Effects of the Forecasting Methods, Precipitation Character, and Satellite Resolution on the Predictability of Short-Term Quantitative Precipitation Nowcasting (QPN from a Geostationary Satellite.

Directory of Open Access Journals (Sweden)

Yu Liu

Full Text Available The prediction of the short-term quantitative precipitation nowcasting (QPN from consecutive gestational satellite images has important implications for hydro-meteorological modeling and forecasting. However, the systematic analysis of the predictability of QPN is limited. The objective of this study is to evaluate effects of the forecasting model, precipitation character, and satellite resolution on the predictability of QPN using images of a Chinese geostationary meteorological satellite Fengyun-2F (FY-2F which covered all intensive observation since its launch despite of only a total of approximately 10 days. In the first step, three methods were compared to evaluate the performance of the QPN methods: a pixel-based QPN using the maximum correlation method (PMC; the Horn-Schunck optical-flow scheme (PHS; and the Pyramid Lucas-Kanade Optical Flow method (PPLK, which is newly proposed here. Subsequently, the effect of the precipitation systems was indicated by 2338 imageries of 8 precipitation periods. Then, the resolution dependence was demonstrated by analyzing the QPN with six spatial resolutions (0.1atial, 0.3a, 0.4atial rand 0.6. The results show that the PPLK improves the predictability of QPN with better performance than the other comparison methods. The predictability of the QPN is significantly determined by the precipitation system, and a coarse spatial resolution of the satellite reduces the predictability of QPN.

Effects of the Forecasting Methods, Precipitation Character, and Satellite Resolution on the Predictability of Short-Term Quantitative Precipitation Nowcasting (QPN) from a Geostationary Satellite.

Science.gov (United States)

Liu, Yu; Xi, Du-Gang; Li, Zhao-Liang; Ji, Wei

2015-01-01

The prediction of the short-term quantitative precipitation nowcasting (QPN) from consecutive gestational satellite images has important implications for hydro-meteorological modeling and forecasting. However, the systematic analysis of the predictability of QPN is limited. The objective of this study is to evaluate effects of the forecasting model, precipitation character, and satellite resolution on the predictability of QPN using images of a Chinese geostationary meteorological satellite Fengyun-2F (FY-2F) which covered all intensive observation since its launch despite of only a total of approximately 10 days. In the first step, three methods were compared to evaluate the performance of the QPN methods: a pixel-based QPN using the maximum correlation method (PMC); the Horn-Schunck optical-flow scheme (PHS); and the Pyramid Lucas-Kanade Optical Flow method (PPLK), which is newly proposed here. Subsequently, the effect of the precipitation systems was indicated by 2338 imageries of 8 precipitation periods. Then, the resolution dependence was demonstrated by analyzing the QPN with six spatial resolutions (0.1atial, 0.3a, 0.4atial rand 0.6). The results show that the PPLK improves the predictability of QPN with better performance than the other comparison methods. The predictability of the QPN is significantly determined by the precipitation system, and a coarse spatial resolution of the satellite reduces the predictability of QPN.

THERMAL AND VISIBLE SATELLITE IMAGE FUSION USING WAVELET IN REMOTE SENSING AND SATELLITE IMAGE PROCESSING

Directory of Open Access Journals (Sweden)

A. H. Ahrari

2017-09-01

Full Text Available Multimodal remote sensing approach is based on merging different data in different portions of electromagnetic radiation that improves the accuracy in satellite image processing and interpretations. Remote Sensing Visible and thermal infrared bands independently contain valuable spatial and spectral information. Visible bands make enough information spatially and thermal makes more different radiometric and spectral information than visible. However low spatial resolution is the most important limitation in thermal infrared bands. Using satellite image fusion, it is possible to merge them as a single thermal image that contains high spectral and spatial information at the same time. The aim of this study is a performance assessment of thermal and visible image fusion quantitatively and qualitatively with wavelet transform and different filters. In this research, wavelet algorithm (Haar and different decomposition filters (mean.linear,ma,min and rand for thermal and panchromatic bands of Landast8 Satellite were applied as shortwave and longwave fusion method . Finally, quality assessment has been done with quantitative and qualitative approaches. Quantitative parameters such as Entropy, Standard Deviation, Cross Correlation, Q Factor and Mutual Information were used. For thermal and visible image fusion accuracy assessment, all parameters (quantitative and qualitative must be analysed with respect to each other. Among all relevant statistical factors, correlation has the most meaningful result and similarity to the qualitative assessment. Results showed that mean and linear filters make better fused images against the other filters in Haar algorithm. Linear and mean filters have same performance and there is not any difference between their qualitative and quantitative results.

Discovering significant evolution patterns from satellite image time series.

Science.gov (United States)

Petitjean, François; Masseglia, Florent; Gançarski, Pierre; Forestier, Germain

2011-12-01

Satellite Image Time Series (SITS) provide us with precious information on land cover evolution. By studying these series of images we can both understand the changes of specific areas and discover global phenomena that spread over larger areas. Changes that can occur throughout the sensing time can spread over very long periods and may have different start time and end time depending on the location, which complicates the mining and the analysis of series of images. This work focuses on frequent sequential pattern mining (FSPM) methods, since this family of methods fits the above-mentioned issues. This family of methods consists of finding the most frequent evolution behaviors, and is actually able to extract long-term changes as well as short term ones, whenever the change may start and end. However, applying FSPM methods to SITS implies confronting two main challenges, related to the characteristics of SITS and the domain's constraints. First, satellite images associate multiple measures with a single pixel (the radiometric levels of different wavelengths corresponding to infra-red, red, etc.), which makes the search space multi-dimensional and thus requires specific mining algorithms. Furthermore, the non evolving regions, which are the vast majority and overwhelm the evolving ones, challenge the discovery of these patterns. We propose a SITS mining framework that enables discovery of these patterns despite these constraints and characteristics. Our proposal is inspired from FSPM and provides a relevant visualization principle. Experiments carried out on 35 images sensed over 20 years show the proposed approach makes it possible to extract relevant evolution behaviors.

New and Emerging Satellite Imaging Capabilities in Support of Safeguards

International Nuclear Information System (INIS)

Johnson, M.; Paquette, J.P.; Spyropoulos, N.; Rainville, L.; Schichor, P.; Hong, M.

2015-01-01

This abstract is focused on new and emerging commercial satellite imagery (CSI) capabilities. For more than a decade, experienced imagery analysts have been exploiting and analyzing CSI in support of the Department of Safeguards. As the remote sensing industry continues to evolve, additional CSI imagery types are becoming available that could enhance our ability to evaluate and verify States' declarations and to investigate the possible presence of undeclared activities. A newly available and promising CSI capability that may have a Safeguards application is Full Motion Video (FMV) imagery collection from satellites. For quite some time, FMV imagery has been collected from airborne platforms, but now FMV sensors are being deployed into space. Like its airborne counterpart, satellite FMV imagery could provide analysts with a great deal of information, including insight into the operational status of facilities and patterns of activity. From a Safeguards perspective, FMV imagery could help the Agency in the evaluation and verification of States' declared facilities and activities. There are advantages of FMV imaging capabilities that cannot be duplicated with other CSI capabilities, including the ability to loiter over areas of interest and the potential to revisit sites multiple times per day. Additional sensor capabilities applicable to the Safeguards mission include, but are not limited to, the following sensors: · Thermal Infrared imaging sensors will be launched in late 2014 to monitor operational status, e.g., heat from a transformer. · High resolution ShortWave Infrared sensors able to characterize materials that could support verification of Additional Protocol declarations under Article 2.a(v). · Unmanned Aerial Vehicles with individual sensors or specific sensor combinations. The Safeguards Symposium provides a forum to showcase and demonstrate safeguards applications for these emerging satellite imaging capabilities. (author)

IoSiS: a radar system for imaging of satellites in space

Science.gov (United States)

Jirousek, M.; Anger, S.; Dill, S.; Schreiber, E.; Peichl, M.

2017-05-01

Space debris nowadays is one of the main threats for satellite systems especially in low earth orbit (LEO). More than 700,000 debris objects with potential to destroy or damage a satellite are estimated. The effects of an impact often are not identifiable directly from ground. High-resolution radar images are helpful in analyzing a possible damage. Therefor DLR is currently developing a radar system called IoSiS (Imaging of Satellites in Space), being based on an existing steering antenna structure and our multi-purpose high-performance radar system GigaRad for experimental investigations. GigaRad is a multi-channel system operating at X band and using a bandwidth of up to 4.4 GHz in the IoSiS configuration, providing fully separated transmit (TX) and receive (RX) channels, and separated antennas. For the observation of small satellites or space debris a highpower traveling-wave-tube amplifier (TWTA) is mounted close to the TX antenna feed. For the experimental phase IoSiS uses a 9 m TX and a 1 m RX antenna mounted on a common steerable positioner. High-resolution radar images are obtained by using Inverse Synthetic Aperture Radar (ISAR) techniques. The guided tracking of known objects during overpass allows here wide azimuth observation angles. Thus high azimuth resolution comparable to the range resolution can be achieved. This paper outlines technical main characteristics of the IoSiS radar system including the basic setup of the antenna, the radar instrument with the RF error correction, and the measurement strategy. Also a short description about a simulation tool for the whole instrument and expected images is shown.

Spectrally Consistent Satellite Image Fusion with Improved Image Priors

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg; Aanæs, Henrik; Jensen, Thomas B.S.

2006-01-01

Here an improvement to our previous framework for satellite image fusion is presented. A framework purely based on the sensor physics and on prior assumptions on the fused image. The contributions of this paper are two fold. Firstly, a method for ensuring 100% spectrally consistency is proposed......, even when more sophisticated image priors are applied. Secondly, a better image prior is introduced, via data-dependent image smoothing....

Northern Everglades, Florida, satellite image map

Science.gov (United States)

Thomas, Jean-Claude; Jones, John W.

2002-01-01

These satellite image maps are one product of the USGS Land Characteristics from Remote Sensing project, funded through the USGS Place-Based Studies Program with support from the Everglades National Park. The objective of this project is to develop and apply innovative remote sensing and geographic information system techniques to map the distribution of vegetation, vegetation characteristics, and related hydrologic variables through space and over time. The mapping and description of vegetation characteristics and their variations are necessary to accurately simulate surface hydrology and other surface processes in South Florida and to monitor land surface changes. As part of this research, data from many airborne and satellite imaging systems have been georeferenced and processed to facilitate data fusion and analysis. These image maps were created using image fusion techniques developed as part of this project.

ANALYSIS OF THE EFFECTS OF IMAGE QUALITY ON DIGITAL MAP GENERATION FROM SATELLITE IMAGES

Directory of Open Access Journals (Sweden)

H. Kim

2012-07-01

Full Text Available High resolution satellite images are widely used to produce and update a digital map since they became widely available. It is well known that the accuracy of digital map produced from satellite images is decided largely by the accuracy of geometric modelling. However digital maps are made by a series of photogrammetric workflow. Therefore the accuracy of digital maps are also affected by the quality of satellite images, such as image interpretability. For satellite images, parameters such as Modulation Transfer Function(MTF, Signal to Noise Ratio(SNR and Ground Sampling Distance(GSD are used to present images quality. Our previous research stressed that such quality parameters may not represent the quality of image products such as digital maps and that parameters for image interpretability such as Ground Resolved Distance(GRD and National Imagery Interpretability Rating Scale(NIIRS need to be considered. In this study, we analyzed the effects of the image quality on accuracy of digital maps produced by satellite images. QuickBird, IKONOS and KOMPSAT-2 imagery were used to analyze as they have similar GSDs. We measured various image quality parameters mentioned above from these images. Then we produced digital maps from the images using a digital photogrammetric workstation. We analyzed the accuracy of the digital maps in terms of their location accuracy and their level of details. Then we compared the correlation between various image quality parameters and the accuracy of digital maps. The results of this study showed that GRD and NIIRS were more critical for map production then GSD, MTF or SNR.

Short-Term Depression, Temporal Summation, and Onset Inhibition Shape Interval Tuning in Midbrain Neurons

Science.gov (United States)

Baker, Christa A.

2014-01-01

A variety of synaptic mechanisms can contribute to single-neuron selectivity for temporal intervals in sensory stimuli. However, it remains unknown how these mechanisms interact to establish single-neuron sensitivity to temporal patterns of sensory stimulation in vivo. Here we address this question in a circuit that allows us to control the precise temporal patterns of synaptic input to interval-tuned neurons in behaviorally relevant ways. We obtained in vivo intracellular recordings under multiple levels of current clamp from midbrain neurons in the mormyrid weakly electric fish Brienomyrus brachyistius during stimulation with electrosensory pulse trains. To reveal the excitatory and inhibitory inputs onto interval-tuned neurons, we then estimated the synaptic conductances underlying responses. We found short-term depression in excitatory and inhibitory pathways onto all interval-tuned neurons. Short-interval selectivity was associated with excitation that depressed less than inhibition at short intervals, as well as temporally summating excitation. Long-interval selectivity was associated with long-lasting onset inhibition. We investigated tuning after separately nullifying the contributions of temporal summation and depression, and found the greatest diversity of interval selectivity among neurons when both mechanisms were at play. Furthermore, eliminating the effects of depression decreased sensitivity to directional changes in interval. These findings demonstrate that variation in depression and summation of excitation and inhibition helps to establish tuning to behaviorally relevant intervals in communication signals, and that depression contributes to neural coding of interval sequences. This work reveals for the first time how the interplay between short-term plasticity and temporal summation mediates the decoding of temporal sequences in awake, behaving animals. PMID:25339741

Using Deep Learning Model for Meteorological Satellite Cloud Image Prediction

Science.gov (United States)

Su, X.

2017-12-01

A satellite cloud image contains much weather information such as precipitation information. Short-time cloud movement forecast is important for precipitation forecast and is the primary means for typhoon monitoring. The traditional methods are mostly using the cloud feature matching and linear extrapolation to predict the cloud movement, which makes that the nonstationary process such as inversion and deformation during the movement of the cloud is basically not considered. It is still a hard task to predict cloud movement timely and correctly. As deep learning model could perform well in learning spatiotemporal features, to meet this challenge, we could regard cloud image prediction as a spatiotemporal sequence forecasting problem and introduce deep learning model to solve this problem. In this research, we use a variant of Gated-Recurrent-Unit(GRU) that has convolutional structures to deal with spatiotemporal features and build an end-to-end model to solve this forecast problem. In this model, both the input and output are spatiotemporal sequences. Compared to Convolutional LSTM(ConvLSTM) model, this model has lower amount of parameters. We imply this model on GOES satellite data and the model perform well.

Integers without Large Prime Factors in Short Intervals: Conditional ...

Indian Academy of Sciences (India)

... Public Lectures · Lecture Workshops · Refresher Courses · Symposia · Live Streaming. Home; Journals; Proceedings – Mathematical Sciences; Volume 120; Issue 5. Integers without Large Prime Factors in Short Intervals: Conditional Results. Goutam Pal Satadal Ganguly. Volume 120 Issue 5 November 2010 pp 515-524 ...

Medical image transmission via communication satellite: evaluation of ultrasonographic images.

Science.gov (United States)

Suzuki, H; Horikoshi, H; Shiba, H; Shimamoto, S

1996-01-01

As compared with terrestrial circuits, communication satellites possess superior characteristics such as wide area coverage, broadcasting functions, high capacity, and resistance to disasters. Utilizing the narrow band channel (64 kbps) of the stationary communication satellite JCSAT1 located at an altitude of 36,000 km above the equator, we investigated satelliterelayed dynamic medical images transmitted by video signals, using hepatic ultrasonography as a model. We conclude that the "variable playing speed transmission scheme" proposed by us is effective for the transmission of dynamic images in the narrow band channel. This promises to permit diverse utilization and applications for purposes such as the transmission of other types of ultrasonic images as well as remotely directed medical diagnosis and treatment.

The prevalence and significance of a short QT interval in 18,825 low-risk individuals including athletes.

Science.gov (United States)

Dhutia, Harshil; Malhotra, Aneil; Parpia, Sameer; Gabus, Vincent; Finocchiaro, Gherardo; Mellor, Greg; Merghani, Ahmed; Millar, Lynne; Narain, Rajay; Sheikh, Nabeel; Behr, Elijah R; Papadakis, Michael; Sharma, Sanjay

2016-01-01

The short QT syndrome is a cardiac channelopathy characterised by accelerated repolarisation which manifests as a short QT interval on the ECG. The definition of a short QT interval is debated, ranging from <390 to ≤320 ms, and its clinical significance in healthy young individuals is unknown. We assessed the prevalence and medium-term significance of an isolated short QT interval in a diverse young British population. Between 2005 and 2013, 18 825 apparently healthy people aged 14-35 years underwent cardiovascular evaluation with history, physical examination and ECG. QT intervals were measured by cardiologists using 4 recommended guidelines (Seattle 2013, Heart Rhythm Society 2013, European Society of Cardiology 2010 and American Heart Association 2009). The prevalence of a short QT interval was 0.1% (26 patients, ≤320 ms), 0.2% (44 patients, ≤330 ms), 7.9% (1478 patients, <380 ms), 15.8% (2973 patients, <390 ms). Male gender and Afro-Caribbean ethnicity had the strongest association with short QT intervals. Athletes had shorter QT intervals than non-athletes but athletic status did not predict short QT intervals. Individuals with short QT intervals ≤320 ms did not report syncope or a sinister family history, and during a follow-up period of 5.3±1.2 years, there were no deaths in this group. The prevalence of a short QT interval depends on the recommended cut-off value. Even at values ≤320 ms, there was an excellent medium-term prognosis among 14 people followed. We conclude that a definition of ≤320 ms is realistic to prevent overdiagnosis and excessive investigations. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Velocity estimation of an airplane through a single satellite image

Institute of Scientific and Technical Information of China (English)

Zhuxin Zhao; Gongjian Wen; Bingwei Hui; Deren Li

2012-01-01

The motion information of a moving target can be recorded in a single image by a push-broom satellite. A push-broom satellite image is composed of many image lines sensed at different time instants. A method to estimate the velocity of a flying airplane from a single image based on the imagery model of the linear push-broom sensor is proposed. Some key points on the high-resolution image of the plane are chosen to determine the velocity (speed and direction). The performance of the method is tested and verified by experiments using a WorldView-1 image.%The motion information of a moving target can be recorded in a single image by a push-broom satellite.A push-broom satellite image is composed of many image lines sensed at different time instants.A method to estimate the velocity of a flying airplane from a single image based on the imagery model of the linear push-broom sensor is proposed.Some key points on the high-resolution image of the plane are chosen to determine the velocity (speed and direction).The performance of the method is tested and verified by experiments using a WorldView-1 image.

Coseismic displacements from SAR image offsets between different satellite sensors: Application to the 2001 Bhuj (India) earthquake

KAUST Repository

Wang, Teng

2015-09-05

Synthetic aperture radar (SAR) image offset tracking is increasingly being used for measuring ground displacements, e.g., due to earthquakes and landslide movement. However, this technique has been applied only to images acquired by the same or identical satellites. Here we propose a novel approach for determining offsets between images acquired by different satellite sensors, extending the usability of existing SAR image archives. The offsets are measured between two multiimage reflectivity maps obtained from different SAR data sets, which provide significantly better results than with single preevent and postevent images. Application to the 2001 Mw7.6 Bhuj earthquake reveals, for the first time, its near-field deformation using multiple preearthquake ERS and postearthquake Envisat images. The rupture model estimated from these cross-sensor offsets and teleseismic waveforms shows a compact fault slip pattern with fairly short rise times (<3 s) and a large stress drop (20 MPa), explaining the intense shaking observed in the earthquake.

Using Fuzzy SOM Strategy for Satellite Image Retrieval and Information Mining

Directory of Open Access Journals (Sweden)

Yo-Ping Huang

2008-02-01

Full Text Available This paper proposes an efficient satellite image retrieval and knowledge discovery model. The strategy comprises two major parts. First, a computational algorithm is used for off-line satellite image feature extraction, image data representation and image retrieval. Low level features are automatically extracted from the segmented regions of satellite images. A self-organization feature map is used to construct a two-layer satellite image concept hierarchy. The events are stored in one layer and the corresponding feature vectors are categorized in the other layer. Second, a user friendly interface is provided that retrieves images of interest and mines useful information based on the events in the concept hierarchy. The proposed system is evaluated with prominent features such as typhoons or high-pressure masses.

South Florida Everglades: satellite image map

Science.gov (United States)

Jones, John W.; Thomas, Jean-Claude; Desmond, G.B.

2001-01-01

These satellite image maps are one product of the USGS Land Characteristics from Remote Sensing project, funded through the USGS Place-Based Studies Program (http://access.usgs.gov/) with support from the Everglades National Park (http://www.nps.gov/ever/). The objective of this project is to develop and apply innovative remote sensing and geographic information system techniques to map the distribution of vegetation, vegetation characteristics, and related hydrologic variables through space and over time. The mapping and description of vegetation characteristics and their variations are necessary to accurately simulate surface hydrology and other surface processes in South Florida and to monitor land surface changes. As part of this research, data from many airborne and satellite imaging systems have been georeferenced and processed to facilitate data fusion and analysis. These image maps were created using image fusion techniques developed as part of this project.

The best printing methods to print satellite images

Directory of Open Access Journals (Sweden)

G.A. Yousif

2011-12-01

In this paper different printing systems were used to print an image of SPOT-4 satellite, caver part of Sharm Elshekh area, Sinai, Egypt, on the same type of paper as much as possible, especially in the photography. This step is followed by measuring the experimental data, and analyzed colors to determine the best printing systems for satellite image printing data. The laser system is the more printing system where produce a wider range of color and highest densities of ink and access much color detail. Followed by the offset system which it recorded the best dot gain. Moreover, the study shows that it can use the advantages of each method according to the satellite image color and quantity to be produced.

[Incidence of long (short) PR interval in electrocardiogram among healthy people in Changsha and its clinical significance].

Science.gov (United States)

Liu, Liping; Lin, Ping; Xu, Yi; Wu, Lijia; Zou, Runmei; Xie, Zhenwu; Wang, Cheng

2016-04-01

To analyze the incidence of long (short) PR interval in electrocardiogram among healthy people in Changsha and the clinical significance.
 Twelve-lead body surface electrocardiogram was taken to measure the heart rates and PR intervals from 4 025 healthy individuals (age range from 6 min after birth to 83 years old) who performed physical examination from Jan, 1993 to Dec, 2012 in the Second Xiangya Hospital, Central South University. Statistics were analyzed by SPSS 16.0.
 The total incidence of short PR interval was 19.65% (791/4 025). The age group from birth to 13 years old had a higher incidence than the other age groups (χ2=432, PPR intervals was 3.58% (144/4 025). The 1 year-old group had the highest incidence (6.74%), which decreased with the increase of age. The lowest incidence of long PR intervals occurred in the age group from 14-17 years old, which gradually increased after 50 years old. There were no significant differences in long (short) PR intervals between the gender (P>0.05).
 The incidence of long (short) PR intervals varies in different age groups of healthy people. The incidences of long (short) PR intervals in children before 10 years old are higher than those in adults, especially the short PR intervals, as a result of the heart rate affected by childhood autonomic nervous function and the change in atrial volume with age. Adults have long (short) PR interval should be regularly followed-up to prevent cardiovascular events.

Entropy-Based Block Processing for Satellite Image Registration

Directory of Open Access Journals (Sweden)

Ikhyun Lee

2012-11-01

Full Text Available Image registration is an important task in many computer vision applications such as fusion systems, 3D shape recovery and earth observation. Particularly, registering satellite images is challenging and time-consuming due to limited resources and large image size. In such scenario, state-of-the-art image registration methods such as scale-invariant feature transform (SIFT may not be suitable due to high processing time. In this paper, we propose an algorithm based on block processing via entropy to register satellite images. The performance of the proposed method is evaluated using different real images. The comparative analysis shows that it not only reduces the processing time but also enhances the accuracy.

The best printing methods to print satellite images

OpenAIRE

G.A. Yousif; R.Sh. Mohamed

2011-01-01

Printing systems operate in general as a system of color its color scale is limited as compared with the system color satellite images. Satellite image is building from very small cell named pixel, which represents the picture element and the unity of color when the image is displayed on the screen, this unit becomes lesser in size and called screen point. This unit posseses different size and shape from the method of printing to another, depending on the output resolution, tools and material...

ASTER 2002-2003 Kansas Satellite Image Database (KSID)

Data.gov (United States)

Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2002-2003 consists of image data gathered by three sensors. The first image data are terrain-corrected, precision...

MODIS 2002-2003 Kansas Satellite Image Database (KSID)

Data.gov (United States)

Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2002-2003 consists of image data gathered by three sensors. The first image data are terrain-corrected, precision...

Reduced short interval cortical inhibition correlates with atomoxetine response in children with attention-deficit hyperactivity disorder (ADHD).

Science.gov (United States)

Chen, Tina H; Wu, Steve W; Welge, Jeffrey A; Dixon, Stephan G; Shahana, Nasrin; Huddleston, David A; Sarvis, Adam R; Sallee, Floyd R; Gilbert, Donald L

2014-12-01

Clinical trials in children with attention-deficit hyperactivity disorder (ADHD) show variability in behavioral responses to the selective norepinephrine reuptake inhibitor atomoxetine. The objective of this study was to determine whether transcranial magnetic stimulation-evoked short interval cortical inhibition might be a biomarker predicting, or correlating with, clinical atomoxetine response. At baseline and after 4 weeks of atomoxetine treatment in 7- to 12-year-old children with ADHD, transcranial magnetic stimulation short interval cortical inhibition was measured, blinded to clinical improvement. Primary analysis was by multivariate analysis of covariance. Baseline short interval cortical inhibition did not predict clinical responses. However, paradoxically, after 4 weeks of atomoxetine, mean short interval cortical inhibition was reduced 31.9% in responders and increased 6.1% in nonresponders (analysis of covariance t 41 = 2.88; P = .0063). Percentage reductions in short interval cortical inhibition correlated with reductions in the ADHD Rating Scale (r = 0.50; P = .0005). In children ages 7 to 12 years with ADHD treated with atomoxetine, improvements in clinical symptoms are correlated with reductions in motor cortex short interval cortical inhibition. © The Author(s) 2014.

Dual-source CT coronary imaging in heart transplant recipients: image quality and optimal reconstruction interval

International Nuclear Information System (INIS)

Bastarrika, Gorka; Arraiza, Maria; Pueyo, Jesus C.; Cecco, Carlo N. de; Ubilla, Matias; Mastrobuoni, Stefano; Rabago, Gregorio

2008-01-01

The image quality and optimal reconstruction interval for coronary arteries in heart transplant recipients undergoing non-invasive dual-source computed tomography (DSCT) coronary angiography was evaluated. Twenty consecutive heart transplant recipients who underwent DSCT coronary angiography were included (19 male, one female; mean age 63.1±10.7 years). Data sets were reconstructed in 5% steps from 30% to 80% of the R-R interval. Two blinded independent observers assessed the image quality of each coronary segments using a five-point scale (from 0 = not evaluative to 4=excellent quality). A total of 289 coronary segments in 20 heart transplant recipients were evaluated. Mean heart rate during the scan was 89.1±10.4 bpm. At the best reconstruction interval, diagnostic image quality (score ≥2) was obtained in 93.4% of the coronary segments (270/289) with a mean image quality score of 3.04± 0.63. Systolic reconstruction intervals provided better image quality scores than diastolic reconstruction intervals (overall mean quality scores obtained with the systolic and diastolic reconstructions 3.03±1.06 and 2.73±1.11, respectively; P<0.001). Different systolic reconstruction intervals (35%, 40%, 45% of RR interval) did not yield to significant differences in image quality scores for the coronary segments (P=0.74). Reconstructions obtained at the systolic phase of the cardiac cycle allowed excellent diagnostic image quality coronary angiograms in heart transplant recipients undergoing DSCT coronary angiography. (orig.)

Classification of high resolution satellite images

OpenAIRE

Karlsson, Anders

2003-01-01

In this thesis the Support Vector Machine (SVM)is applied on classification of high resolution satellite images. Sveral different measures for classification, including texture mesasures, 1st order statistics, and simple contextual information were evaluated. Additionnally, the image was segmented, using an enhanced watershed method, in order to improve the classification accuracy.

An Image Matching Algorithm Integrating Global SRTM and Image Segmentation for Multi-Source Satellite Imagery

Directory of Open Access Journals (Sweden)

Xiao Ling

2016-08-01

Full Text Available This paper presents a novel image matching method for multi-source satellite images, which integrates global Shuttle Radar Topography Mission (SRTM data and image segmentation to achieve robust and numerous correspondences. This method first generates the epipolar lines as a geometric constraint assisted by global SRTM data, after which the seed points are selected and matched. To produce more reliable matching results, a region segmentation-based matching propagation is proposed in this paper, whereby the region segmentations are extracted by image segmentation and are considered to be a spatial constraint. Moreover, a similarity measure integrating Distance, Angle and Normalized Cross-Correlation (DANCC, which considers geometric similarity and radiometric similarity, is introduced to find the optimal correspondences. Experiments using typical satellite images acquired from Resources Satellite-3 (ZY-3, Mapping Satellite-1, SPOT-5 and Google Earth demonstrated that the proposed method is able to produce reliable and accurate matching results.

Smoothing of Fused Spectral Consistent Satellite Images with TV-based Edge Detection

DEFF Research Database (Denmark)

Sveinsson, Johannes; Aanæs, Henrik; Benediktsson, Jon Atli

2007-01-01

based on satellite data. Additionally, most conventional methods are loosely connected to the image forming physics of the satellite image, giving these methods an ad hoc feel. Vesteinsson et al. [1] proposed a method of fusion of satellite images that is based on the properties of imaging physics...... in a statistically meaningful way and was called spectral consistent panshapening (SCP). In this paper we improve this framework for satellite image fusion by introducing a better image prior, via data-dependent image smoothing. The dependency is obtained via total variation edge detection method.......Several widely used methods have been proposed for fusing high resolution panchromatic data and lower resolution multi-channel data. However, many of these methods fail to maintain the spectral consistency of the fused high resolution image, which is of high importance to many of the applications...

Evaluation of short-period rainfall estimates from Kalpana-1 satellite

Indian Academy of Sciences (India)

The INSAT Multispectral Rainfall Algorithm (IMSRA) technique for rainfall estimation, has recently been developed to meet the shortcomings of the Global Precipitation Index (GPI) technique of rainfall estimation from the data of geostationary satellites; especially for accurate short period rainfall estimates. This study ...

Satellite-generated radar images of the earth

International Nuclear Information System (INIS)

Schanda, E.

1980-01-01

The Synthetic Aperture Radar (SAR) on board of SEASAT was the first non-military satellite-borne radar producing high-resolution images of the earth. Several examples of European scenes are discussed to demonstrate the properties of presently available optically processes images. (orig.)

High efficient optical remote sensing images acquisition for nano-satellite: reconstruction algorithms

Science.gov (United States)

Liu, Yang; Li, Feng; Xin, Lei; Fu, Jie; Huang, Puming

2017-10-01

Large amount of data is one of the most obvious features in satellite based remote sensing systems, which is also a burden for data processing and transmission. The theory of compressive sensing(CS) has been proposed for almost a decade, and massive experiments show that CS has favorable performance in data compression and recovery, so we apply CS theory to remote sensing images acquisition. In CS, the construction of classical sensing matrix for all sparse signals has to satisfy the Restricted Isometry Property (RIP) strictly, which limits applying CS in practical in image compression. While for remote sensing images, we know some inherent characteristics such as non-negative, smoothness and etc.. Therefore, the goal of this paper is to present a novel measurement matrix that breaks RIP. The new sensing matrix consists of two parts: the standard Nyquist sampling matrix for thumbnails and the conventional CS sampling matrix. Since most of sun-synchronous based satellites fly around the earth 90 minutes and the revisit cycle is also short, lots of previously captured remote sensing images of the same place are available in advance. This drives us to reconstruct remote sensing images through a deep learning approach with those measurements from the new framework. Therefore, we propose a novel deep convolutional neural network (CNN) architecture which takes in undersampsing measurements as input and outputs an intermediate reconstruction image. It is well known that the training procedure to the network costs long time, luckily, the training step can be done only once, which makes the approach attractive for a host of sparse recovery problems.

Short-interval and long-interval intracortical inhibition of TMS-evoked EEG potentials.

Science.gov (United States)

Premoli, Isabella; Király, Julia; Müller-Dahlhaus, Florian; Zipser, Carl M; Rossini, Pierre; Zrenner, Christoph; Ziemann, Ulf; Belardinelli, Paolo

2018-03-15

Inhibition in the human motor cortex can be probed by means of paired-pulse transcranial magnetic stimulation (ppTMS) at interstimulus intervals of 2-3 ms (short-interval intracortical inhibition, SICI) or ∼100 ms (long-interval intracortical inhibition, LICI). Conventionally, SICI and LICI are recorded as motor evoked potential (MEP) inhibition in the hand muscle. Pharmacological experiments indicate that they are mediated by GABAA and GABAB receptors, respectively. SICI and LICI of TMS-evoked EEG potentials (TEPs) and their pharmacological properties have not been systematically studied. Here, we sought to examine SICI by ppTMS-evoked compared to single-pulse TMS-evoked TEPs, to investigate its pharmacological manipulation and to compare SICI with our previous results on LICI. PpTMS-EEG was applied to the left motor cortex in 16 healthy subjects in a randomized, double-blind placebo-controlled crossover design, testing the effects of a single oral dose 20 mg of diazepam, a positive modulator at the GABAA receptor, vs. 50 mg of the GABAB receptor agonist baclofen on SICI of TEPs. We found significant SICI of the N100 and P180 TEPs prior to drug intake. Diazepam reduced SICI of the N100 TEP, while baclofen enhanced it. Compared to our previous ppTMS-EEG results on LICI, the SICI effects on TEPs, including their drug modulation, were largely analogous. Findings suggest a similar interaction of paired-pulse effects on TEPs irrespective of the interstimulus interval. Therefore, SICI and LICI as measured with TEPs cannot be directly derived from SICI and LICI measured with MEPs, but may offer novel insight into paired-pulse responses recorded directly from the brain rather than muscle. Copyright © 2018 Elsevier Inc. All rights reserved.

Short-Term Wind Power Interval Forecasting Based on an EEMD-RT-RVM Model

Directory of Open Access Journals (Sweden)

Haixiang Zang

2016-01-01

Full Text Available Accurate short-term wind power forecasting is important for improving the security and economic success of power grids. Existing wind power forecasting methods are mostly types of deterministic point forecasting. Deterministic point forecasting is vulnerable to forecasting errors and cannot effectively deal with the random nature of wind power. In order to solve the above problems, we propose a short-term wind power interval forecasting model based on ensemble empirical mode decomposition (EEMD, runs test (RT, and relevance vector machine (RVM. First, in order to reduce the complexity of data, the original wind power sequence is decomposed into a plurality of intrinsic mode function (IMF components and residual (RES component by using EEMD. Next, we use the RT method to reconstruct the components and obtain three new components characterized by the fine-to-coarse order. Finally, we obtain the overall forecasting results (with preestablished confidence levels by superimposing the forecasting results of each new component. Our results show that, compared with existing methods, our proposed short-term interval forecasting method has less forecasting errors, narrower interval widths, and larger interval coverage percentages. Ultimately, our forecasting model is more suitable for engineering applications and other forecasting methods for new energy.

Model-based satellite image fusion

DEFF Research Database (Denmark)

Aanæs, Henrik; Sveinsson, J. R.; Nielsen, Allan Aasbjerg

2008-01-01

A method is proposed for pixel-level satellite image fusion derived directly from a model of the imaging sensor. By design, the proposed method is spectrally consistent. It is argued that the proposed method needs regularization, as is the case for any method for this problem. A framework for pixel...... neighborhood regularization is presented. This framework enables the formulation of the regularization in a way that corresponds well with our prior assumptions of the image data. The proposed method is validated and compared with other approaches on several data sets. Lastly, the intensity......-hue-saturation method is revisited in order to gain additional insight of what implications the spectral consistency has for an image fusion method....

Liver scanning in short interval autopsy material of cancer patients

International Nuclear Information System (INIS)

Appelqvist, P.; Salmo, M.; Kostiainen, S.

1980-01-01

The accuracy of liverscanning alkaline phosphatase and 5'-nucleotidase in the detection of the hepatic metastases was studied in short interval autopsy material of 243 cancer patients. The highest percentage of correct diagnosis was by 5'-nucleotidase, alkaline phosphatase was the second, and scanning third. The overall accuracy of liver scan was 68 per cent. It was the better the shorter the time interval between scanning and autopsy. The higher percentage of incorrect diagnoses of the scan was related to a larger number of false positives, the causes of which were to be verified only in half of the cases. (orig.) [de

Solar irradiance assessment in insular areas using Himawari-8 satellite images

Science.gov (United States)

Liandrat, O.; Cros, S.; Turpin, M.; Pineau, J. F.

2016-12-01

The high amount of surface solar irradiance (SSI) in the tropics is an advantage for a profitable PV production. It will allow many tropical islands to pursue their economic growth with a clean, affordable and locally produced energy. However, the local meteorological conditions induce a very high variability which is problematic for a safe and gainful injection into the power grid. This issue is even more critical in non-interconnected territories where network stability is an absolute necessity. Therefore, the injection of PV power is legally limited in some European oversea territories. In this context, intraday irradiance forecasting (several hours ahead) is particularly useful to mitigate the production variability by reducing the cost of power storage management. At this time scale, cloud cover evolves with a stochastic behaviour not properly represented in numerical weather prediction (NWP) models. Analysing cloud motion using images from geostationary meteorological satellites is a well-known alternative to forecasting SSI up to 6 hours ahead with a better accuracy than NWP models. In this study, we present and apply our satellite-based solar irradiance forecasting methods over two measurement sites located in the field of view of the satellite Himawari-8: Cocos (Keeling) Islands (Australia) and New Caledonia (France). In particular, we converted 4 months of images from Himawari-8 visible channel into cloud index maps. Then, we applied an algorithm computing a cloud motion vector field from a short sequence of consecutive images. Comparisons between forecasted SSI at 1 hour of time horizon and collocated pyranometric measurements show a relative RMSE between 20 and 27%. Error sources related to the tropic insular context (coastal area heterogeneity, sub-pixel scale orographic cloud appearance, convective situation…) are discussed at every implementation step for the different methods.

Remote Sensing Analysis of Vegetation Recovery following Short-Interval Fires in Southern California Shrublands

Science.gov (United States)

Meng, Ran; Dennison, Philip E.; D’Antonio, Carla M.; Moritz, Max A.

2014-01-01

Increased fire frequency has been shown to promote alien plant invasions in the western United States, resulting in persistent vegetation type change. Short interval fires are widely considered to be detrimental to reestablishment of shrub species in southern California chaparral, facilitating the invasion of exotic annuals and producing “type conversion”. However, supporting evidence for type conversion has largely been at local, site scales and over short post-fire time scales. Type conversion has not been shown to be persistent or widespread in chaparral, and past range improvement studies present evidence that chaparral type conversion may be difficult and a relatively rare phenomenon across the landscape. With the aid of remote sensing data covering coastal southern California and a historical wildfire dataset, the effects of short interval fires (fire history, climate and elevation) were analyzed by linear regression. Reduced vegetation cover was found in some lower elevation areas that were burned twice in short interval fires, where non-sprouting species are more common. However, extensive type conversion of chaparral to grassland was not evident in this study. Most variables, with the exception of elevation, were moderately or poorly correlated with differences in vegetation recovery. PMID:25337785

Image Positioning Accuracy Analysis for Super Low Altitude Remote Sensing Satellites

Directory of Open Access Journals (Sweden)

Ming Xu

2012-10-01

Full Text Available Super low altitude remote sensing satellites maintain lower flight altitudes by means of ion propulsion in order to improve image resolution and positioning accuracy. The use of engineering data in design for achieving image positioning accuracy is discussed in this paper based on the principles of the photogrammetry theory. The exact line-of-sight rebuilding of each detection element and this direction precisely intersecting with the Earth's elliptical when the camera on the satellite is imaging are both ensured by the combined design of key parameters. These parameters include: orbit determination accuracy, attitude determination accuracy, camera exposure time, accurately synchronizing the reception of ephemeris with attitude data, geometric calibration and precise orbit verification. Precise simulation calculations show that image positioning accuracy of super low altitude remote sensing satellites is not obviously improved. The attitude determination error of a satellite still restricts its positioning accuracy.

Fundamental Limitations for Imaging GEO Satellites

Science.gov (United States)

2015-10-18

Fundamental limitations for imaging GEO satellites D. Mozurkewich Seabrook Engineering , Seabrook, MD 20706 USA H. R. Schmitt, J. T. Armstrong Naval...higher spatial frequency. Send correspondence to David Mozurkewich, Seabrook Engineering , 9310 Dubarry Ave., Seabrook MD 20706 E-mail: dave

Medical image transmission via communication satellite. Evaluation of bone scintigraphy

International Nuclear Information System (INIS)

Suzuki, Hideki; Inoue, Tomio; Endo, Keigo; Shimamoto, Shigeru.

1995-01-01

As compared with terrestrial circuits, the communication satellite possesses superior characteristics such as wide area coverage, broadcasting, high capacity, and robustness to disasters. Utilizing the narrow band channel (64 kbps) of the geostationary satellite JCSAT 1 located at the altitude of 36,000 km above the equator, the authors investigated satellite-relayed medical imagings by video signals, with bone scintigraphy as a model. Each bone scintigraphy was taken by a handy-video camera, digitalized and transmitted from faculty of technology located at 25 kilometers apart from our department. Clear bone scintigraphy was obtained via satellite, as seen on the view box. Eight nuclear physicians evaluated 20 cases of bone scintigraphy. ROC (Receiver Operating Characteristic) analysis was performed between the scintigraphies on view box and via satellite by the rating method. The area under the ROC curve was 91.6±2.6% via satellite, and 93.2±2.4% on the view box and there was no significant difference between them. These results suggest that the satellite communication is very useful and effective system to send nuclear imagings to distant institutes. (author)

[Medical image transmission via communication satellite: evaluation of bone scintigraphy].

Science.gov (United States)

Suzuki, H; Inoue, T; Endo, K; Shimamoto, S

1995-10-01

As compared with terrestrial circuits, the communication satellite possesses superior characteristics such as wide area coverage, broadcasting, high capacity, and robustness to disasters. Utilizing the narrow band channel (64 kbps) of the geostationary satellite JCSAT1 located at the altitude of 36,000 km above the equator, the authors investigated satellite-relayed medical images by video signals, with bone scintigraphy as a model. Each bone scintigraphy was taken by a handy-video camera, digitalized and transmitted from faculty of technology located at 25 kilometers apart from our department. Clear bone scintigraphy was obtained via satellite, as seen on the view box. Eight nuclear physicians evaluated 20 cases of bone scintigraphy. ROC (Receiver Operating Characteristic) analysis was performed between the scintigraphies on view box and via satellite by the rating method. The area under the ROC curve was 91.6 +/- 2.6% via satellite, and 93.2 +/- 2.4% on the view box and there was no significant difference between them. These results suggest that the satellite communication is very useful and effective system to send nuclear imagings to distant institutes.

Kansas Satellite Image Database (KSID) 2004-2005

Data.gov (United States)

Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID) 2004-2005 consists of terrain-corrected, precision rectified spring, summer, and fall Landsat 5 Thematic Mapper (TM)...

Effects of Short-Interval and Long-Interval Swimming Protocols on Performance, Aerobic Adaptations, and Technical Parameters: A Training Study.

Science.gov (United States)

Dalamitros, Athanasios A; Zafeiridis, Andreas S; Toubekis, Argyris G; Tsalis, George A; Pelarigo, Jailton G; Manou, Vasiliki; Kellis, Spiridon

2016-10-01

Dalamitros, AA, Zafeiridis, AS, Toubekis, AG, Tsalis, GA, Pelarigo, JG, Manou, V, and Kellis, S. Effects of short-interval and long-interval swimming protocols on performance, aerobic adaptations, and technical parameters: A training study. J Strength Cond Res 30(10): 2871-2879, 2016-This study compared 2-interval swimming training programs of different work interval durations, matched for total distance and exercise intensity, on swimming performance, aerobic adaptations, and technical parameters. Twenty-four former swimmers were equally divided to short-interval training group (INT50, 12-16 × 50 m with 15 seconds rest), long-interval training group (INT100, 6-8 × 100 m with 30 seconds rest), and a control group (CON). The 2 experimental groups followed the specified swimming training program for 8 weeks. Before and after training, swimming performance, technical parameters, and indices of aerobic adaptations were assessed. ΙΝΤ50 and ΙΝΤ100 improved swimming performance in 100 and 400-m tests and the maximal aerobic speed (p ≤ 0.05); the performance in the 50-m swim did not change. Posttraining V[Combining Dot Above]O2max values were higher compared with pretraining values in both training groups (p ≤ 0.05), whereas peak aerobic power output increased only in INT100 (p ≤ 0.05). The 1-minute heart rate and blood lactate recovery values decreased after training in both groups (p training in both groups (p ≤ 0.05); no changes were observed in stroke rate after training. Comparisons between groups on posttraining mean values, after adjusting for pretraining values, revealed no significant differences between ΙΝΤ50 and ΙΝΤ100 for all variables; however, all measures were improved vs. the respective values in the CON (p training.

Enhancement of Satellite Image Compression Using a Hybrid (DWT-DCT) Algorithm

Science.gov (United States)

Shihab, Halah Saadoon; Shafie, Suhaidi; Ramli, Abdul Rahman; Ahmad, Fauzan

2017-12-01

Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) image compression techniques have been utilized in most of the earth observation satellites launched during the last few decades. However, these techniques have some issues that should be addressed. The DWT method has proven to be more efficient than DCT for several reasons. Nevertheless, the DCT can be exploited to improve the high-resolution satellite image compression when combined with the DWT technique. Hence, a proposed hybrid (DWT-DCT) method was developed and implemented in the current work, simulating an image compression system on-board on a small remote sensing satellite, with the aim of achieving a higher compression ratio to decrease the onboard data storage and the downlink bandwidth, while avoiding further complex levels of DWT. This method also succeeded in maintaining the reconstructed satellite image quality through replacing the standard forward DWT thresholding and quantization processes with an alternative process that employed the zero-padding technique, which also helped to reduce the processing time of DWT compression. The DCT, DWT and the proposed hybrid methods were implemented individually, for comparison, on three LANDSAT 8 images, using the MATLAB software package. A comparison was also made between the proposed method and three other previously published hybrid methods. The evaluation of all the objective and subjective results indicated the feasibility of using the proposed hybrid (DWT-DCT) method to enhance the image compression process on-board satellites.

Schedule Optimization of Imaging Missions for Multiple Satellites and Ground Stations Using Genetic Algorithm

Science.gov (United States)

Lee, Junghyun; Kim, Heewon; Chung, Hyun; Kim, Haedong; Choi, Sujin; Jung, Okchul; Chung, Daewon; Ko, Kwanghee

2018-04-01

In this paper, we propose a method that uses a genetic algorithm for the dynamic schedule optimization of imaging missions for multiple satellites and ground systems. In particular, the visibility conflicts of communication and mission operation using satellite resources (electric power and onboard memory) are integrated in sequence. Resource consumption and restoration are considered in the optimization process. Image acquisition is an essential part of satellite missions and is performed via a series of subtasks such as command uplink, image capturing, image storing, and image downlink. An objective function for optimization is designed to maximize the usability by considering the following components: user-assigned priority, resource consumption, and image-acquisition time. For the simulation, a series of hypothetical imaging missions are allocated to a multi-satellite control system comprising five satellites and three ground stations having S- and X-band antennas. To demonstrate the performance of the proposed method, simulations are performed via three operation modes: general, commercial, and tactical.

Short-Term Solar Irradiance Forecasts Using Sky Images and Radiative Transfer Model

Directory of Open Access Journals (Sweden)

Juan Du

2018-05-01

Full Text Available In this paper, we propose a novel forecast method which addresses the difficulty in short-term solar irradiance forecasting that arises due to rapidly evolving environmental factors over short time periods. This involves the forecasting of Global Horizontal Irradiance (GHI that combines prediction sky images with a Radiative Transfer Model (RTM. The prediction images (up to 10 min ahead are produced by a non-local optical flow method, which is used to calculate the cloud motion for each pixel, with consecutive sky images at 1 min intervals. The Direct Normal Irradiance (DNI and the diffuse radiation intensity field under clear sky and overcast conditions obtained from the RTM are then mapped to the sky images. Through combining the cloud locations on the prediction image with the corresponding instance of image-based DNI and diffuse radiation intensity fields, the GHI can be quantitatively forecasted for time horizons of 1–10 min ahead. The solar forecasts are evaluated in terms of root mean square error (RMSE and mean absolute error (MAE in relation to in-situ measurements and compared to the performance of the persistence model. The results of our experiment show that GHI forecasts using the proposed method perform better than the persistence model.

