier. The performance of the proposed method was evaluated for three different motor imagery datasets in terms of accuracy, kappa, mutual information, and computation time, and compared with the state-of-the-art algorithms. The results from the study indicate that the proposed method achieves high accuracy with a small amount of training data compared with the state-of-the-art algorithms in motor imagery EEG classification.

Visualization Case Study: Eyjafjallajökull Ash (Invited)

NASA Astrophysics Data System (ADS)

Simmon, R.

2010-12-01

Although data visualization is a powerful tool in Earth science, the resulting imagery is often complex and difficult to interpret for non-experts. Students, journalists, web site visitors, or museum attendees often have difficulty understanding some of the imagery scientists create, particularly false-color imagery and data-driven maps. Many visualizations are designed for data exploration or peer communication, and often follow discipline conventions or are constrained by software defaults. Different techniques are necessary for communication with a broad audience. Data visualization combines ideas from cognitive science, graphic design, and cartography, and applies them to the challenge of presenting data clearly. Visualizers at NASA's Earth Observatory web site (earthobservatory.nasa.gov) use these techniques to craft remote sensing imagery for interested but non-expert readers. Images range from natural-color satellite images and multivariate maps to illustrations of abstract concepts. I will use imagery of the eruption of Iceland's Eyjafjallajökull volcano as a case study, showing specific applications of general design techniques. By using color carefully (including contextual data), precisely aligning disparate data sets, and highlighting important features, we crafted an image that clearly conveys the complex vertical and horizontal distribution of airborne ash.

NASA Earth Observations (NEO): Data Imagery for Education and Visualization

NASA Astrophysics Data System (ADS)

Ward, K.

2008-12-01

NASA Earth Observations (NEO) has dramatically simplified public access to georeferenced imagery of NASA remote sensing data. NEO targets the non-traditional data users who are currently underserved by functionality and formats available from the existing data ordering systems. These users include formal and informal educators, museum and science center personnel, professional communicators, and citizen scientists. NEO currently serves imagery from 45 different datasets with daily, weekly, and/or monthly temporal resolutions, with more datasets currently under development. The imagery from these datasets is produced in coordination with several data partners who are affiliated either with the instrument science teams or with the respective data processing center. NEO is a system of three components -- website, WMS (Web Mapping Service), and ftp archive -- which together are able to meet the wide-ranging needs of our users. Some of these needs include the ability to: view and manipulate imagery using the NEO website -- e.g., applying color palettes, resizing, exporting to a variety of formats including PNG, JPEG, KMZ (Google Earth), GeoTIFF; access the NEO collection via a standards-based API (WMS); and create customized exports for select users (ftp archive) such as Science on a Sphere, NASA's Earth Observatory, and others.

Intense imagery movements: a common and distinct paediatric subgroup of motor stereotypies.

PubMed

Robinson, Sally; Woods, Martin; Cardona, Francesco; Baglioni, Valentina; Hedderly, Tammy

2014-12-01

The aim of this article is to describe a subgroup of children who presented with stereotyped movements in the context of episodes of intense imagery. This is of relevance to current discussions regarding the clinical usefulness of diagnosing motor stereotypies during development. The sample consisted of 10 children (nine males, one female; mean age 8y 6mo [SD 2y 5mo], range 6-15y). Referrals were from acute paediatricians, neurologists, and tertiary epilepsy services. Children were assessed by multidisciplinary teams with expertise in paediatric movement disorders. Stereotypies presented as paroxysmal complex movements involving upper and lower limbs. Imagery themes typically included computer games (60%), cartoons/films (40%), and fantasy scenes (30%). Comorbid developmental difficulties were reported for 80% of children. Brain imaging and electrophysiological investigations had been conducted for 50% of the children before referral to the clinic. The descriptive term 'intense imagery movements' (IIM) was applied if (after interview) the children reported engaging in acts of imagery while performing stereotyped movements. We believe these children may form a common and discrete stereotypy subgroup, with the concept of IIM being clinically useful to ensure the accurate diagnosis and clinical management of this paediatric movement disorder. © 2014 Mac Keith Press.

Scanning silence: mental imagery of complex sounds.

PubMed

Bunzeck, Nico; Wuestenberg, Torsten; Lutz, Kai; Heinze, Hans-Jochen; Jancke, Lutz

2005-07-15

In this functional magnetic resonance imaging (fMRI) study, we investigated the neural basis of mental auditory imagery of familiar complex sounds that did not contain language or music. In the first condition (perception), the subjects watched familiar scenes and listened to the corresponding sounds that were presented simultaneously. In the second condition (imagery), the same scenes were presented silently and the subjects had to mentally imagine the appropriate sounds. During the third condition (control), the participants watched a scrambled version of the scenes without sound. To overcome the disadvantages of the stray acoustic scanner noise in auditory fMRI experiments, we applied sparse temporal sampling technique with five functional clusters that were acquired at the end of each movie presentation. Compared to the control condition, we found bilateral activations in the primary and secondary auditory cortices (including Heschl's gyrus and planum temporale) during perception of complex sounds. In contrast, the imagery condition elicited bilateral hemodynamic responses only in the secondary auditory cortex (including the planum temporale). No significant activity was observed in the primary auditory cortex. The results show that imagery and perception of complex sounds that do not contain language or music rely on overlapping neural correlates of the secondary but not primary auditory cortex.

Extraction of linear features on SAR imagery

NASA Astrophysics Data System (ADS)

Liu, Junyi; Li, Deren; Mei, Xin

2006-10-01

Linear features are usually extracted from SAR imagery by a few edge detectors derived from the contrast ratio edge detector with a constant probability of false alarm. On the other hand, the Hough Transform is an elegant way of extracting global features like curve segments from binary edge images. Randomized Hough Transform can reduce the computation time and memory usage of the HT drastically. While Randomized Hough Transform will bring about a great deal of cells invalid during the randomized sample. In this paper, we propose a new approach to extract linear features on SAR imagery, which is an almost automatic algorithm based on edge detection and Randomized Hough Transform. The presented improved method makes full use of the directional information of each edge candidate points so as to solve invalid cumulate problems. Applied result is in good agreement with the theoretical study, and the main linear features on SAR imagery have been extracted automatically. The method saves storage space and computational time, which shows its effectiveness and applicability.

Mental representation and motor imagery training

PubMed Central

Schack, Thomas; Essig, Kai; Frank, Cornelia; Koester, Dirk

2014-01-01

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, the structural dimensional analysis of mental representation (SDA-M), 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 (MTMR) 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. PMID:24904368

Detecting Uniform Areas for Vicarious Calibration using Landsat TM Imagery: A Study using the Arabian and Saharan Deserts

NASA Technical Reports Server (NTRS)

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

2002-01-01

This paper discusses a method for detecting spatially uniform sites need for radiometric characterization of remote sensing satellites. Such information is critical for scientific research applications of imagery having moderate to high resolutions (<30-m ground sampling distance (GSD)). Previously published literature indicated that areas with the African Saharan and Arabian deserts contained extremely uniform sites with respect to spatial characteristics. We developed an algorithm for detecting site uniformity and applied it to orthorectified Landsat Thematic Mapper (TM) imagery over eight uniform regions of interest. The algorithm's results were assessed using both medium-resolution (30-m GSD) Landsat 7 ETM+ and fine-resolution (<5-m GSD) IKONOS multispectral data collected over sites in Libya and Mali. Fine-resolution imagery over a Libyan site exhibited less than 1 percent nonuniformity. The research shows that Landsat TM products appear highly useful for detecting potential calibration sites for system characterization. In particular, the approach detected spatially uniform regions that frequently occur at multiple scales of observation.

Use of land surface remotely sensed satellite and airborne data for environmental exposure assessment in cancer research

USGS Publications Warehouse

Maxwell, S.K.; Meliker, J.R.; Goovaerts, P.

2010-01-01

In recent years, geographic information systems (GIS) have increasingly been used for reconstructing individual-level exposures to environmental contaminants in epidemiological research. Remotely sensed data can be useful in creating space-time models of environmental measures. The primary advantage of using remotely sensed data is that it allows for study at the local scale (e.g., residential level) without requiring expensive, time-consuming monitoring campaigns. The purpose of our study was to identify how land surface remotely sensed data are currently being used to study the relationship between cancer and environmental contaminants, focusing primarily on agricultural chemical exposure assessment applications. We present the results of a comprehensive literature review of epidemiological research where remotely sensed imagery or land cover maps derived from remotely sensed imagery were applied. We also discuss the strengths and limitations of the most commonly used imagery data (aerial photographs and Landsat satellite imagery) and land cover maps.

Common spatial pattern combined with kernel linear discriminate and generalized radial basis function for motor imagery-based brain computer interface applications

NASA Astrophysics Data System (ADS)

Hekmatmanesh, Amin; Jamaloo, Fatemeh; Wu, Huapeng; Handroos, Heikki; Kilpeläinen, Asko

2018-04-01

Brain Computer Interface (BCI) can be a challenge for developing of robotic, prosthesis and human-controlled systems. This work focuses on the implementation of a common spatial pattern (CSP) base algorithm to detect event related desynchronization patterns. Utilizing famous previous work in this area, features are extracted by filter bank with common spatial pattern (FBCSP) method, and then weighted by a sensitive learning vector quantization (SLVQ) algorithm. In the current work, application of the radial basis function (RBF) as a mapping kernel of linear discriminant analysis (KLDA) method on the weighted features, allows the transfer of data into a higher dimension for more discriminated data scattering by RBF kernel. Afterwards, support vector machine (SVM) with generalized radial basis function (GRBF) kernel is employed to improve the efficiency and robustness of the classification. Averagely, 89.60% accuracy and 74.19% robustness are achieved. BCI Competition III, Iva data set is used to evaluate the algorithm for detecting right hand and foot imagery movement patterns. Results show that combination of KLDA with SVM-GRBF classifier makes 8.9% and 14.19% improvements in accuracy and robustness, respectively. For all the subjects, it is concluded that mapping the CSP features into a higher dimension by RBF and utilization GRBF as a kernel of SVM, improve the accuracy and reliability of the proposed method.

Classification of motor imagery tasks for BCI with multiresolution analysis and multiobjective feature selection.

PubMed

Ortega, Julio; Asensio-Cubero, Javier; Gan, John Q; Ortiz, Andrés

2016-07-15

Brain-computer interfacing (BCI) applications based on the classification of electroencephalographic (EEG) signals require solving high-dimensional pattern classification problems with such a relatively small number of training patterns that curse of dimensionality problems usually arise. Multiresolution analysis (MRA) has useful properties for signal analysis in both temporal and spectral analysis, and has been broadly used in the BCI field. However, MRA usually increases the dimensionality of the input data. Therefore, some approaches to feature selection or feature dimensionality reduction should be considered for improving the performance of the MRA based BCI. This paper investigates feature selection in the MRA-based frameworks for BCI. Several wrapper approaches to evolutionary multiobjective feature selection are proposed with different structures of classifiers. They are evaluated by comparing with baseline methods using sparse representation of features or without feature selection. The statistical analysis, by applying the Kolmogorov-Smirnoff and Kruskal-Wallis tests to the means of the Kappa values evaluated by using the test patterns in each approach, has demonstrated some advantages of the proposed approaches. In comparison with the baseline MRA approach used in previous studies, the proposed evolutionary multiobjective feature selection approaches provide similar or even better classification performances, with significant reduction in the number of features that need to be computed.

Cloud cover determination in polar regions from satellite imagery

NASA Technical Reports Server (NTRS)

Barry, R. G.; Key, J.

1989-01-01

The objectives are to develop a suitable validation data set for evaluating the effectiveness of the International Satellite Cloud Climatology Project (ISCCP) algorithm for cloud retrieval in polar regions, to identify limitations of current procedures and to explore potential means to remedy them using textural classifiers, and to compare synoptic cloud data from model runs with observations. Toward the first goal, a polar data set consisting of visible, thermal, and passive microwave data was developed. The AVHRR and SMMR data were digitally merged to a polar stereographic projection with an effective pixel size of 5 sq km. With this data set, two unconventional methods of classifying the imagery for the analysis of polar clouds and surfaces were examined: one based on fuzzy sets theory and another based on a trained neural network. An algorithm for cloud detection was developed from an early test version of the ISCCP algorithm. This algorithm includes the identification of surface types with passive microwave, then temporal tests at each pixel location in the cloud detection phase. Cloud maps and clear sky radiance composites for 5 day periods are produced. Algorithm testing and validation was done with both actural AVHRR/SMMR data, and simulated imagery. From this point in the algorithm, groups of cloud pixels are examined for their spectral and textural characteristics, and a procedure is developed for the analysis of cloud patterns utilizing albedo, IR temperature, and texture. In a completion of earlier work, empirical analyses of arctic cloud cover were explored through manual interpretations of DMSP imagery and compared to U.S. Air Force 3D-nephanalysis. Comparisons of observed cloudiness from existing climatologies to patterns computed by the GISS climate model were also made.

Mental Imagery for Musical Changes in Loudness

PubMed Central

Bailes, Freya; Bishop, Laura; Stevens, Catherine J.; Dean, Roger T.

2012-01-01

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 s (nil distractor control), or the presentation of a series of four sine tones, or four visual letters or three 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. PMID:23227014

A Cross-Modal Perspective on the Relationships between Imagery and Working Memory

PubMed Central

Likova, Lora T.

2013-01-01

Mapping the distinctions and interrelationships between imagery and working memory (WM) remains challenging. Although each of these major cognitive constructs is defined and treated in various ways across studies, most accept that both imagery and WM involve a form of internal representation available to our awareness. In WM, there is a further emphasis on goal-oriented, active maintenance, and use of this conscious representation to guide voluntary action. Multicomponent WM models incorporate representational buffers, such as the visuo-spatial sketchpad, plus central executive functions. If there is a visuo-spatial “sketchpad” for WM, does imagery involve the same representational buffer? Alternatively, does WM employ an imagery-specific representational mechanism to occupy our awareness? Or do both constructs utilize a more generic “projection screen” of an amodal nature? To address these issues, in a cross-modal fMRI study, I introduce a novel Drawing-Based Memory Paradigm, and conceptualize drawing as a complex behavior that is readily adaptable from the visual to non-visual modalities (such as the tactile modality), which opens intriguing possibilities for investigating cross-modal learning and plasticity. Blindfolded participants were trained through our Cognitive-Kinesthetic Method (Likova, 2010a, 2012) to draw complex objects guided purely by the memory of felt tactile images. If this WM 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 downward 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. The sole visual hierarchy activation was isolated to the primary visual area (V1), and accompanied by deactivation of the entire extrastriate cortex, thus ’cutting-off’ any signal propagation from/to V1 through the visual hierarchy. The implications of these findings for the debate on the interrelationships between the core cognitive constructs of WM and imagery and the nature of internal representations are evaluated. PMID:23346061

Wavelet Analysis for RADARSAT Exploitation: Demonstration of Algorithms for Maritime Surveillance

DTIC Science & Technology

2007-02-01

this study , we demonstrate wavelet analysis for exploitation of RADARSAT ocean imagery, including wind direction estimation, oceanic and atmospheric ...of image striations that can arise as a texture pattern caused by turbulent coherent structures in the marine atmospheric boundary layer. The image...associated change in the pattern texture (i.e., the nature of the turbulent atmospheric structures) across the front. Due to the large spatial scale of

Burnout: An Occupational Hazard.

ERIC Educational Resources Information Center

Hamann, Donald L.; Gordon, Debra G.

2000-01-01

Describes a five-step pattern of burnout and discusses various stress factors that can contribute to burnout. Explores solutions to burnout, such as keeping a balance in life, exercising, and relaxation. Includes sections on balanced breathing, imagery relaxation, and resources for stress reduction. (CMK)

Diurnal ocean surface layer model validation

NASA Technical Reports Server (NTRS)

Hawkins, Jeffrey D.; May, Douglas A.; Abell, Fred, Jr.

1990-01-01

The diurnal ocean surface layer (DOSL) model at the Fleet Numerical Oceanography Center forecasts the 24-hour change in a global sea surface temperatures (SST). Validating the DOSL model is a difficult task due to the huge areas involved and the lack of in situ measurements. Therefore, this report details the use of satellite infrared multichannel SST imagery to provide day and night SSTs that can be directly compared to DOSL products. This water-vapor-corrected imagery has the advantages of high thermal sensitivity (0.12 C), large synoptic coverage (nearly 3000 km across), and high spatial resolution that enables diurnal heating events to be readily located and mapped. Several case studies in the subtropical North Atlantic readily show that DOSL results during extreme heating periods agree very well with satellite-imagery-derived values in terms of the pattern of diurnal warming. The low wind and cloud-free conditions necessary for these events to occur lend themselves well to observation via infrared imagery. Thus, the normally cloud-limited aspects of satellite imagery do not come into play for these particular environmental conditions. The fact that the DOSL model does well in extreme events is beneficial from the standpoint that these cases can be associated with the destruction of the surface acoustic duct. This so-called afternoon effect happens as the afternoon warming of the mixed layer disrupts the sound channel and the propagation of acoustic energy.

Investigating the effects of visual distractors on the performance of a motor imagery brain-computer interface.

PubMed

Emami, Zahra; Chau, Tom

2018-06-01

Brain-computer interfaces (BCIs) allow users to operate a device or application by means of cognitive activity. This technology will ultimately be used in real-world environments which include the presence of distractors. The purpose of the study was to determine the effect of visual distractors on BCI performance. Sixteen able-bodied participants underwent neurofeedback training to achieve motor imagery-guided BCI control in an online paradigm using electroencephalography (EEG) to measure neural signals. Participants then completed two sessions of the motor imagery EEG-BCI protocol in the presence of infrequent, small visual distractors. BCI performance was determined based on classification accuracy. The presence of distractors was found to affect motor imagery-specific patterns in mu and beta power. However, the distractors did not significantly affect the BCI classification accuracy; across participants, the mean classification accuracy was 81.5 ± 14% for non-distractor trials, and 78.3 ± 17% for distractor trials. This minimal consequence suggests that the BCI was robust to distractor effects, despite motor imagery-related brain activity being attenuated amid distractors. A BCI system that mitigates distraction-related effects may improve the ease of its use and ultimately facilitate the effective translation of the technology from the lab to the home. Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Predictive models to determine imagery strategies employed by children to judge hand laterality.

PubMed

Spruijt, Steffie; Jongsma, Marijtje L A; van der Kamp, John; Steenbergen, Bert

2015-01-01

A commonly used paradigm to study motor imagery is the hand laterality judgment task. The present study aimed to determine which strategies young children employ to successfully perform this task. Children of 5 to 8 years old (N = 92) judged laterality of back and palm view hand pictures in different rotation angles. Response accuracy and response duration were registered. Response durations of the trials with a correct judgment were fitted to a-priori defined predictive sinusoid models, representing different strategies to successfully perform the hand laterality judgment task. The first model predicted systematic changes in response duration as a function of rotation angle of the displayed hand. The second model predicted that response durations are affected by biomechanical constraints of hand rotation. If observed data could be best described by the first model, this would argue for a mental imagery strategy that does not involve motor processes to solve the task. The second model reflects a motor imagery strategy to solve the task. In line with previous research, we showed an age-related increase in response accuracy and decrease in response duration in children. Observed data for both back and palm view showed that motor imagery strategies were used to perform hand laterality judgments, but that not all the children use these strategies (appropriately) at all times. A direct comparison of response duration patterns across age sheds new light on age-related differences in the strategies employed to solve the task. Importantly, the employment of the motor imagery strategy for successful task performance did not change with age.

HYPGEO - A collaboration between geophysics and remote sensing for mineral exploration

NASA Astrophysics Data System (ADS)

Meyer, Uwe; Frei, Michaela; Petersen, Hauke; Papenfuß, Anne; Ibs-von Seht, Malte; Stolz, Ronny; Queitsch, Matthias; Buchholz, Peter; Siemon, Bernhard

2017-04-01

The German Federal Institute for Geosciences and Natural Resources (BGR) aims to promote and design application oriented, generic techniques for the detection and 3D-characterisation of mineral deposits. Most newly developed mineral mining structures are still exploiting near surface sources. Since exploration and exploitation of mineral resources are increasingly under public review concerning environmental issues and social acceptance, non-invasive methods using satellites, fixed-wing aircraft, helicopters or unmanned aerial vehicles are preferred techniques within this investigation. Therefore, a data combination of helicopter-borne gamma ray spectrometry, hyperspectral imagery and full tensor gradient magnetometry is being evaluated. Test areas are open pit mining structures in Aznalcollar and Tharsis within the Pyrite Belt of southern Spain. First test flights using gamma-ray spectrometry and gradient magnetometry using SQUID-based sensors have been performed. Hyperspectral imagery has been applied on ground. Rock and core samples from the mines have been taken or investigated for further analysis. The basic idea is to combine surface triggered signals from gamma-ray spectrometry and hyperspectral imagery to enhance the detection of shallow mineralisation structures. In order to investigate whether these structures are connected with near-surface ore veins, gradient magnetometry was applied to model subsurface formations. To verify that good correlations between the applied methods are given, open pit mining structures were chosen, where the mineral content and the local to regional geology is well known.