The SUMO Ship Detector Algorithm for Satellite Radar Images

Directory of Open Access Journals (Sweden)

Harm Greidanus

2017-03-01

Full Text Available Search for Unidentified Maritime Objects (SUMO is an algorithm for ship detection in satellite Synthetic Aperture Radar (SAR images. It has been developed over the course of more than 15 years, using a large amount of SAR images from almost all available SAR satellites operating in L-, C- and X-band. As validated by benchmark tests, it performs very well on a wide range of SAR image modes (from Spotlight to ScanSAR and resolutions (from 1–100 m and for all types and sizes of ships, within the physical limits imposed by the radar imaging. This paper describes, in detail, the algorithmic approach in all of the steps of the ship detection: land masking, clutter estimation, detection thresholding, target clustering, ship attribute estimation and false alarm suppression. SUMO is a pixel-based CFAR (Constant False Alarm Rate detector for multi-look radar images. It assumes a K distribution for the sea clutter, corrected however for deviations of the actual sea clutter from this distribution, implementing a fast and robust method for the clutter background estimation. The clustering of detected pixels into targets (ships uses several thresholds to deal with the typically irregular distribution of the radar backscatter over a ship. In a multi-polarization image, the different channels are fused. Azimuth ambiguities, a common source of false alarms in ship detection, are removed. A reliability indicator is computed for each target. In post-processing, using the results of a series of images, additional false alarms from recurrent (fixed targets including range ambiguities are also removed. SUMO can run in semi-automatic mode, where an operator can verify each detected target. It can also run in fully automatic mode, where batches of over 10,000 images have successfully been processed in less than two hours. The number of satellite SAR systems keeps increasing, as does their application to maritime surveillance. The open data policy of the EU�

SHORT-TERM PRECIPITATION OCCURRENCE PREDICTION FOR STRONG CONVECTIVE WEATHER USING FY2-G SATELLITE DATA: A CASE STUDY OF SHENZHEN,SOUTH CHINA

Directory of Open Access Journals (Sweden)

K. Chen

2016-06-01

Full Text Available Short-term precipitation commonly occurs in south part of China, which brings intensive precipitation in local region for very short time. Massive water would cause the intensive flood inside of city when precipitation amount beyond the capacity of city drainage system. Thousands people’s life could be influenced by those short-term disasters and the higher city managements are required to facing these challenges. How to predict the occurrence of heavy precipitation accurately is one of the worthwhile scientific questions in meteorology. According to recent studies, the accuracy of short-term precipitation prediction based on numerical simulation model still remains low reliability, in some area where lack of local observations, the accuracy may be as low as 10%. The methodology for short term precipitation occurrence prediction still remains a challenge. In this paper, a machine learning method based on SVM was presented to predict short-term precipitation occurrence by using FY2-G satellite imagery and ground in situ observation data. The results were validated by traditional TS score which commonly used in evaluation of weather prediction. The results indicate that the proposed algorithm can present overall accuracy up to 90% for one-hour to six-hour forecast. The result implies the prediction accuracy could be improved by using machine learning method combining with satellite image. This prediction model can be further used to evaluated to predicted other characteristics of weather in Shenzhen in future.

AN APPROACH FOR STITCHING SATELLITE IMAGES IN A BIGDATA MAPREDUCE FRAMEWORK

Directory of Open Access Journals (Sweden)

H. Sarı

2017-11-01

Full Text Available In this study we present a two-step map/reduce framework to stitch satellite mosaic images. The proposed system enable recognition and extraction of objects whose parts falling in separate satellite mosaic images. However this is a time and resource consuming process. The major aim of the study is improving the performance of the image stitching processes by utilizing big data framework. To realize this, we first convert the images into bitmaps (first mapper and then String formats in the forms of 255s and 0s (second mapper, and finally, find the best possible matching position of the images by a reduce function.

An Approach for Stitching Satellite Images in a Bigdata Mapreduce Framework

Science.gov (United States)

Sarı, H.; Eken, S.; Sayar, A.

2017-11-01

In this study we present a two-step map/reduce framework to stitch satellite mosaic images. The proposed system enable recognition and extraction of objects whose parts falling in separate satellite mosaic images. However this is a time and resource consuming process. The major aim of the study is improving the performance of the image stitching processes by utilizing big data framework. To realize this, we first convert the images into bitmaps (first mapper) and then String formats in the forms of 255s and 0s (second mapper), and finally, find the best possible matching position of the images by a reduce function.

Detecting aircrafts from satellite images using saliency and conical ...

Indian Academy of Sciences (India)

Samik Banerjee

automatically detect all kinds of interesting targets in satellite images. .... which is used for text and image categorization, has been also introduced for object ...... 3.4 GHz processor, 32 GB RAM and Windows 7 (64 bit). Operating System. 6.

LAKE ICE DETECTION IN LOW-RESOLUTION OPTICAL SATELLITE IMAGES

Directory of Open Access Journals (Sweden)

M. Tom

2018-05-01

Full Text Available Monitoring and analyzing the (decreasing trends in lake freezing provides important information for climate research. Multi-temporal satellite images are a natural data source to survey ice on lakes. In this paper, we describe a method for lake ice monitoring, which uses low spatial resolution (250 m–1000 m satellite images to determine whether a lake is frozen or not. We report results on four selected lakes in Switzerland: Sihl, Sils, Silvaplana and St. Moritz. These lakes have different properties regarding area, altitude, surrounding topography and freezing frequency, describing cases of medium to high difficulty. Digitized Open Street Map (OSM lake outlines are back-projected on to the image space after generalization. As a pre-processing step, the absolute geolocation error of the lake outlines is corrected by matching the projected outlines to the images. We define the lake ice detection as a two-class (frozen, non-frozen semantic segmentation problem. Several spectral channels of the multi-spectral satellite data are used, both reflective and emissive (thermal. Only the cloud-free (clean pixels which lie completely inside the lake are analyzed. The most useful channels to solve the problem are selected with xgboost and visual analysis of histograms of reference data, while the classification is done with non-linear support vector machine (SVM. We show experimentally that this straight-forward approach works well with both MODIS and VIIRS satellite imagery. Moreover, we show that the algorithm produces consistent results when tested on data from multiple winters.

Lake Ice Detection in Low-Resolution Optical Satellite Images

Science.gov (United States)

Tom, M.; Kälin, U.; Sütterlin, M.; Baltsavias, E.; Schindler, K.

2018-05-01

Monitoring and analyzing the (decreasing) trends in lake freezing provides important information for climate research. Multi-temporal satellite images are a natural data source to survey ice on lakes. In this paper, we describe a method for lake ice monitoring, which uses low spatial resolution (250 m-1000 m) satellite images to determine whether a lake is frozen or not. We report results on four selected lakes in Switzerland: Sihl, Sils, Silvaplana and St. Moritz. These lakes have different properties regarding area, altitude, surrounding topography and freezing frequency, describing cases of medium to high difficulty. Digitized Open Street Map (OSM) lake outlines are back-projected on to the image space after generalization. As a pre-processing step, the absolute geolocation error of the lake outlines is corrected by matching the projected outlines to the images. We define the lake ice detection as a two-class (frozen, non-frozen) semantic segmentation problem. Several spectral channels of the multi-spectral satellite data are used, both reflective and emissive (thermal). Only the cloud-free (clean) pixels which lie completely inside the lake are analyzed. The most useful channels to solve the problem are selected with xgboost and visual analysis of histograms of reference data, while the classification is done with non-linear support vector machine (SVM). We show experimentally that this straight-forward approach works well with both MODIS and VIIRS satellite imagery. Moreover, we show that the algorithm produces consistent results when tested on data from multiple winters.

Design of an Image Motion Compenstaion (IMC Algorithm for Image Registration of the Communication, Ocean, Meteorolotical Satellite (COMS-1

Directory of Open Access Journals (Sweden)

Taek Seo Jung

2006-03-01

Full Text Available This paper presents an Image Motion Compensation (IMC algorithm for the Korea's Communication, Ocean, and Meteorological Satellite (COMS-1. An IMC algorithm is a priority component of image registration in Image Navigation and Registration (INR system to locate and register radiometric image data. Due to various perturbations, a satellite has orbit and attitude errors with respect to a reference motion. These errors cause depointing of the imager aiming direction, and in consequence cause image distortions. To correct the depointing of the imager aiming direction, a compensation algorithm is designed by adapting different equations from those used for the GOES satellites. The capability of the algorithm is compared with that of existing algorithm applied to the GOES's INR system. The algorithm developed in this paper improves pointing accuracy by 40%, and efficiently compensates the depointings of the imager aiming direction.

The Application of the Technology of 3D Satellite Cloud Imaging in Virtual Reality Simulation

Directory of Open Access Journals (Sweden)

Xiao-fang Xie

2007-05-01

Full Text Available Using satellite cloud images to simulate clouds is one of the new visual simulation technologies in Virtual Reality (VR. Taking the original data of satellite cloud images as the source, this paper depicts specifically the technology of 3D satellite cloud imaging through the transforming of coordinates and projection, creating a DEM (Digital Elevation Model of cloud imaging and 3D simulation. A Mercator projection was introduced to create a cloud image DEM, while solutions for geodetic problems were introduced to calculate distances, and the outer-trajectory science of rockets was introduced to obtain the elevation of clouds. For demonstration, we report on a computer program to simulate the 3D satellite cloud images.

Geometric calibration of ERS satellite SAR images

DEFF Research Database (Denmark)

Mohr, Johan Jacob; Madsen, Søren Nørvang

2001-01-01

Geometric calibration of the European Remote Sensing (ERS) Satellite synthetic aperture radar (SAR) slant range images is important in relation to mapping areas without ground reference points and also in relation to automated processing. The relevant SAR system parameters are discussed...

Ice Sheet Change Detection by Satellite Image Differencing

Science.gov (United States)

Bindschadler, Robert A.; Scambos, Ted A.; Choi, Hyeungu; Haran, Terry M.

2010-01-01

Differencing of digital satellite image pairs highlights subtle changes in near-identical scenes of Earth surfaces. Using the mathematical relationships relevant to photoclinometry, we examine the effectiveness of this method for the study of localized ice sheet surface topography changes using numerical experiments. We then test these results by differencing images of several regions in West Antarctica, including some where changes have previously been identified in altimeter profiles. The technique works well with coregistered images having low noise, high radiometric sensitivity, and near-identical solar illumination geometry. Clouds and frosts detract from resolving surface features. The ETM(plus) sensor on Landsat-7, ALI sensor on EO-1, and MODIS sensor on the Aqua and Terra satellite platforms all have potential for detecting localized topographic changes such as shifting dunes, surface inflation and deflation features associated with sub-glacial lake fill-drain events, or grounding line changes. Availability and frequency of MODIS images favor this sensor for wide application, and using it, we demonstrate both qualitative identification of changes in topography and quantitative mapping of slope and elevation changes.

Remote sensing analysis of vegetation recovery following short-interval fires in Southern California shrublands.

Science.gov (United States)

Meng, Ran; Dennison, Philip E; D'Antonio, Carla M; Moritz, Max A

2014-01-01

Increased fire frequency has been shown to promote alien plant invasions in the western United States, resulting in persistent vegetation type change. Short interval fires are widely considered to be detrimental to reestablishment of shrub species in southern California chaparral, facilitating the invasion of exotic annuals and producing "type conversion". However, supporting evidence for type conversion has largely been at local, site scales and over short post-fire time scales. Type conversion has not been shown to be persistent or widespread in chaparral, and past range improvement studies present evidence that chaparral type conversion may be difficult and a relatively rare phenomenon across the landscape. With the aid of remote sensing data covering coastal southern California and a historical wildfire dataset, the effects of short interval fires (<8 years) on chaparral recovery were evaluated by comparing areas that burned twice to adjacent areas burned only once. Twelve pairs of once- and twice-burned areas were compared using normalized burn ratio (NBR) distributions. Correlations between measures of recovery and explanatory factors (fire history, climate and elevation) were analyzed by linear regression. Reduced vegetation cover was found in some lower elevation areas that were burned twice in short interval fires, where non-sprouting species are more common. However, extensive type conversion of chaparral to grassland was not evident in this study. Most variables, with the exception of elevation, were moderately or poorly correlated with differences in vegetation recovery.

Imaging in short stature.

Science.gov (United States)

Chaudhary, Vikas; Bano, Shahina

2012-09-01

Short stature can be a sign of disease, disability, and social stigma causing psychological stress. It is important to have an early diagnosis and treatment. Short stature may result from skeletal dysplasias, endocrine disorders, may be familial, or may be the result of malnutrition and chronic illnesses. A team effort of the healthcare professionals like pediatricians, endocrinologists, radiologists, and pathologists is required to diagnose, treat and monitor various pathological conditions associated with growth abnormality. In this review, we have discussed the role of imaging in diagnosing and characterizing various pathological conditions associated with short stature.

Landsat TM and ETM+ 2002-2003 Kansas Satellite Image Database (KSID)

Data.gov (United States)

Kansas Data Access and Support Center — The Kansas Satellite Image Database (KSID):2002-2003 consists of image data gathered by three sensors. The first image data are terrain-corrected, precision...

STUDY ON THE PARTICLE INJECTIONS DURING HILDCAA INTERVALS

Directory of Open Access Journals (Sweden)

Hee-Jeong Kim

2007-06-01

Full Text Available The relation between substorm occurrences and HILDCAA events has been an issue. We have studied the association of particle injections with substorm onsets during HILDCAA intervals for the first half of year 2003. The examination of aurora images observed by IMAGE spacecraft and electron flux data measured by LANL satellites exhibits a close association of repetitive particle injections with substorm activity. We also find that HILDCAA events can occur equally frequently during slow speed solar wind streams as long as the interplanetary magnetic field exhibits Alfvenic wave feature.

RELATIVE ORIENTATION AND MODIFIED PIECEWISE EPIPOLAR RESAMPLING FOR HIGH RESOLUTION SATELLITE IMAGES

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K. Gong

2017-05-01

Full Text Available High resolution, optical satellite sensors are boosted to a new era in the last few years, because satellite stereo images at half meter or even 30cm resolution are available. Nowadays, high resolution satellite image data have been commonly used for Digital Surface Model (DSM generation and 3D reconstruction. It is common that the Rational Polynomial Coefficients (RPCs provided by the vendors have rough precision and there is no ground control information available to refine the RPCs. Therefore, we present two relative orientation methods by using corresponding image points only: the first method will use quasi ground control information, which is generated from the corresponding points and rough RPCs, for the bias-compensation model; the second method will estimate the relative pointing errors on the matching image and remove this error by an affine model. Both methods do not need ground control information and are applied for the entire image. To get very dense point clouds, the Semi-Global Matching (SGM method is an efficient tool. However, before accomplishing the matching process the epipolar constraints are required. In most conditions, satellite images have very large dimensions, contrary to the epipolar geometry generation and image resampling, which is usually carried out in small tiles. This paper also presents a modified piecewise epipolar resampling method for the entire image without tiling. The quality of the proposed relative orientation and epipolar resampling method are evaluated, and finally sub-pixel accuracy has been achieved in our work.

Image Fusion-Based Land Cover Change Detection Using Multi-Temporal High-Resolution Satellite Images

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Biao Wang

2017-08-01

Full Text Available Change detection is usually treated as a problem of explicitly detecting land cover transitions in satellite images obtained at different times, and helps with emergency response and government management. This study presents an unsupervised change detection method based on the image fusion of multi-temporal images. The main objective of this study is to improve the accuracy of unsupervised change detection from high-resolution multi-temporal images. Our method effectively reduces change detection errors, since spatial displacement and spectral differences between multi-temporal images are evaluated. To this end, a total of four cross-fused images are generated with multi-temporal images, and the iteratively reweighted multivariate alteration detection (IR-MAD method—a measure for the spectral distortion of change information—is applied to the fused images. In this experiment, the land cover change maps were extracted using multi-temporal IKONOS-2, WorldView-3, and GF-1 satellite images. The effectiveness of the proposed method compared with other unsupervised change detection methods is demonstrated through experimentation. The proposed method achieved an overall accuracy of 80.51% and 97.87% for cases 1 and 2, respectively. Moreover, the proposed method performed better when differentiating the water area from the vegetation area compared to the existing change detection methods. Although the water area beneath moderate and sparse vegetation canopy was captured, vegetation cover and paved regions of the water body were the main sources of omission error, and commission errors occurred primarily in pixels of mixed land use and along the water body edge. Nevertheless, the proposed method, in conjunction with high-resolution satellite imagery, offers a robust and flexible approach to land cover change mapping that requires no ancillary data for rapid implementation.

Increased Short-Term Beat-To-Beat Variability of QT Interval in Patients with Acromegaly

Science.gov (United States)

Orosz, Andrea; Csajbók, Éva; Czékus, Csilla; Gavallér, Henriette; Magony, Sándor; Valkusz, Zsuzsanna; Várkonyi, Tamás T.; Nemes, Attila; Baczkó, István; Forster, Tamás; Wittmann, Tibor; Papp, Julius Gy.; Varró, András; Lengyel, Csaba

2015-01-01

Cardiovascular diseases, including ventricular arrhythmias are responsible for increased mortality in patients with acromegaly. Acromegaly may cause repolarization abnormalities such as QT prolongation and impairment of repolarization reserve enhancing liability to arrhythmia. The aim of this study was to determine the short-term beat-to-beat QT variability in patients with acromegaly. Thirty acromegalic patients (23 women and 7 men, mean age±SD: 55.7±10.4 years) were compared with age- and sex-matched volunteers (mean age 51.3±7.6 years). Cardiac repolarization parameters including frequency corrected QT interval, PQ and QRS intervals, duration of terminal part of T waves (Tpeak-Tend) and short-term variability of QT interval were evaluated. All acromegalic patients and controls underwent transthoracic echocardiographic examination. Autonomic function was assessed by means of five standard cardiovascular reflex tests. Comparison of the two groups revealed no significant differences in the conventional ECG parameters of repolarization (QT: 401.1±30.6 ms vs 389.3±16.5 ms, corrected QT interval: 430.1±18.6 ms vs 425.6±17.3 ms, QT dispersion: 38.2±13.2 ms vs 36.6±10.2 ms; acromegaly vs control, respectively). However, short-term beat-to-beat QT variability was significantly increased in acromegalic patients (4.23±1.03 ms vs 3.02±0.80, Pacromegaly in spite of unchanged conventional parameters of ventricular repolarization. This enhanced temporal QT variability may be an early indicator of increased liability to arrhythmia. PMID:25915951

Accuracy assessment of topographic mapping using UAV image integrated with satellite images

International Nuclear Information System (INIS)

Azmi, S M; Ahmad, Baharin; Ahmad, Anuar

2014-01-01

Unmanned Aerial Vehicle or UAV is extensively applied in various fields such as military applications, archaeology, agriculture and scientific research. This study focuses on topographic mapping and map updating. UAV is one of the alternative ways to ease the process of acquiring data with lower operating costs, low manufacturing and operational costs, plus it is easy to operate. Furthermore, UAV images will be integrated with QuickBird images that are used as base maps. The objective of this study is to make accuracy assessment and comparison between topographic mapping using UAV images integrated with aerial photograph and satellite image. The main purpose of using UAV image is as a replacement for cloud covered area which normally exists in aerial photograph and satellite image, and for updating topographic map. Meanwhile, spatial resolution, pixel size, scale, geometric accuracy and correction, image quality and information contents are important requirements needed for the generation of topographic map using these kinds of data. In this study, ground control points (GCPs) and check points (CPs) were established using real time kinematic Global Positioning System (RTK-GPS) technique. There are two types of analysis that are carried out in this study which are quantitative and qualitative assessments. Quantitative assessment is carried out by calculating root mean square error (RMSE). The outputs of this study include topographic map and orthophoto. From this study, the accuracy of UAV image is ± 0.460 m. As conclusion, UAV image has the potential to be used for updating of topographic maps

Recurrent Neural Networks to Correct Satellite Image Classification Maps

Science.gov (United States)

Maggiori, Emmanuel; Charpiat, Guillaume; Tarabalka, Yuliya; Alliez, Pierre

2017-09-01

While initially devised for image categorization, convolutional neural networks (CNNs) are being increasingly used for the pixelwise semantic labeling of images. However, the proper nature of the most common CNN architectures makes them good at recognizing but poor at localizing objects precisely. This problem is magnified in the context of aerial and satellite image labeling, where a spatially fine object outlining is of paramount importance. Different iterative enhancement algorithms have been presented in the literature to progressively improve the coarse CNN outputs, seeking to sharpen object boundaries around real image edges. However, one must carefully design, choose and tune such algorithms. Instead, our goal is to directly learn the iterative process itself. For this, we formulate a generic iterative enhancement process inspired from partial differential equations, and observe that it can be expressed as a recurrent neural network (RNN). Consequently, we train such a network from manually labeled data for our enhancement task. In a series of experiments we show that our RNN effectively learns an iterative process that significantly improves the quality of satellite image classification maps.

Imaging in short stature

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Vikas Chaudhary

2012-01-01

Full Text Available Short stature can be a sign of disease, disability, and social stigma causing psychological stress. It is important to have an early diagnosis and treatment. Short stature may result from skeletal dysplasias, endocrine disorders, may be familial, or may be the result of malnutrition and chronic illnesses. A team effort of the healthcare professionals like pediatricians, endocrinologists, radiologists, and pathologists is required to diagnose, treat and monitor various pathological conditions associated with growth abnormality. In this review, we have discussed the role of imaging in diagnosing and characterizing various pathological conditions associated with short stature.

Muscle Adaptations Following Short-Duration Bed Rest with Integrated Resistance, Interval, and Aerobic Exercise

Science.gov (United States)

Hackney, Kyle J.; Scott, Jessica M.; Buxton, Roxanne; Redd-Goetchius, Elizabeth; Crowell, J. Brent; Everett, Meghan E.; Wickwire, Jason; Ryder, Jeffrey W.; Bloomberg, Jacob J.; Ploutz-Snyder, Lori L.

2011-01-01

Unloading of the musculoskeletal system during space flight results in deconditioning that may impair mission-related task performance in astronauts. Exercise countermeasures have been frequently tested during bed rest (BR) and limb suspension; however, high-intensity, short-duration exercise prescriptions have not been fully explored. PURPOSE: To determine if a high intensity resistance, interval, and aerobic exercise program could protect against muscle atrophy and dysfunction when performed during short duration BR. METHODS: Nine subjects (1 female, 8 male) performed a combination of supine exercises during 2 weeks of horizontal BR. Resistance exercise (3 d / wk) consisted of squat, leg press, hamstring curl, and heel raise exercises (3 sets, 12 repetitions). Aerobic (6 d / wk) sessions alternated continuous (75% VO2 peak) and interval exercise (30 s, 2 min, and 4 min) and were completed on a supine cycle ergometer and vertical treadmill, respectively. Muscle volumes of the upper leg were calculated pre, mid, and post-BR using magnetic resonance imaging. Maximal isometric force (MIF), rate of force development (RFD), and peak power of the lower body extensors were measured twice before BR (averaged to represent pre) and once post BR. ANOVA with repeated measures and a priori planned contrasts were used to test for differences. RESULTS: There were no changes to quadriceps, hamstring, and adductor muscle volumes at mid and post BR time points compared to pre BR (Table 1). Peak power increased significantly from 1614 +/- 372 W to 1739 +/- 359 W post BR (+7.7%, p = 0.035). Neither MIF (pre: 1676 +/- 320 N vs. post: 1711 +/- 250 N, +2.1%, p = 0.333) nor RFD (pre: 7534 +/- 1265 N/ms vs. post: 6951 +/- 1241 N/ms, -7.7%, p = 0.136) were significantly impaired post BR.

Images of war: using satellite images for human rights monitoring in Turkish Kurdistan.

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de Vos, Hugo; Jongerden, Joost; van Etten, Jacob

2008-09-01

In areas of war and armed conflict it is difficult to get trustworthy and coherent information. Civil society and human rights groups often face problems of dealing with fragmented witness reports, disinformation of war propaganda, and difficult direct access to these areas. Turkish Kurdistan was used as a case study of armed conflict to evaluate the potential use of satellite images for verification of witness reports collected by human rights groups. The Turkish army was reported to be burning forests, fields and villages as a strategy in the conflict against guerrilla uprising. This paper concludes that satellite images are useful to validate witness reports of forest fires. Even though the use of this technology for human rights groups will depend on some feasibility factors such as prices, access and expertise, the images proved to be key for analysis of spatial aspects of conflict and valuable for reconstructing a more trustworthy picture.

Improving Eastern Bluebird nest box performance using computer analysis of satellite images

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Sarah Svatora

2012-06-01

Full Text Available Bird conservationists have been introducing man-made boxes in an effort to increase the bluebird population. In this study we use computer analysis of satellite images to show that the performance of the boxes used by Eastern Bluebirds (Sialia sialis in Michigan can be improved by about 48%. The analysis is based on a strongcorrelation found between the edge directionality measured in the satellite image of the area around the box, and the preferences of the birds when selecting their nesting site. The method is based on satellite images taken from Google Earth, and can be used by conservationists to select a box placement strategy that will optimize the efficacy of the boxes deployed in a given area.

CT coronary angiography: Influence of different cardiac reconstruction intervals on image quality and diagnostic accuracy

Energy Technology Data Exchange (ETDEWEB)

Dewey, Marc [Department of Radiology, Charite Medical School, Humboldt-Universitaet zu Berlin (Germany)], E-mail: marc.dewey@charite.de; Teige, Florian [Department of Radiology, Charite Medical School, Humboldt-Universitaet zu Berlin (Germany); Rutsch, Wolfgang [Department of Cardiology, Charite Medical School, Humboldt-Universitaet zu Berlin (Germany)], E-mail: wolfgang.rutsch@charite.de; Schink, Tania [Department of Medical Biometry, Charite Medical School, Humboldt-Universitaet zu Berlin (Germany)], E-mail: peter.martus@charite.de; Hamm, Bernd [Department of Radiology, Charite Medical School, Humboldt-Universitaet zu Berlin (Germany)

2008-07-15

Purpose: To prospectively analyze image quality and diagnostic accuracy of different reconstruction intervals of coronary angiography using multislice computed tomography (MSCT). Materials and methods: For each of 47 patients, 10 ECG-gated MSCT reconstructions were generated throughout the RR interval from 0 to 90%, resulting in altogether 470 datasets. These datasets were randomly analyzed for image quality and accuracy and compared with conventional angiography. Statistical comparison of intervals was performed using nonparametric analysis for repeated measurements to account for clustering of arteries within patients. Results: Image reconstruction intervals centered at 80, 70, and 40% of the RR interval resulted (in that order) in the best overall image quality for all four main coronary vessels. Eighty percent reconstructions also yielded the highest diagnostic accuracy of all intervals. The combination of the three best intervals (80, 70, and 40%) significantly reduced the nondiagnostic rate as compared with 80% alone (p = 0.005). However, the optimal reconstruction interval combination achieved significantly improved specificities and nondiagnostic rates (p < 0.05). The optimal combination consisted of 1.7 {+-} 0.9 reconstruction intervals on average. In approximately half of the patients (49%, 23/47) a single reconstruction was optimal. In 18 (38%), 3 (6%), and 3 (6%) patients one, two, and three additional reconstruction intervals were required, respectively, to achieve optimal quality. In 28% of the patients the optimal combination consisted of reconstructions other than the three best intervals (80, 70, and 40%). Conclusion: Multiple image reconstruction intervals are essential to ensure high image quality and accuracy of CT coronary angiography.

Auto Mission Planning System Design for Imaging Satellites and Its Applications in Environmental Field

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He Yongming

2016-10-01

Full Text Available Satellite hardware has reached a level of development that enables imaging satellites to realize applications in the area of meteorology and environmental monitoring. As the requirements in terms of feasibility and the actual profit achieved by satellite applications increase, we need to comprehensively consider the actual status, constraints, unpredictable information, and complicated requirements. The management of this complex information and the allocation of satellite resources to realize image acquisition have become essential for enhancing the efficiency of satellite instrumentation. In view of this, we designed a satellite auto mission planning system, which includes two sub-systems: the imaging satellite itself and the ground base, and these systems would then collaborate to process complicated missions: the satellite mainly focuses on mission planning and functions according to actual parameters, whereas the ground base provides auxiliary information, management, and control. Based on the requirements analysis, we have devised the application scenarios, main module, and key techniques. Comparison of the simulation results of the system, confirmed the feasibility and optimization efficiency of the system framework, which also stimulates new thinking for the method of monitoring environment and design of mission planning systems.

Relation of increased short-term variability of QT interval to congenital long-QT syndrome

DEFF Research Database (Denmark)

Hinterseer, Martin; Beckmann, Britt-Maria; Thomsen, Morten B

2009-01-01

Apart from clinical symptoms the diagnosis and risk stratification in long-QT syndrome (LQTS) is usually based on the surface electrocardiogram. Studies have indicated that not only prolongation of the QT interval but also an increased short-term variability of QT interval (STV(QT)) is a marker...... that an STV(QT) of 4.9 ms was the optimal cut-off value to predict mutation carriers. When incorporating an STV(QT) >4.9 ms for those whose QTc interval was within the normal limits, sensitivity to distinguish mutation carriers increased to 83% with a specificity of 68%, so that another 15 mutation carriers...

Convolutional neural network features based change detection in satellite images

Science.gov (United States)

Mohammed El Amin, Arabi; Liu, Qingjie; Wang, Yunhong

2016-07-01

With the popular use of high resolution remote sensing (HRRS) satellite images, a huge research efforts have been placed on change detection (CD) problem. An effective feature selection method can significantly boost the final result. While hand-designed features have proven difficulties to design features that effectively capture high and mid-level representations, the recent developments in machine learning (Deep Learning) omit this problem by learning hierarchical representation in an unsupervised manner directly from data without human intervention. In this letter, we propose approaching the change detection problem from a feature learning perspective. A novel deep Convolutional Neural Networks (CNN) features based HR satellite images change detection method is proposed. The main guideline is to produce a change detection map directly from two images using a pretrained CNN. This method can omit the limited performance of hand-crafted features. Firstly, CNN features are extracted through different convolutional layers. Then, a concatenation step is evaluated after an normalization step, resulting in a unique higher dimensional feature map. Finally, a change map was computed using pixel-wise Euclidean distance. Our method has been validated on real bitemporal HRRS satellite images according to qualitative and quantitative analyses. The results obtained confirm the interest of the proposed method.

Short- or long-rest intervals during repeated-sprint training in soccer?

Science.gov (United States)

Iaia, F. Marcello; Fiorenza, Matteo; Larghi, Luca; Alberti, Giampietro; Millet, Grégoire P.; Girard, Olivier

2017-01-01

The present study compared the effects of two repeated-sprint training (RST) programs, differing in duration of the between-sprint rest intervals, on various soccer-related exercise performances. For 5 weeks during the competitive season, twenty-nine young trained male soccer players either replaced two of their habitual fitness conditioning sessions with RST characterized by short (5–15; n = 9) or long (5–30; n = 10) rest intervals, or served as control (n = 10). The 5–15 and 5–30 protocols consisted of 6 repetitions of 30-m (~5 s) straight-line sprints interspersed with 15 s or 30 s of passive recovery, respectively. 5–15 improved 200-m sprint time (2.0±1.5%; pRecovery Test Level 2 increased following 5–15 (11.4±5.0%; psoccer players, RST over a 5-week in-season period is an efficient means to simultaneously develop different components of fitness relevant to match performance, with different benefits induced by shorter compared to longer rest intervals. PMID:28199402

FFT-enhanced IHS transform method for fusing high-resolution satellite images

Science.gov (United States)

Ling, Y.; Ehlers, M.; Usery, E.L.; Madden, M.

2007-01-01

Existing image fusion techniques such as the intensity-hue-saturation (IHS) transform and principal components analysis (PCA) methods may not be optimal for fusing the new generation commercial high-resolution satellite images such as Ikonos and QuickBird. One problem is color distortion in the fused image, which causes visual changes as well as spectral differences between the original and fused images. In this paper, a fast Fourier transform (FFT)-enhanced IHS method is developed for fusing new generation high-resolution satellite images. This method combines a standard IHS transform with FFT filtering of both the panchromatic image and the intensity component of the original multispectral image. Ikonos and QuickBird data are used to assess the FFT-enhanced IHS transform method. Experimental results indicate that the FFT-enhanced IHS transform method may improve upon the standard IHS transform and the PCA methods in preserving spectral and spatial information. ?? 2006 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

Performance Evaluation of Three Different High Resolution Satellite Images in Semi-Automatic Urban Illegal Building Detection

Science.gov (United States)

Khalilimoghadama, N.; Delavar, M. R.; Hanachi, P.

2017-09-01

The problem of overcrowding of mega cities has been bolded in recent years. To meet the need of housing this increased population, which is of great importance in mega cities, a huge number of buildings are constructed annually. With the ever-increasing trend of building constructions, we are faced with the growing trend of building infractions and illegal buildings (IBs). Acquiring multi-temporal satellite images and using change detection techniques is one of the proper methods of IB monitoring. Using the type of satellite images with different spatial and spectral resolutions has always been an issue in efficient detection of the building changes. In this research, three bi-temporal high-resolution satellite images of IRS-P5, GeoEye-1 and QuickBird sensors acquired from the west of metropolitan area of Tehran, capital of Iran, in addition to city maps and municipality property database were used to detect the under construction buildings with improved performance and accuracy. Furthermore, determining the employed bi-temporal satellite images to provide better performance and accuracy in the case of IB detection is the other purpose of this research. The Kappa coefficients of 70 %, 64 %, and 68 % were obtained for producing change image maps using GeoEye-1, IRS-P5, and QuickBird satellite images, respectively. In addition, the overall accuracies of 100 %, 6 %, and 83 % were achieved for IB detection using the satellite images, respectively. These accuracies substantiate the fact that the GeoEye-1 satellite images had the best performance among the employed images in producing change image map and detecting the IBs.

Spatial Data Exploring by Satellite Image Distributed Processing

Science.gov (United States)

Mihon, V. D.; Colceriu, V.; Bektas, F.; Allenbach, K.; Gvilava, M.; Gorgan, D.

2012-04-01

Our society needs and environmental predictions encourage the applications development, oriented on supervising and analyzing different Earth Science related phenomena. Satellite images could be explored for discovering information concerning land cover, hydrology, air quality, and water and soil pollution. Spatial and environment related data could be acquired by imagery classification consisting of data mining throughout the multispectral bands. The process takes in account a large set of variables such as satellite image types (e.g. MODIS, Landsat), particular geographic area, soil composition, vegetation cover, and generally the context (e.g. clouds, snow, and season). All these specific and variable conditions require flexible tools and applications to support an optimal search for the appropriate solutions, and high power computation resources. The research concerns with experiments on solutions of using the flexible and visual descriptions of the satellite image processing over distributed infrastructures (e.g. Grid, Cloud, and GPU clusters). This presentation highlights the Grid based implementation of the GreenLand application. The GreenLand application development is based on simple, but powerful, notions of mathematical operators and workflows that are used in distributed and parallel executions over the Grid infrastructure. Currently it is used in three major case studies concerning with Istanbul geographical area, Rioni River in Georgia, and Black Sea catchment region. The GreenLand application offers a friendly user interface for viewing and editing workflows and operators. The description involves the basic operators provided by GRASS [1] library as well as many other image related operators supported by the ESIP platform [2]. The processing workflows are represented as directed graphs giving the user a fast and easy way to describe complex parallel algorithms, without having any prior knowledge of any programming language or application commands

Short QTc Interval in Males with Klinefelter Syndrome-Influence of CAG Repeat Length, Body Composition, and Testosterone Replacement Therapy

DEFF Research Database (Denmark)

Jørgensen, Inger Norlyk; Skakkebaek, Anne; Andersen, Niels Holmark

2015-01-01

BackgroundKlinefelter syndrome (KS) is a sex chromosomal aneuploidy (47,XXY) affecting 1/660 males. Based on findings in Turner syndrome, we hypothesized that electrocardiogram (ECG) abnormalities would be present in males with KS. ObjectiveTo investigate ECGs in males with KS and compare...... syndrome was determined in participants with a QTc ... interval comparable to controls. No mutations in genes related to short QT syndrome were found. ConclusionWe found short QTc interval in males with KS, with further shortening of the QTc interval by T. These results suggest that genes on the X chromosome could be involved in regulation of the QTc interval...

Very high resolution satellite data: New challenges in image analysis

Digital Repository Service at National Institute of Oceanography (India)

Sathe, P.V.; Muraleedharan, P.M.

with the exception that a ground-based view covers the entire optical range from 400 to 700 nm while satellite images will be wavelength-specific. Although the images will not surpass details observed by a human eye, they will, in principle, be comparable with aerial...

Landsat TM and ETM+ Kansas Satellite Image Database (KSID)

Data.gov (United States)

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

a Semi-Empirical Topographic Correction Model for Multi-Source Satellite Images

Science.gov (United States)

Xiao, Sa; Tian, Xinpeng; Liu, Qiang; Wen, Jianguang; Ma, Yushuang; Song, Zhenwei

2018-04-01

Topographic correction of surface reflectance in rugged terrain areas is the prerequisite for the quantitative application of remote sensing in mountainous areas. Physics-based radiative transfer model can be applied to correct the topographic effect and accurately retrieve the reflectance of the slope surface from high quality satellite image such as Landsat8 OLI. However, as more and more images data available from various of sensors, some times we can not get the accurate sensor calibration parameters and atmosphere conditions which are needed in the physics-based topographic correction model. This paper proposed a semi-empirical atmosphere and topographic corrction model for muti-source satellite images without accurate calibration parameters.Based on this model we can get the topographic corrected surface reflectance from DN data, and we tested and verified this model with image data from Chinese satellite HJ and GF. The result shows that the correlation factor was reduced almost 85 % for near infrared bands and the classification overall accuracy of classification increased 14 % after correction for HJ. The reflectance difference of slope face the sun and face away the sun have reduced after correction.

Detection of jet contrails from satellite images

Science.gov (United States)

Meinert, Dieter

1994-02-01

In order to investigate the influence of modern technology on the world climate it is important to have automatic detection methods for man-induced parameters. In this case the influence of jet contrails on the greenhouse effect shall be investigated by means of images from polar orbiting satellites. Current methods of line recognition and amplification cannot distinguish between contrails and rather sharp edges of natural cirrus or noise. They still rely on human control. Through the combination of different methods from cloud physics, image comparison, pattern recognition, and artificial intelligence we try to overcome this handicap. Here we will present the basic methods applied to each image frame, and list preliminary results derived this way.

GRANULOMETRIC MAPS FROM HIGH RESOLUTION SATELLITE IMAGES

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Catherine Mering

2011-05-01

Full Text Available A new method of land cover mapping from satellite images using granulometric analysis is presented here. Discontinuous landscapes such as steppian bushes of semi arid regions and recently growing urban settlements are especially concerned by this study. Spatial organisations of the land cover are quantified by means of the size distribution analysis of the land cover units extracted from high resolution remotely sensed images. A granulometric map is built by automatic classification of every pixel of the image according to the granulometric density inside a sliding neighbourhood. Granulometric mapping brings some advantages over traditional thematic mapping by remote sensing by focusing on fine spatial events and small changes in one peculiar category of the landscape.

Contribution of visuospatial attention, short-term memory and executive functions to performance in number interval bisection.

Science.gov (United States)

Ranzini, Mariagrazia; Carbè, Katia; Gevers, Wim

2017-05-01

Number interval bisection consists of estimating the mid-number within a pair (1-9=>5). Healthy adults and right-brain damage patients can show biased performance in this task, underestimating and overestimating the mid-number, respectively. The role of visuospatial attention during this task, and its interplay with other cognitive abilities (e.g., working memory) is still object of debate. In this study we explored the relation between visuospatial attention and individual differences in working memory and executive functions during number interval bisection. To manipulate the deployment of visuospatial attention, healthy participants tracked a dot moving to the left or moving to the right while bisecting numerical intervals. We also collected information concerning verbal and visuospatial short-term memory span, and concerning verbal and visuospatial fluency scores. Beside replicating what is typically observed in this task (e.g., underestimation bias), a correlation was observed between verbal short-term memory and bisection bias, and an interesting relation between performance in the number interval bisection, verbal short-term memory, and visuospatial attention. Specifically, performance of those participants with low verbal span was affected by the direction of the moving dot, underestimating at a larger extent when the dot moved leftward than rightward. Finally, it was also observed that participants' verbal fluency ability contributed in the generation of biases in the numerical task. The finding of the involvement of abilities belonging to the verbal domain contributes to unveil the multi-componential nature of number interval bisection. Considering the debate on the nature of number interval bisection and its use in the clinical assessment of deficits following brain damage, this finding may be interesting also from a clinical perspective. Copyright © 2017 Elsevier Ltd. All rights reserved.

METEOROLOGICAL SATELLITE IMAGES IN GEOGRAPHY CLASSES: a didactic possibility

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Diego Correia Maia

2016-01-01

Full Text Available ABSTRACT: The satellite images are still largely unexplored as didactic resource in geography classes, particularly about meteorology. This article aims to contribute to the development of new methodologies of interpretation and understanding, beyond the construction of pedagogical practices involving meteorological satellite images, concepts and issues related to climate issues. The aim of this paper is to present possibilities for the use of meteorological satellite images in the Teaching of Geography, aiming the promoting and the understanding of contents of air masses and fronts and climatic factors. RESUMO: As imagens de satélite ainda são pouco exploradas como recurso didático nas aulas de Geografia, principalmente aquelas relativas à meteorologia. Este artigo visa contribuir com o desenvolvimento de novas metodologias de interpretação e compreensão, além da construção de práticas pedagógicas envolvendo imagens de satélite meteorológico, conceitos e temas ligados às questões climáticas. Seu objetivo é apresentar possibilidades de utilização das imagens de satélite meteorológico no Ensino de Geografia, visando à promoção e ao entendimento dos conteúdos de massas de ar e frentes e de elementos climáticos. Palavras chave

TAREAN: a computational tool for identification and characterization of satellite DNA from unassembled short reads.

Science.gov (United States)

Novák, Petr; Ávila Robledillo, Laura; Koblížková, Andrea; Vrbová, Iva; Neumann, Pavel; Macas, Jirí

2017-07-07

Satellite DNA is one of the major classes of repetitive DNA, characterized by tandemly arranged repeat copies that form contiguous arrays up to megabases in length. This type of genomic organization makes satellite DNA difficult to assemble, which hampers characterization of satellite sequences by computational analysis of genomic contigs. Here, we present tandem repeat analyzer (TAREAN), a novel computational pipeline that circumvents this problem by detecting satellite repeats directly from unassembled short reads. The pipeline first employs graph-based sequence clustering to identify groups of reads that represent repetitive elements. Putative satellite repeats are subsequently detected by the presence of circular structures in their cluster graphs. Consensus sequences of repeat monomers are then reconstructed from the most frequent k-mers obtained by decomposing read sequences from corresponding clusters. The pipeline performance was successfully validated by analyzing low-pass genome sequencing data from five plant species where satellite DNA was previously experimentally characterized. Moreover, novel satellite repeats were predicted for the genome of Vicia faba and three of these repeats were verified by detecting their sequences on metaphase chromosomes using fluorescence in situ hybridization. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Detecting Landscape Disturbance at the Nasca Lines Using SAR Data Collected from Airborne and Satellite Platforms

Directory of Open Access Journals (Sweden)

Douglas C. Comer

2017-10-01

Full Text Available We used synthetic aperture radar (SAR data collected over Peru’s Lines and Geoglyphs of the Nasca and Palpa World Heritage Site to detect and measure landscape disturbance threatening world-renowned archaeological features and ecosystems. We employed algorithms to calculate correlations between pairs of SAR returns, collected at different times, and generate correlation images. Landscape disturbances even on the scale of pedestrian travel are discernible in correlation images generated from airborne, L-band SAR. Correlation images derived from C-band SAR data collected by the European Space Agency’s Sentinel-1 satellites also provide detailed landscape change information. Because the two Sentinel-1 satellites together have a repeat pass interval that can be as short as six days, products derived from their data can not only provide information on the location and degree of ground disturbance, but also identify a time window of about one to three weeks during which disturbance must have occurred. For Sentinel-1, this does not depend on collecting data in fine-beam modes, which generally sacrifice the size of the area covered for a higher spatial resolution. We also report on pixel value stretching for a visual analysis of SAR data, quantitative assessment of landscape disturbance, and statistical testing for significant landscape change.

Geostationary Satellite (GOES) Images

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Visible and Infrared satellite imagery taken from radiometer instruments on SMS (ATS) and GOES satellites in geostationary orbit. These satellites produced...

A short introduction to image analysis - Matlab exercises

DEFF Research Database (Denmark)

Hansen, Michael Adsetts Edberg

2000-01-01

This document contain a short introduction to Image analysis. In addition small exercises has been prepared in order to support the theoretical understanding.......This document contain a short introduction to Image analysis. In addition small exercises has been prepared in order to support the theoretical understanding....

Autonomous Planetary 3-D Reconstruction From Satellite Images

DEFF Research Database (Denmark)

Denver, Troelz

1999-01-01

is discussed.Based on such features, 3-D representations may be compiled from two or more 2-D satellite images. The main purposes of such a mapping system are extraction of landing sites, objects of scientific interest and general planetary surveying. All data processing is performed autonomously onboard...

AUTOMATIC CLOUD DETECTION FROM MULTI-TEMPORAL SATELLITE IMAGES: TOWARDS THE USE OF PLÉIADES TIME SERIES

Directory of Open Access Journals (Sweden)

N. Champion

2012-08-01

Full Text Available Contrary to aerial images, satellite images are often affected by the presence of clouds. Identifying and removing these clouds is one of the primary steps to perform when processing satellite images, as they may alter subsequent procedures such as atmospheric corrections, DSM production or land cover classification. The main goal of this paper is to present the cloud detection approach, developed at the French Mapping agency. Our approach is based on the availability of multi-temporal satellite images (i.e. time series that generally contain between 5 and 10 images and is based on a region-growing procedure. Seeds (corresponding to clouds are firstly extracted through a pixel-to-pixel comparison between the images contained in time series (the presence of a cloud is here assumed to be related to a high variation of reflectance between two images. Clouds are then delineated finely using a dedicated region-growing algorithm. The method, originally designed for panchromatic SPOT5-HRS images, is tested in this paper using time series with 9 multi-temporal satellite images. Our preliminary experiments show the good performances of our method. In a near future, the method will be applied to Pléiades images, acquired during the in-flight commissioning phase of the satellite (launched at the end of 2011. In that context, this is a particular goal of this paper to show to which extent and in which way our method can be adapted to this kind of imagery.

Advantages of Hybrid Global Navigation Satellite Systems

Directory of Open Access Journals (Sweden)

Asim Bilajbegović

2007-05-01

Full Text Available In a decision-making situation, what kind of GPS equipment to purchase, one always has a dilemma, tobuy hybrid (GPS+GLONASS or only GPS receivers? In the case of completeness of the GLONASS satellite system, this dilemma probably would not have existed. The answer to this dilemma is given in the present paper, but for the constellation of the GLONASS satellites in summer 2006 (14 satellites operational. Due to the short operational period of these satellites (for example GLONASS-M, 5 years, and not launching new ones, at this moment (February 25, 2007, only 10 satellites are operational. For the sake of research and giving answers to these questions, about 252 RTK measurements have been done using (GPS and GNSS receivers, on points with different obstructions of horizon. Besides that, initialisation time has been investigated for both systems from about 480 measurements, using rover's antenna with metal cover, during a time interval of 0.5, 2 and 5 seconds. Moreover, accuracy, firmware declared accuracy and redundancy of GPS and GNSS RTK measurements have been investigating.  

Geomorphology of coastal environments from satellite images

International Nuclear Information System (INIS)

Da Rocha Ribeiro, R.; Velho, L.; Schossler, V.

2010-01-01

This study aims at recognizing coastal environments supported by data from the Landsat Thematic Mapper (TM) satellite. The digital processing of images, System Information Geographic (SIG) techniques and field observation in one section of the “Província Costeira do Rio Grande do Sul” between the Rio Grande and the São Gonçalo channels - resulted in a geomorphologic profile and mapping

Multi sensor satellite imagers for commercial remote sensing

Science.gov (United States)

Cronje, T.; Burger, H.; Du Plessis, J.; Du Toit, J. F.; Marais, L.; Strumpfer, F.

2005-10-01

This paper will discuss and compare recent refractive and catodioptric imager designs developed and manufactured at SunSpace for Multi Sensor Satellite Imagers with Panchromatic, Multi-spectral, Area and Hyperspectral sensors on a single Focal Plane Array (FPA). These satellite optical systems were designed with applications to monitor food supplies, crop yield and disaster monitoring in mind. The aim of these imagers is to achieve medium to high resolution (2.5m to 15m) spatial sampling, wide swaths (up to 45km) and noise equivalent reflectance (NER) values of less than 0.5%. State-of-the-art FPA designs are discussed and address the choice of detectors to achieve these performances. Special attention is given to thermal robustness and compactness, the use of folding prisms to place multiple detectors in a large FPA and a specially developed process to customize the spectral selection with the need to minimize mass, power and cost. A refractive imager with up to 6 spectral bands (6.25m GSD) and a catodioptric imager with panchromatic (2.7m GSD), multi-spectral (6 bands, 4.6m GSD), hyperspectral (400nm to 2.35μm, 200 bands, 15m GSD) sensors on the same FPA will be discussed. Both of these imagers are also equipped with real time video view finding capabilities. The electronic units could be subdivided into the Front-End Electronics and Control Electronics with analogue and digital signal processing. A dedicated Analogue Front-End is used for Correlated Double Sampling (CDS), black level correction, variable gain and up to 12-bit digitizing and high speed LVDS data link to a mass memory unit.

Magnetic resonance imaging findings associated with surgically proven rotator interval lesions

Energy Technology Data Exchange (ETDEWEB)

Vinson, Emily N.; Major, Nancy M. [Duke University Medical Center, Department of Radiology, P.O. Box 3808, Durham, NC (United States); Higgins, Laurence D. [Brigham and Women' s Hospital, Department of Orthopedic Surgery, Boston, MA (United States)

2007-05-15

To identify shoulder magnetic resonance imaging (MRI) findings associated with surgically proven rotator interval abnormalities. The preoperative MRI examinations of five patients with surgically proven rotator interval (RI) lesions requiring closure were retrospectively evaluated by three musculoskeletal-trained radiologists in consensus. We assessed the structures in the RI, including the coracohumeral ligament, superior glenohumeral ligament, fat tissue, biceps tendon, and capsule for variations in size and signal alteration. In addition, we noted associated findings of rotator cuff and labral pathology. Three of three of the MR arthrogram studies demonstrated extension of gadolinium to the cortex of the undersurface of the coracoid process compared with the control images, seen best on the sagittal oblique images. Four of five of the studies demonstrated subjective thickening of the coracohumeral ligament, and three of five of the studies demonstrated subjective thickening of the superior glenohumeral ligament. Five of five of the studies demonstrated a labral tear. The MRI arthrogram finding of gadolinium extending to the cortex of the undersurface of the coracoid process was noted on the studies of those patients with rotator interval lesions at surgery in this series. Noting this finding - especially in the presence of a labral tear and/or thickening of the coracohumeral ligament or superior glenohumeral ligament - may be helpful in the preoperative diagnosis of rotator interval lesions. (orig.)

A note on a kind of character sums over the short interval

Indian Academy of Sciences (India)

Abstract. Let p be a prime, χ denote the Dirichlet character modulo p and L(p) = {a ∈ Z+|(a, p) = 1, a¯a ≡ 1(mod p), |a − ¯a| ≤ H}. We study the distribution of elements in the set L(p) in character over the short interval. In this paper, we use the analytic method and show the distribution property of. ∑ n≤N n∈L(p) χ(n),.

Global satellite analysis of the relation between aerosols and short-lived trace gases

NARCIS (Netherlands)

Veefkind, J.P.; Boersma, K.F.; Wang, J.; Kurosu, T.; Chance, K.; Krotkov, N.A.; Levelt, P.F.

2011-01-01

The spatial and temporal correlations between concurrent satellite observations of aerosol optical thickness (AOT) from the Moderate Resolution Imaging Spectroradiometer (MODIS) and tropospheric columns of nitrogen dioxide (NO2), sulfur dioxide (SO2), and formaldehyde (HCHO) from the Ozone

Remote diagnosis via a telecommunication satellite--ultrasonic tomographic image transmission experiments.

Science.gov (United States)

Nakajima, I; Inokuchi, S; Tajima, T; Takahashi, T

1985-04-01

An experiment to transmit ultrasonic tomographic section images required for remote medical diagnosis and care was conducted using the mobile telecommunication satellite OSCAR-10. The images received showed the intestinal condition of a patient incapable of verbal communication, however the image screen had a fairly coarse particle structure. On the basis of these experiments, were considered as the transmission of ultrasonic tomographic images extremely effective in remote diagnosis.

An Improved Image Encryption Algorithm Based on Cyclic Rotations and Multiple Chaotic Sequences: Application to Satellite Images

Directory of Open Access Journals (Sweden)

MADANI Mohammed

2017-10-01

Full Text Available In this paper, a new satellite image encryption algorithm based on the combination of multiple chaotic systems and a random cyclic rotation technique is proposed. Our contribution consists in implementing three different chaotic maps (logistic, sine, and standard combined to improve the security of satellite images. Besides enhancing the encryption, the proposed algorithm also focuses on advanced efficiency of the ciphered images. Compared with classical encryption schemes based on multiple chaotic maps and the Rubik's cube rotation, our approach has not only the same merits of chaos systems like high sensitivity to initial values, unpredictability, and pseudo-randomness, but also other advantages like a higher number of permutations, better performances in Peak Signal to Noise Ratio (PSNR and a Maximum Deviation (MD.

Cardiac Time Intervals by Tissue Doppler Imaging M-Mode

DEFF Research Database (Denmark)

Biering-Sørensen, Tor; Mogelvang, Rasmus; de Knegt, Martina Chantal

2016-01-01

PURPOSE: To define normal values of the cardiac time intervals obtained by tissue Doppler imaging (TDI) M-mode through the mitral valve (MV). Furthermore, to evaluate the association of the myocardial performance index (MPI) obtained by TDI M-mode (MPITDI) and the conventional method of obtaining...

An Investigation on Water Quality of Darlik Dam Drinking Water using Satellite Images

Directory of Open Access Journals (Sweden)

Erhan Alparslan

2010-01-01

Full Text Available Darlik Dam supplies 15% of the water demand of Istanbul Metropolitan City of Turkey. Water quality (WQ in the Darlik Dam was investigated from Landsat 5 TM satellite images of the years 2004, 2005, and 2006 in order to determine land use/land cover changes in the watershed of the dam that may deteriorate its WQ. The images were geometrically and atmospherically corrected for WQ analysis. Next, an investigation was made by multiple regression analysis between the unitless planetary reflectance values of the first four bands of the June 2005 Landsat TM image of the dam and WQ parameters, such as chlorophyll-a, total dissolved matter, turbidity, total phosphorous, and total nitrogen, measured at satellite image acquisition time at seven stations in the dam. Finally, WQ in the dam was studied from satellite images of the years 2004, 2005, and 2006 by pattern recognition techniques in order to determine possible water pollution in the dam. This study was compared to a previous study done by the authors in the Küçükçekmece water reservoir, also in Istanbul City.

Automatic Registration Method for Fusion of ZY-1-02C Satellite Images

Directory of Open Access Journals (Sweden)

Qi Chen

2013-12-01

Full Text Available Automatic image registration (AIR has been widely studied in the fields of medical imaging, computer vision, and remote sensing. In various cases, such as image fusion, high registration accuracy should be achieved to meet application requirements. For satellite images, the large image size and unstable positioning accuracy resulting from the limited manufacturing technology of charge-coupled device, focal plane distortion, and unrecorded spacecraft jitter lead to difficulty in obtaining agreeable corresponding points for registration using only area-based matching or feature-based matching. In this situation, a coarse-to-fine matching strategy integrating two types of algorithms is proven feasible and effective. In this paper, an AIR method for application to the fusion of ZY-1-02C satellite imagery is proposed. First, the images are geometrically corrected. Coarse matching, based on scale invariant feature transform, is performed for the subsampled corrected images, and a rough global estimation is made with the matching results. Harris feature points are then extracted, and the coordinates of the corresponding points are calculated according to the global estimation results. Precise matching is conducted, based on normalized cross correlation and least squares matching. As complex image distortion cannot be precisely estimated, a local estimation using the structure of triangulated irregular network is applied to eliminate the false matches. Finally, image resampling is conducted, based on local affine transformation, to achieve high-precision registration. Experiments with ZY-1-02C datasets demonstrate that the accuracy of the proposed method meets the requirements of fusion application, and its efficiency is also suitable for the commercial operation of the automatic satellite data process system.

Automatic Detection of Clouds and Shadows Using High Resolution Satellite Image Time Series

Science.gov (United States)

Champion, Nicolas

2016-06-01

Detecting clouds and their shadows is one of the primaries steps to perform when processing satellite images because they may alter the quality of some products such as large-area orthomosaics. The main goal of this paper is to present the automatic method developed at IGN-France for detecting clouds and shadows in a sequence of satellite images. In our work, surface reflectance orthoimages are used. They were processed from initial satellite images using a dedicated software. The cloud detection step consists of a region-growing algorithm. Seeds are firstly extracted. For that purpose and for each input ortho-image to process, we select the other ortho-images of the sequence that intersect it. The pixels of the input ortho-image are secondly labelled seeds if the difference of reflectance (in the blue channel) with overlapping ortho-images is bigger than a given threshold. Clouds are eventually delineated using a region-growing method based on a radiometric and homogeneity criterion. Regarding the shadow detection, our method is based on the idea that a shadow pixel is darker when comparing to the other images of the time series. The detection is basically composed of three steps. Firstly, we compute a synthetic ortho-image covering the whole study area. Its pixels have a value corresponding to the median value of all input reflectance ortho-images intersecting at that pixel location. Secondly, for each input ortho-image, a pixel is labelled shadows if the difference of reflectance (in the NIR channel) with the synthetic ortho-image is below a given threshold. Eventually, an optional region-growing step may be used to refine the results. Note that pixels labelled clouds during the cloud detection are not used for computing the median value in the first step; additionally, the NIR input data channel is used to perform the shadow detection, because it appeared to better discriminate shadow pixels. The method was tested on times series of Landsat 8 and Pl

AUTOMATIC DETECTION OF CLOUDS AND SHADOWS USING HIGH RESOLUTION SATELLITE IMAGE TIME SERIES

Directory of Open Access Journals (Sweden)

N. Champion

2016-06-01

Full Text Available Detecting clouds and their shadows is one of the primaries steps to perform when processing satellite images because they may alter the quality of some products such as large-area orthomosaics. The main goal of this paper is to present the automatic method developed at IGN-France for detecting clouds and shadows in a sequence of satellite images. In our work, surface reflectance orthoimages are used. They were processed from initial satellite images using a dedicated software. The cloud detection step consists of a region-growing algorithm. Seeds are firstly extracted. For that purpose and for each input ortho-image to process, we select the other ortho-images of the sequence that intersect it. The pixels of the input ortho-image are secondly labelled seeds if the difference of reflectance (in the blue channel with overlapping ortho-images is bigger than a given threshold. Clouds are eventually delineated using a region-growing method based on a radiometric and homogeneity criterion. Regarding the shadow detection, our method is based on the idea that a shadow pixel is darker when comparing to the other images of the time series. The detection is basically composed of three steps. Firstly, we compute a synthetic ortho-image covering the whole study area. Its pixels have a value corresponding to the median value of all input reflectance ortho-images intersecting at that pixel location. Secondly, for each input ortho-image, a pixel is labelled shadows if the difference of reflectance (in the NIR channel with the synthetic ortho-image is below a given threshold. Eventually, an optional region-growing step may be used to refine the results. Note that pixels labelled clouds during the cloud detection are not used for computing the median value in the first step; additionally, the NIR input data channel is used to perform the shadow detection, because it appeared to better discriminate shadow pixels. The method was tested on times series of Landsat 8

Foodstuff survey around a major nuclear facility with test of satellite images application

International Nuclear Information System (INIS)

Twining, S.; Strydom, J.; Rosson, R.; Koffman, L.; Fledderman, P.; Kahn, B.

2000-01-01

A foodstuff survey was performed around the Savannah River Site, Aiken, South Carolina. It included a census of buildings and fields within 5 km of the boundary and determination of the locations and amounts of crops grown within 80 km of the Savannah River Site center. Recent information for this region was collected on the amounts of meat, poultry, milk, and eggs produced, of deer hunted, and of sports fish caught. The locations and areas devoted to growing each crop were determined by the usual process of applying county agricultural statistics reported by state agencies. This process was compared to crop analysis of two LANDSAT Thematic Mapper images. For use with environmental radionuclide transfer and radiation dose calculation codes, locations within 80 km were defined for 64 sections by 16 sectors centered on the site and by 16-km distance intervals from 16 km to 80 km. The median areas per section devoted to each of four food crops based on county agricultural statistics were about two-thirds of those based on satellite image analysis. Most locally-raised foodstuff was distributed regionally and not retained locally for consumption

Global Solar Radiation in Spain from Satellite Images

International Nuclear Information System (INIS)

Ramirez, L.; Mora, L.; Sidrach de Cardona, M.; Navarro, A. A.; Varela, M.; Cruz, M. de la

2003-01-01

In the context of the present work a series of algorithms of calculation of the solar radiation from satellite images has been developed. These models, have been applied to three years of images of the Meteosat satellite and the results of the treatment have been extrapolated to long term. For the development of the models of solar radiation registered in ground stations have been used, corresponding all of them to localities of peninsular Spain and the Balearic ones. The maximum periods of data available have been used, supposing in most of the cases periods of between 6 and 9 years. From the results has a year type of images of global solar radiation on horizontal surface. The original resolution of the image of 7x7 km in the study latitudes, has been reevaluated to 5x5 km. This supposes to have a value of the typical radiation for every day of the year, each 5x5 km in the study territory. This information, supposes an important advance as far as the knowledge of the space distribution of the radiation solar, impossible to reach about alternative methods. Doubtlessly, the precision of the provided values is not comparable with pyrano metric measures in a concrete locality, but it provides a very valid indicator in places in which it is not had previous information. In addition to the radiation maps, tables of the global solar radiation have been prepared on different inclinations, from the global radiation on horizontal surface calculated for every day of the year and in each pixel of the image. (Author) 24 refs

Analysis of Decadal Vegetation Dynamics Using Multi-Scale Satellite Images

Science.gov (United States)

Chiang, Y.; Chen, K.

2013-12-01

This study aims at quantifying vegetation fractional cover (VFC) by incorporating multi-resolution satellite images, including Formosat-2(RSI), SPOT(HRV/HRG), Landsat (MSS/TM) and Terra/Aqua(MODIS), to investigate long-term and seasonal vegetation dynamics in Taiwan. We used 40-year NDVI records for derivation of VFC, with field campaigns routinely conducted to calibrate the critical NDVI threshold. Given different sensor capabilities in terms of their spatial and spectral properties, translation and infusion of NDVIs was used to assure NDVI coherence and to determine the fraction of vegetation cover at different spatio-temporal scales. Based on the proposed method, a bimodal sequence of intra-annual VFC which corresponds to the dual-cropping agriculture pattern was observed. Compared to seasonal VFC variation (78~90%), decadal VFC reveals moderate oscillations (81~86%), which were strongly linked with landuse changes and several major disturbances. This time-series mapping of VFC can be used to examine vegetation dynamics and its response associated with short-term and long-term anthropogenic/natural events.

AUTOMATED CONSTRUCTION OF COVERAGE CATALOGUES OF ASTER SATELLITE IMAGE FOR URBAN AREAS OF THE WORLD

Directory of Open Access Journals (Sweden)

H. Miyazaki

2012-07-01

Full Text Available We developed an algorithm to determine a combination of satellite images according to observation extent and image quality. The algorithm was for testing necessity for completing coverage of the search extent. The tests excluded unnecessary images with low quality and preserve necessary images with good quality. The search conditions of the satellite images could be extended, indicating the catalogue could be constructed with specified periods required for time series analysis. We applied the method to a database of metadata of ASTER satellite images archived in GEO Grid of National Institute of Advanced Industrial Science and Technology (AIST, Japan. As indexes of populated places with geographical coordinates, we used a database of 3372 populated place of more than 0.1 million populations retrieved from GRUMP Settlement Points, a global gazetteer of cities, which has geographical names of populated places associated with geographical coordinates and population data. From the coordinates of populated places, 3372 extents were generated with radiuses of 30 km, a half of swath of ASTER satellite images. By merging extents overlapping each other, they were assembled into 2214 extents. As a result, we acquired combinations of good quality for 1244 extents, those of low quality for 96 extents, incomplete combinations for 611 extents. Further improvements would be expected by introducing pixel-based cloud assessment and pixel value correction over seasonal variations.

Short-term memory in zebrafish (Danio rerio).

Science.gov (United States)

Jia, Jason; Fernandes, Yohaan; Gerlai, Robert

2014-08-15

Learning and memory represent perhaps the most complex behavioral phenomena. Although their underlying mechanisms have been extensively analyzed, only a fraction of the potential molecular components have been identified. The zebrafish has been proposed as a screening tool with which mechanisms of complex brain functions may be systematically uncovered. However, as a relative newcomer in behavioral neuroscience, the zebrafish has not been well characterized for its cognitive and mnemonic features, thus learning and/or memory screens with adults have not been feasible. Here we study short-term memory of adult zebrafish. We show animated images of conspecifics (the stimulus) to the experimental subject during 1 min intervals on ten occasions separated by different (2, 4, 8 or 16 min long) inter-stimulus intervals (ISI), a between subject experimental design. We quantify the distance of the subject from the image presentation screen during each stimulus presentation interval, during each of the 1-min post-stimulus intervals immediately following the stimulus presentations and during each of the 1-min intervals furthest away from the last stimulus presentation interval and just before the next interval (pre-stimulus interval), respectively. Our results demonstrate significant retention of short-term memory even in the longest ISI group but suggest no acquisition of reference memory. Because in the employed paradigm both stimulus presentation and behavioral response quantification is computer automated, we argue that high-throughput screening for drugs or mutations that alter short-term memory performance of adult zebrafish is now becoming feasible. Copyright © 2014 Elsevier B.V. All rights reserved.

Robust Short-Lag Spatial Coherence Imaging.

Science.gov (United States)

Nair, Arun Asokan; Tran, Trac Duy; Bell, Muyinatu A Lediju

2018-03-01

Short-lag spatial coherence (SLSC) imaging displays the spatial coherence between backscattered ultrasound echoes instead of their signal amplitudes and is more robust to noise and clutter artifacts when compared with traditional delay-and-sum (DAS) B-mode imaging. However, SLSC imaging does not consider the content of images formed with different lags, and thus does not exploit the differences in tissue texture at each short-lag value. Our proposed method improves SLSC imaging by weighting the addition of lag values (i.e., M-weighting) and by applying robust principal component analysis (RPCA) to search for a low-dimensional subspace for projecting coherence images created with different lag values. The RPCA-based projections are considered to be denoised versions of the originals that are then weighted and added across lags to yield a final robust SLSC (R-SLSC) image. Our approach was tested on simulation, phantom, and in vivo liver data. Relative to DAS B-mode images, the mean contrast, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) improvements with R-SLSC images are 21.22 dB, 2.54, and 2.36, respectively, when averaged over simulated, phantom, and in vivo data and over all lags considered, which corresponds to mean improvements of 96.4%, 121.2%, and 120.5%, respectively. When compared with SLSC images, the corresponding mean improvements with R-SLSC images were 7.38 dB, 1.52, and 1.30, respectively (i.e., mean improvements of 14.5%, 50.5%, and 43.2%, respectively). Results show great promise for smoothing out the tissue texture of SLSC images and enhancing anechoic or hypoechoic target visibility at higher lag values, which could be useful in clinical tasks such as breast cyst visualization, liver vessel tracking, and obese patient imaging.

V-SIPAL - A VIRTUAL LABORATORY FOR SATELLITE IMAGE PROCESSING AND ANALYSIS

Directory of Open Access Journals (Sweden)

K. M. Buddhiraju

2012-09-01

Full Text Available In this paper a virtual laboratory for the Satellite Image Processing and Analysis (v-SIPAL being developed at the Indian Institute of Technology Bombay is described. v-SIPAL comprises a set of experiments that are normally carried out by students learning digital processing and analysis of satellite images using commercial software. Currently, the experiments that are available on the server include Image Viewer, Image Contrast Enhancement, Image Smoothing, Edge Enhancement, Principal Component Transform, Texture Analysis by Co-occurrence Matrix method, Image Indices, Color Coordinate Transforms, Fourier Analysis, Mathematical Morphology, Unsupervised Image Classification, Supervised Image Classification and Accuracy Assessment. The virtual laboratory includes a theory module for each option of every experiment, a description of the procedure to perform each experiment, the menu to choose and perform the experiment, a module on interpretation of results when performed with a given image and pre-specified options, bibliography, links to useful internet resources and user-feedback. The user can upload his/her own images for performing the experiments and can also reuse outputs of one experiment in another experiment where applicable. Some of the other experiments currently under development include georeferencing of images, data fusion, feature evaluation by divergence andJ-M distance, image compression, wavelet image analysis and change detection. Additions to the theory module include self-assessment quizzes, audio-video clips on selected concepts, and a discussion of elements of visual image interpretation. V-SIPAL is at the satge of internal evaluation within IIT Bombay and will soon be open to selected educational institutions in India for evaluation.

Prospects of application of survey satellite image for meteorology

Science.gov (United States)

Kapochkina, A. B.; Kapochkin, B. B.; Kucherenko, N. V.

The maximal interest is represented with the information from geostationary satellites. These satellites repeat shootings the chosen territories, allowing to study dynamics of images. Most interesting shootings in IR a range. Studying of survey image is applied to studying linear elements of clouds (LEC). It is established, that "LEC " arise only above breaks of an earth's crust. In research results of the complex analysis of the satellite data, hydrometeorological supervision, seismicity, supervision over deformations of a surface of the Earth are used. It is established that before formation "LEC " in a ground layer arise anomalies of temperature and humidity. The situation above Europe 16 May, 2001 is considered. "LEC " in Europe block carry of air weights from the west to the east. Synoptic conditions above the Great Britain July, 7-10, 2000 is considered. Moving "LEC" trace distribution of deformation waves to an earth's crust. Satellite shootings Europe before earthquake in Greece 14.08.2003 are considered. These days ground supervision were conducted and the data of the geostationary satellite were analyzed. During moving "LEC " occur failures (destruction houses & of gas mains), earthquake. The situation above Iberian peninsula 12-16.11.2001 is considered. "LEC" arose before flooding in Europe. The situation before flooding in Germany June, 6-8, 2002 and flooding on the river Kuban June, 16-23, 2002 is considered. In case of occurrence of tectonic compression of an earth's crust there are "LEC ", tracer intensive movements of air upwards and downwards above negative and positive anomalies of the form of a terrestrial surface, accordingly. Such meteorological situations are dangerous to flights of aircraft, the fast gravitational anomalies influencing into orbits of movement of satellites trace. The situation above equatorial Atlantic 26.03.2003 years is considered. At tectonic compression of continental scale overcast covers the whole continents for more

Satellite image time series simulation for environmental monitoring

Science.gov (United States)

Guo, Tao

2014-11-01

The performance of environmental monitoring heavily depends on the availability of consecutive observation data and it turns out an increasing demand in remote sensing community for satellite image data in the sufficient resolution with respect to both spatial and temporal requirements, which appear to be conflictive and hard to tune tradeoffs. Multiple constellations could be a solution if without concerning cost, and thus it is so far interesting but very challenging to develop a method which can simultaneously improve both spatial and temporal details. There are some research efforts to deal with the problem from various aspects, a type of approaches is to enhance the spatial resolution using techniques of super resolution, pan-sharpen etc. which can produce good visual effects, but mostly cannot preserve spectral signatures and result in losing analytical value. Another type is to fill temporal frequency gaps by adopting time interpolation, which actually doesn't increase informative context at all. In this paper we presented a novel method to generate satellite images in higher spatial and temporal details, which further enables satellite image time series simulation. Our method starts with a pair of high-low resolution data set, and then a spatial registration is done by introducing LDA model to map high and low resolution pixels correspondingly. Afterwards, temporal change information is captured through a comparison of low resolution time series data, and the temporal change is then projected onto high resolution data plane and assigned to each high resolution pixel referring the predefined temporal change patterns of each type of ground objects to generate a simulated high resolution data. A preliminary experiment shows that our method can simulate a high resolution data with a good accuracy. We consider the contribution of our method is to enable timely monitoring of temporal changes through analysis of low resolution images time series only, and usage of

Effects of Per-Pixel Variability on Uncertainties in Bathymetric Retrievals from High-Resolution Satellite Images

Directory of Open Access Journals (Sweden)

Elizabeth J. Botha

2016-05-01

Full Text Available Increased sophistication of high spatial resolution multispectral satellite sensors provides enhanced bathymetric mapping capability. However, the enhancements are counter-acted by per-pixel variability in sunglint, atmospheric path length and directional effects. This case-study highlights retrieval errors from images acquired at non-optimal geometrical combinations. The effects of variations in the environmental noise on water surface reflectance and the accuracy of environmental variable retrievals were quantified. Two WorldView-2 satellite images were acquired, within one minute of each other, with Image 1 placed in a near-optimal sun-sensor geometric configuration and Image 2 placed close to the specular point of the Bidirectional Reflectance Distribution Function (BRDF. Image 2 had higher total environmental noise due to increased surface glint and higher atmospheric path-scattering. Generally, depths were under-estimated from Image 2, compared to Image 1. A partial improvement in retrieval error after glint correction of Image 2 resulted in an increase of the maximum depth to which accurate depth estimations were returned. This case-study indicates that critical analysis of individual images, accounting for the entire sun elevation and azimuth and satellite sensor pointing and geometry as well as anticipated wave height and direction, is required to ensure an image is fit for purpose for aquatic data analysis.

Moving object detection in video satellite image based on deep learning

Science.gov (United States)

Zhang, Xueyang; Xiang, Junhua

2017-11-01

Moving object detection in video satellite image is studied. A detection algorithm based on deep learning is proposed. The small scale characteristics of remote sensing video objects are analyzed. Firstly, background subtraction algorithm of adaptive Gauss mixture model is used to generate region proposals. Then the objects in region proposals are classified via the deep convolutional neural network. Thus moving objects of interest are detected combined with prior information of sub-satellite point. The deep convolution neural network employs a 21-layer residual convolutional neural network, and trains the network parameters by transfer learning. Experimental results about video from Tiantuo-2 satellite demonstrate the effectiveness of the algorithm.

SHADOW DETECTION FROM VERY HIGH RESOLUTON SATELLITE IMAGE USING GRABCUT SEGMENTATION AND RATIO-BAND ALGORITHMS

Directory of Open Access Journals (Sweden)

N. M. S. M. Kadhim

2015-03-01

Full Text Available Very-High-Resolution (VHR satellite imagery is a powerful source of data for detecting and extracting information about urban constructions. Shadow in the VHR satellite imageries provides vital information on urban construction forms, illumination direction, and the spatial distribution of the objects that can help to further understanding of the built environment. However, to extract shadows, the automated detection of shadows from images must be accurate. This paper reviews current automatic approaches that have been used for shadow detection from VHR satellite images and comprises two main parts. In the first part, shadow concepts are presented in terms of shadow appearance in the VHR satellite imageries, current shadow detection methods, and the usefulness of shadow detection in urban environments. In the second part, we adopted two approaches which are considered current state-of-the-art shadow detection, and segmentation algorithms using WorldView-3 and Quickbird images. In the first approach, the ratios between the NIR and visible bands were computed on a pixel-by-pixel basis, which allows for disambiguation between shadows and dark objects. To obtain an accurate shadow candidate map, we further refine the shadow map after applying the ratio algorithm on the Quickbird image. The second selected approach is the GrabCut segmentation approach for examining its performance in detecting the shadow regions of urban objects using the true colour image from WorldView-3. Further refinement was applied to attain a segmented shadow map. Although the detection of shadow regions is a very difficult task when they are derived from a VHR satellite image that comprises a visible spectrum range (RGB true colour, the results demonstrate that the detection of shadow regions in the WorldView-3 image is a reasonable separation from other objects by applying the GrabCut algorithm. In addition, the derived shadow map from the Quickbird image indicates

Shadow Detection from Very High Resoluton Satellite Image Using Grabcut Segmentation and Ratio-Band Algorithms

Science.gov (United States)

Kadhim, N. M. S. M.; Mourshed, M.; Bray, M. T.

2015-03-01

Very-High-Resolution (VHR) satellite imagery is a powerful source of data for detecting and extracting information about urban constructions. Shadow in the VHR satellite imageries provides vital information on urban construction forms, illumination direction, and the spatial distribution of the objects that can help to further understanding of the built environment. However, to extract shadows, the automated detection of shadows from images must be accurate. This paper reviews current automatic approaches that have been used for shadow detection from VHR satellite images and comprises two main parts. In the first part, shadow concepts are presented in terms of shadow appearance in the VHR satellite imageries, current shadow detection methods, and the usefulness of shadow detection in urban environments. In the second part, we adopted two approaches which are considered current state-of-the-art shadow detection, and segmentation algorithms using WorldView-3 and Quickbird images. In the first approach, the ratios between the NIR and visible bands were computed on a pixel-by-pixel basis, which allows for disambiguation between shadows and dark objects. To obtain an accurate shadow candidate map, we further refine the shadow map after applying the ratio algorithm on the Quickbird image. The second selected approach is the GrabCut segmentation approach for examining its performance in detecting the shadow regions of urban objects using the true colour image from WorldView-3. Further refinement was applied to attain a segmented shadow map. Although the detection of shadow regions is a very difficult task when they are derived from a VHR satellite image that comprises a visible spectrum range (RGB true colour), the results demonstrate that the detection of shadow regions in the WorldView-3 image is a reasonable separation from other objects by applying the GrabCut algorithm. In addition, the derived shadow map from the Quickbird image indicates significant performance of

Recurrence of gastroesophageal reflux disease correlated with a short dinner-to-bedtime interval.

Science.gov (United States)

Yang, Jae Hoon; Kang, Ho Suk; Lee, Sun-Young; Kim, Jeong Hwan; Sung, In-Kyung; Park, Hyung Seok; Shim, Chan Sup; Jin, Choon Jo

2014-04-01

Gastroesophageal reflux disease (GERD) can be classified into erosive reflux disease (ERD) and nonerosive gastroesophageal reflux disease (NERD). We aimed to compare the recurrence rates of ERD and NERD and determine the risk factors related to the recurrence. This prospective study comprised 337 consecutive adults who completed questionnaires on their GERD symptoms, height, weight, sleeping position, dinner time, and bedtime. During upper gastrointestinal endoscopy, the presence of a hiatal hernia and mucosal breaks in the low esophagus, esophageal length (the distance between the Z-line and the incisors), and the esophageal length-to-height ratio were recorded. Recurrence was diagnosed when the patient required additional proton pump inhibitor medication after initial recovery with 4-8 weeks of treatment. Recurrence was experienced by 47 (26.0%) of 181 GERD patients. The recurrence rate did not differ between the 48 ERD (27.1%) and 133 NERD (25.6%) patients (P = 0.849). Of the various factors studied, recurrence was found to be correlated with a dinner-to-bedtime interval of less than 3 h (P = 0.002), globus sensation (P = 0.031), and old age (P = 0.047). Logistic regression analysis revealed that a short interval between dinner and bedtime was the only factor significantly related to the recurrence (P = 0.002). Both ERD and NERD patients who sleep within 3 h after eating have a higher risk of GERD recurrence. Our findings highlight the impact of a short dinner-to-bedtime interval on the recurrence of GERD (ClinicalTrials.gov ID: KCT0000134). © 2013 Journal of Gastroenterology and Hepatology Foundation and Wiley Publishing Asia Pty Ltd.

Prediction of GNSS satellite clocks

International Nuclear Information System (INIS)

Broederbauer, V.

2010-01-01

interval 2-3 ns are obtained. This represents a distance-error of 60-90 cm. A comparison of the results from GNSS-VC/static to the predicted Ultra-Rapid-clocks of the ACs of the IGS confirms the very good quality of our clock solution which is at the level of the best AC solutions. The use of GNSS-VC/static for GLONASS-satellite-clocks is problematic. The GLONASS satellite clocks show a hard to characterize behaviour covering a number of jumps and breaks in the time-series within just a few hours. Therefore the prediction of GLONASS-satellite-clocks seems not reasonable at this time. In view of more stable clocks upcoming with the new GLONASS satellite generation K a similar model as used to characterize the GPS Rubidium clock might be applicable. The results of GNSS-VC/static are affected by a three-hours-delay. Thus an almost real-time solution to obtain high quality clock predictions has been established in parallel. The programme GNSS-VC/kalman enables to evaluate the parameters of the prediction-model by a Kalman-filter approach. Because of the short prediction-interval of just six hours the model is reduced to a simple quadratic polynomial. Input-data are RT-clock-corrections evaluated with the programme RTR-Control [Opitz, 2010] based on the observation data provided by the IGS-RT project. The clock correction polynomial coefficients are estimated every minute. After an initialization period of the filter (about 30 minutes) the mean error of the polynomial parameters as well as the evaluated clock corrections is below 2 ns for most of the satellite clock (author) [de

Polar-Orbiting Satellite (POES) Images

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Visible and Infrared satellite imagery taken from camera systems or radiometer instruments on satellites in orbit around the poles. Satellite campaigns include...

3D reconstruction from multi-view VHR-satellite images in MicMac

Science.gov (United States)

Rupnik, Ewelina; Pierrot-Deseilligny, Marc; Delorme, Arthur

2018-05-01

This work addresses the generation of high quality digital surface models by fusing multiple depths maps calculated with the dense image matching method. The algorithm is adapted to very high resolution multi-view satellite images, and the main contributions of this work are in the multi-view fusion. The algorithm is insensitive to outliers, takes into account the matching quality indicators, handles non-correlated zones (e.g. occlusions), and is solved with a multi-directional dynamic programming approach. No geometric constraints (e.g. surface planarity) or auxiliary data in form of ground control points are required for its operation. Prior to the fusion procedures, the RPC geolocation parameters of all images are improved in a bundle block adjustment routine. The performance of the algorithm is evaluated on two VHR (Very High Resolution)-satellite image datasets (Pléiades, WorldView-3) revealing its good performance in reconstructing non-textured areas, repetitive patterns, and surface discontinuities.

NETWORK DESIGN IN CLOSE-RANGE PHOTOGRAMMETRY WITH SHORT BASELINE IMAGES

Directory of Open Access Journals (Sweden)

L. Barazzetti

2017-08-01

Full Text Available The avaibility of automated software for image-based 3D modelling has changed the way people acquire images for photogrammetric applications. Short baseline images are required to match image points with SIFT-like algorithms, obtaining more images than those necessary for “old fashioned” photogrammetric projects based on manual measurements. This paper describes some considerations on network design for short baseline image sequences, especially on precision and reliability of bundle adjustment. Simulated results reveal that the large number of 3D points used for image orientation has very limited impact on network precision.

Magnetic Resonance Imaging in the measurement of whole body muscle mass: A comparison of interval gap methods

International Nuclear Information System (INIS)

Hellmanns, K.; McBean, K.; Thoirs, K.

2015-01-01

Purpose: Magnetic Resonance Imaging (MRI) is commonly used in body composition research to measure whole body skeletal muscle mass (SM). MRI calculation methods of SM can vary by analysing the images at different slice intervals (or interval gaps) along the length of the body. This study compared SM measurements made from MRI images of apparently healthy individuals using different interval gap methods to determine the error associated with each technique. It was anticipated that the results would inform researchers of optimum interval gap measurements to detect a predetermined minimum change in SM. Methods: A method comparison study was used to compare eight interval gap methods (interval gaps of 40, 50, 60, 70, 80, 100, 120 and 140 mm) against a reference 10 mm interval gap method for measuring SM from twenty MRI image sets acquired from apparently healthy participants. Pearson product-moment correlation analysis was used to determine the association between methods. Total error was calculated as the sum of the bias (systematic error) and the random error (limits of agreement) of the mean differences. Percentage error was used to demonstrate proportional error. Results: Pearson product-moment correlation analysis between the reference method and all interval gap methods demonstrated strong and significant associations (r > 0.99, p < 0.0001). The 40 mm interval gap method was comparable with the 10 mm interval reference method and had a low error (total error 0.95 kg, −3.4%). Analysis methods using wider interval gap techniques demonstrated larger errors than reported for dual-energy x-ray absorptiometry (DXA), a technique which is more available, less expensive, and less time consuming than MRI analysis of SM. Conclusions: Researchers using MRI to measure SM can be confident in using a 40 mm interval gap technique when analysing the images to detect minimum changes less than 1 kg. The use of wider intervals will introduce error that is no better

Optimizing the Attitude Control of Small Satellite Constellations for Rapid Response Imaging

Science.gov (United States)

Nag, S.; Li, A.

2016-12-01

Distributed Space Missions (DSMs) such as formation flight and constellations, are being recognized as important solutions to increase measurement samples over space and time. Given the increasingly accurate attitude control systems emerging in the commercial market, small spacecraft now have the ability to slew and point within few minutes of notice. In spite of hardware development in CubeSats at the payload (e.g. NASA InVEST) and subsystems (e.g. Blue Canyon Technologies), software development for tradespace analysis in constellation design (e.g. Goddard's TAT-C), planning and scheduling development in single spacecraft (e.g. GEO-CAPE) and aerial flight path optimizations for UAVs (e.g. NASA Sensor Web), there is a gap in open-source, open-access software tools for planning and scheduling distributed satellite operations in terms of pointing and observing targets. This paper will demonstrate results from a tool being developed for scheduling pointing operations of narrow field-of-view (FOV) sensors over mission lifetime to maximize metrics such as global coverage and revisit statistics. Past research has shown the need for at least fourteen satellites to cover the Earth globally everyday using a LandSat-like sensor. Increasing the FOV three times reduces the need to four satellites, however adds image distortion and BRDF complexities to the observed reflectance. If narrow FOV sensors on a small satellite constellation were commanded using robust algorithms to slew their sensor dynamically, they would be able to coordinately cover the global landmass much faster without compensating for spatial resolution or BRDF effects. Our algorithm to optimize constellation satellite pointing is based on a dynamic programming approach under the constraints of orbital mechanics and existing attitude control systems for small satellites. As a case study for our algorithm, we minimize the time required to cover the 17000 Landsat images with maximum signal to noise ratio fall

Odor-context effects in free recall after a short retention interval: a new methodology for controlling adaptation.

Science.gov (United States)

Isarida, Takeo; Sakai, Tetsuya; Kubota, Takayuki; Koga, Miho; Katayama, Yu; Isarida, Toshiko K

2014-04-01

The present study investigated context effects of incidental odors in free recall after a short retention interval (5 min). With a short retention interval, the results are not confounded by extraneous odors or encounters with the experimental odor and possible rehearsal during a long retention interval. A short study time condition (4 s per item), predicted not to be affected by adaptation to the odor, and a long study time condition (8 s per item) were used. Additionally, we introduced a new method for recovery from adaptation, where a dissimilar odor was briefly presented at the beginning of the retention interval, and we demonstrated the effectiveness of this technique. An incidental learning paradigm was used to prevent overshadowing from confounding the results. In three experiments, undergraduates (N = 200) incidentally studied words presented one-by-one and received a free recall test. Two pairs of odors and a third odor having different semantic-differential characteristics were selected from 14 familiar odors. One of the odors was presented during encoding, and during the test, the same odor (same-context condition) or the other odor within the pair (different-context condition) was presented. Without using a recovery-from-adaptation method, a significant odor-context effect appeared in the 4-s/item condition, but not in the 8-s/item condition. Using the recovery-from-adaptation method, context effects were found for both the 8- and the 4-s/item conditions. The size of the recovered odor-context effect did not change with study time. There were no serial position effects. Implications of the present findings are discussed.

Correlation between plaque control and gingival health using short and extended oral hygiene intervals.

Science.gov (United States)

De David, S C; Mário, T G; De Freitas, G C; Kantorski, K Z; Wikesjö, U M E; Moreira, Carlos Heitor Cunha

2018-02-15

To evaluate the correlation between dental plaque formation and gingival health in subjects performing high oral hygiene standards over short or extended intervals. Fifty-two non-dental students volunteered for this study. The subjects, trained to perform high oral hygiene standards, were randomized to perform oral hygiene at 12-, 24-, 48-, or 72-h interval over 30 days. The plaque index (PlI) and the gingival index (GI) were evaluated at baseline, 15, and 30 days. For the statistical analysis, oral hygiene intervals were collapsed into daily (12 and 24 h; G12/24) and extended (48 and 72 h; G48/72) intervals. Summary statistics (mean ± SD) and Spearman correlations between the PlI and the GI at baseline, 15, and 30 days were estimated. At baseline, correlation coefficients between PlI and GI were positive for both groups (r = 0.29 and r = 0.25). At day 15 and 30, correlation was maintained with similar baseline values for the G48/72 group. GI levels did not increase despite an increase in PlI for the G12/24 group, and the correlation was lower than that observed at baseline (r = 0.13 vs. r = 0.29). In subjects with high oral hygiene standards, the oral hygiene frequency governs the correlation between dental plaque formation and gingival health. Subjects performing high oral hygiene standards at daily intervals will maintain gingival health in difference to subjects using extended hygiene intervals. Subjects performing high oral hygiene standards at daily intervals will maintain gingival health in difference to subjects using extended hygiene intervals.

Lineament systems indentification in Banten site using Spot 5 satellite image

International Nuclear Information System (INIS)

Yuliastuti; Heni Susiati; Yunus Daud; A-Sarwiyana Sastratenaya

2013-01-01

Lineament systems identification in Banten site using SPOT 5 satellite image has been performed. Based on regional site survey in Java Island, Banten is one of the potential candidate sites. The objective of this study was to determine direction and chronology of regional lineament morphology which was consider as fault or faulting in Banten site. The methodology used this study covered satellite image cropping, band selection, edge enhancement filtering, lineament extraction and lineament analysis. Result of the study showed that there were three dominant lineament groups, namely N-S, NW-SE, and E-W. Based on the forming chronology of the lineament, N-S group was the oldest one, followed by E-W group and NW-SE as the youngest group. These lineament groups have been confirmed as a manifestation of fault system structure. (author)

Exploiting Deep Matching and SAR Data for the Geo-Localization Accuracy Improvement of Optical Satellite Images

Directory of Open Access Journals (Sweden)

Nina Merkle

2017-06-01

Full Text Available Improving the geo-localization of optical satellite images is an important pre-processing step for many remote sensing tasks like monitoring by image time series or scene analysis after sudden events. These tasks require geo-referenced and precisely co-registered multi-sensor data. Images captured by the high resolution synthetic aperture radar (SAR satellite TerraSAR-X exhibit an absolute geo-location accuracy within a few decimeters. These images represent therefore a reliable source to improve the geo-location accuracy of optical images, which is in the order of tens of meters. In this paper, a deep learning-based approach for the geo-localization accuracy improvement of optical satellite images through SAR reference data is investigated. Image registration between SAR and optical images requires few, but accurate and reliable matching points. These are derived from a Siamese neural network. The network is trained using TerraSAR-X and PRISM image pairs covering greater urban areas spread over Europe, in order to learn the two-dimensional spatial shifts between optical and SAR image patches. Results confirm that accurate and reliable matching points can be generated with higher matching accuracy and precision with respect to state-of-the-art approaches.

Cardiac time intervals by tissue Doppler imaging M-mode echocardiography

DEFF Research Database (Denmark)

Biering-Sørensen, Tor

2016-01-01

for myocardial myocytes to achieve an LV pressure equal to that of aorta increases, resulting in a prolongation of the isovolumic contraction time (IVCT). Furthermore, the ability of myocardial myocytes to maintain the LV pressure decreases, resulting in reduction in the ejection time (ET). As LV diastolic...... of whether the LV is suffering from impaired systolic or diastolic function. A novel method of evaluating the cardiac time intervals has recently evolved. Using tissue Doppler imaging (TDI) M-mode through the mitral valve (MV) to estimate the cardiac time intervals may be an improved method reflecting global...

Verified Interval Orbit Propagation in Satellite Collision Avoidance

NARCIS (Netherlands)

Römgens, B.A.; Mooij, E.; Naeije, M.C.

2011-01-01

Verified interval integration methods enclose a solution set corresponding to interval initial values and parameters, and bound integration and rounding errors. Verified methods suffer from overestimation of the solution, i.e., non-solutions are also included in the solution enclosure. Two verified

Rapid response flood detection using the MSG geostationary satellite

DEFF Research Database (Denmark)

Proud, Simon Richard; Fensholt, Rasmus; Rasmussen, Laura Vang

2011-01-01

A novel technique for the detection of flooded land using satellite data is presented. This new method takes advantage of the high temporal resolution of the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) aboard the Meteosat Second Generation (MSG) series of satellites to derive several p...... of data gathered during the 2009 flooding events in West Africa shows that the presented method can detect floods of comparable size to the SEVIRI pixel resolution on a short timescale, making it a valuable tool for large scale flood mapping....

Solar resources estimation combining digital terrain models and satellite images techniques

Energy Technology Data Exchange (ETDEWEB)

Bosch, J.L.; Batlles, F.J. [Universidad de Almeria, Departamento de Fisica Aplicada, Ctra. Sacramento s/n, 04120-Almeria (Spain); Zarzalejo, L.F. [CIEMAT, Departamento de Energia, Madrid (Spain); Lopez, G. [EPS-Universidad de Huelva, Departamento de Ingenieria Electrica y Termica, Huelva (Spain)

2010-12-15

One of the most important steps to make use of any renewable energy is to perform an accurate estimation of the resource that has to be exploited. In the designing process of both active and passive solar energy systems, radiation data is required for the site, with proper spatial resolution. Generally, a radiometric stations network is used in this evaluation, but when they are too dispersed or not available for the study area, satellite images can be utilized as indirect solar radiation measurements. Although satellite images cover wide areas with a good acquisition frequency they usually have a poor spatial resolution limited by the size of the image pixel, and irradiation must be interpolated to evaluate solar irradiation at a sub-pixel scale. When pixels are located in flat and homogeneous areas, correlation of solar irradiation is relatively high, and classic interpolation can provide a good estimation. However, in complex topography zones, data interpolation is not adequate and the use of Digital Terrain Model (DTM) information can be helpful. In this work, daily solar irradiation is estimated for a wide mountainous area using a combination of Meteosat satellite images and a DTM, with the advantage of avoiding the necessity of ground measurements. This methodology utilizes a modified Heliosat-2 model, and applies for all sky conditions; it also introduces a horizon calculation of the DTM points and accounts for the effect of snow covers. Model performance has been evaluated against data measured in 12 radiometric stations, with results in terms of the Root Mean Square Error (RMSE) of 10%, and a Mean Bias Error (MBE) of +2%, both expressed as a percentage of the mean value measured. (author)

AUTOMATIC APPROACH TO VHR SATELLITE IMAGE CLASSIFICATION

Directory of Open Access Journals (Sweden)

P. Kupidura

2016-06-01

Full Text Available In this paper, we present a proposition of a fully automatic classification of VHR satellite images. Unlike the most widespread approaches: supervised classification, which requires prior defining of class signatures, or unsupervised classification, which must be followed by an interpretation of its results, the proposed method requires no human intervention except for the setting of the initial parameters. The presented approach bases on both spectral and textural analysis of the image and consists of 3 steps. The first step, the analysis of spectral data, relies on NDVI values. Its purpose is to distinguish between basic classes, such as water, vegetation and non-vegetation, which all differ significantly spectrally, thus they can be easily extracted basing on spectral analysis. The second step relies on granulometric maps. These are the product of local granulometric analysis of an image and present information on the texture of each pixel neighbourhood, depending on the texture grain. The purpose of texture analysis is to distinguish between different classes, spectrally similar, but yet of different texture, e.g. bare soil from a built-up area, or low vegetation from a wooded area. Due to the use of granulometric analysis, based on mathematical morphology opening and closing, the results are resistant to the border effect (qualifying borders of objects in an image as spaces of high texture, which affect other methods of texture analysis like GLCM statistics or fractal analysis. Therefore, the effectiveness of the analysis is relatively high. Several indices based on values of different granulometric maps have been developed to simplify the extraction of classes of different texture. The third and final step of the process relies on a vegetation index, based on near infrared and blue bands. Its purpose is to correct partially misclassified pixels. All the indices used in the classification model developed relate to reflectance values, so the

NEAR REAL-TIME AUTOMATIC MARINE VESSEL DETECTION ON OPTICAL SATELLITE IMAGES

Directory of Open Access Journals (Sweden)

G. Máttyus

2013-05-01

Full Text Available Vessel monitoring and surveillance is important for maritime safety and security, environment protection and border control. Ship monitoring systems based on Synthetic-aperture Radar (SAR satellite images are operational. On SAR images the ships made of metal with sharp edges appear as bright dots and edges, therefore they can be well distinguished from the water. Since the radar is independent from the sun light and can acquire images also by cloudy weather and rain, it provides a reliable service. Vessel detection from spaceborne optical images (VDSOI can extend the SAR based systems by providing more frequent revisit times and overcoming some drawbacks of the SAR images (e.g. lower spatial resolution, difficult human interpretation. Optical satellite images (OSI can have a higher spatial resolution thus enabling the detection of smaller vessels and enhancing the vessel type classification. The human interpretation of an optical image is also easier than as of SAR image. In this paper I present a rapid automatic vessel detection method which uses pattern recognition methods, originally developed in the computer vision field. In the first step I train a binary classifier from image samples of vessels and background. The classifier uses simple features which can be calculated very fast. For the detection the classifier is slided along the image in various directions and scales. The detector has a cascade structure which rejects most of the background in the early stages which leads to faster execution. The detections are grouped together to avoid multiple detections. Finally the position, size(i.e. length and width and heading of the vessels is extracted from the contours of the vessel. The presented method is parallelized, thus it runs fast (in minutes for 16000 × 16000 pixels image on a multicore computer, enabling near real-time applications, e.g. one hour from image acquisition to end user.

Near Real-Time Automatic Marine Vessel Detection on Optical Satellite Images

Science.gov (United States)

Máttyus, G.