Assessing Greater Sage-Grouse Selection of Brood-Rearing Habitat Using Remotely-Sensed Imagery: Can Readily Available High-Resolution Imagery Be Used to Identify Brood-Rearing Habitat Across a Broad Landscape?

PubMed

Westover, Matthew; Baxter, Jared; Baxter, Rick; Day, Casey; Jensen, Ryan; Petersen, Steve; Larsen, Randy

2016-01-01

Greater sage-grouse populations have decreased steadily since European settlement in western North America. Reduced availability of brood-rearing habitat has been identified as a limiting factor for many populations. We used radio-telemetry to acquire locations of sage-grouse broods from 1998 to 2012 in Strawberry Valley, Utah. Using these locations and remotely-sensed NAIP (National Agricultural Imagery Program) imagery, we 1) determined which characteristics of brood-rearing habitat could be used in widely available, high resolution imagery 2) assessed the spatial extent at which sage-grouse selected brood-rearing habitat, and 3) created a predictive habitat model to identify areas of preferred brood-rearing habitat. We used AIC model selection to evaluate support for a list of variables derived from remotely-sensed imagery. We examined the relationship of these explanatory variables at three spatial extents (45, 200, and 795 meter radii). Our top model included 10 variables (percent shrub, percent grass, percent tree, percent paved road, percent riparian, meters of sage/tree edge, meters of riparian/tree edge, distance to tree, distance to transmission lines, and distance to permanent structures). Variables from each spatial extent were represented in our top model with the majority being associated with the larger (795 meter) spatial extent. When applied to our study area, our top model predicted 75% of naïve brood locations suggesting reasonable success using this method and widely available NAIP imagery. We encourage application of our methodology to other sage-grouse populations and species of conservation concern.

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

NASA Technical Reports Server (NTRS)

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.

The usefulness of Skylab/EREP S-190 and S-192 imagery in multistage forest surveys

NASA Technical Reports Server (NTRS)

Langley, P. G.; Vanroessel, J. (Principal Investigator)

1976-01-01

The author has identified the following significant results. The RMSE of point location achieved with the annotation system on S190A imagery was 100 m and 90 m in the x and y direction, respectively. Potential gains in sampling precision attributable to space derived imagery ranged from 4.9 to 43.3 percent depending on the image type, interpretation method, time of year, and sampling method applied. Seasonal variation was significant. S190A products obtained in September yielded higher gains than those obtained in June. Using 100 primary sample units as a base under simple random sampling, the revenue made available for incorporating space acquired data into the sample design to estimate timber volume was as high as $39,400.00.

A fingertip force prediction model for grasp patterns characterised from the chaotic behaviour of EEG.

PubMed

Roy, Rinku; Sikdar, Debdeep; Mahadevappa, Manjunatha; Kumar, C S

2018-05-19

A stable grasp is attained through appropriate hand preshaping and precise fingertip forces. Here, we have proposed a method to decode grasp patterns from motor imagery and subsequent fingertip force estimation model with a slippage avoidance strategy. We have developed a feature-based classification of electroencephalography (EEG) associated with imagination of the grasping postures. Chaotic behaviour of EEG for different grasping patterns has been utilised to capture the dynamics of associated motor activities. We have computed correlation dimension (CD) as the feature and classified with "one against one" multiclass support vector machine (SVM) to discriminate between different grasping patterns. The result of the analysis showed varying classification accuracies at different subband levels. Broad categories of grasping patterns, namely, power grasp and precision grasp, were classified at a 96.0% accuracy rate in the alpha subband. Furthermore, power grasp subtypes were classified with an accuracy of 97.2% in the upper beta subband, whereas precision grasp subtypes showed relatively lower 75.0% accuracy in the alpha subband. Following assessment of fingertip force distributions while grasping, a nonlinear autoregressive (NAR) model with proper prediction of fingertip forces was proposed for each grasp pattern. A slippage detection strategy has been incorporated with automatic recalibration of the regripping force. Intention of each grasp pattern associated with corresponding fingertip force model was virtualised in this work. This integrated system can be utilised as the control strategy for prosthetic hand in the future. The model to virtualise motor imagery based fingertip force prediction with inherent slippage correction for different grasp types ᅟ.

Anomaly detection in hyperspectral imagery: statistics vs. graph-based algorithms

NASA Astrophysics Data System (ADS)

Berkson, Emily E.; Messinger, David W.

2016-05-01

Anomaly detection (AD) algorithms are frequently applied to hyperspectral imagery, but different algorithms produce different outlier results depending on the image scene content and the assumed background model. This work provides the first comparison of anomaly score distributions between common statistics-based anomaly detection algorithms (RX and subspace-RX) and the graph-based Topological Anomaly Detector (TAD). Anomaly scores in statistical AD algorithms should theoretically approximate a chi-squared distribution; however, this is rarely the case with real hyperspectral imagery. The expected distribution of scores found with graph-based methods remains unclear. We also look for general trends in algorithm performance with varied scene content. Three separate scenes were extracted from the hyperspectral MegaScene image taken over downtown Rochester, NY with the VIS-NIR-SWIR ProSpecTIR instrument. In order of most to least cluttered, we study an urban, suburban, and rural scene. The three AD algorithms were applied to each scene, and the distributions of the most anomalous 5% of pixels were compared. We find that subspace-RX performs better than RX, because the data becomes more normal when the highest variance principal components are removed. We also see that compared to statistical detectors, anomalies detected by TAD are easier to separate from the background. Due to their different underlying assumptions, the statistical and graph-based algorithms highlighted different anomalies within the urban scene. These results will lead to a deeper understanding of these algorithms and their applicability across different types of imagery.

Global Near Real-Time MODIS and Landsat Flood Mapping and Product Delivery

NASA Astrophysics Data System (ADS)

Policelli, F. S.; Slayback, D. A.; Tokay, M. M.; Brakenridge, G. R.

2014-12-01

Flooding is the most destructive, frequent, and costly natural disaster faced by modern society, and is increasing in frequency and damage (deaths, displacements, and financial costs) as populations increase and climate change generates more extreme weather events. When major flooding events occur, the disaster management community needs frequently updated and easily accessible information to better understand the extent of flooding and coordinate response efforts. With funding from NASA's Applied Sciences program, we developed and are now operating a near real-time global flood mapping system to help provide flood extent information within 24-48 hours of events. The principal element of the system applies a water detection algorithm to MODIS imagery, which is processed by the LANCE (Land Atmosphere Near real-time Capability for EOS) system at NASA Goddard within a few hours of satellite overpass. Using imagery from both the Terra (10:30 AM local time overpass) and Aqua (1:30 PM) platforms allows the system to deliver an initial daily assessment of flood extent by late afternoon, and more robust assessments after accumulating cloud-free imagery over several days. Cloud cover is the primary limitation in detecting surface water from MODIS imagery. Other issues include the relatively coarse scale of the MODIS imagery (250 meters) for some events, the difficulty of detecting flood waters in areas with continuous canopy cover, confusion of shadow (cloud or terrain) with water, and accurately identifying detected water as flood as opposed to normal water extent. We are working on improvements to address these limitations. We have also begun delivery of near real time water maps at 30 m resolution from Landsat imagery. Although Landsat is not available daily globally, but only every 8 days if imagery from both operating platforms (Landsat 7 and 8) is accessed, it can provide useful higher resolution data on water extent when a clear acquisition coincides with an active flood event. These data products are provided in various formats on our website, and also via live OGC (Open Geospatial Consortium) services, and ArcGIS Online accessible web maps, allowing easy access from a variety of platforms, from desktop GIS software to web browsers on mobile phones. https://oas.gsfc.nasa.gov/floodmap

Stream network analysis from orbital and suborbital imagery, Colorado River Basin, Texas

NASA Technical Reports Server (NTRS)

Baker, V. R. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Orbital SL-2 imagery (earth terrain camera S-190B), received September 5, 1973, was subjected to quantitative network analysis and compared to 7.5 minute topographic mapping (scale: 1/24,000) and U.S.D.A. conventional black and white aerial photography (scale: 1/22,200). Results can only be considered suggestive because detail on the SL-2 imagery was badly obscured by heavy cloud cover. The upper Bee Creek basin was chosen for analysis because it appeared in a relatively cloud-free portion of the orbital imagery. Drainage maps were drawn from the three sources digitized into a computer-compatible format, and analyzed by the WATER system computer program. Even at its small scale (1/172,000) and with bad haze the orbital photo showed much drainage detail. The contour-like character of the Glen Rose Formation's resistant limestone units allowed channel definition. The errors in pattern recognition can be attributed to local areas of dense vegetation and to other areas of very high albedo caused by surficial exposure of caliche. The latter effect caused particular difficulty in the determination of drainage divides.

Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation.

PubMed

Jin, Wei; Gong, Fei; Zeng, Xingbin; Fu, Randi

2016-12-16

Automatic cloud detection and classification using satellite cloud imagery have various meteorological applications such as weather forecasting and climate monitoring. Cloud pattern analysis is one of the research hotspots recently. Since satellites sense the clouds remotely from space, and different cloud types often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite cloud imagery. Satellite observation is susceptible to noises, while traditional cloud classification methods are sensitive to noises and outliers; it is hard for traditional cloud classification methods to achieve reliable results. To deal with these problems, a satellite cloud classification method using adaptive fuzzy sparse representation-based classification (AFSRC) is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite cloud imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC), atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for cloud classification is proposed. Experiment results on FY-2G satellite cloud image show that, the proposed method not only improves the accuracy of cloud classification, but also has strong stability and adaptability with high computational efficiency.

Spatial-temporal event detection in climate parameter imagery.

DOE Office of Scientific and Technical Information (OSTI.GOV)

McKenna, Sean Andrew; Gutierrez, Karen A.

Previously developed techniques that comprise statistical parametric mapping, with applications focused on human brain imaging, are examined and tested here for new applications in anomaly detection within remotely-sensed imagery. Two approaches to analysis are developed: online, regression-based anomaly detection and conditional differences. These approaches are applied to two example spatial-temporal data sets: data simulated with a Gaussian field deformation approach and weekly NDVI images derived from global satellite coverage. Results indicate that anomalies can be identified in spatial temporal data with the regression-based approach. Additionally, la Nina and el Nino climatic conditions are used as different stimuli applied to themore » earth and this comparison shows that el Nino conditions lead to significant decreases in NDVI in both the Amazon Basin and in Southern India.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ellis, J.E.; Swift, D.M.; Hart, T.C.

Landsat multi-spectral scanner (MSS) imagery was used to develop a vegetation type-biomass map of the 84,000 Km/sup 2/ Turkana District, Kenya. NOAA satellite advanced very high resolution radiometry (AVHRR) imagery was overlaid on the MSS map to trace the seasonal and annual dynamics of vegetation communities used by Turkana pastoral nomads, 1981-1984. Four regions (sub-sectional territories) were compared with respect to peak herbaceous biomass, woody canopy cover, and seasonal fluxes in total green biomass. Results demonstrated major variations among regions and between wet and dry season ranges within regions. Pastoral land use patterns appear to minimize effects of seasonal vegetationmore » fluxes on livestock herds.« less

Use of remote sensing for land use policy formulation

NASA Technical Reports Server (NTRS)

1982-01-01

Research projects described include: (1) identifying coniferous forest types in Michigan using LANDSAT imagery; (2) investigating synoptic temperature patterns in Michigan as determined via GOES and HCMM thermal imagery; (3) land surface change detection using satellite data and a geographic data base; (4) determining soil map unit composition by electronic scanning densitometry; and (5) delimiting areas of virus infection in vineyards and blueberry fields in southwestern and western Michigan. Contractual activities involve important farmlands inventory, changes in aquatic vegetation in Saginaw Bay, digitized soil association map of Michigan, and aerial photography for hybrid-poplar research. On-going projects are also being conducted in Jamaica, Honduras, the Dominican Republic and Kenya.

Probabilistic cluster labeling of imagery data

NASA Technical Reports Server (NTRS)

Chittineni, C. B. (Principal Investigator)

1980-01-01

The problem of obtaining the probabilities of class labels for the clusters using spectral and spatial information from a given set of labeled patterns and their neighbors is considered. A relationship is developed between class and clusters conditional densities in terms of probabilities of class labels for the clusters. Expressions are presented for updating the a posteriori probabilities of the classes of a pixel using information from its local neighborhood. Fixed-point iteration schemes are developed for obtaining the optimal probabilities of class labels for the clusters. These schemes utilize spatial information and also the probabilities of label imperfections. Experimental results from the processing of remotely sensed multispectral scanner imagery data are presented.

A study of morphology, provenance, and movement of desert sand seas in Africa, Asia, and Australia

NASA Technical Reports Server (NTRS)

Mckee, E. D.; Breed, C. S.

1973-01-01

A description and classification of major types of sand seas on the basis of morphological pattern and lineation are discussed. The steps involved in analyzing the patterns of deposits on ERTS-1 imagery, where the visible forms are mostly dune complexes rather than individual dunes are outlined. After completion of thematic maps portraying the pattern and lineation of the sand bodies, data on directions and intensity of prevailing and other winds are plotted on corresponding bases, as a preliminary to determination of internal structures through ground truth.

Accuracy assessment of high resolution satellite imagery orientation by leave-one-out method

NASA Astrophysics Data System (ADS)

Brovelli, Maria Antonia; Crespi, Mattia; Fratarcangeli, Francesca; Giannone, Francesca; Realini, Eugenio

Interest in high-resolution satellite imagery (HRSI) is spreading in several application fields, at both scientific and commercial levels. Fundamental and critical goals for the geometric use of this kind of imagery are their orientation and orthorectification, processes able to georeference the imagery and correct the geometric deformations they undergo during acquisition. In order to exploit the actual potentialities of orthorectified imagery in Geomatics applications, the definition of a methodology to assess the spatial accuracy achievable from oriented imagery is a crucial topic. In this paper we want to propose a new method for accuracy assessment based on the Leave-One-Out Cross-Validation (LOOCV), a model validation method already applied in different fields such as machine learning, bioinformatics and generally in any other field requiring an evaluation of the performance of a learning algorithm (e.g. in geostatistics), but never applied to HRSI orientation accuracy assessment. The proposed method exhibits interesting features which are able to overcome the most remarkable drawbacks involved by the commonly used method (Hold-Out Validation — HOV), based on the partitioning of the known ground points in two sets: the first is used in the orientation-orthorectification model (GCPs — Ground Control Points) and the second is used to validate the model itself (CPs — Check Points). In fact the HOV is generally not reliable and it is not applicable when a low number of ground points is available. To test the proposed method we implemented a new routine that performs the LOOCV in the software SISAR, developed by the Geodesy and Geomatics Team at the Sapienza University of Rome to perform the rigorous orientation of HRSI; this routine was tested on some EROS-A and QuickBird images. Moreover, these images were also oriented using the world recognized commercial software OrthoEngine v. 10 (included in the Geomatica suite by PCI), manually performing the LOOCV since only the HOV is implemented. The software comparison guaranteed about the overall correctness and good performances of the SISAR model, whereas the results showed the good features of the LOOCV method.

Himalayan glaciers: understanding contrasting patterns of glacier behavior using multi-temporal satellite imagery

NASA Astrophysics Data System (ADS)

Racoviteanu, A.

2014-12-01

High rates of glacier retreat for the last decades are often reported, and believed to be induced by 20th century climate changes. However, regional glacier fluctuations are complex, and depend on a combination of climate and local topography. Furthermore, in ares such as the Hindu-Kush Himalaya, there are concerns about warming, decreasing monsoon precipitation and their impact on local glacier regimes. Currently, the challenge is in understanding the magnitude of feedbacks between large-scale climate forcing and small-scale glacier behavior. Spatio-temporal patterns of glacier distribution are still llimited in some areas of the high Hindu-Kush Himalaya, but multi-temporal satellite imagery has helped fill spatial and temporal gaps in regional glacier parameters in the last decade. Here I present a synopsis of the behavior of glaciers across the Himalaya, following a west to east gradient. In particular, I focus on spatial patterns of glacier parameters in the eastern Himalaya, which I investigate at multi-spatial scales using remote sensing data from declassified Corona, ASTER, Landsat ETM+, Quickbird and Worldview2 sensors. I also present the use of high-resolution imagery, including texture and thermal analysis for mapping glacier features at small scale, which are particularly useful in understanding surface trends of debris-covered glaciers, which are prevalent in the Himalaya. I compare and contrast spatial patterns of glacier area and élévation changes in the monsoon-influenced eastern Himalaya (the Everest region in the Nepal Himalaya and Sikkim in the Indian Himalaya) with other observations from the dry western Indian Himalaya (Ladakh and Lahul-Spiti), both field measurements and remote sensing-based. In the eastern Himalaya, results point to glacier area change of -0.24 % ± 0.08% per year from the 1960's to the 2006's, with a higher rate of retreat in the last decade (-0.43% /yr). Debris-covered glacier tongues show thinning trends of -30.8 m± 39 m on average over the last four decades, similar to other studies in the same climatic area. However, at small scales, the behavior of glaciers is highly heterogenous, with contrasting patterns of thickening glacier termini versus retreating nad thinning glacier tongues.

The Use of Satellite Observed Cloud Patterns in Northern Hemisphere 300 mb and 1000/300 mb Numerical Analysis.

DTIC Science & Technology

1984-02-01

prediction Extratropical cyclones Objective analysis Bogus techniques 20. ABSTRACT (Continue on reverse aide If necooearn mid Identify by block number) Jh A...quasi-objective statistical method for deriving 300 mb geopotential heights and 1000/300 mb thicknesses in the vicinity of extratropical cyclones 0I...with the aid of satellite imagery is presented. The technique utilizes satellite observed extratropical spiral cloud pattern parameters in conjunction

A study to explore the use of orbital remote sensing to determine native arid plant distribution. [Arizona

NASA Technical Reports Server (NTRS)

Mcginnies, W. G. (Principal Investigator); Conn, J. S.; Haase, E. F.; Lepley, L. K.; Musick, H. B.; Foster, K. E.

1975-01-01

The author has identified the following significant results. Research results include a method for determining the reflectivities of natural areas from ERTS data taking into account sun angle and atmospheric effects on the radiance seen by the satellite sensor. Ground truth spectral signature data for various types of scenes, including ground with and without annuals, and various shrubs were collected. Large areas of varnished desert pavement are visible and mappable on ERTS and high altitude aircraft imagery. A large scale and a small scale vegetation pattern were found to be correlated with presence of desert pavement. A comparison of radiometric data with video recordings shows quantitatively that for most areas of desert vegetation, soils are the most influential factor in determining the signature of a scene. Additive and subtractive image processing techniques were applied in the dark room to enhance vegetational aspects of ERTS.

Single-image-based solution for optics temperature-dependent nonuniformity correction in an uncooled long-wave infrared camera.

PubMed

Cao, Yanpeng; Tisse, Christel-Loic

2014-02-01

In this Letter, we propose an efficient and accurate solution to remove temperature-dependent nonuniformity effects introduced by the imaging optics. This single-image-based approach computes optics-related fixed pattern noise (FPN) by fitting the derivatives of correction model to the gradient components, locally computed on an infrared image. A modified bilateral filtering algorithm is applied to local pixel output variations, so that the refined gradients are most likely caused by the nonuniformity associated with optics. The estimated bias field is subtracted from the raw infrared imagery to compensate the intensity variations caused by optics. The proposed method is fundamentally different from the existing nonuniformity correction (NUC) techniques developed for focal plane arrays (FPAs) and provides an essential image processing functionality to achieve completely shutterless NUC for uncooled long-wave infrared (LWIR) imaging systems.

Polarized skylight navigation.

PubMed

Hamaoui, Moshe

2017-01-20

Vehicle state estimation is an essential prerequisite for navigation. The present approach seeks to use skylight polarization to facilitate state estimation under autonomous unconstrained flight conditions. Atmospheric scattering polarizes incident sunlight such that solar position is mathematically encoded in the resulting skylight polarization pattern. Indeed, several species of insects are able to sense skylight polarization and are believed to navigate polarimetrically. Sun-finding methodologies for polarized skylight navigation (PSN) have been proposed in the literature but typically rely on calibration updates to account for changing atmospheric conditions and/or are limited to 2D operation. To address this technology gap, a gradient-based PSN solution is developed based upon the Rayleigh sky model. The solution is validated in simulation, and effects of measurement error and changing atmospheric conditions are investigated. Finally, an experimental effort is described wherein polarimetric imagery is collected, ground-truth is established through independent imager-attitude measurement, the gradient-based PSN solution is applied, and results are analyzed.

Determination of awareness in patients with severe brain injury using EEG power spectral analysis

PubMed Central

Goldfine, Andrew M.; Victor, Jonathan D.; Conte, Mary M.; Bardin, Jonathan C.; Schiff, Nicholas D.