2013-05-01

Vessel monitoring and surveillance is important for maritime safety and security, environment protection and border control. Ship monitoring systems based on Synthetic-aperture Radar (SAR) satellite images are operational. On SAR images the ships made of metal with sharp edges appear as bright dots and edges, therefore they can be well distinguished from the water. Since the radar is independent from the sun light and can acquire images also by cloudy weather and rain, it provides a reliable service. Vessel detection from spaceborne optical images (VDSOI) can extend the SAR based systems by providing more frequent revisit times and overcoming some drawbacks of the SAR images (e.g. lower spatial resolution, difficult human interpretation). Optical satellite images (OSI) can have a higher spatial resolution thus enabling the detection of smaller vessels and enhancing the vessel type classification. The human interpretation of an optical image is also easier than as of SAR image. In this paper I present a rapid automatic vessel detection method which uses pattern recognition methods, originally developed in the computer vision field. In the first step I train a binary classifier from image samples of vessels and background. The classifier uses simple features which can be calculated very fast. For the detection the classifier is slided along the image in various directions and scales. The detector has a cascade structure which rejects most of the background in the early stages which leads to faster execution. The detections are grouped together to avoid multiple detections. Finally the position, size(i.e. length and width) and heading of the vessels is extracted from the contours of the vessel. The presented method is parallelized, thus it runs fast (in minutes for 16000 × 16000 pixels image) on a multicore computer, enabling near real-time applications, e.g. one hour from image acquisition to end user.

THE ANALYSIS OF MOISTURE DEFICIT BASED ON MODIS AND LANDSAT SATELLITE IMAGES. CASE STUDY: THE OLTENIA PLAIN

Directory of Open Access Journals (Sweden)

ONȚEL IRINA

2014-03-01

Full Text Available Satellite images are an important source of information to identify and analyse some hazardous climatic phenomena such as the dryness and drought. These phenomena are characterized by scarce rainfall, increased evapotranspiration and high soil moisture deficit. The soil water reserve depletes to the wilting coefficient, soon followed by the pedological drought which has negative effects on vegetation and agricultural productivity. The MODIS satellite images (Moderate Resolution Imaging Spectroradiometer allow the monitoring of the vegetation throughout the entire vegetative period, with a frequency of 1-2 days and with a spatial resolution of 250 m, 500 m and 1 km away. Another useful source of information is the LANDSAT satellite images, with a spatial resolution of 30 m. Based on MODIS and Landsat satellite images, were calculated moisture monitoring index such as SIWSI (Shortwave Infrared Water Stress Index. Consequently, some years with low moisture such as 2000, 2002, 2007 and 2012 could be identified. Spatially, the areas with moisture deficit varied from one year to another all over the whole analised period (2000-2012. The remote sensing results was corelated with Standard Precipitation Anomaly, which gives a measure of the severity of a wet or dry event.

Simultaneous hierarchical segmentation and vectorization of satellite images through combined data sampling and anisotropic triangulation

Energy Technology Data Exchange (ETDEWEB)

Grazzini, Jacopo [Los Alamos National Laboratory; Prasad, Lakshman [Los Alamos National Laboratory; Dillard, Scott [PNNL

2010-10-21

The automatic detection, recognition , and segmentation of object classes in remote sensed images is of crucial importance for scene interpretation and understanding. However, it is a difficult task because of the high variability of satellite data. Indeed, the observed scenes usually exhibit a high degree of complexity, where complexity refers to the large variety of pictorial representations of objects with the same semantic meaning and also to the extensive amount of available det.ails. Therefore, there is still a strong demand for robust techniques for automatic information extraction and interpretation of satellite images. In parallel, there is a growing interest in techniques that can extract vector features directly from such imagery. In this paper, we investigate the problem of automatic hierarchical segmentation and vectorization of multispectral satellite images. We propose a new algorithm composed of the following steps: (i) a non-uniform sampling scheme extracting most salient pixels in the image, (ii) an anisotropic triangulation constrained by the sampled pixels taking into account both strength and directionality of local structures present in the image, (iii) a polygonal grouping scheme merging, through techniques based on perceptual information , the obtained segments to a smaller quantity of superior vectorial objects. Besides its computational efficiency, this approach provides a meaningful polygonal representation for subsequent image analysis and/or interpretation.

The effects of rectification and Global Positioning System errors on satellite image-based estimates of forest area

Science.gov (United States)

Ronald E. McRoberts

2010-01-01

Satellite image-based maps of forest attributes are of considerable interest and are used for multiple purposes such as international reporting by countries that have no national forest inventory and small area estimation for all countries. Construction of the maps typically entails, in part, rectifying the satellite images to a geographic coordinate system, observing...

Meteo-marine parameters for highly variable environment in coastal regions from satellite radar images

Science.gov (United States)

Pleskachevsky, A. L.; Rosenthal, W.; Lehner, S.

2016-09-01

The German Bight of the North Sea is the area with highly variable sea state conditions, intensive ship traffic and with a high density of offshore installations, e.g. wind farms in use and under construction. Ship navigation and the docking on offshore constructions is impeded by significant wave heights HS > 1.3 m. For these reasons, improvements are required in recognition and forecasting of sea state HS in the range 0-3 m. Thus, this necessitates the development of new methods to determine the distribution of meteo-marine parameters from remote sensing data with an accuracy of decimetres for HS. The operationalization of these methods then allows the robust automatic processing in near real time (NRT) to support forecast agencies by providing validations for model results. A new empirical algorithm XWAVE_C (C = coastal) for estimation of significant wave height from X-band satellite-borne Synthetic Aperture Radar (SAR) data has been developed, adopted for coastal applications using TerraSAR-X (TS-X) and Tandem-X (TD-X) satellites in the German Bight and implemented into the Sea Sate Processor (SSP) for fully automatic processing for NRT services. The algorithm is based on the spectral analysis of subscenes and the model function uses integrated image spectra parameters as well as local wind information from the analyzed subscene. The algorithm is able to recognize and remove the influence of non-sea state produced signals in the Wadden Sea areas such as dry sandbars as well as nonlinear SAR image distortions produced by e.g. short wind waves and breaking waves. Also parameters of very short waves, which are not visible in SAR images and produce only unsystematic clutter, can be accurately estimated. The SSP includes XWAVE_C, a pre-filtering procedure for removing artefacts such as ships, seamarks, buoys, offshore constructions and slicks, and an additional procedure performing a check of results based on the statistics of the whole scene. The SSP allows an

Accuracy comparison of Pléiades satellite ortho-images using GPS ...

African Journals Online (AJOL)

resolution satellite ortho-image when different types of ground control are used. This required the execution of two orthorectification tests where only the type of GCPs differed. The results of these tests were interesting since it highlighted the ...

Research on active imaging information transmission technology of satellite borne quantum remote sensing

Science.gov (United States)

Bi, Siwen; Zhen, Ming; Yang, Song; Lin, Xuling; Wu, Zhiqiang

2017-08-01

According to the development and application needs of Remote Sensing Science and technology, Prof. Siwen Bi proposed quantum remote sensing. Firstly, the paper gives a brief introduction of the background of quantum remote sensing, the research status and related researches at home and abroad on the theory, information mechanism and imaging experiments of quantum remote sensing and the production of principle prototype.Then, the quantization of pure remote sensing radiation field, the state function and squeezing effect of quantum remote sensing radiation field are emphasized. It also describes the squeezing optical operator of quantum light field in active imaging information transmission experiment and imaging experiments, achieving 2-3 times higher resolution than that of coherent light detection imaging and completing the production of quantum remote sensing imaging prototype. The application of quantum remote sensing technology can significantly improve both the signal-to-noise ratio of information transmission imaging and the spatial resolution of quantum remote sensing .On the above basis, Prof.Bi proposed the technical solution of active imaging information transmission technology of satellite borne quantum remote sensing, launched researches on its system composition and operation principle and on quantum noiseless amplifying devices, providing solutions and technical basis for implementing active imaging information technology of satellite borne Quantum Remote Sensing.

A fast and automatic mosaic method for high-resolution satellite images

Science.gov (United States)

Chen, Hongshun; He, Hui; Xiao, Hongyu; Huang, Jing

2015-12-01

We proposed a fast and fully automatic mosaic method for high-resolution satellite images. First, the overlapped rectangle is computed according to geographical locations of the reference and mosaic images and feature points on both the reference and mosaic images are extracted by a scale-invariant feature transform (SIFT) algorithm only from the overlapped region. Then, the RANSAC method is used to match feature points of both images. Finally, the two images are fused into a seamlessly panoramic image by the simple linear weighted fusion method or other method. The proposed method is implemented in C++ language based on OpenCV and GDAL, and tested by Worldview-2 multispectral images with a spatial resolution of 2 meters. Results show that the proposed method can detect feature points efficiently and mosaic images automatically.

Automated Detection of Buildings from Heterogeneous VHR Satellite Images for Rapid Response to Natural Disasters

Directory of Open Access Journals (Sweden)

Shaodan Li

2017-11-01

Full Text Available In this paper, we present a novel approach for automatically detecting buildings from multiple heterogeneous and uncalibrated very high-resolution (VHR satellite images for a rapid response to natural disasters. In the proposed method, a simple and efficient visual attention method is first used to extract built-up area candidates (BACs from each multispectral (MS satellite image. After this, morphological building indices (MBIs are extracted from all the masked panchromatic (PAN and MS images with BACs to characterize the structural features of buildings. Finally, buildings are automatically detected in a hierarchical probabilistic model by fusing the MBI and masked PAN images. The experimental results show that the proposed method is comparable to supervised classification methods in terms of recall, precision and F-value.

Short echo time, fast gradient-echo imaging

International Nuclear Information System (INIS)

Haacke, E.M.; Lenz, G.W.

1987-01-01

Present fast-gradient-echoes schemes can acquire volume data rapidly and are flexible in T1 or T1/T2 contrast behavior. However, sequences used to date employ echo time (TE) values of about 15 ms +- 5 and, because of in vivo field inhomogeneities (short T2), they suffer badly from signal loss near sinuses and tissue boundaries. The authors implemented sequences with TE = 4-6 ms and found significant improvement in image quality, especially at high fields. Examples with long TEs vs. short TEs are given in the knee, spine, head, and orbits. Further advantages include (1) faster repetition times (15 ms), (2) higher-quality spin-density or T1-weighted images, and (3) reduction of blood motion artifacts

The dark side of the QT interval. The Short QT Syndrome: pathophysiology, clinical presentation and management

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I. Comelli

2012-12-01

Full Text Available A large number of studies has been carried out to investigate the pathophysiology and the clinical implications of QT interval prolongation in the ECG over recent years (1, 2, 3, 4, 5, 6. It was only in the last decade, however, that the scientists have focused on the specular aspects of the long QT syndrome (LQTS, and it is now well established that the abnormal shortening of the QT interval is associated with meaningful clinical consequences and adverse outcomes. The aim of the present article is to summarize knowledge and existing evidence about the Short QT Syndrome (SQTS. SQTS is a rare, albeit largely underdiagnosed, genetically determined disease, which is characterized by a high tendency to develop life-threatening arrhythmias. The two clinical landmarks of SQTS are the presence of a short QT interval (i.e., less than 320 ms in a structurally normal heart. The disease is now classified as a “channellopathy”, and is principally caused by a defective functioning of both potassium and calcium ion channels. The underlying genetic anomalies cause an abnormal ripolarization and a reduced refractoriness of myocardiocites. Pharmacologic treatments are mainly tailored to slow the conduction and to prolong the refractory period of myocardiocites. The implantable cardioverter and defibrillator (ICD is currently considered the therapeutic gold standard (7.

Use of high resolution satellite images for monitoring of earthquakes and volcano activity.

Science.gov (United States)

Arellano-Baeza, Alonso A.

Our studies have shown that the strain energy accumulation deep in the Earth's crust that precedes a strong earthquake can be detected by applying a lineament extraction technique to the high-resolution multispectral satellite images. A lineament is a straight or a somewhat curved feature in a satellite image, which it is possible to detect by a special processing of images based on directional filtering and or Hough transform. We analyzed tens of earthquakes occurred in the Pacific coast of the South America with the Richter scale magnitude ˜4.5, using ASTER/TERRA multispectral satellite images for detection and analysis of changes in the system of lineaments previous to a strong earthquake. All events were located in the regions with small seasonal variations and limited vegetation to facilitate the tracking of features associated with the seismic activity only. It was found that the number and orientation of lineaments changed significantly about one month before an earthquake approximately, and a few months later the system returns to its initial state. This effect increases with the earthquake magnitude. It also was shown that the behavior of lineaments associated to the volcano seismic activity is opposite to that obtained previously for earthquakes. This discrepancy can be explained assuming that in the last case the main reason of earthquakes is compression and accumulation of strength in the Earth's crust due to subduction of tectonic plates, whereas in the first case we deal with the inflation of a volcano edifice due to elevation of pressure and magma intrusion. The results obtained made it possible to include this research as a part of scientific program of Chilean Remote Sensing Satellite mission to be launched in 2010.

Chagas disease study using satellite image processing: A Bolivian case

Science.gov (United States)

Vargas-Cuentas, Natalia I.; Roman-Gonzalez, Avid; Mantari, Alicia Alva; Muñoz, Luis AnthonyAucapuma

2018-03-01

Remote sensing is the technology that has enabled us to obtain information about the Earth's surface without directly contacting it. For this reason, currently, the Bolivian state has considered a list of interesting applications of remote sensing in the country, including the following: biodiversity and environment monitoring, mining and geology, epidemiology, agriculture, water resources and land use planning. The use of satellite images has become a great tool for epidemiology because with this technological advance we can determine the environment in which transmission occurs, the distribution of the disease and its evolution over time. In that context, one of the important diseases related to public health in Bolivia is Chagas disease, also known as South American Trypanosomiasis. Chagas is caused by a blood-sucking bug or Vinchuca, which causes serious intestinal and heart long term problems and affects 33.4% of the Bolivian population. This disease affects mostly humble people, so the Bolivian state invests millions of dollars to acquire medicine and distribute it for free. Due to the above reasons, the present research aims to analyze some areas of Bolivia using satellite images for developing an epidemiology study. The primary objective is to understand the environment in which the transmission of the disease happens, and the climatic conditions under which occurs, observe the behavior of the blood-sucking bug, identify in which months occur higher outbreaks, in which months the bug leaves its eggs, and under which weather conditions this happens. All this information would be contrasted with information extracted from the satellite images and data from the Ministry of Health, and the Institute of Meteorology in Bolivia. All this data will allow us to have a more integrated understanding of this disease and promote new possibilities to prevent and control it.

The Application of Chinese High-Spatial Remote Sensing Satellite Image in Land Law Enforcement Information Extraction

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Wang, N.; Yang, R.

2018-04-01

Chinese high -resolution (HR) remote sensing satellites have made huge leap in the past decade. Commercial satellite datasets, such as GF-1, GF-2 and ZY-3 images, the panchromatic images (PAN) resolution of them are 2 m, 1 m and 2.1 m and the multispectral images (MS) resolution are 8 m, 4 m, 5.8 m respectively have been emerged in recent years. Chinese HR satellite imagery has been free downloaded for public welfare purposes using. Local government began to employ more professional technician to improve traditional land management technology. This paper focused on analysing the actual requirements of the applications in government land law enforcement in Guangxi Autonomous Region. 66 counties in Guangxi Autonomous Region were selected for illegal land utilization spot extraction with fusion Chinese HR images. The procedure contains: A. Defines illegal land utilization spot type. B. Data collection, GF-1, GF-2, and ZY-3 datasets were acquired in the first half year of 2016 and other auxiliary data were collected in 2015. C. Batch process, HR images were collected for batch preprocessing through ENVI/IDL tool. D. Illegal land utilization spot extraction by visual interpretation. E. Obtaining attribute data with ArcGIS Geoprocessor (GP) model. F. Thematic mapping and surveying. Through analysing 42 counties results, law enforcement officials found 1092 illegal land using spots and 16 suspicious illegal mining spots. The results show that Chinese HR satellite images have great potential for feature information extraction and the processing procedure appears robust.

Digital elevation model generation from satellite interferometric synthetic aperture radar: Chapter 5

Science.gov (United States)

Lu, Zhong; Dzurisin, Daniel; Jung, Hyung-Sup; Zhang, Lei; Lee, Wonjin; Lee, Chang-Wook

2012-01-01

An accurate digital elevation model (DEM) is a critical data set for characterizing the natural landscape, monitoring natural hazards, and georeferencing satellite imagery. The ideal interferometric synthetic aperture radar (InSAR) configuration for DEM production is a single-pass two-antenna system. Repeat-pass single-antenna satellite InSAR imagery, however, also can be used to produce useful DEMs. DEM generation from InSAR is advantageous in remote areas where the photogrammetric approach to DEM generation is hindered by inclement weather conditions. There are many sources of errors in DEM generation from repeat-pass InSAR imagery, for example, inaccurate determination of the InSAR baseline, atmospheric delay anomalies, and possible surface deformation because of tectonic, volcanic, or other sources during the time interval spanned by the images. This chapter presents practical solutions to identify and remove various artifacts in repeat-pass satellite InSAR images to generate a high-quality DEM.

Restricted Interval Valued Neutrosophic Sets and Restricted Interval Valued Neutrosophic Topological Spaces

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Anjan Mukherjee

2016-08-01

Full Text Available In this paper we introduce the concept of restricted interval valued neutrosophic sets (RIVNS in short. Some basic operations and properties of RIVNS are discussed. The concept of restricted interval valued neutrosophic topology is also introduced together with restricted interval valued neutrosophic finer and restricted interval valued neutrosophic coarser topology. We also define restricted interval valued neutrosophic interior and closer of a restricted interval valued neutrosophic set. Some theorems and examples are cites. Restricted interval valued neutrosophic subspace topology is also studied.

Three-dimensional information extraction from GaoFen-1 satellite images for landslide monitoring

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Wang, Shixin; Yang, Baolin; Zhou, Yi; Wang, Futao; Zhang, Rui; Zhao, Qing

2018-05-01

To more efficiently use GaoFen-1 (GF-1) satellite images for landslide emergency monitoring, a Digital Surface Model (DSM) can be generated from GF-1 across-track stereo image pairs to build a terrain dataset. This study proposes a landslide 3D information extraction method based on the terrain changes of slope objects. The slope objects are mergences of segmented image objects which have similar aspects; and the terrain changes are calculated from the post-disaster Digital Elevation Model (DEM) from GF-1 and the pre-disaster DEM from GDEM V2. A high mountain landslide that occurred in Wenchuan County, Sichuan Province is used to conduct a 3D information extraction test. The extracted total area of the landslide is 22.58 ha; the displaced earth volume is 652,100 m3; and the average sliding direction is 263.83°. The accuracies of them are 0.89, 0.87 and 0.95, respectively. Thus, the proposed method expands the application of GF-1 satellite images to the field of landslide emergency monitoring.

Background parenchymal enhancement on baseline screening breast MRI: impact on biopsy rate and short-interval follow-up.

LENUS (Irish Health Repository)

Hambly, Niamh M

2011-01-01

Background parenchymal enhancement on breast MRI refers to normal enhancement of the patient\\'s fibroglandular tissue. The aim of this study was to determine the effect of background parenchymal enhancement on short-interval follow-up, biopsy, and cancer detection rate on baseline screening MRI in a high-risk group.

Deep learning for the detection of barchan dunes in satellite images

Science.gov (United States)

Azzaoui, A. M.; Adnani, M.; Elbelrhiti, H.; Chaouki, B. E. K.; Masmoudi, L.

2017-12-01

Barchan dunes are known to be the fastest moving sand dunes in deserts as they form under unidirectional winds and limited sand supply over a firm coherent basement (Elbelrhiti and Hargitai,2015). They were studied in the context of natural hazard monitoring as they could be a threat to human activities and infrastructures. Also, they were studied as a natural phenomenon occurring in other planetary landforms such as Mars or Venus (Bourke et al., 2010). Our region of interest was located in a desert region in the south of Morocco, in a barchan dunes corridor next to the town of Tarfaya. This region which is part of the Sahara desert contained thousands of barchans; which limits the number of dunes that could be studied during field missions. Therefore, we chose to monitor barchan dunes with satellite imagery, which can be seen as a complementary approach to field missions. We collected data from the Sentinel platform (https://scihub.copernicus.eu/dhus/); we used a machine learning method as a basis for the detection of barchan dunes positions in the satellite image. We trained a deep learning model on a mid-sized dataset that contained blocks representing images of barchan dunes, and images of other desert features, that we collected by cropping and annotating the source image. During testing, we browsed the satellite image with a gliding window that evaluated each block, and then produced a probability map. Finally, a threshold on the latter map exposed the location of barchan dunes. We used a subsample of data to train the model and we gradually incremented the size of the training set to get finer results and avoid over fitting. The positions of barchan dunes were successfully detected and deep learning was an effective method for this application. Sentinel-2 images were chosen for their availability and good temporal resolution, which will allow the tracking of barchan dunes in future work. While Sentinel images had sufficient spatial resolution for the

Wind Statistics Offshore based on Satellite Images

DEFF Research Database (Denmark)

Hasager, Charlotte Bay; Mouche, Alexis; Badger, Merete

2009-01-01

-based observations become available. At present preliminary results are obtained using the routine methods. The first step in the process is to retrieve raw SAR data, calibrate the images and use a priori wind direction as input to the geophysical model function. From this process the wind speed maps are produced....... The wind maps are geo-referenced. The second process is the analysis of a series of geo-referenced SAR-based wind maps. Previous research has shown that a relatively large number of images are needed for achieving certain accuracies on mean wind speed, Weibull A and k (scale and shape parameters......Ocean wind maps from satellites are routinely processed both at Risø DTU and CLS based on the European Space Agency Envisat ASAR data. At Risø the a priori wind direction is taken from the atmospheric model NOGAPS (Navel Operational Global Atmospheric Prediction System) provided by the U.S. Navy...

Paired-Pulse TMS and Fine-Wire Recordings Reveal Short-Interval Intracortical Inhibition and Facilitation of Deep Multifidus Muscle Fascicles.

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Hugo Massé-Alarie

Full Text Available Paired-pulse transcranial magnetic stimulation (ppTMS is used to probe inhibitory and excitatory networks within the primary motor cortex (M1. These mechanisms are identified for limb muscles but it is unclear whether they share properties with trunk muscles. The aim was to determine whether it was possible to test the intracortical inhibition and facilitation of the deep multifidus muscle fascicles (DM and at which inter-stimulus intervals (ISI.In ten pain-free individuals, TMS was applied over M1 and motor evoked potentials (MEP were recorded using fine-wire electrodes in DM. MEPs were conditioned with subthreshold stimuli at ISIs of 1 to 12 ms to test short-interval intracortical inhibition (SICI and at 15 ms for long-interval intracortical facilitation. Short-interval facilitation (SICF was tested using 1-ms ISI.SICI of DM was consistently obtained with ISI of 1-, 3-, 4- and 12-ms. Facilitation of DM MEP was only identified using SICF paradigm.A similar pattern of MEP modulation with ISI changes for deep trunk and limb muscles implies that M1 networks share some functional properties.The ppTMS paradigm presents a potential to determine how M1 inhibitory and excitatory mechanisms participate in brain re-organization in back pain that affects control of trunk muscles.

Use of satellite images for the monitoring of water systems

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Hillebrand, Gudrun; Winterscheid, Axel; Baschek, Björn; Wolf, Thomas

2015-04-01

Satellite images are a proven source of information for monitoring ecological indicators in coastal waters and inland river systems. This potential of remote sensing products was demonstrated by recent research projects (e.g. EU-funded project Freshmon - www.freshmon.eu) and other activities by national institutions. Among indicators for water quality, a particular focus was set on the temporal and spatial dynamics of suspended particulate matter (SPM) and Chlorophyll-a (Chl-a). The German Federal Institute of Hydrology (BfG) was using the Weser and Elbe estuaries as test cases to compare in-situ measurements with results obtained from a temporal series of automatically generated maps of SPM distributions based on remote sensing data. Maps of SPM and Chl-a distributions in European inland rivers and alpine lakes were generated by the Freshmon Project. Earth observation based products are a valuable source for additional data that can well supplement in-situ monitoring. For 2015, the BfG and the Institute for Lake Research of the State Institute for the Environment, Measurements and Nature Conservation of Baden-Wuerttemberg, Germany (LUBW) are in the process to start implementing an operational service for monitoring SPM and Chl-a based on satellite images (Landsat 7 & 8, Sentinel 2, and if required other systems with higher spatial resolution, e.g. Rapid Eye). In this 2-years project, which is part of the European Copernicus Programme, the operational service will be set up for - the inland rivers of Rhine and Elbe - the North Sea estuaries of Elbe, Weser and Ems. Furthermore - Lake Constance and other lakes located within the Federal State of Baden-Wuerttemberg. In future, the service can be implemented for other rivers and lakes as well. Key feature of the project is a data base that holds the stock of geo-referenced maps of SPM and Chl-a distributions. Via web-based portals (e.g. GGInA - geo-portal of the BfG; UIS - environmental information system of the

Cardiac Time Intervals Measured by Tissue Doppler Imaging M-mode

DEFF Research Database (Denmark)

Biering-Sørensen, Tor; Møgelvang, Rasmus; Schnohr, Peter

2016-01-01

function was evaluated in 1915 participants by using both conventional echocardiography and tissue Doppler imaging (TDI). The cardiac time intervals, including the isovolumic relaxation time (IVRT), isovolumic contraction time (IVCT), and ejection time (ET), were obtained by TDI M-mode through the mitral......). Additionally, they displayed a significant dose-response relationship, between increasing severity of elevated blood pressure and increasing left ventricular mass index (P

The effects of short versus long inter-set rest intervals in resistance training on measures of muscle hypertrophy: A systematic review.

Science.gov (United States)

Grgic, Jozo; Lazinica, Bruno; Mikulic, Pavle; Krieger, James W; Schoenfeld, Brad Jon

2017-09-01

Although the effects of short versus long inter-set rest intervals in resistance training on measures of muscle hypertrophy have been investigated in several studies, the findings are equivocal and the practical implications remain unclear. In an attempt to provide clarity on the topic, we performed a systematic literature search of PubMed/MEDLINE, Scopus, Web of Science, Cochrane Library, and Physiotherapy Evidence Database (PEDro) electronic databases. Six studies were found to have met the inclusion criteria: (a) an experimental trial published in an English-language peer-reviewed journal; (b) the study compared the use of short (≤60 s) to long (>60 s) inter-set rest intervals in a traditional dynamic resistance exercise using both concentric and eccentric muscle actions, with the only difference in resistance training among groups being the inter-set rest interval duration; (c) at least one method of measuring changes in muscle mass was used in the study; (d) the study lasted for a minimum of four weeks, employed a training frequency of ≥2 resistance training days per week, and (e) used human participants without known chronic disease or injury. Current evidence indicates that both short and long inter-set rest intervals may be useful when training for achieving gains in muscle hypertrophy. Novel findings involving trained participants using measures sensitive to detect changes in muscle hypertrophy suggest a possible advantage for the use of long rest intervals to elicit hypertrophic effects. However, due to the paucity of studies with similar designs, further research is needed to provide a clear differentiation between these two approaches.

The 2017 Hurricane Season: A Revolution in Geostationary Weather Satellite Imaging and Data Processing

Science.gov (United States)

Weiner, A. M.; Gundy, J.; Brown-Bertold, B.; Yates, H.; Dobler, J. T.

2017-12-01

Since their introduction, geostationary weather satellites have enabled us to track hurricane life-cycle movement from development to dissipation. During the 2017 hurricane season, the new GOES-16 geostationary satellite demonstrated just how far we have progressed technologically in geostationary satellite imaging, with hurricane imagery showing never-before-seen detail of the hurricane eye and eyewall structure and life cycle. In addition, new ground system technology, leveraging high-performance computing, delivered imagery and data to forecasters with unprecedented speed—and with updates as often as every 30 seconds. As additional satellites and new products become operational, forecasters will be able to track hurricanes with even greater accuracy and assist in aftermath evaluations. This presentation will present glimpses into the past, a look at the present, and a prediction for the future utilization of geostationary satellites with respect to all facets of hurricane support.

Feature Extraction in Sequential Multimedia Images: with Applications in Satellite Images and On-line Videos

Science.gov (United States)

Liang, Yu-Li

Multimedia data is increasingly important in scientific discovery and people's daily lives. Content of massive multimedia is often diverse and noisy, and motion between frames is sometimes crucial in analyzing those data. Among all, still images and videos are commonly used formats. Images are compact in size but do not contain motion information. Videos record motion but are sometimes too big to be analyzed. Sequential images, which are a set of continuous images with low frame rate, stand out because they are smaller than videos and still maintain motion information. This thesis investigates features in different types of noisy sequential images, and the proposed solutions that intelligently combined multiple features to successfully retrieve visual information from on-line videos and cloudy satellite images. The first task is detecting supraglacial lakes above ice sheet in sequential satellite images. The dynamics of supraglacial lakes on the Greenland ice sheet deeply affect glacier movement, which is directly related to sea level rise and global environment change. Detecting lakes above ice is suffering from diverse image qualities and unexpected clouds. A new method is proposed to efficiently extract prominent lake candidates with irregular shapes, heterogeneous backgrounds, and in cloudy images. The proposed system fully automatize the procedure that track lakes with high accuracy. We further cooperated with geoscientists to examine the tracked lakes and found new scientific findings. The second one is detecting obscene content in on-line video chat services, such as Chatroulette, that randomly match pairs of users in video chat sessions. A big problem encountered in such systems is the presence of flashers and obscene content. Because of various obscene content and unstable qualities of videos capture by home web-camera, detecting misbehaving users is a highly challenging task. We propose SafeVchat, which is the first solution that achieves satisfactory

THE SHORT ROTATION PERIOD OF HI’IAKA, HAUMEA’S LARGEST SATELLITE

Energy Technology Data Exchange (ETDEWEB)

Hastings, Danielle M.; Margot, Jean-Luc [University of California, Los Angeles, Department of Earth, Planetary, and Space Sciences, 595 Charles Young Drive East, Los Angeles, CA 90095 (United States); Ragozzine, Darin [Florida Institute of Technology, Department of Physics and Space Sciences, 150 West University Boulevard, Melbourne, FL 32901 (United States); Fabrycky, Daniel C. [Department of Astronomy and Astrophysics, University of Chicago, 5640 South Ellis Avenue, Chicago, IL 60637 (United States); Burkhart, Luke D.; Holman, Matthew [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Fuentes, Cesar [Departamento de Astronomía, Universidad de Chile, Camino El Observatorio 1515, Santiago (Chile); Brown, Michael E., E-mail: dhastings@g.ucla.edu [California Institute of Technology, Division of Geological and Planetary Sciences, MC 150-21, Pasadena, CA 91125 (United States)

2016-12-01

Hi’iaka is the larger outer satellite of the dwarf planet Haumea. Using relative photometry from the Hubble Space Telescope and Magellan and a phase dispersion minimization analysis, we have identified the rotation period of Hi’iaka to be ∼9.8 hr (double peaked). This is ∼120 times faster than its orbital period, creating new questions about the formation of this system and possible tidal evolution. The rapid rotation suggests that Hi’iaka could have a significant obliquity and spin precession that could be visible in light curves within a few years. We then turn to an investigation of what we learn about the (currently unclear) formation of the Haumea system and family based on this unexpectedly rapid rotation rate. We explore the importance of the initial semimajor axis and rotation period in tidal evolution theory and find that they strongly influence the time required to despin to synchronous rotation, relevant to understanding a wide variety of satellite and binary systems. We find that despinning tides do not necessarily lead to synchronous spin periods for Hi’iaka, even if it formed near the Roche limit. Therefore, the short rotation period of Hi’iaka does not rule out significant tidal evolution. Hi’iaka’s spin period is also consistent with formation near its current location and spin-up due to Haumea-centric impactors.

Automatic Matching of Multi-Source Satellite Images: A Case Study on ZY-1-02C and ETM+

Directory of Open Access Journals (Sweden)

Bo Wang

2017-10-01

Full Text Available The ever-growing number of applications for satellites is being compromised by their poor direct positioning precision. Existing orthoimages, such as enhanced thematic mapper (ETM+ orthoimages, can provide georeferences or improve the geo-referencing accuracy of satellite images, such ZY-1-02C images that have unsatisfactory positioning precision, thus enhancing their processing efficiency and application. In this paper, a feasible image matching approach using multi-source satellite images is proposed on the basis of an experiment carried out with ZY-1-02C Level 1 images and ETM+ orthoimages. The proposed approach overcame differences in rotation angle, scale, and translation between images. The rotation and scale variances were evaluated on the basis of rational polynomial coefficients. The translation vectors were generated after blocking the overall phase correlation. Then, normalized cross-correlation and least-squares matching were applied for matching. Finally, the gross errors of the corresponding points were eliminated by local statistic vectors in a TIN structure. Experimental results showed a matching precision of less than two pixels (root-mean-square error, and comparison results indicated that the proposed method outperforms Scale-Invariant Feature Transform (SIFT, Speeded Up Robust Features (SURF, and Affine-Scale Invariant Feature Transform (A-SIFT in terms of reliability and efficiency.

An anti-image interference quadrature IF architecture for satellite receivers

Directory of Open Access Journals (Sweden)

He Weidong

2014-08-01

Full Text Available Since Global Navigation Satellite System (GNSS signals span a wide range of frequency, wireless signals coming from other communication systems may be aliased and appear as image interference. In quadrature intermediate frequency (IF receivers, image aliasing due to in-phase and quadrature (I/Q channel mismatches is always a big problem. I/Q mismatches occur because of gain and phase imbalances between quadrature mixers and capacitor mismatches in analog-to-digital converters (ADC. As a result, the dynamic range and performance of a receiver are severely degraded. In this paper, several popular receiver architectures are summarized and the image aliasing problem is investigated in detail. Based on this analysis, a low-IF architecture is proposed for a single-chip solution and a novel and feasible anti-image algorithm is investigated. With this anti-image digital processing, the image reject ratio (IRR can reach approximately above 50 dB, which relaxes image rejection specific in front-end circuit designs and allows cheap and highly flexible analog front-end solutions. Simulation and experimental data show that the anti-image algorithm can work effectively, robustly, and steadily.

Laser Guidestar Satellite for Ground-based Adaptive Optics Imaging of Geosynchronous Satellites and Astronomical Targets

Science.gov (United States)

Marlow, W. A.; Cahoy, K.; Males, J.; Carlton, A.; Yoon, H.

2015-12-01

Real-time observation and monitoring of geostationary (GEO) satellites with ground-based imaging systems would be an attractive alternative to fielding high cost, long lead, space-based imagers, but ground-based observations are inherently limited by atmospheric turbulence. Adaptive optics (AO) systems are used to help ground telescopes achieve diffraction-limited seeing. AO systems have historically relied on the use of bright natural guide stars or laser guide stars projected on a layer of the upper atmosphere by ground laser systems. There are several challenges with this approach such as the sidereal motion of GEO objects relative to natural guide stars and limitations of ground-based laser guide stars; they cannot be used to correct tip-tilt, they are not point sources, and have finite angular sizes when detected at the receiver. There is a difference between the wavefront error measured using the guide star compared with the target due to cone effect, which also makes it difficult to use a distributed aperture system with a larger baseline to improve resolution. Inspired by previous concepts proposed by A.H. Greenaway, we present using a space-based laser guide starprojected from a satellite orbiting the Earth. We show that a nanosatellite-based guide star system meets the needs for imaging GEO objects using a low power laser even from 36,000 km altitude. Satellite guide star (SGS) systemswould be well above atmospheric turbulence and could provide a small angular size reference source. CubeSatsoffer inexpensive, frequent access to space at a fraction of the cost of traditional systems, and are now being deployed to geostationary orbits and on interplanetary trajectories. The fundamental CubeSat bus unit of 10 cm cubed can be combined in multiple units and offers a common form factor allowing for easy integration as secondary payloads on traditional launches and rapid testing of new technologies on-orbit. We describe a 6U CubeSat SGS measuring 10 cm x 20 cm x

Synchronous atmospheric radiation correction of GF-2 satellite multispectral image

Science.gov (United States)

Bian, Fuqiang; Fan, Dongdong; Zhang, Yan; Wang, Dandan

2018-02-01

GF-2 remote sensing products have been widely used in many fields for its high-quality information, which provides technical support for the the macroeconomic decisions. Atmospheric correction is the necessary part in the data preprocessing of the quantitative high resolution remote sensing, which can eliminate the signal interference in the radiation path caused by atmospheric scattering and absorption, and reducting apparent reflectance into real reflectance of the surface targets. Aiming at the problem that current research lack of atmospheric date which are synchronization and region matching of the surface observation image, this research utilize the MODIS Level 1B synchronous data to simulate synchronized atmospheric condition, and write programs to implementation process of aerosol retrieval and atmospheric correction, then generate a lookup table of the remote sensing image based on the radioactive transfer model of 6S (second simulation of a satellite signal in the solar spectrum) to correct the atmospheric effect of multispectral image from GF-2 satellite PMS-1 payload. According to the correction results, this paper analyzes the pixel histogram of the reflectance spectrum of the 4 spectral bands of PMS-1, and evaluates the correction results of different spectral bands. Then conducted a comparison experiment on the same GF-2 image based on the QUAC. According to the different targets respectively statistics the average value of NDVI, implement a comparative study of NDVI from two different results. The degree of influence was discussed by whether to adopt synchronous atmospheric date. The study shows that the result of the synchronous atmospheric parameters have significantly improved the quantitative application of the GF-2 remote sensing data.

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

Science.gov (United States)

Iabchoon, Sanwit; Wongsai, Sangdao; Chankon, Kanoksuk

2017-10-01

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

Band co-registration modeling of LAPAN-A3/IPB multispectral imager based on satellite attitude

Science.gov (United States)

Hakim, P. R.; Syafrudin, A. H.; Utama, S.; Jayani, A. P. S.

2018-05-01

One of significant geometric distortion on images of LAPAN-A3/IPB multispectral imager is co-registration error between each color channel detector. Band co-registration distortion usually can be corrected by using several approaches, which are manual method, image matching algorithm, or sensor modeling and calibration approach. This paper develops another approach to minimize band co-registration distortion on LAPAN-A3/IPB multispectral image by using supervised modeling of image matching with respect to satellite attitude. Modeling results show that band co-registration error in across-track axis is strongly influenced by yaw angle, while error in along-track axis is fairly influenced by both pitch and roll angle. Accuracy of the models obtained is pretty good, which lies between 1-3 pixels error for each axis of each pair of band co-registration. This mean that the model can be used to correct the distorted images without the need of slower image matching algorithm, nor the laborious effort needed in manual approach and sensor calibration. Since the calculation can be executed in order of seconds, this approach can be used in real time quick-look image processing in ground station or even in satellite on-board image processing.

Sun glitter imaging of submarine sand waves on the Taiwan Banks: Determination of the relaxation rate of short waves

Science.gov (United States)

Shao, Hao; Li, Yan; Li, Li

2011-06-01

Above sand waves on the seafloor, surface short waves, which are responsible for the radiance distribution in remote sensing imagery, are modulated gradually by the submarine topography. The relaxation rate μr characterizes the rate at which the short waves reach their saturation range after being disturbed. It is a key parameter in the weak hydrodynamic interaction theory and is also a most important parameter in the imaging mechanism used for mapping submarine bottom topography. In this study, a robust expression containing intensity and phase (advection effect) modulations of the perturbed action spectrum of short waves was deduced, by using the first-order weak hydrodynamic interaction theory. On the basis of the phase modulation, a method was developed to determine the relaxation rate in the Sun glitter imaging mechanism. The relaxation rates were estimated using in situ data measured on a cruise over the sand waves of the Taiwan Banks, a sea area between the East China Sea and the South China Sea, on 28-29 August 2006. Results showed that, under a wind speed of 5.0 m s-1, the relaxation rate of short waves was about 0.055 s-1 in response to current variations and about 0.025 s-1 equivalently in response to sea bottom topographic variations. The former value could be applied to interpret the amplitude of submarine topography by using satellite imagery, while the latter one (equivalent relaxation rate μ'r) could help to more accurately calibrate the spatial position of the retrieved sea bottom topography.

Experimental congruence of interval scale production from paired comparisons and ranking for image evaluation

Science.gov (United States)

Handley, John C.; Babcock, Jason S.; Pelz, Jeff B.

2003-12-01

Image evaluation tasks are often conducted using paired comparisons or ranking. To elicit interval scales, both methods rely on Thurstone's Law of Comparative Judgment in which objects closer in psychological space are more often confused in preference comparisons by a putative discriminal random process. It is often debated whether paired comparisons and ranking yield the same interval scales. An experiment was conducted to assess scale production using paired comparisons and ranking. For this experiment a Pioneer Plasma Display and Apple Cinema Display were used for stimulus presentation. Observers performed rank order and paired comparisons tasks on both displays. For each of five scenes, six images were created by manipulating attributes such as lightness, chroma, and hue using six different settings. The intention was to simulate the variability from a set of digital cameras or scanners. Nineteen subjects, (5 females, 14 males) ranging from 19-51 years of age participated in this experiment. Using a paired comparison model and a ranking model, scales were estimated for each display and image combination yielding ten scale pairs, ostensibly measuring the same psychological scale. The Bradley-Terry model was used for the paired comparisons data and the Bradley-Terry-Mallows model was used for the ranking data. Each model was fit using maximum likelihood estimation and assessed using likelihood ratio tests. Approximate 95% confidence intervals were also constructed using likelihood ratios. Model fits for paired comparisons were satisfactory for all scales except those from two image/display pairs; the ranking model fit uniformly well on all data sets. Arguing from overlapping confidence intervals, we conclude that paired comparisons and ranking produce no conflicting decisions regarding ultimate ordering of treatment preferences, but paired comparisons yield greater precision at the expense of lack-of-fit.

DETECTION OF BARCHAN DUNES IN HIGH RESOLUTION SATELLITE IMAGES

Directory of Open Access Journals (Sweden)

M. A. Azzaoui

2016-06-01

Full Text Available Barchan dunes are the fastest moving sand dunes in the desert. We developed a process to detect barchans dunes on High resolution satellite images. It consisted of three steps, we first enhanced the image using histogram equalization and noise reduction filters. Then, the second step proceeds to eliminate the parts of the image having a texture different from that of the barchans dunes. Using supervised learning, we tested a coarse to fine textural analysis based on Kolomogorov Smirnov test and Youden’s J-statistic on co-occurrence matrix. As an output we obtained a mask that we used in the next step to reduce the search area. In the third step we used a gliding window on the mask and check SURF features with SVM to get barchans dunes candidates. Detected barchans dunes were considered as the fusion of overlapping candidates. The results of this approach were very satisfying in processing time and precision.

Sensor and computing resource management for a small satellite

Science.gov (United States)

Bhatia, Abhilasha; Goehner, Kyle; Sand, John; Straub, Jeremy; Mohammad, Atif; Korvald, Christoffer; Nervold, Anders Kose

A small satellite in a low-Earth orbit (e.g., approximately a 300 to 400 km altitude) has an orbital velocity in the range of 8.5 km/s and completes an orbit approximately every 90 minutes. For a satellite with minimal attitude control, this presents a significant challenge in obtaining multiple images of a target region. Presuming an inclination in the range of 50 to 65 degrees, a limited number of opportunities to image a given target or communicate with a given ground station are available, over the course of a 24-hour period. For imaging needs (where solar illumination is required), the number of opportunities is further reduced. Given these short windows of opportunity for imaging, data transfer, and sending commands, scheduling must be optimized. In addition to the high-level scheduling performed for spacecraft operations, payload-level scheduling is also required. The mission requires that images be post-processed to maximize spatial resolution and minimize data transfer (through removing overlapping regions). The payload unit includes GPS and inertial measurement unit (IMU) hardware to aid in image alignment for the aforementioned. The payload scheduler must, thus, split its energy and computing-cycle budgets between determining an imaging sequence (required to capture the highly-overlapping data required for super-resolution and adjacent areas required for mosaicking), processing the imagery (to perform the super-resolution and mosaicking) and preparing the data for transmission (compressing it, etc.). This paper presents an approach for satellite control, scheduling and operations that allows the cameras, GPS and IMU to be used in conjunction to acquire higher-resolution imagery of a target region.

PROBLEMS AND LIMITATIONS OF SATELLITE IMAGE ORIENTATION FOR DETERMINATION OF HEIGHT MODELS

Directory of Open Access Journals (Sweden)

K. Jacobsen

2017-05-01

Full Text Available The usual satellite image orientation is based on bias corrected rational polynomial coefficients (RPC. The RPC are describing the direct sensor orientation of the satellite images. The locations of the projection centres today are without problems, but an accuracy limit is caused by the attitudes. Very high resolution satellites today are very agile, able to change the pointed area over 200km within 10 to 11 seconds. The corresponding fast attitude acceleration of the satellite may cause a jitter which cannot be expressed by the third order RPC, even if it is recorded by the gyros. Only a correction of the image geometry may help, but usually this will not be done. The first indication of jitter problems is shown by systematic errors of the y-parallaxes (py for the intersection of corresponding points during the computation of ground coordinates. These y-parallaxes have a limited influence to the ground coordinates, but similar problems can be expected for the x-parallaxes, determining directly the object height. Systematic y-parallaxes are shown for Ziyuan-3 (ZY3, WorldView-2 (WV2, Pleiades, Cartosat-1, IKONOS and GeoEye. Some of them have clear jitter effects. In addition linear trends of py can be seen. Linear trends in py and tilts in of computed height models may be caused by limited accuracy of the attitude registration, but also by bias correction with affinity transformation. The bias correction is based on ground control points (GCPs. The accuracy of the GCPs usually does not cause some limitations but the identification of the GCPs in the images may be difficult. With 2-dimensional bias corrected RPC-orientation by affinity transformation tilts of the generated height models may be caused, but due to large affine image deformations some satellites, as Cartosat-1, have to be handled with bias correction by affinity transformation. Instead of a 2-dimensional RPC-orientation also a 3-dimensional orientation is possible, respecting the

Problems and Limitations of Satellite Image Orientation for Determination of Height Models

Science.gov (United States)

Jacobsen, K.

2017-05-01

The usual satellite image orientation is based on bias corrected rational polynomial coefficients (RPC). The RPC are describing the direct sensor orientation of the satellite images. The locations of the projection centres today are without problems, but an accuracy limit is caused by the attitudes. Very high resolution satellites today are very agile, able to change the pointed area over 200km within 10 to 11 seconds. The corresponding fast attitude acceleration of the satellite may cause a jitter which cannot be expressed by the third order RPC, even if it is recorded by the gyros. Only a correction of the image geometry may help, but usually this will not be done. The first indication of jitter problems is shown by systematic errors of the y-parallaxes (py) for the intersection of corresponding points during the computation of ground coordinates. These y-parallaxes have a limited influence to the ground coordinates, but similar problems can be expected for the x-parallaxes, determining directly the object height. Systematic y-parallaxes are shown for Ziyuan-3 (ZY3), WorldView-2 (WV2), Pleiades, Cartosat-1, IKONOS and GeoEye. Some of them have clear jitter effects. In addition linear trends of py can be seen. Linear trends in py and tilts in of computed height models may be caused by limited accuracy of the attitude registration, but also by bias correction with affinity transformation. The bias correction is based on ground control points (GCPs). The accuracy of the GCPs usually does not cause some limitations but the identification of the GCPs in the images may be difficult. With 2-dimensional bias corrected RPC-orientation by affinity transformation tilts of the generated height models may be caused, but due to large affine image deformations some satellites, as Cartosat-1, have to be handled with bias correction by affinity transformation. Instead of a 2-dimensional RPC-orientation also a 3-dimensional orientation is possible, respecting the object height

Thematic mapping from satellite imagery

CERN Document Server

Denègre, J

2013-01-01

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

New Satellite Estimates of Mixed-Phase Cloud Properties: A Synergistic Approach for Application to Global Satellite Imager Data

Science.gov (United States)

Smith, W. L., Jr.; Spangenberg, D.; Fleeger, C.; Sun-Mack, S.; Chen, Y.; Minnis, P.

2016-12-01

Determining accurate cloud properties horizontally and vertically over a full range of time and space scales is currently next to impossible using data from either active or passive remote sensors or from modeling systems. Passive satellite imagers provide horizontal and temporal resolution of clouds, but little direct information on vertical structure. Active sensors provide vertical resolution but limited spatial and temporal coverage. Cloud models embedded in NWP can produce realistic clouds but often not at the right time or location. Thus, empirical techniques that integrate information from multiple observing and modeling systems are needed to more accurately characterize clouds and their impacts. Such a strategy is employed here in a new cloud water content profiling technique developed for application to satellite imager cloud retrievals based on VIS, IR and NIR radiances. Parameterizations are developed to relate imager retrievals of cloud top phase, optical depth, effective radius and temperature to ice and liquid water content profiles. The vertical structure information contained in the parameterizations is characterized climatologically from cloud model analyses, aircraft observations, ground-based remote sensing data, and from CloudSat and CALIPSO. Thus, realistic cloud-type dependent vertical structure information (including guidance on cloud phase partitioning) circumvents poor assumptions regarding vertical homogeneity that plague current passive satellite retrievals. This paper addresses mixed phase cloud conditions for clouds with glaciated tops including those associated with convection and mid-latitude storm systems. Novel outcomes of our approach include (1) simultaneous retrievals of ice and liquid water content and path, which are validated with active sensor, microwave and in-situ data, and yield improved global cloud climatologies, and (2) new estimates of super-cooled LWC, which are demonstrated in aviation safety applications and

Review On Feasibility of Using Satellite Imaging for Risk Management of Derailment Related Turnout Component Failures

Science.gov (United States)

Dindar, Serdar; Kaewunruen, Sakdirat; Osman, Mohd H.

2017-10-01

One of the emerging significant advances in engineering, satellite imaging (SI) is becoming very common in any kind of civil engineering projects e.g., bridge, canal, dam, earthworks, power plant, water works etc., to provide an accurate, economical and expeditious means of acquiring a rapid assessment. Satellite imaging services in general utilise combinations of high quality satellite imagery, image processing and interpretation to obtain specific required information, e.g. surface movement analysis. To extract, manipulate and provide such a precise knowledge, several systems, including geographic information systems (GIS) and global positioning system (GPS), are generally used for orthorectification. Although such systems are useful for mitigating risk from projects, their productiveness is arguable and operational risk after application is open to discussion. As the applicability of any novel application to the railway industry is often measured in terms of whether or not it has gained in-depth knowledge and to what degree, as a result of errors during its operation, this novel application generates risk in ongoing projects. This study reviews what can be achievable for risk management of railway turnouts thorough satellite imaging. The methodology is established on the basis of other published articles in this area and the results of applications to understand how applicable such imagining process is on railway turnouts, and how sub-systems in turnouts can be effectively traced/operated with less risk than at present. As a result of this review study, it is aimed that the railway sector better understands risk mitigation in particular applications.

Optimization of the Reconstruction Interval in Neurovascular 4D-CTA Imaging

Science.gov (United States)

Hoogenboom, T.C.H.; van Beurden, R.M.J.; van Teylingen, B.; Schenk, B.; Willems, P.W.A.

2012-01-01

Summary Time resolved whole brain CT angiography (4D-CTA) is a novel imaging technology providing information regarding blood flow. One of the factors that influence the diagnostic value of this examination is the temporal resolution, which is affected by the gantry rotation speed during acquisition and the reconstruction interval during post-processing. Post-processing determines the time spacing between two reconstructed volumes and, unlike rotation speed, does not affect radiation burden. The data sets of six patients who underwent a cranial 4D-CTA were used for this study. Raw data was acquired using a 320-slice scanner with a rotation speed of 2 Hz. The arterial to venous passage of an intravenous contrast bolus was captured during a 15 s continuous scan. The raw data was reconstructed using four different reconstruction-intervals: 0.2, 0.3, 0.5 and 1.0 s. The results were rated by two observers using a standardized score sheet. The appearance of each lesion was rated correctly in all readings. Scoring for quality of temporal resolution revealed a stepwise improvement from the 1.0 s interval to the 0.3 s interval, while no discernable improvement was noted between the 0.3 s and 0.2 s interval. An increase in temporal resolution may improve the diagnostic quality of cranial 4D-CTA. Using a rotation speed of 0.5 s, the optimal reconstruction interval appears to be 0.3 s, beyond which, changes can no longer be discerned. PMID:23217631

The effect of chorionicity and twin-to-twin delivery time interval on short-term outcome of the second twin

DEFF Research Database (Denmark)

Hjortø, Sofie; Nickelsen, Carsten; Petersen, Janne

2013-01-01

Abstract Objectives: To investigate the effect of chorionicity and twin-to-twin delivery time interval on short-term outcome in the second twin. Additionally, to investigate predictors of adverse outcome in both twins. Methods: Data included vaginally delivered twins (≥ 36 weeks) from Copenhagen ...

Meteorological satellite systems

CERN Document Server

Tan, Su-Yin

2014-01-01

“Meteorological Satellite Systems” is a primer on weather satellites and their Earth applications. This book reviews historic developments and recent technological advancements in GEO and polar orbiting meteorological satellites. It explores the evolution of these remote sensing technologies and their capabilities to monitor short- and long-term changes in weather patterns in response to climate change. Satellites developed by various countries, such as U.S. meteorological satellites, EUMETSAT, and Russian, Chinese, Japanese and Indian satellite platforms are reviewed. This book also discusses international efforts to coordinate meteorological remote sensing data collection and sharing. This title provides a ready and quick reference for information about meteorological satellites. It serves as a useful tool for a broad audience that includes students, academics, private consultants, engineers, scientists, and teachers.

Spatial and radiometric characterization of multi-spectrum satellite images through multi-fractal analysis

Science.gov (United States)

Alonso, Carmelo; Tarquis, Ana M.; Zúñiga, Ignacio; Benito, Rosa M.

2017-03-01

Several studies have shown that vegetation indexes can be used to estimate root zone soil moisture. Earth surface images, obtained by high-resolution satellites, presently give a lot of information on these indexes, based on the data of several wavelengths. Because of the potential capacity for systematic observations at various scales, remote sensing technology extends the possible data archives from the present time to several decades back. Because of this advantage, enormous efforts have been made by researchers and application specialists to delineate vegetation indexes from local scale to global scale by applying remote sensing imagery. In this work, four band images have been considered, which are involved in these vegetation indexes, and were taken by satellites Ikonos-2 and Landsat-7 of the same geographic location, to study the effect of both spatial (pixel size) and radiometric (number of bits coding the image) resolution on these wavelength bands as well as two vegetation indexes: the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI). In order to do so, a multi-fractal analysis of these multi-spectral images was applied in each of these bands and the two indexes derived. The results showed that spatial resolution has a similar scaling effect in the four bands, but radiometric resolution has a larger influence in blue and green bands than in red and near-infrared bands. The NDVI showed a higher sensitivity to the radiometric resolution than EVI. Both were equally affected by the spatial resolution. From both factors, the spatial resolution has a major impact in the multi-fractal spectrum for all the bands and the vegetation indexes. This information should be taken in to account when vegetation indexes based on different satellite sensors are obtained.

Environmental Testing Campaign and Verification of Satellite Deimos-2 at INTA

Science.gov (United States)

Hernandez, Daniel; Vazquez, Mercedes; Anon, Manuel; Olivo, Esperanza; Gallego, Pablo; Morillo, Pablo; Parra, Javier; Capraro; Luengo, Mar; Garcia, Beatriz; Villacorta, Pablo

2014-06-01

In this paper the environmental test campaign and verification of the DEIMOS-2 (DM2) satellite will be presented and described. DM2 will be ready for launch in 2014.Firstly, a short description of the satellite is presented, including its physical characteristics and intended optical performances. DEIMOS-2 is a LEO satellite for earth observation that will provide high resolution imaging services for agriculture, civil protection, environmental issues, disasters monitoring, climate change, urban planning, cartography, security and intelligence.Then, the verification and test campaign carried out on the SM and FM models at INTA is described; including Mechanical test for the SM and Climatic, Mechanical and Electromagnetic Compatibility tests for the FM. In addition, this paper includes Centre of Gravity and Moment of Inertia measurements for both models, and other verification activities carried out in order to ensure satellite's health during launch and its in orbit performance.

Mapping of Polar Areas Based on High-Resolution Satellite Images: The Example of the Henryk Arctowski Polish Antarctic Station

Science.gov (United States)

Kurczyński, Zdzisław; Różycki, Sebastian; Bylina, Paweł

2017-12-01

To produce orthophotomaps or digital elevation models, the most commonly used method is photogrammetric measurement. However, the use of aerial images is not easy in polar regions for logistical reasons. In these areas, remote sensing data acquired from satellite systems is much more useful. This paper presents the basic technical requirements of different products which can be obtain (in particular orthoimages and digital elevation model (DEM)) using Very-High-Resolution Satellite (VHRS) images. The study area was situated in the vicinity of the Henryk Arctowski Polish Antarctic Station on the Western Shore of Admiralty Bay, King George Island, Western Antarctic. Image processing was applied on two triplets of images acquired by the Pléiades 1A and 1B in March 2013. The results of the generation of orthoimages from the Pléiades systems without control points showed that the proposed method can achieve Root Mean Squared Error (RMSE) of 3-9 m. The presented Pléiades images are useful for thematic remote sensing analysis and processing of measurements. Using satellite images to produce remote sensing products for polar regions is highly beneficial and reliable and compares well with more expensive airborne photographs or field surveys.

Radiometric and geometric assessment of data from the RapidEye constellation of satellites

Science.gov (United States)

Chander, Gyanesh; Haque, Md. Obaidul; Sampath, Aparajithan; Brunn, A.; Trosset, G.; Hoffmann, D.; Roloff, S.; Thiele, M.; Anderson, C.

2013-01-01

To monitor land surface processes over a wide range of temporal and spatial scales, it is critical to have coordinated observations of the Earth's surface using imagery acquired from multiple spaceborne imaging sensors. The RapidEye (RE) satellite constellation acquires high-resolution satellite images covering the entire globe within a very short period of time by sensors identical in construction and cross-calibrated to each other. To evaluate the RE high-resolution Multi-spectral Imager (MSI) sensor capabilities, a cross-comparison between the RE constellation of sensors was performed first using image statistics based on large common areas observed over pseudo-invariant calibration sites (PICS) by the sensors and, second, by comparing the on-orbit radiometric calibration temporal trending over a large number of calibration sites. For any spectral band, the individual responses measured by the five satellites of the RE constellation were found to differ B2B) alignment of the image data sets. The position accuracy was assessed by comparing the RE imagery against high-resolution aerial imagery, while the B2B characterization was performed by registering each band against every other band to ensure that the proper band alignment is provided for an image product. The B2B results indicate that the internal alignments of these five RE bands are in agreement, with bands typically registered to within 0.25 pixels of each other or better.

Monitoring of Siberian biomass burning smoke from AHI on board geostationary satellite Himawari-8

Science.gov (United States)

Sano, I.; Mukai, S.; Yoshida, A.; Nakata, M.; Minoura, H.; Holben, B. N.

2016-12-01

High frequency aerosol measurements are demanded for evaluation of the model simulations, monitoring the atmospheric qualities such as Particulate Matter (PM2.5), and so on. Geostationary satellite provides us with the high frequency information of the atmosphere. Japanese Meteorological Agency (JMA) launched the Himawari-8 geostationary satellite in 2014 and has prepared Himawari-9 for launching in 2016. Both satellites carry new generation imagers named Advanced Himawari Imager (AHI). They have 16 multi-channels from short visible to thermal infrared wavelengths with 1 km IFOV for visible and 2 km for infrared. Each observation is done within 10 minutes for the Earth full disk. Then high frequency Earth observations are realized. AHI has frequently observed biomass burning plume around East Siberia and its transportation according to weather system. This work retrieves aerosol properties due to the Siberian smoke plume and its movements based on the measurements with AHI. The results are compared with ground based measurements which have newly deployed at an AERONET/Niigata site in Japan. It is shown here that continuous measurements of aerosols from geostationary satellite combination with the polar orbiting satellite provide us with much detail information of aerosol.

Determination of the Impact of Urbanization on Agricultural Lands using Multi-temporal Satellite Sensor Images

Science.gov (United States)

Kaya, S.; Alganci, U.; Sertel, E.; Ustundag, B.

2015-12-01

Throughout the history, agricultural activities have been performed close to urban areas. Main reason behind this phenomenon is the need of fast marketing of the agricultural production to urban residents and financial provision. Thus, using the areas nearby cities for agricultural activities brings out advantage of easy transportation of productions and fast marketing. For decades, heavy migration to cities has directly and negatively affected natural grasslands, forests and agricultural lands. This pressure has caused agricultural lands to be changed into urban areas. Dense urbanization causes increase in impervious surfaces, heat islands and many other problems in addition to destruction of agricultural lands. Considering the negative impacts of urbanization on agricultural lands and natural resources, a periodic monitoring of these changes becomes indisputably important. At this point, satellite images are known to be good data sources for land cover / use change monitoring with their fast data acquisition, large area coverages and temporal resolution properties. Classification of the satellite images provides thematic the land cover / use maps of the earth surface and changes can be determined with GIS based analysis multi-temporal maps. In this study, effects of heavy urbanization over agricultural lands in Istanbul, metropolitan city of Turkey, were investigated with use of multi-temporal Landsat TM satellite images acquired between 1984 and 2011. Images were geometrically registered to each other and classified using supervised maximum likelihood classification algorithm. Resulting thematic maps were exported to GIS environment and destructed agricultural lands by urbanization were determined using spatial analysis.

IMMUNOMETABOLIC RESPONSES AFTER SHORT AND MODERATE REST INTERVALS TO STRENGTH EXERCISE WITH AND WITHOUT SIMILAR TOTAL VOLUME.

Directory of Open Access Journals (Sweden)

Ricardo Agostinete

2016-10-01

Full Text Available This study investigated the influence of short and moderate intervals of recovery with and without equated volume during an acute bout exhaustive strength exercise on metabolic, hormonal and inflammatory responses in healthy adults. Eight physically active men (23.5 ±3.1 performed three randomized sequences: Short (70% of 1RM with 30 seconds of rest; Moderate (70% of 1RM with 90 seconds of rest; and Volume-Equated Short (70% of 1 RM with 30 seconds of rest between sets with a repetition volume equal to that performed in Moderate. All sequences of exercises were performed until movement failure in the squat, bench press and T-bar row exercises, respectively. Glucose, lactate, testosterone, IL-6, IL-10, IL-1ra and MCP-1 levels were assessed at rest, immediate post-exercise, and 1 hour post. There was a main effect of time for testosterone (p<0.001. The post hoc indicated differences between post-exercise and rest and post-1 hour and post-exercise (p<0.001. Lactate increased post-exercise when compared to pre and post-1 hour (p<0.001 and maintained higher post-1 hour in relation to rest. IL-6 was greater post-exercise than rest (p= 0.045 and post-1 hour and rest (p= 0.020. IL-10 was greater post-exercise (p= 0.007 and post-1 hour (p=0.002 than rest. IL-1ra increased post-exercise in relation to rest (p=0.003 and MCP-1 was greater post-exercise than rest (p<0.001 and post-1 hour (p=0.043. There were no significant differences between conditions or interaction. Thus, both short and moderate intervals of recovery induced greater metabolic, hormonal and inflammatory responses after acute bout of exhaustive strength exercise in healthy adult.

Design of a nano-satellite demonstrator of an infrared imaging space interferometer: the HyperCube

Science.gov (United States)

Dohlen, Kjetil; Vives, Sébastien; Rakotonimbahy, Eddy; Sarkar, Tanmoy; Tasnim Ava, Tanzila; Baccichet, Nicola; Savini, Giorgio; Swinyard, Bruce

2014-07-01

The construction of a kilometer-baseline far infrared imaging interferometer is one of the big instrumental challenges for astronomical instrumentation in the coming decades. Recent proposals such as FIRI, SPIRIT, and PFI illustrate both science cases, from exo-planetary science to study of interstellar media and cosmology, and ideas for construction of such instruments, both in space and on the ground. An interesting option for an imaging multi-aperture interferometer with km baseline is the space-based hyper telescope (HT) where a giant, sparsely populated primary mirror is constituted of several free-flying satellites each carrying a mirror segment. All the segments point the same object and direct their part of the pupil towards a common focus where another satellite, containing recombiner optics and a detector unit, is located. In Labeyrie's [1] original HT concept, perfect phasing of all the segments was assumed, allowing snap-shot imaging within a reduced field of view and coronagraphic extinction of the star. However, for a general purpose observatory, image reconstruction using closure phase a posteriori image reconstruction is possible as long as the pupil is fully non-redundant. Such reconstruction allows for much reduced alignment tolerances, since optical path length control is only required to within several tens of wavelengths, rather than within a fraction of a wavelength. In this paper we present preliminary studies for such an instrument and plans for building a miniature version to be flown on a nano satellite. A design for recombiner optics is proposed, including a scheme for exit pupil re-organization, is proposed, indicating the focal plane satellite in the case of a km-baseline interferometer could be contained within a 1m3 unit. Different options for realization of a miniature version are presented, including instruments for solar observations in the visible and the thermal infrared and giant planet observations in the visible, and an

Spatial, Temporal and Spectral Satellite Image Fusion via Sparse Representation

Science.gov (United States)

Song, Huihui

Remote sensing provides good measurements for monitoring and further analyzing the climate change, dynamics of ecosystem, and human activities in global or regional scales. Over the past two decades, the number of launched satellite sensors has been increasing with the development of aerospace technologies and the growing requirements on remote sensing data in a vast amount of application fields. However, a key technological challenge confronting these sensors is that they tradeoff between spatial resolution and other properties, including temporal resolution, spectral resolution, swath width, etc., due to the limitations of hardware technology and budget constraints. To increase the spatial resolution of data with other good properties, one possible cost-effective solution is to explore data integration methods that can fuse multi-resolution data from multiple sensors, thereby enhancing the application capabilities of available remote sensing data. In this thesis, we propose to fuse the spatial resolution with temporal resolution and spectral resolution, respectively, based on sparse representation theory. Taking the study case of Landsat ETM+ (with spatial resolution of 30m and temporal resolution of 16 days) and MODIS (with spatial resolution of 250m ~ 1km and daily temporal resolution) reflectance, we propose two spatial-temporal fusion methods to combine the fine spatial information of Landsat image and the daily temporal resolution of MODIS image. Motivated by that the images from these two sensors are comparable on corresponding bands, we propose to link their spatial information on available Landsat- MODIS image pair (captured on prior date) and then predict the Landsat image from the MODIS counterpart on prediction date. To well-learn the spatial details from the prior images, we use a redundant dictionary to extract the basic representation atoms for both Landsat and MODIS images based on sparse representation. Under the scenario of two prior Landsat

Image Quality Assessment of High-Resolution Satellite Images with Mtf-Based Fuzzy Comprehensive Evaluation Method

Science.gov (United States)

Wu, Z.; Luo, Z.; Zhang, Y.; Guo, F.; He, L.

2018-04-01

A Modulation Transfer Function (MTF)-based fuzzy comprehensive evaluation method was proposed in this paper for the purpose of evaluating high-resolution satellite image quality. To establish the factor set, two MTF features and seven radiant features were extracted from the knife-edge region of image patch, which included Nyquist, MTF0.5, entropy, peak signal to noise ratio (PSNR), average difference, edge intensity, average gradient, contrast and ground spatial distance (GSD). After analyzing the statistical distribution of above features, a fuzzy evaluation threshold table and fuzzy evaluation membership functions was established. The experiments for comprehensive quality assessment of different natural and artificial objects was done with GF2 image patches. The results showed that the calibration field image has the highest quality scores. The water image has closest image quality to the calibration field, quality of building image is a little poor than water image, but much higher than farmland image. In order to test the influence of different features on quality evaluation, the experiment with different weights were tested on GF2 and SPOT7 images. The results showed that different weights correspond different evaluating effectiveness. In the case of setting up the weights of edge features and GSD, the image quality of GF2 is better than SPOT7. However, when setting MTF and PSNR as main factor, the image quality of SPOT7 is better than GF2.

Satellite image analysis and a hybrid ESSS/ANN model to forecast solar irradiance in the tropics

International Nuclear Information System (INIS)

Dong, Zibo; Yang, Dazhi; Reindl, Thomas; Walsh, Wilfred M.

2014-01-01

Highlights: • Satellite image analysis is performed and cloud cover index is classified using self-organizing maps (SOM). • The ESSS model is used to forecast cloud cover index. • Solar irradiance is estimated using multi-layer perceptron (MLP). • The proposed model shows better accuracy than other investigated models. - Abstract: We forecast hourly solar irradiance time series using satellite image analysis and a hybrid exponential smoothing state space (ESSS) model together with artificial neural networks (ANN). Since cloud cover is the major factor affecting solar irradiance, cloud detection and classification are crucial to forecast solar irradiance. Geostationary satellite images provide cloud information, allowing a cloud cover index to be derived and analysed using self-organizing maps (SOM). Owing to the stochastic nature of cloud generation in tropical regions, the ESSS model is used to forecast cloud cover index. Among different models applied in ANN, we favour the multi-layer perceptron (MLP) to derive solar irradiance based on the cloud cover index. This hybrid model has been used to forecast hourly solar irradiance in Singapore and the technique is found to outperform traditional forecasting models

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

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P. Fischer

2018-04-01

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

Integration of Satellite Tracking Data and Satellite Images for Detailed Characteristics of Wildlife Habitats

Science.gov (United States)

Dobrynin, D. V.; Rozhnov, V. V.; Saveliev, A. A.; Sukhova, O. V.; Yachmennikova, A. A.

2017-12-01

Methods of analysis of the results got from satellite tracking of large terrestrial mammals differ in the level of their integration with additional geographic data. The reliable fine-scale cartographic basis for assessing specific wildlife habitats can be developed through the interpretation of multispectral remote sensing data and extrapolation of the results to the entire estimated species range. Topographic maps were ordinated according to classified features using self-organizing maps (Kohonen's SOM). The satellite image of the Ussuriiskyi Nature Reserve area was interpreted for the analysis of movement conditions for seven wild Amur tigers ( Panthera tigris altaica) equipped with GPS collars. 225 SOM classes for cartographic visualization are sufficient for the detailed mapping of all natural complexes that were identified as a result of interpretation. During snow-free periods, tigers preferred deciduous and shrub associations at lower elevations, as well as mixed forests in the valleys of streams that are adjacent to sparse forests and shrub watershed in the mountain ranges; during heavy snow periods, the animals preferred the entire range of plant communities in different relief types, except for open sites in meadows and abandoned fields at foothills. The border zones of different biotopes were typically used by the tigers during all seasons. Amur tigers preferred coniferous forests for long-term movements.

Mutual information registration of multi-spectral and multi-resolution images of DigitalGlobe's WorldView-3 imaging satellite

Science.gov (United States)

Miecznik, Grzegorz; Shafer, Jeff; Baugh, William M.; Bader, Brett; Karspeck, Milan; Pacifici, Fabio

2017-05-01

WorldView-3 (WV-3) is a DigitalGlobe commercial, high resolution, push-broom imaging satellite with three instruments: visible and near-infrared VNIR consisting of panchromatic (0.3m nadir GSD) plus multi-spectral (1.2m), short-wave infrared SWIR (3.7m), and multi-spectral CAVIS (30m). Nine VNIR bands, which are on one instrument, are nearly perfectly registered to each other, whereas eight SWIR bands, belonging to the second instrument, are misaligned with respect to VNIR and to each other. Geometric calibration and ortho-rectification results in a VNIR/SWIR alignment which is accurate to approximately 0.75 SWIR pixel at 3.7m GSD, whereas inter-SWIR, band to band registration is 0.3 SWIR pixel. Numerous high resolution, spectral applications, such as object classification and material identification, require more accurate registration, which can be achieved by utilizing image processing algorithms, for example Mutual Information (MI). Although MI-based co-registration algorithms are highly accurate, implementation details for automated processing can be challenging. One particular challenge is how to compute bin widths of intensity histograms, which are fundamental building blocks of MI. We solve this problem by making the bin widths proportional to instrument shot noise. Next, we show how to take advantage of multiple VNIR bands, and improve registration sensitivity to image alignment. To meet this goal, we employ Canonical Correlation Analysis, which maximizes VNIR/SWIR correlation through an optimal linear combination of VNIR bands. Finally we explore how to register images corresponding to different spatial resolutions. We show that MI computed at a low-resolution grid is more sensitive to alignment parameters than MI computed at a high-resolution grid. The proposed modifications allow us to improve VNIR/SWIR registration to better than ¼ of a SWIR pixel, as long as terrain elevation is properly accounted for, and clouds and water are masked out.

Development and Analysis of Image Registration Program for the Communication, Ocean, Meteorological Satellite (COMS

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Un-Seob Lee

2007-09-01

Full Text Available We developed a software for simulations and analyses of the Image Navigation and Registration (INR system, and compares the characteristics of Image Motion Compensation (IMC algorithms for the INR system. According to the orbit errors and attitude errors, the capabilities of the image distortions are analyzed. The distortions of images can be compensated by GOES IMC algorithm and Modified IMC (MIMC algorithm. The capabilities of each IMC algorithm are confirmed based on compensated images. The MIMC yields better results than GOES IMC although both the algorithms well compensate distorted images. The results of this research can be used as valuable asset to design of INR system for the Communication, Ocean, Meteorological Satellite (COMS.

A graph-based approach to detect spatiotemporal dynamics in satellite image time series

Science.gov (United States)

Guttler, Fabio; Ienco, Dino; Nin, Jordi; Teisseire, Maguelonne; Poncelet, Pascal

2017-08-01

Enhancing the frequency of satellite acquisitions represents a key issue for Earth Observation community nowadays. Repeated observations are crucial for monitoring purposes, particularly when intra-annual process should be taken into account. Time series of images constitute a valuable source of information in these cases. The goal of this paper is to propose a new methodological framework to automatically detect and extract spatiotemporal information from satellite image time series (SITS). Existing methods dealing with such kind of data are usually classification-oriented and cannot provide information about evolutions and temporal behaviors. In this paper we propose a graph-based strategy that combines object-based image analysis (OBIA) with data mining techniques. Image objects computed at each individual timestamp are connected across the time series and generates a set of evolution graphs. Each evolution graph is associated to a particular area within the study site and stores information about its temporal evolution. Such information can be deeply explored at the evolution graph scale or used to compare the graphs and supply a general picture at the study site scale. We validated our framework on two study sites located in the South of France and involving different types of natural, semi-natural and agricultural areas. The results obtained from a Landsat SITS support the quality of the methodological approach and illustrate how the framework can be employed to extract and characterize spatiotemporal dynamics.

MK-801 and memantine act differently on short-term memory tested with different time-intervals in the Morris water maze test.

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Duda, Weronika; Wesierska, Malgorzata; Ostaszewski, Pawel; Vales, Karel; Nekovarova, Tereza; Stuchlik, Ales

2016-09-15

N-methyl-d-aspartate receptors (NMDARs) play a crucial role in spatial memory formation. In neuropharmacological studies their functioning strongly depends on testing conditions and the dosage of NMDAR antagonists. The aim of this study was to assess the immediate effects of NMDAR block by (+)MK-801 or memantine on short-term allothetic memory. Memory was tested in a working memory version of the Morris water maze test. In our version of the test, rats underwent one day of training with 8 trials, and then three experimental days when rats were injected intraperitoneally with low- 5 (MeL), high - 20 (MeH) mg/kg memantine, 0.1mg/kg MK-801 or 1ml/kg saline (SAL) 30min before testing, for three consecutive days. On each experimental day there was just one acquisition and one test trial, with an inter-trial interval of 5 or 15min. During training the hidden platform was relocated after each trial and during the experiment after each day. The follow-up effect was assessed on day 9. Intact rats improved their spatial memory across the one training day. With a 5min interval MeH rats had longer latency then all rats during retrieval. With a 15min interval the MeH rats presented worse working memory measured as retrieval minus acquisition trial for path than SAL and MeL and for latency than MeL rats. MK-801 rats had longer latency than SAL during retrieval. Thus, the high dose of memantine, contrary to low dose of MK-801 disrupts short-term memory independent on the time interval between acquisition and retrieval. This shows that short-term memory tested in a working memory version of water maze is sensitive to several parameters: i.e., NMDA receptor antagonist type, dosage and the time interval between learning and testing. Copyright © 2016. Published by Elsevier B.V.

Screen-detected versus interval cancers: Effect of imaging modality and breast density in the Flemish Breast Cancer Screening Programme

Energy Technology Data Exchange (ETDEWEB)

Timmermans, Lore; Bacher, Klaus; Thierens, Hubert [Ghent University, Department of Basic Medical Sciences, QCC-Gent, Ghent (Belgium); Bleyen, Luc; Herck, Koen van [Ghent University, Centrum voor Preventie en Vroegtijdige Opsporing van Kanker, Ghent (Belgium); Lemmens, Kim; Ongeval, Chantal van; Steen, Andre van [University Hospitals Leuven, Department of Radiology, Leuven (Belgium); Martens, Patrick [Centrum voor Kankeropsporing, Bruges (Belgium); Brabander, Isabel de [Belgian Cancer Registry, Brussels (Belgium); Goossens, Mathieu [UZ Brussel, Dienst Kankerpreventie, Brussels (Belgium)

2017-09-15

To investigate if direct radiography (DR) performs better than screen-film mammography (SF) and computed radiography (CR) in dense breasts in a decentralized organised Breast Cancer Screening Programme. To this end, screen-detected versus interval cancers were studied in different BI-RADS density classes for these imaging modalities. The study cohort consisted of 351,532 women who participated in the Flemish Breast Cancer Screening Programme in 2009 and 2010. Information on screen-detected and interval cancers, breast density scores of radiologist second readers, and imaging modality was obtained by linkage of the databases of the Centre of Cancer Detection and the Belgian Cancer Registry. Overall, 67% of occurring breast cancers are screen detected and 33% are interval cancers, with DR performing better than SF and CR. The interval cancer rate increases gradually with breast density, regardless of modality. In the high-density class, the interval cancer rate exceeds the cancer detection rate for SF and CR, but not for DR. DR is superior to SF and CR with respect to cancer detection rates for high-density breasts. To reduce the high interval cancer rate in dense breasts, use of an additional imaging technique in screening can be taken into consideration. (orig.)

Screen-detected versus interval cancers: Effect of imaging modality and breast density in the Flemish Breast Cancer Screening Programme

International Nuclear Information System (INIS)

Timmermans, Lore; Bacher, Klaus; Thierens, Hubert; Bleyen, Luc; Herck, Koen van; Lemmens, Kim; Ongeval, Chantal van; Steen, Andre van; Martens, Patrick; Brabander, Isabel de; Goossens, Mathieu

2017-01-01

To investigate if direct radiography (DR) performs better than screen-film mammography (SF) and computed radiography (CR) in dense breasts in a decentralized organised Breast Cancer Screening Programme. To this end, screen-detected versus interval cancers were studied in different BI-RADS density classes for these imaging modalities. The study cohort consisted of 351,532 women who participated in the Flemish Breast Cancer Screening Programme in 2009 and 2010. Information on screen-detected and interval cancers, breast density scores of radiologist second readers, and imaging modality was obtained by linkage of the databases of the Centre of Cancer Detection and the Belgian Cancer Registry. Overall, 67% of occurring breast cancers are screen detected and 33% are interval cancers, with DR performing better than SF and CR. The interval cancer rate increases gradually with breast density, regardless of modality. In the high-density class, the interval cancer rate exceeds the cancer detection rate for SF and CR, but not for DR. DR is superior to SF and CR with respect to cancer detection rates for high-density breasts. To reduce the high interval cancer rate in dense breasts, use of an additional imaging technique in screening can be taken into consideration. (orig.)

The Satellite Clock Bias Prediction Method Based on Takagi-Sugeno Fuzzy Neural Network

Science.gov (United States)

Cai, C. L.; Yu, H. G.; Wei, Z. C.; Pan, J. D.

2017-05-01

The continuous improvement of the prediction accuracy of Satellite Clock Bias (SCB) is the key problem of precision navigation. In order to improve the precision of SCB prediction and better reflect the change characteristics of SCB, this paper proposes an SCB prediction method based on the Takagi-Sugeno fuzzy neural network. Firstly, the SCB values are pre-treated based on their characteristics. Then, an accurate Takagi-Sugeno fuzzy neural network model is established based on the preprocessed data to predict SCB. This paper uses the precise SCB data with different sampling intervals provided by IGS (International Global Navigation Satellite System Service) to realize the short-time prediction experiment, and the results are compared with the ARIMA (Auto-Regressive Integrated Moving Average) model, GM(1,1) model, and the quadratic polynomial model. The results show that the Takagi-Sugeno fuzzy neural network model is feasible and effective for the SCB short-time prediction experiment, and performs well for different types of clocks. The prediction results for the proposed method are better than the conventional methods obviously.

Monitoring Seasonal Evapotranspiration in Vulnerable Agriculture using Time Series VHSR Satellite Data

Science.gov (United States)

Dalezios, Nicolas; Spyropoulos, Nicos V.; Tarquis, Ana M.

2015-04-01

The research work stems from the hypothesis that it is possible to perform an estimation of seasonal water needs of olive tree farms under drought periods by cross correlating high spatial, spectral and temporal resolution (~monthly) of satellite data, acquired at well defined time intervals of the phenological cycle of crops, with ground-truth information simultaneously applied during the image acquisitions. The present research is for the first time, demonstrating the coordinated efforts of space engineers, satellite mission control planners, remote sensing scientists and ground teams to record at specific time intervals of the phenological cycle of trees from ground "zero" and from 770 km above the Earth's surface, the status of plants for subsequent cross correlation and analysis regarding the estimation of the seasonal evapotranspiration in vulnerable agricultural environment. The ETo and ETc derived by Penman-Montieth equation and reference Kc tables, compared with new ETd using the Kc extracted from the time series satellite data. Several vegetation indices were also used especially the RedEdge and the chlorophyll one based on WorldView-2 RedEdge and second NIR bands to relate the tree status with water and nutrition needs. Keywords: Evapotransipration, Very High Spatial Resolution - VHSR, time series, remote sensing, vulnerability, agriculture, vegetation indeces.

Satellite Image Time Series Decomposition Based on EEMD

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Yun-long Kong

2015-11-01

Full Text Available Satellite Image Time Series (SITS have recently been of great interest due to the emerging remote sensing capabilities for Earth observation. Trend and seasonal components are two crucial elements of SITS. In this paper, a novel framework of SITS decomposition based on Ensemble Empirical Mode Decomposition (EEMD is proposed. EEMD is achieved by sifting an ensemble of adaptive orthogonal components called Intrinsic Mode Functions (IMFs. EEMD is noise-assisted and overcomes the drawback of mode mixing in conventional Empirical Mode Decomposition (EMD. Inspired by these advantages, the aim of this work is to employ EEMD to decompose SITS into IMFs and to choose relevant IMFs for the separation of seasonal and trend components. In a series of simulations, IMFs extracted by EEMD achieved a clear representation with physical meaning. The experimental results of 16-day compositions of Moderate Resolution Imaging Spectroradiometer (MODIS, Normalized Difference Vegetation Index (NDVI, and Global Environment Monitoring Index (GEMI time series with disturbance illustrated the effectiveness and stability of the proposed approach to monitoring tasks, such as applications for the detection of abrupt changes.

Multi-temporal image analysis of historical aerial photographs and recent satellite imagery reveals evolution of water body surface area and polygonal terrain morphology in Kobuk Valley National Park, Alaska

International Nuclear Information System (INIS)

Necsoiu, Marius; Dinwiddie, Cynthia L; Walter, Gary R; Stothoff, Stuart A; Larsen, Amy

2013-01-01

Multi-temporal image analysis of very-high-resolution historical aerial and recent satellite imagery of the Ahnewetut Wetlands in Kobuk Valley National Park, Alaska, revealed the nature of thaw lake and polygonal terrain evolution over a 54-year period of record comprising two 27-year intervals (1951–1978, 1978–2005). Using active-contouring-based change detection, high-precision orthorectification and co-registration and the normalized difference index, surface area expansion and contraction of 22 shallow water bodies, ranging in size from 0.09 to 179 ha, and the transition of ice-wedge polygons from a low- to a high-centered morphology were quantified. Total surface area decreased by only 0.4% during the first time interval, but decreased by 5.5% during the second time interval. Twelve water bodies (ten lakes and two ponds) were relatively stable with net surface area decreases of ≤10%, including four lakes that gained area during both time intervals, whereas ten water bodies (five lakes and five ponds) had surface area losses in excess of 10%, including two ponds that drained completely. Polygonal terrain remained relatively stable during the first time interval, but transformation of polygons from low- to high-centered was significant during the second time interval. (letter)

Applying a CAD-generated imaging marker to assess short-term breast cancer risk

Science.gov (United States)

Mirniaharikandehei, Seyedehnafiseh; Zarafshani, Ali; Heidari, Morteza; Wang, Yunzhi; Aghaei, Faranak; Zheng, Bin

2018-02-01

Although whether using computer-aided detection (CAD) helps improve radiologists' performance in reading and interpreting mammograms is controversy due to higher false-positive detection rates, objective of this study is to investigate and test a new hypothesis that CAD-generated false-positives, in particular, the bilateral summation of false-positives, is a potential imaging marker associated with short-term breast cancer risk. An image dataset involving negative screening mammograms acquired from 1,044 women was retrospectively assembled. Each case involves 4 images of craniocaudal (CC) and mediolateral oblique (MLO) view of the left and right breasts. In the next subsequent mammography screening, 402 cases were positive for cancer detected and 642 remained negative. A CAD scheme was applied to process all "prior" negative mammograms. Some features from CAD scheme were extracted, which include detection seeds, the total number of false-positive regions, an average of detection scores and the sum of detection scores in CC and MLO view images. Then the features computed from two bilateral images of left and right breasts from either CC or MLO view were combined. In order to predict the likelihood of each testing case being positive in the next subsequent screening, two logistic regression models were trained and tested using a leave-one-case-out based cross-validation method. Data analysis demonstrated the maximum prediction accuracy with an area under a ROC curve of AUC=0.65+/-0.017 and the maximum adjusted odds ratio of 4.49 with a 95% confidence interval of [2.95, 6.83]. The results also illustrated an increasing trend in the adjusted odds ratio and risk prediction scores (pbreast cancer risk.

Differential Spatio-temporal Multiband Satellite Image Clustering using K-means Optimization With Reinforcement Programming

Directory of Open Access Journals (Sweden)

Irene Erlyn Wina Rachmawan

2015-06-01

Full Text Available Deforestration is one of the crucial issues in Indonesia because now Indonesia has world's highest deforestation rate. In other hand, multispectral image delivers a great source of data for studying spatial and temporal changeability of the environmental such as deforestration area. This research present differential image processing methods for detecting nature change of deforestration. Our differential image processing algorithms extract and indicating area automatically. The feature of our proposed idea produce extracted information from multiband satellite image and calculate the area of deforestration by years with calculating data using temporal dataset. Yet, multiband satellite image consists of big data size that were difficult to be handled for segmentation. Commonly, K- Means clustering is considered to be a powerfull clustering algorithm because of its ability to clustering big data. However K-Means has sensitivity of its first generated centroids, which could lead into a bad performance. In this paper we propose a new approach to optimize K-Means clustering using Reinforcement Programming in order to clustering multispectral image. We build a new mechanism for generating initial centroids by implementing exploration and exploitation knowledge from Reinforcement Programming. This optimization will lead a better result for K-means data cluster. We select multispectral image from Landsat 7 in past ten years in Medawai, Borneo, Indonesia, and apply two segmentation areas consist of deforestration land and forest field. We made series of experiments and compared the experimental results of K-means using Reinforcement Programming as optimizing initiate centroid and normal K-means without optimization process. Keywords: Deforestration, Multispectral images, landsat, automatic clustering, K-means.

Simultaneous observation of auroral substorm onset in Polar satellite global images and ground-based all-sky images

Science.gov (United States)

Ieda, Akimasa; Kauristie, Kirsti; Nishimura, Yukitoshi; Miyashita, Yukinaga; Frey, Harald U.; Juusola, Liisa; Whiter, Daniel; Nosé, Masahito; Fillingim, Matthew O.; Honary, Farideh; Rogers, Neil C.; Miyoshi, Yoshizumi; Miura, Tsubasa; Kawashima, Takahiro; Machida, Shinobu

2018-05-01

Substorm onset has originally been defined as a longitudinally extended sudden auroral brightening (Akasofu initial brightening: AIB) followed a few minutes later by an auroral poleward expansion in ground-based all-sky images (ASIs). In contrast, such clearly marked two-stage development has not been evident in satellite-based global images (GIs). Instead, substorm onsets have been identified as localized sudden brightenings that expand immediately poleward. To resolve these differences, optical substorm onset signatures in GIs and ASIs are compared in this study for a substorm that occurred on December 7, 1999. For this substorm, the Polar satellite ultraviolet global imager was operated with a fixed-filter (170 nm) mode, enabling a higher time resolution (37 s) than usual to resolve the possible two-stage development. These data were compared with 20-s resolution green-line (557.7 nm) ASIs at Muonio in Finland. The ASIs revealed the AIB at 2124:50 UT and the subsequent poleward expansion at 2127:50 UT, whereas the GIs revealed only an onset brightening that started at 2127:49 UT. Thus, the onset in the GIs was delayed relative to the AIB and in fact agreed with the poleward expansion in the ASIs. The fact that the AIB was not evident in the GIs may be attributed to the limited spatial resolution of GIs for thin auroral arc brightenings. The implications of these results for the definition of substorm onset are discussed herein.[Figure not available: see fulltext.

A Low-Complexity UEP Methodology Demonstrated on a Turbo-Encoded Wavelet Image Satellite Downlink

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Salemi Eric

2008-01-01

Full Text Available Realizing high-quality digital image transmission via a satellite link, while optimizing resource distribution and minimizing battery consumption, is a challenging task. This paper describes a methodology to optimize a turbo-encoded wavelet-based satellite downlink progressive image transmission system with unequal error protection (UEP techniques. To achieve that goal, we instantiate a generic UEP methodology onto the system, and demonstrate that the proposed solution has little impact on the average performance, while greatly reducing the run-time complexity. Based on a simple design-time distortion model and a low-complexity run-time algorithm, the provided solution can dynamically tune the system's configuration to any bitrate constraint or channel condition. The resulting system outperforms in terms of peak signal-to-noise ratio (PSNR, a state-of-the-art, fine-tuned equal error protection (EEP solution by as much as 2 dB.

A Low-Complexity UEP Methodology Demonstrated on a Turbo-Encoded Wavelet Image Satellite Downlink

Directory of Open Access Journals (Sweden)

Eric Salemi

2008-01-01

Full Text Available Realizing high-quality digital image transmission via a satellite link, while optimizing resource distribution and minimizing battery consumption, is a challenging task. This paper describes a methodology to optimize a turbo-encoded wavelet-based satellite downlink progressive image transmission system with unequal error protection (UEP techniques. To achieve that goal, we instantiate a generic UEP methodology onto the system, and demonstrate that the proposed solution has little impact on the average performance, while greatly reducing the run-time complexity. Based on a simple design-time distortion model and a low-complexity run-time algorithm, the provided solution can dynamically tune the system's configuration to any bitrate constraint or channel condition. The resulting system outperforms in terms of peak signal-to-noise ratio (PSNR, a state-of-the-art, fine-tuned equal error protection (EEP solution by as much as 2 dB.

Multitemporal Satellite Images for Knowledge of the Assyrian Capital Cities and for Monitoring Landscape Transformations in the Upper Course of Tigris River

Directory of Open Access Journals (Sweden)

Giuseppe Scardozzi

2011-01-01

Full Text Available The paper is concerned with the contribution that a rich documentation of multitemporal optical satellite images with high resolution provides for the knowledge of the five great Assyrian capital cities (Ashur, Kar-Tukulti-Ninurta, Kalhu, Dur-Sharrukin, and Nineveh, in northern Iraq. These images also allow monitoring changes of landscape in the higher course of the Tigris during the last half century and document damages in archaeological sites during the two Gulf Wars. The data set, available for each city, consists of panchromatic and multispectral images taken between 2001 and 2007 by modern commercial satellites (Ikonos-2, QuickBird-2, and WorldView-1 and of panchromatic photographs of U.S. spy satellites operating between 1965 and 1969 (Corona KH-4B and Gambit KH-7. These photos were taken before diffusion of mechanized agriculture and the expansion of urban areas, so they are very useful to document many archaeological features and the landscape that has been modified in the last decades, as shown by recent satellite images.

Sun glitter imaging analysis of submarine sand waves in HJ-1A/B satellite CCD images

Science.gov (United States)

Zhang, Huaguo; He, Xiekai; Yang, Kang; Fu, Bin; Guan, Weibing

2014-11-01

Submarine sand waves are a widespread bed-form in tidal environment. Submarine sand waves induce current convergence and divergence that affect sea surface roughness thus become visible in sun glitter images. These sun glitter images have been employed for mapping sand wave topography. However, there are lots of effect factors in sun glitter imaging of the submarine sand waves, such as the imaging geometry and dynamic environment condition. In this paper, several sun glitter images from HJ-1A/B in the Taiwan Banks are selected. These satellite sun glitter images are used to discuss sun glitter imaging characteristics in different sensor parameters and dynamic environment condition. To interpret the imaging characteristics, calculating the sun glitter radiance and analyzing its spatial characteristics of the sand wave in different images is the best way. In this study, a simulated model based on sun glitter radiation transmission is adopted to certify the imaging analysis in further. Some results are drawn based on the study. Firstly, the sun glitter radiation is mainly determined by sensor view angle. Second, the current is another key factor for the sun glitter. The opposite current direction will cause exchanging of bright stripes and dark stripes. Third, brightness reversal would happen at the critical angle. Therefore, when using sun glitter image to obtain depth inversion, one is advised to take advantage of image properties of sand waves and to pay attention to key dynamic environment condition and brightness reversal.

Combined Use of Multi-Temporal Optical and Radar Satellite Images for Grassland Monitoring

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Pauline Dusseux

2014-06-01

Full Text Available The aim of this study was to assess the ability of optical images, SAR (Synthetic Aperture Radar images and the combination of both types of data to discriminate between grasslands and crops in agricultural areas where cloud cover is very high most of the time, which restricts the use of visible and near-infrared satellite data. We compared the performances of variables extracted from four optical and five SAR satellite images with high/very high spatial resolutions acquired during the growing season. A vegetation index, namely the NDVI (Normalized Difference Vegetation Index, and two biophysical variables, the LAI (Leaf Area Index and the fCOVER (fraction of Vegetation Cover were computed using optical time series and polarization (HH, VV, HV, VH. The polarization ratio and polarimetric decomposition (Freeman–Durden and Cloude–Pottier were calculated using SAR time series. Then, variables derived from optical, SAR and both types of remotely-sensed data were successively classified using the Support Vector Machine (SVM technique. The results show that the classification accuracy of SAR variables is higher than those using optical data (0.98 compared to 0.81. They also highlight that the combination of optical and SAR time series data is of prime interest to discriminate grasslands from crops, allowing an improved classification accuracy.

Satellite Eye for Galathea 3. Annual report 2006

DEFF Research Database (Denmark)

Hasager, Charlotte Bay; Sørensen, Peter; Pedersen, Leif Toudal

The Satellite Eye for Galathea 3 project is collecting satellite images from many satellites and, in particular, from the European ENVISAT satellite along the Galathea 3 global route. The expedition takes place from 11 August 2006 to 27 April 2007. Prior to the expedition several satellite images...... Vædderen, pupils in the classrooms and the public at any moment can take a look at the conditions seen from the eyes of the Earth observing satellites....

Mobile satellite service communications tests using a NASA satellite

Science.gov (United States)

Chambers, Katherine H.; Koschmeder, Louis A.; Hollansworth, James E.; ONeill, Jack; Jones, Robert E.; Gibbons, Richard C.

1995-01-01

Emerging applications of commercial mobile satellite communications include satellite delivery of compact disc (CD) quality radio to car drivers who can select their favorite programming as they drive any distance; transmission of current air traffic data to aircraft; and handheld communication of data and images from any remote corner of the world. Experiments with the enabling technologies and tests and demonstrations of these concepts are being conducted before the first satellite is launched by utilizing an existing NASA spacecraft.

kCCA Transformation-Based Radiometric Normalization of Multi-Temporal Satellite Images

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Yang Bai

2018-03-01

Full Text Available Radiation normalization is an essential pre-processing step for generating high-quality satellite sequence images. However, most radiometric normalization methods are linear, and they cannot eliminate the regular nonlinear spectral differences. Here we introduce the well-established kernel canonical correlation analysis (kCCA into radiometric normalization for the first time to overcome this problem, which leads to a new kernel method. It can maximally reduce the image differences among multi-temporal images regardless of the imaging conditions and the reflectivity difference. It also perfectly eliminates the impact of nonlinear changes caused by seasonal variation of natural objects. Comparisons with the multivariate alteration detection (CCA-based normalization and the histogram matching, on Gaofen-1 (GF-1 data, indicate that the kCCA-based normalization can preserve more similarity and better correlation between an image-pair and effectively avoid the color error propagation. The proposed method not only builds the common scale or reference to make the radiometric consistency among GF-1 image sequences, but also highlights the interesting spectral changes while eliminates less interesting spectral changes. Our method enables the application of GF-1 data for change detection, land-use, land-cover change detection etc.

Application of SVM on satellite images to detect hotspots in Jharia coal field region of India

Energy Technology Data Exchange (ETDEWEB)

Gautam, R.S.; Singh, D.; Mittal, A.; Sajin, P. [Indian Institute for Technology, Roorkee (India)

2008-07-01

The present paper deals with the application of Support Vector Machine (SVM) and image analysis techniques on NOAA/AVHRR satellite image to detect hotspots on the Jharia coal field region of India. One of the major advantages of using these satellite data is that the data are free with very good temporal resolution; while, one drawback is that these have low spatial resolution (i.e., approximately 1.1 km at nadir). Therefore, it is important to do research by applying some efficient optimization techniques along with the image analysis techniques to rectify these drawbacks and use satellite images for efficient hotspot detection and monitoring. For this purpose, SVM and multi-threshold techniques are explored for hotspot detection. The multi-threshold algorithm is developed to remove the cloud coverage from the land coverage. This algorithm also highlights the hotspots or fire spots in the suspected regions. SVM has the advantage over multi-thresholding technique that it can learn patterns from the examples and therefore is used to optimize the performance by removing the false points which are highlighted in the threshold technique. Both approaches can be used separately or in combination depending on the size of the image. The RBF (Radial Basis Function) kernel is used in training of three sets of inputs: brightness temperature of channel 3, Normalized Difference Vegetation Index (NDVI) and Global Environment Monitoring Index (GEMI), respectively. This makes a classified image in the output that highlights the hotspot and non-hotspot pixels. The performance of the SVM is also compared with the performance obtained from the neural networks and SVM appears to detect hotspots more accurately (greater than 91% classification accuracy) with lesser false alarm rate. The results obtained are found to be in good agreement with the ground based observations of the hotspots.