2011-01-01

Objective To determine whether EEG spectral analysis could be used to demonstrate awareness in patients with severe brain injury. Methods We recorded EEG from healthy controls and three patients with severe brain injury, ranging from minimally conscious state (MCS) to locked-in-state (LIS), while they were asked to imagine motor and spatial navigation tasks. We assessed EEG spectral differences from 4 to 24 Hz with univariate comparisons (individual frequencies) and multivariate comparisons (patterns across the frequency range). Results In controls, EEG spectral power differed at multiple frequency bands and channels during performance of both tasks compared to a resting baseline. As patterns of signal change were inconsistent between controls, we defined a positive response in patient subjects as consistent spectral changes across task performances. One patient in MCS and one in LIS showed evidence of motor imagery task performance, though with patterns of spectral change different from the controls. Conclusion EEG power spectral analysis demonstrates evidence for performance of mental imagery tasks in healthy controls and patients with severe brain injury. Significance EEG power spectral analysis can be used as a flexible bedside tool to demonstrate awareness in brain-injured patients who are otherwise unable to communicate. PMID:21514214

Neuromuscular electrical stimulation induced brain patterns to decode motor imagery.

PubMed

Vidaurre, C; Pascual, J; Ramos-Murguialday, A; Lorenz, R; Blankertz, B; Birbaumer, N; Müller, K-R

2013-09-01

Regardless of the paradigm used to implement a brain-computer interface (BCI), all systems suffer from BCI-inefficiency. In the case of patients the inefficiency can be high. Some solutions have been proposed to overcome this problem, however they have not been completely successful yet. EEG from 10 healthy users was recorded during neuromuscular electrical stimulation (NMES) of hands and feet and during motor imagery (MI) of the same limbs. Features and classifiers were computed using part of these data to decode MI. Offline analyses showed that it was possible to decode MI using a classifier based on afferent patterns induced by NMES and even infer a better model than with MI data. Afferent NMES motor patterns can support the calibration of BCI systems and be used to decode MI. This finding might be a new way to train sensorimotor rhythm (SMR) based BCI systems for healthy users having difficulties to attain BCI control. It might also be an alternative to train MI-based BCIs for users who cannot perform real movements but have remaining afferents (ALS, stroke patients). Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

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

PubMed Central

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

Applying High Resolution Imagery to Understand the Role of Dynamics in the Diminishing Arctic Sea Ice Cover

DTIC Science & Technology

2015-09-30

observations collected by the NASA Operation IceBridge (OIB) project, including high-resolution visible-band imagery (Onana et al., 2013), snow depth ( Newman et...2014; Farrell et al., 2015; Hutchings et al., 2015; Richter-Menge and Farrell, 2014), snow depth ( Newman et al., 2014; Webster et al., 2014), sea ice...with A. Mahoney , H. Eicken and C. Haas on an ONR-funded project "Mass balance of multi-year sea ice in the southern Beaufort Sea". This effort

Application of ERTS-1 imagery to the study of caribou movements and winter dispersal in relation to prevailing snowcover

NASA Technical Reports Server (NTRS)

Lent, P. C. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Step-wise discriminate analysis has demonstrated the feasibility of feature identification using linear discriminate functions of ERTS-1 MSS band densities and their ratios. The analysis indicated that features such as small streams can be detected even when they are in dark mountain shadow. The potential utility of this and similar analytic techniques appears considerable, and the limits it can be applied to analysis of ERTS-1 imagery are not yet fully known.

Motor Imagery Experiences and Use: Asking Patients after Stroke Where, When, What, Why, and How They Use Imagery: A Qualitative Investigation

PubMed Central

Schuster, Corina; Glässel, Andrea; Scheidhauer, Anne; Ettlin, Thierry; Butler, Jenny

2012-01-01

Background. A framework on where, when, what, why, and how to use imagery from sports psychology was explored whether it can be applied in patients after stroke in their chronic stage. Methods. Eleven patients (ages 31–85, 3 females, 1.3–6.4 years after stroke) were interviewed. Semistructured interviews were conducted before and after a two-week MI intervention period with six MI sessions. Information was obtained regarding experiences and knowledge of MI, and the evaluation of an MI practical example. The coding scheme was based on the framework and a hierarchical categorisation. Results. Information regarding domains where, when, what, why, and how to use imagery was addressed. Patients imagined themselves as healthy individuals, did not focus on surroundings during MI practice,and reported to use positive imagery only. After MI training, patients became more flexible regarding their location and position during MI practice. Conclusions. MI became an automatic process, and patients did not need specific concentration and quietness as mentioned in the first interview. Patients recommended daily MI training and began to transfer MI to practice movements that were affected by the stroke. In contrast to sports, patients did not talk about how MI was triggered rather than how MI was designed. PMID:22593834

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

NASA Astrophysics Data System (ADS)

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

2010-05-01

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

Phenology-based Spartina alterniflora mapping in coastal wetland of the Yangtze Estuary using time series of GaoFen satellite no. 1 wide field of view imagery

NASA Astrophysics Data System (ADS)

Ai, Jinquan; Gao, Wei; Gao, Zhiqiang; Shi, Runhe; Zhang, Chao

2017-04-01

Spartina alterniflora is an aggressive invasive plant species that replaces native species, changes the structure and function of the ecosystem across coastal wetlands in China, and is thus a major conservation concern. Mapping the spread of its invasion is a necessary first step for the implementation of effective ecological management strategies. The performance of a phenology-based approach for S. alterniflora mapping is explored in the coastal wetland of the Yangtze Estuary using a time series of GaoFen satellite no. 1 wide field of view camera (GF-1 WFV) imagery. First, a time series of the normalized difference vegetation index (NDVI) was constructed to evaluate the phenology of S. alterniflora. Two phenological stages (the senescence stage from November to mid-December and the green-up stage from late April to May) were determined as important for S. alterniflora detection in the study area based on NDVI temporal profiles, spectral reflectance curves of S. alterniflora and its coexistent species, and field surveys. Three phenology feature sets representing three major phenology-based detection strategies were then compared to map S. alterniflora: (1) the single-date imagery acquired within the optimal phenological window, (2) the multitemporal imagery, including four images from the two important phenological windows, and (3) the monthly NDVI time series imagery. Support vector machines and maximum likelihood classifiers were applied on each phenology feature set at different training sample sizes. For all phenology feature sets, the overall results were produced consistently with high mapping accuracies under sufficient training samples sizes, although significantly improved classification accuracies (10%) were obtained when the monthly NDVI time series imagery was employed. The optimal single-date imagery had the lowest accuracies of all detection strategies. The multitemporal analysis demonstrated little reduction in the overall accuracy compared with the use of monthly NDVI time series imagery. These results show the importance of considering the phenological stage for image selection for mapping S. alterniflora using GF-1 WFV imagery. Furthermore, in light of the better tradeoff between the number of images and classification accuracy when using multitemporal GF-1 WFV imagery, we suggest using multitemporal imagery acquired at appropriate phenological windows for S. alterniflora mapping at regional scales.

Professional Orchestral Conductors' Use of Selected Teaching Behaviors in Rehearsal

ERIC Educational Resources Information Center

Whitaker, Jennifer A.

2017-01-01

This descriptive study examined professional conductors' use of rehearsal time in sequential pattern components, discussing task presentation targets, and using verbal imagery and modeling techniques. Commercially available videos of 15 professional conductors rehearsing prominent orchestras were scripted, coded, and timed for selected teaching…

Multi-channel linear descriptors for event-related EEG collected in brain computer interface.

PubMed

Pei, Xiao-mei; Zheng, Chong-xun; Xu, Jin; Bin, Guang-yu; Wang, Hong-wu

2006-03-01

By three multi-channel linear descriptors, i.e. spatial complexity (omega), field power (sigma) and frequency of field changes (phi), event-related EEG data within 8-30 Hz were investigated during imagination of left or right hand movement. Studies on the event-related EEG data indicate that a two-channel version of omega, sigma and phi could reflect the antagonistic ERD/ERS patterns over contralateral and ipsilateral areas and also characterize different phases of the changing brain states in the event-related paradigm. Based on the selective two-channel linear descriptors, the left and right hand motor imagery tasks are classified to obtain satisfactory results, which testify the validity of the three linear descriptors omega, sigma and phi for characterizing event-related EEG. The preliminary results show that omega, sigma together with phi have good separability for left and right hand motor imagery tasks, which could be considered for classification of two classes of EEG patterns in the application of brain computer interfaces.

Change detection and classification of land cover in multispectral satellite imagery using clustering of sparse approximations (CoSA) over learned feature dictionaries

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.

Neuromimetic machine vision and pattern recognition algorithms are of great interest for landscape characterization and change detection in satellite imagery in support of global climate change science and modeling. We present results from an ongoing effort to extend machine vision methods to the environmental sciences, using adaptive sparse signal processing combined with machine learning. A Hebbian learning rule is used to build multispectral, multiresolution dictionaries from regional satellite normalized band difference index data. Land cover labels are automatically generated via our CoSA algorithm: Clustering of Sparse Approximations, using a clustering distance metric that combines spectral and spatial textural characteristics tomore » help separate geologic, vegetative, and hydrologie features. We demonstrate our method on example Worldview-2 satellite images of an Arctic region, and use CoSA labels to detect seasonal surface changes. In conclusion, our results suggest that neuroscience-based models are a promising approach to practical pattern recognition and change detection problems in remote sensing.« less

Change detection and classification of land cover in multispectral satellite imagery using clustering of sparse approximations (CoSA) over learned feature dictionaries

DOE PAGES

Moody, Daniela I.; Brumby, Steven P.; Rowland, Joel C.; ...

2014-10-01

Neuromimetic machine vision and pattern recognition algorithms are of great interest for landscape characterization and change detection in satellite imagery in support of global climate change science and modeling. We present results from an ongoing effort to extend machine vision methods to the environmental sciences, using adaptive sparse signal processing combined with machine learning. A Hebbian learning rule is used to build multispectral, multiresolution dictionaries from regional satellite normalized band difference index data. Land cover labels are automatically generated via our CoSA algorithm: Clustering of Sparse Approximations, using a clustering distance metric that combines spectral and spatial textural characteristics tomore » help separate geologic, vegetative, and hydrologie features. We demonstrate our method on example Worldview-2 satellite images of an Arctic region, and use CoSA labels to detect seasonal surface changes. In conclusion, our results suggest that neuroscience-based models are a promising approach to practical pattern recognition and change detection problems in remote sensing.« less

Using Fractal and Local Binary Pattern Features for Classification of ECOG Motor Imagery Tasks Obtained from the Right Brain Hemisphere.

PubMed

Xu, Fangzhou; Zhou, Weidong; Zhen, Yilin; Yuan, Qi; Wu, Qi

2016-09-01

The feature extraction and classification of brain signal is very significant in brain-computer interface (BCI). In this study, we describe an algorithm for motor imagery (MI) classification of electrocorticogram (ECoG)-based BCI. The proposed approach employs multi-resolution fractal measures and local binary pattern (LBP) operators to form a combined feature for characterizing an ECoG epoch recording from the right hemisphere of the brain. A classifier is trained by using the gradient boosting in conjunction with ordinary least squares (OLS) method. The fractal intercept, lacunarity and LBP features are extracted to classify imagined movements of either the left small finger or the tongue. Experimental results on dataset I of BCI competition III demonstrate the superior performance of our method. The cross-validation accuracy and accuracy is 90.6% and 95%, respectively. Furthermore, the low computational burden of this method makes it a promising candidate for real-time BCI systems.

Mapping Hydrothermal Alterations in the Muteh Gold Mining Area in Iran by using ASTER satellite Imagery data

NASA Astrophysics Data System (ADS)

Asadi Haroni, Hooshang; Hassan Tabatabaei, Seyed

2016-04-01

Muteh gold mining area is located in 160 km NW of Isfahan town. Gold mineralization is meso-thermal type and associated with silisic, seresitic and carbonate alterations as well as with hematite and goethite. Image processing and interpretation were applied on the ASTER satellite imagery data of about 400 km2 at the Muteh gold mining area to identify hydrothermal alterations and iron oxides associated with gold mineralization. After applying preprocessing methods such as radiometric and geometric corrections, image processing methods of Principal Components Analysis (PCA), Least Square Fit (Ls-Fit) and Spectral Angle Mapper (SAM) were applied on the ASTER data to identify hydrothermal alterations and iron oxides. In this research reference spectra of minerals such as chlorite, hematite, clay minerals and phengite identified from laboratory spectral analysis of collected samples were used to map the hydrothermal alterations. Finally, identified hydrothermal alteration and iron oxides were validated by visiting and sampling some of the mapped hydrothermal alterations.

Comparing multiple turbulence restoration algorithms performance on noisy anisoplanatic imagery

NASA Astrophysics Data System (ADS)

Rucci, Michael A.; Hardie, Russell C.; Dapore, Alexander J.

2017-05-01

In this paper, we compare the performance of multiple turbulence mitigation algorithms to restore imagery degraded by atmospheric turbulence and camera noise. In order to quantify and compare algorithm performance, imaging scenes were simulated by applying noise and varying levels of turbulence. For the simulation, a Monte-Carlo wave optics approach is used to simulate the spatially and temporally varying turbulence in an image sequence. A Poisson-Gaussian noise mixture model is then used to add noise to the observed turbulence image set. These degraded image sets are processed with three separate restoration algorithms: Lucky Look imaging, bispectral speckle imaging, and a block matching method with restoration filter. These algorithms were chosen because they incorporate different approaches and processing techniques. The results quantitatively show how well the algorithms are able to restore the simulated degraded imagery.

An evaluation of remote sensing technologies for the detection of fugitive contamination at selected Superfund hazardous waste sites in Pennsylvania

USGS Publications Warehouse

Slonecker, E. Terrence; Fisher, Gary B.

2014-01-01

This evaluation was conducted to assess the potential for using both traditional remote sensing, such as aerial imagery, and emerging remote sensing technology, such as hyperspectral imaging, as tools for postclosure monitoring of selected hazardous waste sites. Sixteen deleted Superfund (SF) National Priorities List (NPL) sites in Pennsylvania were imaged with a Civil Air Patrol (CAP) Airborne Real-Time Cueing Hyperspectral Enhanced Reconnaissance (ARCHER) sensor between 2009 and 2012. Deleted sites are those sites that have been remediated and removed from the NPL. The imagery was processed to radiance and atmospherically corrected to relative reflectance with standard software routines using the Environment for Visualizing Imagery (ENVI, ITT–VIS, Boulder, Colorado) software. Standard routines for anomaly detection, endmember collection, vegetation stress, and spectral analysis were applied.

Correcting infrared satellite estimates of sea surface temperature for atmospheric water vapor attenuation

NASA Technical Reports Server (NTRS)

Emery, William J.; Yu, Yunyue; Wick, Gary A.; Schluessel, Peter; Reynolds, Richard W.

1994-01-01

A new satellite sea surface temperature (SST) algorithm is developed that uses nearly coincident measurements from the microwave special sensor microwave imager (SSM/I) to correct for atmospheric moisture attenuation of the infrared signal from the advanced very high resolution radiometer (AVHRR). This new SST algorithm is applied to AVHRR imagery from the South Pacific and Norwegian seas, which are then compared with simultaneous in situ (ship based) measurements of both skin and bulk SST. In addition, an SST algorithm using a quadratic product of the difference between the two AVHRR thermal infrared channels is compared with the in situ measurements. While the quadratic formulation provides a considerable improvement over the older cross product (CPSST) and multichannel (MCSST) algorithms, the SSM/I corrected SST (called the water vapor or WVSST) shows overall smaller errors when compared to both the skin and bulk in situ SST observations. Applied to individual AVHRR images, the WVSST reveals an SST difference pattern (CPSST-WVSST) similar in shape to the water vapor structure while the CPSST-quadratic SST difference appears unrelated in pattern to the nearly coincident water vapor pattern. An application of the WVSST to week-long composites of global area coverage (GAC) AVHRR data demonstrates again the manner in which the WVSST corrects the AVHRR for atmospheric moisture attenuation. By comparison the quadratic SST method underestimates the SST corrections in the lower latitudes and overestimates the SST in th e higher latitudes. Correlations between the AVHRR thermal channel differences and the SSM/I water vapor demonstrate the inability of the channel difference to represent water vapor in the midlatitude and high latitudes during summer. Compared against drifting buoy data the WVSST and the quadratic SST both exhibit the same general behavior with the relatively small differences with the buoy temperatures.

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

NASA Astrophysics Data System (ADS)

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 (<=2 m) imagery and ongoing advances in computing power and analysis tools raises the prospect of performing ecosystem mapping at fine spatial scales over large study domains. Here we demonstrate cutting-edge mapping approaches over a ~35,000 km² study area on Alaska's North Slope using calibrated and atmospherically-corrected mosaics of high-resolution WorldView-2 and GeoEye-1 imagery: (1) an a priori spectral approach incorporating the Satellite Imagery Automatic Mapper (SIAM) algorithms; (2) image segmentation techniques; and (3) texture metrics. The SIAM spectral approach classifies radiometrically-calibrated imagery to general vegetation density categories and non-vegetated classes. The SIAM classes were developed globally and their applicability in arctic tundra 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.

Automatic extraction of plots from geo-registered UAS imagery of crop fields with complex planting schemes

NASA Astrophysics Data System (ADS)

Hearst, Anthony A.

Complex planting schemes are common in experimental crop fields and can make it difficult to extract plots of interest from high-resolution imagery of the fields gathered by Unmanned Aircraft Systems (UAS). This prevents UAS imagery from being applied in High-Throughput Precision Phenotyping and other areas of agricultural research. If the imagery is accurately geo-registered, then it may be possible to extract plots from the imagery based on their map coordinates. To test this approach, a UAS was used to acquire visual imagery of 5 ha of soybean fields containing 6.0 m2 plots in a complex planting scheme. Sixteen artificial targets were setup in the fields before flights and different spatial configurations of 0 to 6 targets were used as Ground Control Points (GCPs) for geo-registration, resulting in a total of 175 geo-registered image mosaics with a broad range of geo-registration accuracies. Geo-registration accuracy was quantified based on the horizontal Root Mean Squared Error (RMSE) of targets used as checkpoints. Twenty test plots were extracted from the geo-registered imagery. Plot extraction accuracy was quantified based on the percentage of the desired plot area that was extracted. It was found that using 4 GCPs along the perimeter of the field minimized the horizontal RMSE and enabled a plot extraction accuracy of at least 70%, with a mean plot extraction accuracy of 92%. Future work will focus on further enhancing the plot extraction accuracy through additional image processing techniques so that it becomes sufficiently accurate for all practical purposes in agricultural research and potentially other areas of research.

Expertise shapes domain-specific functional cerebral asymmetry during mental imagery: the case of culinary arts and music.

PubMed

Bensafi, Moustafa; Fournel, Arnaud; Joussain, Pauline; Poncelet, Johan; Przybylski, Lauranne; Rouby, Catherine; Tillmann, Barbara

2017-06-01

Mental imagery in experts has been documented in visual arts, music and dance. Here, we examined this issue in an understudied art domain, namely, culinary arts. Previous research investigating mental imagery in experts has reported either a stronger involvement of the right hemisphere or bilateral brain activation. The first aim of our study was to examine whether culinary arts also recruit such a hemispheric pattern specifically during odor mental imagery. In a second aim, we investigated whether expertise effects observed in a given sensory domain transfer to another modality. We combined psychophysics and neurophysiology to study mental imagery in cooks, musicians and controls. We collected response times and event-related potentials (ERP) while participants mentally compared the odor of fruits, the timbre of musical instruments and the size of fruits, musical instruments and manufactured objects. Cooks were faster in imagining fruit odors, and musicians were faster in imagining the timbre of musical instruments. These differences were not observed in control participants. This expertise effect was reflected in the ERP late positive complex (LPC): only experts showed symmetric bilateral activation, specifically when cooks imagined odors and when musicians imagined timbres. In contrast, the LPC was significantly greater in the left hemisphere than in the right hemisphere for non-expert participants in all conditions. These findings suggest that sensory expertise does not involve transfer of mental imagery ability across modalities and highlight for the first time that olfactory expertise in cooks induces a balance of activations between hemispheres as does musical expertise in musicians. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Imagery May Arise from Associations Formed through Sensory Experience: A Network of Spiking Neurons Controlling a Robot Learns Visual Sequences in Order to Perform a Mental Rotation Task

PubMed Central

McKinstry, Jeffrey L.; Fleischer, Jason G.; Chen, Yanqing; Gall, W. Einar; Edelman, Gerald M.