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

Science.gov (United States)

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

2014-01-01

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

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

Directory of Open Access Journals (Sweden)

Seth Stapleton

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

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

Science.gov (United States)

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

2014-01-01

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

Evaluation of skeletal muscle during exercise on short repetition time MR imaging

International Nuclear Information System (INIS)

Yoshioka, Hiroshi; Niitsu, Mamoru; Anno, Izumi; Takahashi, Hideyuki; Kuno, Shinya; Matsumoto, Kunihiko; Itai, Yuji

1992-01-01

There have been many reports on the effects of exercise on skeletal muscle signal intensities based on magnetic resonance (MR) imaging. These images were obtained using T 2 -weighted MR images. The purpose of this study was to observe muscles during exercise while shortening the repetition time (TR) on spin echo images. In addition, inactive and active muscles were differentiated in the same manner. T 2 values of the tibialis anterior m. were calculated from TR=400 ms to TR=3000 ms. These values were mostly constant and didn't depend upon TR. Increases in signal intensities of the exercise muscles could be observed on the short TR (600 ms) MR images since the changes of the signal intensities mainly depend upon T 2 values. Thus, the T 2 value is useful as a quantitative index to assess the exercise muscle even on the short TR MR images. (author)

HIMAWARI-8 Geostationary Satellite Observation of the Internal Solitary Waves in the South China Sea

Science.gov (United States)

Gao, Q.; Dong, D.; Yang, X.; Husi, L.; Shang, H.

2018-04-01

The new generation geostationary meteorological satellite, Himawari-8 (H-8), was launched in 2015. Its main payload, the Advanced Himawari Imager (AHI), can observe the earth with 10-minute interval and as high as 500-m spatial resolution. This makes the H-8 satellite an ideal data source for marine and atmospheric phenomena monitoring. In this study, the propagation of internal solitary waves (ISWs) in the South China Sea is investigated using AHI imagery time series for the first time. Three ISWs cases were studied at 3:30-8:00 UTC on 30 May, 2016. In all, 28 ISWs were detected and tracked between the time series image pairs. The propagation direction and phase speeds of these ISWs are calculated and analyzed. The observation results show that the properties of ISW propagation not stable and maintains nonlinear during its lifetime. The resultant ISW speeds agree well with the theoretical values estimated from the Taylor-Goldstein equation using Argo dataset. This study has demonstrated that the new generation geostationary satellite can be a useful tool to monitor and investigate the oceanic internal waves.

Inter-pregnancy interval and pregnancy outcomes among HIV ...

African Journals Online (AJOL)

owner

Abstract Background: Both short and long inter-pregnancy intervals have been associated with higher risk of adverse pregnancy outcomes. More so, short inter- pregnancy interval among HIV- positive women implies higher birth rate and subsequently a higher number of neonates exposed to HIV and potentially at.

PLEIADES-HR INNOVATIVE TECHNIQUES FOR GEOMETRIC IMAGE QUALITY COMMISSIONING

Directory of Open Access Journals (Sweden)

D. Greslou

2012-07-01

Full Text Available Since the beginning of 2012, the first Pleiades-HR satellite of the program conducted by the French National Space Agency, CNES, delivers 20 km wide color scenes with a 70 cm ground sampling distance. A second satellite should be launched in 2013 which will achieve an almost world-wide coverage with a revisit interval of 24h. The assessment of the image quality and the calibration operation have been performed by CNES Image Quality team during the 6 month commissioning phase that followed the satellite launch. The geometric commissioning activities consist in improve the geometric quality of the images in order to meet very demanding specifications as localization accuracy, local coherence, dynamic stability, length alteration … This goal has been achieved through the implementation of new methods of calibration and performance assessment. Some of these methods are based on the exploitation of very specific satellite acquisitions that have been achieved thanks to the amazing agility of the Pleiades satellite. Thus, many stars acquisitions and very slow earth pictures have been processed to characterize dynamic phenomena. Similarly, “along-cross track” pairs have been exploited to improve the accuracy of the focal plane description. This paper deals with these new methods. It describes their accuracy and their operational interests.

Studying a free fall experiment using short sequences of images

International Nuclear Information System (INIS)

Vera, Francisco; Romanque, Cristian

2008-01-01

We discuss a new alternative for obtaining position and time coordinates from a video of a free fall experiment. In our approach, after converting the video to a short sequence of images, the images are analyzed using a web page application developed by the author. The main advantage of the setup explained in this work, is that it is simple to use, no software license fees are necessary, and can be scaled-up to be used by a big number of students in introductory physics courses. The steps involved in the full analysis of a falling object are: we grab a short digital video of the experiment and convert it to a sequence of images, then, using a web page that includes all the necessary javascript, the student can easily click on the object of interest to obtain the (x,y,t) coordinates, finally, the student analyze motion using a spreadsheet.

Rule-based land cover classification from very high-resolution satellite image with multiresolution segmentation

Science.gov (United States)

Haque, Md. Enamul; Al-Ramadan, Baqer; Johnson, Brian A.

2016-07-01

Multiresolution segmentation and rule-based classification techniques are used to classify objects from very high-resolution satellite images of urban areas. Custom rules are developed using different spectral, geometric, and textural features with five scale parameters, which exploit varying classification accuracy. Principal component analysis is used to select the most important features out of a total of 207 different features. In particular, seven different object types are considered for classification. The overall classification accuracy achieved for the rule-based method is 95.55% and 98.95% for seven and five classes, respectively. Other classifiers that are not using rules perform at 84.17% and 97.3% accuracy for seven and five classes, respectively. The results exploit coarse segmentation for higher scale parameter and fine segmentation for lower scale parameter. The major contribution of this research is the development of rule sets and the identification of major features for satellite image classification where the rule sets are transferable and the parameters are tunable for different types of imagery. Additionally, the individual objectwise classification and principal component analysis help to identify the required object from an arbitrary number of objects within images given ground truth data for the training.

Cyclone track forecasting based on satellite images using artificial neural networks

OpenAIRE

Kovordanyi, Rita; Roy, Chandan

2009-01-01

Many places around the world are exposed to tropical cyclones and associated storm surges. In spite of massive efforts, a great number of people die each year as a result of cyclone events. To mitigate this damage, improved forecasting techniques must be developed. The technique presented here uses artificial neural networks to interpret NOAA-AVHRR satellite images. A multi-layer neural network, resembling the human visual system, was trained to forecast the movement of cyclones based on sate...

Object-Oriented Analysis of Satellite Images Using Artificial Neural Networks for Post-Earthquake Buildings Change Detection

Science.gov (United States)

Khodaverdi zahraee, N.; Rastiveis, H.

2017-09-01

Earthquake is one of the most divesting natural events that threaten human life during history. After the earthquake, having information about the damaged area, the amount and type of damage can be a great help in the relief and reconstruction for disaster managers. It is very important that these measures should be taken immediately after the earthquake because any negligence could be more criminal losses. The purpose of this paper is to propose and implement an automatic approach for mapping destructed buildings after an earthquake using pre- and post-event high resolution satellite images. In the proposed method after preprocessing, segmentation of both images is performed using multi-resolution segmentation technique. Then, the segmentation results are intersected with ArcGIS to obtain equal image objects on both images. After that, appropriate textural features, which make a better difference between changed or unchanged areas, are calculated for all the image objects. Finally, subtracting the extracted textural features from pre- and post-event images, obtained values are applied as an input feature vector in an artificial neural network for classifying the area into two classes of changed and unchanged areas. The proposed method was evaluated using WorldView2 satellite images, acquired before and after the 2010 Haiti earthquake. The reported overall accuracy of 93% proved the ability of the proposed method for post-earthquake buildings change detection.

Tile-Level Annotation of Satellite Images Using Multi-Level Max-Margin Discriminative Random Field

Directory of Open Access Journals (Sweden)

Hong Sun

2013-05-01

Full Text Available This paper proposes a multi-level max-margin discriminative analysis (M3DA framework, which takes both coarse and fine semantics into consideration, for the annotation of high-resolution satellite images. In order to generate more discriminative topic-level features, the M3DA uses the maximum entropy discrimination latent Dirichlet Allocation (MedLDA model. Moreover, for improving the spatial coherence of visual words neglected by M3DA, conditional random field (CRF is employed to optimize the soft label field composed of multiple label posteriors. The framework of M3DA enables one to combine word-level features (generated by support vector machines and topic-level features (generated by MedLDA via the bag-of-words representation. The experimental results on high-resolution satellite images have demonstrated that, using the proposed method can not only obtain suitable semantic interpretation, but also improve the annotation performance by taking into account the multi-level semantics and the contextual information.

Improving Sediment Transport Prediction by Assimilating Satellite Images in a Tidal Bay Model of Hong Kong

Directory of Open Access Journals (Sweden)

Peng Zhang

2014-03-01

Full Text Available Numerical models being one of the major tools for sediment dynamic studies in complex coastal waters are now benefitting from remote sensing images that are easily available for model inputs. The present study explored various methods of integrating remote sensing ocean color data into a numerical model to improve sediment transport prediction in a tide-dominated bay in Hong Kong, Deep Bay. Two sea surface sediment datasets delineated from satellite images from the Moderate Resolution Imaging Spectra-radiometer (MODIS were assimilated into a coastal ocean model of the bay for one tidal cycle. It was found that remote sensing sediment information enhanced the sediment transport model ability by validating the model results with in situ measurements. Model results showed that root mean square errors of forecast sediment both at the surface layer and the vertical layers from the model with satellite sediment assimilation are reduced by at least 36% over the model without assimilation.

Road Network Extraction from VHR Satellite Images Using Context Aware Object Feature Integration and Tensor Voting

Directory of Open Access Journals (Sweden)

Mehdi Maboudi

2016-08-01

Full Text Available Road networks are very important features in geospatial databases. Even though high-resolution optical satellite images have already been acquired for more than a decade, tools for automated extraction of road networks from these images are still rare. One consequence of this is the need for manual interaction which, in turn, is time and cost intensive. In this paper, a multi-stage approach is proposed which integrates structural, spectral, textural, as well as contextual information of objects to extract road networks from very high resolution satellite images. Highlights of the approach are a novel linearity index employed for the discrimination of elongated road segments from other objects and customized tensor voting which is utilized to fill missing parts of the network. Experiments are carried out with different datasets. Comparison of the achieved results with the results of seven state-of-the-art methods demonstrated the efficiency of the proposed approach.

Screen-detected versus interval cancers: Effect of imaging modality and breast density in the Flemish Breast Cancer Screening Programme.

Science.gov (United States)

Timmermans, Lore; Bleyen, Luc; Bacher, Klaus; Van Herck, Koen; Lemmens, Kim; Van Ongeval, Chantal; Van Steen, Andre; Martens, Patrick; De Brabander, Isabel; Goossens, Mathieu; Thierens, Hubert

2017-09-01

To investigate if direct radiography (DR) performs better than screen-film mammography (SF) and computed radiography (CR) in dense breasts in a decentralized organised Breast Cancer Screening Programme. To this end, screen-detected versus interval cancers were studied in different BI-RADS density classes for these imaging modalities. The study cohort consisted of 351,532 women who participated in the Flemish Breast Cancer Screening Programme in 2009 and 2010. Information on screen-detected and interval cancers, breast density scores of radiologist second readers, and imaging modality was obtained by linkage of the databases of the Centre of Cancer Detection and the Belgian Cancer Registry. Overall, 67% of occurring breast cancers are screen detected and 33% are interval cancers, with DR performing better than SF and CR. The interval cancer rate increases gradually with breast density, regardless of modality. In the high-density class, the interval cancer rate exceeds the cancer detection rate for SF and CR, but not for DR. DR is superior to SF and CR with respect to cancer detection rates for high-density breasts. To reduce the high interval cancer rate in dense breasts, use of an additional imaging technique in screening can be taken into consideration. • Interval cancer rate increases gradually with breast density, regardless of modality. • Cancer detection rate in high-density breasts is superior in DR. • IC rate exceeds CDR for SF and CR in high-density breasts. • DR performs better in high-density breasts for third readings and false-positives.

Short interval follow-up after a benign concordant MR-guided vacuum assisted breast biopsy - is it worthwhile?

Energy Technology Data Exchange (ETDEWEB)

Shaylor, Sara D.; Melsaether, Amy N.; Gupta, Avani; Babb, James; Moy, Linda [NYU School of Medicine, Department of Radiology, New York, NY (United States); Heller, Samantha L. [St. George' s Healthcare Trust, Department of Radiology, London (United Kingdom); Gupta, Dipti [Northwestern Memorial Hospital, Breast and Women' s Imaging Center, Chicago, IL (United States)

2014-06-15

To determine the utility of short-interval follow-up after benign concordant MRI-guided breast biopsy. Institutional review board approved, retrospective review of consecutive biopsies performed over 3 years (2007-10) yielded 170 women with 188 lesions that were considered benign concordant. Indication for original study, biopsy results, follow-up recommendations, compliance and outcomes of subsequent MRI and mammography examinations were reviewed. The most common indication for breast MRI was high-risk screening 119/170 (70 %). Overall, 59 % of lesions (113/188) had follow-up MRI. Of those lesions (n = 113), 43 % (49/113) presented within 7 months, 26 % (29/113) presented within 8-13 months, 11.5 % (13/113) presented within 14-22 months, and 19 % (22/113) presented after 23 months. At initial follow-up, 37 % of lesions were stable and 61 % were decreased in size. Three lesions were recommended for excision based on follow-up imaging with one malignancy diagnosed 2 years following biopsy. One additional patient had MRI-detected bilateral cancers remote from the biopsy site 3 years after biopsy. Overall cancer yield of lesions with follow-up MRI was 0.9 % (1/113); no cancers were detected at 6 months. Our data suggests that 6-month follow-up may not be required and that annual screening MRI would be acceptable to maintain a reasonable cancer detection rate. (orig.)

Short interval follow-up after a benign concordant MR-guided vacuum assisted breast biopsy - is it worthwhile?

International Nuclear Information System (INIS)

Shaylor, Sara D.; Melsaether, Amy N.; Gupta, Avani; Babb, James; Moy, Linda; Heller, Samantha L.; Gupta, Dipti

2014-01-01

To determine the utility of short-interval follow-up after benign concordant MRI-guided breast biopsy. Institutional review board approved, retrospective review of consecutive biopsies performed over 3 years (2007-10) yielded 170 women with 188 lesions that were considered benign concordant. Indication for original study, biopsy results, follow-up recommendations, compliance and outcomes of subsequent MRI and mammography examinations were reviewed. The most common indication for breast MRI was high-risk screening 119/170 (70 %). Overall, 59 % of lesions (113/188) had follow-up MRI. Of those lesions (n = 113), 43 % (49/113) presented within 7 months, 26 % (29/113) presented within 8-13 months, 11.5 % (13/113) presented within 14-22 months, and 19 % (22/113) presented after 23 months. At initial follow-up, 37 % of lesions were stable and 61 % were decreased in size. Three lesions were recommended for excision based on follow-up imaging with one malignancy diagnosed 2 years following biopsy. One additional patient had MRI-detected bilateral cancers remote from the biopsy site 3 years after biopsy. Overall cancer yield of lesions with follow-up MRI was 0.9 % (1/113); no cancers were detected at 6 months. Our data suggests that 6-month follow-up may not be required and that annual screening MRI would be acceptable to maintain a reasonable cancer detection rate. (orig.)

Sediment plume model-a comparison between use of measured turbidity data and satellite images for model calibration.

Science.gov (United States)

Sadeghian, Amir; Hudson, Jeff; Wheater, Howard; Lindenschmidt, Karl-Erich

2017-08-01

In this study, we built a two-dimensional sediment transport model of Lake Diefenbaker, Saskatchewan, Canada. It was calibrated by using measured turbidity data from stations along the reservoir and satellite images based on a flood event in 2013. In June 2013, there was heavy rainfall for two consecutive days on the frozen and snow-covered ground in the higher elevations of western Alberta, Canada. The runoff from the rainfall and the melted snow caused one of the largest recorded inflows to the headwaters of the South Saskatchewan River and Lake Diefenbaker downstream. An estimated discharge peak of over 5200 m 3 /s arrived at the reservoir inlet with a thick sediment front within a few days. The sediment plume moved quickly through the entire reservoir and remained visible from satellite images for over 2 weeks along most of the reservoir, leading to concerns regarding water quality. The aims of this study are to compare, quantitatively and qualitatively, the efficacy of using turbidity data and satellite images for sediment transport model calibration and to determine how accurately a sediment transport model can simulate sediment transport based on each of them. Both turbidity data and satellite images were very useful for calibrating the sediment transport model quantitatively and qualitatively. Model predictions and turbidity measurements show that the flood water and suspended sediments entered upstream fairly well mixed and moved downstream as overflow with a sharp gradient at the plume front. The model results suggest that the settling and resuspension rates of sediment are directly proportional to flow characteristics and that the use of constant coefficients leads to model underestimation or overestimation unless more data on sediment formation become available. Hence, this study reiterates the significance of the availability of data on sediment distribution and characteristics for building a robust and reliable sediment transport model.

Verifying Air Force Weather Passive Satellite Derived Cloud Analysis Products

Science.gov (United States)

Nobis, T. E.

2017-12-01

Air Force Weather (AFW) has developed an hourly World-Wide Merged Cloud Analysis (WWMCA) using imager data from 16 geostationary and polar-orbiting satellites. The analysis product contains information on cloud fraction, height, type and various optical properties including optical depth and integrated water path. All of these products are derived using a suite of algorithms which rely exclusively on passively sensed data from short, mid and long wave imager data. The system integrates satellites with a wide-range of capabilities, from the relatively simple two-channel OLS imager to the 16 channel ABI/AHI to create a seamless global analysis in real time. Over the last couple of years, AFW has started utilizing independent verification data from active sensed cloud measurements to better understand the performance limitations of the WWMCA. Sources utilized include space based lidars (CALIPSO, CATS) and radar (CloudSat) as well as ground based lidars from the Department of Energy ARM sites and several European cloud radars. This work will present findings from our efforts to compare active and passive sensed cloud information including comparison techniques/limitations as well as performance of the passive derived cloud information against the active.

Space situational awareness satellites and ground based radiation counting and imaging detector technology

International Nuclear Information System (INIS)

Jansen, Frank; Behrens, Joerg; Pospisil, Stanislav; Kudela, Karel

2011-01-01

We review the current status from the scientific and technological point of view of solar energetic particles, solar and galactic cosmic ray measurements as well as high energy UV-, X- and gamma-ray imaging of the Sun. These particles and electromagnetic data are an important tool for space situational awareness (SSA) aspects like space weather storm predictions to avoid failures in space, air and ground based technological systems. Real time data acquisition, position and energy sensitive imaging are demanded by the international space weather forecast services. We present how newly developed, highly miniaturized radiation detectors can find application in space in view of future SSA related satellites as a novel space application due to their counting and imaging capabilities.

Space situational awareness satellites and ground based radiation counting and imaging detector technology

Energy Technology Data Exchange (ETDEWEB)

Jansen, Frank, E-mail: frank.jansen@dlr.de [DLR Institute of Space Systems, Robert-Hooke-Str. 7, 28359 Bremen (Germany); Behrens, Joerg [DLR Institute of Space Systems, Robert-Hooke-Str. 7, 28359 Bremen (Germany); Pospisil, Stanislav [Czech Technical University, IEAP, 12800 Prague 2, Horska 3a/22 (Czech Republic); Kudela, Karel [Slovak Academy of Sciences, IEP, 04001 Kosice, Watsonova 47 (Slovakia)

2011-05-15

We review the current status from the scientific and technological point of view of solar energetic particles, solar and galactic cosmic ray measurements as well as high energy UV-, X- and gamma-ray imaging of the Sun. These particles and electromagnetic data are an important tool for space situational awareness (SSA) aspects like space weather storm predictions to avoid failures in space, air and ground based technological systems. Real time data acquisition, position and energy sensitive imaging are demanded by the international space weather forecast services. We present how newly developed, highly miniaturized radiation detectors can find application in space in view of future SSA related satellites as a novel space application due to their counting and imaging capabilities.

Perception of short time scale intervals in a hypnotic virtuoso

NARCIS (Netherlands)

Noreika, Valdas; Falter, Christine M.; Arstila, Valtteri; Wearden, John H.; Kallio, Sakari

2012-01-01

Previous studies showed that hypnotized individuals underestimate temporal intervals in the range of several seconds to tens of minutes. However, no previous work has investigated whether duration perception is equally disorderly when shorter time intervals are probed. In this study, duration

Backthinned TDI CCD image sensor design and performance for the Pleiades high resolution Earth observation satellites

Science.gov (United States)

Materne, A.; Bardoux, A.; Geoffray, H.; Tournier, T.; Kubik, P.; Morris, D.; Wallace, I.; Renard, C.

2017-11-01

The PLEIADES-HR Earth observing satellites, under CNES development, combine a 0.7m resolution panchromatic channel, and a multispectral channel allowing a 2.8 m resolution, in 4 spectral bands. The 2 satellites will be placed on a sun-synchronous orbit at an altitude of 695 km. The camera operates in push broom mode, providing images across a 20 km swath. This paper focuses on the specifications, design and performance of the TDI detectors developed by e2v technologies under CNES contract for the panchromatic channel. Design drivers, derived from the mission and satellite requirements, architecture of the sensor and measurement results for key performances of the first prototypes are presented.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Aynak mineral district in Afghanistan: Chapter E in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Aynak mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kundalyan mineral district in Afghanistan: Chapter H in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kundalyan mineral district, which has porphyry copper and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Herat mineral district in Afghanistan: Chapter T in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Herat mineral district, which has barium and limestone deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Badakhshan mineral district in Afghanistan: Chapter F in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Badakhshan mineral district, which has gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products

Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This DS consists of the locally enhanced ALOS image mosaics for each of the 24 mineral project areas (referred to herein as areas of interest), whose locality names, locations, and main mineral occurrences are shown on the index map of Afghanistan (fig. 1). ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency, but the image processing has altered the original pixel structure and all image values of the JAXA

Inexpensive land-use maps extracted from satellite data

Science.gov (United States)

Barney, T. W.; Barr, D. J.; Elifrits, C. D.; Johannsen, C. J.

1979-01-01

Satellite images are interpretable with minimal skill and equipment by employing method which uses false color composite print of image of area transmitted from Landsat satellite. Method is effective for those who have little experience with satellite imagery, little time, and little money available.

Fast susceptibility-weighted imaging with three-dimensional short-axis propeller (SAP)-echo-planar imaging.

Science.gov (United States)

Holdsworth, Samantha J; Yeom, Kristen W; Moseley, Michael E; Skare, S

2015-05-01

Susceptibility-weighted imaging (SWI) in neuroimaging can be challenging due to long scan times of three-dimensional (3D) gradient recalled echo (GRE), while faster techniques such as 3D interleaved echo-planar imaging (iEPI) are prone to motion artifacts. Here we outline and implement a 3D short-axis propeller echo-planar imaging (SAP-EPI) trajectory as a faster, motion-correctable approach for SWI. Experiments were conducted on a 3T MRI system. The 3D SAP-EPI, 3D iEPI, and 3D GRE SWI scans were acquired on two volunteers. Controlled motion experiments were conducted to test the motion-correction capability of 3D SAP-EPI. The 3D SAP-EPI SWI data were acquired on two pediatric patients as a potential alternative to 2D GRE used clinically. The 3D GRE images had a better target resolution (0.47 × 0.94 × 2 mm, scan time = 5 min), iEPI and SAP-EPI images (resolution = 0.94 × 0.94 × 2 mm) were acquired in a faster scan time (1:52 min) with twice the brain coverage. SAP-EPI showed motion-correction capability and some immunity to undersampling from rejected data. While 3D SAP-EPI suffers from some geometric distortion, its short scan time and motion-correction capability suggest that SAP-EPI may be a useful alternative to GRE and iEPI for use in SWI, particularly in uncooperative patients. © 2014 Wiley Periodicals, Inc.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kunduz mineral district in Afghanistan: Chapter S in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kunduz mineral district, which has celestite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Dudkash mineral district in Afghanistan: Chapter R in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Dudkash mineral district, which has industrial mineral deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Tourmaline mineral district in Afghanistan: Chapter J in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Tourmaline mineral district, which has tin deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products

Effects of satellite image spatial aggregation and resolution on estimates of forest land area

Science.gov (United States)

M.D. Nelson; R.E. McRoberts; G.R. Holden; M.E. Bauer

2009-01-01

Satellite imagery is being used increasingly in association with national forest inventories (NFIs) to produce maps and enhance estimates of forest attributes. We simulated several image spatial resolutions within sparsely and heavily forested study areas to assess resolution effects on estimates of forest land area, independent of other sensor characteristics. We...

Inter-pregnancy interval and pregnancy outcomes among HIV ...

African Journals Online (AJOL)

Background: Both short and long inter-pregnancy intervals have been associated with higher risk of adverse pregnancy outcomes. More so, short interpregnancy interval among HIVpositive women implies higher birth rate and subsequently a higher number of neonates exposed to HIV and potentially at r i s k o f mo t h e r ...

Post launch calibration and testing of the Advanced Baseline Imager on the GOES-R satellite

Science.gov (United States)

Lebair, William; Rollins, C.; Kline, John; Todirita, M.; Kronenwetter, J.

2016-05-01

The Geostationary Operational Environmental Satellite R (GOES-R) series is the planned next generation of operational weather satellites for the United State's National Oceanic and Atmospheric Administration. The first launch of the GOES-R series is planned for October 2016. The GOES-R series satellites and instruments are being developed by the National Aeronautics and Space Administration (NASA). One of the key instruments on the GOES-R series is the Advance Baseline Imager (ABI). The ABI is a multi-channel, visible through infrared, passive imaging radiometer. The ABI will provide moderate spatial and spectral resolution at high temporal and radiometric resolution to accurately monitor rapidly changing weather. Initial on-orbit calibration and performance characterization is crucial to establishing baseline used to maintain performance throughout mission life. A series of tests has been planned to establish the post launch performance and establish the parameters needed to process the data in the Ground Processing Algorithm. The large number of detectors for each channel required to provide the needed temporal coverage presents unique challenges for accurately calibrating ABI and minimizing striping. This paper discusses the planned tests to be performed on ABI over the six-month Post Launch Test period and the expected performance as it relates to ground tests.

Heuristic Scheduling Algorithm Oriented Dynamic Tasks for Imaging Satellites

Directory of Open Access Journals (Sweden)

Maocai Wang

2014-01-01

Full Text Available Imaging satellite scheduling is an NP-hard problem with many complex constraints. This paper researches the scheduling problem for dynamic tasks oriented to some emergency cases. After the dynamic properties of satellite scheduling were analyzed, the optimization model is proposed in this paper. Based on the model, two heuristic algorithms are proposed to solve the problem. The first heuristic algorithm arranges new tasks by inserting or deleting them, then inserting them repeatedly according to the priority from low to high, which is named IDI algorithm. The second one called ISDR adopts four steps: insert directly, insert by shifting, insert by deleting, and reinsert the tasks deleted. Moreover, two heuristic factors, congestion degree of a time window and the overlapping degree of a task, are employed to improve the algorithm’s performance. Finally, a case is given to test the algorithms. The results show that the IDI algorithm is better than ISDR from the running time point of view while ISDR algorithm with heuristic factors is more effective with regard to algorithm performance. Moreover, the results also show that our method has good performance for the larger size of the dynamic tasks in comparison with the other two methods.

T1-weighted vs. short-TE-long-TR images. Usefulness for knee MR examinations of ligament and meniscal lesions

International Nuclear Information System (INIS)

Endo, Hideho; Wada, Mitsuyoshi; Shiotani, Seiji; Niitsu, Mamoru; Itai, Yuji

2000-01-01

The purpose of this study was to compare short-TE-long-TR images with T1-weighed images in knee MR examinations. Sagittal MR images of the knee were obtained in 31 patients with knee pain. T1-weighted images were obtained by the spin-echo technique (TR/TE =350/15), and short-TE-long-TR images by fast spin-echo (TR/TE =1300/15) with an echo-train length of 5. Contrast-to-noise-ratios (CNRs) of the anterior cruciate ligament and synovial space, meniscus and articular cartilage, and meniscal lesion and normal meniscus were compared between short-TE-long-TR images and T1-weighted images. On each of the three examinations, short-TE-long-TR images provided significantly higher CNRs than T1-weighted images. It was concluded that short-TE-long-TR images can be a useful alternative to T1-weighted images in evaluating the anterior cruciate ligament and meniscal lesions. (author)

T1-weighted vs. short-TE-long-TR images. Usefulness for knee MR examinations of ligament and meniscal lesions

Energy Technology Data Exchange (ETDEWEB)

Endo, Hideho; Wada, Mitsuyoshi; Shiotani, Seiji [Tsukuba Medical Center Hospital, Ibaraki (Japan); Niitsu, Mamoru; Itai, Yuji

2000-11-01

The purpose of this study was to compare short-TE-long-TR images with T1-weighed images in knee MR examinations. Sagittal MR images of the knee were obtained in 31 patients with knee pain. T1-weighted images were obtained by the spin-echo technique (TR/TE =350/15), and short-TE-long-TR images by fast spin-echo (TR/TE =1300/15) with an echo-train length of 5. Contrast-to-noise-ratios (CNRs) of the anterior cruciate ligament and synovial space, meniscus and articular cartilage, and meniscal lesion and normal meniscus were compared between short-TE-long-TR images and T1-weighted images. On each of the three examinations, short-TE-long-TR images provided significantly higher CNRs than T1-weighted images. It was concluded that short-TE-long-TR images can be a useful alternative to T1-weighted images in evaluating the anterior cruciate ligament and meniscal lesions. (author)

Integrating multisensor satellite data merging and image reconstruction in support of machine learning for better water quality management.

Science.gov (United States)

Chang, Ni-Bin; Bai, Kaixu; Chen, Chi-Farn

2017-10-01

Monitoring water quality changes in lakes, reservoirs, estuaries, and coastal waters is critical in response to the needs for sustainable development. This study develops a remote sensing-based multiscale modeling system by integrating multi-sensor satellite data merging and image reconstruction algorithms in support of feature extraction with machine learning leading to automate continuous water quality monitoring in environmentally sensitive regions. This new Earth observation platform, termed "cross-mission data merging and image reconstruction with machine learning" (CDMIM), is capable of merging multiple satellite imageries to provide daily water quality monitoring through a series of image processing, enhancement, reconstruction, and data mining/machine learning techniques. Two existing key algorithms, including Spectral Information Adaptation and Synthesis Scheme (SIASS) and SMart Information Reconstruction (SMIR), are highlighted to support feature extraction and content-based mapping. Whereas SIASS can support various data merging efforts to merge images collected from cross-mission satellite sensors, SMIR can overcome data gaps by reconstructing the information of value-missing pixels due to impacts such as cloud obstruction. Practical implementation of CDMIM was assessed by predicting the water quality over seasons in terms of the concentrations of nutrients and chlorophyll-a, as well as water clarity in Lake Nicaragua, providing synergistic efforts to better monitor the aquatic environment and offer insightful lake watershed management strategies. Copyright © 2017 Elsevier Ltd. All rights reserved.

Ship Detection in Optical Satellite Image Based on RX Method and PCAnet

Science.gov (United States)

Shao, Xiu; Li, Huali; Lin, Hui; Kang, Xudong; Lu, Ting

2017-12-01

In this paper, we present a novel method for ship detection in optical satellite image based on the ReedXiaoli (RX) method and the principal component analysis network (PCAnet). The proposed method consists of the following three steps. First, the spatially adjacent pixels in optical image are arranged into a vector, transforming the optical image into a 3D cube image. By taking this process, the contextual information of the spatially adjacent pixels can be integrated to magnify the discrimination between ship and background. Second, the RX anomaly detection method is adopted to preliminarily extract ship candidates from the produced 3D cube image. Finally, real ships are further confirmed among ship candidates by applying the PCAnet and the support vector machine (SVM). Specifically, the PCAnet is a simple deep learning network which is exploited to perform feature extraction, and the SVM is applied to achieve feature pooling and decision making. Experimental results demonstrate that our approach is effective in discriminating between ships and false alarms, and has a good ship detection performance.

Satellite Images and Aerial Photographs of the Effects of Hurricanes Katrina and Rita on Coastal Louisiana

Science.gov (United States)

Barras, John A.

2007-01-01

Introduction Hurricane Katrina made landfall on the eastern coastline of Louisiana on August 29, 2005; Hurricane Rita made landfall on the western coastline of Louisiana on September 24, 2005. Comparison of Landsat Thematic Mapper (TM) satellite imagery acquired before and after the landfalls of Katrina and Rita and classified to identify land and water demonstrated that water area increased by 217 mi2 (562 km2) in coastal Louisiana as a result of the storms. Approximately 82 mi2 (212 km2) of new water areas were in areas primarily impacted by Hurricane Katrina (Mississippi River Delta basin, Breton Sound basin, Pontchartrain basin, and Pearl River basin), whereas 99 mi2 (256 km2) were in areas primarily impacted by Hurricane Rita (Calcasieu/Sabine basin, Mermentau basin, Teche/Vermilion basin, Atchafalaya basin, and Terrebonne basin). Barataria basin contained new water areas caused by both hurricanes, resulting in some 18 mi2 (46.6 km2) of new water areas. The fresh marsh and intermediate marsh communities' land areas decreased by 122 mi2 (316 km2) and 90 mi2 (233.1 km2), respectively, and the brackish marsh and saline marsh communities' land areas decreased by 33 mi2 (85.5 km2) and 28 mi2 (72.5 km2), respectively. These new water areas represent land losses caused by direct removal of wetlands. They also indicate transitory changes in water area caused by remnant flooding, removal of aquatic vegetation, scouring of marsh vegetation, and water-level variation attributed to normal tidal and meteorological variation between satellite images. Permanent losses cannot be estimated until several growing seasons have passed and the transitory impacts of the hurricanes are minimized. The purpose of this study was to provide preliminary information on water area changes in coastal Louisiana acquired shortly after the landfalls of both hurricanes (detectable with Landsat TM imagery) and to serve as a regional baseline for monitoring posthurricane wetland recovery. The land

A new approach for agroecosystems monitoring using high-revisit multitemporal satellite data series

Science.gov (United States)

Diez, M.; Moclán, C.; Romo, A.; Pirondini, F.

2014-10-01

With increasing population pressure throughout the world and the need for increased agricultural production there is a definite need for improved management of the world's agricultural resources. Comprehensive, reliable and timely information on agricultural resources is necessary for the implementation of effective management decisions. In that sense, the demand for high-quality and high-frequency geo-information for monitoring of agriculture and its associated ecosystems has been growing in the recent decades. Satellite image data enable direct observation of large areas at frequent intervals and therefore allow unprecedented mapping and monitoring of crops evolution. Furthermore, real time analysis can assist in making timely management decisions that affect the outcome of the crops. The DEIMOS-1 satellite, owned and operated by ELECNOR DEIMOS IMAGING (Spain), provides 22m, 3-band imagery with a very wide (620-km) swath, and has been specifically designed to produce high-frequency revisit on very large areas. This capability has been proved through the contracts awarded to Airbus Defence and Space every year since 2011, where DEIMOS-1 has provided the USDA with the bulk of the imagery used to monitor the crop season in the Lower 48, in cooperation with its twin satellite DMCii's UK-DMC2. Furthermore, high density agricultural areas have been targeted with increased frequency and analyzed in near real time to monitor tightly the evolution. In this paper we present the results obtained from a campaign carried out in 2013 with DEIMOS-1 and UK-DMC2 satellites. These campaigns provided a high-frequency revisit of target areas, with one image every two days on average: almost a ten-fold frequency improvement with respect to Landsat-8. The results clearly show the effectiveness of a high-frequency monitoring approach with high resolution images with respect to classic strategies where results are more exposed to weather conditions.

Left ventricular aneurysm in short axis: a comparison of magnetic resonance, ultrasound and thallium-201 SPECT images

International Nuclear Information System (INIS)

Ahmad, M.; Johnson, R.F. Jr.; Fawcett, H.D.; Schreiber, M.H.

1987-01-01

Short axis magnetic resonance images of a left ventricular aneurysm were compared to similar views obtained by echocardiography and by thallium-201 single photon emission computed tomography. Images of the dyskinetic left ventricular apex and the contractile left ventricular base were analyzed and compared. Unlike the previously reported orthogonal plane magnetic resonance images, short axis imaging provided representative and quantitative information in views comparable to those obtained by standard noninvasive imaging techniques. These data indicate that short axis magnetic resonance imaging is capable of identifying and sizing the aneurysmal and the residual segments of the left ventricle. The findings may be of prognostic value in patients with left ventricular aneurysm

Bandwidth compression of the digitized HDTV images for transmission via satellites

Science.gov (United States)

Al-Asmari, A. KH.; Kwatra, S. C.

1992-01-01

This paper investigates a subband coding scheme to reduce the transmission bandwidth of the digitized HDTV images. The HDTV signals are decomposed into seven bands. Each band is then independently encoded. The based band is DPCM encoded and the high bands are encoded by using nonuniform Laplacian quantizers with a dead zone. By selecting the dead zone on the basis of energy in the high bands an acceptable image quality is achieved at an average of 45 Mbits/sec (Mbps) rate. This rate is comparable to some very hardware intensive schemes of transform compression or vector quantization proposed in the literature. The subband coding scheme used in this study is considered to be of medium complexity. The 45 Mbps rate is suitable for transmission of HDTV signals via satellites.

Relationship between heart rate and quiescent interval of the cardiac cycle in children using MRI

Energy Technology Data Exchange (ETDEWEB)

Zhang, Wei [Texas Children' s Hospital, E. B. Singleton Department of Pediatric Radiology, Houston, TX (United States); Bogale, Saivivek [Baylor University Medical Center, Department of Radiology, Dallas, TX (United States); Golriz, Farahnaz [Baylor College of Medicine, Department of Radiology, Houston, TX (United States); Krishnamurthy, Rajesh [Nationwide Children' s Hospital, Department of Diagnostic Radiology, Columbus, OH (United States)

2017-11-15

Imaging the heart in children comes with the challenge of constant cardiac motion. A prospective electrocardiography-triggered CT scan allows for scanning during a predetermined phase of the cardiac cycle with least motion. This technique requires knowing the optimal quiescent intervals of cardiac cycles in a pediatric population. To evaluate high-temporal-resolution cine MRI of the heart in children to determine the relationship of heart rate to the optimal quiescent interval within the cardiac cycle. We included a total of 225 consecutive patients ages 0-18 years who had high-temporal-resolution cine steady-state free-precession sequence performed as part of a magnetic resonance imaging (MRI) or magnetic resonance angiography study of the heart. We determined the location and duration of the quiescent interval in systole and diastole for heart rates ranging 40-178 beats per minute (bpm). We performed the Wilcoxon signed rank test to compare the duration of quiescent interval in systole and diastole for each heart rate group. The duration of the quiescent interval at heart rates <80 bpm and >90 bpm was significantly longer in diastole and systole, respectively (P<.0001 for all ranges, except for 90-99 bpm [P=.02]). For heart rates 80-89 bpm, diastolic interval was longer than systolic interval, but the difference was not statistically significant (P=.06). We created a chart depicting optimal quiescent intervals across a range of heart rates that could be applied for prospective electrocardiography-triggered CT imaging of the heart. The optimal quiescent interval at heart rates <80 bpm is in diastole and at heart rates ≥90 bpm is in systole. The period of quiescence at heart rates 80-89 bpm is uniformly short in systole and diastole. (orig.)

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Katawas mineral district in Afghanistan: Chapter N in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Katawas mineral district, which has gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©AXA, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA

Kinematic Orbit Determination Method Optimization and Test Analysis for BDS Satellites with Short-arc Tracking Data

Directory of Open Access Journals (Sweden)

GUO Rui

2017-04-01

Full Text Available Rapid orbit recovery is a puzzle for the BDS satellites after orbit maneuvers. Two kinematic orbit determination methods are studied, with two orbit determination models being established. The receiver system error and serious multipath error exist in the BDS system. The co-location method is proposed to estimate and calibrate the receiver system errors. A CNMC (code noise and multipath correction method is introduced to weaken the multipath error. Therefore the data quality is controlled efficiently for the receivers in the short tracking arc. The GEO/IGSO/MEO real data is emploied to carry out tests and validation. Using 10 min short tracking arc, the kinematic precise orbit determination accuracy is about 3.27 m for the GEOs, and 8.19 m for the IGSOs, and 5.9 m for the MEOs. Rapid orbit determination is achieved, which satisfying the orbit requirements from the BDS RDSS services. The kinematic precise orbit determination method also supports the RDSS service walking up to the global world.

The Short Wave Aerostat-Mounted Imager (SWAMI): A novel platform for acquiring remotely sensed data from a tethered balloon

Science.gov (United States)

Vierling, L.A.; Fersdahl, M.; Chen, X.; Li, Z.; Zimmerman, P.

2006-01-01

We describe a new remote sensing system called the Short Wave Aerostat-Mounted Imager (SWAMI). The SWAMI is designed to acquire co-located video imagery and hyperspectral data to study basic remote sensing questions and to link landscape level trace gas fluxes with spatially and temporally appropriate spectral observations. The SWAMI can fly at altitudes up to 2 km above ground level to bridge the spatial gap between radiometric measurements collected near the surface and those acquired by other aircraft or satellites. The SWAMI platform consists of a dual channel hyperspectral spectroradiometer, video camera, GPS, thermal infrared sensor, and several meteorological and control sensors. All SWAMI functions (e.g. data acquisition and sensor pointing) can be controlled from the ground via wireless transmission. Sample data from the sampling platform are presented, along with several potential scientific applications of SWAMI data.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Bakhud mineral district in Afghanistan: Chapter U in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.; Davis, Philip A.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Bakhud mineral district, which has industrial fluorite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Uruzgan mineral district in Afghanistan: Chapter V in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Uruzgan mineral district, which has tin and tungsten deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Baghlan mineral district in Afghanistan: Chapter P in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Baghlan mineral district, which has industrial clay and gypsum deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2006, 2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from

Reconstruction of Missing Pixels in Satellite Images Using the Data Interpolating Empirical Orthogonal Function (DINEOF)

Science.gov (United States)

Liu, X.; Wang, M.

2016-02-01

For coastal and inland waters, complete (in spatial) and frequent satellite measurements are important in order to monitor and understand coastal biological and ecological processes and phenomena, such as diurnal variations. High-frequency images of the water diffuse attenuation coefficient at the wavelength of 490 nm (Kd(490)) derived from the Korean Geostationary Ocean Color Imager (GOCI) provide a unique opportunity to study diurnal variation of the water turbidity in coastal regions of the Bohai Sea, Yellow Sea, and East China Sea. However, there are lots of missing pixels in the original GOCI-derived Kd(490) images due to clouds and various other reasons. Data Interpolating Empirical Orthogonal Function (DINEOF) is a method to reconstruct missing data in geophysical datasets based on Empirical Orthogonal Function (EOF). In this study, the DINEOF is applied to GOCI-derived Kd(490) data in the Yangtze River mouth and the Yellow River mouth regions, the DINEOF reconstructed Kd(490) data are used to fill in the missing pixels, and the spatial patterns and temporal functions of the first three EOF modes are also used to investigate the sub-diurnal variation due to the tidal forcing. In addition, DINEOF method is also applied to the Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi National Polar-orbiting Partnership (SNPP) satellite to reconstruct missing pixels in the daily Kd(490) and chlorophyll-a concentration images, and some application examples in the Chesapeake Bay and the Gulf of Mexico will be presented.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Takhar mineral district in Afghanistan: Chapter Q in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Takhar mineral district, which has industrial evaporite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

Image Mosaicking Approach for a Double-Camera System in the GaoFen2 Optical Remote Sensing Satellite Based on the Big Virtual Camera.

Science.gov (United States)

Cheng, Yufeng; Jin, Shuying; Wang, Mi; Zhu, Ying; Dong, Zhipeng

2017-06-20

The linear array push broom imaging mode is widely used for high resolution optical satellites (HROS). Using double-cameras attached by a high-rigidity support along with push broom imaging is one method to enlarge the field of view while ensuring high resolution. High accuracy image mosaicking is the key factor of the geometrical quality of complete stitched satellite imagery. This paper proposes a high accuracy image mosaicking approach based on the big virtual camera (BVC) in the double-camera system on the GaoFen2 optical remote sensing satellite (GF2). A big virtual camera can be built according to the rigorous imaging model of a single camera; then, each single image strip obtained by each TDI-CCD detector can be re-projected to the virtual detector of the big virtual camera coordinate system using forward-projection and backward-projection to obtain the corresponding single virtual image. After an on-orbit calibration and relative orientation, the complete final virtual image can be obtained by stitching the single virtual images together based on their coordinate information on the big virtual detector image plane. The paper subtly uses the concept of the big virtual camera to obtain a stitched image and the corresponding high accuracy rational function model (RFM) for concurrent post processing. Experiments verified that the proposed method can achieve seamless mosaicking while maintaining the geometric accuracy.

Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output

DEFF Research Database (Denmark)

Bøvith, Thomas; Nielsen, Allan Aasbjerg; Hansen, Lars Kai

2006-01-01

A method for detecting clutter in weather radar images by information fusion is presented. Radar data, satellite images, and output from a numerical weather prediction model are combined and the radar echoes are classified using supervised classification. The presented method uses indirect...... information on precipitation in the atmosphere from Meteosat-8 multispectral images and near-surface temperature estimates from the DMI-HIRLAM-S05 numerical weather prediction model. Alternatively, an operational nowcasting product called 'Precipitating Clouds' based on Meteosat-8 input is used. A scale...

Drag on a Satellite Moving across a Spherical Galaxy: Tidal and Frictional Forces in Short-lived Encounters

Science.gov (United States)

Colpi, Monica; Pallavicini, Andrea

1998-07-01

The drag force on a satellite of mass M moving with speed V in the gravitational field of a spherically symmetric background of stars is computed. During the encounter, the stars are subject to a time-dependent force that alters their equilibrium. The resulting distortion in the stellar density field acts back to produce a force FΔ that decelerates the satellite. This force is computed using a perturbative technique known as linear response theory. In this paper, we extend the formalism of linear response to derive the correct expression for the back-reaction force FΔ that applies when the stellar system is described by an equilibrium one-particle distribution function. FΔ is expressed in terms of a suitable correlation function that couples the satellite dynamics to the unperturbed dynamics of the stars. At time t, the force depends upon the whole history of the composite system. In the formalism, we account for the shift of the stellar center of mass resulting from linear momentum conservation. The self-gravity of the response is neglected since it contributes to a higher order in the perturbation. Linear response theory applies also to the case of a satellite orbiting outside the spherical galaxy. The case of a satellite moving on a straight line, at high speed relative to the stellar dispersion velocity, is explored. We find that the satellite during its passage raises (1) global tides in the stellar distribution and (2) a wake, i.e., an overdense region behind its trail. If the satellite motion is external to the galaxy, it suffers a dissipative force that is not exclusively acting along V but acquires a component along R, the position vector relative to the center of the spherical galaxy. We derive the analytical expression of the force in the impulse approximation. In penetrating short-lived encounters, the satellite moves across the stellar distribution and the transient wake excited in the density field is responsible for most of the deceleration. We

Sentinel-2: next generation satellites for optical land observation from space

Science.gov (United States)

Lautenschläger, G.; Gessner, R.; Gockel, W.; Haas, C.; Schweickert, G.; Bursch, S.; Welsch, M.; Sontag, H.

2013-10-01

The first Sentinel-2 satellites, which constitute the next generation of operational Earth observation satellites for optical land monitoring from space, are undergoing completion in the facilities at Astrium ready for launch end 2014. Sentinel-2 will feature a major breakthrough in the area of optical land observation since it will for the first time enable continuous and systematic acquisition of all land surfaces world-wide with the Multi-Spectral Instrument (MSI), thus providing the basis for a truly operational service. Flying in the same orbital plane and spaced at 180°, the constellation of two satellites, designed for an in-orbit nominal operational lifetime of 7 years each, will acquire all land surfaces in only 5 days at the equator. In order to support emergency operations, the satellites can further be operated in an extended observation mode allowing to image any point on Earth even on a daily basis. MSI acquires images in 13 spectral channels from Visible-to-Near Infrared (VNIR) to Short Wave Infrared (SWIR) with a swath of almost 300 km on ground and a spatial resolution up to 10 m. The data ensure continuity to the existing data sets produced by the series of Landsat and SPOT satellites, and will further provide detailed spectral information to enable derivation of biophysical or geophysical products. Excellent geometric image quality performances are achieved with geolocation better than 16 m, thanks to an innovative instrument design in conjunction with a high-performance satellite AOCS subsystem centered around a 2-band GPS receiver, high-performance star trackers and a fiberoptic gyro. To cope with the high data volume on-board, data are compressed using a state-of-the-art wavelet compression scheme. Thanks to a powerful mission data handling system built around a newly developed very large solid-state mass memory based on flash technology, on-board compression losses will be kept to a minimum. The Sentinel-2 satellite design features a highly

Weather Satellite Pictures and How to Obtain Them.

Science.gov (United States)

Petit, Noel J.; Johnson, Philip

1982-01-01

An introduction to satellite meteorology is presented to promote use of live weather satellite photographs in the classroom. Topics addressed include weather satellites, how they work, earth emissions, satellite photography, satellite image analysis, obtaining satellite pictures, and future considerations. Includes sources for materials to…

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Haji-Gak mineral district in Afghanistan: Chapter C in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Haji-Gak mineral district, which has iron ore deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2006,2007), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kharnak-Kanjar mineral district in Afghanistan: Chapter K in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kharnak-Kanjar mineral district, which has mercury deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Dusar-Shaida mineral district in Afghanistan: Chapter I in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Dusar-Shaida mineral district, which has copper and tin deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the

High resolution satellite image indexing and retrieval using SURF features and bag of visual words

Science.gov (United States)

Bouteldja, Samia; Kourgli, Assia

2017-03-01

In this paper, we evaluate the performance of SURF descriptor for high resolution satellite imagery (HRSI) retrieval through a BoVW model on a land-use/land-cover (LULC) dataset. Local feature approaches such as SIFT and SURF descriptors can deal with a large variation of scale, rotation and illumination of the images, providing, therefore, a better discriminative power and retrieval efficiency than global features, especially for HRSI which contain a great range of objects and spatial patterns. Moreover, we combine SURF and color features to improve the retrieval accuracy, and we propose to learn a category-specific dictionary for each image category which results in a more discriminative image representation and boosts the image retrieval performance.

Short-interval test-retest interrater reliability of the Dutch version of the structured clinical interview for DSM-IV personality disorders (SCID-II)

NARCIS (Netherlands)

Weertman, A; ArntZ, A; Dreessen, L; van Velzen, C; Vertommen, S

2003-01-01

This study examined the short-interval test-retest reliability of the Structured Clinical Interview (SCID-II: First, Spitzer, Gibbon, & Williams, 1995) for DSM-IV personality disorders (PDs). The SCID-II was administered to 69 in- and outpatients on two occasions separated by 1 to 6 weeks. The

Particle Image Velocimetry

DEFF Research Database (Denmark)

Zhang, Chen; Vasilevskis, Sandijs; Kozlowski, Bartosz

Particle image velocimetry (PIV) is a non-intrusive, whole filed optical method providing instantaneous velocity information in fluids. The flow is seeded with tracer particles. The particles are illuminated in the target area with a light sheet at least twice within a short time interval....... The camera images the target area and captures each light pulse in separate image frames. The displacement of the particle between the light pulses can be used to determine the velocity vectors. This guideline introduces the principle of the PIV system and the system configuration. The measurement procedure...

Mapping soil heterogeneity using RapidEye satellite images

Science.gov (United States)

Piccard, Isabelle; Eerens, Herman; Dong, Qinghan; Gobin, Anne; Goffart, Jean-Pierre; Curnel, Yannick; Planchon, Viviane

2016-04-01

In the frame of BELCAM, a project funded by the Belgian Science Policy Office (BELSPO), researchers from UCL, ULg, CRA-W and VITO aim to set up a collaborative system to develop and deliver relevant information for agricultural monitoring in Belgium. The main objective is to develop remote sensing methods and processing chains able to ingest crowd sourcing data, provided by farmers or associated partners, and to deliver in return relevant and up-to-date information for crop monitoring at the field and district level based on Sentinel-1 and -2 satellite imagery. One of the developments within BELCAM concerns an automatic procedure to detect soil heterogeneity within a parcel using optical high resolution images. Such heterogeneity maps can be used to adjust farming practices according to the detected heterogeneity. This heterogeneity may for instance be caused by differences in mineral composition of the soil, organic matter content, soil moisture or soil texture. Local differences in plant growth may be indicative for differences in soil characteristics. As such remote sensing derived vegetation indices may be used to reveal soil heterogeneity. VITO started to delineate homogeneous zones within parcels by analyzing a series of RapidEye images acquired in 2015 (as a precursor for Sentinel-2). Both unsupervised classification (ISODATA, K-means) and segmentation techniques were tested. Heterogeneity maps were generated from images acquired at different moments during the season (13 May, 30 June, 17 July, 31 August, 11 September and 1 November 2015). Tests were performed using blue, green, red, red edge and NIR reflectances separately and using derived indices such as NDVI, fAPAR, CIrededge, NDRE2. The results for selected winter wheat, maize and potato fields were evaluated together with experts from the collaborating agricultural research centers. For a few fields UAV images and/or yield measurements were available for comparison.

Interval timing in genetically modified mice: a simple paradigm

OpenAIRE

Balci, F.; Papachristos, E. B.; Gallistel, C. R.; Brunner, D.; Gibson, J.; Shumyatsky, G. P.

2007-01-01

We describe a behavioral screen for the quantitative study of interval timing and interval memory in mice. Mice learn to switch from a short-latency feeding station to a long-latency station when the short latency has passed without a feeding. The psychometric function is the cumulative distribution of switch latencies. Its median measures timing accuracy and its interquartile interval measures timing precision. Next, using this behavioral paradigm, we have examined mice with a gene knockout ...

Analysis and Assessment of Land Use Change in Alexandria, Egypt Using Satellite Images, GIS, and Modelling Techniques

International Nuclear Information System (INIS)

Abdou Azaz, L.K.

2008-01-01

Alexandria is the second largest urban governorate in Egypt and has seen significant urban growth in its modern and contemporary history. This study investigates the urban growth phenomenon in Alexandria, Egypt, using the integration of remote sensing and GIS. The urban physical expansion and change were detected using Landsat satellite images. The satellite images of years 1984 and 1993 were first geo referenced, achieving a very small RMSE that provided high accuracy data for satellite image analysis. Then, the images were classified using a tailored classification scheme with accuracy of 93.82% and 95.27% for 1984 and 1993 images respectively. This high accuracy enabled detecting land use/land cover changes with high confidence using a post-classification comparison method. One of the most important findings here is the loss of cultivated land in favour of urban expansion. If the current loss rates continued, 75% of green lands would be lost by year 2191. These hazardous rates call for an urban growth management policy that can preserve such valuable resources to achieve sustainable urban development. Modelling techniques can help in defining the scenarios of urban growth. In this study, the SLEUTH urban growth model was applied to predict future urban expansion in Alexandria until the year 2055. The application of this model in Alexandria of Egypt with its different environmental characteristics is the first application outside USA and Europe. The results revealed that future urban growth would continue along the edges of the current urban extent. This means that the cultivated lands in the east and the southeast of the city will be decreased. To deal with such crisis, there is a serious need for a comprehensive urban growth management programme that can be based on the best practices in similar situations

Dsm Based Orientation of Large Stereo Satellite Image Blocks

Science.gov (United States)

d'Angelo, P.; Reinartz, P.

2012-07-01

High resolution stereo satellite imagery is well suited for the creation of digital surface models (DSM). A system for highly automated and operational DSM and orthoimage generation based on CARTOSAT-1 imagery is presented, with emphasis on fully automated georeferencing. The proposed system processes level-1 stereo scenes using the rational polynomial coefficients (RPC) universal sensor model. The RPC are derived from orbit and attitude information and have a much lower accuracy than the ground resolution of approximately 2.5 m. In order to use the images for orthorectification or DSM generation, an affine RPC correction is required. In this paper, GCP are automatically derived from lower resolution reference datasets (Landsat ETM+ Geocover and SRTM DSM). The traditional method of collecting the lateral position from a reference image and interpolating the corresponding height from the DEM ignores the higher lateral accuracy of the SRTM dataset. Our method avoids this drawback by using a RPC correction based on DSM alignment, resulting in improved geolocation of both DSM and ortho images. Scene based method and a bundle block adjustment based correction are developed and evaluated for a test site covering the nothern part of Italy, for which 405 Cartosat-1 Stereopairs are available. Both methods are tested against independent ground truth. Checks against this ground truth indicate a lateral error of 10 meters.

Development and validation of a short-lag spatial coherence theory for photoacoustic imaging

Science.gov (United States)

Graham, Michelle T.; Lediju Bell, Muyinatu A.

2018-02-01

We previously derived spatial coherence theory to be implemented for studying theoretical properties of ShortLag Spatial Coherence (SLSC) beamforming applied to photoacoustic images. In this paper, our newly derived theoretical equation is evaluated to generate SLSC images of a point target and a 1.2 mm diameter target and corresponding lateral profiles. We compared SLSC images simulated solely based on our theory to SLSC images created after beamforming acoustic channel data from k-Wave simulations of 1.2 mm-diameter disc target. This process was repeated for a point target and the full width at half the maximum signal amplitudes were measured to estimate the resolution of each imaging system. Resolution as a function of lag was comparable for the first 10% of the receive aperture (i.e., the short-lag region), after which resolution measurements diverged by a maximum of 1 mm between the two types of simulated images. These results indicate the potential for both simulation methods to be utilized as independent resources to study coherence-based photoacoustic beamformers when imaging point-like targets.

Automatic Centerline Extraction of Coverd Roads by Surrounding Objects from High Resolution Satellite Images

Science.gov (United States)

Kamangir, H.; Momeni, M.; Satari, M.

2017-09-01

This paper presents an automatic method to extract road centerline networks from high and very high resolution satellite images. The present paper addresses the automated extraction roads covered with multiple natural and artificial objects such as trees, vehicles and either shadows of buildings or trees. In order to have a precise road extraction, this method implements three stages including: classification of images based on maximum likelihood algorithm to categorize images into interested classes, modification process on classified images by connected component and morphological operators to extract pixels of desired objects by removing undesirable pixels of each class, and finally line extraction based on RANSAC algorithm. In order to evaluate performance of the proposed method, the generated results are compared with ground truth road map as a reference. The evaluation performance of the proposed method using representative test images show completeness values ranging between 77% and 93%.

Congenital Short QT Syndrome

Directory of Open Access Journals (Sweden)

Charles Antzelevitch

2004-04-01

Full Text Available Long QT intervals in the ECG have long been associated with sudden cardiac death. The congenital long QT syndrome was first described in individuals with structurally normal hearts in 1957.1 Little was known about the significance of a short QT interval. In 1993, after analyzing 6693 consecutive Holter recordings Algra et al concluded that an increased risk of sudden death was present not only in patients with long QT interval, but also in patients with short QT interval (<400 ms.2 Because this was a retrospective analysis, further evaluation of the data was not possible. It was not until 2000 that a short-QT syndrome (SQTS was proposed as a new inherited clinical syndrome by Gussak et al.3 The initial report was of two siblings and their mother all of whom displayed persistently short QT interval. The youngest was a 17 year old female presenting with several episodes of paroxysmal atrial fibrillation requiring electrical cardioversion.3 Her QT interval measured 280 msec at a heart rate of 69. Her 21 year old brother displayed a QT interval of 272 msec at a heart rate of 58, whereas the 51 year old mother showed a QT of 260 msec at a heart rate of 74. The authors also noted similar ECG findings in another unrelated 37 year old patient associated with sudden cardiac death.

Use of high resolution satellite images for tracking of changes in the lineament structure, caused by earthquakes

OpenAIRE

Arellano-Baeza, A. A.; Garcia, R. V.; Trejo-Soto, M.

2007-01-01

Over the last decades strong efforts have been made to apply new spaceborn technologies to the study and possible forecast of strong earthquakes. In this study we use ASTER/TERRA multispectral satellite images for detection and analysis of changes in the system of lineaments previous to a strong earthquake. A lineament is a straight or a somewhat curved feature in an image, which it is possible to detect by a special processing of images based on directional filtering and or Hough transform. ...

Technical and cost advantages of silicon carbide telescopes for small-satellite imaging applications

Science.gov (United States)

Kasunic, Keith J.; Aikens, Dave; Szwabowski, Dean; Ragan, Chip; Tinker, Flemming

2017-09-01

Small satellites ("SmallSats") are a growing segment of the Earth imaging and remote sensing market. Designed to be relatively low cost and with performance tailored to specific end-use applications, they are driving changes in optical telescope assembly (OTA) requirements. OTAs implemented in silicon carbide (SiC) provide performance advantages for space applications but have been predominately limited to large programs. A new generation of lightweight and thermally-stable designs is becoming commercially available, expanding the application of SiC to small satellites. This paper reviews the cost and technical advantages of an OTA designed using SiC for small satellite platforms. Taking into account faceplate fabrication quilting and surface distortion after gravity release, an optimized open-back SiC design with a lightweighting of 70% for a 125-mm SmallSat-class primary mirror has an estimated mass area density of 2.8 kg/m2 and an aspect ratio of 40:1. In addition, the thermally-induced surface error of such optimized designs is estimated at λ/150 RMS per watt of absorbed power. Cost advantages of SiC include reductions in launch mass, thermal-management infrastructure, and manufacturing time based on allowable assembly tolerances.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kandahar mineral district in Afghanistan: Chapter Z in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kandahar mineral district, which has bauxite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2006,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Farah mineral district in Afghanistan: Chapter FF in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.

2014-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Farah mineral district, which has spectral reflectance anomalies indicative of copper, zinc, lead, silver, and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2007, 2008, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Zarkashan mineral district in Afghanistan: Chapter G in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Zarkashan mineral district, which has copper and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Khanneshin mineral district in Afghanistan: Chapter A in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Khanneshin mineral district, which has uranium, thorium, rare-earth-element, and apatite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Nalbandon mineral district in Afghanistan: Chapter L in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Nalbandon mineral district, which has lead and zinc deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2007, 2008, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Balkhab mineral district in Afghanistan: Chapter B in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Balkhab mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match

Orbit Determination Using SLR Data for STSAT-2C:Short-arc Analysis

Directory of Open Access Journals (Sweden)

Young-Rok Kim

2015-09-01

Full Text Available In this study, we present the results of orbit determination (OD using satellite laser ranging (SLR data for the Science and Technology Satellite (STSAT-2C by a short-arc analysis. For SLR data processing, the NASA/GSFC GEODYN II software with one year (2013/04 – 2014/04 of normal point observations is used. As there is only an extremely small quantity of SLR observations of STSAT-2C and they are sparsely distribution, the selection of the arc length and the estimation intervals for the atmospheric drag coefficients and the empirical acceleration parameters was made on an arc-to-arc basis. For orbit quality assessment, the post-fit residuals of each short-arc and orbit overlaps of arcs are investigated. The OD results show that the weighted root mean square post-fit residuals of short-arcs are less than 1 cm, and the average 1-day orbit overlaps are superior to 50/600/900 m for the radial/cross-track/along-track components. These results demonstrate that OD for STSAT-2C was successfully achieved with cm-level range precision. However its orbit quality did not reach the same level due to the availability of few and sparse measurement conditions. From a mission analysis viewpoint, obtaining the results of OD for STSAT-2C is significant for generating enhanced orbit predictions for more frequent tracking.

Mapping plasma structures in the high-latitude ionosphere using beacon satellite, incoherent scatter radar and ground-based magnetometer observations

Directory of Open Access Journals (Sweden)

T. Neubert

2002-06-01

Full Text Available In the autumn of the year 2000, four radio receivers capable of tracking various beacon satellites were set up along the southwestern coast of Greenland. They are used to reconstruct images of the ionospheric plasma density distribution via the tomographic method. In order to test and validate tomographic imaging under the highly variable conditions often prevailing in the high-latitude ionosphere, a time interval was selected when the Sondrestrom incoherent scatter radar conducted measurements of the ionospheric plasma density while the radio receivers tracked a number of beacon satellites. A comparison between two-dimensional images of the plasma density distribution obtained from the radar and the satellite receivers revealed generally good agreement between radar measurements and tomographic images. Observed discrepancies can be attributed to F region plasma patches moving through the field of view with a speed of several hundred meters per second, thereby smearing out the tomographic image. A notable mismatch occurred around local magnetic midnight when a magnetospheric substorm breakup occurred in the vicinity of southwest Greenland (identified from ground-based magnetometer observations. The breakup was associated with a sudden intensification of the westward auroral electrojet which was centered at about 69 and extended up to some 73 corrected geomagnetic latitude. Ground-based magnetometer data may thus have the potential of indicating when the tomographic method is at risk and may fail. We finally outline the application of tomographic imaging, when combined with magnetic field data, to estimate ionospheric Joule heating rates.

Mapping Impervious Surface Expansion using Medium-resolution Satellite Image Time Series: A Case Study in the Yangtze River Delta, China

Science.gov (United States)

Gao, Feng; DeColstoun, Eric Brown; Ma, Ronghua; Weng, Qihao; Masek, Jeffrey G.; Chen, Jin; Pan, Yaozhong; Song, Conghe

2012-01-01

Cities have been expanding rapidly worldwide, especially over the past few decades. Mapping the dynamic expansion of impervious surface in both space and time is essential for an improved understanding of the urbanization process, land-cover and land-use change, and their impacts on the environment. Landsat and other medium-resolution satellites provide the necessary spatial details and temporal frequency for mapping impervious surface expansion over the past four decades. Since the US Geological Survey opened the historical record of the Landsat image archive for free access in 2008, the decades-old bottleneck of data limitation has gone. Remote-sensing scientists are now rich with data, and the challenge is how to make best use of this precious resource. In this article, we develop an efficient algorithm to map the continuous expansion of impervious surface using a time series of four decades of medium-resolution satellite images. The algorithm is based on a supervised classification of the time-series image stack using a decision tree. Each imerpervious class represents urbanization starting in a different image. The algorithm also allows us to remove inconsistent training samples because impervious expansion is not reversible during the study period. The objective is to extract a time series of complete and consistent impervious surface maps from a corresponding times series of images collected from multiple sensors, and with a minimal amount of image preprocessing effort. The approach was tested in the lower Yangtze River Delta region, one of the fastest urban growth areas in China. Results from nearly four decades of medium-resolution satellite data from the Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper plus (ETM+) and China-Brazil Earth Resources Satellite (CBERS) show a consistent urbanization process that is consistent with economic development plans and policies. The time-series impervious spatial extent maps derived

Primena satelitskih snimaka za dopunu sadržaja topografskih karata / An application of satellite images for improving the content of topographic maps

Directory of Open Access Journals (Sweden)

Miodrag D. Regodić

2010-10-01

Full Text Available Neažurnost sadržaja topografskih karata (TK, uslovljena ponajviše stvarnim ekonomskim teškoćama pri izradi novih i dopuni postojećih izdanja, kao i nedovoljnost i sve teže stanje pri izradi ostalih geotopografskih materijala (GTM, u velikoj meri otežavaju geotopografsko obezbeđenje (GTOb vojske u miru, kao i u svim periodima pripreme i vođenja ratnih dejstava. Rešenje ovog problema je u iznalaženju adekvatnog načina upotrebe proizvoda svih vrsta daljinskih snimanja, a naročito u obradi kvalitetnih satelitskih snimaka. Kao najbolji pokazatelj velikih mogućnosti daljinske detekcije, korišćenjem satelitskih snimaka, u kartografskoj praksi primenom kvalitetnih softverskih rešenja, u radu je predstavljena dopuna topografske karte nedostajućim topografskim sadržajem. / Lack of updated content of topographic maps (TMs, mainly due to economic issues regarding the publishing of existing or revised TMs, substantially affects geo-topographic supply (GTS of the Army both in peace and warfare time, as well as shortage of other geo-topographic materials (GTMs. The solution to this problem is in finding an appropriate method of using products of all types of remote sensing, high quality satellite images in particular. Having shown the best possibilities of remote sensing while using satellite images in mapping through the quality software solutions, the author presents an addition to topographic maps based on missing topographic data. Introduction Numerous natural and social phenomena are constantly observed, surveyed, registered and analyzed. Permanent or periodical satellite surveillance and recording for different purposes are growing in importance. The purposes can range from meteorological issues, through study of large water surfaces to military intelligence, etc. These recording can be used in making topographic, thematic and working maps as well as other geo-topographic material. Processing and analyzing of ikonos2 satellite images

TESIS experiment on XUV imaging spectroscopy of the Sun onboard the CORONAS-PHOTON satellite

Science.gov (United States)

Kuzin, S. V.; Zhitnik, I. A.; Bogachev, S. A.; Shestov, S. V.; Bugaenko, O. I.; Suhodrev, N. K.; Pertsov, A. A.; Mitrofanov, A. V.; Ignat'ev, A. P.; Slemzin, V. A.

We present a brief description of new complex of space telescopes and spectrographs, TESIS, which will be placed aboard the CORONAS-PHOTON satellite. The complex is intended for high-resolution imaging observation of full Sun in the coronal spectral lines and in the spectral lines of the solar transition region. TESIS will be launched at the end of 2007 - early of 2008. About 25 % of the daily TESIS images will be free for use and for downloading from the TESIS data center that is planned to open 2 months before the TESIS launching at http://www.tesis.lebedev.ru

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the South Helmand mineral district in Afghanistan: Chapter O in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the South Helmand mineral district, which has travertine deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2008, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the North Takhar mineral district in Afghanistan: Chapter D in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the North Takhar mineral district, which has placer gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

Detection and Extraction of Roads from High Resolution Satellites Images with Dynamic Programming

Science.gov (United States)

Benzouai, Siham; Smara, Youcef

2010-12-01

The advent of satellite images allows now a regular and a fast digitizing and update of geographic data, especially roads which are very useful for Geographic Information Systems (GIS) applications such as transportation, urban pollution, geomarketing, etc. For this, several studies have been conducted to automate roads extraction in order to minimize the manual processes [4]. In this work, we are interested in roads extraction from satellite imagery with high spatial resolution (at best equal to 10 m). The method is semi automatic and follows a linear approach where road is considered as a linear object. As roads extraction is a pattern recognition problem, it is useful, above all, to characterize roads. After, we realize a pre-processing by applying an Infinite Size Edge Filter -ISEF- and processing method based on dynamic programming concept, in particular, Fishler algorithm designed by F*.

Global Solar radiation in Spain from Satellite Images; Radiacion Solar Global en la Espana Peninsular a partir de images de satelite

Energy Technology Data Exchange (ETDEWEB)

Ramirez Santigosa, L.; Mora Lopez, L.; Sidrach de Cardona Ortin, M.; Navarro Fernandez, A. A.; Varela conde, M.; Cruz Echeandia, M. de la

2003-07-01

In the context of the present work a series of algorithms of calculation of the solar radiation from satellite images has been developed. These models, have been applied to three years of images of the Meteosat satellite and the results of the treatment have been extrapolated to long term. For the development of the models of solar radiation registered in ground stations have been used, corresponding all of them to localities of peninsular Spain and the Balearic ones. The maximum periods of data available have been used, supposing in most of the cases periods of between 6 and 9 years. From the results has a year type of images of global solar radiation on horizontal surface. The original resolution of the image of 7x7 km in the study latitudes, has been revaluate to 5x5 km. This supposes to have a value of the typical radiation for every day of the year, each 5x5 km in the study territory. This information, supposes an important advance as far as the knowledge of the space distribution of the radiation solar,impossible to reach about alternative methods. Doubtlessly, the precision of the provided values is not comparable with pyranometric measures in a concrete localise, but it provides a very valid indicator in places in which, it not had previous information. In addition to the radiation maps, tables of the global solar radiation have been prepared on different inclinations, from the global radiation on horizontal surface calculated for every day of the year and in each pixel of the image. (Author) 24 refs.

Short-circuit current density imaging of crystalline silicon solar cells via lock-in thermography: Robustness and simplifications

International Nuclear Information System (INIS)

Fertig, Fabian; Greulich, Johannes; Rein, Stefan

2014-01-01

Spatially resolved determination of solar cell parameters is beneficial for loss analysis and optimization of conversion efficiency. One key parameter that has been challenging to access by an imaging technique on solar cell level is short-circuit current density. This work discusses the robustness of a recently suggested approach to determine short-circuit current density spatially resolved based on a series of lock-in thermography images and options for a simplified image acquisition procedure. For an accurate result, one or two emissivity-corrected illuminated lock-in thermography images and one dark lock-in thermography image have to be recorded. The dark lock-in thermography image can be omitted if local shunts are negligible. Furthermore, it is shown that omitting the correction of lock-in thermography images for local emissivity variations only leads to minor distortions for standard silicon solar cells. Hence, adequate acquisition of one image only is sufficient to generate a meaningful map of short-circuit current density. Beyond that, this work illustrates the underlying physics of the recently proposed method and demonstrates its robustness concerning varying excitation conditions and locally increased series resistance. Experimentally gained short-circuit current density images are validated for monochromatic illumination in comparison to the reference method of light-beam induced current

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni1 mineral district in Afghanistan: Chapter DD in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.

2014-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghazni1 mineral district, which has spectral reflectance anomalies indicative of clay, aluminum, gold, silver, mercury, and sulfur deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni2 mineral district in Afghanistan: Chapter EE in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.

2014-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghazni2 mineral district, which has spectral reflectance anomalies indicative of gold, mercury, and sulfur deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image

Built-Up Area Detection from High-Resolution Satellite Images Using Multi-Scale Wavelet Transform and Local Spatial Statistics

Science.gov (United States)

Chen, Y.; Zhang, Y.; Gao, J.; Yuan, Y.; Lv, Z.

2018-04-01

Recently, built-up area detection from high-resolution satellite images (HRSI) has attracted increasing attention because HRSI can provide more detailed object information. In this paper, multi-resolution wavelet transform and local spatial autocorrelation statistic are introduced to model the spatial patterns of built-up areas. First, the input image is decomposed into high- and low-frequency subbands by wavelet transform at three levels. Then the high-frequency detail information in three directions (horizontal, vertical and diagonal) are extracted followed by a maximization operation to integrate the information in all directions. Afterward, a cross-scale operation is implemented to fuse different levels of information. Finally, local spatial autocorrelation statistic is introduced to enhance the saliency of built-up features and an adaptive threshold algorithm is used to achieve the detection of built-up areas. Experiments are conducted on ZY-3 and Quickbird panchromatic satellite images, and the results show that the proposed method is very effective for built-up area detection.

Simulation of seagrass bed mapping by satellite images based on the radiative transfer model

Science.gov (United States)

Sagawa, Tatsuyuki; Komatsu, Teruhisa

2015-06-01

Seagrass and seaweed beds play important roles in coastal marine ecosystems. They are food sources and habitats for many marine organisms, and influence the physical, chemical, and biological environment. They are sensitive to human impacts such as reclamation and pollution. Therefore, their management and preservation are necessary for a healthy coastal environment. Satellite remote sensing is a useful tool for mapping and monitoring seagrass beds. The efficiency of seagrass mapping, seagrass bed classification in particular, has been evaluated by mapping accuracy using an error matrix. However, mapping accuracies are influenced by coastal environments such as seawater transparency, bathymetry, and substrate type. Coastal management requires sufficient accuracy and an understanding of mapping limitations for monitoring coastal habitats including seagrass beds. Previous studies are mainly based on case studies in specific regions and seasons. Extensive data are required to generalise assessments of classification accuracy from case studies, which has proven difficult. This study aims to build a simulator based on a radiative transfer model to produce modelled satellite images and assess the visual detectability of seagrass beds under different transparencies and seagrass coverages, as well as to examine mapping limitations and classification accuracy. Our simulations led to the development of a model of water transparency and the mapping of depth limits and indicated the possibility for seagrass density mapping under certain ideal conditions. The results show that modelling satellite images is useful in evaluating the accuracy of classification and that establishing seagrass bed monitoring by remote sensing is a reliable tool.

PROCEDURES FOR ACCURATE PRODUCTION OF COLOR IMAGES FROM SATELLITE OR AIRCRAFT MULTISPECTRAL DIGITAL DATA.

Science.gov (United States)

Duval, Joseph S.

1985-01-01

Because the display and interpretation of satellite and aircraft remote-sensing data make extensive use of color film products, accurate reproduction of the color images is important. To achieve accurate color reproduction, the exposure and chemical processing of the film must be monitored and controlled. By using a combination of sensitometry, densitometry, and transfer functions that control film response curves, all of the different steps in the making of film images can be monitored and controlled. Because a sensitometer produces a calibrated exposure, the resulting step wedge can be used to monitor the chemical processing of the film. Step wedges put on film by image recording machines provide a means of monitoring the film exposure and color balance of the machines.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghunday-Achin mineral district in Afghanistan, in Davis, P.A, compiler, Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.; Davis, Philip A.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghunday-Achin mineral district, which has magnesite and talc deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

High-intensity interval training: Modulating interval duration in overweight/obese men.

Science.gov (United States)

Smith-Ryan, Abbie E; Melvin, Malia N; Wingfield, Hailee L

2015-05-01

High-intensity interval training (HIIT) is a time-efficient strategy shown to induce various cardiovascular and metabolic adaptations. Little is known about the optimal tolerable combination of intensity and volume necessary for adaptations, especially in clinical populations. In a randomized controlled pilot design, we evaluated the effects of two types of interval training protocols, varying in intensity and interval duration, on clinical outcomes in overweight/obese men. Twenty-five men [body mass index (BMI) > 25 kg · m(2)] completed baseline body composition measures: fat mass (FM), lean mass (LM) and percent body fat (%BF) and fasting blood glucose, lipids and insulin (IN). A graded exercise cycling test was completed for peak oxygen consumption (VO2peak) and power output (PO). Participants were randomly assigned to high-intensity short interval (1MIN-HIIT), high-intensity interval (2MIN-HIIT) or control groups. 1MIN-HIIT and 2MIN-HIIT completed 3 weeks of cycling interval training, 3 days/week, consisting of either 10 × 1 min bouts at 90% PO with 1 min rests (1MIN-HIIT) or 5 × 2 min bouts with 1 min rests at undulating intensities (80%-100%) (2MIN-HIIT). There were no significant training effects on FM (Δ1.06 ± 1.25 kg) or %BF (Δ1.13% ± 1.88%), compared to CON. Increases in LM were not significant but increased by 1.7 kg and 2.1 kg for 1MIN and 2MIN-HIIT groups, respectively. Increases in VO2peak were also not significant for 1MIN (3.4 ml·kg(-1) · min(-1)) or 2MIN groups (2.7 ml · kg(-1) · min(-1)). IN sensitivity (HOMA-IR) improved for both training groups (Δ-2.78 ± 3.48 units; p < 0.05) compared to CON. HIIT may be an effective short-term strategy to improve cardiorespiratory fitness and IN sensitivity in overweight males.

A General Approach to Enhance Short Wave Satellite Imagery by Removing Background Atmospheric Effects

Directory of Open Access Journals (Sweden)

Ronald Scheirer

2018-04-01

Full Text Available Atmospheric interaction distorts the surface signal received by a space-borne instrument. Images derived from visible channels appear often too bright and with reduced contrast. This hampers the use of RGB imagery otherwise useful in ocean color applications and in forecasting or operational disaster monitoring, for example forest fires. In order to correct for the dominant source of atmospheric noise, a simple, fast and flexible algorithm has been developed. The algorithm is implemented in Python and freely available in PySpectral which is part of the PyTroll family of open source packages, allowing easy access to powerful real-time image-processing tools. Pre-calculated look-up tables of top of atmosphere reflectance are derived by off-line calculations with RTM DISORT as part of the LibRadtran package. The approach is independent of platform and sensor bands, and allows it to be applied to any band in the visible spectral range. Due to the use of standard atmospheric profiles and standard aerosol loads, it is possible just to reduce the background disturbance. Thus signals from excess aerosols become more discernible. Examples of uncorrected and corrected satellite images demonstrate that this flexible real-time algorithm is a useful tool for atmospheric correction.

Forecasting Global Horizontal Irradiance Using the LETKF and a Combination of Advected Satellite Images and Sparse Ground Sensors

Science.gov (United States)

Harty, T. M.; Lorenzo, A.; Holmgren, W.; Morzfeld, M.

2017-12-01

The irradiance incident on a solar panel is the main factor in determining the power output of that panel. For this reason, accurate global horizontal irradiance (GHI) estimates and forecasts are critical when determining the optimal location for a solar power plant, forecasting utility scale solar power production, or forecasting distributed, behind the meter rooftop solar power production. Satellite images provide a basis for producing the GHI estimates needed to undertake these objectives. The focus of this work is to combine satellite derived GHI estimates with ground sensor measurements and an advection model. The idea is to use accurate but sparsely distributed ground sensors to improve satellite derived GHI estimates which can cover large areas (the size of a city or a region of the United States). We use a Bayesian framework to perform the data assimilation, which enables us to produce irradiance forecasts and associated uncertainties which incorporate both satellite and ground sensor data. Within this framework, we utilize satellite images taken from the GOES-15 geostationary satellite (available every 15-30 minutes) as well as ground data taken from irradiance sensors and rooftop solar arrays (available every 5 minutes). The advection model, driven by wind forecasts from a numerical weather model, simulates cloud motion between measurements. We use the Local Ensemble Transform Kalman Filter (LETKF) to perform the data assimilation. We present preliminary results towards making such a system useful in an operational context. We explain how localization and inflation in the LETKF, perturbations of wind-fields, and random perturbations of the advection model, affect the accuracy of our estimates and forecasts. We present experiments showing the accuracy of our forecasted GHI over forecast-horizons of 15 mins to 1 hr. The limitations of our approach and future improvements are also discussed.

Extracting oil palm crown from WorldView-2 satellite image

Science.gov (United States)

Korom, A.; Phua, M.-H.; Hirata, Y.; Matsuura, T.

2014-02-01

Oil palm (OP) is the most commercial crop in Malaysia. Estimating the crowns is important for biomass estimation from high resolution satellite (HRS) image. This study examined extraction of individual OP crown from a WorldView-2 image using twofold algorithms, i.e., masking of Non-OP pixels and detection of individual OP crown based on the watershed segmentation of greyscale images. The study site was located in Beluran district, central Sabah, where matured OPs with the age ranging from 15 to 25 years old have been planted. We examined two compound vegetation indices of (NDVI+1)*DVI and NDII for masking non-OP crown areas. Using kappa statistics, an optimal threshold value was set with the highest accuracy at 90.6% for differentiating OP crown areas from Non-OP areas. After the watershed segmentation of OP crown areas with additional post-procedures, about 77% of individual OP crowns were successfully detected in comparison to the manual based delineation. Shape and location of each crown segment was then assessed based on a modified version of the goodness measures of Möller et al which was 0.3, indicating an acceptable CSGM (combined segmentation goodness measures) agreements between the automated and manually delineated crowns (perfect case is '1').

Extracting oil palm crown from WorldView-2 satellite image

International Nuclear Information System (INIS)

Korom, A; Phua, M-H; Hirata, Y; Matsuura, T

2014-01-01

Oil palm (OP) is the most commercial crop in Malaysia. Estimating the crowns is important for biomass estimation from high resolution satellite (HRS) image. This study examined extraction of individual OP crown from a WorldView-2 image using twofold algorithms, i.e., masking of Non-OP pixels and detection of individual OP crown based on the watershed segmentation of greyscale images. The study site was located in Beluran district, central Sabah, where matured OPs with the age ranging from 15 to 25 years old have been planted. We examined two compound vegetation indices of (NDVI+1)*DVI and NDII for masking non-OP crown areas. Using kappa statistics, an optimal threshold value was set with the highest accuracy at 90.6% for differentiating OP crown areas from Non-OP areas. After the watershed segmentation of OP crown areas with additional post-procedures, about 77% of individual OP crowns were successfully detected in comparison to the manual based delineation. Shape and location of each crown segment was then assessed based on a modified version of the goodness measures of Möller et al which was 0.3, indicating an acceptable CSGM (combined segmentation goodness measures) agreements between the automated and manually delineated crowns (perfect case is '1')

Minimizing Gaps of Daily Ndvi Map with Geostationary Satellite Remote Sensing Data

Science.gov (United States)

Lee, S.; Ryu, Y.; Jiang, C.

2015-12-01

Satellite based remote sensing has been used to monitor plant phenology. Numerous studies have generally utilized normalized difference vegetation index (NDVI) to quantify phenological patterns and changes in regional to the global scales. Obtaining the NDVI values during summer in East Asian Monsoon regions is important because most plants grow vigorously in this season. However, satellite derived NDVI data are error prone to clouds during most of the period. Various methods have attempted to reduce the effect of cloud in temporal and spatial NDVI monitoring; the fundamental solution is to have a large data pool that includes multiple images in short period and supplements NDVI values in same period. Multiple images of geostationary satellite in a day can be a method to expand the pool. In this study, we suggest an approach that minimizes data gaps in NDVI of the day through geostationary satellite derived NDVI composition. We acquired data from Geostationary Ocean Color Imager (GOCI) which is a satellite that was launched to monitor ocean around the Korean peninsula, China, Japan and Russia. The satellite observes eight times per day (09:00 - 16:00, every hour) at 500 x 500 m resolution from 2011 to 2015. GOCI red- and near infrared radiance was converted into surface reflectance by using 6S Radiative Transfer Model (6S). We calculated NDVI tiles for each of observed eight tiles per day and made one day NDVI through maximum-value composite method. We evaluated the composite GOCI derived NDVI by comparing with daily MODIS-derived NDVI (composited from MOD09GA and MYD09GA), 16-day Landsat 8-derived NDVI, and in-situ light emitting diode (LED) NDVI measurements at a homogeneous deciduous forest and rice paddy sites. We found that GOCI-derived NDVI maps revealed little data gaps compared to MODIS and Landsat, and GOCI derived NDVI time series were smoother than MODIS derived NDVI time series in summer. GOCI-derived NDVI agreed well with in-situ observations of NDVI

Supervised Classification High-Resolution Remote-Sensing Image Based on Interval Type-2 Fuzzy Membership Function

Directory of Open Access Journals (Sweden)

Chunyan Wang

2018-05-01

Full Text Available Because of the degradation of classification accuracy that is caused by the uncertainty of pixel class and classification decisions of high-resolution remote-sensing images, we proposed a supervised classification method that is based on an interval type-2 fuzzy membership function for high-resolution remote-sensing images. We analyze the data features of a high-resolution remote-sensing image and construct a type-1 membership function model in a homogenous region by supervised sampling in order to characterize the uncertainty of the pixel class. On the basis of the fuzzy membership function model in the homogeneous region and in accordance with the 3σ criterion of normal distribution, we proposed a method for modeling three types of interval type-2 membership functions and analyze the different types of functions to improve the uncertainty of pixel class expressed by the type-1 fuzzy membership function and to enhance the accuracy of classification decision. According to the principle that importance will increase with a decrease in the distance between the original, upper, and lower fuzzy membership of the training data and the corresponding frequency value in the histogram, we use the weighted average sum of three types of fuzzy membership as the new fuzzy membership of the pixel to be classified and then integrated into the neighborhood pixel relations, constructing a classification decision model. We use the proposed method to classify real high-resolution remote-sensing images and synthetic images. Additionally, we qualitatively and quantitatively evaluate the test results. The results show that a higher classification accuracy can be achieved with the proposed algorithm.

Multi-Satellite Observation Scheduling for Large Area Disaster Emergency Response

Science.gov (United States)

Niu, X. N.; Tang, H.; Wu, L. X.

2018-04-01

an optimal imaging plan, plays a key role in coordinating multiple satellites to monitor the disaster area. In the paper, to generate imaging plan dynamically according to the disaster relief, we propose a dynamic satellite task scheduling method for large area disaster response. First, an initial robust scheduling scheme is generated by a robust satellite scheduling model in which both the profit and the robustness of the schedule are simultaneously maximized. Then, we use a multi-objective optimization model to obtain a series of decomposing schemes. Based on the initial imaging plan, we propose a mixed optimizing algorithm named HA_NSGA-II to allocate the decomposing results thus to obtain an adjusted imaging schedule. A real disaster scenario, i.e., 2008 Wenchuan earthquake, is revisited in terms of rapid response using satellite resources and used to evaluate the performance of the proposed method with state-of-the-art approaches. We conclude that our satellite scheduling model can optimize the usage of satellite resources so as to obtain images in disaster response in a more timely and efficient manner.

Quaternion-Based Texture Analysis of Multiband Satellite Images: Application to the Estimation of Aboveground Biomass in the East Region of Cameroon.

Science.gov (United States)

Djiongo Kenfack, Cedrigue Boris; Monga, Olivier; Mpong, Serge Moto; Ndoundam, René

2018-03-01

Within the last decade, several approaches using quaternion numbers to handle and model multiband images in a holistic manner were introduced. The quaternion Fourier transform can be efficiently used to model texture in multidimensional data such as color images. For practical application, multispectral satellite data appear as a primary source for measuring past trends and monitoring changes in forest carbon stocks. In this work, we propose a texture-color descriptor based on the quaternion Fourier transform to extract relevant information from multiband satellite images. We propose a new multiband image texture model extraction, called FOTO++, in order to address biomass estimation issues. The first stage consists in removing noise from the multispectral data while preserving the edges of canopies. Afterward, color texture descriptors are extracted thanks to a discrete form of the quaternion Fourier transform, and finally the support vector regression method is used to deduce biomass estimation from texture indices. Our texture features are modeled using a vector composed with the radial spectrum coming from the amplitude of the quaternion Fourier transform. We conduct several experiments in order to study the sensitivity of our model to acquisition parameters. We also assess its performance both on synthetic images and on real multispectral images of Cameroonian forest. The results show that our model is more robust to acquisition parameters than the classical Fourier Texture Ordination model (FOTO). Our scheme is also more accurate for aboveground biomass estimation. We stress that a similar methodology could be implemented using quaternion wavelets. These results highlight the potential of the quaternion-based approach to study multispectral satellite images.

Small satellites and their regulation

CERN Document Server

Jakhu, Ram S

2014-01-01

Since the launch of UoSat-1 of the University of Surrey (United Kingdom) in 1981, small satellites proved regularly to be useful, beneficial, and cost-effective tools. Typical tasks cover education and workforce development, technology demonstration, verification and validation, scientific and engineering research as well as commercial applications. Today the launch masses range over almost three orders of magnitude starting at less than a kilogram up to a few hundred kilograms, with budgets of less than US$ 100.00 and up to millions within very short timeframes of sometimes less than two years. Therefore each category of small satellites provides specific challenges in design, development and operations. Small satellites offer great potentials to gain responsive, low-cost access to space within a short timeframe for institutions, companies, regions and countries beyond the traditional big players in the space arena. For these reasons (particularly the low cost of construction, launch and operation), small (m...

Assessment of different topographic corrections in AWiFS satellite ...

Indian Academy of Sciences (India)

Snow and Avalanche Study Establishment, Defence Research and Development Organisation,. Chandigarh 160 ... IRS P6 satellite images and the qualitative and quantitative comparative analysis in detail. Both .... Top: AWiFS satellite image of Western Himalaya and bottom: zoom image of the study area shown with white.

Reprocessing the Historical Satellite Passive Microwave Record at Enhanced Spatial Resolutions using Image Reconstruction

Science.gov (United States)

Hardman, M.; Brodzik, M. J.; Long, D. G.; Paget, A. C.; Armstrong, R. L.

2015-12-01

Beginning in 1978, the satellite passive microwave data record has been a mainstay of remote sensing of the cryosphere, providing twice-daily, near-global spatial coverage for monitoring changes in hydrologic and cryospheric parameters that include precipitation, soil moisture, surface water, vegetation, snow water equivalent, sea ice concentration and sea ice motion. Currently available global gridded passive microwave data sets serve a diverse community of hundreds of data users, but do not meet many requirements of modern Earth System Data Records (ESDRs) or Climate Data Records (CDRs), most notably in the areas of intersensor calibration, quality-control, provenance and consistent processing methods. The original gridding techniques were relatively primitive and were produced on 25 km grids using the original EASE-Grid definition that is not easily accommodated in modern software packages. Further, since the first Level 3 data sets were produced, the Level 2 passive microwave data on which they were based have been reprocessed as Fundamental CDRs (FCDRs) with improved calibration and documentation. We are funded by NASA MEaSUREs to reprocess the historical gridded data sets as EASE-Grid 2.0 ESDRs, using the most mature available Level 2 satellite passive microwave (SMMR, SSM/I-SSMIS, AMSR-E) records from 1978 to the present. We have produced prototype data from SSM/I and AMSR-E for the year 2003, for review and feedback from our Early Adopter user community. The prototype data set includes conventional, low-resolution ("drop-in-the-bucket" 25 km) grids and enhanced-resolution grids derived from the two candidate image reconstruction techniques we are evaluating: 1) Backus-Gilbert (BG) interpolation and 2) a radiometer version of Scatterometer Image Reconstruction (SIR). We summarize our temporal subsetting technique, algorithm tuning parameters and computational costs, and include sample SSM/I images at enhanced resolutions of up to 3 km. We are actively

Development of a Lyman-α Imaging Solar Telescope for the Satellite

Directory of Open Access Journals (Sweden)

M. Jang

2005-09-01

Full Text Available Long term observations of full-disk Lyman-α irradiance have been made by the instruments on various satellites. In addition, several sounding rockets dating back to the 1950s and up through the present have measured the Lyman-α irradiance. Previous full disk Lyman-α images of the sun have been very interesting and useful scientifically, but have been only five-minute ``snapshots" obtained on sounding rocket flights. All of these observations to date have been snapshots, with no time resolution to observe changes in the chromospheric structure as a result of the evolving magnetic field, and its effect on the Lyman-α intensity. The Lyman-α Imaging Solar Telescope(LIST can provide a unique opportunity for the study of the sun in the Lyman-α region with the high time and spatial resolution for the first time. Up to the 2nd year development, the preliminary design of the optics, mechanical structure and electronics system has been completed. Also the mechanical structure analysis, thermal analysis were performed and the material for the structure was chosen as a result of these analyses. And the test plan and the verification matrix were decided. The operation systems, technical and scientific operation, were studied and finally decided. Those are the technical operation, mechanical working modes for the observation and safety, the scientific operation and the process of the acquired data. The basic techniques acquired through the development of satellite based solar telescope are essential for the construction of space environment forecast system in the future. The techniques which we developed through this study, like mechanical, optical and data processing techniques, could be applied extensively not only to the process of the future production of flight models of this kind, but also to the related industries. Also, we can utilize the scientific achievements which are obtained throughout the project. And these can be utilized to build a high

Assessment of Machine Learning Algorithms for Automatic Benthic Cover Monitoring and Mapping Using Towed Underwater Video Camera and High-Resolution Satellite Images

Directory of Open Access Journals (Sweden)

Hassan Mohamed

2018-05-01

Full Text Available Benthic habitat monitoring is essential for many applications involving biodiversity, marine resource management, and the estimation of variations over temporal and spatial scales. Nevertheless, both automatic and semi-automatic analytical methods for deriving ecologically significant information from towed camera images are still limited. This study proposes a methodology that enables a high-resolution towed camera with a Global Navigation Satellite System (GNSS to adaptively monitor and map benthic habitats. First, the towed camera finishes a pre-programmed initial survey to collect benthic habitat videos, which can then be converted to geo-located benthic habitat images. Second, an expert labels a number of benthic habitat images to class habitats manually. Third, attributes for categorizing these images are extracted automatically using the Bag of Features (BOF algorithm. Fourth, benthic cover categories are detected automatically using Weighted Majority Voting (WMV ensembles for Support Vector Machines (SVM, K-Nearest Neighbor (K-NN, and Bagging (BAG classifiers. Fifth, WMV-trained ensembles can be used for categorizing more benthic cover images automatically. Finally, correctly categorized geo-located images can provide ground truth samples for benthic cover mapping using high-resolution satellite imagery. The proposed methodology was tested over Shiraho, Ishigaki Island, Japan, a heterogeneous coastal area. The WMV ensemble exhibited 89% overall accuracy for categorizing corals, sediments, seagrass, and algae species. Furthermore, the same WMV ensemble produced a benthic cover map using a Quickbird satellite image with 92.7% overall accuracy.