2016-01-01

Mental imagery occurs “when a representation of the type created during the initial phases of perception is present but the stimulus is not actually being perceived.” How does the capability to perform mental imagery arise? Extending the idea that imagery arises from learned associations, we propose that mental rotation, a specific form of imagery, could arise through the mechanism of sequence learning–that is, by learning to regenerate the sequence of mental images perceived while passively observing a rotating object. To demonstrate the feasibility of this proposal, we constructed a simulated nervous system and embedded it within a behaving humanoid robot. By observing a rotating object, the system learns the sequence of neural activity patterns generated by the visual system in response to the object. After learning, it can internally regenerate a similar sequence of neural activations upon briefly viewing the static object. This system learns to perform a mental rotation task in which the subject must determine whether two objects are identical despite differences in orientation. As with human subjects, the time taken to respond is proportional to the angular difference between the two stimuli. Moreover, as reported in humans, the system fills in intermediate angles during the task, and this putative mental rotation activates the same pathways that are activated when the system views physical rotation. This work supports the proposal that mental rotation arises through sequence learning and the idea that mental imagery aids perception through learned associations, and suggests testable predictions for biological experiments. PMID:27653977

Large Area Scene Selection Interface (LASSI). Methodology of Selecting Landsat Imagery for the Global Land Survey 2005

NASA Technical Reports Server (NTRS)

Franks, Shannon; Masek, Jeffrey G.; Headley, Rachel M.; Gasch, John; Arvidson, Terry

2009-01-01

The Global Land Survey (GLS) 2005 is a cloud-free, orthorectified collection of Landsat imagery acquired during the 2004-2007 epoch intended to support global land-cover and ecological monitoring. Due to the numerous complexities in selecting imagery for the GLS2005, NASA and the U.S. Geological Survey (USGS) sponsored the development of an automated scene selection tool, the Large Area Scene Selection Interface (LASSI), to aid in the selection of imagery for this data set. This innovative approach to scene selection applied a user-defined weighting system to various scene parameters: image cloud cover, image vegetation greenness, choice of sensor, and the ability of the Landsat 7 Scan Line Corrector (SLC)-off pair to completely fill image gaps, among others. The parameters considered in scene selection were weighted according to their relative importance to the data set, along with the algorithm's sensitivity to that weight. This paper describes the methodology and analysis that established the parameter weighting strategy, as well as the post-screening processes used in selecting the optimal data set for GLS2005.

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

NASA Astrophysics Data System (ADS)

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

Generation, Validation, and Application of Abundance Map Reference Data for Spectral Unmixing

NASA Astrophysics Data System (ADS)

Williams, McKay D.

Reference data ("ground truth") maps traditionally have been used to assess the accuracy of imaging spectrometer classification algorithms. However, these reference data can be prohibitively expensive to produce, often do not include sub-pixel abundance estimates necessary to assess spectral unmixing algorithms, and lack published validation reports. Our research proposes methodologies to efficiently generate, validate, and apply abundance map reference data (AMRD) to airborne remote sensing scenes. We generated scene-wide AMRD for three different remote sensing scenes using our remotely sensed reference data (RSRD) technique, which spatially aggregates unmixing results from fine scale imagery (e.g., 1-m Ground Sample Distance (GSD)) to co-located coarse scale imagery (e.g., 10-m GSD or larger). We validated the accuracy of this methodology by estimating AMRD in 51 randomly-selected 10 m x 10 m plots, using seven independent methods and observers, including field surveys by two observers, imagery analysis by two observers, and RSRD using three algorithms. Results indicated statistically-significant differences between all versions of AMRD, suggesting that all forms of reference data need to be validated. Given these significant differences between the independent versions of AMRD, we proposed that the mean of all (MOA) versions of reference data for each plot and class were most likely to represent true abundances. We then compared each version of AMRD to MOA. Best case accuracy was achieved by a version of imagery analysis, which had a mean coverage area error of 2.0%, with a standard deviation of 5.6%. One of the RSRD algorithms was nearly as accurate, achieving a mean error of 3.0%, with a standard deviation of 6.3%, showing the potential of RSRD-based AMRD generation. Application of validated AMRD to specific coarse scale imagery involved three main parts: 1) spatial alignment of coarse and fine scale imagery, 2) aggregation of fine scale abundances to produce coarse scale imagery-specific AMRD, and 3) demonstration of comparisons between coarse scale unmixing abundances and AMRD. Spatial alignment was performed using our scene-wide spectral comparison (SWSC) algorithm, which aligned imagery with accuracy approaching the distance of a single fine scale pixel. We compared simple rectangular aggregation to coarse sensor point spread function (PSF) aggregation, and found that the PSF approach returned lower error, but that rectangular aggregation more accurately estimated true abundances at ground level. We demonstrated various metrics for comparing unmixing results to AMRD, including mean absolute error (MAE) and linear regression (LR). We additionally introduced reference data mean adjusted MAE (MA-MAE), and reference data confidence interval adjusted MAE (CIA-MAE), which account for known error in the reference data itself. MA-MAE analysis indicated that fully constrained linear unmixing of coarse scale imagery across all three scenes returned an error of 10.83% per class and pixel, with regression analysis yielding a slope = 0.85, intercept = 0.04, and R2 = 0.81. Our reference data research has demonstrated a viable methodology to efficiently generate, validate, and apply AMRD to specific examples of airborne remote sensing imagery, thereby enabling direct quantitative assessment of spectral unmixing performance.

Spectral Mixture Analysis to map burned areas in Brazil's deforestation arc from 1992 to 2011

NASA Astrophysics Data System (ADS)

Antunes Daldegan, G.; Ribeiro, F.; Roberts, D. A.

2017-12-01

The two most extensive biomes in South America, the Amazon and the Cerrado, are subject to several fire events every dry season. Both are known for their ecological and environmental importance. However, due to the intensive human occupation over the last four decades, they have been facing high deforestation rates. The Cerrado biome is adapted to fire and is considered a fire-dependent landscape. In contrast, the Amazon as a tropical moist broadleaf forest does not display similar characteristics and is classified as a fire-sensitive landscape. Nonetheless, studies have shown that forest areas that have already been burned become more prone to experience recurrent burns. Remote sensing has been extensively used by a large number of researchers studying fire occurrence at a global scale, as well as in both landscapes aforementioned. Digital image processing aiming to map fire activity has been applied to a number of imagery from sensors of various spatial, temporal, and spectral resolutions. More specifically, several studies have used Landsat data to map fire scars in the Amazon forest and in the Cerrado. An advantage of using Landsat data is the potential to map fire scars at a finer spatial resolution, when compared to products derived from imagery of sensors featuring better temporal resolution but coarser spatial resolution, such as MODIS (Moderate Resolution Imaging Spectrometer) and GOES (Geostationary Operational Environmental Satellite). This study aimed to map burned areas present in the Amazon-Cerrado transition zone by applying Spectral Mixture Analysis on Landsat imagery for a period of 20 years (1992-2011). The study area is a subset of this ecotone, centered at the State of Mato Grosso. By taking advantage of the Landsat 5TM and Landsat 7ETM+ imagery collections available in Google Earth Engine platform and applying Spectral Mixture Analysis (SMA) techniques over them permitted to model fire scar fractions and delimitate burned areas. Overlaying yearly burned areas allowed to identify areas with high fire recurrence.

Astronaut Photography of the Earth: A Long-Term Dataset for Earth Systems Research, Applications, and Education

NASA Technical Reports Server (NTRS)

Stefanov, William L.

2017-01-01

The NASA Earth observations dataset obtained by humans in orbit using handheld film and digital cameras is freely accessible to the global community through the online searchable database at https://eol.jsc.nasa.gov, and offers a useful compliment to traditional ground-commanded sensor data. The dataset includes imagery from the NASA Mercury (1961) through present-day International Space Station (ISS) programs, and currently totals over 2.6 million individual frames. Geographic coverage of the dataset includes land and oceans areas between approximately 52 degrees North and South latitudes, but is spatially and temporally discontinuous. The photographic dataset includes some significant impediments for immediate research, applied, and educational use: commercial RGB films and camera systems with overlapping bandpasses; use of different focal length lenses, unconstrained look angles, and variable spacecraft altitudes; and no native geolocation information. Such factors led to this dataset being underutilized by the community but recent advances in automated and semi-automated image geolocation, image feature classification, and web-based services are adding new value to the astronaut-acquired imagery. A coupled ground software and on-orbit hardware system for the ISS is in development for planned deployment in mid-2017; this system will capture camera pose information for each astronaut photograph to allow automated, full georegistration of the data. The ground system component of the system is currently in use to fully georeference imagery collected in response to International Disaster Charter activations, and the auto-registration procedures are being applied to the extensive historical database of imagery to add value for research and educational purposes. In parallel, machine learning techniques are being applied to automate feature identification and classification throughout the dataset, in order to build descriptive metadata that will improve search capabilities. It is expected that these value additions will increase interest and use of the dataset by the global community.

Task-dependent activation of distinct fast and slow(er) motor pathways during motor imagery.

PubMed

Keller, Martin; Taube, Wolfgang; Lauber, Benedikt

2018-02-22

Motor imagery and actual movements share overlapping activation of brain areas but little is known about task-specific activation of distinct motor pathways during mental simulation of movements. For real contractions, it was demonstrated that the slow(er) motor pathways are activated differently in ballistic compared to tonic contractions but it is unknown if this also holds true for imagined contractions. The aim of the present study was to assess the activity of fast and slow(er) motor pathways during mentally simulated movements of ballistic and tonic contractions. H-reflexes were conditioned with transcranial magnetic stimulation at different interstimulus intervals to assess the excitability of fast and slow(er) motor pathways during a) the execution of tonic and ballistic contractions, b) motor imagery of these contraction types, and c) at rest. In contrast to the fast motor pathways, the slow(er) pathways displayed a task-specific activation: for imagined ballistic as well as real ballistic contractions, the activation was reduced compared to rest whereas enhanced activation was found for imagined tonic and real tonic contractions. This study provides evidence that the excitability of fast and slow(er) motor pathways during motor imagery resembles the activation pattern observed during real contractions. The findings indicate that motor imagery results in task- and pathway-specific subliminal activation of distinct subsets of neurons in the primary motor cortex. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Stereoscopy in cinematographic synthetic imagery

NASA Astrophysics Data System (ADS)

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.

Convective cell development and propagation in a mesoscale convective complex

NASA Technical Reports Server (NTRS)

Ahn, Yoo-Shin; Brundidge, Kenneth C.

1987-01-01

A case study was made of the mesoscale convective complex (MCC) which occurred over southern Oklahoma and northern Texas on 27 May 1981. This storm moved in an eastsoutheasterly direction and during much of its lifetime was observable by radars at Oklahoma City, Ok. and Stephenville, Tx. It was found that the direction of cell (VIP level 3 or more reflectivity) propagation was somewhat erratic but approximately the same as the system (VIP level 1 reflectivity) movement and the ambient wind. New cells developed along and behind the gust front make it appear that once the MCC is initiated, a synergistic relationship exists between the gust front and the MCC. The relationship between rainfall patterns and amounts and the infrared (IR) temperature field in the satellite imagery were examined. The 210 K isotherm of GOES IR imagery was found to encompass the rain area of the storm. The heaviest rainfall was in the vicinity of the VIP level 3 cells and mostly contained within the 205 K isotherm of GOES IR imagery.

Facilitating the exploitation of ERTS imagery using snow enhancement techniques

NASA Technical Reports Server (NTRS)

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

1973-01-01

The author has identified the following significant results. New fracture detail within New England test area has been interpreted from ERTS-1 images. Comparative analysis of snow-free imagery (1096-15065 and 1096-15072) has demonstrated that MSS bands 5 and 7 supply the greatest amount of geological fracture detail. Interpretation of the first snow-covered ERTS-1 images (1132-15074 and 1168-15065) in correlation with ground snow depth data indicates that a heavy blanket of snow (less than 9 inches) accentuates major structural features while a light dusting (greater than 1 inch) accentuates more subtle topographic expressions. Snow cover was found to accentuate drainage patterns which are indicative of lithological and/or structural variations. Snow cover provided added enhancement for viewing and detecting topographically expressed fractures and faults. A recent field investigation was conducted within the New England test area to field check lineaments observed from analysis of ERTS-1 imagery, collect snow depth readings, and obtain structural joint readings at key locations in the test area.

Mapping southern Atlantic coastal marshland, South Carolina-Georgia, using ERTS-1 imagery

NASA Technical Reports Server (NTRS)

Anderson, R. R. (Principal Investigator); Carter, V. L.; Mcginness, J. W., Jr.

1973-01-01

The author has identified the following significant results. Southeastern coastal marshes are among the most extensive and productive in the United States. A relatively low cost, moderately accurate method is needed to map these areas for management and protection. Ground based and low altitude aircraft methods for mapping are time consuming and quite expensive. The launch of NASA's ERTS-1 has provided an opportunity to test the feasibility of mapping wetlands using small scale imagery. The test site selected was an area from the South Carolina border to Saint Catherine's Island, Georgia. Results of the investigation indicate that the following may be ascertained from ERTS-1 imagery: (1) upper wetland boundary; (2) drainage pattern in the wetland; (3) plant communities such as Spartina alterniflora, Spartina patens, Juncus roemerianus; (4) ditching activities associated with agriculture; (5) lagooning for water-side home development. Conclusions are that ERTS-1 will be an excellent tool for many types of coastal wetland mapping.

The price had better be right: women's reactions to sexual stimuli vary with market factors.

PubMed

Vohs, Kathleen D; Sengupta, Jaideep; Dahl, Darren W

2014-01-01

Two experiments tested when and why women's typically negative, spontaneous reactions to sexual imagery would soften. Sexual economics theory predicts that women want sex to be seen as rare and special. We reasoned that this outlook would translate to women tolerating sexual images more when those images are linked to high worth as opposed to low worth. We manipulated whether an ad promoted an expensive or a cheap product using a sexually charged or a neutral scene. As predicted, women found sexual imagery distasteful when it was used to promote a cheap product, but this reaction to sexual imagery was mitigated if the product promoted was expensive. This pattern was not observed among men. Furthermore, we predicted and found that sexual ads promoting cheap products heightened feelings of being upset and angry among women. These findings suggest that women's reactions to sexual images can reveal deep-seated preferences about how sex should be used and understood.

Artic and subarctic environmental analyses utilizing ERTS-1 imagery. Cold regions environmental analysis based on ERTS-1 imagery (preprint)

NASA Technical Reports Server (NTRS)

Anderson, D. M. (Principal Investigator); Haugen, R. K.; Gatto, L. W.; Slaughter, C. W.; Marlar, T. L.; Mckim, H. L.

1972-01-01

There are no author-identified significant results in this report. An overriding problem in arctic and subarctic environmental research has been the absence of long-term observational data and the sparseness of geographical coverage of existing data. A first look report is presented on the use of ERTS-1 imagery as a major tool in two large area environmental studies: (1) investigation of sedimentation and other nearshore marine processes in Cook Inlet, Alaska; and (2) a regional study of permafrost regimes in the discontinuous permafrost zone of Alaska. These studies incorporate ground truth acquisition techniques that are probably similar to most ERTS investigations. Studies of oceanographic processes in Cook Inlet will be focused on seasonal changes in nearshore bathymetry, tidal and major current circulation patterns, and coastal sedimentation processes, applicable to navigation, construction, and maintenance of harbors. Analyses will be made of the regional permafrost distribution and regimes in the Upper Koyukuk-Kobuk River area located in NW Alaska.

Remote sensing in Iowa agriculture. [cropland inventory, soils, forestland, and crop diseases

NASA Technical Reports Server (NTRS)

Mahlstede, J. P. (Principal Investigator); Carlson, R. E.

1973-01-01

The author has identified the following significant results. Results include the estimation of forested and crop vegetation acreages using the ERTS-1 imagery. The methods used to achieve these estimates still require refinement, but the results appear promising. Practical applications would be directed toward achieving current land use inventories of these natural resources. This data is presently collected by sampling type surveys. If ERTS-1 can observe this and area estimates can be determined accurately, then a step forward has been achieved. Cost benefit relationship will have to be favorable. Problems still exist in these estimation techniques due to the diversity of the scene observed in the ERTS-1 imagery covering other part of Iowa. This is due to influence of topography and soils upon the adaptability of the vegetation to specific areas of the state. The state mosaic produced from ERTS-1 imagery shows these patterns very well. Research directed to acreage estimates is continuing.

Natural resource inventories and management applications in the Great Basin. [Nevada vegetation and wildlands

NASA Technical Reports Server (NTRS)

Tueller, P. T.; Lorain, G.; Halvorson, R. M.

1974-01-01

ERTS-1 resolution capabilities and repetitive coverage have allowed the acquisition of several statewide inventories of natural resource features not previously completed or that could not be completed in any other way. Familiarity with landform, tone, pattern and other converging factors, along with multidate imagery, has been required. Nevada's vegetation has been mapped from ERTS-1. Dynamic characteristics of the landscape have been studied. Sequential ERTS-1 imagery has proved its usefulness for mapping vegetation, following vegetation phenology changes, monitoring changes in lakes and reservoirs (including water quality), determining changes in surface mining use, making fire fuel estimates and determining potential hazard, mapping the distribution of rain and snow events, making range readiness determinations, monitoring marshland management practices and other uses. Feasibility has been determined, but details of incorporating the data in management systems awaits further research and development. The need is to accurately define the steps necessary to extract required or usable information from ERTS imagery and fit it into on-going management programs.

Monitoring the vernal advancement and retrogradation (green wave effect) of natural vegetation

NASA Technical Reports Server (NTRS)

Rouse, J. W., Jr. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Preliminary evaluation of autumnal phase ground truth data suggests that the sampling procedures at the Great Plains Corridor network test sites are adequate to show relatively small temporal changes in above-ground vegetation biomass and vegetation condition. Vegetation changes measured August through December, reflect grazing intensity and environmental conditions at the test sites. Preliminary analysis of black and white imagery suggests that detail in vegetation patterns is much greater than originally anticipated. A first look analysis of single band imagery and digital data at two locations shows that woodland, grassland, and cropland areas are easily delineated. Computer derived grey-scale maps from MSS digital data were shown to be useful in identifying the location of small fields and features of the natural and cultivated lands. Single band imagery and digital data are believed to have important application for synoptic land use mapping and inventory. Initial ratio analysis, using band 5 and 7 data, suggests the applicability in the greenness of a vegetative scene.

Spatial and Temporal Varying Thresholds for Cloud Detection in Satellite Imagery

NASA Technical Reports Server (NTRS)

Jedlovec, Gary; Haines, Stephanie

2007-01-01

A new cloud detection technique has been developed and applied to both geostationary and polar orbiting satellite imagery having channels in the thermal infrared and short wave infrared spectral regions. The bispectral composite threshold (BCT) technique uses only the 11 micron and 3.9 micron channels, and composite imagery generated from these channels, in a four-step cloud detection procedure to produce a binary cloud mask at single pixel resolution. A unique aspect of this algorithm is the use of 20-day composites of the 11 micron and the 11 - 3.9 micron channel difference imagery to represent spatially and temporally varying clear-sky thresholds for the bispectral cloud tests. The BCT cloud detection algorithm has been applied to GOES and MODIS data over the continental United States over the last three years with good success. The resulting products have been validated against "truth" datasets (generated by the manual determination of the sky conditions from available satellite imagery) for various seasons from the 2003-2005 periods. The day and night algorithm has been shown to determine the correct sky conditions 80-90% of the time (on average) over land and ocean areas. Only a small variation in algorithm performance occurs between day-night, land-ocean, and between seasons. The algorithm performs least well. during he winter season with only 80% of the sky conditions determined correctly. The algorithm was found to under-determine clouds at night and during times of low sun angle (in geostationary satellite data) and tends to over-determine the presence of clouds during the day, particularly in the summertime. Since the spectral tests use only the short- and long-wave channels common to most multispectral scanners; the application of the BCT technique to a variety of satellite sensors including SEVERI should be straightforward and produce similar performance results.

Sampling Of SAR Imagery For Wind Resource Assesment

NASA Astrophysics Data System (ADS)

Badger, Merete; Badger, Jake; Hasager, Charlotte; Nielsen, Morten

2010-04-01

Wind resources over the sea can be assessed from a series of wind fields retrieved from Envisat ASAR imagery, or other SAR data. Previous wind resource maps have been produced through random sampling of 70 or more satellite scenes over a given area of interest followed by fitting of a Weibull function to the data. Here we introduce a more advanced sampling strategy based on wind class methodology that is normally applied in Risø DTU’s numerical modeling of wind resources. The aim is to obtain a more representative data set using fewer satellite SAR scenes. The new sampling strategy has been applied within a wind and solar resource assessment study for the United Arab Emirates (UAE) and also for wind resource mapping over a domain in the North Sea, as part of the EU- NORSEWInD project (2008-2012).

Korean coastal water depth/sediment and land cover mapping (1:25,000) by computer analysis of LANDSAT imagery

NASA Technical Reports Server (NTRS)

Park, K. Y.; Miller, L. D.

1978-01-01

Computer analysis was applied to single date LANDSAT MSS imagery of a sample coastal area near Seoul, Korea equivalent to a 1:50,000 topographic map. Supervised image processing yielded a test classification map from this sample image containing 12 classes: 5 water depth/sediment classes, 2 shoreline/tidal classes, and 5 coastal land cover classes at a scale of 1:25,000 and with a training set accuracy of 76%. Unsupervised image classification was applied to a subportion of the site analyzed and produced classification maps comparable in results in a spatial sense. The results of this test indicated that it is feasible to produce such quantitative maps for detailed study of dynamic coastal processes given a LANDSAT image data base at sufficiently frequent time intervals.

Combined use of remote sensing and seismic observations to infer geologically recent crustal deformation, active faulting, and stress fields. [California and Pennsylvania

NASA Technical Reports Server (NTRS)

Alexander, S. S. (Principal Investigator)

1982-01-01

Characteristic traits for earthquakes associated with strike-slip motion in Central California and the Salton Sea area, as revealed in ground based studies and LANDSAT imagery, were compared. The mapped lineaments are found to be oriented in several dominant directions. One direction is the same as the trend of the San Andreas fault. The other directions differ from area to area and may reflect the stresses of earlier geologic processes. The pattern of lineament orientations is significantly LANDSAT MSS data, SEASAT synthetic aperture radar data, and magnetic field data from the South Mountain area west of Gettysburg, Pennsylvania were registered to match each other in spatial position and merged. Pattern recognition techniques were applied to the composite data set to determine its utility in recognizing different rock types and structures in vegetated terrain around South Mountain. With the use of a texture algorithm to enhance geologic features, a classification of the entire area was made. A test of the correlation between SAR tone and texture, LANDSAT tone and texture, and magnetic field data revealed no tone or texture measures linking any two of the original data sets.

Gabor Filters and Neural Networks for Segmentation of Synthetic Aperture Radar Imagery

DTIC Science & Technology

1990-12-01

unending enthusiasm focused my efforts. I would also like to thank Dr Matthew Kabrisky and Maj Rogers for their enlightening pattern recognition courses...merit in neurophysiology . Specifically, interest in the Gabor function results from recent research demonstrating its close approximation to measured

Observation of wave celerity evolution in the nearshore using digital video imagery

NASA Astrophysics Data System (ADS)

Yoo, J.; Fritz, H. M.; Haas, K. A.; Work, P. A.; Barnes, C. F.; Cho, Y.

2008-12-01

Celerity of incident waves in the nearshore is observed from oblique video imagery collected at Myrtle Beach, S.C.. The video camera covers the field view of length scales O(100) m. Celerity of waves propagating in shallow water including the surf zone is estimated by applying advanced image processing and analysis methods to the individual video images sampled at 3 Hz. Original image sequences are processed through video image frame differencing, directional low-pass image filtering to reduce the noise arising from foam in the surf zone. The breaking wave celerity is computed along a cross-shore transect from the wave crest tracks extracted by a Radon transform-based line detection method. The observed celerity from the nearshore video imagery is larger than the linear wave celerity computed from the measured water depths over the entire surf zone. Compared to the nonlinear shallow water wave equation (NSWE)-based celerity computed using the measured depths and wave heights, in general, the video-based celerity shows good agreements over the surf zone except the regions across the incipient wave breaking locations. In the regions across the breaker points, the observed wave celerity is even larger than the NSWE-based celerity due to the transition of wave crest shapes. The observed celerity using the video imagery can be used to monitor the nearshore geometry through depth inversion based on the nonlinear wave celerity theories. For this purpose, the exceeding celerity across the breaker points needs to be corrected accordingly compared to a nonlinear wave celerity theory applied.

Image enhancements of Landsat 8 (OLI) and SAR data for preliminary landslide identification and mapping applied to the central region of Kenya

NASA Astrophysics Data System (ADS)

Mwaniki, M. W.; Kuria, D. N.; Boitt, M. K.; Ngigi, T. G.

2017-04-01

Image enhancements lead to improved performance and increased accuracy of feature extraction, recognition, identification, classification and hence change detection. This increases the utility of remote sensing to suit environmental applications and aid disaster monitoring of geohazards involving large areas. The main aim of this study was to compare the effect of image enhancement applied to synthetic aperture radar (SAR) data and Landsat 8 imagery in landslide identification and mapping. The methodology involved pre-processing Landsat 8 imagery, image co-registration, despeckling of the SAR data, after which Landsat 8 imagery was enhanced by Principal and Independent Component Analysis (PCA and ICA), a spectral index involving bands 7 and 4, and using a False Colour Composite (FCC) with the components bearing the most geologic information. The SAR data were processed using textural and edge filters, and computation of SAR incoherence. The enhanced spatial, textural and edge information from the SAR data was incorporated to the spectral information from Landsat 8 imagery during the knowledge based classification. The methodology was tested in the central highlands of Kenya, characterized by rugged terrain and frequent rainfall induced landslides. The results showed that the SAR data complemented Landsat 8 data which had enriched spectral information afforded by the FCC with enhanced geologic information. The SAR classification depicted landslides along the ridges and lineaments, important information lacking in the Landsat 8 image classification. The success of landslide identification and classification was attributed to the enhanced geologic features by spectral, textural and roughness properties.

Index finger motor imagery EEG pattern recognition in BCI applications using dictionary cleaned sparse representation-based classification for healthy people

NASA Astrophysics Data System (ADS)

Miao, Minmin; Zeng, Hong; Wang, Aimin; Zhao, Fengkui; Liu, Feixiang

2017-09-01

Electroencephalogram (EEG)-based motor imagery (MI) brain-computer interface (BCI) has shown its effectiveness for the control of rehabilitation devices designed for large body parts of the patients with neurologic impairments. In order to validate the feasibility of using EEG to decode the MI of a single index finger and constructing a BCI-enhanced finger rehabilitation system, we collected EEG data during right hand index finger MI and rest state for five healthy subjects and proposed a pattern recognition approach for classifying these two mental states. First, Fisher's linear discriminant criteria and power spectral density analysis were used to analyze the event-related desynchronization patterns. Second, both band power and approximate entropy were extracted as features. Third, aiming to eliminate the abnormal samples in the dictionary and improve the classification performance of the conventional sparse representation-based classification (SRC) method, we proposed a novel dictionary cleaned sparse representation-based classification (DCSRC) method for final classification. The experimental results show that the proposed DCSRC method gives better classification accuracies than SRC and an average classification accuracy of 81.32% is obtained for five subjects. Thus, it is demonstrated that single right hand index finger MI can be decoded from the sensorimotor rhythms, and the feature patterns of index finger MI and rest state can be well recognized for robotic exoskeleton initiation.

Applied Remote Sensing Program (ARSP)

NASA Technical Reports Server (NTRS)

Mouat, D. A.; Johnson, J. D.; Foster, K. E.

1977-01-01

Descriptions of projects engaged by the Applied Remote Sensors Program in the state of Arizona are contained in an annual report for the fiscal year 1976-1977. Remote sensing techniques included thermal infrared imagery in analog and digital form and conversion of data into thermograms. Delineation of geologic areas, surveys of vegetation and inventory of resources were also presented.

Landsat and agriculture—Case studies on the uses and benefits of Landsat imagery in agricultural monitoring and production

USGS Publications Warehouse

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

2017-03-29

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

Archaeological Evidence for Abrupt Cimate Change: Results from Satellite Imagery Analysis and Subsequent Ground-Truthing in the El-Manzalah Region, Northeast Egyptian Delta

NASA Astrophysics Data System (ADS)

Parcak, S. H.

2003-12-01

The abrupt global climate changes recorded at 8.2, 5.2 and 4.2 ka BP caused a wide range of transformations within ancient societies, including the focus of this study: ancient Egypt . In the case of the climatic changes that occurred at 4.2 ka BP, scholars have debated hotly the events surrounding the "collapse" of the Old Kingdom. Despite such studies into the Old Kingdom's "collapse", there have been insufficient regional settlement pattern studies in Egypt to augment hypotheses concerning the mechanisms behind the cultural transformations that occurred at the end of the Old Kingdom. Utilizing a combination of satellite imagery analysis and subsequent ground-truthing techniques over a broad region in the East Delta, this study aims to reconstruct pharaonic settlement distributions in relation to the changing northeast delta topography, river courses, marshlands, and coastline. Although geo-political and religious factors played varying roles in settlement patterns, this study overlies the economic and environmental components behind the settlement of individual sites and areas. For instance, prior to the formation of the Manzala lagoon, beginning in the 4th century AD, the Mendesian branch of the Nile flowed past Mendes and its satellite, maritime port at Tell Tebilla: As early as the Old Kingdom, Tell Tebilla provided an ideal location for the formation of a town, being well-located to exploit both riverine and maritime transportation routes through trade, and regional floral and faunal resources from hunting, fishing, cultivation and animal husbandry. Key factors such as long-term fluctuations in precipitation, flood levels, and river courses, can affect dramatically the fortunes of individual settlements, areas, and regions, resulting in the decline and abandonment of some sites and the foundation and flourishing of other sites, especially within marginal regions. The Egyptian delta represents an ideal region for studying the impacts of climatic changes through time since it is particularly sensitive to river changes, coastal expansion, and changes within the floral and faunal resource base available to settlements through time. In order to locate ancient settlements in the northeast delta, this study introduced a variety of innovative techniques involving satellite image analysis through Corona, Spot, Landsat and ASTER images, in conjunction with existing archaeological survey data and maps. All known sites were plotted against the satellite imagery data, in order to ascertain whether the newly designed site identification methods worked. The technique had a 95 percent success rate in locating over 100 previously known sites. This technique was next applied to locate new sites and sites believed to be destroyed. In order to verify the accuracy of this new site locational technique, this writer conducted ground-truthing during the summer of 2003, assessing and photographing over 60 new and little known sites in the East Delta. The surface pottery from each site was examined and photographed, and revealed settlements dating to the Old Kingdom, Late Period and Roman Periods. Each known and newly-discovered settlement will be plotted on maps of the eastern Delta, in order to show site disbursement during the time periods represented, especially in relation to geziras, rivers, canals, marshes and the ancient coastline. The paper demonstrates the affects that abrupt climatic changes had on ancient settlement patterns, and reveals how satellite imagery interpretation is applicable to similar studies in other regions.

Comparing Features for Classification of MEG Responses to Motor Imagery.

PubMed

Halme, Hanna-Leena; Parkkonen, Lauri

2016-01-01

Motor imagery (MI) with real-time neurofeedback could be a viable approach, e.g., in rehabilitation of cerebral stroke. Magnetoencephalography (MEG) noninvasively measures electric brain activity at high temporal resolution and is well-suited for recording oscillatory brain signals. MI is known to modulate 10- and 20-Hz oscillations in the somatomotor system. In order to provide accurate feedback to the subject, the most relevant MI-related features should be extracted from MEG data. In this study, we evaluated several MEG signal features for discriminating between left- and right-hand MI and between MI and rest. MEG was measured from nine healthy participants imagining either left- or right-hand finger tapping according to visual cues. Data preprocessing, feature extraction and classification were performed offline. The evaluated MI-related features were power spectral density (PSD), Morlet wavelets, short-time Fourier transform (STFT), common spatial patterns (CSP), filter-bank common spatial patterns (FBCSP), spatio-spectral decomposition (SSD), and combined SSD+CSP, CSP+PSD, CSP+Morlet, and CSP+STFT. We also compared four classifiers applied to single trials using 5-fold cross-validation for evaluating the classification accuracy and its possible dependence on the classification algorithm. In addition, we estimated the inter-session left-vs-right accuracy for each subject. The SSD+CSP combination yielded the best accuracy in both left-vs-right (mean 73.7%) and MI-vs-rest (mean 81.3%) classification. CSP+Morlet yielded the best mean accuracy in inter-session left-vs-right classification (mean 69.1%). There were large inter-subject differences in classification accuracy, and the level of the 20-Hz suppression correlated significantly with the subjective MI-vs-rest accuracy. Selection of the classification algorithm had only a minor effect on the results. We obtained good accuracy in sensor-level decoding of MI from single-trial MEG data. Feature extraction methods utilizing both the spatial and spectral profile of MI-related signals provided the best classification results, suggesting good performance of these methods in an online MEG neurofeedback system.

Applying Lidar and High-Resolution Multispectral Imagery for Improved Quantification and Mapping of Tundra Vegetation Structure and Distribution in the Alaskan Arctic

NASA Astrophysics Data System (ADS)

Greaves, Heather E.

Climate change is disproportionately affecting high northern latitudes, and the extreme temperatures, remoteness, and sheer size of the Arctic tundra biome have always posed challenges that make application of remote sensing technology especially appropriate. Advances in high-resolution remote sensing continually improve our ability to measure characteristics of tundra vegetation communities, which have been difficult to characterize previously due to their low stature and their distribution in complex, heterogeneous patches across large landscapes. In this work, I apply terrestrial lidar, airborne lidar, and high-resolution airborne multispectral imagery to estimate tundra vegetation characteristics for a research area near Toolik Lake, Alaska. Initially, I explored methods for estimating shrub biomass from terrestrial lidar point clouds, finding that a canopy-volume based algorithm performed best. Although shrub biomass estimates derived from airborne lidar data were less accurate than those from terrestrial lidar data, algorithm parameters used to derive biomass estimates were similar for both datasets. Additionally, I found that airborne lidar-based shrub biomass estimates were just as accurate whether calibrated against terrestrial lidar data or harvested shrub biomass--suggesting that terrestrial lidar potentially could replace destructive biomass harvest. Along with smoothed Normalized Differenced Vegetation Index (NDVI) derived from airborne imagery, airborne lidar-derived canopy volume was an important predictor in a Random Forest model trained to estimate shrub biomass across the 12.5 km2 covered by our lidar and imagery data. The resulting 0.80 m resolution shrub biomass maps should provide important benchmarks for change detection in the Toolik area, especially as deciduous shrubs continue to expand in tundra regions. Finally, I applied 33 lidar- and imagery-derived predictor layers in a validated Random Forest modeling approach to map vegetation community distribution at 20 cm resolution across the data collection area, creating maps that will enable validation of coarser maps, as well as study of fine-scale ecological processes in the area. These projects have pushed the limits of what can be accomplished for vegetation mapping using airborne remote sensing in a challenging but important region; it is my hope that the methods explored here will illuminate potential paths forward as landscapes and technologies inevitably continue to change.

Using Satellite Imagery to Assess Large-Scale Habitat Characteristics of Adirondack Park, New York, USA

NASA Astrophysics Data System (ADS)

McClain, Bobbi J.; Porter, William F.

2000-11-01

Satellite imagery is a useful tool for large-scale habitat analysis; however, its limitations need to be tested. We tested these limitations by varying the methods of a habitat evaluation for white-tailed deer ( Odocoileus virginianus) in the Adirondack Park, New York, USA, utilizing harvest data to create and validate the assessment models. We used two classified images, one with a large minimum mapping unit but high accuracy and one with no minimum mapping unit but slightly lower accuracy, to test the sensitivity of the evaluation to these differences. We tested the utility of two methods of assessment, habitat suitability index modeling, and pattern recognition modeling. We varied the scale at which the models were applied by using five separate sizes of analysis windows. Results showed that the presence of a large minimum mapping unit eliminates important details of the habitat. Window size is relatively unimportant if the data are averaged to a large resolution (i.e., township), but if the data are used at the smaller resolution, then the window size is an important consideration. In the Adirondacks, the proportion of hardwood and softwood in an area is most important to the spatial dynamics of deer populations. The low occurrence of open area in all parts of the park either limits the effect of this cover type on the population or limits our ability to detect the effect. The arrangement and interspersion of cover types were not significant to deer populations.

Enhancing performance of a motor imagery based brain-computer interface by incorporating electrical stimulation-induced SSSEP

NASA Astrophysics Data System (ADS)

Yi, Weibo; Qiu, Shuang; Wang, Kun; Qi, Hongzhi; Zhao, Xin; He, Feng; Zhou, Peng; Yang, Jiajia; Ming, Dong

2017-04-01

Objective. We proposed a novel simultaneous hybrid brain-computer interface (BCI) by incorporating electrical stimulation into a motor imagery (MI) based BCI system. The goal of this study was to enhance the overall performance of an MI-based BCI. In addition, the brain oscillatory pattern in the hybrid task was also investigated. Approach. 64-channel electroencephalographic (EEG) data were recorded during MI, selective attention (SA) and hybrid tasks in fourteen healthy subjects. In the hybrid task, subjects performed MI with electrical stimulation which was applied to bilateral median nerve on wrists simultaneously. Main results. The hybrid task clearly presented additional steady-state somatosensory evoked potential (SSSEP) induced by electrical stimulation with MI-induced event-related desynchronization (ERD). By combining ERD and SSSEP features, the performance in the hybrid task was significantly better than in both MI and SA tasks, achieving a ~14% improvement in total relative to the MI task alone and reaching ~89% in mean classification accuracy. On the contrary, there was no significant enhancement obtained in performance while separate ERD feature was utilized in the hybrid task. In terms of the hybrid task, the performance using combined feature was significantly better than using separate ERD or SSSEP feature. Significance. The results in this work validate the feasibility of our proposed approach to form a novel MI-SSSEP hybrid BCI outperforming a conventional MI-based BCI through combing MI with electrical stimulation.

Human Migration and Agricultural Expansion: An Impending Threat to the Maya Biosphere Reserve

NASA Technical Reports Server (NTRS)

Sader, Steven; Reining, Conard; Sever, Thomas L.; Soza, Carlos

1997-01-01

Evidence is presented of the current threats to the Maya Biosphere Reserve in northern Guatemala as derived through time-series Landsat Thematic Mapper observations and analysis. Estimates of deforestation rates and trends are examined for different management units within the reserve and buffer zones. The satellite imagery was used to quantify and monitor rates, patterns, and trends of forest clearing during a time period corresponding to new road construction and significant human migration into the newly accessible forest region. Satellite imagery is appropriate technology in a vast and remote tropical region where aerial photography and extensive field-based methods are not cost-effective and current, timely data is essential for establishing conservation priorities.

Digital processing of satellite imagery application to jungle areas of Peru

NASA Technical Reports Server (NTRS)

Pomalaza, J. C. (Principal Investigator); Pomalaza, C. A.; Espinoza, J.

1976-01-01

The author has identified the following significant results. The use of clustering methods permits the development of relatively fast classification algorithms that could be implemented in an inexpensive computer system with limited amount of memory. Analysis of CCTs using these techniques can provide a great deal of detail permitting the use of the maximum resolution of LANDSAT imagery. Potential cases were detected in which the use of other techniques for classification using a Gaussian approximation for the distribution functions can be used with advantage. For jungle areas, channels 5 and 7 can provide enough information to delineate drainage patterns, swamp and wet areas, and make a reasonable broad classification of forest types.

Applications of ERTS-1 data to landscape change in eastern Tennessee

NASA Technical Reports Server (NTRS)

Rehder, J. B. (Principal Investigator)

1973-01-01

The author has identified the following significant results. The analysis of landscape change in eastern Tennessee from ERTS-1 data is being derived from three avenues of experimentation and analysis: (1) a multi-stage sampling procedure utilizing ground and aircraft imagery for ground truth and control; (2) a densitometric and computer analytical experiment for the analysis of gray tone signatures and comparisons for landscape change detection and monitoring; and (3) an ERTS image enhancement procedure for the detection and analysis of photomorphic regions. Significant results include: maps of strip mining changes and forest inventory, watershed identification and delimitation, and agricultural regions derived from spring plowing patterns appearing on the ERTS-1 imagery.

Selective loss of verbal imagery.

PubMed

Mehta, Z; Newcombe, F

1996-05-01

This single case study of the ability to generate verbal and non-verbal imagery in a woman who sustained a gunshot wound to the brain reports a significant difficulty in generating images of word shapes but not a significant problem in generating object images. Further dissociation, however, was observed in her ability to generate images of living vs non-living material. She made more errors in imagery and factual information tasks for non-living items than for living items. This pattern contrasts with our previous report of the agnosic patient, M.S., who had severe difficulty in generating images of living material, whereas his ability to image the shape of words was comparable to that of normal control subjects. Furthermore, with regard to the generation of images of living compared with non-living material, M.S. shows more errors with living than nonliving items. In contrast, the present patient, S.M., made significantly more errors with non-living relative to living items. There appear to be two types of double dissociation which reinforce the growing evidence of dissociable impairments in the ability to generate images for different types of verbal and non-verbal material. Such dissociations, presumably related to sensory and cognitive processing demands, address the problem of the neural basis of imagery.

Application of ERTS-1 data to the protection and management of New Jersey's coastal environment

NASA Technical Reports Server (NTRS)

Yunghans, R. S.; Feinberg, E. B.; Wobber, F. J.; Mairs, R. L. (Principal Investigator); Garofalo, D.; Thibault, D. A.; Amato, R. V.; Pettinger, L. R.