Satellite Sensor Requirements for Monitoring Essential Biodiversity Variables of Coastal Ecosystems

Science.gov (United States)

Muller-Karger, Frank E.; Hestir, Erin; Ade, Christiana; Turpie, Kevin; Roberts, Dar A.; Siegel, David; Miller, Robert J.; Humm, David; Izenberg, Noam; Keller, Mary;

Link between EMIC waves in a plasmaspheric plume and a detached sub-auroral proton arc with observations of Cluster and IMAGE satellites

Science.gov (United States)

Yuan, Zhigang; Deng, Xiaohua; Lin, Xi; Pang, Ye; Zhou, Meng; Décréau, P. M. E.; Trotignon, J. G.; Lucek, E.; Frey, H. U.; Wang, Jingfang

2010-04-01

In this paper, we report observations from a Cluster satellite showing that ULF wave occurred in the outer boundary of a plasmaspheric plume on September 4, 2005. The band of observed ULF waves is between the He+ ion gyrofrequency and O+ ion gyrofrequency at the equatorial plane, implying that those ULF waves can be identified as EMIC waves generated by ring current ions in the equatorial plane and strongly affected by rich cold He+ ions in plasmaspheric plumes. During the interval of observed EMIC waves, the footprint of Cluster SC3 lies in a subauroral proton arc observed by the IMAGE FUV instrument, demonstrating that the subauroral proton arc was caused by energetic ring current protons scattered into the loss cone under the Ring Current (RC)-EMIC interaction in the plasmaspheric plume. Therefore, the paper provides a direct proof that EMIC waves can be generated in the plasmaspheric plume and scatter RC ions to cause subauroral proton arcs.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Nuristan mineral district in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.; Davis, Philip A.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Nuristan mineral district, which has gem, lithium, and cesium deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS

Deterministic and probabilistic interval prediction for short-term wind power generation based on variational mode decomposition and machine learning methods

International Nuclear Information System (INIS)

Zhang, Yachao; Liu, Kaipei; Qin, Liang; An, Xueli

2016-01-01

Highlights: • Variational mode decomposition is adopted to process original wind power series. • A novel combined model based on machine learning methods is established. • An improved differential evolution algorithm is proposed for weight adjustment. • Probabilistic interval prediction is performed by quantile regression averaging. - Abstract: Due to the increasingly significant energy crisis nowadays, the exploitation and utilization of new clean energy gains more and more attention. As an important category of renewable energy, wind power generation has become the most rapidly growing renewable energy in China. However, the intermittency and volatility of wind power has restricted the large-scale integration of wind turbines into power systems. High-precision wind power forecasting is an effective measure to alleviate the negative influence of wind power generation on the power systems. In this paper, a novel combined model is proposed to improve the prediction performance for the short-term wind power forecasting. Variational mode decomposition is firstly adopted to handle the instability of the raw wind power series, and the subseries can be reconstructed by measuring sample entropy of the decomposed modes. Then the base models can be established for each subseries respectively. On this basis, the combined model is developed based on the optimal virtual prediction scheme, the weight matrix of which is dynamically adjusted by a self-adaptive multi-strategy differential evolution algorithm. Besides, a probabilistic interval prediction model based on quantile regression averaging and variational mode decomposition-based hybrid models is presented to quantify the potential risks of the wind power series. The simulation results indicate that: (1) the normalized mean absolute errors of the proposed combined model from one-step to three-step forecasting are 4.34%, 6.49% and 7.76%, respectively, which are much lower than those of the base models and the hybrid

Applying a new computer-aided detection scheme generated imaging marker to predict short-term breast cancer risk

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Mirniaharikandehei, Seyedehnafiseh; Hollingsworth, Alan B.; Patel, Bhavika; Heidari, Morteza; Liu, Hong; Zheng, Bin

2018-05-01

This study aims to investigate the feasibility of identifying a new quantitative imaging marker based on false-positives generated by a computer-aided detection (CAD) scheme to help predict short-term breast cancer risk. An image dataset including four view mammograms acquired from 1044 women was retrospectively assembled. All mammograms were originally interpreted as negative by radiologists. In the next subsequent mammography screening, 402 women were diagnosed with breast cancer and 642 remained negative. An existing CAD scheme was applied ‘as is’ to process each image. From CAD-generated results, four detection features including the total number of (1) initial detection seeds and (2) the final detected false-positive regions, (3) average and (4) sum of detection scores, were computed from each image. Then, by combining the features computed from two bilateral images of left and right breasts from either craniocaudal or mediolateral oblique view, two logistic regression models were trained and tested using a leave-one-case-out cross-validation method to predict the likelihood of each testing case being positive in the next subsequent screening. The new prediction model yielded the maximum prediction accuracy with an area under a ROC curve of AUC  =  0.65  ±  0.017 and the maximum adjusted odds ratio of 4.49 with a 95% confidence interval of (2.95, 6.83). The results also showed an increasing trend in the adjusted odds ratio and risk prediction scores (p  breast cancer risk.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Panjsher Valley mineral district in Afghanistan: Chapter M in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.; Cagney, Laura E.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Panjsher Valley mineral district, which has emerald and silver-iron deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2009, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from

Seagrass mapping in Greek territorial waters using Landsat-8 satellite images

Science.gov (United States)

Topouzelis, Konstantinos; Makri, Despina; Stoupas, Nikolaos; Papakonstantinou, Apostolos; Katsanevakis, Stelios

2018-05-01

Seagrass meadows are among the most valuable coastal ecosystems on earth due to their structural and functional roles in the coastal environment. This study demonstrates remote sensing's capacity to produce seagrass distribution maps on a regional scale. The seagrass coverage maps provided here describe and quantify for the first time the extent and the spatial distribution of seagrass meadows in Greek waters. This information is needed for identifying priority conservation sites and to help coastal ecosystem managers and stakeholders to develop conservation strategies and design a resilient network of protected marine areas. The results were based on an object-based image analysis of 50 Landsat-8 satellite images. The time window of image acquisition was between June 2013 and July 2015. In total, the seagrass coverage in Greek waters was estimated at 2619 km2. The largest coverages of individual seagrass meadows were found around Lemnos Island (124 km2), Corfu Island (46 km2), and East Peloponnese (47 km2). The accuracy assessment of the detected areas was based on 62 Natura 2000 sites, for which habitat maps were available. The mean total accuracy for all 62 sites was estimated at 76.3%.

A general theory for the Uranian satellites

Science.gov (United States)

Laskar, J.

1986-01-01

A general analytical theory of the five main satellites of Uranus, including the secular and short period terms hereafter denoted by GUST, is presented. A comparison is made with an internal numerical integration with nominal masses of Veillet (1983). The precision of the theory goes from about 10 km for Miranda to 100 km for Oberon. The short period terms in the motions of Titania and Oberon are larger than 500 km. They should make possible the determination of the masses of the outer satellites through the optical data of Voyager encounter.

Validation of satellite data through the remote sensing techniques and the inclusion of them into agricultural education pilot programs

Science.gov (United States)

Papadavid, Georgios; Kountios, Georgios; Bournaris, T.; Michailidis, Anastasios; Hadjimitsis, Diofantos G.

2016-08-01

Nowadays, the remote sensing techniques have a significant role in all the fields of agricultural extensions as well as agricultural economics and education but they are used more specifically in hydrology. The aim of this paper is to demonstrate the use of field spectroscopy for validation of the satellite data and how combination of remote sensing techniques and field spectroscopy can have more accurate results for irrigation purposes. For this reason vegetation indices are used which are mostly empirical equations describing vegetation parameters during the lifecycle of the crops. These numbers are generated by some combination of remote sensing bands and may have some relationship to the amount of vegetation in a given image pixel. Due to the fact that most of the commonly used vegetation indices are only concerned with red-near-infrared spectrum and can be divided to perpendicular and ratio based indices the specific goal of the research is to illustrate the effect of the atmosphere to those indices, in both categories. In this frame field spectroscopy is employed in order to derive the spectral signatures of different crops in red and infrared spectrum after a campaign of ground measurements. The main indices have been calculated using satellite images taken at interval dates during the whole lifecycle of the crops by using a GER 1500 spectro-radiomete. These indices was compared to those extracted from satellite images after applying an atmospheric correction algorithm -darkest pixel- to the satellite images at a pre-processing level so as the indices would be in comparable form to those of the ground measurements. Furthermore, there has been a research made concerning the perspectives of the inclusion of the above mentioned remote satellite techniques to agricultural education pilot programs.

Satellite Images-Based Obstacle Recognition and Trajectory Generation for Agricultural Vehicles

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Mehmet Bodur

2015-12-01

Full Text Available In this study, a method for the generation of tracking trajectory points, detection and positioning of obstacles in agricultural fields have been presented. Our principal contribution is to produce traceable GPS trajectories for agricultural vehicles to be utilized by path planning algorithms, rather than a new path planning algorithm. The proposed system works with minimal initialization requirements, specifically, a single geographical coordinate entry of an agricultural field. The automation of agricultural plantation requires many aspects to be addressed, many of which have been covered in previous studies. Depending on the type of crop, different agricultural vehicles may be used in the field. However, regardless of their application, they all follow a specified trajectory in the field. This study takes advantage of satellite images for the detection and positioning of obstacles, and the generation of GPS trajectories in the agricultural realm. A set of image processing techniques is applied in Matlab for detection and positioning.

Galileo's first images of Jupiter and the Galilean satellites

Science.gov (United States)

Belton, M.J.S.; Head, J. W.; Ingersoll, A.P.; Greeley, R.; McEwen, A.S.; Klaasen, K.P.; Senske, D.; Pappalardo, R.; Collins, G.; Vasavada, A.R.; Sullivan, R.; Simonelli, D.; Geissler, P.; Carr, M.H.; Davies, M.E.; Veverka, J.; Gierasch, P.J.; Banfield, D.; Bell, M.; Chapman, C.R.; Anger, C.; Greenberg, R.; Neukum, G.; Pilcher, C.B.; Beebe, R.F.; Burns, J.A.; Fanale, F.; Ip, W.; Johnson, T.V.; Morrison, D.; Moore, J.; Orton, G.S.; Thomas, P.; West, R.A.

1996-01-01

The first images of Jupiter, Io, Europa, and Ganymede from the Galileo spacecraft reveal new information about Jupiter's Great Red Spot (GRS) and the surfaces of the Galilean satellites. Features similar to clusters of thunderstorms were found in the GRS. Nearby wave structures suggest that the GRS may be a shallow atmospheric feature. Changes in surface color and plume distribution indicate differences in resurfacing processes near hot spots on lo. Patchy emissions were seen while Io was in eclipse by Jupiter. The outer margins of prominent linear markings (triple bands) on Europa are diffuse, suggesting that material has been vented from fractures. Numerous small circular craters indicate localized areas of relatively old surface. Pervasive brittle deformation of an ice layer appears to have formed grooves on Ganymede. Dark terrain unexpectedly shows distinctive albedo variations to the limit of resolution.

Numerical investigation of debris materials prior to debris flow hazards using satellite images

Science.gov (United States)

Zhang, N.; Matsushima, T.

2018-05-01

The volume of debris flows occurred in mountainous areas is mainly affected by the volume of debris materials deposited at the valley bottom. Quantitative evaluation of debris materials prior to debris flow hazards is important to predict and prevent hazards. At midnight on 7th August 2010, two catastrophic debris flows were triggered by the torrential rain from two valleys in the northern part of Zhouqu City, NW China, resulting in 1765 fatalities and huge economic losses. In the present study, a depth-integrated particle method is adopted to simulate the debris materials, based on 2.5 m resolution satellite images. In the simulation scheme, the materials are modeled as dry granular solids, and they travel down from the slopes and are deposited at the valley bottom. The spatial distributions of the debris materials are investigated in terms of location, volume and thickness. Simulation results show good agreement with post-disaster satellite images and field observation data. Additionally, the effect of the spatial distributions of the debris materials on subsequent debris flows is also evaluated. It is found that the spatial distributions of the debris materials strongly influence affected area, runout distance and flow discharge. This study might be useful in hazard assessments prior to debris flow hazards by investigating diverse scenarios in which the debris materials are unknown.

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Parwan mineral district in Afghanistan: Chapter CC in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

Science.gov (United States)

Davis, Philip A.

2013-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Parwan mineral district, which has gold and copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006, 2007), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

Influence of acute high-intensity aerobic interval exercise bout on selective attention and short-term memory tasks.

Science.gov (United States)

Alves, Christiano R R; Tessaro, Victor H; Teixeira, Luis A C; Murakava, Karina; Roschel, Hamilton; Gualano, Bruno; Takito, Monica Y

2014-02-01

Acute moderate intensity continuous aerobic exercise can improve specific cognitive functions, such as short-term memory and selective attention. Moreover, high-intensity interval training (HIT) has been recently proposed as a time-efficient alternative to traditional cardiorespiratory exercise. However, considering previous speculations that the exercise intensity affects cognition in a U-shaped fashion, it was hypothesized that a HIT session may impair cognitive performance. Therefore, this study assessed the effects of an acute HIT session on selective attention and short-term memory tasks. 22 healthy middle-aged individuals (M age = 53.7 yr.) engaged in both (1) a HIT session, 10 1 min. cycling bouts at the intensity corresponding to 80% of the reserve heart rate interspersed by 1 min. active pauses cycling at 60% of the reserve heart rate and (2) a control session, consisting of an active condition with low-intensity active stretching exercise. Before and after each experimental session, cognitive performance was assessed by the Victoria Version of the Stroop test (a selective attention test) and the Digit Span test (a short-term memory test). Following the HIT session, the time to complete the Stroop "Color word" test was significantly lower when compared with that of the control session. The performances in the other subtasks of the Stroop test as well as in the Digit Span test were not significantly different. A HIT session can improve cognitive function.

Cadastral Resurvey using High Resolution Satellite Ortho Image - challenges: A case study in Odisha, India

Science.gov (United States)

Parida, P. K.; Sanabada, M. K.; Tripathi, S.

2014-11-01

Advancements in satellite sensor technology enabling capturing of geometrically accurate images of earth's surface coupled with DGPS/ETS and GIS technology holds the capability of large scale mapping of land resources at cadastral level. High Resolution Satellite Images depict field bunds distinctly. Thus plot parcels are to be delineated from cloud free ortho-images and obscured/difficult areas are to be surveyed using DGPS and ETS. The vector datasets thus derived through RS/DGPS/ETS survey are to be integrated in GIS environment to generate the base cadastral vector datasets for further settlement/title confirmation activities. The objective of this paper is to illustrate the efficacy of a hybrid methodology employed in Pitambarpur Sasana village under Digapahandi Tahasil of Ganjam district, as a pilot project, particularly in Odisha scenario where the land parcel size is very small. One of the significant observations of the study is matching of Cadastral map area i.e. 315.454 Acres, the image map area i.e. 314.887 Acres and RoR area i.e. 313.815 Acre. It was revealed that 79 % of plots derived by high-tech survey method show acceptable level of accuracy despite the fact that the mode of area measurement by ground and automated method has significant variability. The variations are more in case of Government lands, Temple/Trust lands, Common Property Resources and plots near to river/nalas etc. The study indicates that the adopted technology can be extended to other districts and cadastral resurvey and updating work can be done for larger areas of the country using this methodology.

Use of high-resolution satellite images for detection of geological structures related to Central Andes geothermal field, Chile.

Science.gov (United States)

Benavides-Rivas, C. L.; Soto-Pinto, C. A.; Arellano-Baeza, A. A.

2014-12-01

Central valley and the border with Argentina in the center, and in the fault system Liquiñe-Ofqui in the South of the country. High resolution images from the LANDSAT 8 satellite have been used to delineate the geological structures related to the potential geothermal reservoirs located at the northern end of the Southern Volcanic Zone of Chile. It was done by applying the lineament extraction technique, using the ADALGEO software, developed by [Soto et al., 2013]. These structures have been compared with the distribution of main geological structures obtained in the field. It was found that the lineament density increases in the areas of the major heat flux indicating that the lineament analysis could be a power tool for the detection of faults and joint zones associated to the geothermal fields. A lineament is generally defined as a straight or slightly curved feature in the landscape visible satellite image as an aligned sequence of pixel intensity contrast compared to the background. The system features extracted from satellite images is not identical to the geological lineaments that are generally determined by ground surveys, however, generally reflects the structure of faults and fractures in the crust. A temporal sequence of eight Landsat multispectral images of Central Andes geothermal field, located in VI region de Chile, was used to study changes in the configuration of the lineaments during 2011. The presence of minerals with silicification, epidotization, and albitization, which are typical for geothrmal reservoirs, was also identified, using their spectral characteristics, and subsequently corroborated in the field. Both lineament analysis and spectral analysis gave similar location of the reservoir, which increases reliability of the results.

Observations of short gamma-ray bursts.

Science.gov (United States)

Fox, Derek B; Roming, Peter W A

2007-05-15

We review recent observations of short-hard gamma-ray bursts and their afterglows. The launch and successful ongoing operations of the Swift satellite, along with several localizations from the High-Energy Transient Explorer mission, have provoked a revolution in short-burst studies: first, by quickly providing high-quality positions to observers; and second, via rapid and sustained observations from the Swift satellite itself. We make a complete accounting of Swift-era short-burst localizations and proposed host galaxies, and discuss the implications of these observations for the distances, energetics and environments of short bursts, and the nature of their progenitors. We then review the physical modelling of short-burst afterglows: while the simplest afterglow models are inadequate to explain the observations, there have been several notable successes. Finally, we address the case of an unusual burst that threatens to upset the simple picture in which long bursts are due to the deaths of massive stars, and short bursts to compact-object merger events.

REQUIREMENTS FOR IMAGE QUALITY OF EMERGENCY SPACECRAFTS

Directory of Open Access Journals (Sweden)

A. I. Altukhov

2015-05-01

Full Text Available The paper deals with the method for formation of quality requirements to the images of emergency spacecrafts. The images are obtained by means of remote sensing of near-earth space orbital deployment in the visible range. of electromagnetic radiation. The method is based on a joint taking into account conditions of space survey, characteristics of surveillance equipment, main design features of the observed spacecrafts and orbital inspection tasks. Method. Quality score is the predicted linear resolution image that gives the possibility to create a complete view of pictorial properties of the space image obtained by electro-optical system from the observing satellite. Formulation of requirements to the numerical value of this indicator is proposed to perform based on the properties of remote sensing system, forming images in the conditions of outer space, and the properties of the observed emergency spacecraft: dimensions, platform construction of the satellite, on-board equipment placement. For method implementation the authors have developed a predictive model of requirements to a linear resolution for images of emergency spacecrafts, making it possible to select the intervals of space shooting and get the satellite images required for quality interpretation. Main results. To verify the proposed model functionality we have carried out calculations of the numerical values for the linear resolution of the image, ensuring the successful task of determining the gross structural damage of the spacecrafts and identifying changes in their spatial orientation. As input data were used with dimensions and geometric primitives corresponding to the shape of deemed inspected spacecrafts: Resurs-P", "Canopus-B", "Electro-L". Numerical values of the linear resolution images have been obtained, ensuring the successful task solution for determining the gross structural damage of spacecrafts.

Application of Interval Type-2 Fuzzy Logic System in Short Term Load Forecasting on Special Days

Directory of Open Access Journals (Sweden)

Agus Dharma

2011-05-01

Full Text Available This paper presents the application of Interval Type-2 fuzzy logic systems (Interval Type-2 FLS in short term load forecasting (STLF on special days, study case in Bali Indonesia. Type-2 FLS is characterized by a concept called footprint of uncertainty (FOU that provides the extra mathematical dimension that equips Type-2 FLS with the potential to outperform their Type-1 counterparts. While a Type-2 FLS has the capability to model more complex relationships, the output of a Type-2 fuzzy inference engine needs to be type-reduced. Type reduction is used by applying the Karnik-Mendel (KM iterative algorithm. This type reduction maps the output of Type-2 FSs into Type-1 FSs then the defuzzification with centroid method converts that Type-1 reduced FSs into a number. The proposed method was tested with the actual load data of special days using 4 days peak load before special days and at the time of special day for the year 2002-2006. There are 20 items of special days in Bali that are used to be forecasted in the year 2005 and 2006 respectively. The test results showed an accurate forecasting with the mean average percentage error of 1.0335% and 1.5683% in the year 2005 and 2006 respectively.

Slope mass movements on SPOT satellite images: A case of the Železniki area (W Slovenia after flash floods in September 2007

Directory of Open Access Journals (Sweden)

Mateja Jemec

2008-12-01

Full Text Available Flash floods in Slovenia, which was exposed on September 18th 2007, demanded 6 lives, several thousand houses and over one thousand kilometres of roads were damaged and more also than 50 bridges. The highest amount of rain fell at west and north-west parts of Slovenia (northern Primorska region and southern Gorenjska region,from where heavy rain spread eastwards over the central Slovenia and in east part of Slovenia. In the article we focused on area of western and north-western part of Slovenia. The aim of present research was in the first phase to describe methodology to determine landslide occurrences from satellite images before and after natural disaster on Železniki region. Second phase was based on comparison of obtained results with the existing models for prediction of slope mass movements, and finally also to determine identificability of landslide types on a satellite image.Results have shown, that the highest part of obtaining area from supervised and unsupervised classification of satellite images, are comparable with classes of landslide susceptibility, where occurrences of landslide are largest.

Instantaneous Shoreline Extraction Utilizing Integrated Spectrum and Shadow Analysis From LiDAR Data and High-resolution Satellite Imagery

Science.gov (United States)

Lee, I.-Chieh

Shoreline delineation and shoreline change detection are expensive processes in data source acquisition and manual shoreline delineation. These costs confine the frequency and interval of shoreline mapping periods. In this dissertation, a new shoreline delineation approach was developed targeting on lowering the data source cost and reducing human labor. To lower the cost of data sources, we used the public domain LiDAR data sets and satellite images to delineate shorelines without the requirement of data sets being acquired simultaneously, which is a new concept in this field. To reduce the labor cost, we made improvements in classifying LiDAR points and satellite images. Analyzing shadow relations with topography to improve the satellite image classification performance is also a brand-new concept. The extracted shoreline of the proposed approach could achieve an accuracy of 1.495 m RMSE, or 4.452m at the 95% confidence level. Consequently, the proposed approach could successfully lower the cost and shorten the processing time, in other words, to increase the shoreline mapping frequency with a reasonable accuracy. However, the extracted shoreline may not compete with the shoreline extracted by aerial photogrammetric procedures in the aspect of accuracy. Hence, this is a trade-off between cost and accuracy. This approach consists of three phases, first, a shoreline extraction procedure based mainly on LiDAR point cloud data with multispectral information from satellite images. Second, an object oriented shoreline extraction procedure to delineate shoreline solely from satellite images; in this case WorldView-2 images were used. Third, a shoreline integration procedure combining these two shorelines based on actual shoreline changes and physical terrain properties. The actual data source cost would only be from the acquisition of satellite images. On the other hand, only two processes needed human attention. First, the shoreline within harbor areas needed to be

Looking at Earth from space: Direct readout from environmental satellites

Science.gov (United States)

1994-01-01

Direct readout is the capability to acquire information directly from meteorological satellites. Data can be acquired from NASA-developed, National Oceanic and Atmospheric Administration (NOAA)-operated satellites, as well as from other nations' meteorological satellites. By setting up a personal computer-based ground (Earth) station to receive satellite signals, direct readout may be obtained. The electronic satellite signals are displayed as images on the computer screen. The images can display gradients of the Earth's topography and temperature, cloud formations, the flow and direction of winds and water currents, the formation of hurricanes, the occurrence of an eclipse, and a view of Earth's geography. Both visible and infrared images can be obtained. This booklet introduces the satellite systems, ground station configuration, and computer requirements involved in direct readout. Also included are lists of associated resources and vendors.

Multispectral image enhancement processing for microsat-borne imager

Science.gov (United States)

Sun, Jianying; Tan, Zheng; Lv, Qunbo; Pei, Linlin

2017-10-01

With the rapid development of remote sensing imaging technology, the micro satellite, one kind of tiny spacecraft, appears during the past few years. A good many studies contribute to dwarfing satellites for imaging purpose. Generally speaking, micro satellites weigh less than 100 kilograms, even less than 50 kilograms, which are slightly larger or smaller than the common miniature refrigerators. However, the optical system design is hard to be perfect due to the satellite room and weight limitation. In most cases, the unprocessed data captured by the imager on the microsatellite cannot meet the application need. Spatial resolution is the key problem. As for remote sensing applications, the higher spatial resolution of images we gain, the wider fields we can apply them. Consequently, how to utilize super resolution (SR) and image fusion to enhance the quality of imagery deserves studying. Our team, the Key Laboratory of Computational Optical Imaging Technology, Academy Opto-Electronics, is devoted to designing high-performance microsat-borne imagers and high-efficiency image processing algorithms. This paper addresses a multispectral image enhancement framework for space-borne imagery, jointing the pan-sharpening and super resolution techniques to deal with the spatial resolution shortcoming of microsatellites. We test the remote sensing images acquired by CX6-02 satellite and give the SR performance. The experiments illustrate the proposed approach provides high-quality images.

Short interval measurement of the Thomson scattering system at the pellet injection by using the event triggering system in LHD

International Nuclear Information System (INIS)

Yasuhara, R.; Sakamoto, R.; Motojima, G.; Yamada, I.; Hayashi, H.

2013-01-01

We have demonstrated Thomson scattering measurements of a short interval less than 1 ms by using the event triggering system with a multi-laser configuration. We have tried to measure this system at the pellet injection and obtained electron temperature and density profiles before and just after the pellet injection. Obtained profiles were dramatically changed after pellet injection with shot-by-shot measurements. This measurement technique will contribute understanding the physics of the pellet deposition. (author)

Satellite monitoring of remote volcanoes improves study efforts in Alaska

Science.gov (United States)

Dean, K.; Servilla, M.; Roach, A.; Foster, B.; Engle, K.

Satellite monitoring of remote volcanoes is greatly benefitting the Alaska Volcano Observatory (AVO), and last year's eruption of the Okmok Volcano in the Aleutian Islands is a good case in point. The facility was able to issue and refine warnings of the eruption and related activity quickly, something that could not have been done using conventional seismic surveillance techniques, since seismometers have not been installed at these locations.AVO monitors about 100 active volcanoes in the North Pacific (NOPAC) region, but only a handful are observed by costly and logistically complex conventional means. The region is remote and vast, about 5000 × 2500 km, extending from Alaska west to the Kamchatka Peninsula in Russia (Figure 1). Warnings are transmitted to local communities and airlines that might be endangered by eruptions. More than 70,000 passenger and cargo flights fly over the region annually, and airborne volcanic ash is a threat to them. Many remote eruptions have been detected shortly after the initial magmatic activity using satellite data, and eruption clouds have been tracked across air traffic routes. Within minutes after eruptions are detected, information is relayed to government agencies, private companies, and the general public using telephone, fax, and e-mail. Monitoring of volcanoes using satellite image data involves direct reception, real-time monitoring, and data analysis. Two satellite data receiving stations, located at the Geophysical Institute, University of Alaska Fairbanks (UAF), are capable of receiving data from the advanced very high resolution radiometer (AVHRR) on National Oceanic and Atmospheric Administration (NOAA) polar orbiting satellites and from synthetic aperture radar (SAR) equipped satellites.

CLOUD DETECTION OF OPTICAL SATELLITE IMAGES USING SUPPORT VECTOR MACHINE

Directory of Open Access Journals (Sweden)

K.-Y. Lee

2016-06-01

Full Text Available Cloud covers are generally present in optical remote-sensing images, which limit the usage of acquired images and increase the difficulty of data analysis, such as image compositing, correction of atmosphere effects, calculations of vegetation induces, land cover classification, and land cover change detection. In previous studies, thresholding is a common and useful method in cloud detection. However, a selected threshold is usually suitable for certain cases or local study areas, and it may be failed in other cases. In other words, thresholding-based methods are data-sensitive. Besides, there are many exceptions to control, and the environment is changed dynamically. Using the same threshold value on various data is not effective. In this study, a threshold-free method based on Support Vector Machine (SVM is proposed, which can avoid the abovementioned problems. A statistical model is adopted to detect clouds instead of a subjective thresholding-based method, which is the main idea of this study. The features used in a classifier is the key to a successful classification. As a result, Automatic Cloud Cover Assessment (ACCA algorithm, which is based on physical characteristics of clouds, is used to distinguish the clouds and other objects. In the same way, the algorithm called Fmask (Zhu et al., 2012 uses a lot of thresholds and criteria to screen clouds, cloud shadows, and snow. Therefore, the algorithm of feature extraction is based on the ACCA algorithm and Fmask. Spatial and temporal information are also important for satellite images. Consequently, co-occurrence matrix and temporal variance with uniformity of the major principal axis are used in proposed method. We aim to classify images into three groups: cloud, non-cloud and the others. In experiments, images acquired by the Landsat 7 Enhanced Thematic Mapper Plus (ETM+ and images containing the landscapes of agriculture, snow area, and island are tested. Experiment results demonstrate

Cloud Detection of Optical Satellite Images Using Support Vector Machine

Science.gov (United States)

Lee, Kuan-Yi; Lin, Chao-Hung

2016-06-01

Cloud covers are generally present in optical remote-sensing images, which limit the usage of acquired images and increase the difficulty of data analysis, such as image compositing, correction of atmosphere effects, calculations of vegetation induces, land cover classification, and land cover change detection. In previous studies, thresholding is a common and useful method in cloud detection. However, a selected threshold is usually suitable for certain cases or local study areas, and it may be failed in other cases. In other words, thresholding-based methods are data-sensitive. Besides, there are many exceptions to control, and the environment is changed dynamically. Using the same threshold value on various data is not effective. In this study, a threshold-free method based on Support Vector Machine (SVM) is proposed, which can avoid the abovementioned problems. A statistical model is adopted to detect clouds instead of a subjective thresholding-based method, which is the main idea of this study. The features used in a classifier is the key to a successful classification. As a result, Automatic Cloud Cover Assessment (ACCA) algorithm, which is based on physical characteristics of clouds, is used to distinguish the clouds and other objects. In the same way, the algorithm called Fmask (Zhu et al., 2012) uses a lot of thresholds and criteria to screen clouds, cloud shadows, and snow. Therefore, the algorithm of feature extraction is based on the ACCA algorithm and Fmask. Spatial and temporal information are also important for satellite images. Consequently, co-occurrence matrix and temporal variance with uniformity of the major principal axis are used in proposed method. We aim to classify images into three groups: cloud, non-cloud and the others. In experiments, images acquired by the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and images containing the landscapes of agriculture, snow area, and island are tested. Experiment results demonstrate the detection

PRELIMINARY RESULTS OF THE COMPARISON OF SATELLITE IMAGERS USING TUZ GÖLÜ AS A REFERENCE STANDARD

Directory of Open Access Journals (Sweden)

H. Özen

2012-07-01

Full Text Available Earth surfaces, such as deserts, salt lakes, and playas, have been widely used in the vicarious radiometric calibration of optical earth observation satellites. In 2009, the Infrared and Visible Optical Sensors (IVOS sub-group of the Committee of Earth Observation Satellites (CEOS Working Group on Calibration and Validation (WGCV designated eight LANDNET reference sites to focus international efforts, facilitate traceability and enable the establishment of measurement "best practices." With support from the European Space Agency (ESA, one of the LANDNET sites, the Tuz Gölü salt lake located in central Turkey, was selected to host a cross-comparison of measurement instrumentation and methodologies conducted by 11 different ground teams across the globe. This paper provides an overview of the preliminary results of the cross-comparison of the ground-based spectral measurements made during the CEOS Land Comparison 13-27 August, 2010 with the simultaneous satellite image data acquisitions of the same site.

Use of SEVIRI images and derived products in a WMO Sand and dust Storm Warning System

Energy Technology Data Exchange (ETDEWEB)

MartInez, M A; Ruiz, J; Cuevas, E [Agencia Estatal de MeteorologIa (AEMET) (Spain)], E-mail: mig@inm.es

2009-03-01

The Visible/IR images of SEVIRI (Spinning Enhanced Visible and Infrared Imager), on board Meteosat Second Generation (MSG) satellites, are used to monitor dust events. Satellite-based detection of dust is a difficult problem due in part to the observing-system limitations. The main difficulty is that the dust can be confused with water/ice clouds. SEVIRI is not as optimal for the viewing of dust as SEAWIFS or MODIS, due to the fact that both of them count with additional short-wavelength channels. However, the SEVIRI 15-minute loop images can detect small dust plumes as well as subtle changes from one image to the next. A description of how the AEMET, former INM, is developing the environment to support MSG satellite imagery to the WMO/GEO Sand and Dust Storm Warning System (SDS WS) for Europe, Africa and Middle East Regional Centre will be briefly presented, together with some on-going operational developments to best monitor dust events.

Local Analysis Approach for Short Wavelength Geopotential Variations

Science.gov (United States)

Bender, P. L.

2009-12-01

results from different arcs crossing the region can be seen most easily for an orbit with moderate inclination, such as 50 to 65 deg., so that the crossing angle between south-to-north (S-N) and N-S passes is fairly large over most regions well away from the poles. In that case, after filtering to pass the shorter wavelengths, the results for a given time interval can be combined to give the short wavelength W-E variations in the geopotential efficiently. For continents with extensive meteorological measurements available, like Europe and North America, a very rough guess at the surface mass density variation uncertainties is about 3 kg/m^2. This is based on the apparent accuracy of carefully calibrated surface pressure measurements. If a substantial part of the resulting uncertainties in the geopotential height at satellite altitude are at wavelengths less than about 1,500 km, they will dominate the measurement uncertainty at short spatial wavelengths for a GRACE-type mission with laser interferometry. This would be the case, even if the uncertainty in the atmospheric and oceanic mass distribution at large distances has a fairly small effect. However, the geopotential accuracy would still be substantially better than for the results achievable with a microwave ranging system.

An introduction to optimal satellite range scheduling

CERN Document Server

Vázquez Álvarez, Antonio José

2015-01-01

The satellite range scheduling (SRS) problem, an important operations research problem in the aerospace industry consisting of allocating tasks among satellites and Earth-bound objects, is examined in this book. SRS principles and solutions are applicable to many areas, including: Satellite communications, where tasks are communication intervals between sets of satellites and ground stations Earth observation, where tasks are observations of spots on the Earth by satellites Sensor scheduling, where tasks are observations of satellites by sensors on the Earth. This self-contained monograph begins with a structured compendium of the problem and moves on to explain the optimal approach to the solution, which includes aspects from graph theory, set theory, game theory and belief networks. This book is accessible to students, professionals and researchers in a variety of fields, including: operations research, optimization, scheduling theory, dynamic programming and game theory. Taking account of the distributed, ...

Diffusion-weighted perinatal postmortem magnetic resonance imaging as a marker of postmortem interval

Energy Technology Data Exchange (ETDEWEB)

Arthurs, Owen J. [Great Ormond Street Hospital for Children NHS Foundation Trust, Department of Radiology, London (United Kingdom); UCL Institute of Child Health, Imaging and Biophysics, London (United Kingdom); Price, Gemma C. [Great Ormond Street Hospital for Children NHS Foundation Trust, Department of Radiology, London (United Kingdom); Carmichael, David W. [UCL Institute of Child Health, Imaging and Biophysics, London (United Kingdom); Jones, Rod; Norman, Wendy; Taylor, Andrew M. [Great Ormond Street Hospital for Children NHS Foundation Trust, Cardiorespiratory Division, London (United Kingdom); UCL Institute of Cardiovascular Science, Centre for Cardiovascular Imaging, London (United Kingdom); Sebire, Neil J. [Great Ormond Street Hospital for Children NHS Foundation Trust, Department of Histopathology, London (United Kingdom); UCL Institute of Child Health, Histopathology, London (United Kingdom)

2015-05-01

To evaluate perinatal body organ apparent diffusion coefficient (ADC) values at postmortem magnetic resonance imaging (PMMR) in order to evaluate postmortem changes. Postmortem diffusion-weighted imaging (DWI) of the thorax and abdomen were performed with diffusion gradient values b = 0, 500, and 1000 s/mm{sup 2} on 15 foetal and childhood cases (mean 33.3 ± 7.8 weeks gestation) compared to 44 live infants (mean age 75.5 ± 53.4 days). Mean ADC values were calculated from regions of interest (ROIs) for the lungs, liver, spleen and renal cortex, compared to normative live infantile body ADC values of similar gestational age. Mean ADC values were significantly lower in postmortem cases than in normal controls for liver (0.88 10{sup -3} mm{sup 2}/s ± SD 0.39 vs. 1.13 ± 0.13; p < 0.05) and renal cortex (0.85 ± 0.26 vs. 1.19 ± 0.13; p < 0.05) but not spleen or muscle. Mean lung ADC values were significantly higher than normal controls (1.06 ± 0.18 vs. 0 ± 0; p < 0.001), and there was a significant correlation between postmortem interval and lung ADC (R{sup 2} = 0.55). Lung PMMR ADC values are related to postmortem interval, making them a potential marker of time since death. Further research is needed to understand the organ-specific changes which occur in the postmortem period. (orig.)

Satellite observations make it possible to estimate Poyang Lake’s water budget

International Nuclear Information System (INIS)

Feng Lian; Chen Xiaoling; Hu, Chuanmin; Li Rongfang

2011-01-01

Using moderate resolution imaging spectroradiometer (MODIS) satellite imagery with hydrologic and meteorological data, we developed a box model to estimate the water exchange between Poyang Lake (the largest freshwater lake of China) and the Changjiang (Yangtze) River from 2000 to 2009. Significant intra- and inter-annual variability of the water budget was found, with an annual mean outflow of Poyang Lake of 120.2 ± 31.2 billion m 3 during 2000–2009 and a declining trend of 5.7 billion m 3 yr −1 (p = 0.09). The impoundment of the Three Gorges Dam (TGD) on the Changjiang River in June 2003 led to a rapid lake–river outflow of 760.6 million m 3 day −1 , resulting in a loss of 7864.5 million m 3 of water from the lake in a short period. Shortly thereafter, a statistically significant decrease in the drainage basin’s runoff coefficient was discovered. These findings provide large-scale evidence on how local precipitation and the TGD control the lake’s water budget, where continuous monitoring using the established approach and satellite data may provide critical information to help make water management decisions.

Short-term retention of pictures and words as a function of type of distraction and length of delay interval.

Science.gov (United States)

Pellegrino, J W; Siegel, A W; Dhawan, M

1976-01-01

Picture and word triads were tested in a Brown-Peterson short-term retention task at varying delay intervals (3, 10, or 30 sec) and under acoustic and simultaneous acoustic and visual distraction. Pictures were superior to words at all delay intervals under single acoustic distraction. Dual distraction consistently reduced picture retention while simultaneously facilitating word retention. The results were interpreted in terms of the dual coding hypothesis with modality-specific interference effects in the visual and acoustic processing systems. The differential effects of dual distraction were related to the introduction of visual interference and differential levels of functional acoustic interference across dual and single distraction tasks. The latter was supported by a constant 2/1 ratio in the backward counting rates of the acoustic vs. dual distraction tasks. The results further suggest that retention may not depend on total processing load of the distraction task, per se, but rather that processing load operates within modalities.

Cloud detection, classification and motion estimation using geostationary satellite imagery for cloud cover forecast

International Nuclear Information System (INIS)

Escrig, H.; Batlles, F.J.; Alonso, J.; Baena, F.M.; Bosch, J.L.; Salbidegoitia, I.B.; Burgaleta, J.I.

2013-01-01

Considering that clouds are the greatest causes to solar radiation blocking, short term cloud forecasting can help power plant operation and therefore improve benefits. Cloud detection, classification and motion vector determination are key to forecasting sun obstruction by clouds. Geostationary satellites provide cloud information covering wide areas, allowing cloud forecast to be performed for several hours in advance. Herein, the methodology developed and tested in this study is based on multispectral tests and binary cross correlations followed by coherence and quality control tests over resulting motion vectors. Monthly synthetic surface albedo image and a method to reject erroneous correlation vectors were developed. Cloud classification in terms of opacity and height of cloud top is also performed. A whole-sky camera has been used for validation, showing over 85% of agreement between the camera and the satellite derived cloud cover, whereas error in motion vectors is below 15%. - Highlights: ► A methodology for detection, classification and movement of clouds is presented. ► METEOSAT satellite images are used to obtain a cloud mask. ► The prediction of cloudiness is estimated with 90% in overcast conditions. ► Results for partially covered sky conditions showed a 75% accuracy. ► Motion vectors are estimated from the clouds with a success probability of 86%

A robust object-based shadow detection method for cloud-free high resolution satellite images over urban areas and water bodies

Science.gov (United States)

Tatar, Nurollah; Saadatseresht, Mohammad; Arefi, Hossein; Hadavand, Ahmad

2018-06-01

Unwanted contrast in high resolution satellite images such as shadow areas directly affects the result of further processing in urban remote sensing images. Detecting and finding the precise position of shadows is critical in different remote sensing processing chains such as change detection, image classification and digital elevation model generation from stereo images. The spectral similarity between shadow areas, water bodies, and some dark asphalt roads makes the development of robust shadow detection algorithms challenging. In addition, most of the existing methods work on pixel-level and neglect the contextual information contained in neighboring pixels. In this paper, a new object-based shadow detection framework is introduced. In the proposed method a pixel-level shadow mask is built by extending established thresholding methods with a new C4 index which enables to solve the ambiguity of shadow and water bodies. Then the pixel-based results are further processed in an object-based majority analysis to detect the final shadow objects. Four different high resolution satellite images are used to validate this new approach. The result shows the superiority of the proposed method over some state-of-the-art shadow detection method with an average of 96% in F-measure.

Strengthening IAEA safeguards using high-resolution commercial satellite imagery

International Nuclear Information System (INIS)

Zhang Hui

2001-01-01

Full text: In May 1997, the IAEA Board of Governors adopted the Additional Safeguards Protocol to improve its ability to detect the undeclared production of fissile material. This new strengthened safeguards system has opened the door for the IAEA to use of all types of information, including the potential use of commercial satellite imagery. We have therefore been investigating the feasibility of strengthening IAEA safeguards using commercial satellite imagery. Based on our analysis on a number of one-meter resolution IKONOS satellite images of military nuclear production facilities at nuclear states including Russia, China, India, Pakistan and Israel, we found that the new high-resolution commercial satellite imagery would play a new and valuable role in strengthening IAEA safeguards. Since 1999, images with a resolution of one meter have been available commercially from Space Imaging's IKONOS satellite. One-meter images from other companies are expected to enter the market soon. Although still an order of magnitude less capable than military imaging satellites, the capabilities of these new high-resolution commercial satellites are good enough to detect and identify the major visible characteristics of nuclear production facilities and sites. Unlike the classified spy satellite photos limited to few countries, the commercial satellite imagery is commercially available to anyone who wants to purchase it. Therefore, the new commercial satellite open a new chance that each state, international organizations, and non-governmental groups could use the commercial images to play a more proactive role in monitoring the nuclear activities in related countries and verifying the compliance of non-proliferation agreements. This could help galvanize support for intensified efforts to slow the pace of nuclear proliferation. To produce fissile materials (plutonium and highly enriched uranium) for weapons, a country would operate dedicated plutonium-production reactors and the

Utilization of satellite images to understand the dynamics of Pampas shallow lakes

Directory of Open Access Journals (Sweden)

V. S. Aliaga

2016-06-01

Full Text Available The aim of this study was to analyze satellite images of different spatial resolutions to interpret the morphometric behavior of six shallow lakes of the Pampas, Argentina. These are characterized by having different rainfall regimes. Morphometric response considering each location, site conditions and dry and wet extreme events is analyzed. Standardized Precipitation Index (IEP for determination of wet, dry and normal years was used. This analysis showed that the Pampas shallow lakes do not behave in the same way to the rainfall events. Its origin, socio-economic use and rainfall patterns affect their spatiotemporal variation and morphometric.

Satellite image simulations for model-supervised, dynamic retrieval of crop type and land use intensity

Science.gov (United States)

Bach, H.; Klug, P.; Ruf, T.; Migdall, S.; Schlenz, F.; Hank, T.; Mauser, W.

2015-04-01

To support food security, information products about the actual cropping area per crop type, the current status of agricultural production and estimated yields, as well as the sustainability of the agricultural management are necessary. Based on this information, well-targeted land management decisions can be made. Remote sensing is in a unique position to contribute to this task as it is globally available and provides a plethora of information about current crop status. M4Land is a comprehensive system in which a crop growth model (PROMET) and a reflectance model (SLC) are coupled in order to provide these information products by analyzing multi-temporal satellite images. SLC uses modelled surface state parameters from PROMET, such as leaf area index or phenology of different crops to simulate spatially distributed surface reflectance spectra. This is the basis for generating artificial satellite images considering sensor specific configurations (spectral bands, solar and observation geometries). Ensembles of model runs are used to represent different crop types, fertilization status, soil colour and soil moisture. By multi-temporal comparisons of simulated and real satellite images, the land cover/crop type can be classified in a dynamically, model-supervised way and without in-situ training data. The method is demonstrated in an agricultural test-site in Bavaria. Its transferability is studied by analysing PROMET model results for the rest of Germany. Especially the simulated phenological development can be verified on this scale in order to understand whether PROMET is able to adequately simulate spatial, as well as temporal (intra- and inter-season) crop growth conditions, a prerequisite for the model-supervised approach. This sophisticated new technology allows monitoring of management decisions on the field-level using high resolution optical data (presently RapidEye and Landsat). The M4Land analysis system is designed to integrate multi-mission data and is

Use of geostationary meteorological satellite images in convective rain estimation for flash-flood forecasting

Science.gov (United States)

Wardah, T.; Abu Bakar, S. H.; Bardossy, A.; Maznorizan, M.

2008-07-01

SummaryFrequent flash-floods causing immense devastation in the Klang River Basin of Malaysia necessitate an improvement in the real-time forecasting systems being used. The use of meteorological satellite images in estimating rainfall has become an attractive option for improving the performance of flood forecasting-and-warning systems. In this study, a rainfall estimation algorithm using the infrared (IR) information from the Geostationary Meteorological Satellite-5 (GMS-5) is developed for potential input in a flood forecasting system. Data from the records of GMS-5 IR images have been retrieved for selected convective cells to be trained with the radar rain rate in a back-propagation neural network. The selected data as inputs to the neural network, are five parameters having a significant correlation with the radar rain rate: namely, the cloud-top brightness-temperature of the pixel of interest, the mean and the standard deviation of the temperatures of the surrounding five by five pixels, the rate of temperature change, and the sobel operator that indicates the temperature gradient. In addition, three numerical weather prediction (NWP) products, namely the precipitable water content, relative humidity, and vertical wind, are also included as inputs. The algorithm is applied for the areal rainfall estimation in the upper Klang River Basin and compared with another technique that uses power-law regression between the cloud-top brightness-temperature and radar rain rate. Results from both techniques are validated against previously recorded Thiessen areal-averaged rainfall values with coefficient correlation values of 0.77 and 0.91 for the power-law regression and the artificial neural network (ANN) technique, respectively. An extra lead time of around 2 h is gained when the satellite-based ANN rainfall estimation is coupled with a rainfall-runoff model to forecast a flash-flood event in the upper Klang River Basin.

JPSS Preparations at the Satellite Proving Ground for Marine, Precipitation, and Satellite Analysis

Science.gov (United States)

Folmer, M. J.; Berndt, E.; Clark, J.; Orrison, A.; Kibler, J.; Sienkiewicz, J. M.; Nelson, J. A., Jr.; Goldberg, M.

2016-12-01

The National Oceanic and Atmospheric Administration (NOAA) Satellite Proving Ground (PG) for Marine, Precipitation, and Satellite Analysis (MPS) has been demonstrating and evaluating Suomi National Polar-orbiting Partnership (S-NPP) products along with other polar-orbiting satellite platforms in preparation for the Joint Polar Satellite System - 1 (JPSS-1) launch in March 2017. The first S-NPP imagery was made available to the MPS PG during the evolution of Hurricane Sandy in October 2012 and has since been popular in operations. Since this event the MPS PG Satellite Liaison has been working with forecasters on ways to integrate single-channel and multispectral imagery from the Visible Infrared Imaging Radiometer Suite (VIIRS), the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Advanced Very High Resolution Radiometer (AVHRR)into operations to complement numerical weather prediction and geostationary satellite savvy National Weather Service (NWS) National Centers. Additional unique products have been introduced to operations to address specific forecast challenges, including the Cooperative Institute for Research in the Atmosphere (CIRA) Layered Precipitable Water, the National Environmental Satellite, Data, and Information Service (NESDIS) Snowfall Rate product, NOAA Unique Combined Atmospheric Processing System (NUCAPS) Soundings, ozone products from the Atmospheric Infrared Sounder (AIRS), Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS), and Infrared Atmospheric Sounding Interferometer (IASI). In addition, new satellite domains have been created to provide forecasters at the NWS Ocean Prediction Center and Weather Prediction Center with better quality imagery at high latitudes. This has led to research projects that are addressing forecast challenges such as tropical to extratropical transition and explosive cyclogenesis. This presentation will provide examples of how the MPS PG has been introducing and integrating

An artificial neural network ensemble model for estimating global solar radiation from Meteosat satellite images

International Nuclear Information System (INIS)

Linares-Rodriguez, Alvaro; Ruiz-Arias, José Antonio; Pozo-Vazquez, David; Tovar-Pescador, Joaquin

2013-01-01

An optimized artificial neural network ensemble model is built to estimate daily global solar radiation over large areas. The model uses clear-sky estimates and satellite images as input variables. Unlike most studies using satellite imagery based on visible channels, our model also exploits all information within infrared channels of the Meteosat 9 satellite. A genetic algorithm is used to optimize selection of model inputs, for which twelve are selected – eleven 3-km Meteosat 9 channels and one clear-sky term. The model is validated in Andalusia (Spain) from January 2008 through December 2008. Measured data from 83 stations across the region are used, 65 for training and 18 independent ones for testing the model. At the latter stations, the ensemble model yields an overall root mean square error of 6.74% and correlation coefficient of 99%; the generated estimates are relatively accurate and errors spatially uniform. The model yields reliable results even on cloudy days, improving on current models based on satellite imagery. - Highlights: • Daily solar radiation data are generated using an artificial neural network ensemble. • Eleven Meteosat channels observations and a clear sky term are used as model inputs. • Model exploits all information within infrared Meteosat channels. • Measured data for a year from 83 ground stations are used. • The proposed approach has better performance than existing models on daily basis