1973-01-01

The author has identified the following significant results. This catalogue was prepared as a part of the joint ERTS-1 New Jersey coastal mapping experiment. First look analysis of ERTS-1 images indicates that numerous coastal oceanographic patterns can be mapped on a sequential basis using ERTS-1 images. Analysis of imagery indicates a predominant southwesterly drift of dumped wasted in the surface waters. Initial analysis of imagery indicates that the effects of tidal flushing of New York harbor extend as far south as Long Branch, New Jersey. Analysis of imagery from 3 September, 1972, indicates a wide band of turbid water extending several miles offshore around Barnegat Inlet. First look analysis of imagery from 10 October, 1972, illustrates the increased reflectance of turbid waters within the bays, sounds, and thoroughfares behind the barrier islands in the southern New Jersey shore area. The estuarine waters emanating from both Brigantine and Absecon Inlets are very turbid relative to the waters further offshore and to the north and south. The tidal prism appears to be quite large but the movement of water once outside the inlets is not very rapid. The waters are not moving away from the coastline but rather along the coast.

Principal sources and dispersal patterns of suspended particulate matter in nearshore surface waters of the northeast Pacific Ocean and seasonal variation in snow cover in the Sierra Nevada

NASA Technical Reports Server (NTRS)

Carlson, P. R. (Principal Investigator); Harden, D. R.

1973-01-01

The author has identified the following significant results. ERTS-1 imagery used in conjunction with the surface-drift cards indicated a southerly flow direction of the central California near surface coastal currents during mid-June 1973. The near-surface currents off northern California and southern Oregon were more complex. Some drift cards were recovered north and some south of their release points; however, the prevalent direction of flow was northerly. General agreement in flow direction of coastal currents obtained from ERTS-1 imagery and drift card data reinforces the image interpretation. Complete seasonal coverage of nearshore circulation interpreted from ERTS-1 imagery will provide information necessary for proper coastal zone management. Extent of snow cover can be readily delimited on ERTS-1 band 5. In the central Sierra Nevada Mountains this past winter season, the snow line, as recorded by ERTS-1, reached an elevation of less than 1500 meters in January but had melted back to between 2500 and 3000 meters by the end of May. ERTS-1 imagery seems to provide sufficient resolution to make it a useful tool for monitoring changes in snow cover in the Sierra Nevada Mountains.

Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation

PubMed Central

Jin, Wei; Gong, Fei; Zeng, Xingbin; Fu, Randi

2016-01-01

Automatic cloud detection and classification using satellite cloud imagery have various meteorological applications such as weather forecasting and climate monitoring. Cloud pattern analysis is one of the research hotspots recently. Since satellites sense the clouds remotely from space, and different cloud types often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite cloud imagery. Satellite observation is susceptible to noises, while traditional cloud classification methods are sensitive to noises and outliers; it is hard for traditional cloud classification methods to achieve reliable results. To deal with these problems, a satellite cloud classification method using adaptive fuzzy sparse representation-based classification (AFSRC) is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite cloud imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC), atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for cloud classification is proposed. Experiment results on FY-2G satellite cloud image show that, the proposed method not only improves the accuracy of cloud classification, but also has strong stability and adaptability with high computational efficiency. PMID:27999261

Force related hemodynamic responses during execution and imagery of a hand grip task: A functional near infrared spectroscopy study.

PubMed

Wriessnegger, Selina C; Kirchmeyr, Daniela; Bauernfeind, Günther; Müller-Putz, Gernot R

2017-10-01

We examined force related hemodynamic changes during the performance of a motor execution (ME) and motor imagery (MI) task by means of multichannel functional near infrared spectroscopy (fNIRS). The hemodynamic responses of fourteen healthy participants were measured while they performed a hand grip execution or imagery task with low and high grip forces. We found an overall higher increase of [oxy-Hb] concentration changes during ME for both grip forces but with a delayed peak maximum for the lower grip force. During the MI task with lower grip force, the [oxy-Hb] level increases are stronger compared to the MI with higher grip force. The facilitation in performing MI with higher grip strength might thus indicate less inhibition of the actual motor act which could also explain the later increase onset of [oxy-Hb] in the ME task with the lower grip force. Our results suggest that execution and imagery of a hand grip task with high and low grip forces, leads to different cortical activation patterns. Since impaired control of grip forces during object manipulation in particular is one aspect of fine motor control deficits after stroke, our study will contribute to future rehabilitation programs enhancing patient's grip force control. Copyright © 2017 Elsevier Inc. All rights reserved.

Predicting workload profiles of brain-robot interface and electromygraphic neurofeedback with cortical resting-state networks: personal trait or task-specific challenge?

NASA Astrophysics Data System (ADS)

Fels, Meike; Bauer, Robert; Gharabaghi, Alireza

2015-08-01

Objective. Novel rehabilitation strategies apply robot-assisted exercises and neurofeedback tasks to facilitate intensive motor training. We aimed to disentangle task-specific and subject-related contributions to the perceived workload of these interventions and the related cortical activation patterns. Approach. We assessed the perceived workload with the NASA Task Load Index in twenty-one subjects who were exposed to two different feedback tasks in a cross-over design: (i) brain-robot interface (BRI) with haptic/proprioceptive feedback of sensorimotor oscillations related to motor imagery, and (ii) control of neuromuscular activity with feedback of the electromyography (EMG) of the same hand. We also used electroencephalography to examine the cortical activation patterns beforehand in resting state and during the training session of each task. Main results. The workload profile of BRI feedback differed from EMG feedback and was particularly characterized by the experience of frustration. The frustration level was highly correlated across tasks, suggesting subject-related relevance of this workload component. Those subjects who were specifically challenged by the respective tasks could be detected by an interhemispheric alpha-band network in resting state before the training and by their sensorimotor theta-band activation pattern during the exercise. Significance. Neurophysiological profiles in resting state and during the exercise may provide task-independent workload markers for monitoring and matching participants’ ability and task difficulty of neurofeedback interventions.

Using forest inventory plot data and satellite imagery from MODIS and Landsat-TM to model spatial distribution patterns of honeysuckle and privet

Treesearch

Dumitru Salajanu; Dennis M. Jacobs

2009-01-01

Forest inventory and analysis data monitor the presence and extent of certain non-native invasive species. Onforestland, non-native species are considered part of the understory vegetation and can be found near canopyopenings as well as and...

Ocean Thermal Feature Recognition, Discrimination and Tracking Using Infrared Satellite Imagery

DTIC Science & Technology

1991-06-01

rejected if the temperature in the mapped area exceeds classification criteria ............................... 17 viii 2.6 Ideal feature space mapping from...in seconds, and 1P is the side dimension of the pixel in meters. Figure 2.6: Ideal feature space mapping from pattern tile - search tile comparison. 20

Multiple-scale proximal sensor and remote imagery technology for sustaining agricultural productivity during climate change

USDA-ARS?s Scientific Manuscript database

Changes in climatic patterns have had dramatic influence on agricultural areas worldwide, particularly in irrigated arid-zone agricultural areas subjected to recurring drought, such as California’s San Joaquin Valley. Climate change has impacted water availability, which subsequently has impacted so...

Patterns of zone management uncertainty in cotton using tarnished plant bug distributions, NDVI, soil EC, yield and thermal imagery

USDA-ARS?s Scientific Manuscript database

Management zones for various crops have been delineated using NDVI (Normalized Difference Vegetation Index), apparent bulk soil electrical conductivity (ECa - Veris), and yield data; however, estimations of uncertainty for these data layers are equally important considerations. The objective of this...

High-resolution IKONOS satellite imagery for normalized difference vegetative index-related assessment applied to land clearance studies

NASA Astrophysics Data System (ADS)

Lavers, Chris R.; Mason, Travis

2017-07-01

High-resolution satellite imagery permits verification of human rights land clearance violations across international borders as a result of unstable regimes or socio-economic upheaval. Without direct access to these areas to validate allegations of human rights abuse, the use of remote sensing tools, techniques, and data is extremely important. Humanitarian assessment can benefit from software-based solutions, involving radiometrically calibrated normalized difference vegetation index and temporal change imagery. We discuss the introduction of a matrix filter approach for change detection studies to help assist rapid building detection over large search areas against a bright background to evaluate internally displaced people in the 2005 Porta Farm Zimbabwe clearances. Future wide-scale near real-time space-based monitoring with a range of digital filters would be of great benefit to international human rights observers and human rights networks.

LANDSAT-1 data, its use in a soil survey program

NASA Technical Reports Server (NTRS)

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

1975-01-01

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

Short-lived brain state after cued motor imagery in naive subjects.

PubMed

Pfurtscheller, G; Scherer, R; Müller-Putz, G R; Lopes da Silva, F H

2008-10-01

Multi-channel electroencephalography recordings have shown that a visual cue, indicating right hand, left hand or foot motor imagery, can induce a short-lived brain state in the order of about 500 ms. In the present study, 10 able-bodied subjects without any motor imagery experience (naive subjects) were asked to imagine the indicated limb movement for some seconds. Common spatial filtering and linear single-trial classification was applied to discriminate between two conditions (two brain states: right hand vs. left hand, left hand vs. foot and right hand vs. foot). The corresponding classification accuracies (mean +/- SD) were 80.0 +/- 10.6%, 83.3 +/- 10.2% and 83.6 +/- 8.8%, respectively. Inspection of central mu and beta rhythms revealed a short-lasting somatotopically specific event-related desynchronization (ERD) in the upper mu and/or beta bands starting approximately 300 ms after the cue onset and lasting for less than 1 s.

Automated vehicle detection in forward-looking infrared imagery.

PubMed

Der, Sandor; Chan, Alex; Nasrabadi, Nasser; Kwon, Heesung

2004-01-10

We describe an algorithm for the detection and clutter rejection of military vehicles in forward-looking infrared (FLIR) imagery. The detection algorithm is designed to be a prescreener that selects regions for further analysis and uses a spatial anomaly approach that looks for target-sized regions of the image that differ in texture, brightness, edge strength, or other spatial characteristics. The features are linearly combined to form a confidence image that is thresholded to find likely target locations. The clutter rejection portion uses target-specific information extracted from training samples to reduce the false alarms of the detector. The outputs of the clutter rejecter and detector are combined by a higher-level evidence integrator to improve performance over simple concatenation of the detector and clutter rejecter. The algorithm has been applied to a large number of FLIR imagery sets, and some of these results are presented here.

Quantifying genre: an operational definition of tragedy and comedy based on Shakespeare's plays.

PubMed

Whissell, Cynthia

2007-08-01

Emotion and imagery in the words of Shakespeare's plays, as measured by the Dictionary of Affect in Language, were used to predict genre (tragedy or comedy). Genre distinctions, which were associated with small effect sizes, were established on the basis of 23 plays and then applied to other plays. A discriminant function which combined lower emotional Pleasantness with higher emotional Activation or arousal and more pictorial Imagery successfully (91% of the time) predicted whether a play was a tragedy or a comedy. The genre-discriminating formula provided meaningful categorizations of 23 additional plays. As hypothesized, comedies employed more Pleasant words than tragedies. Tragedies employed more Active words (p < .001). Unexpectedly, comedies rather than tragedies employed words with lower Imagery (greater Abstraction). The predicted elevation of language in tragedy was noted instead in the use of more verse, fewer common words, and fewer personal pronouns (less subjectivity).

Are synesthetes exceptional beyond their synesthetic associations? A systematic comparison of creativity, personality, cognition, and mental imagery in synesthetes and controls.

PubMed

Chun, Charlotte A; Hupé, Jean-Michel

2016-08-01

Synesthesia has historically been linked with enhanced creativity, but this had never been demonstrated in a systematically recruited sample. The current study offers a broad examination of creativity, personality, cognition, and mental imagery in a small sample of systematically recruited synesthetes and controls (n = 65). Synesthetes scored higher on some measures of creativity, personality traits of absorption and openness, and cognitive abilities of verbal comprehension and mental imagery. The differences were smaller than those reported in the literature, indicating that previous studies may have overestimated group differences, perhaps due to biased recruitment procedures. Nonetheless, most of our results replicated literature findings, yielding two possibilities: (1) our study was influenced by similar biases, or (2) differences between synesthetes and controls, though modest, are robust across recruitment methods. The covariance among our measures warrants interpretation of these differences as a pattern of associations with synesthesia, leaving open the possibility that this pattern could be explained by differences on a single measured trait, or even a hidden, untested trait. More generally, this study highlights the difficulty of comparing groups of people in psychology, not to mention neuropsychology and neuroimaging studies. The requirements discussed here - systematic recruitment procedures, large battery of tests, and large cohorts - are best fulfilled through collaborative efforts and cumulative science. © 2015 The Authors. British Journal of Psychology published by John Wiley & Sons Ltd on behalf of British Psychological Society.

Environmental applications utilizing digital aerial imagery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Monday, H.M.

1995-06-01

This paper discusses the use of satellite imagery, aerial photography, and computerized airborne imagery as applied to environmental mapping, analysis, and monitoring. A project conducted by the City of Irving, Texas involves compliance with national pollutant discharge elimination system (NPDES) requirements stipulated by the Environmental Protection Agency. The purpose of the project was the development and maintenance of a stormwater drainage utility. Digital imagery was collected for a portion of the city to map the City`s porous and impervious surfaces which will then be overlaid with property boundaries in the City`s existing Geographic information System (GIS). This information will allowmore » the City to determine an equitable tax for each land parcel according to the amount of water each parcel is contributing to the stormwater system. Another project involves environmental compliance for warm water discharges created by utility companies. Environmental consultants are using digital airborne imagery to analyze thermal plume affects as well as monitoring power generation facilities. A third project involves wetland restoration. Due to freeway and other forms of construction, plus a major reduction of fresh water supplies, the Southern California coastal wetlands are being seriously threatened. These wetlands, rich spawning grounds for plant and animal life, are home to thousands of waterfowl and shore birds who use this habitat for nesting and feeding grounds. Under the leadership of Southern California Edison (SCE) and CALTRANS (California Department of Transportation), several wetland areas such as the San Dieguito Lagoon (Del Mar, California), the Sweetwater Marsh (San Diego, California), and the Tijuana Estuary (San Diego, California) are being restored and closely monitored using digital airborne imagery.« less

Task 1: Correlation of satellite and ground data in air pollution studies. Task 2: Investigation to relate the chlorophyll and suspended sediment content in the waters of the lower Chesapeake Bay to ERTS-1 imagery. Task 3: The use of ERTS-1 to more fully utilize and apply marine station data to the study of productivity along the Eastern Shelf expanded waters of the United States

NASA Technical Reports Server (NTRS)

Copeland, G. E. (Principal Investigator); Bandy, A. R.; Fleischer, P.; Ludwick, J. C. (Principal Investigator); Hanna, W. J.; Gosink, T. A.; Bowker, D. W.; Marshall, H. G. (Principal Investigator)

1972-01-01

The author has identified the following significant results. Analysis of U-2 imagery of CARETS site indicates smoke plumes can be easily detected. First look at selected ERTS-1 color composites demonstrates plumes from forest fires can be detected.

Automatic orientation and 3D modelling from markerless rock art imagery

NASA Astrophysics Data System (ADS)

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.

An efficient rhythmic component expression and weighting synthesis strategy for classifying motor imagery EEG in a brain computer interface

NASA Astrophysics Data System (ADS)

Wang, Tao; He, Bin

2004-03-01

The recognition of mental states during motor imagery tasks is crucial for EEG-based brain computer interface research. We have developed a new algorithm by means of frequency decomposition and weighting synthesis strategy for recognizing imagined right- and left-hand movements. A frequency range from 5 to 25 Hz was divided into 20 band bins for each trial, and the corresponding envelopes of filtered EEG signals for each trial were extracted as a measure of instantaneous power at each frequency band. The dimensionality of the feature space was reduced from 200 (corresponding to 2 s) to 3 by down-sampling of envelopes of the feature signals, and subsequently applying principal component analysis. The linear discriminate analysis algorithm was then used to classify the features, due to its generalization capability. Each frequency band bin was weighted by a function determined according to the classification accuracy during the training process. The present classification algorithm was applied to a dataset of nine human subjects, and achieved a success rate of classification of 90% in training and 77% in testing. The present promising results suggest that the present classification algorithm can be used in initiating a general-purpose mental state recognition based on motor imagery tasks.

Comparison of satellite reflectance algorithms for estimating ...

EPA Pesticide Factsheets

We analyzed 10 established and 4 new satellite reflectance algorithms for estimating chlorophyll-a (Chl-a) in a temperate reservoir in southwest Ohio using coincident hyperspectral aircraft imagery and dense water truth collected within one hour of image acquisition to develop simple proxies for algal blooms and to facilitate portability between multispectral satellite imagers for regional algal bloom monitoring. Narrow band hyperspectral aircraft images were upscaled spectrally and spatially to simulate 5 current and near future satellite imaging systems. Established and new Chl-a algorithms were then applied to the synthetic satellite images and then compared to calibrated Chl-a water truth measurements collected from 44 sites within one hour of aircraft acquisition of the imagery. Masks based on the spatial resolution of the synthetic satellite imagery were then applied to eliminate mixed pixels including vegetated shorelines. Medium-resolution Landsat and finer resolution data were evaluated against 29 coincident water truth sites. Coarse-resolution MODIS and MERIS-like data were evaluated against 9 coincident water truth sites. Each synthetic satellite data set was then evaluated for the performance of a variety of spectrally appropriate algorithms with regard to the estimation of Chl-a concentrations against the water truth data set. The goal is to inform water resource decisions on the appropriate satellite data acquisition and processing for the es

A novel approach for epipolar resampling of cross-track linear pushbroom imagery using orbital parameters model

NASA Astrophysics Data System (ADS)

Jannati, Mojtaba; Valadan Zoej, Mohammad Javad; Mokhtarzade, Mehdi

2018-03-01

This paper presents a novel approach to epipolar resampling of cross-track linear pushbroom imagery using orbital parameters model (OPM). The backbone of the proposed method relies on modification of attitude parameters of linear array stereo imagery in such a way to parallelize the approximate conjugate epipolar lines (ACELs) with the instantaneous base line (IBL) of the conjugate image points (CIPs). Afterward, a complementary rotation is applied in order to parallelize all the ACELs throughout the stereo imagery. The new estimated attitude parameters are evaluated based on the direction of the IBL and the ACELs. Due to the spatial and temporal variability of the IBL (respectively changes in column and row numbers of the CIPs) and nonparallel nature of the epipolar lines in the stereo linear images, some polynomials in the both column and row numbers of the CIPs are used to model new attitude parameters. As the instantaneous position of sensors remains fix, the digital elevation model (DEM) of the area of interest is not required in the resampling process. According to the experimental results obtained from two pairs of SPOT and RapidEye stereo imagery with a high elevation relief, the average absolute values of remained vertical parallaxes of CIPs in the normalized images were obtained 0.19 and 0.28 pixels respectively, which confirm the high accuracy and applicability of the proposed method.

Integrating geologic and satellite radar data for mapping dome-and-basin patterns in the In Ouzzal Terrane, Western Hoggar, Algeria

NASA Astrophysics Data System (ADS)

Deroin, Jean-Paul; Djemai, Safouane; Bendaoud, Abderrahmane; Brahmi, Boualem; Ouzegane, Khadidja; Kienast, Jean-Robert

2014-11-01

The In Ouzzal Terrane (IOT) located in the north-western part of the Tuareg Shield forms an elongated N-S trending block, more than 400 km long and 80 km wide. It involves an Archaean crust remobilized during a very high-temperature metamorphic event related to the Palaeoproterozoic orogeny. The IOT largely crops out in the rocky and sandy desert of Western Hoggar. It corresponds mainly to a flat area with some reliefs composed of Late Panafrican granites, dyke networks or Cambrian volcanic rocks. These flat areas are generally covered by thin sand veneers. They are favorable for discriminating bedrock geological units using imaging radar, backscattering measurements, and field checking, because the stony desert is particularly sensitive to the radar parameters such as wavelength or polarization. The main radar data used are those obtained with the ALOS-PALSAR sensor (L-band), in ScanSAR mode (large swath) and Fine Beam modes. The PALSAR sensor has been also compared to ENVISAT-ASAR and to optical imagery. Detailed mapping of some key areas indicates extensive Archaean dome-and-basin patterns. In certain parts, the supracrustal synforms and orthogneiss domes exhibit linear or circular features corresponding to shear zones or rolling structures, respectively. The geological mapping of these dome-and-basin structures, and more generally of the Archaean and Proterozoic lithological units, is more accurate with the SAR imagery, particularly when using the L-band, than with the optical imagery. A quantitative approach is carried out in order to estimate the backscatter properties of the main rock types. Due to the large variety of configurations, radar satellite imagery such as ALOS PALSAR represents a key tool for geological mapping in arid region at different scales from the largest (e.g., 1:500,000) to the smallest (e.g., 1:50,000).

A Comparison of the Red Green Blue Air Mass Imagery and Hyperspectral Infrared Retrieved Profiles

NASA Technical Reports Server (NTRS)

Berndt, E. B.; Folmer, Michael; Dunion, Jason

2014-01-01

The Red Green Blue (RGB) Air Mass imagery is derived from multiple channels or paired channel differences. Multiple channel products typically provide additional information than a single channel can provide alone. The RGB Air Mass imagery simplifies the interpretation of temperature and moisture characteristics of air masses surrounding synoptic and mesoscale features. Despite the ease of interpretation of multiple channel products, the combination of channels and channel differences means the resulting product does not represent a quantity or physical parameter such as brightness temperature in conventional single channel satellite imagery. Without a specific quantity to reference, forecasters are often confused as to what RGB products represent. Hyperspectral infrared retrieved profiles of temperature, moisture, and ozone can provide insight about the air mass represented on the RGB Air Mass product and provide confidence in the product and representation of air masses despite the lack of a quantity to reference for interpretation. This study focuses on RGB Air Mass analysis of Hurricane Sandy as it moved north along the U.S. East Coast, while transitioning to a hybrid extratropical storm. Soundings and total column ozone retrievals were analyzed using data from the Cross-track Infrared and Advanced Technology Microwave Sounder Suite (CrIMSS) on the Suomi National Polar Orbiting Partnership satellite and the Atmospheric Infrared Sounder (AIRS) on the National Aeronautics and Space Administration Aqua satellite along with dropsondes that were collected from National Oceanic and Atmospheric Administration and Air Force research aircraft. By comparing these datasets to the RGB Air Mass, it is possible to capture quantitative information that could help in analyzing the synoptic environment enough to diagnose the onset of extratropical transition. This was done by identifying any stratospheric air intrusions (SAIs) that existed in the vicinity of Sandy as the wind field expanded and the cloud pattern evolved into an atypical pattern.

Using High Resolution Commercial Satellite Imagery to Quantify Spatial Features of Urban Areas and their Relationship to Quality of Life Indicators in Accra, Ghana

NASA Astrophysics Data System (ADS)

Sandborn, A.; Engstrom, R.; Yu, Q.

2014-12-01

Mapping urban areas via satellite imagery is an important task for detecting and anticipating land cover and land use change at multiple scales. As developing countries experience substantial urban growth and expansion, remotely sensed based estimates of population and quality of life indicators can provide timely and spatially explicit information to researchers and planners working to determine how cities are changing. In this study, we use commercial high spatial resolution satellite imagery in combination with fine resolution census data to determine the ability of using remotely sensed data to reveal the spatial patterns of quality of life in Accra, Ghana. Traditionally, spectral characteristics are used on a per-pixel basis to determine land cover; however, in this study, we test a new methodology that quantifies spatial characteristics using a variety of spatial features observed in the imagery to determine the properties of an urban area. The spatial characteristics used in this study include histograms of oriented gradients, PanTex, Fourier transform, and line support regions. These spatial features focus on extracting structural and textural patterns of built-up areas, such as homogeneous building orientations and straight line indices. Information derived from aggregating the descriptive statistics of the spatial features at both the fine-resolution census unit and the larger neighborhood level are then compared to census derived quality of life indicators including information about housing, education, and population estimates. Preliminary results indicate that there are correlations between straight line indices and census data including available electricity and literacy rates. Results from this study will be used to determine if this methodology provides a new and improved way to measure a city structure in developing cities and differentiate between residential and commercial land use zones, as well as formal versus informal housing areas.

Inferring the Ecological Niche of Toxoplasma gondii and Bartonella spp. in Wild Felids.

PubMed

Escobar, Luis E; Carver, Scott; Romero-Alvarez, Daniel; VandeWoude, Sue; Crooks, Kevin R; Lappin, Michael R; Craft, Meggan E

2017-01-01

Traditional epidemiological studies of disease in animal populations often focus on directly transmitted pathogens. One reason pathogens with complex lifecycles are understudied could be due to challenges associated with detection in vectors and the environment. Ecological niche modeling (ENM) is a methodological approach that overcomes some of the detection challenges often seen with vector or environmentally dependent pathogens. We test this approach using a unique dataset of two pathogens in wild felids across North America: Toxoplasma gondii and Bartonella spp. in bobcats ( Lynx rufus ) and puma ( Puma concolor ). We found three main patterns. First, T. gondii showed a broader use of environmental conditions than did Bartonella spp. Also, ecological niche models, and Normalized Difference Vegetation Index satellite imagery, were useful even when applied to wide-ranging hosts. Finally, ENM results from one region could be applied to other regions, thus transferring information across different landscapes. With this research, we detail the uncertainty of epidemiological risk models across novel environments, thereby advancing tools available for epidemiological decision-making. We propose that ENM could be a valuable tool for enabling understanding of transmission risk, contributing to more focused prevention and control options for infectious diseases.

Movement imagery classification in EMOTIV cap based system by Naïve Bayes.

PubMed

Stock, Vinicius N; Balbinot, Alexandre

2016-08-01

Brain-computer interfaces (BCI) provide means of communications and control, in assistive technology, which do not require motor activity from the user. The goal of this study is to promote classification of two types of imaginary movements, left and right hands, in an EMOTIV cap based system, using the Naïve Bayes classifier. A preliminary analysis with respect to results obtained by other experiments in this field is also conducted. Processing of the electroencephalography (EEG) signals is done applying Common Spatial Pattern filters. The EPOC electrodes cap is used for EEG acquisition, in two test subjects, for two distinct trial formats. The channels picked are FC5, FC6, P7 and P8 of the 10-20 system, and a discussion about the differences of using C3, C4, P3 and P4 positions is proposed. Dataset 3 of the BCI Competition II is also analyzed using the implemented algorithms. The maximum classification results for the proposed experiment and for the BCI Competition dataset were, respectively, 79% and 85% The conclusion of this study is that the picked positions for electrodes may be applied for BCI systems with satisfactory classification rates.

Cotton growth modeling and assessment using unmanned aircraft system visual-band imagery

NASA Astrophysics Data System (ADS)

Chu, Tianxing; Chen, Ruizhi; Landivar, Juan A.; Maeda, Murilo M.; Yang, Chenghai; Starek, Michael J.

2016-07-01

This paper explores the potential of using unmanned aircraft system (UAS)-based visible-band images to assess cotton growth. By applying the structure-from-motion algorithm, the cotton plant height (ph) and canopy cover (cc) information were retrieved from the point cloud-based digital surface models (DSMs) and orthomosaic images. Both UAS-based ph and cc follow a sigmoid growth pattern as confirmed by ground-based studies. By applying an empirical model that converts the cotton ph to cc, the estimated cc shows strong correlation (R2=0.990) with the observed cc. An attempt for modeling cotton yield was carried out using the ph and cc information obtained on June 26, 2015, the date when sigmoid growth curves for both ph and cc tended to decline in slope. In a cross-validation test, the correlation between the ground-measured yield and the estimated equivalent derived from the ph and/or cc was compared. Generally, combining ph and cc, the performance of the yield estimation is most comparable against the observed yield. On the other hand, the observed yield and cc-based estimation produce the second strongest correlation, regardless of the complexity of the models.

A New Approach to Automated Labeling of Internal Features of Hardwood Logs Using CT Images

Treesearch

Daniel L. Schmoldt; Pei Li; A. Lynn Abbott

1996-01-01

The feasibility of automatically identifying internal features of hardwood logs using CT imagery has been established previously. Features of primary interest are bark, knots, voids, decay, and clear wood. Our previous approach: filtered original CT images, applied histogram segmentation, grew volumes to extract 3-d regions, and applied a rule base, with Dempster-...

Abstracting GIS Layers from Hyperspectral Imagery

DTIC Science & Technology

2009-03-01

Difference Vegetative Index ( NDVI ) 2-20 2.2.10 Separating Trees from Grass . . . . . . . . . . . 2-22 2.3 Spatial Analysis...2-18 2.10. Example of the Normalized Difference Vegetation Index ( NDVI ) applied to a hyperspectral image. . . . . . . . . . . . . . . . . . 2-20...3.5. Example of applying NDVI to a SOM. . . . . . . . . . . . . . . 3-8 3.6. Visualization of the NIR scatter tree ID algorithm. . . . . . . . 3-9 ix

Landscape pattern metrics and regional assessment

USGS Publications Warehouse

O'Neill, R. V.; Riitters, K.H.; Wickham, J.D.; Jones, K.B.

1999-01-01

The combination of remote imagery data, geographic information systems software, and landscape ecology theory provides a unique basis for monitoring and assessing large-scale ecological systems. The unique feature of the work has been the need to develop and interpret quantitative measures of spatial pattern-the landscape indices. This article reviews what is known about the statistical properties of these pattern metrics and suggests some additional metrics based on island biogeography, percolation theory, hierarchy theory, and economic geography. Assessment applications of this approach have required interpreting the pattern metrics in terms of specific environmental endpoints, such as wildlife and water quality, and research into how to represent synergystic effects of many overlapping sources of stress.

Online and Offline Performance Gains Following Motor Imagery Practice: A Comprehensive Review of Behavioral and Neuroimaging Studies.

PubMed

Di Rienzo, Franck; Debarnot, Ursula; Daligault, Sébastien; Saruco, Elodie; Delpuech, Claude; Doyon, Julien; Collet, Christian; Guillot, Aymeric

2016-01-01

There is now compelling evidence that motor imagery (MI) promotes motor learning. While MI has been shown to influence the early stages of the learning process, recent data revealed that sleep also contributes to the consolidation of the memory trace. How such "online" and "offline" processes take place and how they interact to impact the neural underpinnings of movements has received little attention. The aim of the present review is twofold: (i) providing an overview of recent applied and fundamental studies investigating the effects of MI practice (MIP) on motor learning; and (ii) detangling applied and fundamental findings in support of a sleep contribution to motor consolidation after MIP. We conclude with an integrative approach of online and offline learning resulting from intense MIP in healthy participants, and underline research avenues in the motor learning/clinical domains.

Cloud cover determination in polar regions from satellite imagery

NASA Technical Reports Server (NTRS)

Barry, R. G.; Maslanik, J. A.; Key, J. R.

1987-01-01

A definition is undertaken of the spectral and spatial characteristics of clouds and surface conditions in the polar regions, and to the creation of calibrated, geometrically correct data sets suitable for quantitative analysis. Ways are explored in which this information can be applied to cloud classifications as new methods or as extensions to existing classification schemes. A methodology is developed that uses automated techniques to merge Advanced Very High Resolution Radiometer (AVHRR) and Scanning Multichannel Microwave Radiometer (SMMR) data, and to apply first-order calibration and zenith angle corrections to the AVHRR imagery. Cloud cover and surface types are manually interpreted, and manual methods are used to define relatively pure training areas to describe the textural and multispectral characteristics of clouds over several surface conditions. The effects of viewing angle and bidirectional reflectance differences are studied for several classes, and the effectiveness of some key components of existing classification schemes is tested.

The Goddard Profiling Algorithm (GPROF): Description and Current Applications

NASA Technical Reports Server (NTRS)

Olson, William S.; Yang, Song; Stout, John E.; Grecu, Mircea

2004-01-01

Atmospheric scientists use different methods for interpreting satellite data. In the early days of satellite meteorology, the analysis of cloud pictures from satellites was primarily subjective. As computer technology improved, satellite pictures could be processed digitally, and mathematical algorithms were developed and applied to the digital images in different wavelength bands to extract information about the atmosphere in an objective way. The kind of mathematical algorithm one applies to satellite data may depend on the complexity of the physical processes that lead to the observed image, and how much information is contained in the satellite images both spatially and at different wavelengths. Imagery from satellite-borne passive microwave radiometers has limited horizontal resolution, and the observed microwave radiances are the result of complex physical processes that are not easily modeled. For this reason, a type of algorithm called a Bayesian estimation method is utilized to interpret passive microwave imagery in an objective, yet computationally efficient manner.

Method for the visualization of landform by mapping using low altitude UAV application

NASA Astrophysics Data System (ADS)

Sharan Kumar, N.; Ashraf Mohamad Ismail, Mohd; Sukor, Nur Sabahiah Abdul; Cheang, William

2018-05-01

Unmanned Aerial Vehicle (UAV) and Digital Photogrammetry are evolving drastically in mapping technology. The significance and necessity for digital landform mapping are developing with years. In this study, a mapping workflow is applied to obtain two different input data sets which are the orthophoto and DSM. A fine flying technology is used to capture Low Altitude Aerial Photography (LAAP). Low altitude UAV (Drone) with the fixed advanced camera was utilized for imagery while computerized photogrammetry handling using Photo Scan was applied for cartographic information accumulation. The data processing through photogrammetry and orthomosaic processes is the main applications. High imagery quality is essential for the effectiveness and nature of normal mapping output such as 3D model, Digital Elevation Model (DEM), Digital Surface Model (DSM) and Ortho Images. The exactitude of Ground Control Points (GCP), flight altitude and the resolution of the camera are essential for good quality DEM and Orthophoto.

Online and Offline Performance Gains Following Motor Imagery Practice: A Comprehensive Review of Behavioral and Neuroimaging Studies

PubMed Central

Di Rienzo, Franck; Debarnot, Ursula; Daligault, Sébastien; Saruco, Elodie; Delpuech, Claude; Doyon, Julien; Collet, Christian; Guillot, Aymeric

2016-01-01

There is now compelling evidence that motor imagery (MI) promotes motor learning. While MI has been shown to influence the early stages of the learning process, recent data revealed that sleep also contributes to the consolidation of the memory trace. How such “online” and “offline” processes take place and how they interact to impact the neural underpinnings of movements has received little attention. The aim of the present review is twofold: (i) providing an overview of recent applied and fundamental studies investigating the effects of MI practice (MIP) on motor learning; and (ii) detangling applied and fundamental findings in support of a sleep contribution to motor consolidation after MIP. We conclude with an integrative approach of online and offline learning resulting from intense MIP in healthy participants, and underline research avenues in the motor learning/clinical domains. PMID:27445755

Applicability of ERTS-1 to Montana geology

NASA Technical Reports Server (NTRS)

Weidman, R. M. (Principal Investigator); Alt, D. D.; Berg, R. A.; Johns, W. M.; Flood, R. E.; Hawley, K. T.; Wackwitz, L. K.

1973-01-01

The author has identified the following significant results. A detailed band 7 ERTS-1 lineament map covering western Montana and northern Idaho has been prepared and is being evaluated by direct comparison with geologic maps, by statistical plots of lineaments and known faults, and by field checking. Lineament patterns apparent in the Idaho and Boulder batholiths do not correspond to any known geologic structures. A band 5 mosaic of Montana and adjacent areas has been laid and a lineament annotation prepared for comparison with the band 7 map. All work to date indicates that ERTS-1 imagery is very useful for revealing patterns of high-angle faults, though much less useful for mapping rock units and patterns of low-angle faults. Large-scale mosaics of U-2 photographs of three test sites have been prepared for annotation and comparison with ERTS-1 maps. Mapping of Quaternary deposits in the Glacial Lake Missoula basin using U-2 color infrared transparencies has been successful resulting in the discovery of some deposits not previously mapped. Detailed work has been done for Test Site 354 D using ERTS-1 imagery; criteria for recognition of several rock types have been found. Photogeologic mapping for southeastern Montana suggest Wasatch deposits where none shown of geologic map.

Can the Psycho-Emotional State be Optimized by Regular Use of Positive Imagery?, Psychological and Electroencephalographic Study of Self-Guided Training

PubMed Central

Velikova, Svetla; Sjaaheim, Haldor; Nordtug, Bente

2017-01-01

The guided imagery training is considered as an effective method and therefore widely used in modern cognitive psychotherapy, while less is known about the effectiveness of self-guided. The present study investigated the effects of regular use of self-guided positive imagery, applying both subjective (assessment of the psycho-emotional state) and objective (electroencephalographic, EEG) approaches to research. Thirty healthy subjects participated in the cognitive imagery-training program for 12 weeks. The schedule began with group training with an instructor for 2 days, where the participants learned various techniques of positive imagery, after which they continued their individual training at home. Psychological and EEG evaluations were applied at the baseline and at the end of the training period. The impact of training on the psycho-emotional states of the participants was evaluated through: Center for epidemiologic studies- Depression (CES-D) 20 item scale, Satisfaction with life scale (SWLS) and General Self-Efficacy scale (GSE). EEGs (19-channels) were recorded at rest with eyes closed. EEG analysis was performed using Low resolution electromagnetic tomography (LORETA) software that allows the comparison of current source density (CSD) and functional connectivity (lagged phase and coherence) in the default mode network before and after a workout. Initial assessment with CES-D indicated that 22 participants had subthreshold depression. After the training participants had less prominent depressive symptoms (CES-D, p = 0.002), were more satisfied with their lives (SWLS, p = 0.036), and also evaluated themselves as more effective (GSE, p = 0.0002). LORETA source analysis revealed an increase in the CSD in the right mPFC (Brodmann area 10) for beta-2 band after training (p = 0.038). LORETA connectivity analysis demonstrated an increase in lagged coherence between temporal gyruses of both hemispheres in the delta band, as well as between the Posterior cingulate cortex and right BA21 in the theta band after a workout. Since mPFC is involved in emotional regulation, functional changes in this region can be seen in line with the results of psychological tests and their objective validation. A possible activation of GAMK-ergic system is discussed. Self-guided positive imagery (after instructions) can be helpful for emotional selfregulation in healthy subjects and has the potential to be useful in subthreshold depression. PMID:28127281

Integration of geological remote-sensing techniques in subsurface analysis

USGS Publications Warehouse

Taranik, James V.; Trautwein, Charles M.

1976-01-01

Geological remote sensing is defined as the study of the Earth utilizing electromagnetic radiation which is either reflected or emitted from its surface in wavelengths ranging from 0.3 micrometre to 3 metres. The natural surface of the Earth is composed of a diversified combination of surface cover types, and geologists must understand the characteristics of surface cover types to successfully evaluate remotely-sensed data. In some areas landscape surface cover changes throughout the year, and analysis of imagery acquired at different times of year can yield additional geological information. Integration of different scales of analysis allows landscape features to be effectively interpreted. Interpretation of the static elements displayed on imagery is referred to as an image interpretation. Image interpretation is dependent upon: (1) the geologist's understanding of the fundamental aspects of image formation, and (2.) his ability to detect, delineate, and classify image radiometric data; recognize radiometric patterns; and identify landscape surface characteristics as expressed on imagery. A geologic interpretation integrates surface characteristics of the landscape with subsurface geologic relationships. Development of a geologic interpretation from imagery is dependent upon: (1) the geologist's ability to interpret geomorphic processes from their static surface expression as landscape characteristics on imagery, (2) his ability to conceptualize the dynamic processes responsible for the evolution 6f interpreted geologic relationships (his ability to develop geologic models). The integration of geologic remote-sensing techniques in subsurface analysis is illustrated by development of an exploration model for ground water in the Tucson area of Arizona, and by the development of an exploration model for mineralization in southwest Idaho.

Mapping cropping patterns in irrigated rice fields in West Java: Towards mapping vulnerability to flooding using time-series MODIS imageries

NASA Astrophysics Data System (ADS)

Sianturi, Riswan; Jetten, V. G.; Sartohadi, Junun

2018-04-01

Information on the vulnerability to flooding is vital to understand the potential damages from flood events. A method to determine the vulnerability to flooding in irrigated rice fields using the Enhanced Vegetation Index (EVI) was proposed in this study. In doing so, the time-series EVI derived from time-series 8 day 500 m spatial resolution MODIS imageries (MOD09A1) was used to generate cropping patterns in irrigated rice fields in West Java. Cropping patterns were derived from the spatial distribution and phenology metrics so that it is possible to show the variation of vulnerability in space and time. Vulnerability curves and cropping patterns were used to determine the vulnerability to flooding in irrigated rice fields. Cropping patterns capture the shift in the vulnerability, which may lead to either an increase or decrease of the degree of damage in rice fields of origin and other rice fields. The comparison of rice field areas between MOD09A1 and ALOS PALSAR and MOD09A1 and Agricultural Statistics showed consistent results with R2 = 0.81 and R2 = 0.93, respectively. The estimated and observed DOYs showed RMSEs = 9.21, 9.29, and 9.69 days for the Start of Season (SOS), heading stage, and End of Season (EOS), respectively. Using the method, one can estimate the relative damage provided available information on the flood depth and velocity. The results of the study may support the efforts to reduce the potential damages from flooding in irrigated rice fields.

EEG classification for motor imagery and resting state in BCI applications using multi-class Adaboost extreme learning machine

NASA Astrophysics Data System (ADS)

Gao, Lin; Cheng, Wei; Zhang, Jinhua; Wang, Jue

2016-08-01

Brain-computer interface (BCI) systems provide an alternative communication and control approach for people with limited motor function. Therefore, the feature extraction and classification approach should differentiate the relative unusual state of motion intention from a common resting state. In this paper, we sought a novel approach for multi-class classification in BCI applications. We collected electroencephalographic (EEG) signals registered by electrodes placed over the scalp during left hand motor imagery, right hand motor imagery, and resting state for ten healthy human subjects. We proposed using the Kolmogorov complexity (Kc) for feature extraction and a multi-class Adaboost classifier with extreme learning machine as base classifier for classification, in order to classify the three-class EEG samples. An average classification accuracy of 79.5% was obtained for ten subjects, which greatly outperformed commonly used approaches. Thus, it is concluded that the proposed method could improve the performance for classification of motor imagery tasks for multi-class samples. It could be applied in further studies to generate the control commands to initiate the movement of a robotic exoskeleton or orthosis, which finally facilitates the rehabilitation of disabled people.

D Surface Generation from Aerial Thermal Imagery

NASA Astrophysics Data System (ADS)

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.

Disorder-specific emotional imagery for differential and quantitative assessment of agoraphobia.

PubMed

Engel, Kirsten-Rita; Bandelow, Borwin; Neumann, Charlott; Obst, Katrin; Wedekind, Dirk

2012-01-01

Visual emotional stimulation is supposed to elicit psycho-vegetative reactions, which are similar to as the ones elicited by exposure to actual experience. Visual stimulation paradigms have been widely used in studies on agoraphobia with and without panic disorder. However, the applied imagery has hardly ever been disorder- and subject- specific. 51 patients with an ICD-10 and DSM-IV diagnosis of agoraphobia with or without panic disorder (PDA) and matching healthy controls have been examined. Subjects were confronted with 146 picture showing characteristic agoraphobic situations (high places, narrow places, crowds, public transport facilities, or wide places) or pictures associated with acute physical emergency (panic) situations, which had been pre-selected by anxiety experts. Participants were asked to rate emotional arousal induced by the respective images on the Self- Assessment Manikin scale (SAM). Data on PDA severity (PAS) depressive symptoms (MADRS) and sociodemographic data were recorded. Saliva cortisol levels were measured before and after exposure in a second test applying the individually mostly feared stimuli combined with emotionally neutral pictures for every single patient. 117 of the PDA-specific images were rated significantly more fear-eliciting by patients than by healthy individuals. Sub-categorization into agoraphobia clusters showed differential effects of clusters with regard to gender distribution, severity of PDA and cortisol secretion during exposure. In this study disorder specific and individual characteristics of agoraphobia were assessed for use in future trials applying emotional imagery. It could be used for the differential assessment of PDA and associated neurobiological and psychological phenomena and in neuroimaging paradigms.

Earthquake Damage Assessment Using Very High Resolution Satelliteimagery

NASA Astrophysics Data System (ADS)

Chiroiu, L.; André, G.; Bahoken, F.; Guillande, R.

Various studies using satellite imagery were applied in the last years in order to assess natural hazard damages, most of them analyzing the case of floods, hurricanes or landslides. For the case of earthquakes, the medium or small spatial resolution data available in the recent past did not allow a reliable identification of damages, due to the size of the elements (e.g. buildings or other structures), too small compared with the pixel size. The recent progresses of remote sensing in terms of spatial resolution and data processing makes possible a reliable damage detection to the elements at risk. Remote sensing techniques applied to IKONOS (1 meter resolution) and IRS (5 meters resolution) imagery were used in order to evaluate seismic vulnerability and post earthquake damages. A fast estimation of losses was performed using a multidisciplinary approach based on earthquake engineering and geospatial analysis. The results, integrated into a GIS database, could be transferred via satellite networks to the rescue teams deployed on the affected zone, in order to better coordinate the emergency operations. The methodology was applied to the city of Bhuj and Anjar after the 2001 Gujarat (India) Earthquake.

Geological applications of LANDSAT-1 imagery to the Great Salt Lake area

NASA Technical Reports Server (NTRS)

Anderson, A. T.; Smith, A. F.

1975-01-01

The ERTS program has been designed as a research and development tool to demonstrate that remote sensing from orbital altitudes is a feasible and practical approach to efficient management of earth resources. From this synoptic view and repetitive coverage provided by ERTS imagery of the Great Salt Lake area, large geological and structural features, trends, and patterns have been identified and mapped. A comparative analysis of lineaments observed in September and December data was conducted, existing mineral locations were plotted, and areas considered prospective for mineralization based on apparent structure-mineralization relationships were defined. The additional information obtained using ERTS data provides an added source of information to aid in the development of more effective mineral exploration programs.

Mola Interpretations: Elementary

ERIC Educational Resources Information Center

Guidetti, Mary D.

2004-01-01

In this article, the author describes how she introduced the mola designs of the Kuna people of the San Blas Islands to her fifth grade class. The students became excited by the tropical imagery; the wildlife, intertwined with the flowering plant life and the ocean, in colorful and black and-white patterns, because it brought forth such…

Marked Difference

ERIC Educational Resources Information Center

Lampela, Laurel

2008-01-01

Helen Cozza is a contemporary artist living in New Mexico who began working as a painter and moved into printmaking. Prevalent in her work is the use of the grid and the patterns created by weaving. The imagery is reminiscent of the environmental deterioration that Cozza observed in Buffalo and Cleveland where she lived for many years. Cozza knew…

Landscape pattern metrics and regional assessment

Treesearch

Robert V. O' Neill; Kurt H. Riitters; J.D. Wickham; Bruce K. Jones

1999-01-01

The combination of remote imagery data, geographic information systems software, and landscape ecology theory provides a unique basis for monitoring and assessing large-scale ecological systems. The unique feature of the work has been the need to develop interpret quantitative measures of spatial patter-the landscape indices. This article reviews what is known about...

Exploring Classroom Interaction with Dynamic Social Network Analysis

ERIC Educational Resources Information Center

Bokhove, Christian

2018-01-01

This article reports on an exploratory project in which technology and dynamic social network analysis (SNA) are used for modelling classroom interaction. SNA focuses on the links between social actors, draws on graphic imagery to reveal and display the patterning of those links, and develops mathematical and computational models to describe and…

Analysis of ERTS-1 imagery and its application to evaluation of Wyoming's natural resources

NASA Technical Reports Server (NTRS)

Marrs, R. W.

1973-01-01

The author has identified the following significant results. A summary of the significant results of the studies completed during the July-August, 1973 period includes: (1) ERTS-1 image brightness contrasts can be related to important contrasts in rangeland and forest vegetation communities of the Laramie Basin. (2) Stereoscopic viewing is essential for correct structural interpretation in outcrop patterns in some areas. (3) Complex fracture patterns which may have exerted a controlling influence on intrusive activity in the Absaroka Mountains can be mapped from ERTS. (4) Volcanic lithologies of the Yellowstone region are often differentiated on the basis of their textures, and cannot be successfully mapped by photogeologic interpretation of ERTS-1 imagery. Ground spectral readings confirm a general lack of contrast between these lithologies in the four ERTS-1 MSS bands. (5) Major dune fields can be recognized and defined from ERTS-1 image interpretations and recognition of differences in stabilizing plant communities (some of which may be mappable from ERTS-1) yields information about migration history of the dune fields.

Optimal design of a bank of spatio-temporal filters for EEG signal classification.

PubMed

Higashi, Hiroshi; Tanaka, Toshihisa

2011-01-01

The spatial weights for electrodes called common spatial pattern (CSP) are known to be effective in EEG signal classification for motor imagery based brain computer interfaces (MI-BCI). To achieve accurate classification in CSP, the frequency filter should be properly designed. To this end, several methods for designing the filter have been proposed. However, the existing methods cannot consider plural brain activities described with different frequency bands and different spatial patterns such as activities of mu and beta rhythms. In order to efficiently extract these brain activities, we propose a method to design plural filters and spatial weights which extract desired brain activity. The proposed method designs finite impulse response (FIR) filters and the associated spatial weights by optimization of an objective function which is a natural extension of CSP. Moreover, we show by a classification experiment that the bank of FIR filters which are designed by introducing an orthogonality into the objective function can extract good discriminative features. Moreover, the experiment result suggests that the proposed method can automatically detect and extract brain activities related to motor imagery.

Application of an optimization algorithm to satellite ocean color imagery: A case study in Southwest Florida coastal waters

NASA Astrophysics Data System (ADS)

Hu, Chuanmin; Lee, Zhongping; Muller-Karger, Frank E.; Carder, Kendall L.

2003-05-01

A spectra-matching optimization algorithm, designed for hyperspectral sensors, has been implemented to process SeaWiFS-derived multi-spectral water-leaving radiance data. The algorithm has been tested over Southwest Florida coastal waters. The total spectral absorption and backscattering coefficients can be well partitioned with the inversion algorithm, resulting in RMS errors generally less than 5% in the modeled spectra. For extremely turbid waters that come from either river runoff or sediment resuspension, the RMS error is in the range of 5-15%. The bio-optical parameters derived in this optically complex environment agree well with those obtained in situ. Further, the ability to separate backscattering (a proxy for turbidity) from the satellite signal makes it possible to trace water movement patterns, as indicated by the total absorption imagery. The derived patterns agree with those from concurrent surface drifters. For waters where CDOM overwhelmingly dominates the optical signal, however, the procedure tends to regard CDOM as the sole source of absorption, implying the need for better atmospheric correction and for adjustment of some model coefficients for this particular region.

Discriminative spatial-frequency-temporal feature extraction and classification of motor imagery EEG: An sparse regression and Weighted Naïve Bayesian Classifier-based approach.

PubMed

Miao, Minmin; Zeng, Hong; Wang, Aimin; Zhao, Changsen; Liu, Feixiang

2017-02-15

Common spatial pattern (CSP) is most widely used in motor imagery based brain-computer interface (BCI) systems. In conventional CSP algorithm, pairs of the eigenvectors corresponding to both extreme eigenvalues are selected to construct the optimal spatial filter. In addition, an appropriate selection of subject-specific time segments and frequency bands plays an important role in its successful application. This study proposes to optimize spatial-frequency-temporal patterns for discriminative feature extraction. Spatial optimization is implemented by channel selection and finding discriminative spatial filters adaptively on each time-frequency segment. A novel Discernibility of Feature Sets (DFS) criteria is designed for spatial filter optimization. Besides, discriminative features located in multiple time-frequency segments are selected automatically by the proposed sparse time-frequency segment common spatial pattern (STFSCSP) method which exploits sparse regression for significant features selection. Finally, a weight determined by the sparse coefficient is assigned for each selected CSP feature and we propose a Weighted Naïve Bayesian Classifier (WNBC) for classification. Experimental results on two public EEG datasets demonstrate that optimizing spatial-frequency-temporal patterns in a data-driven manner for discriminative feature extraction greatly improves the classification performance. The proposed method gives significantly better classification accuracies in comparison with several competing methods in the literature. The proposed approach is a promising candidate for future BCI systems. Copyright © 2016 Elsevier B.V. All rights reserved.

Je pense donc je fais: transcranial direct current stimulation modulates brain oscillations associated with motor imagery and movement observation.

PubMed

Lapenta, Olivia M; Minati, Ludovico; Fregni, Felipe; Boggio, Paulo S

2013-01-01

Motor system neural networks are activated during movement imagery, observation and execution, with a neural signature characterized by suppression of the Mu rhythm. In order to investigate the origin of this neurophysiological marker, we tested whether transcranial direct current stimulation (tDCS) modifies Mu rhythm oscillations during tasks involving observation and imagery of biological and non-biological movements. We applied tDCS (anodal, cathodal, and sham) in 21 male participants (mean age 23.8 ± 3.06), over the left M1 with a current of 2 mA for 20 min. Following this, we recorded the EEG at C3, C4, and Cz and surrounding C3 and C4 electrodes. Analyses of C3 and C4 showed significant effects for biological vs. non-biological movement (p = 0.005), and differential hemisphere effects according to the type of stimulation (p = 0.04) and type of movement (p = 0.02). Analyses of surrounding electrodes revealed significant interaction effects considering type of stimulation and imagery or observation of biological or non-biological movement (p = 0.03). The main findings of this study were (1) Mu desynchronization during biological movement of the hand region in the contralateral hemisphere after sham tDCS; (2) polarity-dependent modulation effects of tDCS on the Mu rhythm, i.e., anodal tDCS led to Mu synchronization while cathodal tDCS led to Mu desynchronization during movement observation and imagery (3) specific focal and opposite inter-hemispheric effects, i.e., contrary effects for the surrounding electrodes during imagery condition and also for inter-hemispheric electrodes (C3 vs. C4). These findings provide insights into the cortical oscillations during movement observation and imagery. Furthermore, it shows that tDCS can be highly focal when guided by a behavioral task.

Hyperspectral Vehicle BRDF Learning: An Exploration of Vehicle Reflectance Variation and Optimal Measures of Spectral Similarity for Vehicle Reacquisition and Tracking Algorithms

NASA Astrophysics Data System (ADS)

Svejkosky, Joseph

The spectral signatures of vehicles in hyperspectral imagery exhibit temporal variations due to the preponderance of surfaces with material properties that display non-Lambertian bi-directional reflectance distribution functions (BRDFs). These temporal variations are caused by changing illumination conditions, changing sun-target-sensor geometry, changing road surface properties, and changing vehicle orientations. To quantify these variations and determine their relative importance in a sub-pixel vehicle reacquisition and tracking scenario, a hyperspectral vehicle BRDF sampling experiment was conducted in which four vehicles were rotated at different orientations and imaged over a six-hour period. The hyperspectral imagery was calibrated using novel in-scene methods and converted to reflectance imagery. The resulting BRDF sampled time-series imagery showed a strong vehicle level BRDF dependence on vehicle shape in off-nadir imaging scenarios and a strong dependence on vehicle color in simulated nadir imaging scenarios. The imagery also exhibited spectral features characteristic of sampling the BRDF of non-Lambertian targets, which were subsequently verified with simulations. In addition, the imagery demonstrated that the illumination contribution from vehicle adjacent horizontal surfaces significantly altered the shape and magnitude of the vehicle reflectance spectrum. The results of the BRDF sampling experiment illustrate the need for a target vehicle BRDF model and detection scheme that incorporates non-Lambertian BRDFs. A new detection algorithm called Eigenvector Loading Regression (ELR) is proposed that learns a hyperspectral vehicle BRDF from a series of BRDF measurements using regression in a lower dimensional space and then applies the learned BRDF to make test spectrum predictions. In cases of non-Lambertian vehicle BRDF, this detection methodology performs favorably when compared to subspace detections algorithms and graph-based detection algorithms that do not account for the target BRDF. The algorithms are compared using a test environment in which observed spectral reflectance signatures from the BRDF sampling experiment are implanted into aerial hyperspectral imagery that contain large quantities of vehicles.

From One Pixel to One Earth: Building a Living Atlas in the Cloud to Analyze and Monitor Global Patterns

NASA Astrophysics Data System (ADS)

Moody, D.; Brumby, S. P.; Chartrand, R.; Franco, E.; Keisler, R.; Kelton, T.; Kontgis, C.; Mathis, M.; Raleigh, D.; Rudelis, X.; Skillman, S.; Warren, M. S.; Longbotham, N.

2016-12-01

The recent computing performance revolution has driven improvements in sensor, communication, and storage technology. Historical, multi-decadal remote sensing datasets at the petabyte scale are now available in commercial clouds, with new satellite constellations generating petabytes per year of high-resolution imagery with daily global coverage. Cloud computing and storage, combined with recent advances in machine learning and open software, are enabling understanding of the world at an unprecedented scale and detail. We have assembled all available satellite imagery from the USGS Landsat, NASA MODIS, and ESA Sentinel programs, as well as commercial PlanetScope and RapidEye imagery, and have analyzed over 2.8 quadrillion multispectral pixels. We leveraged the commercial cloud to generate a tiled, spatio-temporal mosaic of the Earth for fast iteration and development of new algorithms combining analysis techniques from remote sensing, machine learning, and scalable compute infrastructure. Our data platform enables processing at petabytes per day rates using multi-source data to produce calibrated, georeferenced imagery stacks at desired points in time and space that can be used for pixel level or global scale analysis. We demonstrate our data platform capability by using the European Space Agency's (ESA) published 2006 and 2009 GlobCover 20+ category label maps to train and test a Land Cover Land Use (LCLU) classifier, and generate current self-consistent LCLU maps in Brazil. We train a standard classifier on 2006 GlobCover categories using temporal imagery stacks, and we validate our results on co-registered 2009 Globcover LCLU maps and 2009 imagery. We then extend the derived LCLU model to current imagery stacks to generate an updated, in-season label map. Changes in LCLU labels can now be seamlessly monitored for a given location across the years in order to track, for example, cropland expansion, forest growth, and urban developments. An example of change monitoring is illustrated in the included figure showing rainfed cropland change in the Mato Grosso region of Brazil between 2006 and 2009.

Synergistic Use of WorldView-2 Imagery and Airborne LiDAR Data for Urban Land Cover Classification

NASA Astrophysics Data System (ADS)

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

2017-02-01

There are lots of challenges for deriving urban land cover types for high resolution optical imagery because of spectral similarity of different objects, mixed pixels, shadows of buildings and large tree crowns. In order to reduce these uncertainties, recently, it’s a trend of the classification of urban land cover from multi-source sensors in the field of urban remote sensing. In this study, a hierarchical support vector machine (SVM) classification method was applied to the urban land cover mapping, using the WorldView-2 imagery and airborne Light Detection and Ranging (LiDAR) data. The results showed that: (1) The overall accuracy (OA) and overall kappa (OK) were 72.92% and 0.66 for WorldView-2 imagery alone; while the OA and OK were improved up to 89.44% and 0.87 for the synergistic use of the two types of data source. (2) Buildings and road/parking lots extracted from fused data were more precision and well-shaped. The two classes from fused data were optimally classified with higher producer’s accuracy and user’s accuracy than WorldView-2 imagery alone. The trees were also easily separated from the grasslands when the airborne LiDAR data was added. (3) The fused data could reduce the phenomenon of different spectral character of the complex and detailed objects. It was also helpful to address the problem of shadows from the high-rise buildings. The results from this study indicate that the synergistic use of high resolution optical imagery and airborne LiDAR data can be an efficient approach to improving the classification of urban land cover.

Muscular responses appear to be associated with existence of kinesthetic perception during combination of tendon co-vibration and motor imagery.

PubMed

Shibata, Eriko; Kaneko, Fuminari; Katayose, Masaki

2017-11-01

The afferent inputs from peripheral sensory receptors and efferent signals from the central nervous system that underlie intentional movement can contribute to kinesthetic perception. Previous studies have revealed that tendon vibration to wrist muscles elicits an excitatory response-known as the antagonist vibratory response-in muscles antagonistic to the vibrated muscles. Therefore, the present study aimed to further investigate the effect of tendon vibration combined with motor imagery on kinesthetic perception and muscular activation. Two vibrators were applied to the tendons of the left flexor carpi radialis and extensor carpi radialis. When the vibration frequency was the same between flexors and extensors, no participant perceived movement and no muscle activity was induced. When participants imagined flexing their wrists during tendon vibration, the velocity of perceptual flexion movement increased. Furthermore, muscle activity of the flexor increased only during motor imagery. These results demonstrate that kinesthetic perception can be induced during the combination of motor imagery and co-vibration, even with no experience of kinesthetic perception from an afferent input with co-vibration at the same frequency. Although motor responses were observed during combined co-vibration and motor imagery, no such motor responses were recorded during either co-vibration alone or motor imagery alone, suggesting that muscular responses during the combined condition are associated with kinesthetic perception. Thus, the present findings indicate that kinesthetic perception is influenced by the interaction between afferent input from muscle spindles and the efferent signals that underlie intentional movement. We propose that the physiological behavior resulting from kinesthetic perception affects the process of modifying agonist muscle activity, which will be investigated in a future study.

Application of Thermal Infrared Multiband Scanner (TIMS) data to mapping of Plutonic and stratified rock and assemblages in accreted terrains of the Northern Sierra, California

NASA Technical Reports Server (NTRS)

Taranik, James V.; Davis, David; Borengasser, Marcus

1986-01-01

The Thermal Infrared Multispectral Scanner (TIMS) data were acquired over the Donner Pass area in California on September 12, 1985. The higher peaks in the area approach 9,200 feet in elevation, while the canyon of the north fork of the American River is only 3000 feet in elevation. The vegetation is dominated by conifers, although manzanita and other shrubs are present in areas where soils have developed. The data contain noise patterns which cut across scan lines diagonally. The TIMS data were analyzed using both photointerpretative and digital processing techniques. Preliminary image interpretation and field analysis confirmed that TIMS image data displays the chert units and silicic volcanics as bright red. The imagery appears to display zoning in the batholithic and hypabyssal intrusive rocks, although this was not field checked at this time. Rocks which appear to be more dioritic in composition appear purple on the imagery, while rocks more granitic in composition appear shades of red and pink. Areas that have more than 40% vegetative cover appear green on the imagery.